jd7h / dreamcraft3d

DreamCraft3D is a text and image to 3D model. Dreamcraft3D uses DeepFloyd IF and Stable Zero123, non-commercial research-only models. Please make sure you read and abide to the relevant licenses before using it. (Updated 1 year, 3 months ago)

Cold

Public
582 runs
L40S
GitHub
Paper
License

Iterate in playground

Run with an API

Playground API Examples README Versions

Prediction

jd7h/dreamcraft3d:cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30

Model

jd7h/dreamcraft3d:cf19b73a

6zgbl6lbf3ftxjuaawjwu7ak4a

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

28m

Created

over 1 year ago by @replicate-internal

Input

image
prompt: A green leafy plant in a striped terracotta pot
num_steps: 800
guidance_scale: 5
use_fast_configs

{
  "image": "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
  "prompt": "A green leafy plant in a striped terracotta pot",
  "num_steps": 800,
  "guidance_scale": 5,
  "use_fast_configs": true
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run jd7h/dreamcraft3d using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jd7h/dreamcraft3d:cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30",
  {
    input: {
      image: "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
      prompt: "A green leafy plant in a striped terracotta pot",
      num_steps: 800,
      guidance_scale: 5,
      use_fast_configs: true
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run jd7h/dreamcraft3d using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jd7h/dreamcraft3d:cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30",
    input={
        "image": "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
        "prompt": "A green leafy plant in a striped terracotta pot",
        "num_steps": 800,
        "guidance_scale": 5,
        "use_fast_configs": True
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Run jd7h/dreamcraft3d using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "jd7h/dreamcraft3d:cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30",
    "input": {
      "image": "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
      "prompt": "A green leafy plant in a striped terracotta pot",
      "num_steps": 800,
      "guidance_scale": 5,
      "use_fast_configs": true
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

mesh.zip

{
  "completed_at": "2024-02-22T14:02:47.589665Z",
  "created_at": "2024-02-22T13:34:42.992767Z",
  "data_removed": false,
  "error": null,
  "id": "6zgbl6lbf3ftxjuaawjwu7ak4a",
  "input": {
    "image": "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
    "prompt": "A green leafy plant in a striped terracotta pot",
    "num_steps": 800,
    "guidance_scale": 5,
    "use_fast_configs": true
  },
  "logs": "Using seed 3731177029\nSeed set to 3731177029\nPreprocessing image...\n[INFO] background removal...\n\u001b[1;31m2024-02-22 13:40:23.104407995 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1831, index: 1, mask: {1, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.104414275 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1830, index: 0, mask: {48, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.104502865 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1832, index: 2, mask: {49, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.104535295 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1833, index: 3, mask: {2, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.104613524 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1834, index: 4, mask: {50, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.107023935 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1841, index: 11, mask: {6, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.107094724 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1842, index: 12, mask: {54, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.107029744 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1908, index: 78, mask: {87, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.107404823 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1844, index: 14, mask: {55, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.119497582 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1843, index: 13, mask: {7, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.107393863 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1914, index: 84, mask: {90, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.123661054 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1911, index: 81, mask: {41, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.123722614 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1909, index: 79, mask: {40, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.123701134 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1910, index: 80, mask: {88, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.127291970 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1916, index: 86, mask: {91, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.127624198 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1915, index: 85, mask: {43, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.130148067 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1912, index: 82, mask: {89, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.131521142 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1835, index: 5, mask: {3, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135786034 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1902, index: 72, mask: {84, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.142269357 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1836, index: 6, mask: {51, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.147488775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1919, index: 89, mask: {45, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.151492068 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1920, index: 90, mask: {93, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.151515108 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1845, index: 15, mask: {8, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.152578874 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1921, index: 91, mask: {46, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.155036124 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1922, index: 92, mask: {94, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.159492425 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1923, index: 93, mask: {47, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.159619344 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1847, index: 17, mask: {9, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.163491428 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1924, index: 94, mask: {95, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.167512541 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1848, index: 18, mask: {57, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.175204479 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1918, index: 88, mask: {92, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.175514908 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1849, index: 19, mask: {10, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.183547044 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1850, index: 20, mask: {58, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203673140 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1865, index: 35, mask: {18, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203714850 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1867, index: 37, mask: {19, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203730010 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1868, index: 38, mask: {67, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208804658 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1880, index: 50, mask: {73, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208933648 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1892, index: 62, mask: {79, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.211571717 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1896, index: 66, mask: {81, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.218757077 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1898, index: 68, mask: {82, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.219530623 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1899, index: 69, mask: {35, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.159503775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1846, index: 16, mask: {56, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208690009 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1872, index: 42, mask: {69, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135794754 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1903, index: 73, mask: {37, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208878768 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1887, index: 57, mask: {29, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208739099 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1876, index: 46, mask: {71, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135799404 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1904, index: 74, mask: {85, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208820138 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1882, index: 52, mask: {74, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208661999 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1871, index: 41, mask: {21, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.211522277 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1894, index: 64, mask: {80, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.211549267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1895, index: 65, mask: {33, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208761849 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1877, index: 47, mask: {24, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135804604 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1905, index: 75, mask: {38, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203705640 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1866, index: 36, mask: {66, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.211499897 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1893, index: 63, mask: {32, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135809804 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1906, index: 76, mask: {86, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208906798 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1889, index: 59, mask: {30, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208719959 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1874, index: 44, mask: {70, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.135814794 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1907, index: 77, mask: {39, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.208775729 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1879, index: 49, mask: {25, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203510801 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1855, index: 25, mask: {13, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203596991 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1917, index: 87, mask: {44, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.191524490 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1854, index: 24, mask: {60, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.203625340 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1862, index: 32, mask: {64, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.255050885 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1856, index: 26, mask: {61, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.226268595 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1853, index: 23, mask: {12, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.226295085 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1883, index: 53, mask: {27, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231529973 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1869, index: 39, mask: {20, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.235482157 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1864, index: 34, mask: {65, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.239481860 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1897, index: 67, mask: {34, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.247489267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1913, index: 83, mask: {42, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231551533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1878, index: 48, mask: {72, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.235490787 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1888, index: 58, mask: {77, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.235501267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1891, index: 61, mask: {31, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231560853 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1884, index: 54, mask: {75, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.235479747 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1885, index: 55, mask: {28, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.226300705 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1873, index: 43, mask: {22, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.226262175 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1863, index: 33, mask: {17, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231541763 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1875, index: 45, mask: {23, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231485533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1886, index: 56, mask: {76, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.231574443 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1890, index: 60, mask: {78, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.226293125 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1870, index: 40, mask: {68, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.255088475 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1881, index: 51, mask: {26, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.255135895 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1837, index: 7, mask: {4, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.287495189 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1901, index: 71, mask: {36, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n\u001b[1;31m2024-02-22 13:40:23.295484056 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1900, index: 70, mask: {83, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.\u001b[m\n[INFO] depth estimation...\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/timm/models/_factory.py:117: UserWarning: Mapping deprecated model name vit_base_resnet50_384 to current vit_base_r50_s16_384.orig_in21k_ft_in1k.\nmodel = create_fn(\n[INFO] normal estimation...\nRunning step 1: NeRF\n{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},\n'data': {'image_path': '/src/outputs/image_rgba.png', 'height': [64, 128], 'width': [64, 128], 'resolution_milestones': [3000], 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': [64, 128], 'width': [64, 128], 'batch_size': [1, 1], 'resolution_milestones': [3000], 'eval_height': 128, 'eval_width': 128, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 200, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},\n'data_type': 'dreamcraft3d-single-image-datamodule',\n'description': '',\n'exp_dir': 'outputs/dreamcraft3d-coarse-nerf',\n'exp_root_dir': 'outputs',\n'n_gpus': 1,\n'name': 'dreamcraft3d-coarse-nerf',\n'resume': None,\n'seed': 0,\n'system': {'stage': 'coarse', 'geometry_type': 'implicit-volume', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'density_bias': 'blob_magic3d', 'density_activation': 'softplus', 'density_blob_scale': 10.0, 'density_blob_std': 0.5, 'pos_encoding_config': {'otype': 'ProgressiveBandHashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'nerf-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'return_normal_perturb': True, 'return_comp_normal': True}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 1.0, 'lambda_3d_normal_smooth': [1000, 5.0, 1.0, 1001], 'lambda_orient': [1000, 1.0, 10.0, 1001], 'lambda_sparsity': [1000, 0.1, 10.0, 1001], 'lambda_opaque': [1000, 0.1, 10.0, 1001], 'lambda_clip': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.01, 'betas': [0.9, 0.99], 'eps': 1e-08}}},\n'system_type': 'dreamcraft3d-system',\n'tag': 'replicate_user',\n'timestamp': '@20240222-134035',\n'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},\n'trial_dir': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035',\n'trial_name': 'replicate_user@20240222-134035',\n'use_timestamp': True}\nLoading Deep Floyd ...\nCouldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74ed3-77c3833b6edb1358569cd2db;c0fe2e5f-e2c0-465b-af4c-23a1c171d42e)\nCannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.\nRepo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..\nWill try to load from local cache.\nLoading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]\nLoading pipeline components...:  33%|███▎      | 1/3 [00:00<00:00,  3.80it/s]\nLoading pipeline components...: 100%|██████████| 3/3 [00:00<00:00,  9.15it/s]\nLoading pipeline components...: 100%|██████████| 3/3 [00:00<00:00,  8.02it/s]\nLoaded Deep Floyd!\nLoading Stable Zero123 ...\nget obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion\nLatentDiffusion: Running in eps-prediction mode\nDiffusionWrapper has 859.53 M params.\nKeeping EMAs of 688.\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\n  0%|                                               | 0.00/890M [00:00<?, ?iB/s]\n  1%|▍                                      | 11.0M/890M [00:00<00:07, 116MiB/s]\n  3%|█▏                                     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12.4MiB/s]\n 16%|██████▏                                | 142M/890M [00:05<00:59, 13.1MiB/s]\n 16%|██████▎                                | 143M/890M [00:05<01:09, 11.3MiB/s]\n 16%|██████▎                                | 144M/890M [00:06<01:10, 11.1MiB/s]\n 16%|██████▍                                | 147M/890M [00:06<00:54, 14.2MiB/s]\n 17%|██████▌                                | 150M/890M [00:06<00:38, 20.1MiB/s]\n 17%|██████▊                                | 154M/890M [00:06<00:29, 25.9MiB/s]\n 18%|██████▉                                | 157M/890M [00:06<00:31, 24.7MiB/s]\n 18%|██████▉                                | 159M/890M [00:06<00:39, 19.4MiB/s]\n 18%|███████                                | 161M/890M [00:06<00:52, 14.4MiB/s]\n 18%|███████▏                               | 163M/890M [00:07<00:58, 13.1MiB/s]\n 19%|███████▏                               | 165M/890M [00:07<00:55, 13.6MiB/s]\n 19%|███████▎                               | 167M/890M [00:07<00:49, 15.2MiB/s]\n 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95%|█████████████████████████████████████▏ | 847M/890M [00:19<00:00, 93.8MiB/s]\n 96%|█████████████████████████████████████▌ | 856M/890M [00:20<00:00, 93.1MiB/s]\n 98%|███████████████████████████████████████ | 868M/890M [00:20<00:00, 102MiB/s]\n 99%|██████████████████████████████████████▍| 878M/890M [00:20<00:00, 94.3MiB/s]\n100%|██████████████████████████████████████▉| 888M/890M [00:20<00:00, 98.6MiB/s]\n100%|███████████████████████████████████████| 890M/890M [00:20<00:00, 45.8MiB/s]\nLoaded Stable Zero123!\nUsing prompt [A green leafy plant in a striped terracotta pot] and negative prompt []\nUsing view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\nloaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth\nUsing 16bit Automatic Mixed Precision (AMP)\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\nYou are using a CUDA device ('NVIDIA A40') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])\n[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])\n[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n| Name       | Type                 | Params\n----------------------------------------------------\n0 | geometry   | ImplicitVolume       | 12.6 M\n1 | material   | NoMaterial           | 0\n2 | background | SolidColorBackground | 0\n3 | renderer   | NeRFVolumeRenderer   | 0\n----------------------------------------------------\n12.6 M    Trainable params\n0         Non-trainable params\n12.6 M    Total params\n50.417    Total estimated model params size (MB)\nValidation results will be saved to outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\nTraining: |          | 0/? [00:00<?, ?it/s]\nTraining: |          | 0/? [00:00<?, ?it/s]\nEpoch 0: |          | 0/? [00:00<?, ?it/s] \nEpoch 0: |          | 1/? [00:00<00:00,  5.54it/s]\nEpoch 0: |          | 1/? [00:00<00:00,  5.51it/s, train/loss=58.90]\nEpoch 0: |          | 2/? [00:00<00:00,  2.90it/s, train/loss=58.90]\nEpoch 0: |          | 2/? [00:00<00:00,  2.90it/s, train/loss=40.50]\nEpoch 0: |          | 3/? [00:00<00:00,  3.98it/s, train/loss=40.50]\nEpoch 0: |          | 3/? [00:00<00:00,  3.97it/s, train/loss=58.60]\nEpoch 0: |          | 4/? [00:01<00:00,  3.74it/s, train/loss=58.60]\nEpoch 0: |          | 4/? [00:01<00:00,  3.74it/s, train/loss=69.90]\nEpoch 0: |          | 5/? [00:01<00:00,  4.38it/s, train/loss=69.90]\nEpoch 0: |          | 5/? [00:01<00:00,  4.38it/s, train/loss=57.90]\nEpoch 0: |          | 6/? [00:01<00:00,  4.11it/s, train/loss=57.90]\nEpoch 0: |          | 6/? [00:01<00:00,  4.11it/s, train/loss=73.10]\nEpoch 0: |          | 7/? [00:01<00:00,  4.59it/s, train/loss=73.10]\nEpoch 0: |          | 7/? [00:01<00:00,  4.59it/s, train/loss=56.60]\nEpoch 0: |          | 8/? [00:01<00:00,  4.34it/s, train/loss=56.60]\nEpoch 0: |          | 8/? [00:01<00:00,  4.34it/s, train/loss=41.30]\nEpoch 0: |          | 9/? [00:01<00:00,  4.72it/s, train/loss=41.30]\nEpoch 0: |          | 9/? [00:01<00:00,  4.71it/s, train/loss=54.50]\nEpoch 0: |          | 10/? [00:02<00:00,  4.49it/s, train/loss=54.50]\nEpoch 0: |          | 10/? [00:02<00:00,  4.49it/s, train/loss=80.40]\nEpoch 0: |          | 11/? [00:02<00:00,  4.80it/s, train/loss=80.40]\nEpoch 0: |          | 11/? [00:02<00:00,  4.80it/s, train/loss=51.40]\nEpoch 0: |          | 12/? [00:02<00:00,  4.61it/s, train/loss=51.40]\nEpoch 0: |          | 12/? [00:02<00:00,  4.60it/s, train/loss=108.0]\nEpoch 0: |          | 13/? [00:02<00:00,  4.87it/s, train/loss=108.0]\nEpoch 0: |          | 13/? [00:02<00:00,  4.87it/s, train/loss=47.50]\nEpoch 0: |          | 14/? [00:02<00:00,  4.69it/s, train/loss=47.50]\nEpoch 0: |          | 14/? [00:02<00:00,  4.69it/s, train/loss=52.10]\nEpoch 0: |          | 15/? [00:03<00:00,  4.92it/s, train/loss=52.10]\nEpoch 0: |          | 15/? [00:03<00:00,  4.92it/s, train/loss=42.80]\nEpoch 0: |          | 16/? [00:03<00:00,  4.74it/s, train/loss=42.80]\nEpoch 0: |          | 16/? [00:03<00:00,  4.74it/s, train/loss=76.90]\nEpoch 0: |          | 17/? [00:03<00:00,  4.94it/s, train/loss=76.90]\nEpoch 0: |          | 17/? [00:03<00:00,  4.94it/s, train/loss=37.60]\nEpoch 0: |          | 18/? [00:03<00:00,  4.79it/s, train/loss=37.60]\nEpoch 0: |          | 18/? [00:03<00:00,  4.79it/s, train/loss=123.0]\nEpoch 0: |          | 19/? [00:03<00:00,  4.98it/s, train/loss=123.0]\nEpoch 0: |          | 19/? [00:03<00:00,  4.97it/s, train/loss=32.60]\nEpoch 0: |          | 20/? [00:04<00:00,  4.84it/s, train/loss=32.60]\nEpoch 0: |          | 20/? [00:04<00:00,  4.84it/s, train/loss=62.40]\nEpoch 0: |          | 21/? [00:04<00:00,  5.01it/s, train/loss=62.40]\nEpoch 0: |          | 21/? [00:04<00:00,  5.01it/s, train/loss=28.20]\nEpoch 0: |          | 22/? [00:04<00:00,  4.88it/s, train/loss=28.20]\nEpoch 0: |          | 22/? [00:04<00:00,  4.88it/s, train/loss=49.50]\nEpoch 0: |          | 23/? [00:04<00:00,  5.03it/s, train/loss=49.50]\nEpoch 0: |          | 23/? [00:04<00:00,  5.03it/s, train/loss=24.40]\nEpoch 0: |          | 24/? [00:04<00:00,  4.92it/s, train/loss=24.40]\nEpoch 0: |          | 24/? 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[00:06<00:00,  5.14it/s, train/loss=16.20]\nEpoch 0: |          | 32/? [00:06<00:00,  5.05it/s, train/loss=16.20]\nEpoch 0: |          | 32/? [00:06<00:00,  5.05it/s, train/loss=41.90]\nEpoch 0: |          | 33/? [00:06<00:00,  5.17it/s, train/loss=41.90]\nEpoch 0: |          | 33/? [00:06<00:00,  5.17it/s, train/loss=15.50]\nEpoch 0: |          | 34/? [00:06<00:00,  5.08it/s, train/loss=15.50]\nEpoch 0: |          | 34/? [00:06<00:00,  5.08it/s, train/loss=47.50]\nEpoch 0: |          | 35/? [00:06<00:00,  5.19it/s, train/loss=47.50]\nEpoch 0: |          | 35/? [00:06<00:00,  5.18it/s, train/loss=14.20]\nEpoch 0: |          | 36/? [00:07<00:00,  5.08it/s, train/loss=14.20]\nEpoch 0: |          | 36/? [00:07<00:00,  5.08it/s, train/loss=41.60]\nEpoch 0: |          | 37/? [00:07<00:00,  5.19it/s, train/loss=41.60]\nEpoch 0: |          | 37/? [00:07<00:00,  5.19it/s, train/loss=12.90]\nEpoch 0: |          | 38/? [00:07<00:00,  5.11it/s, train/loss=12.90]\nEpoch 0: |          | 38/? [00:07<00:00,  5.11it/s, train/loss=50.40]\nEpoch 0: |          | 39/? [00:07<00:00,  5.21it/s, train/loss=50.40]\nEpoch 0: |          | 39/? [00:07<00:00,  5.21it/s, train/loss=11.80]\nEpoch 0: |          | 40/? [00:07<00:00,  5.13it/s, train/loss=11.80]\nEpoch 0: |          | 40/? [00:07<00:00,  5.13it/s, train/loss=82.60]\nEpoch 0: |          | 41/? [00:07<00:00,  5.23it/s, train/loss=82.60]\nEpoch 0: |          | 41/? [00:07<00:00,  5.23it/s, train/loss=10.90]\nEpoch 0: |          | 42/? [00:08<00:00,  5.15it/s, train/loss=10.90]\nEpoch 0: |          | 42/? [00:08<00:00,  5.15it/s, train/loss=63.40]\nEpoch 0: |          | 43/? [00:08<00:00,  5.24it/s, train/loss=63.40]\nEpoch 0: |          | 43/? [00:08<00:00,  5.24it/s, train/loss=10.30]\nEpoch 0: |          | 44/? [00:08<00:00,  5.17it/s, train/loss=10.30]\nEpoch 0: |          | 44/? [00:08<00:00,  5.17it/s, train/loss=70.20]\nEpoch 0: |          | 45/? [00:08<00:00,  5.26it/s, train/loss=70.20]\nEpoch 0: |          | 45/? [00:08<00:00,  5.26it/s, train/loss=10.00]\nEpoch 0: |          | 46/? [00:08<00:00,  5.19it/s, train/loss=10.00]\nEpoch 0: |          | 46/? [00:08<00:00,  5.19it/s, train/loss=60.70]\nEpoch 0: |          | 47/? [00:08<00:00,  5.28it/s, train/loss=60.70]\nEpoch 0: |          | 47/? [00:08<00:00,  5.28it/s, train/loss=9.830]\nEpoch 0: |          | 48/? [00:09<00:00,  5.21it/s, train/loss=9.830]\nEpoch 0: |          | 48/? [00:09<00:00,  5.21it/s, train/loss=61.30]\nEpoch 0: |          | 49/? [00:09<00:00,  5.29it/s, train/loss=61.30]\nEpoch 0: |          | 49/? [00:09<00:00,  5.29it/s, train/loss=9.610]\nEpoch 0: |          | 50/? [00:09<00:00,  5.23it/s, train/loss=9.610]\nEpoch 0: |          | 50/? [00:09<00:00,  5.23it/s, train/loss=61.80]\nEpoch 0: |          | 51/? [00:09<00:00,  5.30it/s, train/loss=61.80]\nEpoch 0: |          | 51/? [00:09<00:00,  5.30it/s, train/loss=9.420]\nEpoch 0: |          | 52/? [00:09<00:00,  5.24it/s, train/loss=9.420]\nEpoch 0: |          | 52/? [00:09<00:00,  5.24it/s, train/loss=38.50]\nEpoch 0: |          | 53/? [00:09<00:00,  5.32it/s, train/loss=38.50]\nEpoch 0: |          | 53/? [00:09<00:00,  5.32it/s, train/loss=9.250]\nEpoch 0: |          | 54/? [00:10<00:00,  5.26it/s, train/loss=9.250]\nEpoch 0: |          | 54/? [00:10<00:00,  5.26it/s, train/loss=43.80]\nEpoch 0: |          | 55/? [00:10<00:00,  5.33it/s, train/loss=43.80]\nEpoch 0: |          | 55/? [00:10<00:00,  5.33it/s, train/loss=9.020]\nEpoch 0: |          | 56/? [00:10<00:00,  5.27it/s, train/loss=9.020]\nEpoch 0: |          | 56/? [00:10<00:00,  5.27it/s, train/loss=88.30]\nEpoch 0: |          | 57/? [00:10<00:00,  5.34it/s, train/loss=88.30]\nEpoch 0: |          | 57/? [00:10<00:00,  5.34it/s, train/loss=8.820]\nEpoch 0: |          | 58/? [00:10<00:00,  5.29it/s, train/loss=8.820]\nEpoch 0: |          | 58/? [00:10<00:00,  5.29it/s, train/loss=65.20]\nEpoch 0: |          | 59/? [00:11<00:00,  5.35it/s, train/loss=65.20]\nEpoch 0: |          | 59/? [00:11<00:00,  5.35it/s, train/loss=8.700]\nEpoch 0: |          | 60/? [00:11<00:00,  5.30it/s, train/loss=8.700]\nEpoch 0: |          | 60/? [00:11<00:00,  5.30it/s, train/loss=48.50]\nEpoch 0: |          | 61/? [00:11<00:00,  5.36it/s, train/loss=48.50]\nEpoch 0: |          | 61/? [00:11<00:00,  5.36it/s, train/loss=8.640]\nEpoch 0: |          | 62/? [00:11<00:00,  5.31it/s, train/loss=8.640]\nEpoch 0: |          | 62/? [00:11<00:00,  5.30it/s, train/loss=63.30]\nEpoch 0: |          | 63/? [00:11<00:00,  5.37it/s, train/loss=63.30]\nEpoch 0: |          | 63/? [00:11<00:00,  5.37it/s, train/loss=8.580]\nEpoch 0: |          | 64/? [00:12<00:00,  5.32it/s, train/loss=8.580]\nEpoch 0: |          | 64/? [00:12<00:00,  5.31it/s, train/loss=73.00]\nEpoch 0: |          | 65/? [00:12<00:00,  5.37it/s, train/loss=73.00]\nEpoch 0: |          | 65/? [00:12<00:00,  5.37it/s, train/loss=8.530]\nEpoch 0: |          | 66/? [00:12<00:00,  5.32it/s, train/loss=8.530]\nEpoch 0: |          | 66/? [00:12<00:00,  5.32it/s, train/loss=114.0]\nEpoch 0: |          | 67/? [00:12<00:00,  5.38it/s, train/loss=114.0]\nEpoch 0: |          | 67/? [00:12<00:00,  5.38it/s, train/loss=8.480]\nEpoch 0: |          | 68/? [00:12<00:00,  5.28it/s, train/loss=8.480]\nEpoch 0: |          | 68/? [00:12<00:00,  5.28it/s, train/loss=47.50]\nEpoch 0: |          | 69/? [00:12<00:00,  5.34it/s, train/loss=47.50]\nEpoch 0: |          | 69/? [00:12<00:00,  5.34it/s, train/loss=8.460]\nEpoch 0: |          | 70/? [00:13<00:00,  5.30it/s, train/loss=8.460]\nEpoch 0: |          | 70/? [00:13<00:00,  5.30it/s, train/loss=71.40]\nEpoch 0: |          | 71/? [00:13<00:00,  5.36it/s, train/loss=71.40]\nEpoch 0: |          | 71/? [00:13<00:00,  5.35it/s, train/loss=8.390]\nEpoch 0: |          | 72/? [00:13<00:00,  5.31it/s, train/loss=8.390]\nEpoch 0: |          | 72/? [00:13<00:00,  5.31it/s, train/loss=54.80]\nEpoch 0: |          | 73/? [00:13<00:00,  5.37it/s, train/loss=54.80]\nEpoch 0: |          | 73/? [00:13<00:00,  5.37it/s, train/loss=8.210]\nEpoch 0: |          | 74/? [00:13<00:00,  5.33it/s, train/loss=8.210]\nEpoch 0: |          | 74/? [00:13<00:00,  5.33it/s, train/loss=46.20]\nEpoch 0: |          | 75/? [00:13<00:00,  5.38it/s, train/loss=46.20]\nEpoch 0: |          | 75/? [00:13<00:00,  5.38it/s, train/loss=8.040]\nEpoch 0: |          | 76/? [00:14<00:00,  5.34it/s, train/loss=8.040]\nEpoch 0: |          | 76/? [00:14<00:00,  5.34it/s, train/loss=79.50]\nEpoch 0: |          | 77/? [00:14<00:00,  5.39it/s, train/loss=79.50]\nEpoch 0: |          | 77/? [00:14<00:00,  5.39it/s, train/loss=7.990]\nEpoch 0: |          | 78/? [00:14<00:00,  5.35it/s, train/loss=7.990]\nEpoch 0: |          | 78/? [00:14<00:00,  5.35it/s, train/loss=41.70]\nEpoch 0: |          | 79/? [00:14<00:00,  5.40it/s, train/loss=41.70]\nEpoch 0: |          | 79/? [00:14<00:00,  5.40it/s, train/loss=8.030]\nEpoch 0: |          | 80/? [00:14<00:00,  5.36it/s, train/loss=8.030]\nEpoch 0: |          | 80/? [00:14<00:00,  5.36it/s, train/loss=64.90]\nEpoch 0: |          | 81/? [00:14<00:00,  5.41it/s, train/loss=64.90]\nEpoch 0: |          | 81/? [00:14<00:00,  5.41it/s, train/loss=8.050]\nEpoch 0: |          | 82/? [00:15<00:00,  5.37it/s, train/loss=8.050]\nEpoch 0: |          | 82/? [00:15<00:00,  5.37it/s, train/loss=62.00]\nEpoch 0: |          | 83/? [00:15<00:00,  5.42it/s, train/loss=62.00]\nEpoch 0: |          | 83/? [00:15<00:00,  5.42it/s, train/loss=8.020]\nEpoch 0: |          | 84/? [00:15<00:00,  5.38it/s, train/loss=8.020]\nEpoch 0: |          | 84/? [00:15<00:00,  5.38it/s, train/loss=45.70]\nEpoch 0: |          | 85/? [00:15<00:00,  5.43it/s, train/loss=45.70]\nEpoch 0: |          | 85/? [00:15<00:00,  5.43it/s, train/loss=7.980]\nEpoch 0: |          | 86/? [00:15<00:00,  5.39it/s, train/loss=7.980]\nEpoch 0: |          | 86/? [00:15<00:00,  5.39it/s, train/loss=61.90]\nEpoch 0: |          | 87/? [00:16<00:00,  5.44it/s, train/loss=61.90]\nEpoch 0: |          | 87/? [00:16<00:00,  5.44it/s, train/loss=7.940]\nEpoch 0: |          | 88/? [00:16<00:00,  5.40it/s, train/loss=7.940]\nEpoch 0: |          | 88/? [00:16<00:00,  5.40it/s, train/loss=72.20]\nEpoch 0: |          | 89/? [00:16<00:00,  5.45it/s, train/loss=72.20]\nEpoch 0: |          | 89/? [00:16<00:00,  5.45it/s, train/loss=7.930]\nEpoch 0: |          | 90/? [00:16<00:00,  5.41it/s, train/loss=7.930]\nEpoch 0: |          | 90/? [00:16<00:00,  5.41it/s, train/loss=70.50]\nEpoch 0: |          | 91/? [00:16<00:00,  5.45it/s, train/loss=70.50]\nEpoch 0: |          | 91/? [00:16<00:00,  5.45it/s, train/loss=7.950]\nEpoch 0: |          | 92/? [00:16<00:00,  5.41it/s, train/loss=7.950]\nEpoch 0: |          | 92/? [00:17<00:00,  5.41it/s, train/loss=55.00]\nEpoch 0: |          | 93/? [00:17<00:00,  5.45it/s, train/loss=55.00]\nEpoch 0: |          | 93/? [00:17<00:00,  5.45it/s, train/loss=7.930]\nEpoch 0: |          | 94/? [00:17<00:00,  5.41it/s, train/loss=7.930]\nEpoch 0: |          | 94/? [00:17<00:00,  5.41it/s, train/loss=47.60]\nEpoch 0: |          | 95/? [00:17<00:00,  5.45it/s, train/loss=47.60]\nEpoch 0: |          | 95/? [00:17<00:00,  5.45it/s, train/loss=7.880]\nEpoch 0: |          | 96/? [00:17<00:00,  5.42it/s, train/loss=7.880]\nEpoch 0: |          | 96/? [00:17<00:00,  5.42it/s, train/loss=53.40]\nEpoch 0: |          | 97/? [00:17<00:00,  5.46it/s, train/loss=53.40]\nEpoch 0: |          | 97/? [00:17<00:00,  5.46it/s, train/loss=7.830]\nEpoch 0: |          | 98/? [00:18<00:00,  5.43it/s, train/loss=7.830]\nEpoch 0: |          | 98/? [00:18<00:00,  5.43it/s, train/loss=52.20]\nEpoch 0: |          | 99/? [00:18<00:00,  5.47it/s, train/loss=52.20]\nEpoch 0: |          | 99/? [00:18<00:00,  5.47it/s, train/loss=7.710]\nEpoch 0: |          | 100/? [00:18<00:00,  5.44it/s, train/loss=7.710]\nEpoch 0: |          | 100/? [00:18<00:00,  5.44it/s, train/loss=46.20]\nEpoch 0: |          | 101/? [00:18<00:00,  5.48it/s, train/loss=46.20]\nEpoch 0: |          | 101/? [00:18<00:00,  5.48it/s, train/loss=7.540]\nEpoch 0: |          | 102/? [00:18<00:00,  5.45it/s, train/loss=7.540]\nEpoch 0: |          | 102/? [00:18<00:00,  5.45it/s, train/loss=63.90]\nEpoch 0: |          | 103/? [00:18<00:00,  5.49it/s, train/loss=63.90]\nEpoch 0: |          | 103/? [00:18<00:00,  5.49it/s, train/loss=7.310]\nEpoch 0: |          | 104/? [00:19<00:00,  5.46it/s, train/loss=7.310]\nEpoch 0: |          | 104/? [00:19<00:00,  5.46it/s, train/loss=70.90]\nEpoch 0: |          | 105/? [00:19<00:00,  5.49it/s, train/loss=70.90]\nEpoch 0: |          | 105/? [00:19<00:00,  5.49it/s, train/loss=7.160]\nEpoch 0: |          | 106/? [00:19<00:00,  5.46it/s, train/loss=7.160]\nEpoch 0: |          | 106/? [00:19<00:00,  5.46it/s, train/loss=59.10]\nEpoch 0: |          | 107/? [00:19<00:00,  5.50it/s, train/loss=59.10]\nEpoch 0: |          | 107/? [00:19<00:00,  5.50it/s, train/loss=7.080]\nEpoch 0: |          | 108/? [00:19<00:00,  5.47it/s, train/loss=7.080]\nEpoch 0: |          | 108/? [00:19<00:00,  5.47it/s, train/loss=57.80]\nEpoch 0: |          | 109/? [00:19<00:00,  5.51it/s, train/loss=57.80]\nEpoch 0: |          | 109/? [00:19<00:00,  5.51it/s, train/loss=7.080]\nEpoch 0: |          | 110/? [00:20<00:00,  5.47it/s, train/loss=7.080]\nEpoch 0: |          | 110/? [00:20<00:00,  5.47it/s, train/loss=41.90]\nEpoch 0: |          | 111/? [00:20<00:00,  5.51it/s, train/loss=41.90]\nEpoch 0: |          | 111/? [00:20<00:00,  5.51it/s, train/loss=7.140]\nEpoch 0: |          | 112/? [00:20<00:00,  5.48it/s, train/loss=7.140]\nEpoch 0: |          | 112/? [00:20<00:00,  5.48it/s, train/loss=56.10]\nEpoch 0: |          | 113/? [00:20<00:00,  5.52it/s, train/loss=56.10]\nEpoch 0: |          | 113/? [00:20<00:00,  5.52it/s, train/loss=7.250]\nEpoch 0: |          | 114/? [00:20<00:00,  5.49it/s, train/loss=7.250]\nEpoch 0: |          | 114/? [00:20<00:00,  5.49it/s, train/loss=48.80]\nEpoch 0: |          | 115/? [00:20<00:00,  5.53it/s, train/loss=48.80]\nEpoch 0: |          | 115/? [00:20<00:00,  5.53it/s, train/loss=7.310]\nEpoch 0: |          | 116/? [00:21<00:00,  5.50it/s, train/loss=7.310]\nEpoch 0: |          | 116/? [00:21<00:00,  5.50it/s, train/loss=51.80]\nEpoch 0: |          | 117/? [00:21<00:00,  5.54it/s, train/loss=51.80]\nEpoch 0: |          | 117/? [00:21<00:00,  5.54it/s, train/loss=7.300]\nEpoch 0: |          | 118/? [00:21<00:00,  5.51it/s, train/loss=7.300]\nEpoch 0: |          | 118/? [00:21<00:00,  5.51it/s, train/loss=47.40]\nEpoch 0: |          | 119/? [00:21<00:00,  5.54it/s, train/loss=47.40]\nEpoch 0: |          | 119/? [00:21<00:00,  5.54it/s, train/loss=7.190]\nEpoch 0: |          | 120/? [00:21<00:00,  5.52it/s, train/loss=7.190]\nEpoch 0: |          | 120/? [00:21<00:00,  5.52it/s, train/loss=49.40]\nEpoch 0: |          | 121/? [00:21<00:00,  5.55it/s, train/loss=49.40]\nEpoch 0: |          | 121/? [00:21<00:00,  5.55it/s, train/loss=7.070]\nEpoch 0: |          | 122/? [00:22<00:00,  5.52it/s, train/loss=7.070]\nEpoch 0: |          | 122/? [00:22<00:00,  5.52it/s, train/loss=48.40]\nEpoch 0: |          | 123/? [00:22<00:00,  5.56it/s, train/loss=48.40]\nEpoch 0: |          | 123/? [00:22<00:00,  5.56it/s, train/loss=6.940]\nEpoch 0: |          | 124/? [00:22<00:00,  5.53it/s, train/loss=6.940]\nEpoch 0: |          | 124/? [00:22<00:00,  5.53it/s, train/loss=98.00]\nEpoch 0: |          | 125/? [00:22<00:00,  5.56it/s, train/loss=98.00]\nEpoch 0: |          | 125/? [00:22<00:00,  5.56it/s, train/loss=6.790]\nEpoch 0: |          | 126/? [00:22<00:00,  5.54it/s, train/loss=6.790]\nEpoch 0: |          | 126/? [00:22<00:00,  5.54it/s, train/loss=34.70]\nEpoch 0: |          | 127/? [00:22<00:00,  5.57it/s, train/loss=34.70]\nEpoch 0: |          | 127/? [00:22<00:00,  5.57it/s, train/loss=6.770]\nEpoch 0: |          | 128/? [00:23<00:00,  5.54it/s, train/loss=6.770]\nEpoch 0: |          | 128/? [00:23<00:00,  5.54it/s, train/loss=24.60]\nEpoch 0: |          | 129/? [00:23<00:00,  5.58it/s, train/loss=24.60]\nEpoch 0: |          | 129/? [00:23<00:00,  5.58it/s, train/loss=6.750]\nEpoch 0: |          | 130/? [00:23<00:00,  5.55it/s, train/loss=6.750]\nEpoch 0: |          | 130/? [00:23<00:00,  5.55it/s, train/loss=42.10]\nEpoch 0: |          | 131/? [00:23<00:00,  5.59it/s, train/loss=42.10]\nEpoch 0: |          | 131/? [00:23<00:00,  5.59it/s, train/loss=6.640]\nEpoch 0: |          | 132/? [00:23<00:00,  5.56it/s, train/loss=6.640]\nEpoch 0: |          | 132/? [00:23<00:00,  5.56it/s, train/loss=64.70]\nEpoch 0: |          | 133/? [00:23<00:00,  5.59it/s, train/loss=64.70]\nEpoch 0: |          | 133/? [00:23<00:00,  5.59it/s, train/loss=6.450]\nEpoch 0: |          | 134/? [00:24<00:00,  5.57it/s, train/loss=6.450]\nEpoch 0: |          | 134/? [00:24<00:00,  5.57it/s, train/loss=47.10]\nEpoch 0: |          | 135/? [00:24<00:00,  5.60it/s, train/loss=47.10]\nEpoch 0: |          | 135/? [00:24<00:00,  5.60it/s, train/loss=6.330]\nEpoch 0: |          | 136/? [00:24<00:00,  5.57it/s, train/loss=6.330]\nEpoch 0: |          | 136/? [00:24<00:00,  5.57it/s, train/loss=42.00]\nEpoch 0: |          | 137/? [00:24<00:00,  5.61it/s, train/loss=42.00]\nEpoch 0: |          | 137/? [00:24<00:00,  5.61it/s, train/loss=6.280]\nEpoch 0: |          | 138/? [00:24<00:00,  5.58it/s, train/loss=6.280]\nEpoch 0: |          | 138/? [00:24<00:00,  5.58it/s, train/loss=46.60]\nEpoch 0: |          | 139/? [00:24<00:00,  5.61it/s, train/loss=46.60]\nEpoch 0: |          | 139/? [00:24<00:00,  5.61it/s, train/loss=6.390]\nEpoch 0: |          | 140/? [00:25<00:00,  5.59it/s, train/loss=6.390]\nEpoch 0: |          | 140/? [00:25<00:00,  5.59it/s, train/loss=33.50]\nEpoch 0: |          | 141/? [00:25<00:00,  5.62it/s, train/loss=33.50]\nEpoch 0: |          | 141/? [00:25<00:00,  5.62it/s, train/loss=6.580]\nEpoch 0: |          | 142/? [00:25<00:00,  5.59it/s, train/loss=6.580]\nEpoch 0: |          | 142/? [00:25<00:00,  5.59it/s, train/loss=30.50]\nEpoch 0: |          | 143/? [00:25<00:00,  5.63it/s, train/loss=30.50]\nEpoch 0: |          | 143/? [00:25<00:00,  5.63it/s, train/loss=6.660]\nEpoch 0: |          | 144/? [00:25<00:00,  5.60it/s, train/loss=6.660]\nEpoch 0: |          | 144/? [00:25<00:00,  5.60it/s, train/loss=38.60]\nEpoch 0: |          | 145/? [00:25<00:00,  5.62it/s, train/loss=38.60]\nEpoch 0: |          | 145/? [00:25<00:00,  5.62it/s, train/loss=6.590]\nEpoch 0: |          | 146/? [00:26<00:00,  5.60it/s, train/loss=6.590]\nEpoch 0: |          | 146/? [00:26<00:00,  5.60it/s, train/loss=34.10]\nEpoch 0: |          | 147/? [00:26<00:00,  5.62it/s, train/loss=34.10]\nEpoch 0: |          | 147/? [00:26<00:00,  5.62it/s, train/loss=6.380]\nEpoch 0: |          | 148/? [00:26<00:00,  5.59it/s, train/loss=6.380]\nEpoch 0: |          | 148/? [00:26<00:00,  5.59it/s, train/loss=64.90]\nEpoch 0: |          | 149/? [00:26<00:00,  5.62it/s, train/loss=64.90]\nEpoch 0: |          | 149/? [00:26<00:00,  5.62it/s, train/loss=6.170]\nEpoch 0: |          | 150/? [00:26<00:00,  5.59it/s, train/loss=6.170]\nEpoch 0: |          | 150/? [00:26<00:00,  5.59it/s, train/loss=38.60]\nEpoch 0: |          | 151/? [00:26<00:00,  5.62it/s, train/loss=38.60]\nEpoch 0: |          | 151/? [00:26<00:00,  5.62it/s, train/loss=6.060]\nEpoch 0: |          | 152/? [00:27<00:00,  5.60it/s, train/loss=6.060]\nEpoch 0: |          | 152/? [00:27<00:00,  5.60it/s, train/loss=45.40]\nEpoch 0: |          | 153/? [00:27<00:00,  5.62it/s, train/loss=45.40]\nEpoch 0: |          | 153/? [00:27<00:00,  5.62it/s, train/loss=5.980]\nEpoch 0: |          | 154/? [00:27<00:00,  5.60it/s, train/loss=5.980]\nEpoch 0: |          | 154/? [00:27<00:00,  5.60it/s, train/loss=33.70]\nEpoch 0: |          | 155/? [00:27<00:00,  5.63it/s, train/loss=33.70]\nEpoch 0: |          | 155/? [00:27<00:00,  5.63it/s, train/loss=5.930]\nEpoch 0: |          | 156/? [00:27<00:00,  5.60it/s, train/loss=5.930]\nEpoch 0: |          | 156/? [00:27<00:00,  5.60it/s, train/loss=35.70]\nEpoch 0: |          | 157/? [00:27<00:00,  5.63it/s, train/loss=35.70]\nEpoch 0: |          | 157/? [00:27<00:00,  5.63it/s, train/loss=5.870]\nEpoch 0: |          | 158/? [00:28<00:00,  5.60it/s, train/loss=5.870]\nEpoch 0: |          | 158/? [00:28<00:00,  5.60it/s, train/loss=26.40]\nEpoch 0: |          | 159/? [00:28<00:00,  5.63it/s, train/loss=26.40]\nEpoch 0: |          | 159/? [00:28<00:00,  5.63it/s, train/loss=5.840]\nEpoch 0: |          | 160/? [00:28<00:00,  5.61it/s, train/loss=5.840]\nEpoch 0: |          | 160/? [00:28<00:00,  5.61it/s, train/loss=49.70]\nEpoch 0: |          | 161/? [00:28<00:00,  5.64it/s, train/loss=49.70]\nEpoch 0: |          | 161/? [00:28<00:00,  5.64it/s, train/loss=5.760]\nEpoch 0: |          | 162/? [00:28<00:00,  5.61it/s, train/loss=5.760]\nEpoch 0: |          | 162/? [00:28<00:00,  5.61it/s, train/loss=51.80]\nEpoch 0: |          | 163/? [00:28<00:00,  5.64it/s, train/loss=51.80]\nEpoch 0: |          | 163/? [00:28<00:00,  5.64it/s, train/loss=5.590]\nEpoch 0: |          | 164/? [00:29<00:00,  5.62it/s, train/loss=5.590]\nEpoch 0: |          | 164/? [00:29<00:00,  5.62it/s, train/loss=25.90]\nEpoch 0: |          | 165/? [00:29<00:00,  5.65it/s, train/loss=25.90]\nEpoch 0: |          | 165/? [00:29<00:00,  5.65it/s, train/loss=5.480]\nEpoch 0: |          | 166/? [00:29<00:00,  5.63it/s, train/loss=5.480]\nEpoch 0: |          | 166/? [00:29<00:00,  5.62it/s, train/loss=44.60]\nEpoch 0: |          | 167/? [00:29<00:00,  5.65it/s, train/loss=44.60]\nEpoch 0: |          | 167/? [00:29<00:00,  5.65it/s, train/loss=5.450]\nEpoch 0: |          | 168/? [00:29<00:00,  5.63it/s, train/loss=5.450]\nEpoch 0: |          | 168/? [00:29<00:00,  5.63it/s, train/loss=28.10]\nEpoch 0: |          | 169/? [00:29<00:00,  5.66it/s, train/loss=28.10]\nEpoch 0: |          | 169/? [00:29<00:00,  5.66it/s, train/loss=5.520]\nEpoch 0: |          | 170/? [00:30<00:00,  5.63it/s, train/loss=5.520]\nEpoch 0: |          | 170/? [00:30<00:00,  5.63it/s, train/loss=40.30]\nEpoch 0: |          | 171/? [00:30<00:00,  5.66it/s, train/loss=40.30]\nEpoch 0: |          | 171/? [00:30<00:00,  5.66it/s, train/loss=5.610]\nEpoch 0: |          | 172/? [00:30<00:00,  5.64it/s, train/loss=5.610]\nEpoch 0: |          | 172/? [00:30<00:00,  5.64it/s, train/loss=31.20]\nEpoch 0: |          | 173/? [00:30<00:00,  5.66it/s, train/loss=31.20]\nEpoch 0: |          | 173/? [00:30<00:00,  5.66it/s, train/loss=5.690]\nEpoch 0: |          | 174/? [00:30<00:00,  5.64it/s, train/loss=5.690]\nEpoch 0: |          | 174/? [00:30<00:00,  5.64it/s, train/loss=22.80]\nEpoch 0: |          | 175/? [00:30<00:00,  5.66it/s, train/loss=22.80]\nEpoch 0: |          | 175/? [00:30<00:00,  5.66it/s, train/loss=5.640]\nEpoch 0: |          | 176/? [00:31<00:00,  5.64it/s, train/loss=5.640]\nEpoch 0: |          | 176/? [00:31<00:00,  5.64it/s, train/loss=38.40]\nEpoch 0: |          | 177/? [00:31<00:00,  5.67it/s, train/loss=38.40]\nEpoch 0: |          | 177/? [00:31<00:00,  5.66it/s, train/loss=5.450]\nEpoch 0: |          | 178/? [00:31<00:00,  5.65it/s, train/loss=5.450]\nEpoch 0: |          | 178/? [00:31<00:00,  5.64it/s, train/loss=25.80]\nEpoch 0: |          | 179/? [00:31<00:00,  5.67it/s, train/loss=25.80]\nEpoch 0: |          | 179/? [00:31<00:00,  5.67it/s, train/loss=5.300]\nEpoch 0: |          | 180/? [00:31<00:00,  5.65it/s, train/loss=5.300]\nEpoch 0: |          | 180/? [00:31<00:00,  5.65it/s, train/loss=46.20]\nEpoch 0: |          | 181/? [00:31<00:00,  5.68it/s, train/loss=46.20]\nEpoch 0: |          | 181/? [00:31<00:00,  5.68it/s, train/loss=5.170]\nEpoch 0: |          | 182/? [00:32<00:00,  5.66it/s, train/loss=5.170]\nEpoch 0: |          | 182/? [00:32<00:00,  5.66it/s, train/loss=28.60]\nEpoch 0: |          | 183/? [00:32<00:00,  5.68it/s, train/loss=28.60]\nEpoch 0: |          | 183/? [00:32<00:00,  5.68it/s, train/loss=5.060]\nEpoch 0: |          | 184/? [00:32<00:00,  5.66it/s, train/loss=5.060]\nEpoch 0: |          | 184/? [00:32<00:00,  5.66it/s, train/loss=25.50]\nEpoch 0: |          | 185/? [00:32<00:00,  5.68it/s, train/loss=25.50]\nEpoch 0: |          | 185/? [00:32<00:00,  5.68it/s, train/loss=5.020]\nEpoch 0: |          | 186/? [00:32<00:00,  5.66it/s, train/loss=5.020]\nEpoch 0: |          | 186/? [00:32<00:00,  5.66it/s, train/loss=20.50]\nEpoch 0: |          | 187/? [00:32<00:00,  5.69it/s, train/loss=20.50]\nEpoch 0: |          | 187/? [00:32<00:00,  5.69it/s, train/loss=4.970]\nEpoch 0: |          | 188/? [00:33<00:00,  5.67it/s, train/loss=4.970]\nEpoch 0: |          | 188/? [00:33<00:00,  5.67it/s, train/loss=21.20]\nEpoch 0: |          | 189/? [00:33<00:00,  5.69it/s, train/loss=21.20]\nEpoch 0: |          | 189/? [00:33<00:00,  5.69it/s, train/loss=4.920]\nEpoch 0: |          | 190/? [00:33<00:00,  5.67it/s, train/loss=4.920]\nEpoch 0: |          | 190/? [00:33<00:00,  5.67it/s, train/loss=31.50]\nEpoch 0: |          | 191/? [00:33<00:00,  5.70it/s, train/loss=31.50]\nEpoch 0: |          | 191/? [00:33<00:00,  5.70it/s, train/loss=4.870]\nEpoch 0: |          | 192/? [00:33<00:00,  5.68it/s, train/loss=4.870]\nEpoch 0: |          | 192/? [00:33<00:00,  5.68it/s, train/loss=65.00]\nEpoch 0: |          | 193/? [00:33<00:00,  5.70it/s, train/loss=65.00]\nEpoch 0: |          | 193/? [00:33<00:00,  5.70it/s, train/loss=4.860]\nEpoch 0: |          | 194/? [00:34<00:00,  5.68it/s, train/loss=4.860]\nEpoch 0: |          | 194/? [00:34<00:00,  5.68it/s, train/loss=19.90]\nEpoch 0: |          | 195/? [00:34<00:00,  5.71it/s, train/loss=19.90]\nEpoch 0: |          | 195/? [00:34<00:00,  5.71it/s, train/loss=4.850]\nEpoch 0: |          | 196/? [00:34<00:00,  5.69it/s, train/loss=4.850]\nEpoch 0: |          | 196/? [00:34<00:00,  5.69it/s, train/loss=25.90]\nEpoch 0: |          | 197/? [00:34<00:00,  5.71it/s, train/loss=25.90]\nEpoch 0: |          | 197/? [00:34<00:00,  5.71it/s, train/loss=4.860]\nEpoch 0: |          | 198/? [00:34<00:00,  5.69it/s, train/loss=4.860]\nEpoch 0: |          | 198/? [00:34<00:00,  5.69it/s, train/loss=41.40]\nEpoch 0: |          | 199/? [00:34<00:00,  5.71it/s, train/loss=41.40]\nEpoch 0: |          | 199/? [00:34<00:00,  5.71it/s, train/loss=4.860]\nEpoch 0: |          | 200/? [00:35<00:00,  5.70it/s, train/loss=4.860]\nEpoch 0: |          | 200/? [00:35<00:00,  5.70it/s, train/loss=22.20]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:00, 53.35it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:00, 54.05it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:00, 54.08it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:00, 54.15it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:00, 54.23it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:00, 54.34it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:00, 54.29it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:00, 54.34it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:00, 54.38it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:00, 54.49it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:00, 54.56it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:00<00:00, 54.56it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:00<00:00, 54.60it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:00<00:00, 54.60it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:00<00:00, 54.60it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:00<00:00, 54.59it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:00<00:00, 53.41it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:00<00:00, 53.67it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:00<00:00, 53.89it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:00<00:00, 54.02it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:00<00:00, 54.18it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:00<00:00, 54.30it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:00<00:00, 54.46it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:00<00:00, 54.60it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:00<00:00, 54.73it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:00<00:00, 54.86it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:00<00:00, 54.97it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:00<00:00, 55.03it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:00<00:00, 54.81it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:00<00:00, 54.89it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:00<00:00, 54.48it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:00<00:00, 54.12it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:00<00:00, 53.75it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:00<00:00, 53.80it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:00<00:00, 53.90it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:00<00:00, 54.01it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:00<00:00, 54.00it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:00<00:00, 53.98it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:00<00:00, 53.96it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 53.95it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 200/? [00:36<00:00,  5.50it/s, train/loss=22.20]\nEpoch 0: |          | 201/? [00:36<00:00,  5.49it/s, train/loss=22.20]\nEpoch 0: |          | 201/? [00:36<00:00,  5.49it/s, train/loss=4.850]\nEpoch 0: |          | 202/? [00:36<00:00,  5.47it/s, train/loss=4.850]\nEpoch 0: |          | 202/? [00:36<00:00,  5.47it/s, train/loss=16.20]\nEpoch 0: |          | 203/? [00:36<00:00,  5.49it/s, train/loss=16.20]\nEpoch 0: |          | 203/? [00:36<00:00,  5.49it/s, train/loss=4.840]\nEpoch 0: |          | 204/? [00:37<00:00,  5.48it/s, train/loss=4.840]\nEpoch 0: |          | 204/? [00:37<00:00,  5.48it/s, train/loss=40.60]\nEpoch 0: |          | 205/? [00:37<00:00,  5.50it/s, train/loss=40.60]\nEpoch 0: |          | 205/? [00:37<00:00,  5.50it/s, train/loss=4.810]\nEpoch 0: |          | 206/? [00:37<00:00,  5.48it/s, train/loss=4.810]\nEpoch 0: |          | 206/? [00:37<00:00,  5.48it/s, train/loss=15.70]\nEpoch 0: |          | 207/? [00:37<00:00,  5.51it/s, train/loss=15.70]\nEpoch 0: |          | 207/? [00:37<00:00,  5.51it/s, train/loss=4.780]\nEpoch 0: |          | 208/? [00:37<00:00,  5.49it/s, train/loss=4.780]\nEpoch 0: |          | 208/? [00:37<00:00,  5.49it/s, train/loss=10.70]\nEpoch 0: |          | 209/? [00:37<00:00,  5.51it/s, train/loss=10.70]\nEpoch 0: |          | 209/? [00:37<00:00,  5.51it/s, train/loss=4.740]\nEpoch 0: |          | 210/? [00:38<00:00,  5.50it/s, train/loss=4.740]\nEpoch 0: |          | 210/? [00:38<00:00,  5.50it/s, train/loss=34.00]\nEpoch 0: |          | 211/? [00:38<00:00,  5.51it/s, train/loss=34.00]\nEpoch 0: |          | 211/? [00:38<00:00,  5.51it/s, train/loss=4.660]\nEpoch 0: |          | 212/? [00:38<00:00,  5.50it/s, train/loss=4.660]\nEpoch 0: |          | 212/? [00:38<00:00,  5.50it/s, train/loss=30.70]\nEpoch 0: |          | 213/? [00:38<00:00,  5.52it/s, train/loss=30.70]\nEpoch 0: |          | 213/? [00:38<00:00,  5.52it/s, train/loss=4.570]\nEpoch 0: |          | 214/? [00:38<00:00,  5.50it/s, train/loss=4.570]\nEpoch 0: |          | 214/? [00:38<00:00,  5.50it/s, train/loss=15.90]\nEpoch 0: |          | 215/? [00:38<00:00,  5.52it/s, train/loss=15.90]\nEpoch 0: |          | 215/? [00:38<00:00,  5.52it/s, train/loss=4.540]\nEpoch 0: |          | 216/? [00:39<00:00,  5.50it/s, train/loss=4.540]\nEpoch 0: |          | 216/? [00:39<00:00,  5.50it/s, train/loss=25.80]\nEpoch 0: |          | 217/? [00:39<00:00,  5.52it/s, train/loss=25.80]\nEpoch 0: |          | 217/? [00:39<00:00,  5.52it/s, train/loss=4.500]\nEpoch 0: |          | 218/? [00:39<00:00,  5.50it/s, train/loss=4.500]\nEpoch 0: |          | 218/? [00:39<00:00,  5.50it/s, train/loss=30.50]\nEpoch 0: |          | 219/? [00:39<00:00,  5.52it/s, train/loss=30.50]\nEpoch 0: |          | 219/? [00:39<00:00,  5.52it/s, train/loss=4.460]\nEpoch 0: |          | 220/? [00:39<00:00,  5.50it/s, train/loss=4.460]\nEpoch 0: |          | 220/? [00:39<00:00,  5.50it/s, train/loss=67.90]\nEpoch 0: |          | 221/? [00:40<00:00,  5.52it/s, train/loss=67.90]\nEpoch 0: |          | 221/? [00:40<00:00,  5.52it/s, train/loss=4.400]\nEpoch 0: |          | 222/? [00:40<00:00,  5.50it/s, train/loss=4.400]\nEpoch 0: |          | 222/? [00:40<00:00,  5.50it/s, train/loss=21.40]\nEpoch 0: |          | 223/? [00:40<00:00,  5.52it/s, train/loss=21.40]\nEpoch 0: |          | 223/? [00:40<00:00,  5.52it/s, train/loss=4.370]\nEpoch 0: |          | 224/? [00:40<00:00,  5.50it/s, train/loss=4.370]\nEpoch 0: |          | 224/? [00:40<00:00,  5.50it/s, train/loss=37.50]\nEpoch 0: |          | 225/? [00:40<00:00,  5.52it/s, train/loss=37.50]\nEpoch 0: |          | 225/? [00:40<00:00,  5.52it/s, train/loss=4.340]\nEpoch 0: |          | 226/? [00:41<00:00,  5.50it/s, train/loss=4.340]\nEpoch 0: |          | 226/? [00:41<00:00,  5.50it/s, train/loss=8.740]\nEpoch 0: |          | 227/? [00:41<00:00,  5.52it/s, train/loss=8.740]\nEpoch 0: |          | 227/? [00:41<00:00,  5.52it/s, train/loss=4.320]\nEpoch 0: |          | 228/? [00:41<00:00,  5.50it/s, train/loss=4.320]\nEpoch 0: |          | 228/? [00:41<00:00,  5.50it/s, train/loss=11.40]\nEpoch 0: |          | 229/? [00:41<00:00,  5.52it/s, train/loss=11.40]\nEpoch 0: |          | 229/? [00:41<00:00,  5.52it/s, train/loss=4.270]\nEpoch 0: |          | 230/? [00:41<00:00,  5.50it/s, train/loss=4.270]\nEpoch 0: |          | 230/? [00:41<00:00,  5.50it/s, train/loss=16.20]\nEpoch 0: |          | 231/? [00:41<00:00,  5.52it/s, train/loss=16.20]\nEpoch 0: |          | 231/? [00:41<00:00,  5.52it/s, train/loss=4.210]\nEpoch 0: |          | 232/? [00:42<00:00,  5.51it/s, train/loss=4.210]\nEpoch 0: |          | 232/? [00:42<00:00,  5.51it/s, train/loss=14.70]\nEpoch 0: |          | 233/? [00:42<00:00,  5.52it/s, train/loss=14.70]\nEpoch 0: |          | 233/? [00:42<00:00,  5.52it/s, train/loss=4.140]\nEpoch 0: |          | 234/? [00:42<00:00,  5.51it/s, train/loss=4.140]\nEpoch 0: |          | 234/? [00:42<00:00,  5.51it/s, train/loss=13.80]\nEpoch 0: |          | 235/? [00:42<00:00,  5.52it/s, train/loss=13.80]\nEpoch 0: |          | 235/? [00:42<00:00,  5.52it/s, train/loss=4.070]\nEpoch 0: |          | 236/? [00:42<00:00,  5.51it/s, train/loss=4.070]\nEpoch 0: |          | 236/? [00:42<00:00,  5.51it/s, train/loss=21.90]\nEpoch 0: |          | 237/? [00:42<00:00,  5.52it/s, train/loss=21.90]\nEpoch 0: |          | 237/? [00:42<00:00,  5.52it/s, train/loss=3.970]\nEpoch 0: |          | 238/? [00:43<00:00,  5.51it/s, train/loss=3.970]\nEpoch 0: |          | 238/? [00:43<00:00,  5.51it/s, train/loss=30.50]\nEpoch 0: |          | 239/? [00:43<00:00,  5.53it/s, train/loss=30.50]\nEpoch 0: |          | 239/? [00:43<00:00,  5.53it/s, train/loss=3.910]\nEpoch 0: |          | 240/? [00:43<00:00,  5.51it/s, train/loss=3.910]\nEpoch 0: |          | 240/? [00:43<00:00,  5.51it/s, train/loss=12.20]\nEpoch 0: |          | 241/? [00:43<00:00,  5.53it/s, train/loss=12.20]\nEpoch 0: |          | 241/? [00:43<00:00,  5.53it/s, train/loss=3.890]\nEpoch 0: |          | 242/? [00:43<00:00,  5.51it/s, train/loss=3.890]\nEpoch 0: |          | 242/? [00:43<00:00,  5.51it/s, train/loss=52.70]\nEpoch 0: |          | 243/? [00:43<00:00,  5.53it/s, train/loss=52.70]\nEpoch 0: |          | 243/? [00:43<00:00,  5.53it/s, train/loss=3.820]\nEpoch 0: |          | 244/? [00:44<00:00,  5.51it/s, train/loss=3.820]\nEpoch 0: |          | 244/? [00:44<00:00,  5.51it/s, train/loss=12.60]\nEpoch 0: |          | 245/? [00:44<00:00,  5.53it/s, train/loss=12.60]\nEpoch 0: |          | 245/? [00:44<00:00,  5.53it/s, train/loss=3.750]\nEpoch 0: |          | 246/? [00:44<00:00,  5.52it/s, train/loss=3.750]\nEpoch 0: |          | 246/? [00:44<00:00,  5.52it/s, train/loss=22.40]\nEpoch 0: |          | 247/? [00:44<00:00,  5.53it/s, train/loss=22.40]\nEpoch 0: |          | 247/? [00:44<00:00,  5.53it/s, train/loss=3.740]\nEpoch 0: |          | 248/? [00:44<00:00,  5.52it/s, train/loss=3.740]\nEpoch 0: |          | 248/? [00:44<00:00,  5.52it/s, train/loss=31.60]\nEpoch 0: |          | 249/? [00:44<00:00,  5.54it/s, train/loss=31.60]\nEpoch 0: |          | 249/? [00:44<00:00,  5.54it/s, train/loss=3.760]\nEpoch 0: |          | 250/? [00:45<00:00,  5.53it/s, train/loss=3.760]\nEpoch 0: |          | 250/? [00:45<00:00,  5.53it/s, train/loss=9.880]\nEpoch 0: |          | 251/? [00:45<00:00,  5.54it/s, train/loss=9.880]\nEpoch 0: |          | 251/? [00:45<00:00,  5.54it/s, train/loss=3.770]\nEpoch 0: |          | 252/? [00:45<00:00,  5.53it/s, train/loss=3.770]\nEpoch 0: |          | 252/? [00:45<00:00,  5.53it/s, train/loss=28.30]\nEpoch 0: |          | 253/? [00:45<00:00,  5.55it/s, train/loss=28.30]\nEpoch 0: |          | 253/? [00:45<00:00,  5.55it/s, train/loss=3.730]\nEpoch 0: |          | 254/? [00:45<00:00,  5.54it/s, train/loss=3.730]\nEpoch 0: |          | 254/? [00:45<00:00,  5.54it/s, train/loss=11.40]\nEpoch 0: |          | 255/? [00:45<00:00,  5.55it/s, train/loss=11.40]\nEpoch 0: |          | 255/? [00:45<00:00,  5.55it/s, train/loss=3.640]\nEpoch 0: |          | 256/? [00:46<00:00,  5.54it/s, train/loss=3.640]\nEpoch 0: |          | 256/? [00:46<00:00,  5.54it/s, train/loss=24.80]\nEpoch 0: |          | 257/? [00:46<00:00,  5.56it/s, train/loss=24.80]\nEpoch 0: |          | 257/? [00:46<00:00,  5.56it/s, train/loss=3.570]\nEpoch 0: |          | 258/? [00:46<00:00,  5.54it/s, train/loss=3.570]\nEpoch 0: |          | 258/? [00:46<00:00,  5.54it/s, train/loss=37.10]\nEpoch 0: |          | 259/? [00:46<00:00,  5.56it/s, train/loss=37.10]\nEpoch 0: |          | 259/? [00:46<00:00,  5.56it/s, train/loss=3.530]\nEpoch 0: |          | 260/? [00:46<00:00,  5.55it/s, train/loss=3.530]\nEpoch 0: |          | 260/? [00:46<00:00,  5.55it/s, train/loss=23.60]\nEpoch 0: |          | 261/? [00:46<00:00,  5.56it/s, train/loss=23.60]\nEpoch 0: |          | 261/? [00:46<00:00,  5.56it/s, train/loss=3.540]\nEpoch 0: |          | 262/? [00:47<00:00,  5.55it/s, train/loss=3.540]\nEpoch 0: |          | 262/? [00:47<00:00,  5.55it/s, train/loss=45.00]\nEpoch 0: |          | 263/? [00:47<00:00,  5.57it/s, train/loss=45.00]\nEpoch 0: |          | 263/? [00:47<00:00,  5.57it/s, train/loss=3.530]\nEpoch 0: |          | 264/? [00:47<00:00,  5.55it/s, train/loss=3.530]\nEpoch 0: |          | 264/? [00:47<00:00,  5.55it/s, train/loss=10.10]\nEpoch 0: |          | 265/? [00:47<00:00,  5.57it/s, train/loss=10.10]\nEpoch 0: |          | 265/? [00:47<00:00,  5.57it/s, train/loss=3.530]\nEpoch 0: |          | 266/? [00:47<00:00,  5.56it/s, train/loss=3.530]\nEpoch 0: |          | 266/? [00:47<00:00,  5.56it/s, train/loss=12.90]\nEpoch 0: |          | 267/? [00:47<00:00,  5.57it/s, train/loss=12.90]\nEpoch 0: |          | 267/? [00:47<00:00,  5.57it/s, train/loss=3.530]\nEpoch 0: |          | 268/? [00:48<00:00,  5.56it/s, train/loss=3.530]\nEpoch 0: |          | 268/? [00:48<00:00,  5.56it/s, train/loss=32.20]\nEpoch 0: |          | 269/? [00:48<00:00,  5.58it/s, train/loss=32.20]\nEpoch 0: |          | 269/? [00:48<00:00,  5.58it/s, train/loss=3.480]\nEpoch 0: |          | 270/? [00:48<00:00,  5.57it/s, train/loss=3.480]\nEpoch 0: |          | 270/? [00:48<00:00,  5.57it/s, train/loss=10.20]\nEpoch 0: |          | 271/? [00:48<00:00,  5.58it/s, train/loss=10.20]\nEpoch 0: |          | 271/? [00:48<00:00,  5.58it/s, train/loss=3.440]\nEpoch 0: |          | 272/? [00:48<00:00,  5.57it/s, train/loss=3.440]\nEpoch 0: |          | 272/? [00:48<00:00,  5.57it/s, train/loss=9.860]\nEpoch 0: |          | 273/? [00:48<00:00,  5.59it/s, train/loss=9.860]\nEpoch 0: |          | 273/? [00:48<00:00,  5.59it/s, train/loss=3.400]\nEpoch 0: |          | 274/? [00:49<00:00,  5.57it/s, train/loss=3.400]\nEpoch 0: |          | 274/? [00:49<00:00,  5.57it/s, train/loss=25.90]\nEpoch 0: |          | 275/? [00:49<00:00,  5.59it/s, train/loss=25.90]\nEpoch 0: |          | 275/? [00:49<00:00,  5.59it/s, train/loss=3.400]\nEpoch 0: |          | 276/? [00:49<00:00,  5.58it/s, train/loss=3.400]\nEpoch 0: |          | 276/? [00:49<00:00,  5.58it/s, train/loss=37.60]\nEpoch 0: |          | 277/? [00:49<00:00,  5.59it/s, train/loss=37.60]\nEpoch 0: |          | 277/? [00:49<00:00,  5.59it/s, train/loss=3.430]\nEpoch 0: |          | 278/? [00:49<00:00,  5.58it/s, train/loss=3.430]\nEpoch 0: |          | 278/? [00:49<00:00,  5.58it/s, train/loss=18.80]\nEpoch 0: |          | 279/? [00:49<00:00,  5.60it/s, train/loss=18.80]\nEpoch 0: |          | 279/? [00:49<00:00,  5.60it/s, train/loss=3.440]\nEpoch 0: |          | 280/? [00:50<00:00,  5.58it/s, train/loss=3.440]\nEpoch 0: |          | 280/? [00:50<00:00,  5.58it/s, train/loss=28.50]\nEpoch 0: |          | 281/? [00:50<00:00,  5.60it/s, train/loss=28.50]\nEpoch 0: |          | 281/? [00:50<00:00,  5.60it/s, train/loss=3.410]\nEpoch 0: |          | 282/? [00:50<00:00,  5.59it/s, train/loss=3.410]\nEpoch 0: |          | 282/? [00:50<00:00,  5.59it/s, train/loss=9.970]\nEpoch 0: |          | 283/? [00:50<00:00,  5.60it/s, train/loss=9.970]\nEpoch 0: |          | 283/? [00:50<00:00,  5.60it/s, train/loss=3.390]\nEpoch 0: |          | 284/? [00:50<00:00,  5.59it/s, train/loss=3.390]\nEpoch 0: |          | 284/? [00:50<00:00,  5.59it/s, train/loss=40.30]\nEpoch 0: |          | 285/? [00:50<00:00,  5.60it/s, train/loss=40.30]\nEpoch 0: |          | 285/? [00:50<00:00,  5.60it/s, train/loss=3.380]\nEpoch 0: |          | 286/? [00:51<00:00,  5.59it/s, train/loss=3.380]\nEpoch 0: |          | 286/? [00:51<00:00,  5.59it/s, train/loss=31.70]\nEpoch 0: |          | 287/? [00:51<00:00,  5.61it/s, train/loss=31.70]\nEpoch 0: |          | 287/? [00:51<00:00,  5.61it/s, train/loss=3.400]\nEpoch 0: |          | 288/? [00:51<00:00,  5.60it/s, train/loss=3.400]\nEpoch 0: |          | 288/? [00:51<00:00,  5.60it/s, train/loss=15.20]\nEpoch 0: |          | 289/? [00:51<00:00,  5.61it/s, train/loss=15.20]\nEpoch 0: |          | 289/? [00:51<00:00,  5.61it/s, train/loss=3.410]\nEpoch 0: |          | 290/? [00:51<00:00,  5.60it/s, train/loss=3.410]\nEpoch 0: |          | 290/? [00:51<00:00,  5.60it/s, train/loss=14.10]\nEpoch 0: |          | 291/? [00:51<00:00,  5.61it/s, train/loss=14.10]\nEpoch 0: |          | 291/? [00:51<00:00,  5.61it/s, train/loss=3.420]\nEpoch 0: |          | 292/? [00:52<00:00,  5.60it/s, train/loss=3.420]\nEpoch 0: |          | 292/? [00:52<00:00,  5.60it/s, train/loss=19.10]\nEpoch 0: |          | 293/? [00:52<00:00,  5.61it/s, train/loss=19.10]\nEpoch 0: |          | 293/? [00:52<00:00,  5.61it/s, train/loss=3.400]\nEpoch 0: |          | 294/? [00:52<00:00,  5.60it/s, train/loss=3.400]\nEpoch 0: |          | 294/? [00:52<00:00,  5.60it/s, train/loss=24.80]\nEpoch 0: |          | 295/? [00:52<00:00,  5.62it/s, train/loss=24.80]\nEpoch 0: |          | 295/? [00:52<00:00,  5.62it/s, train/loss=3.340]\nEpoch 0: |          | 296/? [00:52<00:00,  5.61it/s, train/loss=3.340]\nEpoch 0: |          | 296/? [00:52<00:00,  5.60it/s, train/loss=39.10]\nEpoch 0: |          | 297/? [00:52<00:00,  5.62it/s, train/loss=39.10]\nEpoch 0: |          | 297/? [00:52<00:00,  5.62it/s, train/loss=3.290]\nEpoch 0: |          | 298/? [00:53<00:00,  5.61it/s, train/loss=3.290]\nEpoch 0: |          | 298/? [00:53<00:00,  5.61it/s, train/loss=8.320]\nEpoch 0: |          | 299/? [00:53<00:00,  5.62it/s, train/loss=8.320]\nEpoch 0: |          | 299/? [00:53<00:00,  5.62it/s, train/loss=3.340]\nEpoch 0: |          | 300/? [00:53<00:00,  5.61it/s, train/loss=3.340]\nEpoch 0: |          | 300/? [00:53<00:00,  5.61it/s, train/loss=19.60]\nEpoch 0: |          | 301/? [00:53<00:00,  5.63it/s, train/loss=19.60]\nEpoch 0: |          | 301/? [00:53<00:00,  5.63it/s, train/loss=3.370]\nEpoch 0: |          | 302/? [00:53<00:00,  5.61it/s, train/loss=3.370]\nEpoch 0: |          | 302/? [00:53<00:00,  5.61it/s, train/loss=28.90]\nEpoch 0: |          | 303/? [00:53<00:00,  5.63it/s, train/loss=28.90]\nEpoch 0: |          | 303/? [00:53<00:00,  5.63it/s, train/loss=3.270]\nEpoch 0: |          | 304/? [00:54<00:00,  5.62it/s, train/loss=3.270]\nEpoch 0: |          | 304/? [00:54<00:00,  5.62it/s, train/loss=24.00]\nEpoch 0: |          | 305/? [00:54<00:00,  5.63it/s, train/loss=24.00]\nEpoch 0: |          | 305/? [00:54<00:00,  5.63it/s, train/loss=3.110]\nEpoch 0: |          | 306/? [00:54<00:00,  5.62it/s, train/loss=3.110]\nEpoch 0: |          | 306/? [00:54<00:00,  5.62it/s, train/loss=18.70]\nEpoch 0: |          | 307/? [00:54<00:00,  5.63it/s, train/loss=18.70]\nEpoch 0: |          | 307/? [00:54<00:00,  5.63it/s, train/loss=3.060]\nEpoch 0: |          | 308/? [00:54<00:00,  5.62it/s, train/loss=3.060]\nEpoch 0: |          | 308/? [00:54<00:00,  5.62it/s, train/loss=24.10]\nEpoch 0: |          | 309/? [00:54<00:00,  5.63it/s, train/loss=24.10]\nEpoch 0: |          | 309/? [00:54<00:00,  5.63it/s, train/loss=3.140]\nEpoch 0: |          | 310/? [00:55<00:00,  5.62it/s, train/loss=3.140]\nEpoch 0: |          | 310/? [00:55<00:00,  5.62it/s, train/loss=24.70]\nEpoch 0: |          | 311/? [00:55<00:00,  5.63it/s, train/loss=24.70]\nEpoch 0: |          | 311/? [00:55<00:00,  5.63it/s, train/loss=3.210]\nEpoch 0: |          | 312/? [00:55<00:00,  5.62it/s, train/loss=3.210]\nEpoch 0: |          | 312/? [00:55<00:00,  5.62it/s, train/loss=15.20]\nEpoch 0: |          | 313/? [00:55<00:00,  5.64it/s, train/loss=15.20]\nEpoch 0: |          | 313/? [00:55<00:00,  5.64it/s, train/loss=3.240]\nEpoch 0: |          | 314/? [00:55<00:00,  5.63it/s, train/loss=3.240]\nEpoch 0: |          | 314/? [00:55<00:00,  5.63it/s, train/loss=31.30]\nEpoch 0: |          | 315/? [00:55<00:00,  5.64it/s, train/loss=31.30]\nEpoch 0: |          | 315/? [00:55<00:00,  5.64it/s, train/loss=3.230]\nEpoch 0: |          | 316/? [00:56<00:00,  5.63it/s, train/loss=3.230]\nEpoch 0: |          | 316/? [00:56<00:00,  5.63it/s, train/loss=16.70]\nEpoch 0: |          | 317/? [00:56<00:00,  5.64it/s, train/loss=16.70]\nEpoch 0: |          | 317/? [00:56<00:00,  5.64it/s, train/loss=3.200]\nEpoch 0: |          | 318/? [00:56<00:00,  5.63it/s, train/loss=3.200]\nEpoch 0: |          | 318/? [00:56<00:00,  5.63it/s, train/loss=18.80]\nEpoch 0: |          | 319/? [00:56<00:00,  5.65it/s, train/loss=18.80]\nEpoch 0: |          | 319/? [00:56<00:00,  5.65it/s, train/loss=3.190]\nEpoch 0: |          | 320/? [00:56<00:00,  5.64it/s, train/loss=3.190]\nEpoch 0: |          | 320/? [00:56<00:00,  5.64it/s, train/loss=37.10]\nEpoch 0: |          | 321/? [00:56<00:00,  5.65it/s, train/loss=37.10]\nEpoch 0: |          | 321/? [00:56<00:00,  5.65it/s, train/loss=3.160]\nEpoch 0: |          | 322/? [00:57<00:00,  5.64it/s, train/loss=3.160]\nEpoch 0: |          | 322/? [00:57<00:00,  5.64it/s, train/loss=29.70]\nEpoch 0: |          | 323/? [00:57<00:00,  5.65it/s, train/loss=29.70]\nEpoch 0: |          | 323/? [00:57<00:00,  5.65it/s, train/loss=3.120]\nEpoch 0: |          | 324/? [00:57<00:00,  5.64it/s, train/loss=3.120]\nEpoch 0: |          | 324/? [00:57<00:00,  5.64it/s, train/loss=22.20]\nEpoch 0: |          | 325/? [00:57<00:00,  5.66it/s, train/loss=22.20]\nEpoch 0: |          | 325/? [00:57<00:00,  5.66it/s, train/loss=3.130]\nEpoch 0: |          | 326/? [00:57<00:00,  5.65it/s, train/loss=3.130]\nEpoch 0: |          | 326/? [00:57<00:00,  5.65it/s, train/loss=23.50]\nEpoch 0: |          | 327/? [00:57<00:00,  5.66it/s, train/loss=23.50]\nEpoch 0: |          | 327/? [00:57<00:00,  5.66it/s, train/loss=3.110]\nEpoch 0: |          | 328/? [00:58<00:00,  5.65it/s, train/loss=3.110]\nEpoch 0: |          | 328/? [00:58<00:00,  5.65it/s, train/loss=37.80]\nEpoch 0: |          | 329/? [00:58<00:00,  5.66it/s, train/loss=37.80]\nEpoch 0: |          | 329/? [00:58<00:00,  5.66it/s, train/loss=3.010]\nEpoch 0: |          | 330/? [00:58<00:00,  5.65it/s, train/loss=3.010]\nEpoch 0: |          | 330/? [00:58<00:00,  5.65it/s, train/loss=30.40]\nEpoch 0: |          | 331/? [00:58<00:00,  5.66it/s, train/loss=30.40]\nEpoch 0: |          | 331/? [00:58<00:00,  5.66it/s, train/loss=2.920]\nEpoch 0: |          | 332/? [00:58<00:00,  5.65it/s, train/loss=2.920]\nEpoch 0: |          | 332/? [00:58<00:00,  5.65it/s, train/loss=20.70]\nEpoch 0: |          | 333/? [00:58<00:00,  5.67it/s, train/loss=20.70]\nEpoch 0: |          | 333/? [00:58<00:00,  5.67it/s, train/loss=2.860]\nEpoch 0: |          | 334/? [00:59<00:00,  5.66it/s, train/loss=2.860]\nEpoch 0: |          | 334/? [00:59<00:00,  5.66it/s, train/loss=10.10]\nEpoch 0: |          | 335/? [00:59<00:00,  5.67it/s, train/loss=10.10]\nEpoch 0: |          | 335/? [00:59<00:00,  5.67it/s, train/loss=2.800]\nEpoch 0: |          | 336/? [00:59<00:00,  5.66it/s, train/loss=2.800]\nEpoch 0: |          | 336/? [00:59<00:00,  5.66it/s, train/loss=38.50]\nEpoch 0: |          | 337/? [00:59<00:00,  5.67it/s, train/loss=38.50]\nEpoch 0: |          | 337/? [00:59<00:00,  5.67it/s, train/loss=2.760]\nEpoch 0: |          | 338/? [00:59<00:00,  5.66it/s, train/loss=2.760]\nEpoch 0: |          | 338/? [00:59<00:00,  5.66it/s, train/loss=17.30]\nEpoch 0: |          | 339/? [00:59<00:00,  5.68it/s, train/loss=17.30]\nEpoch 0: |          | 339/? [00:59<00:00,  5.68it/s, train/loss=2.760]\nEpoch 0: |          | 340/? [01:00<00:00,  5.66it/s, train/loss=2.760]\nEpoch 0: |          | 340/? [01:00<00:00,  5.66it/s, train/loss=30.30]\nEpoch 0: |          | 341/? [01:00<00:00,  5.68it/s, train/loss=30.30]\nEpoch 0: |          | 341/? [01:00<00:00,  5.68it/s, train/loss=2.770]\nEpoch 0: |          | 342/? [01:00<00:00,  5.67it/s, train/loss=2.770]\nEpoch 0: |          | 342/? [01:00<00:00,  5.67it/s, train/loss=40.10]\nEpoch 0: |          | 343/? [01:00<00:00,  5.68it/s, train/loss=40.10]\nEpoch 0: |          | 343/? [01:00<00:00,  5.68it/s, train/loss=2.790]\nEpoch 0: |          | 344/? [01:00<00:00,  5.67it/s, train/loss=2.790]\nEpoch 0: |          | 344/? [01:00<00:00,  5.67it/s, train/loss=7.000]\nEpoch 0: |          | 345/? [01:00<00:00,  5.68it/s, train/loss=7.000]\nEpoch 0: |          | 345/? [01:00<00:00,  5.68it/s, train/loss=2.850]\nEpoch 0: |          | 346/? [01:00<00:00,  5.67it/s, train/loss=2.850]\nEpoch 0: |          | 346/? [01:00<00:00,  5.67it/s, train/loss=23.60]\nEpoch 0: |          | 347/? [01:01<00:00,  5.69it/s, train/loss=23.60]\nEpoch 0: |          | 347/? [01:01<00:00,  5.69it/s, train/loss=2.880]\nEpoch 0: |          | 348/? [01:01<00:00,  5.68it/s, train/loss=2.880]\nEpoch 0: |          | 348/? [01:01<00:00,  5.68it/s, train/loss=57.60]\nEpoch 0: |          | 349/? [01:01<00:00,  5.69it/s, train/loss=57.60]\nEpoch 0: |          | 349/? [01:01<00:00,  5.69it/s, train/loss=2.860]\nEpoch 0: |          | 350/? [01:01<00:00,  5.68it/s, train/loss=2.860]\nEpoch 0: |          | 350/? [01:01<00:00,  5.68it/s, train/loss=14.50]\nEpoch 0: |          | 351/? [01:01<00:00,  5.69it/s, train/loss=14.50]\nEpoch 0: |          | 351/? [01:01<00:00,  5.69it/s, train/loss=2.870]\nEpoch 0: |          | 352/? [01:01<00:00,  5.68it/s, train/loss=2.870]\nEpoch 0: |          | 352/? [01:01<00:00,  5.68it/s, train/loss=11.60]\nEpoch 0: |          | 353/? [01:01<00:00,  5.69it/s, train/loss=11.60]\nEpoch 0: |          | 353/? [01:01<00:00,  5.69it/s, train/loss=2.890]\nEpoch 0: |          | 354/? [01:02<00:00,  5.68it/s, train/loss=2.890]\nEpoch 0: |          | 354/? [01:02<00:00,  5.68it/s, train/loss=49.20]\nEpoch 0: |          | 355/? [01:02<00:00,  5.70it/s, train/loss=49.20]\nEpoch 0: |          | 355/? [01:02<00:00,  5.70it/s, train/loss=2.900]\nEpoch 0: |          | 356/? [01:02<00:00,  5.69it/s, train/loss=2.900]\nEpoch 0: |          | 356/? [01:02<00:00,  5.69it/s, train/loss=7.090]\nEpoch 0: |          | 357/? [01:02<00:00,  5.70it/s, train/loss=7.090]\nEpoch 0: |          | 357/? [01:02<00:00,  5.70it/s, train/loss=2.930]\nEpoch 0: |          | 358/? [01:02<00:00,  5.69it/s, train/loss=2.930]\nEpoch 0: |          | 358/? [01:02<00:00,  5.69it/s, train/loss=68.30]\nEpoch 0: |          | 359/? [01:02<00:00,  5.70it/s, train/loss=68.30]\nEpoch 0: |          | 359/? [01:02<00:00,  5.70it/s, train/loss=3.030]\nEpoch 0: |          | 360/? [01:03<00:00,  5.69it/s, train/loss=3.030]\nEpoch 0: |          | 360/? [01:03<00:00,  5.69it/s, train/loss=14.50]\nEpoch 0: |          | 361/? [01:03<00:00,  5.70it/s, train/loss=14.50]\nEpoch 0: |          | 361/? [01:03<00:00,  5.70it/s, train/loss=3.160]\nEpoch 0: |          | 362/? [01:03<00:00,  5.69it/s, train/loss=3.160]\nEpoch 0: |          | 362/? [01:03<00:00,  5.69it/s, train/loss=9.390]\nEpoch 0: |          | 363/? [01:03<00:00,  5.71it/s, train/loss=9.390]\nEpoch 0: |          | 363/? [01:03<00:00,  5.71it/s, train/loss=3.190]\nEpoch 0: |          | 364/? [01:03<00:00,  5.70it/s, train/loss=3.190]\nEpoch 0: |          | 364/? [01:03<00:00,  5.70it/s, train/loss=34.60]\nEpoch 0: |          | 365/? [01:03<00:00,  5.71it/s, train/loss=34.60]\nEpoch 0: |          | 365/? [01:03<00:00,  5.71it/s, train/loss=3.110]\nEpoch 0: |          | 366/? [01:04<00:00,  5.70it/s, train/loss=3.110]\nEpoch 0: |          | 366/? [01:04<00:00,  5.70it/s, train/loss=13.80]\nEpoch 0: |          | 367/? [01:04<00:00,  5.71it/s, train/loss=13.80]\nEpoch 0: |          | 367/? [01:04<00:00,  5.71it/s, train/loss=2.990]\nEpoch 0: |          | 368/? [01:04<00:00,  5.70it/s, train/loss=2.990]\nEpoch 0: |          | 368/? [01:04<00:00,  5.70it/s, train/loss=24.20]\nEpoch 0: |          | 369/? [01:04<00:00,  5.71it/s, train/loss=24.20]\nEpoch 0: |          | 369/? [01:04<00:00,  5.71it/s, train/loss=2.900]\nEpoch 0: |          | 370/? [01:04<00:00,  5.70it/s, train/loss=2.900]\nEpoch 0: |          | 370/? [01:04<00:00,  5.70it/s, train/loss=19.60]\nEpoch 0: |          | 371/? [01:04<00:00,  5.72it/s, train/loss=19.60]\nEpoch 0: |          | 371/? [01:04<00:00,  5.72it/s, train/loss=2.840]\nEpoch 0: |          | 372/? [01:05<00:00,  5.71it/s, train/loss=2.840]\nEpoch 0: |          | 372/? [01:05<00:00,  5.71it/s, train/loss=24.40]\nEpoch 0: |          | 373/? [01:05<00:00,  5.72it/s, train/loss=24.40]\nEpoch 0: |          | 373/? [01:05<00:00,  5.72it/s, train/loss=2.810]\nEpoch 0: |          | 374/? [01:05<00:00,  5.71it/s, train/loss=2.810]\nEpoch 0: |          | 374/? [01:05<00:00,  5.71it/s, train/loss=10.40]\nEpoch 0: |          | 375/? [01:05<00:00,  5.72it/s, train/loss=10.40]\nEpoch 0: |          | 375/? [01:05<00:00,  5.72it/s, train/loss=2.780]\nEpoch 0: |          | 376/? [01:05<00:00,  5.71it/s, train/loss=2.780]\nEpoch 0: |          | 376/? [01:05<00:00,  5.71it/s, train/loss=34.00]\nEpoch 0: |          | 377/? [01:05<00:00,  5.72it/s, train/loss=34.00]\nEpoch 0: |          | 377/? [01:05<00:00,  5.72it/s, train/loss=2.710]\nEpoch 0: |          | 378/? [01:06<00:00,  5.71it/s, train/loss=2.710]\nEpoch 0: |          | 378/? [01:06<00:00,  5.71it/s, train/loss=24.10]\nEpoch 0: |          | 379/? [01:06<00:00,  5.72it/s, train/loss=24.10]\nEpoch 0: |          | 379/? [01:06<00:00,  5.72it/s, train/loss=2.650]\nEpoch 0: |          | 380/? [01:06<00:00,  5.71it/s, train/loss=2.650]\nEpoch 0: |          | 380/? [01:06<00:00,  5.71it/s, train/loss=17.60]\nEpoch 0: |          | 381/? [01:06<00:00,  5.73it/s, train/loss=17.60]\nEpoch 0: |          | 381/? [01:06<00:00,  5.73it/s, train/loss=2.650]\nEpoch 0: |          | 382/? [01:06<00:00,  5.72it/s, train/loss=2.650]\nEpoch 0: |          | 382/? [01:06<00:00,  5.72it/s, train/loss=31.10]\nEpoch 0: |          | 383/? [01:06<00:00,  5.73it/s, train/loss=31.10]\nEpoch 0: |          | 383/? [01:06<00:00,  5.73it/s, train/loss=2.690]\nEpoch 0: |          | 384/? [01:07<00:00,  5.72it/s, train/loss=2.690]\nEpoch 0: |          | 384/? [01:07<00:00,  5.72it/s, train/loss=27.60]\nEpoch 0: |          | 385/? [01:07<00:00,  5.73it/s, train/loss=27.60]\nEpoch 0: |          | 385/? [01:07<00:00,  5.73it/s, train/loss=2.720]\nEpoch 0: |          | 386/? [01:07<00:00,  5.72it/s, train/loss=2.720]\nEpoch 0: |          | 386/? [01:07<00:00,  5.72it/s, train/loss=19.10]\nEpoch 0: |          | 387/? [01:07<00:00,  5.73it/s, train/loss=19.10]\nEpoch 0: |          | 387/? [01:07<00:00,  5.73it/s, train/loss=2.690]\nEpoch 0: |          | 388/? [01:07<00:00,  5.72it/s, train/loss=2.690]\nEpoch 0: |          | 388/? [01:07<00:00,  5.72it/s, train/loss=9.580]\nEpoch 0: |          | 389/? [01:07<00:00,  5.74it/s, train/loss=9.580]\nEpoch 0: |          | 389/? [01:07<00:00,  5.74it/s, train/loss=2.640]\nEpoch 0: |          | 390/? [01:08<00:00,  5.73it/s, train/loss=2.640]\nEpoch 0: |          | 390/? [01:08<00:00,  5.73it/s, train/loss=16.10]\nEpoch 0: |          | 391/? [01:08<00:00,  5.74it/s, train/loss=16.10]\nEpoch 0: |          | 391/? [01:08<00:00,  5.74it/s, train/loss=2.580]\nEpoch 0: |          | 392/? [01:08<00:00,  5.73it/s, train/loss=2.580]\nEpoch 0: |          | 392/? [01:08<00:00,  5.73it/s, train/loss=37.50]\nEpoch 0: |          | 393/? [01:08<00:00,  5.74it/s, train/loss=37.50]\nEpoch 0: |          | 393/? [01:08<00:00,  5.74it/s, train/loss=2.530]\nEpoch 0: |          | 394/? [01:08<00:00,  5.73it/s, train/loss=2.530]\nEpoch 0: |          | 394/? [01:08<00:00,  5.73it/s, train/loss=15.50]\nEpoch 0: |          | 395/? [01:08<00:00,  5.74it/s, train/loss=15.50]\nEpoch 0: |          | 395/? [01:08<00:00,  5.74it/s, train/loss=2.500]\nEpoch 0: |          | 396/? [01:09<00:00,  5.73it/s, train/loss=2.500]\nEpoch 0: |          | 396/? [01:09<00:00,  5.73it/s, train/loss=19.40]\nEpoch 0: |          | 397/? [01:09<00:00,  5.74it/s, train/loss=19.40]\nEpoch 0: |          | 397/? [01:09<00:00,  5.74it/s, train/loss=2.490]\nEpoch 0: |          | 398/? [01:09<00:00,  5.74it/s, train/loss=2.490]\nEpoch 0: |          | 398/? [01:09<00:00,  5.73it/s, train/loss=19.80]\nEpoch 0: |          | 399/? [01:09<00:00,  5.75it/s, train/loss=19.80]\nEpoch 0: |          | 399/? [01:09<00:00,  5.75it/s, train/loss=2.490]\nEpoch 0: |          | 400/? [01:09<00:00,  5.74it/s, train/loss=2.490]\nEpoch 0: |          | 400/? [01:09<00:00,  5.74it/s, train/loss=34.10]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:00, 71.57it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:00, 70.04it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:00, 70.02it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:00, 70.00it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:00, 69.62it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:00, 69.44it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:00, 69.47it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:00, 69.54it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:00, 69.70it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:00, 69.82it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:00, 69.97it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:00<00:00, 69.85it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:00<00:00, 68.85it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:00<00:00, 68.93it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:00<00:00, 68.83it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:00<00:00, 68.29it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:00<00:00, 67.23it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:00<00:00, 67.04it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:00<00:00, 66.67it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:00<00:00, 66.50it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:00<00:00, 66.28it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:00<00:00, 63.16it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:00<00:00, 63.25it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:00<00:00, 63.45it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:00<00:00, 63.66it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:00<00:00, 63.87it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:00<00:00, 64.11it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:00<00:00, 64.35it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:00<00:00, 64.58it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:00<00:00, 64.80it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:00<00:00, 64.93it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:00<00:00, 64.18it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:00<00:00, 64.16it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:00<00:00, 63.86it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:00<00:00, 63.84it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:00<00:00, 63.81it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:00<00:00, 63.78it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:00<00:00, 62.42it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:00<00:00, 62.44it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 62.45it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 400/? [01:10<00:00,  5.65it/s, train/loss=34.10]\nEpoch 0: |          | 401/? [01:11<00:00,  5.57it/s, train/loss=34.10]\nEpoch 0: |          | 401/? [01:11<00:00,  5.57it/s, train/loss=2.480]\nEpoch 0: |          | 402/? [01:12<00:00,  5.57it/s, train/loss=2.480]\nEpoch 0: |          | 402/? [01:12<00:00,  5.57it/s, train/loss=15.00]\nEpoch 0: |          | 403/? [01:12<00:00,  5.58it/s, train/loss=15.00]\nEpoch 0: |          | 403/? [01:12<00:00,  5.58it/s, train/loss=2.480]\nEpoch 0: |          | 404/? [01:12<00:00,  5.57it/s, train/loss=2.480]\nEpoch 0: |          | 404/? [01:12<00:00,  5.57it/s, train/loss=23.00]\nEpoch 0: |          | 405/? [01:12<00:00,  5.58it/s, train/loss=23.00]\nEpoch 0: |          | 405/? [01:12<00:00,  5.58it/s, train/loss=2.470]\nEpoch 0: |          | 406/? [01:12<00:00,  5.57it/s, train/loss=2.470]\nEpoch 0: |          | 406/? [01:12<00:00,  5.57it/s, train/loss=9.820]\nEpoch 0: |          | 407/? [01:12<00:00,  5.58it/s, train/loss=9.820]\nEpoch 0: |          | 407/? [01:12<00:00,  5.58it/s, train/loss=2.460]\nEpoch 0: |          | 408/? [01:13<00:00,  5.57it/s, train/loss=2.460]\nEpoch 0: |          | 408/? [01:13<00:00,  5.57it/s, train/loss=18.50]\nEpoch 0: |          | 409/? [01:13<00:00,  5.58it/s, train/loss=18.50]\nEpoch 0: |          | 409/? [01:13<00:00,  5.58it/s, train/loss=2.450]\nEpoch 0: |          | 410/? [01:13<00:00,  5.58it/s, train/loss=2.450]\nEpoch 0: |          | 410/? [01:13<00:00,  5.58it/s, train/loss=21.70]\nEpoch 0: |          | 411/? [01:13<00:00,  5.59it/s, train/loss=21.70]\nEpoch 0: |          | 411/? [01:13<00:00,  5.59it/s, train/loss=2.470]\nEpoch 0: |          | 412/? [01:13<00:00,  5.58it/s, train/loss=2.470]\nEpoch 0: |          | 412/? [01:13<00:00,  5.58it/s, train/loss=25.70]\nEpoch 0: |          | 413/? [01:13<00:00,  5.59it/s, train/loss=25.70]\nEpoch 0: |          | 413/? [01:13<00:00,  5.59it/s, train/loss=2.480]\nEpoch 0: |          | 414/? [01:14<00:00,  5.58it/s, train/loss=2.480]\nEpoch 0: |          | 414/? [01:14<00:00,  5.58it/s, train/loss=49.00]\nEpoch 0: |          | 415/? [01:14<00:00,  5.59it/s, train/loss=49.00]\nEpoch 0: |          | 415/? [01:14<00:00,  5.59it/s, train/loss=2.460]\nEpoch 0: |          | 416/? [01:14<00:00,  5.58it/s, train/loss=2.460]\nEpoch 0: |          | 416/? [01:14<00:00,  5.58it/s, train/loss=14.30]\nEpoch 0: |          | 417/? [01:14<00:00,  5.59it/s, train/loss=14.30]\nEpoch 0: |          | 417/? [01:14<00:00,  5.59it/s, train/loss=2.490]\nEpoch 0: |          | 418/? [01:14<00:00,  5.58it/s, train/loss=2.490]\nEpoch 0: |          | 418/? [01:14<00:00,  5.58it/s, train/loss=12.00]\nEpoch 0: |          | 419/? [01:14<00:00,  5.60it/s, train/loss=12.00]\nEpoch 0: |          | 419/? [01:14<00:00,  5.60it/s, train/loss=2.520]\nEpoch 0: |          | 420/? [01:15<00:00,  5.59it/s, train/loss=2.520]\nEpoch 0: |          | 420/? [01:15<00:00,  5.59it/s, train/loss=10.10]\nEpoch 0: |          | 421/? [01:15<00:00,  5.60it/s, train/loss=10.10]\nEpoch 0: |          | 421/? [01:15<00:00,  5.60it/s, train/loss=2.520]\nEpoch 0: |          | 422/? [01:15<00:00,  5.59it/s, train/loss=2.520]\nEpoch 0: |          | 422/? [01:15<00:00,  5.59it/s, train/loss=27.00]\nEpoch 0: |          | 423/? [01:15<00:00,  5.60it/s, train/loss=27.00]\nEpoch 0: |          | 423/? [01:15<00:00,  5.60it/s, train/loss=2.470]\nEpoch 0: |          | 424/? [01:15<00:00,  5.59it/s, train/loss=2.470]\nEpoch 0: |          | 424/? [01:15<00:00,  5.59it/s, train/loss=22.70]\nEpoch 0: |          | 425/? [01:15<00:00,  5.60it/s, train/loss=22.70]\nEpoch 0: |          | 425/? [01:15<00:00,  5.60it/s, train/loss=2.420]\nEpoch 0: |          | 426/? [01:16<00:00,  5.60it/s, train/loss=2.420]\nEpoch 0: |          | 426/? [01:16<00:00,  5.60it/s, train/loss=9.020]\nEpoch 0: |          | 427/? [01:16<00:00,  5.61it/s, train/loss=9.020]\nEpoch 0: |          | 427/? [01:16<00:00,  5.61it/s, train/loss=2.360]\nEpoch 0: |          | 428/? [01:16<00:00,  5.60it/s, train/loss=2.360]\nEpoch 0: |          | 428/? [01:16<00:00,  5.60it/s, train/loss=41.80]\nEpoch 0: |          | 429/? [01:16<00:00,  5.61it/s, train/loss=41.80]\nEpoch 0: |          | 429/? [01:16<00:00,  5.61it/s, train/loss=2.330]\nEpoch 0: |          | 430/? [01:16<00:00,  5.60it/s, train/loss=2.330]\nEpoch 0: |          | 430/? [01:16<00:00,  5.60it/s, train/loss=36.30]\nEpoch 0: |          | 431/? [01:16<00:00,  5.61it/s, train/loss=36.30]\nEpoch 0: |          | 431/? [01:16<00:00,  5.61it/s, train/loss=2.320]\nEpoch 0: |          | 432/? [01:17<00:00,  5.60it/s, train/loss=2.320]\nEpoch 0: |          | 432/? [01:17<00:00,  5.60it/s, train/loss=16.50]\nEpoch 0: |          | 433/? [01:17<00:00,  5.61it/s, train/loss=16.50]\nEpoch 0: |          | 433/? [01:17<00:00,  5.61it/s, train/loss=2.340]\nEpoch 0: |          | 434/? [01:17<00:00,  5.61it/s, train/loss=2.340]\nEpoch 0: |          | 434/? [01:17<00:00,  5.61it/s, train/loss=23.30]\nEpoch 0: |          | 435/? [01:17<00:00,  5.62it/s, train/loss=23.30]\nEpoch 0: |          | 435/? [01:17<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 436/? [01:17<00:00,  5.61it/s, train/loss=2.350]\nEpoch 0: |          | 436/? [01:17<00:00,  5.61it/s, train/loss=32.70]\nEpoch 0: |          | 437/? [01:17<00:00,  5.62it/s, train/loss=32.70]\nEpoch 0: |          | 437/? [01:17<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 438/? [01:18<00:00,  5.61it/s, train/loss=2.350]\nEpoch 0: |          | 438/? [01:18<00:00,  5.61it/s, train/loss=33.70]\nEpoch 0: |          | 439/? [01:18<00:00,  5.62it/s, train/loss=33.70]\nEpoch 0: |          | 439/? [01:18<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 440/? [01:18<00:00,  5.61it/s, train/loss=2.350]\nEpoch 0: |          | 440/? [01:18<00:00,  5.61it/s, train/loss=12.70]\nEpoch 0: |          | 441/? [01:18<00:00,  5.62it/s, train/loss=12.70]\nEpoch 0: |          | 441/? [01:18<00:00,  5.62it/s, train/loss=2.360]\nEpoch 0: |          | 442/? [01:18<00:00,  5.62it/s, train/loss=2.360]\nEpoch 0: |          | 442/? [01:18<00:00,  5.62it/s, train/loss=16.30]\nEpoch 0: |          | 443/? [01:18<00:00,  5.63it/s, train/loss=16.30]\nEpoch 0: |          | 443/? [01:18<00:00,  5.63it/s, train/loss=2.330]\nEpoch 0: |          | 444/? [01:19<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 444/? [01:19<00:00,  5.62it/s, train/loss=21.40]\nEpoch 0: |          | 445/? [01:19<00:00,  5.63it/s, train/loss=21.40]\nEpoch 0: |          | 445/? [01:19<00:00,  5.63it/s, train/loss=2.320]\nEpoch 0: |          | 446/? [01:19<00:00,  5.62it/s, train/loss=2.320]\nEpoch 0: |          | 446/? [01:19<00:00,  5.62it/s, train/loss=19.00]\nEpoch 0: |          | 447/? [01:19<00:00,  5.63it/s, train/loss=19.00]\nEpoch 0: |          | 447/? [01:19<00:00,  5.63it/s, train/loss=2.330]\nEpoch 0: |          | 448/? [01:19<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 448/? [01:19<00:00,  5.62it/s, train/loss=16.60]\nEpoch 0: |          | 449/? [01:19<00:00,  5.63it/s, train/loss=16.60]\nEpoch 0: |          | 449/? [01:19<00:00,  5.63it/s, train/loss=2.320]\nEpoch 0: |          | 450/? [01:20<00:00,  5.62it/s, train/loss=2.320]\nEpoch 0: |          | 450/? [01:20<00:00,  5.62it/s, train/loss=18.70]\nEpoch 0: |          | 451/? [01:20<00:00,  5.63it/s, train/loss=18.70]\nEpoch 0: |          | 451/? [01:20<00:00,  5.63it/s, train/loss=2.290]\nEpoch 0: |          | 452/? [01:20<00:00,  5.62it/s, train/loss=2.290]\nEpoch 0: |          | 452/? [01:20<00:00,  5.62it/s, train/loss=10.30]\nEpoch 0: |          | 453/? [01:20<00:00,  5.63it/s, train/loss=10.30]\nEpoch 0: |          | 453/? [01:20<00:00,  5.63it/s, train/loss=2.250]\nEpoch 0: |          | 454/? [01:20<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 454/? [01:20<00:00,  5.62it/s, train/loss=25.40]\nEpoch 0: |          | 455/? [01:20<00:00,  5.63it/s, train/loss=25.40]\nEpoch 0: |          | 455/? [01:20<00:00,  5.63it/s, train/loss=2.210]\nEpoch 0: |          | 456/? [01:21<00:00,  5.62it/s, train/loss=2.210]\nEpoch 0: |          | 456/? [01:21<00:00,  5.62it/s, train/loss=8.850]\nEpoch 0: |          | 457/? [01:21<00:00,  5.63it/s, train/loss=8.850]\nEpoch 0: |          | 457/? [01:21<00:00,  5.63it/s, train/loss=2.160]\nEpoch 0: |          | 458/? [01:21<00:00,  5.62it/s, train/loss=2.160]\nEpoch 0: |          | 458/? [01:21<00:00,  5.62it/s, train/loss=13.90]\nEpoch 0: |          | 459/? [01:21<00:00,  5.63it/s, train/loss=13.90]\nEpoch 0: |          | 459/? [01:21<00:00,  5.63it/s, train/loss=2.120]\nEpoch 0: |          | 460/? [01:21<00:00,  5.62it/s, train/loss=2.120]\nEpoch 0: |          | 460/? [01:21<00:00,  5.62it/s, train/loss=32.80]\nEpoch 0: |          | 461/? [01:21<00:00,  5.63it/s, train/loss=32.80]\nEpoch 0: |          | 461/? [01:21<00:00,  5.63it/s, train/loss=2.120]\nEpoch 0: |          | 462/? [01:22<00:00,  5.62it/s, train/loss=2.120]\nEpoch 0: |          | 462/? [01:22<00:00,  5.62it/s, train/loss=12.30]\nEpoch 0: |          | 463/? [01:22<00:00,  5.63it/s, train/loss=12.30]\nEpoch 0: |          | 463/? [01:22<00:00,  5.63it/s, train/loss=2.140]\nEpoch 0: |          | 464/? [01:22<00:00,  5.62it/s, train/loss=2.140]\nEpoch 0: |          | 464/? [01:22<00:00,  5.62it/s, train/loss=24.00]\nEpoch 0: |          | 465/? [01:22<00:00,  5.63it/s, train/loss=24.00]\nEpoch 0: |          | 465/? [01:22<00:00,  5.63it/s, train/loss=2.120]\nEpoch 0: |          | 466/? [01:22<00:00,  5.62it/s, train/loss=2.120]\nEpoch 0: |          | 466/? [01:22<00:00,  5.62it/s, train/loss=28.10]\nEpoch 0: |          | 467/? [01:22<00:00,  5.63it/s, train/loss=28.10]\nEpoch 0: |          | 467/? [01:22<00:00,  5.63it/s, train/loss=2.070]\nEpoch 0: |          | 468/? [01:23<00:00,  5.62it/s, train/loss=2.070]\nEpoch 0: |          | 468/? [01:23<00:00,  5.62it/s, train/loss=12.20]\nEpoch 0: |          | 469/? [01:23<00:00,  5.63it/s, train/loss=12.20]\nEpoch 0: |          | 469/? [01:23<00:00,  5.63it/s, train/loss=2.060]\nEpoch 0: |          | 470/? [01:23<00:00,  5.62it/s, train/loss=2.060]\nEpoch 0: |          | 470/? [01:23<00:00,  5.62it/s, train/loss=20.10]\nEpoch 0: |          | 471/? [01:23<00:00,  5.63it/s, train/loss=20.10]\nEpoch 0: |          | 471/? [01:23<00:00,  5.63it/s, train/loss=2.090]\nEpoch 0: |          | 472/? [01:24<00:00,  5.62it/s, train/loss=2.090]\nEpoch 0: |          | 472/? [01:24<00:00,  5.62it/s, train/loss=16.70]\nEpoch 0: |          | 473/? [01:24<00:00,  5.63it/s, train/loss=16.70]\nEpoch 0: |          | 473/? [01:24<00:00,  5.63it/s, train/loss=2.170]\nEpoch 0: |          | 474/? [01:24<00:00,  5.62it/s, train/loss=2.170]\nEpoch 0: |          | 474/? [01:24<00:00,  5.62it/s, train/loss=36.50]\nEpoch 0: |          | 475/? [01:24<00:00,  5.63it/s, train/loss=36.50]\nEpoch 0: |          | 475/? [01:24<00:00,  5.63it/s, train/loss=2.250]\nEpoch 0: |          | 476/? [01:24<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 476/? [01:24<00:00,  5.62it/s, train/loss=45.30]\nEpoch 0: |          | 477/? [01:24<00:00,  5.63it/s, train/loss=45.30]\nEpoch 0: |          | 477/? [01:24<00:00,  5.63it/s, train/loss=2.370]\nEpoch 0: |          | 478/? [01:25<00:00,  5.62it/s, train/loss=2.370]\nEpoch 0: |          | 478/? [01:25<00:00,  5.62it/s, train/loss=29.20]\nEpoch 0: |          | 479/? [01:25<00:00,  5.63it/s, train/loss=29.20]\nEpoch 0: |          | 479/? [01:25<00:00,  5.63it/s, train/loss=2.420]\nEpoch 0: |          | 480/? [01:25<00:00,  5.62it/s, train/loss=2.420]\nEpoch 0: |          | 480/? [01:25<00:00,  5.62it/s, train/loss=20.70]\nEpoch 0: |          | 481/? [01:25<00:00,  5.63it/s, train/loss=20.70]\nEpoch 0: |          | 481/? [01:25<00:00,  5.63it/s, train/loss=2.400]\nEpoch 0: |          | 482/? [01:25<00:00,  5.62it/s, train/loss=2.400]\nEpoch 0: |          | 482/? [01:25<00:00,  5.62it/s, train/loss=24.80]\nEpoch 0: |          | 483/? [01:25<00:00,  5.62it/s, train/loss=24.80]\nEpoch 0: |          | 483/? [01:25<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 484/? [01:26<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 484/? [01:26<00:00,  5.62it/s, train/loss=17.00]\nEpoch 0: |          | 485/? [01:26<00:00,  5.62it/s, train/loss=17.00]\nEpoch 0: |          | 485/? [01:26<00:00,  5.62it/s, train/loss=2.290]\nEpoch 0: |          | 486/? [01:26<00:00,  5.62it/s, train/loss=2.290]\nEpoch 0: |          | 486/? [01:26<00:00,  5.62it/s, train/loss=29.70]\nEpoch 0: |          | 487/? [01:26<00:00,  5.62it/s, train/loss=29.70]\nEpoch 0: |          | 487/? [01:26<00:00,  5.62it/s, train/loss=2.260]\nEpoch 0: |          | 488/? [01:26<00:00,  5.62it/s, train/loss=2.260]\nEpoch 0: |          | 488/? [01:26<00:00,  5.62it/s, train/loss=24.80]\nEpoch 0: |          | 489/? [01:26<00:00,  5.62it/s, train/loss=24.80]\nEpoch 0: |          | 489/? [01:26<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 490/? [01:27<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 490/? [01:27<00:00,  5.62it/s, train/loss=34.60]\nEpoch 0: |          | 491/? [01:27<00:00,  5.62it/s, train/loss=34.60]\nEpoch 0: |          | 491/? [01:27<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 492/? [01:27<00:00,  5.62it/s, train/loss=2.250]\nEpoch 0: |          | 492/? [01:27<00:00,  5.62it/s, train/loss=27.40]\nEpoch 0: |          | 493/? [01:27<00:00,  5.62it/s, train/loss=27.40]\nEpoch 0: |          | 493/? [01:27<00:00,  5.62it/s, train/loss=2.270]\nEpoch 0: |          | 494/? [01:27<00:00,  5.62it/s, train/loss=2.270]\nEpoch 0: |          | 494/? [01:27<00:00,  5.62it/s, train/loss=17.20]\nEpoch 0: |          | 495/? [01:28<00:00,  5.62it/s, train/loss=17.20]\nEpoch 0: |          | 495/? [01:28<00:00,  5.62it/s, train/loss=2.320]\nEpoch 0: |          | 496/? [01:28<00:00,  5.62it/s, train/loss=2.320]\nEpoch 0: |          | 496/? [01:28<00:00,  5.62it/s, train/loss=31.80]\nEpoch 0: |          | 497/? [01:28<00:00,  5.62it/s, train/loss=31.80]\nEpoch 0: |          | 497/? [01:28<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 498/? [01:28<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 498/? [01:28<00:00,  5.62it/s, train/loss=33.30]\nEpoch 0: |          | 499/? [01:28<00:00,  5.62it/s, train/loss=33.30]\nEpoch 0: |          | 499/? [01:28<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 500/? [01:29<00:00,  5.62it/s, train/loss=2.350]\nEpoch 0: |          | 500/? [01:29<00:00,  5.62it/s, train/loss=15.50]\nEpoch 0: |          | 501/? [01:29<00:00,  5.62it/s, train/loss=15.50]\nEpoch 0: |          | 501/? [01:29<00:00,  5.62it/s, train/loss=2.380]\nEpoch 0: |          | 502/? [01:29<00:00,  5.62it/s, train/loss=2.380]\nEpoch 0: |          | 502/? [01:29<00:00,  5.62it/s, train/loss=11.30]\nEpoch 0: |          | 503/? [01:29<00:00,  5.62it/s, train/loss=11.30]\nEpoch 0: |          | 503/? [01:29<00:00,  5.62it/s, train/loss=2.360]\nEpoch 0: |          | 504/? [01:29<00:00,  5.62it/s, train/loss=2.360]\nEpoch 0: |          | 504/? [01:29<00:00,  5.62it/s, train/loss=9.480]\nEpoch 0: |          | 505/? [01:29<00:00,  5.62it/s, train/loss=9.480]\nEpoch 0: |          | 505/? [01:29<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 506/? [01:30<00:00,  5.62it/s, train/loss=2.330]\nEpoch 0: |          | 506/? [01:30<00:00,  5.62it/s, train/loss=15.00]\nEpoch 0: |          | 507/? [01:30<00:00,  5.62it/s, train/loss=15.00]\nEpoch 0: |          | 507/? [01:30<00:00,  5.62it/s, train/loss=2.290]\nEpoch 0: |          | 508/? [01:30<00:00,  5.62it/s, train/loss=2.290]\nEpoch 0: |          | 508/? [01:30<00:00,  5.62it/s, train/loss=9.350]\nEpoch 0: |          | 509/? [01:30<00:00,  5.62it/s, train/loss=9.350]\nEpoch 0: |          | 509/? [01:30<00:00,  5.62it/s, train/loss=2.240]\nEpoch 0: |          | 510/? [01:30<00:00,  5.62it/s, train/loss=2.240]\nEpoch 0: |          | 510/? [01:30<00:00,  5.62it/s, train/loss=21.50]\nEpoch 0: |          | 511/? [01:30<00:00,  5.63it/s, train/loss=21.50]\nEpoch 0: |          | 511/? [01:30<00:00,  5.63it/s, train/loss=2.190]\nEpoch 0: |          | 512/? [01:31<00:00,  5.62it/s, train/loss=2.190]\nEpoch 0: |          | 512/? [01:31<00:00,  5.62it/s, train/loss=24.70]\nEpoch 0: |          | 513/? [01:31<00:00,  5.63it/s, train/loss=24.70]\nEpoch 0: |          | 513/? [01:31<00:00,  5.63it/s, train/loss=2.150]\nEpoch 0: |          | 514/? [01:31<00:00,  5.62it/s, train/loss=2.150]\nEpoch 0: |          | 514/? [01:31<00:00,  5.62it/s, train/loss=27.40]\nEpoch 0: |          | 515/? [01:31<00:00,  5.63it/s, train/loss=27.40]\nEpoch 0: |          | 515/? [01:31<00:00,  5.63it/s, train/loss=2.130]\nEpoch 0: |          | 516/? [01:31<00:00,  5.62it/s, train/loss=2.130]\nEpoch 0: |          | 516/? [01:31<00:00,  5.62it/s, train/loss=33.50]\nEpoch 0: |          | 517/? [01:31<00:00,  5.63it/s, train/loss=33.50]\nEpoch 0: |          | 517/? [01:31<00:00,  5.63it/s, train/loss=2.140]\nEpoch 0: |          | 518/? [01:32<00:00,  5.63it/s, train/loss=2.140]\nEpoch 0: |          | 518/? [01:32<00:00,  5.62it/s, train/loss=14.40]\nEpoch 0: |          | 519/? [01:32<00:00,  5.63it/s, train/loss=14.40]\nEpoch 0: |          | 519/? [01:32<00:00,  5.63it/s, train/loss=2.180]\nEpoch 0: |          | 520/? [01:32<00:00,  5.63it/s, train/loss=2.180]\nEpoch 0: |          | 520/? [01:32<00:00,  5.63it/s, train/loss=60.00]\nEpoch 0: |          | 521/? [01:32<00:00,  5.64it/s, train/loss=60.00]\nEpoch 0: |          | 521/? [01:32<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 522/? [01:32<00:00,  5.63it/s, train/loss=2.210]\nEpoch 0: |          | 522/? [01:32<00:00,  5.63it/s, train/loss=20.10]\nEpoch 0: |          | 523/? [01:32<00:00,  5.64it/s, train/loss=20.10]\nEpoch 0: |          | 523/? [01:32<00:00,  5.64it/s, train/loss=2.260]\nEpoch 0: |          | 524/? [01:33<00:00,  5.63it/s, train/loss=2.260]\nEpoch 0: |          | 524/? [01:33<00:00,  5.63it/s, train/loss=32.00]\nEpoch 0: |          | 525/? [01:33<00:00,  5.64it/s, train/loss=32.00]\nEpoch 0: |          | 525/? [01:33<00:00,  5.64it/s, train/loss=2.300]\nEpoch 0: |          | 526/? [01:33<00:00,  5.63it/s, train/loss=2.300]\nEpoch 0: |          | 526/? [01:33<00:00,  5.63it/s, train/loss=32.60]\nEpoch 0: |          | 527/? [01:33<00:00,  5.64it/s, train/loss=32.60]\nEpoch 0: |          | 527/? [01:33<00:00,  5.64it/s, train/loss=2.300]\nEpoch 0: |          | 528/? [01:33<00:00,  5.63it/s, train/loss=2.300]\nEpoch 0: |          | 528/? [01:33<00:00,  5.63it/s, train/loss=29.10]\nEpoch 0: |          | 529/? [01:33<00:00,  5.64it/s, train/loss=29.10]\nEpoch 0: |          | 529/? [01:33<00:00,  5.64it/s, train/loss=2.290]\nEpoch 0: |          | 530/? [01:34<00:00,  5.63it/s, train/loss=2.290]\nEpoch 0: |          | 530/? [01:34<00:00,  5.63it/s, train/loss=37.40]\nEpoch 0: |          | 531/? [01:34<00:00,  5.64it/s, train/loss=37.40]\nEpoch 0: |          | 531/? [01:34<00:00,  5.64it/s, train/loss=2.250]\nEpoch 0: |          | 532/? [01:34<00:00,  5.64it/s, train/loss=2.250]\nEpoch 0: |          | 532/? [01:34<00:00,  5.64it/s, train/loss=50.00]\nEpoch 0: |          | 533/? [01:34<00:00,  5.64it/s, train/loss=50.00]\nEpoch 0: |          | 533/? [01:34<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 534/? [01:34<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 534/? [01:34<00:00,  5.64it/s, train/loss=18.50]\nEpoch 0: |          | 535/? [01:34<00:00,  5.65it/s, train/loss=18.50]\nEpoch 0: |          | 535/? [01:34<00:00,  5.65it/s, train/loss=2.210]\nEpoch 0: |          | 536/? [01:35<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 536/? [01:35<00:00,  5.64it/s, train/loss=15.60]\nEpoch 0: |          | 537/? [01:35<00:00,  5.65it/s, train/loss=15.60]\nEpoch 0: |          | 537/? [01:35<00:00,  5.65it/s, train/loss=2.220]\nEpoch 0: |          | 538/? [01:35<00:00,  5.64it/s, train/loss=2.220]\nEpoch 0: |          | 538/? [01:35<00:00,  5.64it/s, train/loss=10.90]\nEpoch 0: |          | 539/? [01:35<00:00,  5.65it/s, train/loss=10.90]\nEpoch 0: |          | 539/? [01:35<00:00,  5.65it/s, train/loss=2.210]\nEpoch 0: |          | 540/? [01:35<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 540/? [01:35<00:00,  5.64it/s, train/loss=46.40]\nEpoch 0: |          | 541/? [01:35<00:00,  5.65it/s, train/loss=46.40]\nEpoch 0: |          | 541/? [01:35<00:00,  5.65it/s, train/loss=2.180]\nEpoch 0: |          | 542/? [01:36<00:00,  5.64it/s, train/loss=2.180]\nEpoch 0: |          | 542/? [01:36<00:00,  5.64it/s, train/loss=11.40]\nEpoch 0: |          | 543/? [01:36<00:00,  5.65it/s, train/loss=11.40]\nEpoch 0: |          | 543/? [01:36<00:00,  5.65it/s, train/loss=2.160]\nEpoch 0: |          | 544/? [01:36<00:00,  5.65it/s, train/loss=2.160]\nEpoch 0: |          | 544/? [01:36<00:00,  5.65it/s, train/loss=48.70]\nEpoch 0: |          | 545/? [01:36<00:00,  5.65it/s, train/loss=48.70]\nEpoch 0: |          | 545/? [01:36<00:00,  5.65it/s, train/loss=2.150]\nEpoch 0: |          | 546/? [01:36<00:00,  5.65it/s, train/loss=2.150]\nEpoch 0: |          | 546/? [01:36<00:00,  5.65it/s, train/loss=22.10]\nEpoch 0: |          | 547/? [01:36<00:00,  5.66it/s, train/loss=22.10]\nEpoch 0: |          | 547/? [01:36<00:00,  5.65it/s, train/loss=2.240]\nEpoch 0: |          | 548/? [01:37<00:00,  5.65it/s, train/loss=2.240]\nEpoch 0: |          | 548/? [01:37<00:00,  5.65it/s, train/loss=29.10]\nEpoch 0: |          | 549/? [01:37<00:00,  5.66it/s, train/loss=29.10]\nEpoch 0: |          | 549/? [01:37<00:00,  5.66it/s, train/loss=2.350]\nEpoch 0: |          | 550/? [01:37<00:00,  5.65it/s, train/loss=2.350]\nEpoch 0: |          | 550/? [01:37<00:00,  5.65it/s, train/loss=12.00]\nEpoch 0: |          | 551/? [01:37<00:00,  5.66it/s, train/loss=12.00]\nEpoch 0: |          | 551/? [01:37<00:00,  5.66it/s, train/loss=2.400]\nEpoch 0: |          | 552/? [01:37<00:00,  5.65it/s, train/loss=2.400]\nEpoch 0: |          | 552/? [01:37<00:00,  5.65it/s, train/loss=17.40]\nEpoch 0: |          | 553/? [01:37<00:00,  5.66it/s, train/loss=17.40]\nEpoch 0: |          | 553/? [01:37<00:00,  5.66it/s, train/loss=2.390]\nEpoch 0: |          | 554/? [01:37<00:00,  5.65it/s, train/loss=2.390]\nEpoch 0: |          | 554/? [01:37<00:00,  5.65it/s, train/loss=17.00]\nEpoch 0: |          | 555/? [01:38<00:00,  5.66it/s, train/loss=17.00]\nEpoch 0: |          | 555/? [01:38<00:00,  5.66it/s, train/loss=2.330]\nEpoch 0: |          | 556/? [01:38<00:00,  5.66it/s, train/loss=2.330]\nEpoch 0: |          | 556/? [01:38<00:00,  5.66it/s, train/loss=19.20]\nEpoch 0: |          | 557/? [01:38<00:00,  5.66it/s, train/loss=19.20]\nEpoch 0: |          | 557/? [01:38<00:00,  5.66it/s, train/loss=2.260]\nEpoch 0: |          | 558/? [01:38<00:00,  5.66it/s, train/loss=2.260]\nEpoch 0: |          | 558/? [01:38<00:00,  5.66it/s, train/loss=24.90]\nEpoch 0: |          | 559/? [01:38<00:00,  5.66it/s, train/loss=24.90]\nEpoch 0: |          | 559/? [01:38<00:00,  5.66it/s, train/loss=2.240]\nEpoch 0: |          | 560/? [01:38<00:00,  5.66it/s, train/loss=2.240]\nEpoch 0: |          | 560/? [01:38<00:00,  5.66it/s, train/loss=37.70]\nEpoch 0: |          | 561/? [01:39<00:00,  5.67it/s, train/loss=37.70]\nEpoch 0: |          | 561/? [01:39<00:00,  5.67it/s, train/loss=2.240]\nEpoch 0: |          | 562/? [01:39<00:00,  5.66it/s, train/loss=2.240]\nEpoch 0: |          | 562/? [01:39<00:00,  5.66it/s, train/loss=29.60]\nEpoch 0: |          | 563/? [01:39<00:00,  5.67it/s, train/loss=29.60]\nEpoch 0: |          | 563/? [01:39<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 564/? [01:39<00:00,  5.66it/s, train/loss=2.200]\nEpoch 0: |          | 564/? [01:39<00:00,  5.66it/s, train/loss=13.10]\nEpoch 0: |          | 565/? [01:39<00:00,  5.67it/s, train/loss=13.10]\nEpoch 0: |          | 565/? [01:39<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 566/? [01:39<00:00,  5.66it/s, train/loss=2.180]\nEpoch 0: |          | 566/? [01:39<00:00,  5.66it/s, train/loss=14.70]\nEpoch 0: |          | 567/? [01:39<00:00,  5.67it/s, train/loss=14.70]\nEpoch 0: |          | 567/? [01:39<00:00,  5.67it/s, train/loss=2.170]\nEpoch 0: |          | 568/? [01:40<00:00,  5.66it/s, train/loss=2.170]\nEpoch 0: |          | 568/? [01:40<00:00,  5.66it/s, train/loss=25.70]\nEpoch 0: |          | 569/? [01:40<00:00,  5.67it/s, train/loss=25.70]\nEpoch 0: |          | 569/? [01:40<00:00,  5.67it/s, train/loss=2.150]\nEpoch 0: |          | 570/? [01:40<00:00,  5.67it/s, train/loss=2.150]\nEpoch 0: |          | 570/? [01:40<00:00,  5.67it/s, train/loss=20.20]\nEpoch 0: |          | 571/? [01:40<00:00,  5.67it/s, train/loss=20.20]\nEpoch 0: |          | 571/? [01:40<00:00,  5.67it/s, train/loss=2.120]\nEpoch 0: |          | 572/? [01:40<00:00,  5.66it/s, train/loss=2.120]\nEpoch 0: |          | 572/? [01:40<00:00,  5.66it/s, train/loss=24.90]\nEpoch 0: |          | 573/? [01:41<00:00,  5.67it/s, train/loss=24.90]\nEpoch 0: |          | 573/? [01:41<00:00,  5.67it/s, train/loss=2.140]\nEpoch 0: |          | 574/? [01:41<00:00,  5.67it/s, train/loss=2.140]\nEpoch 0: |          | 574/? [01:41<00:00,  5.67it/s, train/loss=19.00]\nEpoch 0: |          | 575/? [01:41<00:00,  5.67it/s, train/loss=19.00]\nEpoch 0: |          | 575/? [01:41<00:00,  5.67it/s, train/loss=2.190]\nEpoch 0: |          | 576/? [01:41<00:00,  5.67it/s, train/loss=2.190]\nEpoch 0: |          | 576/? [01:41<00:00,  5.67it/s, train/loss=11.50]\nEpoch 0: |          | 577/? [01:41<00:00,  5.67it/s, train/loss=11.50]\nEpoch 0: |          | 577/? [01:41<00:00,  5.67it/s, train/loss=2.240]\nEpoch 0: |          | 578/? [01:41<00:00,  5.67it/s, train/loss=2.240]\nEpoch 0: |          | 578/? [01:41<00:00,  5.67it/s, train/loss=19.60]\nEpoch 0: |          | 579/? [01:42<00:00,  5.68it/s, train/loss=19.60]\nEpoch 0: |          | 579/? [01:42<00:00,  5.68it/s, train/loss=2.230]\nEpoch 0: |          | 580/? [01:42<00:00,  5.67it/s, train/loss=2.230]\nEpoch 0: |          | 580/? [01:42<00:00,  5.67it/s, train/loss=39.90]\nEpoch 0: |          | 581/? [01:42<00:00,  5.68it/s, train/loss=39.90]\nEpoch 0: |          | 581/? [01:42<00:00,  5.68it/s, train/loss=2.140]\nEpoch 0: |          | 582/? [01:42<00:00,  5.67it/s, train/loss=2.140]\nEpoch 0: |          | 582/? [01:42<00:00,  5.67it/s, train/loss=14.50]\nEpoch 0: |          | 583/? [01:42<00:00,  5.68it/s, train/loss=14.50]\nEpoch 0: |          | 583/? [01:42<00:00,  5.68it/s, train/loss=2.050]\nEpoch 0: |          | 584/? [01:42<00:00,  5.67it/s, train/loss=2.050]\nEpoch 0: |          | 584/? [01:42<00:00,  5.67it/s, train/loss=28.80]\nEpoch 0: |          | 585/? [01:43<00:00,  5.68it/s, train/loss=28.80]\nEpoch 0: |          | 585/? [01:43<00:00,  5.68it/s, train/loss=2.020]\nEpoch 0: |          | 586/? [01:43<00:00,  5.67it/s, train/loss=2.020]\nEpoch 0: |          | 586/? [01:43<00:00,  5.67it/s, train/loss=32.90]\nEpoch 0: |          | 587/? [01:43<00:00,  5.68it/s, train/loss=32.90]\nEpoch 0: |          | 587/? [01:43<00:00,  5.68it/s, train/loss=2.000]\nEpoch 0: |          | 588/? [01:43<00:00,  5.67it/s, train/loss=2.000]\nEpoch 0: |          | 588/? [01:43<00:00,  5.67it/s, train/loss=26.10]\nEpoch 0: |          | 589/? [01:43<00:00,  5.68it/s, train/loss=26.10]\nEpoch 0: |          | 589/? [01:43<00:00,  5.68it/s, train/loss=2.020]\nEpoch 0: |          | 590/? [01:43<00:00,  5.68it/s, train/loss=2.020]\nEpoch 0: |          | 590/? [01:43<00:00,  5.68it/s, train/loss=37.00]\nEpoch 0: |          | 591/? [01:43<00:00,  5.68it/s, train/loss=37.00]\nEpoch 0: |          | 591/? [01:43<00:00,  5.68it/s, train/loss=2.080]\nEpoch 0: |          | 592/? [01:44<00:00,  5.68it/s, train/loss=2.080]\nEpoch 0: |          | 592/? [01:44<00:00,  5.68it/s, train/loss=17.80]\nEpoch 0: |          | 593/? [01:44<00:00,  5.68it/s, train/loss=17.80]\nEpoch 0: |          | 593/? [01:44<00:00,  5.68it/s, train/loss=2.140]\nEpoch 0: |          | 594/? [01:44<00:00,  5.68it/s, train/loss=2.140]\nEpoch 0: |          | 594/? [01:44<00:00,  5.68it/s, train/loss=27.40]\nEpoch 0: |          | 595/? [01:44<00:00,  5.69it/s, train/loss=27.40]\nEpoch 0: |          | 595/? [01:44<00:00,  5.69it/s, train/loss=2.160]\nEpoch 0: |          | 596/? [01:44<00:00,  5.68it/s, train/loss=2.160]\nEpoch 0: |          | 596/? [01:44<00:00,  5.68it/s, train/loss=26.80]\nEpoch 0: |          | 597/? [01:44<00:00,  5.69it/s, train/loss=26.80]\nEpoch 0: |          | 597/? [01:44<00:00,  5.69it/s, train/loss=2.160]\nEpoch 0: |          | 598/? [01:45<00:00,  5.68it/s, train/loss=2.160]\nEpoch 0: |          | 598/? [01:45<00:00,  5.68it/s, train/loss=32.30]\nEpoch 0: |          | 599/? [01:45<00:00,  5.69it/s, train/loss=32.30]\nEpoch 0: |          | 599/? [01:45<00:00,  5.69it/s, train/loss=2.180]\nEpoch 0: |          | 600/? [01:45<00:00,  5.68it/s, train/loss=2.180]\nEpoch 0: |          | 600/? [01:45<00:00,  5.68it/s, train/loss=27.90]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:00, 62.82it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:00, 63.32it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:00, 64.21it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:00, 65.06it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:00, 65.52it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:00, 65.97it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:00, 66.31it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:00, 66.59it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:00, 66.79it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:00, 66.84it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:00, 66.80it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:00<00:00, 66.97it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:00<00:00, 66.92it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:00<00:00, 66.42it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:00<00:00, 66.48it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:00<00:00, 66.46it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:00<00:00, 66.55it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:00<00:00, 66.63it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:00<00:00, 66.70it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:00<00:00, 66.75it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:00<00:00, 66.67it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:00<00:00, 66.75it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:00<00:00, 66.76it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:00<00:00, 66.78it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:00<00:00, 66.79it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:00<00:00, 66.81it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:00<00:00, 66.88it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:00<00:00, 66.93it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:00<00:00, 67.00it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:00<00:00, 66.79it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:00<00:00, 65.50it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:00<00:00, 65.37it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:00<00:00, 64.63it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:00<00:00, 64.36it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:00<00:00, 64.40it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:00<00:00, 64.43it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:00<00:00, 64.44it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:00<00:00, 64.43it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:00<00:00, 64.41it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 64.39it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 600/? [01:46<00:00,  5.62it/s, train/loss=27.90]\nEpoch 0: |          | 601/? [01:47<00:00,  5.60it/s, train/loss=27.90]\nEpoch 0: |          | 601/? [01:47<00:00,  5.60it/s, train/loss=2.240]\nEpoch 0: |          | 602/? [01:47<00:00,  5.60it/s, train/loss=2.240]\nEpoch 0: |          | 602/? [01:47<00:00,  5.60it/s, train/loss=27.10]\nEpoch 0: |          | 603/? [01:47<00:00,  5.61it/s, train/loss=27.10]\nEpoch 0: |          | 603/? [01:47<00:00,  5.61it/s, train/loss=2.310]\nEpoch 0: |          | 604/? [01:47<00:00,  5.60it/s, train/loss=2.310]\nEpoch 0: |          | 604/? [01:47<00:00,  5.60it/s, train/loss=33.40]\nEpoch 0: |          | 605/? [01:47<00:00,  5.61it/s, train/loss=33.40]\nEpoch 0: |          | 605/? [01:47<00:00,  5.61it/s, train/loss=2.350]\nEpoch 0: |          | 606/? [01:48<00:00,  5.60it/s, train/loss=2.350]\nEpoch 0: |          | 606/? [01:48<00:00,  5.60it/s, train/loss=13.90]\nEpoch 0: |          | 607/? [01:48<00:00,  5.61it/s, train/loss=13.90]\nEpoch 0: |          | 607/? [01:48<00:00,  5.61it/s, train/loss=2.310]\nEpoch 0: |          | 608/? [01:48<00:00,  5.60it/s, train/loss=2.310]\nEpoch 0: |          | 608/? [01:48<00:00,  5.60it/s, train/loss=19.40]\nEpoch 0: |          | 609/? [01:48<00:00,  5.61it/s, train/loss=19.40]\nEpoch 0: |          | 609/? [01:48<00:00,  5.61it/s, train/loss=2.240]\nEpoch 0: |          | 610/? [01:48<00:00,  5.60it/s, train/loss=2.240]\nEpoch 0: |          | 610/? [01:48<00:00,  5.60it/s, train/loss=10.60]\nEpoch 0: |          | 611/? [01:48<00:00,  5.61it/s, train/loss=10.60]\nEpoch 0: |          | 611/? [01:48<00:00,  5.61it/s, train/loss=2.180]\nEpoch 0: |          | 612/? [01:49<00:00,  5.61it/s, train/loss=2.180]\nEpoch 0: |          | 612/? [01:49<00:00,  5.61it/s, train/loss=23.00]\nEpoch 0: |          | 613/? [01:49<00:00,  5.61it/s, train/loss=23.00]\nEpoch 0: |          | 613/? [01:49<00:00,  5.61it/s, train/loss=2.130]\nEpoch 0: |          | 614/? [01:49<00:00,  5.61it/s, train/loss=2.130]\nEpoch 0: |          | 614/? [01:49<00:00,  5.61it/s, train/loss=15.30]\nEpoch 0: |          | 615/? [01:49<00:00,  5.61it/s, train/loss=15.30]\nEpoch 0: |          | 615/? [01:49<00:00,  5.61it/s, train/loss=2.090]\nEpoch 0: |          | 616/? [01:49<00:00,  5.61it/s, train/loss=2.090]\nEpoch 0: |          | 616/? [01:49<00:00,  5.61it/s, train/loss=34.00]\nEpoch 0: |          | 617/? [01:49<00:00,  5.62it/s, train/loss=34.00]\nEpoch 0: |          | 617/? [01:49<00:00,  5.62it/s, train/loss=2.060]\nEpoch 0: |          | 618/? [01:50<00:00,  5.61it/s, train/loss=2.060]\nEpoch 0: |          | 618/? [01:50<00:00,  5.61it/s, train/loss=10.70]\nEpoch 0: |          | 619/? [01:50<00:00,  5.62it/s, train/loss=10.70]\nEpoch 0: |          | 619/? [01:50<00:00,  5.62it/s, train/loss=2.020]\nEpoch 0: |          | 620/? [01:50<00:00,  5.61it/s, train/loss=2.020]\nEpoch 0: |          | 620/? [01:50<00:00,  5.61it/s, train/loss=12.90]\nEpoch 0: |          | 621/? [01:50<00:00,  5.62it/s, train/loss=12.90]\nEpoch 0: |          | 621/? [01:50<00:00,  5.62it/s, train/loss=1.970]\nEpoch 0: |          | 622/? [01:50<00:00,  5.61it/s, train/loss=1.970]\nEpoch 0: |          | 622/? [01:50<00:00,  5.61it/s, train/loss=21.60]\nEpoch 0: |          | 623/? [01:50<00:00,  5.62it/s, train/loss=21.60]\nEpoch 0: |          | 623/? [01:50<00:00,  5.62it/s, train/loss=1.930]\nEpoch 0: |          | 624/? [01:51<00:00,  5.61it/s, train/loss=1.930]\nEpoch 0: |          | 624/? [01:51<00:00,  5.61it/s, train/loss=36.80]\nEpoch 0: |          | 625/? [01:51<00:00,  5.62it/s, train/loss=36.80]\nEpoch 0: |          | 625/? [01:51<00:00,  5.62it/s, train/loss=1.920]\nEpoch 0: |          | 626/? [01:51<00:00,  5.62it/s, train/loss=1.920]\nEpoch 0: |          | 626/? [01:51<00:00,  5.62it/s, train/loss=26.50]\nEpoch 0: |          | 627/? [01:51<00:00,  5.62it/s, train/loss=26.50]\nEpoch 0: |          | 627/? [01:51<00:00,  5.62it/s, train/loss=1.930]\nEpoch 0: |          | 628/? [01:51<00:00,  5.62it/s, train/loss=1.930]\nEpoch 0: |          | 628/? [01:51<00:00,  5.62it/s, train/loss=28.90]\nEpoch 0: |          | 629/? [01:51<00:00,  5.62it/s, train/loss=28.90]\nEpoch 0: |          | 629/? [01:51<00:00,  5.62it/s, train/loss=1.910]\nEpoch 0: |          | 630/? [01:52<00:00,  5.62it/s, train/loss=1.910]\nEpoch 0: |          | 630/? [01:52<00:00,  5.62it/s, train/loss=35.60]\nEpoch 0: |          | 631/? [01:52<00:00,  5.63it/s, train/loss=35.60]\nEpoch 0: |          | 631/? [01:52<00:00,  5.63it/s, train/loss=1.900]\nEpoch 0: |          | 632/? [01:52<00:00,  5.62it/s, train/loss=1.900]\nEpoch 0: |          | 632/? [01:52<00:00,  5.62it/s, train/loss=15.00]\nEpoch 0: |          | 633/? [01:52<00:00,  5.63it/s, train/loss=15.00]\nEpoch 0: |          | 633/? [01:52<00:00,  5.63it/s, train/loss=1.970]\nEpoch 0: |          | 634/? [01:52<00:00,  5.62it/s, train/loss=1.970]\nEpoch 0: |          | 634/? [01:52<00:00,  5.62it/s, train/loss=19.70]\nEpoch 0: |          | 635/? [01:52<00:00,  5.63it/s, train/loss=19.70]\nEpoch 0: |          | 635/? [01:52<00:00,  5.63it/s, train/loss=2.050]\nEpoch 0: |          | 636/? [01:53<00:00,  5.62it/s, train/loss=2.050]\nEpoch 0: |          | 636/? [01:53<00:00,  5.62it/s, train/loss=33.90]\nEpoch 0: |          | 637/? [01:53<00:00,  5.63it/s, train/loss=33.90]\nEpoch 0: |          | 637/? [01:53<00:00,  5.63it/s, train/loss=2.140]\nEpoch 0: |          | 638/? [01:53<00:00,  5.63it/s, train/loss=2.140]\nEpoch 0: |          | 638/? [01:53<00:00,  5.62it/s, train/loss=30.40]\nEpoch 0: |          | 639/? [01:53<00:00,  5.63it/s, train/loss=30.40]\nEpoch 0: |          | 639/? [01:53<00:00,  5.63it/s, train/loss=2.220]\nEpoch 0: |          | 640/? [01:53<00:00,  5.63it/s, train/loss=2.220]\nEpoch 0: |          | 640/? [01:53<00:00,  5.63it/s, train/loss=25.00]\nEpoch 0: |          | 641/? [01:53<00:00,  5.63it/s, train/loss=25.00]\nEpoch 0: |          | 641/? [01:53<00:00,  5.63it/s, train/loss=2.240]\nEpoch 0: |          | 642/? [01:54<00:00,  5.63it/s, train/loss=2.240]\nEpoch 0: |          | 642/? [01:54<00:00,  5.63it/s, train/loss=10.00]\nEpoch 0: |          | 643/? [01:54<00:00,  5.63it/s, train/loss=10.00]\nEpoch 0: |          | 643/? [01:54<00:00,  5.63it/s, train/loss=2.220]\nEpoch 0: |          | 644/? [01:54<00:00,  5.63it/s, train/loss=2.220]\nEpoch 0: |          | 644/? [01:54<00:00,  5.63it/s, train/loss=22.80]\nEpoch 0: |          | 645/? [01:54<00:00,  5.63it/s, train/loss=22.80]\nEpoch 0: |          | 645/? [01:54<00:00,  5.63it/s, train/loss=2.190]\nEpoch 0: |          | 646/? [01:54<00:00,  5.63it/s, train/loss=2.190]\nEpoch 0: |          | 646/? [01:54<00:00,  5.63it/s, train/loss=22.90]\nEpoch 0: |          | 647/? [01:54<00:00,  5.64it/s, train/loss=22.90]\nEpoch 0: |          | 647/? [01:54<00:00,  5.64it/s, train/loss=2.190]\nEpoch 0: |          | 648/? [01:55<00:00,  5.63it/s, train/loss=2.190]\nEpoch 0: |          | 648/? [01:55<00:00,  5.63it/s, train/loss=42.40]\nEpoch 0: |          | 649/? [01:55<00:00,  5.64it/s, train/loss=42.40]\nEpoch 0: |          | 649/? [01:55<00:00,  5.64it/s, train/loss=2.190]\nEpoch 0: |          | 650/? [01:55<00:00,  5.63it/s, train/loss=2.190]\nEpoch 0: |          | 650/? [01:55<00:00,  5.63it/s, train/loss=61.90]\nEpoch 0: |          | 651/? [01:55<00:00,  5.64it/s, train/loss=61.90]\nEpoch 0: |          | 651/? [01:55<00:00,  5.64it/s, train/loss=2.180]\nEpoch 0: |          | 652/? [01:55<00:00,  5.63it/s, train/loss=2.180]\nEpoch 0: |          | 652/? [01:55<00:00,  5.63it/s, train/loss=38.10]\nEpoch 0: |          | 653/? [01:55<00:00,  5.64it/s, train/loss=38.10]\nEpoch 0: |          | 653/? [01:55<00:00,  5.64it/s, train/loss=2.180]\nEpoch 0: |          | 654/? [01:56<00:00,  5.63it/s, train/loss=2.180]\nEpoch 0: |          | 654/? [01:56<00:00,  5.63it/s, train/loss=20.60]\nEpoch 0: |          | 655/? [01:56<00:00,  5.64it/s, train/loss=20.60]\nEpoch 0: |          | 655/? [01:56<00:00,  5.64it/s, train/loss=2.230]\nEpoch 0: |          | 656/? [01:56<00:00,  5.64it/s, train/loss=2.230]\nEpoch 0: |          | 656/? [01:56<00:00,  5.64it/s, train/loss=18.20]\nEpoch 0: |          | 657/? [01:56<00:00,  5.64it/s, train/loss=18.20]\nEpoch 0: |          | 657/? [01:56<00:00,  5.64it/s, train/loss=2.270]\nEpoch 0: |          | 658/? [01:56<00:00,  5.64it/s, train/loss=2.270]\nEpoch 0: |          | 658/? [01:56<00:00,  5.64it/s, train/loss=17.30]\nEpoch 0: |          | 659/? [01:56<00:00,  5.64it/s, train/loss=17.30]\nEpoch 0: |          | 659/? [01:56<00:00,  5.64it/s, train/loss=2.290]\nEpoch 0: |          | 660/? [01:57<00:00,  5.64it/s, train/loss=2.290]\nEpoch 0: |          | 660/? [01:57<00:00,  5.64it/s, train/loss=11.40]\nEpoch 0: |          | 661/? [01:57<00:00,  5.64it/s, train/loss=11.40]\nEpoch 0: |          | 661/? [01:57<00:00,  5.64it/s, train/loss=2.270]\nEpoch 0: |          | 662/? [01:57<00:00,  5.64it/s, train/loss=2.270]\nEpoch 0: |          | 662/? [01:57<00:00,  5.64it/s, train/loss=14.50]\nEpoch 0: |          | 663/? [01:57<00:00,  5.65it/s, train/loss=14.50]\nEpoch 0: |          | 663/? [01:57<00:00,  5.65it/s, train/loss=2.210]\nEpoch 0: |          | 664/? [01:57<00:00,  5.64it/s, train/loss=2.210]\nEpoch 0: |          | 664/? [01:57<00:00,  5.64it/s, train/loss=24.50]\nEpoch 0: |          | 665/? [01:57<00:00,  5.65it/s, train/loss=24.50]\nEpoch 0: |          | 665/? [01:57<00:00,  5.65it/s, train/loss=2.100]\nEpoch 0: |          | 666/? [01:58<00:00,  5.64it/s, train/loss=2.100]\nEpoch 0: |          | 666/? [01:58<00:00,  5.64it/s, train/loss=29.30]\nEpoch 0: |          | 667/? [01:58<00:00,  5.65it/s, train/loss=29.30]\nEpoch 0: |          | 667/? [01:58<00:00,  5.65it/s, train/loss=2.000]\nEpoch 0: |          | 668/? [01:58<00:00,  5.64it/s, train/loss=2.000]\nEpoch 0: |          | 668/? [01:58<00:00,  5.64it/s, train/loss=24.10]\nEpoch 0: |          | 669/? [01:58<00:00,  5.65it/s, train/loss=24.10]\nEpoch 0: |          | 669/? [01:58<00:00,  5.65it/s, train/loss=1.960]\nEpoch 0: |          | 670/? [01:58<00:00,  5.64it/s, train/loss=1.960]\nEpoch 0: |          | 670/? [01:58<00:00,  5.64it/s, train/loss=32.10]\nEpoch 0: |          | 671/? [01:58<00:00,  5.65it/s, train/loss=32.10]\nEpoch 0: |          | 671/? [01:58<00:00,  5.65it/s, train/loss=1.950]\nEpoch 0: |          | 672/? [01:59<00:00,  5.65it/s, train/loss=1.950]\nEpoch 0: |          | 672/? [01:59<00:00,  5.65it/s, train/loss=21.70]\nEpoch 0: |          | 673/? [01:59<00:00,  5.65it/s, train/loss=21.70]\nEpoch 0: |          | 673/? [01:59<00:00,  5.65it/s, train/loss=1.960]\nEpoch 0: |          | 674/? [01:59<00:00,  5.65it/s, train/loss=1.960]\nEpoch 0: |          | 674/? [01:59<00:00,  5.65it/s, train/loss=31.20]\nEpoch 0: |          | 675/? [01:59<00:00,  5.65it/s, train/loss=31.20]\nEpoch 0: |          | 675/? [01:59<00:00,  5.65it/s, train/loss=1.980]\nEpoch 0: |          | 676/? [01:59<00:00,  5.65it/s, train/loss=1.980]\nEpoch 0: |          | 676/? [01:59<00:00,  5.65it/s, train/loss=10.90]\nEpoch 0: |          | 677/? [01:59<00:00,  5.65it/s, train/loss=10.90]\nEpoch 0: |          | 677/? [01:59<00:00,  5.65it/s, train/loss=2.000]\nEpoch 0: |          | 678/? [02:00<00:00,  5.65it/s, train/loss=2.000]\nEpoch 0: |          | 678/? [02:00<00:00,  5.65it/s, train/loss=11.30]\nEpoch 0: |          | 679/? [02:00<00:00,  5.66it/s, train/loss=11.30]\nEpoch 0: |          | 679/? [02:00<00:00,  5.66it/s, train/loss=2.020]\nEpoch 0: |          | 680/? [02:00<00:00,  5.65it/s, train/loss=2.020]\nEpoch 0: |          | 680/? [02:00<00:00,  5.65it/s, train/loss=26.00]\nEpoch 0: |          | 681/? [02:00<00:00,  5.66it/s, train/loss=26.00]\nEpoch 0: |          | 681/? [02:00<00:00,  5.66it/s, train/loss=2.000]\nEpoch 0: |          | 682/? [02:00<00:00,  5.65it/s, train/loss=2.000]\nEpoch 0: |          | 682/? [02:00<00:00,  5.65it/s, train/loss=26.70]\nEpoch 0: |          | 683/? [02:00<00:00,  5.66it/s, train/loss=26.70]\nEpoch 0: |          | 683/? [02:00<00:00,  5.66it/s, train/loss=1.980]\nEpoch 0: |          | 684/? [02:01<00:00,  5.65it/s, train/loss=1.980]\nEpoch 0: |          | 684/? [02:01<00:00,  5.65it/s, train/loss=8.930]\nEpoch 0: |          | 685/? [02:01<00:00,  5.66it/s, train/loss=8.930]\nEpoch 0: |          | 685/? [02:01<00:00,  5.66it/s, train/loss=1.980]\nEpoch 0: |          | 686/? [02:01<00:00,  5.65it/s, train/loss=1.980]\nEpoch 0: |          | 686/? [02:01<00:00,  5.65it/s, train/loss=37.30]\nEpoch 0: |          | 687/? [02:01<00:00,  5.66it/s, train/loss=37.30]\nEpoch 0: |          | 687/? [02:01<00:00,  5.66it/s, train/loss=1.970]\nEpoch 0: |          | 688/? [02:01<00:00,  5.65it/s, train/loss=1.970]\nEpoch 0: |          | 688/? [02:01<00:00,  5.65it/s, train/loss=30.80]\nEpoch 0: |          | 689/? [02:01<00:00,  5.66it/s, train/loss=30.80]\nEpoch 0: |          | 689/? [02:01<00:00,  5.66it/s, train/loss=2.160]\nEpoch 0: |          | 690/? [02:02<00:00,  5.65it/s, train/loss=2.160]\nEpoch 0: |          | 690/? [02:02<00:00,  5.65it/s, train/loss=32.70]\nEpoch 0: |          | 691/? [02:02<00:00,  5.66it/s, train/loss=32.70]\nEpoch 0: |          | 691/? [02:02<00:00,  5.66it/s, train/loss=2.230]\nEpoch 0: |          | 692/? [02:02<00:00,  5.65it/s, train/loss=2.230]\nEpoch 0: |          | 692/? [02:02<00:00,  5.65it/s, train/loss=22.50]\nEpoch 0: |          | 693/? [02:02<00:00,  5.66it/s, train/loss=22.50]\nEpoch 0: |          | 693/? [02:02<00:00,  5.66it/s, train/loss=2.280]\nEpoch 0: |          | 694/? [02:02<00:00,  5.65it/s, train/loss=2.280]\nEpoch 0: |          | 694/? [02:02<00:00,  5.65it/s, train/loss=23.20]\nEpoch 0: |          | 695/? [02:02<00:00,  5.66it/s, train/loss=23.20]\nEpoch 0: |          | 695/? [02:02<00:00,  5.66it/s, train/loss=2.250]\nEpoch 0: |          | 696/? [02:03<00:00,  5.65it/s, train/loss=2.250]\nEpoch 0: |          | 696/? [02:03<00:00,  5.65it/s, train/loss=40.20]\nEpoch 0: |          | 697/? [02:03<00:00,  5.66it/s, train/loss=40.20]\nEpoch 0: |          | 697/? [02:03<00:00,  5.66it/s, train/loss=2.170]\nEpoch 0: |          | 698/? [02:03<00:00,  5.66it/s, train/loss=2.170]\nEpoch 0: |          | 698/? [02:03<00:00,  5.66it/s, train/loss=16.40]\nEpoch 0: |          | 699/? [02:03<00:00,  5.66it/s, train/loss=16.40]\nEpoch 0: |          | 699/? [02:03<00:00,  5.66it/s, train/loss=2.140]\nEpoch 0: |          | 700/? [02:03<00:00,  5.66it/s, train/loss=2.140]\nEpoch 0: |          | 700/? [02:03<00:00,  5.66it/s, train/loss=13.90]\nEpoch 0: |          | 701/? [02:03<00:00,  5.66it/s, train/loss=13.90]\nEpoch 0: |          | 701/? [02:03<00:00,  5.66it/s, train/loss=2.160]\nEpoch 0: |          | 702/? [02:04<00:00,  5.66it/s, train/loss=2.160]\nEpoch 0: |          | 702/? [02:04<00:00,  5.66it/s, train/loss=18.10]\nEpoch 0: |          | 703/? [02:04<00:00,  5.67it/s, train/loss=18.10]\nEpoch 0: |          | 703/? [02:04<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 704/? [02:04<00:00,  5.66it/s, train/loss=2.180]\nEpoch 0: |          | 704/? [02:04<00:00,  5.66it/s, train/loss=23.20]\nEpoch 0: |          | 705/? [02:04<00:00,  5.67it/s, train/loss=23.20]\nEpoch 0: |          | 705/? [02:04<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 706/? [02:04<00:00,  5.66it/s, train/loss=2.180]\nEpoch 0: |          | 706/? [02:04<00:00,  5.66it/s, train/loss=31.30]\nEpoch 0: |          | 707/? [02:04<00:00,  5.67it/s, train/loss=31.30]\nEpoch 0: |          | 707/? [02:04<00:00,  5.67it/s, train/loss=2.160]\nEpoch 0: |          | 708/? [02:04<00:00,  5.66it/s, train/loss=2.160]\nEpoch 0: |          | 708/? [02:04<00:00,  5.66it/s, train/loss=19.40]\nEpoch 0: |          | 709/? [02:05<00:00,  5.67it/s, train/loss=19.40]\nEpoch 0: |          | 709/? [02:05<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 710/? [02:05<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 710/? [02:05<00:00,  5.67it/s, train/loss=31.20]\nEpoch 0: |          | 711/? [02:05<00:00,  5.67it/s, train/loss=31.20]\nEpoch 0: |          | 711/? [02:05<00:00,  5.67it/s, train/loss=2.220]\nEpoch 0: |          | 712/? [02:05<00:00,  5.67it/s, train/loss=2.220]\nEpoch 0: |          | 712/? [02:05<00:00,  5.67it/s, train/loss=46.40]\nEpoch 0: |          | 713/? [02:05<00:00,  5.67it/s, train/loss=46.40]\nEpoch 0: |          | 713/? [02:05<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 714/? [02:06<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 714/? [02:06<00:00,  5.67it/s, train/loss=31.40]\nEpoch 0: |          | 715/? [02:06<00:00,  5.67it/s, train/loss=31.40]\nEpoch 0: |          | 715/? [02:06<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 716/? [02:06<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 716/? [02:06<00:00,  5.67it/s, train/loss=35.10]\nEpoch 0: |          | 717/? [02:06<00:00,  5.67it/s, train/loss=35.10]\nEpoch 0: |          | 717/? [02:06<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 718/? [02:06<00:00,  5.67it/s, train/loss=2.200]\nEpoch 0: |          | 718/? [02:06<00:00,  5.67it/s, train/loss=23.40]\nEpoch 0: |          | 719/? [02:06<00:00,  5.67it/s, train/loss=23.40]\nEpoch 0: |          | 719/? [02:06<00:00,  5.67it/s, train/loss=2.210]\nEpoch 0: |          | 720/? [02:07<00:00,  5.67it/s, train/loss=2.210]\nEpoch 0: |          | 720/? [02:07<00:00,  5.67it/s, train/loss=16.20]\nEpoch 0: |          | 721/? [02:07<00:00,  5.67it/s, train/loss=16.20]\nEpoch 0: |          | 721/? [02:07<00:00,  5.67it/s, train/loss=2.210]\nEpoch 0: |          | 722/? [02:07<00:00,  5.67it/s, train/loss=2.210]\nEpoch 0: |          | 722/? [02:07<00:00,  5.67it/s, train/loss=22.00]\nEpoch 0: |          | 723/? [02:07<00:00,  5.67it/s, train/loss=22.00]\nEpoch 0: |          | 723/? [02:07<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 724/? [02:07<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 724/? [02:07<00:00,  5.67it/s, train/loss=50.60]\nEpoch 0: |          | 725/? [02:07<00:00,  5.68it/s, train/loss=50.60]\nEpoch 0: |          | 725/? [02:07<00:00,  5.68it/s, train/loss=2.160]\nEpoch 0: |          | 726/? [02:08<00:00,  5.67it/s, train/loss=2.160]\nEpoch 0: |          | 726/? [02:08<00:00,  5.67it/s, train/loss=44.00]\nEpoch 0: |          | 727/? [02:08<00:00,  5.68it/s, train/loss=44.00]\nEpoch 0: |          | 727/? [02:08<00:00,  5.68it/s, train/loss=2.180]\nEpoch 0: |          | 728/? [02:08<00:00,  5.67it/s, train/loss=2.180]\nEpoch 0: |          | 728/? [02:08<00:00,  5.67it/s, train/loss=33.60]\nEpoch 0: |          | 729/? [02:08<00:00,  5.68it/s, train/loss=33.60]\nEpoch 0: |          | 729/? [02:08<00:00,  5.68it/s, train/loss=2.210]\nEpoch 0: |          | 730/? [02:08<00:00,  5.67it/s, train/loss=2.210]\nEpoch 0: |          | 730/? [02:08<00:00,  5.67it/s, train/loss=20.70]\nEpoch 0: |          | 731/? [02:08<00:00,  5.68it/s, train/loss=20.70]\nEpoch 0: |          | 731/? [02:08<00:00,  5.68it/s, train/loss=2.210]\nEpoch 0: |          | 732/? [02:08<00:00,  5.68it/s, train/loss=2.210]\nEpoch 0: |          | 732/? [02:08<00:00,  5.68it/s, train/loss=19.10]\nEpoch 0: |          | 733/? [02:09<00:00,  5.68it/s, train/loss=19.10]\nEpoch 0: |          | 733/? [02:09<00:00,  5.68it/s, train/loss=2.180]\nEpoch 0: |          | 734/? [02:09<00:00,  5.68it/s, train/loss=2.180]\nEpoch 0: |          | 734/? [02:09<00:00,  5.68it/s, train/loss=17.30]\nEpoch 0: |          | 735/? [02:09<00:00,  5.68it/s, train/loss=17.30]\nEpoch 0: |          | 735/? [02:09<00:00,  5.68it/s, train/loss=2.130]\nEpoch 0: |          | 736/? [02:09<00:00,  5.68it/s, train/loss=2.130]\nEpoch 0: |          | 736/? [02:09<00:00,  5.68it/s, train/loss=32.90]\nEpoch 0: |          | 737/? [02:09<00:00,  5.68it/s, train/loss=32.90]\nEpoch 0: |          | 737/? [02:09<00:00,  5.68it/s, train/loss=2.070]\nEpoch 0: |          | 738/? [02:09<00:00,  5.68it/s, train/loss=2.070]\nEpoch 0: |          | 738/? [02:09<00:00,  5.68it/s, train/loss=25.10]\nEpoch 0: |          | 739/? [02:09<00:00,  5.69it/s, train/loss=25.10]\nEpoch 0: |          | 739/? [02:09<00:00,  5.69it/s, train/loss=2.010]\nEpoch 0: |          | 740/? [02:10<00:00,  5.68it/s, train/loss=2.010]\nEpoch 0: |          | 740/? [02:10<00:00,  5.68it/s, train/loss=26.20]\nEpoch 0: |          | 741/? [02:10<00:00,  5.69it/s, train/loss=26.20]\nEpoch 0: |          | 741/? [02:10<00:00,  5.69it/s, train/loss=1.970]\nEpoch 0: |          | 742/? [02:10<00:00,  5.68it/s, train/loss=1.970]\nEpoch 0: |          | 742/? [02:10<00:00,  5.68it/s, train/loss=38.50]\nEpoch 0: |          | 743/? [02:10<00:00,  5.69it/s, train/loss=38.50]\nEpoch 0: |          | 743/? [02:10<00:00,  5.69it/s, train/loss=1.960]\nEpoch 0: |          | 744/? [02:10<00:00,  5.68it/s, train/loss=1.960]\nEpoch 0: |          | 744/? [02:10<00:00,  5.68it/s, train/loss=26.20]\nEpoch 0: |          | 745/? [02:10<00:00,  5.69it/s, train/loss=26.20]\nEpoch 0: |          | 745/? [02:10<00:00,  5.69it/s, train/loss=1.960]\nEpoch 0: |          | 746/? [02:11<00:00,  5.68it/s, train/loss=1.960]\nEpoch 0: |          | 746/? [02:11<00:00,  5.68it/s, train/loss=29.00]\nEpoch 0: |          | 747/? [02:11<00:00,  5.69it/s, train/loss=29.00]\nEpoch 0: |          | 747/? [02:11<00:00,  5.69it/s, train/loss=1.990]\nEpoch 0: |          | 748/? [02:11<00:00,  5.69it/s, train/loss=1.990]\nEpoch 0: |          | 748/? [02:11<00:00,  5.69it/s, train/loss=15.30]\nEpoch 0: |          | 749/? [02:11<00:00,  5.69it/s, train/loss=15.30]\nEpoch 0: |          | 749/? [02:11<00:00,  5.69it/s, train/loss=2.030]\nEpoch 0: |          | 750/? [02:11<00:00,  5.69it/s, train/loss=2.030]\nEpoch 0: |          | 750/? [02:11<00:00,  5.69it/s, train/loss=52.50]\nEpoch 0: |          | 751/? [02:11<00:00,  5.69it/s, train/loss=52.50]\nEpoch 0: |          | 751/? [02:11<00:00,  5.69it/s, train/loss=2.080]\nEpoch 0: |          | 752/? [02:12<00:00,  5.69it/s, train/loss=2.080]\nEpoch 0: |          | 752/? [02:12<00:00,  5.69it/s, train/loss=38.80]\nEpoch 0: |          | 753/? [02:12<00:00,  5.69it/s, train/loss=38.80]\nEpoch 0: |          | 753/? [02:12<00:00,  5.69it/s, train/loss=2.160]\nEpoch 0: |          | 754/? [02:12<00:00,  5.69it/s, train/loss=2.160]\nEpoch 0: |          | 754/? [02:12<00:00,  5.69it/s, train/loss=16.20]\nEpoch 0: |          | 755/? [02:12<00:00,  5.70it/s, train/loss=16.20]\nEpoch 0: |          | 755/? [02:12<00:00,  5.69it/s, train/loss=2.220]\nEpoch 0: |          | 756/? [02:12<00:00,  5.69it/s, train/loss=2.220]\nEpoch 0: |          | 756/? [02:12<00:00,  5.69it/s, train/loss=35.80]\nEpoch 0: |          | 757/? [02:12<00:00,  5.70it/s, train/loss=35.80]\nEpoch 0: |          | 757/? [02:12<00:00,  5.70it/s, train/loss=2.240]\nEpoch 0: |          | 758/? [02:13<00:00,  5.69it/s, train/loss=2.240]\nEpoch 0: |          | 758/? [02:13<00:00,  5.69it/s, train/loss=64.60]\nEpoch 0: |          | 759/? [02:13<00:00,  5.70it/s, train/loss=64.60]\nEpoch 0: |          | 759/? [02:13<00:00,  5.70it/s, train/loss=2.280]\nEpoch 0: |          | 760/? [02:13<00:00,  5.69it/s, train/loss=2.280]\nEpoch 0: |          | 760/? [02:13<00:00,  5.69it/s, train/loss=38.20]\nEpoch 0: |          | 761/? [02:13<00:00,  5.70it/s, train/loss=38.20]\nEpoch 0: |          | 761/? [02:13<00:00,  5.70it/s, train/loss=2.400]\nEpoch 0: |          | 762/? [02:13<00:00,  5.69it/s, train/loss=2.400]\nEpoch 0: |          | 762/? [02:13<00:00,  5.69it/s, train/loss=23.40]\nEpoch 0: |          | 763/? [02:13<00:00,  5.70it/s, train/loss=23.40]\nEpoch 0: |          | 763/? [02:13<00:00,  5.70it/s, train/loss=2.530]\nEpoch 0: |          | 764/? [02:14<00:00,  5.70it/s, train/loss=2.530]\nEpoch 0: |          | 764/? [02:14<00:00,  5.70it/s, train/loss=37.80]\nEpoch 0: |          | 765/? [02:14<00:00,  5.70it/s, train/loss=37.80]\nEpoch 0: |          | 765/? [02:14<00:00,  5.70it/s, train/loss=2.580]\nEpoch 0: |          | 766/? [02:14<00:00,  5.70it/s, train/loss=2.580]\nEpoch 0: |          | 766/? [02:14<00:00,  5.70it/s, train/loss=9.400]\nEpoch 0: |          | 767/? [02:14<00:00,  5.70it/s, train/loss=9.400]\nEpoch 0: |          | 767/? [02:14<00:00,  5.70it/s, train/loss=2.530]\nEpoch 0: |          | 768/? [02:14<00:00,  5.70it/s, train/loss=2.530]\nEpoch 0: |          | 768/? [02:14<00:00,  5.70it/s, train/loss=17.00]\nEpoch 0: |          | 769/? [02:14<00:00,  5.70it/s, train/loss=17.00]\nEpoch 0: |          | 769/? [02:14<00:00,  5.70it/s, train/loss=2.400]\nEpoch 0: |          | 770/? [02:15<00:00,  5.70it/s, train/loss=2.400]\nEpoch 0: |          | 770/? [02:15<00:00,  5.70it/s, train/loss=17.40]\nEpoch 0: |          | 771/? [02:15<00:00,  5.70it/s, train/loss=17.40]\nEpoch 0: |          | 771/? [02:15<00:00,  5.70it/s, train/loss=2.240]\nEpoch 0: |          | 772/? [02:15<00:00,  5.70it/s, train/loss=2.240]\nEpoch 0: |          | 772/? [02:15<00:00,  5.70it/s, train/loss=43.20]\nEpoch 0: |          | 773/? [02:15<00:00,  5.71it/s, train/loss=43.20]\nEpoch 0: |          | 773/? [02:15<00:00,  5.71it/s, train/loss=2.160]\nEpoch 0: |          | 774/? [02:15<00:00,  5.70it/s, train/loss=2.160]\nEpoch 0: |          | 774/? [02:15<00:00,  5.70it/s, train/loss=21.60]\nEpoch 0: |          | 775/? [02:15<00:00,  5.71it/s, train/loss=21.60]\nEpoch 0: |          | 775/? [02:15<00:00,  5.71it/s, train/loss=2.140]\nEpoch 0: |          | 776/? [02:16<00:00,  5.70it/s, train/loss=2.140]\nEpoch 0: |          | 776/? [02:16<00:00,  5.70it/s, train/loss=20.60]\nEpoch 0: |          | 777/? [02:16<00:00,  5.71it/s, train/loss=20.60]\nEpoch 0: |          | 777/? [02:16<00:00,  5.71it/s, train/loss=2.150]\nEpoch 0: |          | 778/? [02:16<00:00,  5.70it/s, train/loss=2.150]\nEpoch 0: |          | 778/? [02:16<00:00,  5.70it/s, train/loss=14.50]\nEpoch 0: |          | 779/? [02:16<00:00,  5.71it/s, train/loss=14.50]\nEpoch 0: |          | 779/? [02:16<00:00,  5.71it/s, train/loss=2.200]\nEpoch 0: |          | 780/? [02:16<00:00,  5.70it/s, train/loss=2.200]\nEpoch 0: |          | 780/? [02:16<00:00,  5.70it/s, train/loss=29.70]\nEpoch 0: |          | 781/? [02:16<00:00,  5.71it/s, train/loss=29.70]\nEpoch 0: |          | 781/? [02:16<00:00,  5.71it/s, train/loss=2.210]\nEpoch 0: |          | 782/? [02:17<00:00,  5.71it/s, train/loss=2.210]\nEpoch 0: |          | 782/? [02:17<00:00,  5.71it/s, train/loss=6.770]\nEpoch 0: |          | 783/? [02:17<00:00,  5.71it/s, train/loss=6.770]\nEpoch 0: |          | 783/? [02:17<00:00,  5.71it/s, train/loss=2.180]\nEpoch 0: |          | 784/? [02:17<00:00,  5.71it/s, train/loss=2.180]\nEpoch 0: |          | 784/? [02:17<00:00,  5.71it/s, train/loss=51.80]\nEpoch 0: |          | 785/? [02:17<00:00,  5.71it/s, train/loss=51.80]\nEpoch 0: |          | 785/? [02:17<00:00,  5.71it/s, train/loss=2.120]\nEpoch 0: |          | 786/? [02:17<00:00,  5.71it/s, train/loss=2.120]\nEpoch 0: |          | 786/? [02:17<00:00,  5.71it/s, train/loss=13.10]\nEpoch 0: |          | 787/? [02:17<00:00,  5.71it/s, train/loss=13.10]\nEpoch 0: |          | 787/? [02:17<00:00,  5.71it/s, train/loss=2.060]\nEpoch 0: |          | 788/? [02:18<00:00,  5.71it/s, train/loss=2.060]\nEpoch 0: |          | 788/? [02:18<00:00,  5.71it/s, train/loss=31.40]\nEpoch 0: |          | 789/? [02:18<00:00,  5.71it/s, train/loss=31.40]\nEpoch 0: |          | 789/? [02:18<00:00,  5.71it/s, train/loss=2.040]\nEpoch 0: |          | 790/? [02:18<00:00,  5.71it/s, train/loss=2.040]\nEpoch 0: |          | 790/? [02:18<00:00,  5.71it/s, train/loss=18.20]\nEpoch 0: |          | 791/? [02:18<00:00,  5.71it/s, train/loss=18.20]\nEpoch 0: |          | 791/? [02:18<00:00,  5.71it/s, train/loss=2.020]\nEpoch 0: |          | 792/? [02:18<00:00,  5.71it/s, train/loss=2.020]\nEpoch 0: |          | 792/? [02:18<00:00,  5.71it/s, train/loss=19.10]\nEpoch 0: |          | 793/? [02:18<00:00,  5.72it/s, train/loss=19.10]\nEpoch 0: |          | 793/? [02:18<00:00,  5.72it/s, train/loss=2.000]\nEpoch 0: |          | 794/? [02:19<00:00,  5.71it/s, train/loss=2.000]\nEpoch 0: |          | 794/? [02:19<00:00,  5.71it/s, train/loss=11.40]\nEpoch 0: |          | 795/? [02:19<00:00,  5.72it/s, train/loss=11.40]\nEpoch 0: |          | 795/? [02:19<00:00,  5.72it/s, train/loss=1.990]\nEpoch 0: |          | 796/? [02:19<00:00,  5.71it/s, train/loss=1.990]\nEpoch 0: |          | 796/? [02:19<00:00,  5.71it/s, train/loss=21.00]\nEpoch 0: |          | 797/? [02:19<00:00,  5.72it/s, train/loss=21.00]\nEpoch 0: |          | 797/? [02:19<00:00,  5.72it/s, train/loss=1.990]\nEpoch 0: |          | 798/? [02:19<00:00,  5.71it/s, train/loss=1.990]\nEpoch 0: |          | 798/? [02:19<00:00,  5.71it/s, train/loss=19.80]\nEpoch 0: |          | 799/? [02:19<00:00,  5.72it/s, train/loss=19.80]\nEpoch 0: |          | 799/? [02:19<00:00,  5.72it/s, train/loss=1.960]\nEpoch 0: |          | 800/? [02:20<00:00,  5.71it/s, train/loss=1.960]\nEpoch 0: |          | 800/? [02:20<00:00,  5.71it/s, train/loss=19.80]\nValidation: |          | 0/? 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[02:21<00:00,  5.65it/s, train/loss=19.80]\n`Trainer.fit` stopped: `max_steps=800` reached.\nEpoch 0: |          | 800/? [02:21<00:00,  5.65it/s, train/loss=19.80]\nEpoch 0: |          | 800/? [02:21<00:00,  5.64it/s, train/loss=19.80]\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])\n[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\nTesting: |          | 0/? 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outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save\nRunning step 2: NeuS\n{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},\n'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 128, 'width': 128, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': 128, 'width': 128, 'batch_size': 1, 'eval_height': 256, 'eval_width': 256, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},\n'data_type': 'dreamcraft3d-single-image-datamodule',\n'description': '',\n'exp_dir': 'outputs/dreamcraft3d-coarse-neus',\n'exp_root_dir': 'outputs',\n'n_gpus': 1,\n'name': 'dreamcraft3d-coarse-neus',\n'resume': None,\n'seed': 0,\n'system': {'stage': 'coarse', 'geometry_type': 'implicit-sdf', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'sdf_bias': 'sphere', 'sdf_bias_params': 0.5, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'neus-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'cos_anneal_end_steps': 800, 'eval_chunk_size': 8192}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_orient': 10.0, 'lambda_sparsity': 0.1, 'lambda_opaque': 0.1, 'lambda_clip': 0.0, 'lambda_eikonal': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'betas': [0.9, 0.99], 'eps': 1e-15}, 'params': {'geometry.encoding': {'lr': 0.01}, 'geometry.sdf_network': {'lr': 0.001}, 'geometry.feature_network': {'lr': 0.001}, 'renderer': {'lr': 0.001}}}, 'weights': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/ckpts/last.ckpt'},\n'system_type': 'dreamcraft3d-system',\n'tag': 'replicate_user',\n'timestamp': '@20240222-134422',\n'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},\n'trial_dir': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422',\n'trial_name': 'replicate_user@20240222-134422',\n'use_timestamp': True}\nLoading Deep Floyd ...\nCouldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74fb6-298d8d076e9d29f944cbc198;0e1233af-4a94-4850-a984-d00aa82f1e06)\nCannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.\nRepo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..\nWill try to load from local cache.\nLoading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]\nLoading pipeline components...:  33%|███▎      | 1/3 [00:00<00:00,  4.81it/s]\nLoading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 12.46it/s]\nLoaded Deep Floyd!\nLoading Stable Zero123 ...\nget obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion\nLatentDiffusion: Running in eps-prediction mode\nDiffusionWrapper has 859.53 M params.\nKeeping EMAs of 688.\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\nLoaded Stable Zero123!\nUsing prompt [A green leafy plant in a striped terracotta pot] and negative prompt []\nUsing view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]\nloaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth\nUsing 16bit Automatic Mixed Precision (AMP)\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])\n[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])\n[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n| Name       | Type                 | Params\n----------------------------------------------------\n0 | geometry   | ImplicitSDF          | 12.6 M\n1 | material   | NoMaterial           | 0\n2 | background | SolidColorBackground | 0\n3 | renderer   | NeuSVolumeRenderer   | 1\n----------------------------------------------------\n12.6 M    Trainable params\n0         Non-trainable params\n12.6 M    Total params\n50.417    Total estimated model params size (MB)\nValidation results will be saved to outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save\nTraining: |          | 0/? [00:00<?, ?it/s]\nTraining: |          | 0/? [00:00<?, ?it/s]\nEpoch 0: |          | 0/? [00:00<?, ?it/s] \nEpoch 0: |          | 1/? [00:00<00:00,  8.63it/s]\nEpoch 0: |          | 1/? [00:00<00:00,  8.58it/s, train/loss=82.50]\nEpoch 0: |          | 2/? [00:00<00:00,  4.07it/s, train/loss=82.50]\nEpoch 0: |          | 2/? [00:00<00:00,  4.07it/s, train/loss=13.30]\nEpoch 0: |          | 3/? [00:00<00:00,  5.11it/s, train/loss=13.30]\nEpoch 0: |          | 3/? [00:00<00:00,  5.10it/s, train/loss=70.40]\nEpoch 0: |          | 4/? [00:00<00:00,  4.22it/s, train/loss=70.40]\nEpoch 0: |          | 4/? [00:00<00:00,  4.21it/s, train/loss=15.60]\nEpoch 0: |          | 5/? [00:01<00:00,  4.76it/s, train/loss=15.60]\nEpoch 0: |          | 5/? [00:01<00:00,  4.75it/s, train/loss=61.30]\nEpoch 0: |          | 6/? [00:01<00:00,  4.18it/s, train/loss=61.30]\nEpoch 0: |          | 6/? [00:01<00:00,  4.17it/s, train/loss=14.90]\nEpoch 0: |          | 7/? [00:01<00:00,  4.39it/s, train/loss=14.90]\nEpoch 0: |          | 7/? [00:01<00:00,  4.38it/s, train/loss=53.20]\nEpoch 0: |          | 8/? [00:02<00:00,  3.95it/s, train/loss=53.20]\nEpoch 0: |          | 8/? [00:02<00:00,  3.95it/s, train/loss=29.60]\nEpoch 0: |          | 9/? [00:02<00:00,  4.12it/s, train/loss=29.60]\nEpoch 0: |          | 9/? [00:02<00:00,  4.12it/s, train/loss=45.60]\nEpoch 0: |          | 10/? [00:02<00:00,  3.83it/s, train/loss=45.60]\nEpoch 0: |          | 10/? [00:02<00:00,  3.83it/s, train/loss=42.30]\nEpoch 0: |          | 11/? [00:02<00:00,  3.97it/s, train/loss=42.30]\nEpoch 0: |          | 11/? [00:02<00:00,  3.97it/s, train/loss=39.00]\nEpoch 0: |          | 12/? [00:03<00:00,  3.77it/s, train/loss=39.00]\nEpoch 0: |          | 12/? [00:03<00:00,  3.77it/s, train/loss=23.80]\nEpoch 0: |          | 13/? [00:03<00:00,  3.88it/s, train/loss=23.80]\nEpoch 0: |          | 13/? [00:03<00:00,  3.88it/s, train/loss=33.10]\nEpoch 0: |          | 14/? [00:03<00:00,  3.70it/s, train/loss=33.10]\nEpoch 0: |          | 14/? [00:03<00:00,  3.70it/s, train/loss=28.80]\nEpoch 0: |          | 15/? [00:03<00:00,  3.88it/s, train/loss=28.80]\nEpoch 0: |          | 15/? [00:03<00:00,  3.88it/s, train/loss=28.20]\nEpoch 0: |          | 16/? [00:04<00:00,  3.81it/s, train/loss=28.20]\nEpoch 0: |          | 16/? [00:04<00:00,  3.81it/s, train/loss=52.40]\nEpoch 0: |          | 17/? [00:04<00:00,  3.97it/s, train/loss=52.40]\nEpoch 0: |          | 17/? [00:04<00:00,  3.97it/s, train/loss=24.40]\nEpoch 0: |          | 18/? [00:04<00:00,  3.90it/s, train/loss=24.40]\nEpoch 0: |          | 18/? [00:04<00:00,  3.90it/s, train/loss=14.60]\nEpoch 0: |          | 19/? [00:04<00:00,  4.05it/s, train/loss=14.60]\nEpoch 0: |          | 19/? [00:04<00:00,  4.04it/s, train/loss=21.40]\nEpoch 0: |          | 20/? [00:05<00:00,  3.98it/s, train/loss=21.40]\nEpoch 0: |          | 20/? [00:05<00:00,  3.98it/s, train/loss=11.20]\nEpoch 0: |          | 21/? [00:05<00:00,  4.11it/s, train/loss=11.20]\nEpoch 0: |          | 21/? [00:05<00:00,  4.11it/s, train/loss=19.20]\nEpoch 0: |          | 22/? [00:05<00:00,  4.05it/s, train/loss=19.20]\nEpoch 0: |          | 22/? [00:05<00:00,  4.05it/s, train/loss=45.90]\nEpoch 0: |          | 23/? [00:05<00:00,  4.18it/s, train/loss=45.90]\nEpoch 0: |          | 23/? [00:05<00:00,  4.18it/s, train/loss=17.60]\nEpoch 0: |          | 24/? [00:05<00:00,  4.12it/s, train/loss=17.60]\nEpoch 0: |          | 24/? [00:05<00:00,  4.12it/s, train/loss=15.40]\nEpoch 0: |          | 25/? [00:05<00:00,  4.24it/s, train/loss=15.40]\nEpoch 0: |          | 25/? [00:05<00:00,  4.24it/s, train/loss=16.30]\nEpoch 0: |          | 26/? [00:06<00:00,  4.18it/s, train/loss=16.30]\nEpoch 0: |          | 26/? [00:06<00:00,  4.18it/s, train/loss=29.90]\nEpoch 0: |          | 27/? [00:06<00:00,  4.30it/s, train/loss=29.90]\nEpoch 0: |          | 27/? [00:06<00:00,  4.30it/s, train/loss=15.40]\nEpoch 0: |          | 28/? [00:06<00:00,  4.24it/s, train/loss=15.40]\nEpoch 0: |          | 28/? [00:06<00:00,  4.24it/s, train/loss=13.20]\nEpoch 0: |          | 29/? [00:06<00:00,  4.36it/s, train/loss=13.20]\nEpoch 0: |          | 29/? [00:06<00:00,  4.36it/s, train/loss=14.50]\nEpoch 0: |          | 30/? [00:06<00:00,  4.30it/s, train/loss=14.50]\nEpoch 0: |          | 30/? [00:06<00:00,  4.30it/s, train/loss=6.360]\nEpoch 0: |          | 31/? [00:07<00:00,  4.41it/s, train/loss=6.360]\nEpoch 0: |          | 31/? [00:07<00:00,  4.41it/s, train/loss=13.70]\nEpoch 0: |          | 32/? [00:07<00:00,  4.36it/s, train/loss=13.70]\nEpoch 0: |          | 32/? [00:07<00:00,  4.36it/s, train/loss=14.30]\nEpoch 0: |          | 33/? [00:07<00:00,  4.41it/s, train/loss=14.30]\nEpoch 0: |          | 33/? [00:07<00:00,  4.41it/s, train/loss=13.00]\nEpoch 0: |          | 34/? [00:07<00:00,  4.36it/s, train/loss=13.00]\nEpoch 0: |          | 34/? [00:07<00:00,  4.36it/s, train/loss=12.60]\nEpoch 0: |          | 35/? [00:07<00:00,  4.46it/s, train/loss=12.60]\nEpoch 0: |          | 35/? [00:07<00:00,  4.45it/s, train/loss=12.40]\nEpoch 0: |          | 36/? [00:08<00:00,  4.41it/s, train/loss=12.40]\nEpoch 0: |          | 36/? [00:08<00:00,  4.41it/s, train/loss=16.80]\nEpoch 0: |          | 37/? [00:08<00:00,  4.50it/s, train/loss=16.80]\nEpoch 0: |          | 37/? [00:08<00:00,  4.50it/s, train/loss=11.90]\nEpoch 0: |          | 38/? [00:08<00:00,  4.45it/s, train/loss=11.90]\nEpoch 0: |          | 38/? [00:08<00:00,  4.45it/s, train/loss=52.20]\nEpoch 0: |          | 39/? [00:08<00:00,  4.54it/s, train/loss=52.20]\nEpoch 0: |          | 39/? [00:08<00:00,  4.54it/s, train/loss=11.30]\nEpoch 0: |          | 40/? [00:08<00:00,  4.50it/s, train/loss=11.30]\nEpoch 0: |          | 40/? [00:08<00:00,  4.49it/s, train/loss=16.60]\nEpoch 0: |          | 41/? [00:08<00:00,  4.58it/s, train/loss=16.60]\nEpoch 0: |          | 41/? [00:08<00:00,  4.58it/s, train/loss=10.90]\nEpoch 0: |          | 42/? [00:09<00:00,  4.54it/s, train/loss=10.90]\nEpoch 0: |          | 42/? [00:09<00:00,  4.54it/s, train/loss=24.50]\nEpoch 0: |          | 43/? [00:09<00:00,  4.61it/s, train/loss=24.50]\nEpoch 0: |          | 43/? [00:09<00:00,  4.61it/s, train/loss=10.50]\nEpoch 0: |          | 44/? [00:09<00:00,  4.57it/s, train/loss=10.50]\nEpoch 0: |          | 44/? [00:09<00:00,  4.57it/s, train/loss=35.50]\nEpoch 0: |          | 45/? [00:09<00:00,  4.65it/s, train/loss=35.50]\nEpoch 0: |          | 45/? [00:09<00:00,  4.65it/s, train/loss=10.10]\nEpoch 0: |          | 46/? [00:09<00:00,  4.61it/s, train/loss=10.10]\nEpoch 0: |          | 46/? [00:09<00:00,  4.61it/s, train/loss=26.20]\nEpoch 0: |          | 47/? [00:10<00:00,  4.68it/s, train/loss=26.20]\nEpoch 0: |          | 47/? [00:10<00:00,  4.68it/s, train/loss=9.790]\nEpoch 0: |          | 48/? [00:10<00:00,  4.64it/s, train/loss=9.790]\nEpoch 0: |          | 48/? [00:10<00:00,  4.64it/s, train/loss=14.20]\nEpoch 0: |          | 49/? [00:10<00:00,  4.72it/s, train/loss=14.20]\nEpoch 0: |          | 49/? [00:10<00:00,  4.72it/s, train/loss=9.460]\nEpoch 0: |          | 50/? [00:10<00:00,  4.68it/s, train/loss=9.460]\nEpoch 0: |          | 50/? [00:10<00:00,  4.68it/s, train/loss=31.70]\nEpoch 0: |          | 51/? [00:10<00:00,  4.75it/s, train/loss=31.70]\nEpoch 0: |          | 51/? [00:10<00:00,  4.75it/s, train/loss=9.160]\nEpoch 0: |          | 52/? [00:11<00:00,  4.71it/s, train/loss=9.160]\nEpoch 0: |          | 52/? [00:11<00:00,  4.71it/s, train/loss=24.50]\nEpoch 0: |          | 53/? [00:11<00:00,  4.78it/s, train/loss=24.50]\nEpoch 0: |          | 53/? [00:11<00:00,  4.78it/s, train/loss=8.860]\nEpoch 0: |          | 54/? [00:11<00:00,  4.74it/s, train/loss=8.860]\nEpoch 0: |          | 54/? [00:11<00:00,  4.74it/s, train/loss=22.90]\nEpoch 0: |          | 55/? [00:11<00:00,  4.81it/s, train/loss=22.90]\nEpoch 0: |          | 55/? [00:11<00:00,  4.81it/s, train/loss=8.610]\nEpoch 0: |          | 56/? [00:11<00:00,  4.77it/s, train/loss=8.610]\nEpoch 0: |          | 56/? [00:11<00:00,  4.77it/s, train/loss=50.00]\nEpoch 0: |          | 57/? [00:11<00:00,  4.83it/s, train/loss=50.00]\nEpoch 0: |          | 57/? [00:11<00:00,  4.83it/s, train/loss=8.320]\nEpoch 0: |          | 58/? [00:12<00:00,  4.79it/s, train/loss=8.320]\nEpoch 0: |          | 58/? [00:12<00:00,  4.79it/s, train/loss=10.20]\nEpoch 0: |          | 59/? [00:12<00:00,  4.86it/s, train/loss=10.20]\nEpoch 0: |          | 59/? [00:12<00:00,  4.86it/s, train/loss=8.120]\nEpoch 0: |          | 60/? [00:12<00:00,  4.82it/s, train/loss=8.120]\nEpoch 0: |          | 60/? [00:12<00:00,  4.82it/s, train/loss=25.00]\nEpoch 0: |          | 61/? [00:12<00:00,  4.88it/s, train/loss=25.00]\nEpoch 0: |          | 61/? [00:12<00:00,  4.88it/s, train/loss=7.890]\nEpoch 0: |          | 62/? [00:12<00:00,  4.85it/s, train/loss=7.890]\nEpoch 0: |          | 62/? [00:12<00:00,  4.85it/s, train/loss=39.10]\nEpoch 0: |          | 63/? [00:12<00:00,  4.91it/s, train/loss=39.10]\nEpoch 0: |          | 63/? [00:12<00:00,  4.91it/s, train/loss=7.680]\nEpoch 0: |          | 64/? [00:13<00:00,  4.87it/s, train/loss=7.680]\nEpoch 0: |          | 64/? [00:13<00:00,  4.87it/s, train/loss=19.80]\nEpoch 0: |          | 65/? [00:13<00:00,  4.93it/s, train/loss=19.80]\nEpoch 0: |          | 65/? [00:13<00:00,  4.93it/s, train/loss=7.520]\nEpoch 0: |          | 66/? [00:13<00:00,  4.89it/s, train/loss=7.520]\nEpoch 0: |          | 66/? [00:13<00:00,  4.89it/s, train/loss=25.30]\nEpoch 0: |          | 67/? [00:13<00:00,  4.95it/s, train/loss=25.30]\nEpoch 0: |          | 67/? [00:13<00:00,  4.95it/s, train/loss=7.340]\nEpoch 0: |          | 68/? [00:13<00:00,  4.92it/s, train/loss=7.340]\nEpoch 0: |          | 68/? [00:13<00:00,  4.92it/s, train/loss=26.40]\nEpoch 0: |          | 69/? [00:13<00:00,  4.97it/s, train/loss=26.40]\nEpoch 0: |          | 69/? [00:13<00:00,  4.97it/s, train/loss=7.160]\nEpoch 0: |          | 70/? [00:14<00:00,  4.94it/s, train/loss=7.160]\nEpoch 0: |          | 70/? [00:14<00:00,  4.94it/s, train/loss=28.30]\nEpoch 0: |          | 71/? [00:14<00:00,  4.99it/s, train/loss=28.30]\nEpoch 0: |          | 71/? [00:14<00:00,  4.99it/s, train/loss=6.960]\nEpoch 0: |          | 72/? [00:14<00:00,  4.96it/s, train/loss=6.960]\nEpoch 0: |          | 72/? [00:14<00:00,  4.96it/s, train/loss=19.70]\nEpoch 0: |          | 73/? [00:14<00:00,  5.01it/s, train/loss=19.70]\nEpoch 0: |          | 73/? [00:14<00:00,  5.01it/s, train/loss=6.810]\nEpoch 0: |          | 74/? [00:14<00:00,  4.98it/s, train/loss=6.810]\nEpoch 0: |          | 74/? [00:14<00:00,  4.98it/s, train/loss=25.40]\nEpoch 0: |          | 75/? [00:14<00:00,  5.03it/s, train/loss=25.40]\nEpoch 0: |          | 75/? [00:14<00:00,  5.03it/s, train/loss=6.630]\nEpoch 0: |          | 76/? [00:15<00:00,  5.00it/s, train/loss=6.630]\nEpoch 0: |          | 76/? [00:15<00:00,  5.00it/s, train/loss=38.60]\nEpoch 0: |          | 77/? [00:15<00:00,  5.05it/s, train/loss=38.60]\nEpoch 0: |          | 77/? [00:15<00:00,  5.05it/s, train/loss=6.480]\nEpoch 0: |          | 78/? [00:15<00:00,  5.02it/s, train/loss=6.480]\nEpoch 0: |          | 78/? [00:15<00:00,  5.02it/s, train/loss=13.70]\nEpoch 0: |          | 79/? [00:15<00:00,  5.07it/s, train/loss=13.70]\nEpoch 0: |          | 79/? [00:15<00:00,  5.07it/s, train/loss=6.330]\nEpoch 0: |          | 80/? [00:15<00:00,  5.04it/s, train/loss=6.330]\nEpoch 0: |          | 80/? [00:15<00:00,  5.03it/s, train/loss=32.80]\nEpoch 0: |          | 81/? [00:15<00:00,  5.08it/s, train/loss=32.80]\nEpoch 0: |          | 81/? [00:15<00:00,  5.08it/s, train/loss=6.160]\nEpoch 0: |          | 82/? [00:16<00:00,  5.05it/s, train/loss=6.160]\nEpoch 0: |          | 82/? [00:16<00:00,  5.05it/s, train/loss=79.20]\nEpoch 0: |          | 83/? [00:16<00:00,  5.10it/s, train/loss=79.20]\nEpoch 0: |          | 83/? [00:16<00:00,  5.10it/s, train/loss=6.010]\nEpoch 0: |          | 84/? [00:16<00:00,  5.07it/s, train/loss=6.010]\nEpoch 0: |          | 84/? [00:16<00:00,  5.07it/s, train/loss=9.970]\nEpoch 0: |          | 85/? [00:16<00:00,  5.11it/s, train/loss=9.970]\nEpoch 0: |          | 85/? [00:16<00:00,  5.11it/s, train/loss=6.020]\nEpoch 0: |          | 86/? [00:16<00:00,  5.08it/s, train/loss=6.020]\nEpoch 0: |          | 86/? [00:16<00:00,  5.08it/s, train/loss=9.380]\nEpoch 0: |          | 87/? [00:16<00:00,  5.13it/s, train/loss=9.380]\nEpoch 0: |          | 87/? [00:16<00:00,  5.13it/s, train/loss=5.970]\nEpoch 0: |          | 88/? [00:17<00:00,  5.10it/s, train/loss=5.970]\nEpoch 0: |          | 88/? [00:17<00:00,  5.10it/s, train/loss=43.40]\nEpoch 0: |          | 89/? [00:17<00:00,  5.14it/s, train/loss=43.40]\nEpoch 0: |          | 89/? [00:17<00:00,  5.14it/s, train/loss=5.850]\nEpoch 0: |          | 90/? [00:17<00:00,  5.11it/s, train/loss=5.850]\nEpoch 0: |          | 90/? [00:17<00:00,  5.11it/s, train/loss=31.80]\nEpoch 0: |          | 91/? [00:17<00:00,  5.16it/s, train/loss=31.80]\nEpoch 0: |          | 91/? [00:17<00:00,  5.16it/s, train/loss=5.750]\nEpoch 0: |          | 92/? [00:17<00:00,  5.13it/s, train/loss=5.750]\nEpoch 0: |          | 92/? [00:17<00:00,  5.13it/s, train/loss=30.60]\nEpoch 0: |          | 93/? [00:17<00:00,  5.17it/s, train/loss=30.60]\nEpoch 0: |          | 93/? [00:17<00:00,  5.17it/s, train/loss=5.680]\nEpoch 0: |          | 94/? [00:18<00:00,  5.14it/s, train/loss=5.680]\nEpoch 0: |          | 94/? [00:18<00:00,  5.14it/s, train/loss=7.830]\nEpoch 0: |          | 95/? [00:18<00:00,  5.18it/s, train/loss=7.830]\nEpoch 0: |          | 95/? [00:18<00:00,  5.18it/s, train/loss=5.570]\nEpoch 0: |          | 96/? [00:18<00:00,  5.16it/s, train/loss=5.570]\nEpoch 0: |          | 96/? [00:18<00:00,  5.16it/s, train/loss=74.70]\nEpoch 0: |          | 97/? [00:18<00:00,  5.20it/s, train/loss=74.70]\nEpoch 0: |          | 97/? [00:18<00:00,  5.20it/s, train/loss=5.550]\nEpoch 0: |          | 98/? [00:18<00:00,  5.17it/s, train/loss=5.550]\nEpoch 0: |          | 98/? [00:18<00:00,  5.17it/s, train/loss=28.10]\nEpoch 0: |          | 99/? [00:18<00:00,  5.21it/s, train/loss=28.10]\nEpoch 0: |          | 99/? [00:18<00:00,  5.21it/s, train/loss=5.500]\nEpoch 0: |          | 100/? [00:19<00:00,  5.18it/s, train/loss=5.500]\nEpoch 0: |          | 100/? [00:19<00:00,  5.18it/s, train/loss=26.30]\nEpoch 0: |          | 101/? [00:19<00:00,  5.22it/s, train/loss=26.30]\nEpoch 0: |          | 101/? [00:19<00:00,  5.22it/s, train/loss=5.460]\nEpoch 0: |          | 102/? [00:19<00:00,  5.20it/s, train/loss=5.460]\nEpoch 0: |          | 102/? [00:19<00:00,  5.20it/s, train/loss=18.60]\nEpoch 0: |          | 103/? [00:19<00:00,  5.24it/s, train/loss=18.60]\nEpoch 0: |          | 103/? [00:19<00:00,  5.24it/s, train/loss=5.390]\nEpoch 0: |          | 104/? [00:19<00:00,  5.21it/s, train/loss=5.390]\nEpoch 0: |          | 104/? [00:19<00:00,  5.21it/s, train/loss=35.60]\nEpoch 0: |          | 105/? [00:20<00:00,  5.25it/s, train/loss=35.60]\nEpoch 0: |          | 105/? [00:20<00:00,  5.25it/s, train/loss=5.390]\nEpoch 0: |          | 106/? [00:20<00:00,  5.22it/s, train/loss=5.390]\nEpoch 0: |          | 106/? [00:20<00:00,  5.22it/s, train/loss=27.10]\nEpoch 0: |          | 107/? [00:20<00:00,  5.26it/s, train/loss=27.10]\nEpoch 0: |          | 107/? [00:20<00:00,  5.26it/s, train/loss=5.360]\nEpoch 0: |          | 108/? [00:20<00:00,  5.23it/s, train/loss=5.360]\nEpoch 0: |          | 108/? [00:20<00:00,  5.23it/s, train/loss=19.40]\nEpoch 0: |          | 109/? [00:20<00:00,  5.27it/s, train/loss=19.40]\nEpoch 0: |          | 109/? [00:20<00:00,  5.27it/s, train/loss=5.320]\nEpoch 0: |          | 110/? [00:20<00:00,  5.24it/s, train/loss=5.320]\nEpoch 0: |          | 110/? [00:20<00:00,  5.24it/s, train/loss=11.00]\nEpoch 0: |          | 111/? [00:21<00:00,  5.28it/s, train/loss=11.00]\nEpoch 0: |          | 111/? [00:21<00:00,  5.28it/s, train/loss=5.210]\nEpoch 0: |          | 112/? [00:21<00:00,  5.25it/s, train/loss=5.210]\nEpoch 0: |          | 112/? [00:21<00:00,  5.25it/s, train/loss=31.30]\nEpoch 0: |          | 113/? [00:21<00:00,  5.29it/s, train/loss=31.30]\nEpoch 0: |          | 113/? [00:21<00:00,  5.29it/s, train/loss=5.080]\nEpoch 0: |          | 114/? [00:21<00:00,  5.27it/s, train/loss=5.080]\nEpoch 0: |          | 114/? [00:21<00:00,  5.26it/s, train/loss=13.40]\nEpoch 0: |          | 115/? [00:21<00:00,  5.30it/s, train/loss=13.40]\nEpoch 0: |          | 115/? [00:21<00:00,  5.30it/s, train/loss=5.000]\nEpoch 0: |          | 116/? [00:21<00:00,  5.28it/s, train/loss=5.000]\nEpoch 0: |          | 116/? [00:21<00:00,  5.28it/s, train/loss=21.70]\nEpoch 0: |          | 117/? [00:22<00:00,  5.31it/s, train/loss=21.70]\nEpoch 0: |          | 117/? [00:22<00:00,  5.31it/s, train/loss=4.900]\nEpoch 0: |          | 118/? [00:22<00:00,  5.29it/s, train/loss=4.900]\nEpoch 0: |          | 118/? [00:22<00:00,  5.29it/s, train/loss=29.80]\nEpoch 0: |          | 119/? [00:22<00:00,  5.32it/s, train/loss=29.80]\nEpoch 0: |          | 119/? [00:22<00:00,  5.32it/s, train/loss=4.820]\nEpoch 0: |          | 120/? [00:22<00:00,  5.30it/s, train/loss=4.820]\nEpoch 0: |          | 120/? [00:22<00:00,  5.30it/s, train/loss=16.00]\nEpoch 0: |          | 121/? [00:22<00:00,  5.33it/s, train/loss=16.00]\nEpoch 0: |          | 121/? [00:22<00:00,  5.33it/s, train/loss=4.760]\nEpoch 0: |          | 122/? [00:22<00:00,  5.31it/s, train/loss=4.760]\nEpoch 0: |          | 122/? [00:22<00:00,  5.31it/s, train/loss=9.140]\nEpoch 0: |          | 123/? [00:23<00:00,  5.34it/s, train/loss=9.140]\nEpoch 0: |          | 123/? [00:23<00:00,  5.34it/s, train/loss=4.590]\nEpoch 0: |          | 124/? [00:23<00:00,  5.31it/s, train/loss=4.590]\nEpoch 0: |          | 124/? [00:23<00:00,  5.31it/s, train/loss=15.00]\nEpoch 0: |          | 125/? [00:23<00:00,  5.35it/s, train/loss=15.00]\nEpoch 0: |          | 125/? [00:23<00:00,  5.35it/s, train/loss=4.540]\nEpoch 0: |          | 126/? [00:23<00:00,  5.33it/s, train/loss=4.540]\nEpoch 0: |          | 126/? [00:23<00:00,  5.32it/s, train/loss=29.10]\nEpoch 0: |          | 127/? [00:23<00:00,  5.36it/s, train/loss=29.10]\nEpoch 0: |          | 127/? [00:23<00:00,  5.36it/s, train/loss=4.470]\nEpoch 0: |          | 128/? [00:23<00:00,  5.33it/s, train/loss=4.470]\nEpoch 0: |          | 128/? [00:23<00:00,  5.33it/s, train/loss=14.60]\nEpoch 0: |          | 129/? [00:24<00:00,  5.37it/s, train/loss=14.60]\nEpoch 0: |          | 129/? [00:24<00:00,  5.37it/s, train/loss=4.440]\nEpoch 0: |          | 130/? [00:24<00:00,  5.34it/s, train/loss=4.440]\nEpoch 0: |          | 130/? [00:24<00:00,  5.34it/s, train/loss=53.50]\nEpoch 0: |          | 131/? [00:24<00:00,  5.38it/s, train/loss=53.50]\nEpoch 0: |          | 131/? [00:24<00:00,  5.38it/s, train/loss=4.370]\nEpoch 0: |          | 132/? [00:24<00:00,  5.35it/s, train/loss=4.370]\nEpoch 0: |          | 132/? [00:24<00:00,  5.35it/s, train/loss=21.30]\nEpoch 0: |          | 133/? [00:24<00:00,  5.39it/s, train/loss=21.30]\nEpoch 0: |          | 133/? [00:24<00:00,  5.38it/s, train/loss=4.300]\nEpoch 0: |          | 134/? [00:24<00:00,  5.36it/s, train/loss=4.300]\nEpoch 0: |          | 134/? [00:24<00:00,  5.36it/s, train/loss=41.60]\nEpoch 0: |          | 135/? [00:25<00:00,  5.39it/s, train/loss=41.60]\nEpoch 0: |          | 135/? [00:25<00:00,  5.39it/s, train/loss=4.300]\nEpoch 0: |          | 136/? [00:25<00:00,  5.37it/s, train/loss=4.300]\nEpoch 0: |          | 136/? [00:25<00:00,  5.37it/s, train/loss=56.40]\nEpoch 0: |          | 137/? [00:25<00:00,  5.40it/s, train/loss=56.40]\nEpoch 0: |          | 137/? [00:25<00:00,  5.40it/s, train/loss=4.250]\nEpoch 0: |          | 138/? [00:25<00:00,  5.38it/s, train/loss=4.250]\nEpoch 0: |          | 138/? [00:25<00:00,  5.38it/s, train/loss=27.90]\nEpoch 0: |          | 139/? [00:25<00:00,  5.41it/s, train/loss=27.90]\nEpoch 0: |          | 139/? [00:25<00:00,  5.41it/s, train/loss=4.200]\nEpoch 0: |          | 140/? [00:25<00:00,  5.39it/s, train/loss=4.200]\nEpoch 0: |          | 140/? [00:25<00:00,  5.39it/s, train/loss=23.60]\nEpoch 0: |          | 141/? [00:26<00:00,  5.42it/s, train/loss=23.60]\nEpoch 0: |          | 141/? [00:26<00:00,  5.42it/s, train/loss=4.210]\nEpoch 0: |          | 142/? [00:26<00:00,  5.39it/s, train/loss=4.210]\nEpoch 0: |          | 142/? [00:26<00:00,  5.39it/s, train/loss=34.30]\nEpoch 0: |          | 143/? [00:26<00:00,  5.42it/s, train/loss=34.30]\nEpoch 0: |          | 143/? [00:26<00:00,  5.42it/s, train/loss=4.270]\nEpoch 0: |          | 144/? [00:26<00:00,  5.40it/s, train/loss=4.270]\nEpoch 0: |          | 144/? [00:26<00:00,  5.40it/s, train/loss=11.00]\nEpoch 0: |          | 145/? [00:26<00:00,  5.43it/s, train/loss=11.00]\nEpoch 0: |          | 145/? [00:26<00:00,  5.43it/s, train/loss=4.260]\nEpoch 0: |          | 146/? [00:26<00:00,  5.41it/s, train/loss=4.260]\nEpoch 0: |          | 146/? [00:26<00:00,  5.41it/s, train/loss=16.60]\nEpoch 0: |          | 147/? [00:27<00:00,  5.44it/s, train/loss=16.60]\nEpoch 0: |          | 147/? [00:27<00:00,  5.44it/s, train/loss=4.250]\nEpoch 0: |          | 148/? [00:27<00:00,  5.42it/s, train/loss=4.250]\nEpoch 0: |          | 148/? [00:27<00:00,  5.42it/s, train/loss=56.10]\nEpoch 0: |          | 149/? [00:27<00:00,  5.45it/s, train/loss=56.10]\nEpoch 0: |          | 149/? [00:27<00:00,  5.45it/s, train/loss=4.270]\nEpoch 0: |          | 150/? [00:27<00:00,  5.43it/s, train/loss=4.270]\nEpoch 0: |          | 150/? [00:27<00:00,  5.43it/s, train/loss=17.70]\nEpoch 0: |          | 151/? [00:27<00:00,  5.46it/s, train/loss=17.70]\nEpoch 0: |          | 151/? [00:27<00:00,  5.46it/s, train/loss=4.270]\nEpoch 0: |          | 152/? [00:27<00:00,  5.44it/s, train/loss=4.270]\nEpoch 0: |          | 152/? [00:27<00:00,  5.44it/s, train/loss=29.20]\nEpoch 0: |          | 153/? [00:28<00:00,  5.46it/s, train/loss=29.20]\nEpoch 0: |          | 153/? [00:28<00:00,  5.46it/s, train/loss=4.220]\nEpoch 0: |          | 154/? [00:28<00:00,  5.44it/s, train/loss=4.220]\nEpoch 0: |          | 154/? [00:28<00:00,  5.44it/s, train/loss=24.70]\nEpoch 0: |          | 155/? [00:28<00:00,  5.47it/s, train/loss=24.70]\nEpoch 0: |          | 155/? [00:28<00:00,  5.47it/s, train/loss=4.170]\nEpoch 0: |          | 156/? [00:28<00:00,  5.45it/s, train/loss=4.170]\nEpoch 0: |          | 156/? [00:28<00:00,  5.45it/s, train/loss=32.10]\nEpoch 0: |          | 157/? [00:28<00:00,  5.48it/s, train/loss=32.10]\nEpoch 0: |          | 157/? [00:28<00:00,  5.48it/s, train/loss=4.130]\nEpoch 0: |          | 158/? [00:28<00:00,  5.46it/s, train/loss=4.130]\nEpoch 0: |          | 158/? [00:28<00:00,  5.46it/s, train/loss=50.40]\nEpoch 0: |          | 159/? [00:29<00:00,  5.47it/s, train/loss=50.40]\nEpoch 0: |          | 159/? [00:29<00:00,  5.47it/s, train/loss=4.160]\nEpoch 0: |          | 160/? [00:29<00:00,  5.45it/s, train/loss=4.160]\nEpoch 0: |          | 160/? [00:29<00:00,  5.45it/s, train/loss=39.00]\nEpoch 0: |          | 161/? [00:29<00:00,  5.47it/s, train/loss=39.00]\nEpoch 0: |          | 161/? [00:29<00:00,  5.47it/s, train/loss=4.080]\nEpoch 0: |          | 162/? [00:29<00:00,  5.45it/s, train/loss=4.080]\nEpoch 0: |          | 162/? [00:29<00:00,  5.45it/s, train/loss=23.90]\nEpoch 0: |          | 163/? [00:29<00:00,  5.48it/s, train/loss=23.90]\nEpoch 0: |          | 163/? [00:29<00:00,  5.48it/s, train/loss=4.140]\nEpoch 0: |          | 164/? [00:30<00:00,  5.46it/s, train/loss=4.140]\nEpoch 0: |          | 164/? [00:30<00:00,  5.46it/s, train/loss=20.70]\nEpoch 0: |          | 165/? [00:30<00:00,  5.48it/s, train/loss=20.70]\nEpoch 0: |          | 165/? [00:30<00:00,  5.48it/s, train/loss=3.990]\nEpoch 0: |          | 166/? [00:30<00:00,  5.46it/s, train/loss=3.990]\nEpoch 0: |          | 166/? [00:30<00:00,  5.46it/s, train/loss=46.60]\nEpoch 0: |          | 167/? [00:30<00:00,  5.49it/s, train/loss=46.60]\nEpoch 0: |          | 167/? [00:30<00:00,  5.49it/s, train/loss=4.030]\nEpoch 0: |          | 168/? [00:30<00:00,  5.47it/s, train/loss=4.030]\nEpoch 0: |          | 168/? [00:30<00:00,  5.47it/s, train/loss=31.20]\nEpoch 0: |          | 169/? [00:30<00:00,  5.50it/s, train/loss=31.20]\nEpoch 0: |          | 169/? [00:30<00:00,  5.50it/s, train/loss=3.920]\nEpoch 0: |          | 170/? [00:31<00:00,  5.48it/s, train/loss=3.920]\nEpoch 0: |          | 170/? [00:31<00:00,  5.48it/s, train/loss=24.30]\nEpoch 0: |          | 171/? [00:31<00:00,  5.49it/s, train/loss=24.30]\nEpoch 0: |          | 171/? [00:31<00:00,  5.49it/s, train/loss=3.860]\nEpoch 0: |          | 172/? [00:31<00:00,  5.47it/s, train/loss=3.860]\nEpoch 0: |          | 172/? [00:31<00:00,  5.47it/s, train/loss=48.80]\nEpoch 0: |          | 173/? [00:31<00:00,  5.49it/s, train/loss=48.80]\nEpoch 0: |          | 173/? [00:31<00:00,  5.49it/s, train/loss=3.870]\nEpoch 0: |          | 174/? [00:31<00:00,  5.45it/s, train/loss=3.870]\nEpoch 0: |          | 174/? [00:31<00:00,  5.45it/s, train/loss=29.00]\nEpoch 0: |          | 175/? [00:31<00:00,  5.47it/s, train/loss=29.00]\nEpoch 0: |          | 175/? [00:31<00:00,  5.47it/s, train/loss=3.860]\nEpoch 0: |          | 176/? [00:32<00:00,  5.45it/s, train/loss=3.860]\nEpoch 0: |          | 176/? [00:32<00:00,  5.45it/s, train/loss=28.10]\nEpoch 0: |          | 177/? [00:32<00:00,  5.47it/s, train/loss=28.10]\nEpoch 0: |          | 177/? [00:32<00:00,  5.47it/s, train/loss=3.830]\nEpoch 0: |          | 178/? [00:32<00:00,  5.45it/s, train/loss=3.830]\nEpoch 0: |          | 178/? [00:32<00:00,  5.45it/s, train/loss=29.80]\nEpoch 0: |          | 179/? [00:32<00:00,  5.48it/s, train/loss=29.80]\nEpoch 0: |          | 179/? [00:32<00:00,  5.48it/s, train/loss=3.810]\nEpoch 0: |          | 180/? [00:32<00:00,  5.46it/s, train/loss=3.810]\nEpoch 0: |          | 180/? [00:32<00:00,  5.46it/s, train/loss=22.60]\nEpoch 0: |          | 181/? [00:32<00:00,  5.49it/s, train/loss=22.60]\nEpoch 0: |          | 181/? [00:32<00:00,  5.49it/s, train/loss=3.810]\nEpoch 0: |          | 182/? [00:33<00:00,  5.47it/s, train/loss=3.810]\nEpoch 0: |          | 182/? [00:33<00:00,  5.47it/s, train/loss=17.40]\nEpoch 0: |          | 183/? [00:33<00:00,  5.49it/s, train/loss=17.40]\nEpoch 0: |          | 183/? [00:33<00:00,  5.49it/s, train/loss=3.830]\nEpoch 0: |          | 184/? [00:33<00:00,  5.47it/s, train/loss=3.830]\nEpoch 0: |          | 184/? [00:33<00:00,  5.47it/s, train/loss=26.80]\nEpoch 0: |          | 185/? [00:33<00:00,  5.50it/s, train/loss=26.80]\nEpoch 0: |          | 185/? [00:33<00:00,  5.50it/s, train/loss=3.770]\nEpoch 0: |          | 186/? [00:33<00:00,  5.48it/s, train/loss=3.770]\nEpoch 0: |          | 186/? [00:33<00:00,  5.48it/s, train/loss=24.20]\nEpoch 0: |          | 187/? [00:33<00:00,  5.51it/s, train/loss=24.20]\nEpoch 0: |          | 187/? [00:33<00:00,  5.51it/s, train/loss=3.750]\nEpoch 0: |          | 188/? [00:34<00:00,  5.49it/s, train/loss=3.750]\nEpoch 0: |          | 188/? [00:34<00:00,  5.49it/s, train/loss=24.00]\nEpoch 0: |          | 189/? [00:34<00:00,  5.51it/s, train/loss=24.00]\nEpoch 0: |          | 189/? [00:34<00:00,  5.51it/s, train/loss=3.690]\nEpoch 0: |          | 190/? [00:34<00:00,  5.50it/s, train/loss=3.690]\nEpoch 0: |          | 190/? [00:34<00:00,  5.50it/s, train/loss=21.50]\nEpoch 0: |          | 191/? [00:34<00:00,  5.52it/s, train/loss=21.50]\nEpoch 0: |          | 191/? [00:34<00:00,  5.52it/s, train/loss=3.680]\nEpoch 0: |          | 192/? [00:34<00:00,  5.50it/s, train/loss=3.680]\nEpoch 0: |          | 192/? [00:34<00:00,  5.50it/s, train/loss=36.10]\nEpoch 0: |          | 193/? [00:34<00:00,  5.53it/s, train/loss=36.10]\nEpoch 0: |          | 193/? [00:34<00:00,  5.52it/s, train/loss=3.640]\nEpoch 0: |          | 194/? [00:35<00:00,  5.51it/s, train/loss=3.640]\nEpoch 0: |          | 194/? [00:35<00:00,  5.51it/s, train/loss=13.30]\nEpoch 0: |          | 195/? [00:35<00:00,  5.53it/s, train/loss=13.30]\nEpoch 0: |          | 195/? [00:35<00:00,  5.53it/s, train/loss=3.600]\nEpoch 0: |          | 196/? [00:35<00:00,  5.51it/s, train/loss=3.600]\nEpoch 0: |          | 196/? [00:35<00:00,  5.51it/s, train/loss=33.60]\nEpoch 0: |          | 197/? [00:35<00:00,  5.53it/s, train/loss=33.60]\nEpoch 0: |          | 197/? [00:35<00:00,  5.52it/s, train/loss=3.520]\nEpoch 0: |          | 198/? [00:36<00:00,  5.50it/s, train/loss=3.520]\nEpoch 0: |          | 198/? [00:36<00:00,  5.50it/s, train/loss=35.50]\nEpoch 0: |          | 199/? [00:36<00:00,  5.51it/s, train/loss=35.50]\nEpoch 0: |          | 199/? [00:36<00:00,  5.51it/s, train/loss=3.470]\nEpoch 0: |          | 200/? [00:36<00:00,  5.48it/s, train/loss=3.470]\nEpoch 0: |          | 200/? [00:36<00:00,  5.48it/s, train/loss=14.60]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:10,  3.63it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:10,  3.65it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:10,  3.66it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:01<00:09,  3.65it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:01<00:09,  3.66it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:01<00:09,  3.66it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:01<00:08,  3.68it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:02<00:08,  3.67it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:02<00:08,  3.68it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:02<00:08,  3.68it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:02<00:07,  3.69it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:03<00:07,  3.69it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:03<00:07,  3.70it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:03<00:07,  3.70it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:04<00:06,  3.71it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:04<00:06,  3.71it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:04<00:06,  3.72it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:04<00:05,  3.72it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:05<00:05,  3.72it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:05<00:05,  3.73it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:05<00:05,  3.73it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:05<00:04,  3.73it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:06<00:04,  3.73it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:06<00:04,  3.73it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:06<00:04,  3.74it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:06<00:03,  3.74it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:07<00:03,  3.74it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:07<00:03,  3.75it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:07<00:02,  3.75it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:07<00:02,  3.75it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:08<00:02,  3.76it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:08<00:02,  3.76it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:08<00:01,  3.76it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:09<00:01,  3.77it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:09<00:01,  3.77it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:09<00:01,  3.78it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:09<00:00,  3.78it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:10<00:00,  3.79it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:10<00:00,  3.78it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:10<00:00,  3.78it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 200/? [00:47<00:00,  4.18it/s, train/loss=14.60]\nEpoch 0: |          | 201/? [00:48<00:00,  4.17it/s, train/loss=14.60]\nEpoch 0: |          | 201/? [00:48<00:00,  4.17it/s, train/loss=3.450]\nEpoch 0: |          | 202/? [00:48<00:00,  4.16it/s, train/loss=3.450]\nEpoch 0: |          | 202/? [00:48<00:00,  4.16it/s, train/loss=29.70]\nEpoch 0: |          | 203/? [00:48<00:00,  4.17it/s, train/loss=29.70]\nEpoch 0: |          | 203/? [00:48<00:00,  4.17it/s, train/loss=3.370]\nEpoch 0: |          | 204/? [00:49<00:00,  4.16it/s, train/loss=3.370]\nEpoch 0: |          | 204/? [00:49<00:00,  4.16it/s, train/loss=36.30]\nEpoch 0: |          | 205/? [00:49<00:00,  4.17it/s, train/loss=36.30]\nEpoch 0: |          | 205/? [00:49<00:00,  4.17it/s, train/loss=3.240]\nEpoch 0: |          | 206/? [00:49<00:00,  4.17it/s, train/loss=3.240]\nEpoch 0: |          | 206/? [00:49<00:00,  4.17it/s, train/loss=20.20]\nEpoch 0: |          | 207/? [00:49<00:00,  4.19it/s, train/loss=20.20]\nEpoch 0: |          | 207/? [00:49<00:00,  4.19it/s, train/loss=3.100]\nEpoch 0: |          | 208/? [00:49<00:00,  4.18it/s, train/loss=3.100]\nEpoch 0: |          | 208/? [00:49<00:00,  4.18it/s, train/loss=30.20]\nEpoch 0: |          | 209/? [00:49<00:00,  4.20it/s, train/loss=30.20]\nEpoch 0: |          | 209/? [00:49<00:00,  4.20it/s, train/loss=2.980]\nEpoch 0: |          | 210/? [00:50<00:00,  4.20it/s, train/loss=2.980]\nEpoch 0: |          | 210/? [00:50<00:00,  4.20it/s, train/loss=22.10]\nEpoch 0: |          | 211/? [00:50<00:00,  4.21it/s, train/loss=22.10]\nEpoch 0: |          | 211/? [00:50<00:00,  4.21it/s, train/loss=2.870]\nEpoch 0: |          | 212/? [00:50<00:00,  4.21it/s, train/loss=2.870]\nEpoch 0: |          | 212/? [00:50<00:00,  4.21it/s, train/loss=31.50]\nEpoch 0: |          | 213/? [00:50<00:00,  4.22it/s, train/loss=31.50]\nEpoch 0: |          | 213/? [00:50<00:00,  4.22it/s, train/loss=2.790]\nEpoch 0: |          | 214/? [00:50<00:00,  4.22it/s, train/loss=2.790]\nEpoch 0: |          | 214/? [00:50<00:00,  4.22it/s, train/loss=20.80]\nEpoch 0: |          | 215/? [00:50<00:00,  4.24it/s, train/loss=20.80]\nEpoch 0: |          | 215/? [00:50<00:00,  4.24it/s, train/loss=2.730]\nEpoch 0: |          | 216/? [00:51<00:00,  4.23it/s, train/loss=2.730]\nEpoch 0: |          | 216/? [00:51<00:00,  4.23it/s, train/loss=65.60]\nEpoch 0: |          | 217/? [00:51<00:00,  4.25it/s, train/loss=65.60]\nEpoch 0: |          | 217/? [00:51<00:00,  4.25it/s, train/loss=2.680]\nEpoch 0: |          | 218/? [00:51<00:00,  4.25it/s, train/loss=2.680]\nEpoch 0: |          | 218/? [00:51<00:00,  4.25it/s, train/loss=23.40]\nEpoch 0: |          | 219/? [00:51<00:00,  4.26it/s, train/loss=23.40]\nEpoch 0: |          | 219/? [00:51<00:00,  4.26it/s, train/loss=2.660]\nEpoch 0: |          | 220/? [00:51<00:00,  4.26it/s, train/loss=2.660]\nEpoch 0: |          | 220/? [00:51<00:00,  4.26it/s, train/loss=27.50]\nEpoch 0: |          | 221/? [00:51<00:00,  4.28it/s, train/loss=27.50]\nEpoch 0: |          | 221/? [00:51<00:00,  4.28it/s, train/loss=2.650]\nEpoch 0: |          | 222/? [00:51<00:00,  4.27it/s, train/loss=2.650]\nEpoch 0: |          | 222/? [00:51<00:00,  4.27it/s, train/loss=89.30]\nEpoch 0: |          | 223/? [00:52<00:00,  4.29it/s, train/loss=89.30]\nEpoch 0: |          | 223/? [00:52<00:00,  4.29it/s, train/loss=2.650]\nEpoch 0: |          | 224/? [00:52<00:00,  4.28it/s, train/loss=2.650]\nEpoch 0: |          | 224/? [00:52<00:00,  4.28it/s, train/loss=46.50]\nEpoch 0: |          | 225/? [00:52<00:00,  4.30it/s, train/loss=46.50]\nEpoch 0: |          | 225/? [00:52<00:00,  4.30it/s, train/loss=2.650]\nEpoch 0: |          | 226/? [00:52<00:00,  4.29it/s, train/loss=2.650]\nEpoch 0: |          | 226/? [00:52<00:00,  4.29it/s, train/loss=24.20]\nEpoch 0: |          | 227/? [00:52<00:00,  4.31it/s, train/loss=24.20]\nEpoch 0: |          | 227/? [00:52<00:00,  4.31it/s, train/loss=2.630]\nEpoch 0: |          | 228/? [00:52<00:00,  4.30it/s, train/loss=2.630]\nEpoch 0: |          | 228/? [00:52<00:00,  4.30it/s, train/loss=21.20]\nEpoch 0: |          | 229/? [00:52<00:00,  4.32it/s, train/loss=21.20]\nEpoch 0: |          | 229/? [00:52<00:00,  4.32it/s, train/loss=2.570]\nEpoch 0: |          | 230/? [00:53<00:00,  4.32it/s, train/loss=2.570]\nEpoch 0: |          | 230/? [00:53<00:00,  4.32it/s, train/loss=28.80]\nEpoch 0: |          | 231/? [00:53<00:00,  4.33it/s, train/loss=28.80]\nEpoch 0: |          | 231/? [00:53<00:00,  4.33it/s, train/loss=2.490]\nEpoch 0: |          | 232/? [00:53<00:00,  4.33it/s, train/loss=2.490]\nEpoch 0: |          | 232/? [00:53<00:00,  4.33it/s, train/loss=18.90]\nEpoch 0: |          | 233/? [00:53<00:00,  4.34it/s, train/loss=18.90]\nEpoch 0: |          | 233/? [00:53<00:00,  4.34it/s, train/loss=2.410]\nEpoch 0: |          | 234/? [00:53<00:00,  4.34it/s, train/loss=2.410]\nEpoch 0: |          | 234/? [00:53<00:00,  4.34it/s, train/loss=27.70]\nEpoch 0: |          | 235/? [00:53<00:00,  4.35it/s, train/loss=27.70]\nEpoch 0: |          | 235/? [00:53<00:00,  4.35it/s, train/loss=2.350]\nEpoch 0: |          | 236/? [00:54<00:00,  4.35it/s, train/loss=2.350]\nEpoch 0: |          | 236/? [00:54<00:00,  4.35it/s, train/loss=26.80]\nEpoch 0: |          | 237/? [00:54<00:00,  4.36it/s, train/loss=26.80]\nEpoch 0: |          | 237/? [00:54<00:00,  4.36it/s, train/loss=2.300]\nEpoch 0: |          | 238/? [00:54<00:00,  4.36it/s, train/loss=2.300]\nEpoch 0: |          | 238/? [00:54<00:00,  4.36it/s, train/loss=21.90]\nEpoch 0: |          | 239/? [00:54<00:00,  4.38it/s, train/loss=21.90]\nEpoch 0: |          | 239/? [00:54<00:00,  4.37it/s, train/loss=2.240]\nEpoch 0: |          | 240/? [00:54<00:00,  4.37it/s, train/loss=2.240]\nEpoch 0: |          | 240/? [00:54<00:00,  4.37it/s, train/loss=6.910]\nEpoch 0: |          | 241/? [00:54<00:00,  4.39it/s, train/loss=6.910]\nEpoch 0: |          | 241/? [00:54<00:00,  4.39it/s, train/loss=2.190]\nEpoch 0: |          | 242/? [00:55<00:00,  4.38it/s, train/loss=2.190]\nEpoch 0: |          | 242/? [00:55<00:00,  4.38it/s, train/loss=20.40]\nEpoch 0: |          | 243/? [00:55<00:00,  4.40it/s, train/loss=20.40]\nEpoch 0: |          | 243/? [00:55<00:00,  4.40it/s, train/loss=2.140]\nEpoch 0: |          | 244/? [00:55<00:00,  4.39it/s, train/loss=2.140]\nEpoch 0: |          | 244/? [00:55<00:00,  4.39it/s, train/loss=27.40]\nEpoch 0: |          | 245/? [00:55<00:00,  4.41it/s, train/loss=27.40]\nEpoch 0: |          | 245/? [00:55<00:00,  4.41it/s, train/loss=2.100]\nEpoch 0: |          | 246/? [00:55<00:00,  4.40it/s, train/loss=2.100]\nEpoch 0: |          | 246/? [00:55<00:00,  4.40it/s, train/loss=21.10]\nEpoch 0: |          | 247/? [00:55<00:00,  4.42it/s, train/loss=21.10]\nEpoch 0: |          | 247/? [00:55<00:00,  4.42it/s, train/loss=2.060]\nEpoch 0: |          | 248/? [00:56<00:00,  4.41it/s, train/loss=2.060]\nEpoch 0: |          | 248/? [00:56<00:00,  4.41it/s, train/loss=12.50]\nEpoch 0: |          | 249/? [00:56<00:00,  4.43it/s, train/loss=12.50]\nEpoch 0: |          | 249/? [00:56<00:00,  4.43it/s, train/loss=2.020]\nEpoch 0: |          | 250/? [00:56<00:00,  4.42it/s, train/loss=2.020]\nEpoch 0: |          | 250/? [00:56<00:00,  4.42it/s, train/loss=24.50]\nEpoch 0: |          | 251/? [00:56<00:00,  4.43it/s, train/loss=24.50]\nEpoch 0: |          | 251/? [00:56<00:00,  4.43it/s, train/loss=1.990]\nEpoch 0: |          | 252/? [00:56<00:00,  4.43it/s, train/loss=1.990]\nEpoch 0: |          | 252/? [00:56<00:00,  4.43it/s, train/loss=10.80]\nEpoch 0: |          | 253/? [00:56<00:00,  4.44it/s, train/loss=10.80]\nEpoch 0: |          | 253/? [00:56<00:00,  4.44it/s, train/loss=1.960]\nEpoch 0: |          | 254/? [00:57<00:00,  4.44it/s, train/loss=1.960]\nEpoch 0: |          | 254/? [00:57<00:00,  4.44it/s, train/loss=44.30]\nEpoch 0: |          | 255/? [00:57<00:00,  4.45it/s, train/loss=44.30]\nEpoch 0: |          | 255/? [00:57<00:00,  4.45it/s, train/loss=1.930]\nEpoch 0: |          | 256/? [00:57<00:00,  4.45it/s, train/loss=1.930]\nEpoch 0: |          | 256/? [00:57<00:00,  4.45it/s, train/loss=34.80]\nEpoch 0: |          | 257/? [00:57<00:00,  4.46it/s, train/loss=34.80]\nEpoch 0: |          | 257/? [00:57<00:00,  4.46it/s, train/loss=1.910]\nEpoch 0: |          | 258/? [00:57<00:00,  4.46it/s, train/loss=1.910]\nEpoch 0: |          | 258/? [00:57<00:00,  4.46it/s, train/loss=30.50]\nEpoch 0: |          | 259/? [00:57<00:00,  4.47it/s, train/loss=30.50]\nEpoch 0: |          | 259/? [00:57<00:00,  4.47it/s, train/loss=1.900]\nEpoch 0: |          | 260/? [00:58<00:00,  4.47it/s, train/loss=1.900]\nEpoch 0: |          | 260/? [00:58<00:00,  4.47it/s, train/loss=37.80]\nEpoch 0: |          | 261/? [00:58<00:00,  4.48it/s, train/loss=37.80]\nEpoch 0: |          | 261/? [00:58<00:00,  4.48it/s, train/loss=1.890]\nEpoch 0: |          | 262/? [00:58<00:00,  4.48it/s, train/loss=1.890]\nEpoch 0: |          | 262/? [00:58<00:00,  4.48it/s, train/loss=24.40]\nEpoch 0: |          | 263/? [00:58<00:00,  4.49it/s, train/loss=24.40]\nEpoch 0: |          | 263/? [00:58<00:00,  4.49it/s, train/loss=1.900]\nEpoch 0: |          | 264/? [00:58<00:00,  4.49it/s, train/loss=1.900]\nEpoch 0: |          | 264/? [00:58<00:00,  4.49it/s, train/loss=36.50]\nEpoch 0: |          | 265/? [00:58<00:00,  4.50it/s, train/loss=36.50]\nEpoch 0: |          | 265/? [00:58<00:00,  4.50it/s, train/loss=1.930]\nEpoch 0: |          | 266/? [00:59<00:00,  4.50it/s, train/loss=1.930]\nEpoch 0: |          | 266/? [00:59<00:00,  4.50it/s, train/loss=40.20]\nEpoch 0: |          | 267/? [00:59<00:00,  4.51it/s, train/loss=40.20]\nEpoch 0: |          | 267/? [00:59<00:00,  4.51it/s, train/loss=1.960]\nEpoch 0: |          | 268/? [00:59<00:00,  4.51it/s, train/loss=1.960]\nEpoch 0: |          | 268/? [00:59<00:00,  4.51it/s, train/loss=15.30]\nEpoch 0: |          | 269/? [00:59<00:00,  4.52it/s, train/loss=15.30]\nEpoch 0: |          | 269/? [00:59<00:00,  4.52it/s, train/loss=1.980]\nEpoch 0: |          | 270/? [00:59<00:00,  4.52it/s, train/loss=1.980]\nEpoch 0: |          | 270/? [00:59<00:00,  4.52it/s, train/loss=11.80]\nEpoch 0: |          | 271/? [00:59<00:00,  4.53it/s, train/loss=11.80]\nEpoch 0: |          | 271/? [00:59<00:00,  4.53it/s, train/loss=1.980]\nEpoch 0: |          | 272/? [01:00<00:00,  4.53it/s, train/loss=1.980]\nEpoch 0: |          | 272/? [01:00<00:00,  4.53it/s, train/loss=37.30]\nEpoch 0: |          | 273/? [01:00<00:00,  4.54it/s, train/loss=37.30]\nEpoch 0: |          | 273/? [01:00<00:00,  4.54it/s, train/loss=1.930]\nEpoch 0: |          | 274/? [01:00<00:00,  4.53it/s, train/loss=1.930]\nEpoch 0: |          | 274/? [01:00<00:00,  4.53it/s, train/loss=20.50]\nEpoch 0: |          | 275/? [01:00<00:00,  4.55it/s, train/loss=20.50]\nEpoch 0: |          | 275/? [01:00<00:00,  4.55it/s, train/loss=1.890]\nEpoch 0: |          | 276/? [01:00<00:00,  4.54it/s, train/loss=1.890]\nEpoch 0: |          | 276/? [01:00<00:00,  4.54it/s, train/loss=15.60]\nEpoch 0: |          | 277/? [01:00<00:00,  4.55it/s, train/loss=15.60]\nEpoch 0: |          | 277/? [01:00<00:00,  4.55it/s, train/loss=1.880]\nEpoch 0: |          | 278/? [01:01<00:00,  4.54it/s, train/loss=1.880]\nEpoch 0: |          | 278/? [01:01<00:00,  4.54it/s, train/loss=51.20]\nEpoch 0: |          | 279/? [01:01<00:00,  4.56it/s, train/loss=51.20]\nEpoch 0: |          | 279/? [01:01<00:00,  4.56it/s, train/loss=1.880]\nEpoch 0: |          | 280/? [01:01<00:00,  4.55it/s, train/loss=1.880]\nEpoch 0: |          | 280/? [01:01<00:00,  4.55it/s, train/loss=22.40]\nEpoch 0: |          | 281/? [01:01<00:00,  4.56it/s, train/loss=22.40]\nEpoch 0: |          | 281/? [01:01<00:00,  4.56it/s, train/loss=1.880]\nEpoch 0: |          | 282/? [01:01<00:00,  4.56it/s, train/loss=1.880]\nEpoch 0: |          | 282/? [01:01<00:00,  4.56it/s, train/loss=12.20]\nEpoch 0: |          | 283/? [01:01<00:00,  4.57it/s, train/loss=12.20]\nEpoch 0: |          | 283/? [01:01<00:00,  4.57it/s, train/loss=1.850]\nEpoch 0: |          | 284/? [01:02<00:00,  4.57it/s, train/loss=1.850]\nEpoch 0: |          | 284/? [01:02<00:00,  4.57it/s, train/loss=26.80]\nEpoch 0: |          | 285/? [01:02<00:00,  4.58it/s, train/loss=26.80]\nEpoch 0: |          | 285/? [01:02<00:00,  4.58it/s, train/loss=1.800]\nEpoch 0: |          | 286/? [01:02<00:00,  4.58it/s, train/loss=1.800]\nEpoch 0: |          | 286/? [01:02<00:00,  4.58it/s, train/loss=19.70]\nEpoch 0: |          | 287/? [01:02<00:00,  4.59it/s, train/loss=19.70]\nEpoch 0: |          | 287/? [01:02<00:00,  4.59it/s, train/loss=1.770]\nEpoch 0: |          | 288/? [01:02<00:00,  4.58it/s, train/loss=1.770]\nEpoch 0: |          | 288/? [01:02<00:00,  4.58it/s, train/loss=27.50]\nEpoch 0: |          | 289/? [01:02<00:00,  4.60it/s, train/loss=27.50]\nEpoch 0: |          | 289/? [01:02<00:00,  4.60it/s, train/loss=1.740]\nEpoch 0: |          | 290/? [01:03<00:00,  4.59it/s, train/loss=1.740]\nEpoch 0: |          | 290/? [01:03<00:00,  4.59it/s, train/loss=35.80]\nEpoch 0: |          | 291/? [01:03<00:00,  4.61it/s, train/loss=35.80]\nEpoch 0: |          | 291/? [01:03<00:00,  4.61it/s, train/loss=1.740]\nEpoch 0: |          | 292/? [01:03<00:00,  4.60it/s, train/loss=1.740]\nEpoch 0: |          | 292/? [01:03<00:00,  4.60it/s, train/loss=28.60]\nEpoch 0: |          | 293/? [01:03<00:00,  4.61it/s, train/loss=28.60]\nEpoch 0: |          | 293/? [01:03<00:00,  4.61it/s, train/loss=1.750]\nEpoch 0: |          | 294/? [01:03<00:00,  4.61it/s, train/loss=1.750]\nEpoch 0: |          | 294/? [01:03<00:00,  4.61it/s, train/loss=33.70]\nEpoch 0: |          | 295/? [01:03<00:00,  4.62it/s, train/loss=33.70]\nEpoch 0: |          | 295/? [01:03<00:00,  4.62it/s, train/loss=1.760]\nEpoch 0: |          | 296/? [01:04<00:00,  4.62it/s, train/loss=1.760]\nEpoch 0: |          | 296/? [01:04<00:00,  4.62it/s, train/loss=36.40]\nEpoch 0: |          | 297/? [01:04<00:00,  4.63it/s, train/loss=36.40]\nEpoch 0: |          | 297/? [01:04<00:00,  4.63it/s, train/loss=1.760]\nEpoch 0: |          | 298/? [01:04<00:00,  4.62it/s, train/loss=1.760]\nEpoch 0: |          | 298/? [01:04<00:00,  4.62it/s, train/loss=9.910]\nEpoch 0: |          | 299/? [01:04<00:00,  4.64it/s, train/loss=9.910]\nEpoch 0: |          | 299/? [01:04<00:00,  4.64it/s, train/loss=1.740]\nEpoch 0: |          | 300/? [01:04<00:00,  4.63it/s, train/loss=1.740]\nEpoch 0: |          | 300/? [01:04<00:00,  4.63it/s, train/loss=11.90]\nEpoch 0: |          | 301/? [01:04<00:00,  4.65it/s, train/loss=11.90]\nEpoch 0: |          | 301/? [01:04<00:00,  4.65it/s, train/loss=1.710]\nEpoch 0: |          | 302/? [01:05<00:00,  4.64it/s, train/loss=1.710]\nEpoch 0: |          | 302/? [01:05<00:00,  4.64it/s, train/loss=31.00]\nEpoch 0: |          | 303/? [01:05<00:00,  4.65it/s, train/loss=31.00]\nEpoch 0: |          | 303/? [01:05<00:00,  4.65it/s, train/loss=1.710]\nEpoch 0: |          | 304/? [01:05<00:00,  4.65it/s, train/loss=1.710]\nEpoch 0: |          | 304/? [01:05<00:00,  4.65it/s, train/loss=23.80]\nEpoch 0: |          | 305/? [01:05<00:00,  4.66it/s, train/loss=23.80]\nEpoch 0: |          | 305/? [01:05<00:00,  4.66it/s, train/loss=1.760]\nEpoch 0: |          | 306/? [01:05<00:00,  4.66it/s, train/loss=1.760]\nEpoch 0: |          | 306/? [01:05<00:00,  4.66it/s, train/loss=13.10]\nEpoch 0: |          | 307/? [01:05<00:00,  4.67it/s, train/loss=13.10]\nEpoch 0: |          | 307/? [01:05<00:00,  4.67it/s, train/loss=1.800]\nEpoch 0: |          | 308/? [01:06<00:00,  4.67it/s, train/loss=1.800]\nEpoch 0: |          | 308/? [01:06<00:00,  4.67it/s, train/loss=20.90]\nEpoch 0: |          | 309/? [01:06<00:00,  4.68it/s, train/loss=20.90]\nEpoch 0: |          | 309/? [01:06<00:00,  4.68it/s, train/loss=1.770]\nEpoch 0: |          | 310/? [01:06<00:00,  4.67it/s, train/loss=1.770]\nEpoch 0: |          | 310/? [01:06<00:00,  4.67it/s, train/loss=36.20]\nEpoch 0: |          | 311/? [01:06<00:00,  4.69it/s, train/loss=36.20]\nEpoch 0: |          | 311/? [01:06<00:00,  4.68it/s, train/loss=1.700]\nEpoch 0: |          | 312/? [01:06<00:00,  4.68it/s, train/loss=1.700]\nEpoch 0: |          | 312/? [01:06<00:00,  4.68it/s, train/loss=29.00]\nEpoch 0: |          | 313/? [01:06<00:00,  4.69it/s, train/loss=29.00]\nEpoch 0: |          | 313/? [01:06<00:00,  4.69it/s, train/loss=1.640]\nEpoch 0: |          | 314/? [01:06<00:00,  4.69it/s, train/loss=1.640]\nEpoch 0: |          | 314/? [01:06<00:00,  4.69it/s, train/loss=12.90]\nEpoch 0: |          | 315/? [01:07<00:00,  4.70it/s, train/loss=12.90]\nEpoch 0: |          | 315/? [01:07<00:00,  4.70it/s, train/loss=1.620]\nEpoch 0: |          | 316/? [01:07<00:00,  4.70it/s, train/loss=1.620]\nEpoch 0: |          | 316/? [01:07<00:00,  4.70it/s, train/loss=19.40]\nEpoch 0: |          | 317/? [01:07<00:00,  4.71it/s, train/loss=19.40]\nEpoch 0: |          | 317/? [01:07<00:00,  4.71it/s, train/loss=1.590]\nEpoch 0: |          | 318/? [01:07<00:00,  4.70it/s, train/loss=1.590]\nEpoch 0: |          | 318/? [01:07<00:00,  4.70it/s, train/loss=17.20]\nEpoch 0: |          | 319/? [01:07<00:00,  4.72it/s, train/loss=17.20]\nEpoch 0: |          | 319/? [01:07<00:00,  4.71it/s, train/loss=1.570]\nEpoch 0: |          | 320/? [01:07<00:00,  4.71it/s, train/loss=1.570]\nEpoch 0: |          | 320/? [01:07<00:00,  4.71it/s, train/loss=8.480]\nEpoch 0: |          | 321/? [01:07<00:00,  4.72it/s, train/loss=8.480]\nEpoch 0: |          | 321/? [01:07<00:00,  4.72it/s, train/loss=1.620]\nEpoch 0: |          | 322/? [01:08<00:00,  4.72it/s, train/loss=1.620]\nEpoch 0: |          | 322/? [01:08<00:00,  4.72it/s, train/loss=20.80]\nEpoch 0: |          | 323/? [01:08<00:00,  4.73it/s, train/loss=20.80]\nEpoch 0: |          | 323/? [01:08<00:00,  4.73it/s, train/loss=1.580]\nEpoch 0: |          | 324/? [01:08<00:00,  4.72it/s, train/loss=1.580]\nEpoch 0: |          | 324/? [01:08<00:00,  4.72it/s, train/loss=12.70]\nEpoch 0: |          | 325/? [01:08<00:00,  4.74it/s, train/loss=12.70]\nEpoch 0: |          | 325/? [01:08<00:00,  4.74it/s, train/loss=1.560]\nEpoch 0: |          | 326/? [01:08<00:00,  4.73it/s, train/loss=1.560]\nEpoch 0: |          | 326/? [01:08<00:00,  4.73it/s, train/loss=28.90]\nEpoch 0: |          | 327/? [01:08<00:00,  4.74it/s, train/loss=28.90]\nEpoch 0: |          | 327/? [01:08<00:00,  4.74it/s, train/loss=1.540]\nEpoch 0: |          | 328/? [01:09<00:00,  4.74it/s, train/loss=1.540]\nEpoch 0: |          | 328/? [01:09<00:00,  4.74it/s, train/loss=24.00]\nEpoch 0: |          | 329/? [01:09<00:00,  4.75it/s, train/loss=24.00]\nEpoch 0: |          | 329/? [01:09<00:00,  4.75it/s, train/loss=1.520]\nEpoch 0: |          | 330/? [01:09<00:00,  4.75it/s, train/loss=1.520]\nEpoch 0: |          | 330/? [01:09<00:00,  4.75it/s, train/loss=21.20]\nEpoch 0: |          | 331/? [01:09<00:00,  4.76it/s, train/loss=21.20]\nEpoch 0: |          | 331/? [01:09<00:00,  4.76it/s, train/loss=1.510]\nEpoch 0: |          | 332/? [01:09<00:00,  4.75it/s, train/loss=1.510]\nEpoch 0: |          | 332/? [01:09<00:00,  4.75it/s, train/loss=71.20]\nEpoch 0: |          | 333/? [01:09<00:00,  4.76it/s, train/loss=71.20]\nEpoch 0: |          | 333/? [01:09<00:00,  4.76it/s, train/loss=1.500]\nEpoch 0: |          | 334/? [01:10<00:00,  4.76it/s, train/loss=1.500]\nEpoch 0: |          | 334/? [01:10<00:00,  4.76it/s, train/loss=15.70]\nEpoch 0: |          | 335/? [01:10<00:00,  4.77it/s, train/loss=15.70]\nEpoch 0: |          | 335/? [01:10<00:00,  4.77it/s, train/loss=1.510]\nEpoch 0: |          | 336/? [01:10<00:00,  4.77it/s, train/loss=1.510]\nEpoch 0: |          | 336/? [01:10<00:00,  4.77it/s, train/loss=40.90]\nEpoch 0: |          | 337/? [01:10<00:00,  4.78it/s, train/loss=40.90]\nEpoch 0: |          | 337/? [01:10<00:00,  4.78it/s, train/loss=1.530]\nEpoch 0: |          | 338/? [01:10<00:00,  4.77it/s, train/loss=1.530]\nEpoch 0: |          | 338/? [01:10<00:00,  4.77it/s, train/loss=52.10]\nEpoch 0: |          | 339/? [01:10<00:00,  4.79it/s, train/loss=52.10]\nEpoch 0: |          | 339/? [01:10<00:00,  4.79it/s, train/loss=1.570]\nEpoch 0: |          | 340/? [01:11<00:00,  4.78it/s, train/loss=1.570]\nEpoch 0: |          | 340/? [01:11<00:00,  4.78it/s, train/loss=13.10]\nEpoch 0: |          | 341/? [01:11<00:00,  4.79it/s, train/loss=13.10]\nEpoch 0: |          | 341/? [01:11<00:00,  4.79it/s, train/loss=1.650]\nEpoch 0: |          | 342/? [01:11<00:00,  4.79it/s, train/loss=1.650]\nEpoch 0: |          | 342/? [01:11<00:00,  4.79it/s, train/loss=35.70]\nEpoch 0: |          | 343/? [01:11<00:00,  4.80it/s, train/loss=35.70]\nEpoch 0: |          | 343/? [01:11<00:00,  4.80it/s, train/loss=1.690]\nEpoch 0: |          | 344/? [01:11<00:00,  4.79it/s, train/loss=1.690]\nEpoch 0: |          | 344/? [01:11<00:00,  4.79it/s, train/loss=37.80]\nEpoch 0: |          | 345/? [01:11<00:00,  4.81it/s, train/loss=37.80]\nEpoch 0: |          | 345/? [01:11<00:00,  4.81it/s, train/loss=1.700]\nEpoch 0: |          | 346/? [01:12<00:00,  4.80it/s, train/loss=1.700]\nEpoch 0: |          | 346/? [01:12<00:00,  4.80it/s, train/loss=14.10]\nEpoch 0: |          | 347/? [01:12<00:00,  4.81it/s, train/loss=14.10]\nEpoch 0: |          | 347/? [01:12<00:00,  4.81it/s, train/loss=1.700]\nEpoch 0: |          | 348/? [01:12<00:00,  4.81it/s, train/loss=1.700]\nEpoch 0: |          | 348/? [01:12<00:00,  4.81it/s, train/loss=43.30]\nEpoch 0: |          | 349/? [01:12<00:00,  4.82it/s, train/loss=43.30]\nEpoch 0: |          | 349/? [01:12<00:00,  4.82it/s, train/loss=1.670]\nEpoch 0: |          | 350/? [01:12<00:00,  4.81it/s, train/loss=1.670]\nEpoch 0: |          | 350/? [01:12<00:00,  4.81it/s, train/loss=21.80]\nEpoch 0: |          | 351/? [01:12<00:00,  4.82it/s, train/loss=21.80]\nEpoch 0: |          | 351/? [01:12<00:00,  4.82it/s, train/loss=1.620]\nEpoch 0: |          | 352/? [01:13<00:00,  4.82it/s, train/loss=1.620]\nEpoch 0: |          | 352/? [01:13<00:00,  4.82it/s, train/loss=38.20]\nEpoch 0: |          | 353/? [01:13<00:00,  4.83it/s, train/loss=38.20]\nEpoch 0: |          | 353/? [01:13<00:00,  4.83it/s, train/loss=1.580]\nEpoch 0: |          | 354/? [01:13<00:00,  4.83it/s, train/loss=1.580]\nEpoch 0: |          | 354/? [01:13<00:00,  4.83it/s, train/loss=14.50]\nEpoch 0: |          | 355/? [01:13<00:00,  4.84it/s, train/loss=14.50]\nEpoch 0: |          | 355/? [01:13<00:00,  4.84it/s, train/loss=1.550]\nEpoch 0: |          | 356/? [01:13<00:00,  4.83it/s, train/loss=1.550]\nEpoch 0: |          | 356/? [01:13<00:00,  4.83it/s, train/loss=27.10]\nEpoch 0: |          | 357/? [01:13<00:00,  4.84it/s, train/loss=27.10]\nEpoch 0: |          | 357/? [01:13<00:00,  4.84it/s, train/loss=1.530]\nEpoch 0: |          | 358/? [01:13<00:00,  4.84it/s, train/loss=1.530]\nEpoch 0: |          | 358/? [01:13<00:00,  4.84it/s, train/loss=22.20]\nEpoch 0: |          | 359/? [01:14<00:00,  4.85it/s, train/loss=22.20]\nEpoch 0: |          | 359/? [01:14<00:00,  4.85it/s, train/loss=1.510]\nEpoch 0: |          | 360/? [01:14<00:00,  4.84it/s, train/loss=1.510]\nEpoch 0: |          | 360/? [01:14<00:00,  4.84it/s, train/loss=16.60]\nEpoch 0: |          | 361/? [01:14<00:00,  4.86it/s, train/loss=16.60]\nEpoch 0: |          | 361/? [01:14<00:00,  4.86it/s, train/loss=1.510]\nEpoch 0: |          | 362/? [01:14<00:00,  4.85it/s, train/loss=1.510]\nEpoch 0: |          | 362/? [01:14<00:00,  4.85it/s, train/loss=29.70]\nEpoch 0: |          | 363/? [01:14<00:00,  4.86it/s, train/loss=29.70]\nEpoch 0: |          | 363/? [01:14<00:00,  4.86it/s, train/loss=1.500]\nEpoch 0: |          | 364/? [01:14<00:00,  4.86it/s, train/loss=1.500]\nEpoch 0: |          | 364/? [01:14<00:00,  4.86it/s, train/loss=34.00]\nEpoch 0: |          | 365/? [01:14<00:00,  4.87it/s, train/loss=34.00]\nEpoch 0: |          | 365/? [01:14<00:00,  4.87it/s, train/loss=1.500]\nEpoch 0: |          | 366/? [01:15<00:00,  4.86it/s, train/loss=1.500]\nEpoch 0: |          | 366/? [01:15<00:00,  4.86it/s, train/loss=15.00]\nEpoch 0: |          | 367/? [01:15<00:00,  4.87it/s, train/loss=15.00]\nEpoch 0: |          | 367/? [01:15<00:00,  4.87it/s, train/loss=1.490]\nEpoch 0: |          | 368/? [01:15<00:00,  4.86it/s, train/loss=1.490]\nEpoch 0: |          | 368/? [01:15<00:00,  4.86it/s, train/loss=24.70]\nEpoch 0: |          | 369/? [01:15<00:00,  4.86it/s, train/loss=24.70]\nEpoch 0: |          | 369/? [01:15<00:00,  4.86it/s, train/loss=1.630]\nEpoch 0: |          | 370/? [01:16<00:00,  4.85it/s, train/loss=1.630]\nEpoch 0: |          | 370/? [01:16<00:00,  4.85it/s, train/loss=30.90]\nEpoch 0: |          | 371/? [01:16<00:00,  4.86it/s, train/loss=30.90]\nEpoch 0: |          | 371/? [01:16<00:00,  4.86it/s, train/loss=1.620]\nEpoch 0: |          | 372/? [01:16<00:00,  4.85it/s, train/loss=1.620]\nEpoch 0: |          | 372/? [01:16<00:00,  4.85it/s, train/loss=26.20]\nEpoch 0: |          | 373/? [01:16<00:00,  4.86it/s, train/loss=26.20]\nEpoch 0: |          | 373/? [01:16<00:00,  4.86it/s, train/loss=1.610]\nEpoch 0: |          | 374/? [01:17<00:00,  4.85it/s, train/loss=1.610]\nEpoch 0: |          | 374/? [01:17<00:00,  4.85it/s, train/loss=15.60]\nEpoch 0: |          | 375/? [01:17<00:00,  4.85it/s, train/loss=15.60]\nEpoch 0: |          | 375/? [01:17<00:00,  4.85it/s, train/loss=1.600]\nEpoch 0: |          | 376/? [01:17<00:00,  4.85it/s, train/loss=1.600]\nEpoch 0: |          | 376/? [01:17<00:00,  4.85it/s, train/loss=30.70]\nEpoch 0: |          | 377/? [01:17<00:00,  4.86it/s, train/loss=30.70]\nEpoch 0: |          | 377/? [01:17<00:00,  4.86it/s, train/loss=1.590]\nEpoch 0: |          | 378/? [01:17<00:00,  4.85it/s, train/loss=1.590]\nEpoch 0: |          | 378/? [01:17<00:00,  4.85it/s, train/loss=28.90]\nEpoch 0: |          | 379/? [01:17<00:00,  4.86it/s, train/loss=28.90]\nEpoch 0: |          | 379/? [01:17<00:00,  4.86it/s, train/loss=1.580]\nEpoch 0: |          | 380/? [01:18<00:00,  4.86it/s, train/loss=1.580]\nEpoch 0: |          | 380/? [01:18<00:00,  4.86it/s, train/loss=39.10]\nEpoch 0: |          | 381/? [01:18<00:00,  4.87it/s, train/loss=39.10]\nEpoch 0: |          | 381/? [01:18<00:00,  4.87it/s, train/loss=1.600]\nEpoch 0: |          | 382/? [01:18<00:00,  4.86it/s, train/loss=1.600]\nEpoch 0: |          | 382/? [01:18<00:00,  4.86it/s, train/loss=20.10]\nEpoch 0: |          | 383/? [01:18<00:00,  4.87it/s, train/loss=20.10]\nEpoch 0: |          | 383/? [01:18<00:00,  4.87it/s, train/loss=1.660]\nEpoch 0: |          | 384/? [01:18<00:00,  4.87it/s, train/loss=1.660]\nEpoch 0: |          | 384/? [01:18<00:00,  4.87it/s, train/loss=39.30]\nEpoch 0: |          | 385/? [01:18<00:00,  4.88it/s, train/loss=39.30]\nEpoch 0: |          | 385/? [01:18<00:00,  4.88it/s, train/loss=1.710]\nEpoch 0: |          | 386/? [01:19<00:00,  4.87it/s, train/loss=1.710]\nEpoch 0: |          | 386/? [01:19<00:00,  4.87it/s, train/loss=9.900]\nEpoch 0: |          | 387/? [01:19<00:00,  4.88it/s, train/loss=9.900]\nEpoch 0: |          | 387/? [01:19<00:00,  4.88it/s, train/loss=1.710]\nEpoch 0: |          | 388/? [01:19<00:00,  4.88it/s, train/loss=1.710]\nEpoch 0: |          | 388/? [01:19<00:00,  4.88it/s, train/loss=27.30]\nEpoch 0: |          | 389/? [01:19<00:00,  4.89it/s, train/loss=27.30]\nEpoch 0: |          | 389/? [01:19<00:00,  4.89it/s, train/loss=1.700]\nEpoch 0: |          | 390/? [01:19<00:00,  4.89it/s, train/loss=1.700]\nEpoch 0: |          | 390/? [01:19<00:00,  4.89it/s, train/loss=23.70]\nEpoch 0: |          | 391/? [01:19<00:00,  4.90it/s, train/loss=23.70]\nEpoch 0: |          | 391/? [01:19<00:00,  4.90it/s, train/loss=1.670]\nEpoch 0: |          | 392/? [01:20<00:00,  4.89it/s, train/loss=1.670]\nEpoch 0: |          | 392/? [01:20<00:00,  4.89it/s, train/loss=22.80]\nEpoch 0: |          | 393/? [01:20<00:00,  4.90it/s, train/loss=22.80]\nEpoch 0: |          | 393/? [01:20<00:00,  4.90it/s, train/loss=1.640]\nEpoch 0: |          | 394/? [01:20<00:00,  4.90it/s, train/loss=1.640]\nEpoch 0: |          | 394/? [01:20<00:00,  4.90it/s, train/loss=26.00]\nEpoch 0: |          | 395/? [01:20<00:00,  4.91it/s, train/loss=26.00]\nEpoch 0: |          | 395/? [01:20<00:00,  4.91it/s, train/loss=1.640]\nEpoch 0: |          | 396/? [01:20<00:00,  4.90it/s, train/loss=1.640]\nEpoch 0: |          | 396/? [01:20<00:00,  4.90it/s, train/loss=9.660]\nEpoch 0: |          | 397/? [01:20<00:00,  4.91it/s, train/loss=9.660]\nEpoch 0: |          | 397/? [01:20<00:00,  4.91it/s, train/loss=1.630]\nEpoch 0: |          | 398/? [01:21<00:00,  4.91it/s, train/loss=1.630]\nEpoch 0: |          | 398/? [01:21<00:00,  4.91it/s, train/loss=12.90]\nEpoch 0: |          | 399/? [01:21<00:00,  4.92it/s, train/loss=12.90]\nEpoch 0: |          | 399/? [01:21<00:00,  4.92it/s, train/loss=1.610]\nEpoch 0: |          | 400/? [01:21<00:00,  4.91it/s, train/loss=1.610]\nEpoch 0: |          | 400/? [01:21<00:00,  4.91it/s, train/loss=37.30]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:08,  4.51it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:08,  4.40it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:08,  4.44it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:08,  4.44it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:01<00:07,  4.45it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:01<00:07,  4.44it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:01<00:07,  4.48it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:01<00:07,  4.47it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:02<00:06,  4.47it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:02<00:06,  4.50it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:02<00:06,  4.50it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:02<00:06,  4.50it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:02<00:05,  4.53it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:03<00:05,  4.52it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:03<00:05,  4.54it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:03<00:05,  4.56it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:03<00:05,  4.58it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:03<00:04,  4.58it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:04<00:04,  4.59it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:04<00:04,  4.60it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:04<00:04,  4.61it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:04<00:03,  4.62it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:04<00:03,  4.61it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:05<00:03,  4.61it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:05<00:03,  4.61it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:05<00:03,  4.62it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:05<00:02,  4.61it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:06<00:02,  4.60it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:06<00:02,  4.60it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:06<00:02,  4.61it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:06<00:01,  4.62it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:06<00:01,  4.63it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:07<00:01,  4.63it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:07<00:01,  4.64it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:07<00:01,  4.64it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:07<00:00,  4.64it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:07<00:00,  4.63it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:08<00:00,  4.62it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:08<00:00,  4.63it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:08<00:00,  4.63it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 400/? [01:30<00:00,  4.40it/s, train/loss=37.30]\nEpoch 0: |          | 401/? [01:31<00:00,  4.36it/s, train/loss=37.30]\nEpoch 0: |          | 401/? [01:31<00:00,  4.36it/s, train/loss=1.570]\nEpoch 0: |          | 402/? [01:32<00:00,  4.36it/s, train/loss=1.570]\nEpoch 0: |          | 402/? [01:32<00:00,  4.36it/s, train/loss=12.40]\nEpoch 0: |          | 403/? [01:32<00:00,  4.37it/s, train/loss=12.40]\nEpoch 0: |          | 403/? [01:32<00:00,  4.37it/s, train/loss=1.540]\nEpoch 0: |          | 404/? [01:32<00:00,  4.37it/s, train/loss=1.540]\nEpoch 0: |          | 404/? [01:32<00:00,  4.37it/s, train/loss=18.20]\nEpoch 0: |          | 405/? [01:32<00:00,  4.37it/s, train/loss=18.20]\nEpoch 0: |          | 405/? [01:32<00:00,  4.37it/s, train/loss=1.510]\nEpoch 0: |          | 406/? [01:32<00:00,  4.37it/s, train/loss=1.510]\nEpoch 0: |          | 406/? [01:32<00:00,  4.37it/s, train/loss=23.10]\nEpoch 0: |          | 407/? [01:32<00:00,  4.38it/s, train/loss=23.10]\nEpoch 0: |          | 407/? [01:32<00:00,  4.38it/s, train/loss=1.500]\nEpoch 0: |          | 408/? [01:33<00:00,  4.38it/s, train/loss=1.500]\nEpoch 0: |          | 408/? [01:33<00:00,  4.38it/s, train/loss=16.30]\nEpoch 0: |          | 409/? [01:33<00:00,  4.39it/s, train/loss=16.30]\nEpoch 0: |          | 409/? [01:33<00:00,  4.39it/s, train/loss=1.490]\nEpoch 0: |          | 410/? [01:33<00:00,  4.38it/s, train/loss=1.490]\nEpoch 0: |          | 410/? [01:33<00:00,  4.38it/s, train/loss=27.70]\nEpoch 0: |          | 411/? [01:33<00:00,  4.39it/s, train/loss=27.70]\nEpoch 0: |          | 411/? [01:33<00:00,  4.39it/s, train/loss=1.500]\nEpoch 0: |          | 412/? [01:33<00:00,  4.39it/s, train/loss=1.500]\nEpoch 0: |          | 412/? [01:33<00:00,  4.39it/s, train/loss=11.30]\nEpoch 0: |          | 413/? [01:33<00:00,  4.40it/s, train/loss=11.30]\nEpoch 0: |          | 413/? [01:33<00:00,  4.40it/s, train/loss=1.490]\nEpoch 0: |          | 414/? [01:34<00:00,  4.40it/s, train/loss=1.490]\nEpoch 0: |          | 414/? [01:34<00:00,  4.40it/s, train/loss=11.10]\nEpoch 0: |          | 415/? [01:34<00:00,  4.41it/s, train/loss=11.10]\nEpoch 0: |          | 415/? [01:34<00:00,  4.41it/s, train/loss=1.480]\nEpoch 0: |          | 416/? [01:34<00:00,  4.40it/s, train/loss=1.480]\nEpoch 0: |          | 416/? [01:34<00:00,  4.40it/s, train/loss=21.90]\nEpoch 0: |          | 417/? [01:34<00:00,  4.41it/s, train/loss=21.90]\nEpoch 0: |          | 417/? [01:34<00:00,  4.41it/s, train/loss=1.460]\nEpoch 0: |          | 418/? [01:34<00:00,  4.41it/s, train/loss=1.460]\nEpoch 0: |          | 418/? [01:34<00:00,  4.41it/s, train/loss=35.50]\nEpoch 0: |          | 419/? [01:34<00:00,  4.42it/s, train/loss=35.50]\nEpoch 0: |          | 419/? [01:34<00:00,  4.42it/s, train/loss=1.440]\nEpoch 0: |          | 420/? [01:35<00:00,  4.42it/s, train/loss=1.440]\nEpoch 0: |          | 420/? [01:35<00:00,  4.42it/s, train/loss=40.30]\nEpoch 0: |          | 421/? [01:35<00:00,  4.43it/s, train/loss=40.30]\nEpoch 0: |          | 421/? [01:35<00:00,  4.43it/s, train/loss=1.400]\nEpoch 0: |          | 422/? [01:35<00:00,  4.42it/s, train/loss=1.400]\nEpoch 0: |          | 422/? [01:35<00:00,  4.42it/s, train/loss=23.00]\nEpoch 0: |          | 423/? [01:35<00:00,  4.43it/s, train/loss=23.00]\nEpoch 0: |          | 423/? [01:35<00:00,  4.43it/s, train/loss=1.370]\nEpoch 0: |          | 424/? [01:35<00:00,  4.43it/s, train/loss=1.370]\nEpoch 0: |          | 424/? [01:35<00:00,  4.43it/s, train/loss=17.50]\nEpoch 0: |          | 425/? [01:35<00:00,  4.44it/s, train/loss=17.50]\nEpoch 0: |          | 425/? [01:35<00:00,  4.44it/s, train/loss=1.360]\nEpoch 0: |          | 426/? [01:36<00:00,  4.44it/s, train/loss=1.360]\nEpoch 0: |          | 426/? [01:36<00:00,  4.44it/s, train/loss=26.50]\nEpoch 0: |          | 427/? [01:36<00:00,  4.45it/s, train/loss=26.50]\nEpoch 0: |          | 427/? [01:36<00:00,  4.45it/s, train/loss=1.370]\nEpoch 0: |          | 428/? [01:36<00:00,  4.44it/s, train/loss=1.370]\nEpoch 0: |          | 428/? [01:36<00:00,  4.44it/s, train/loss=40.60]\nEpoch 0: |          | 429/? [01:36<00:00,  4.45it/s, train/loss=40.60]\nEpoch 0: |          | 429/? [01:36<00:00,  4.45it/s, train/loss=1.410]\nEpoch 0: |          | 430/? [01:36<00:00,  4.45it/s, train/loss=1.410]\nEpoch 0: |          | 430/? [01:36<00:00,  4.45it/s, train/loss=9.530]\nEpoch 0: |          | 431/? [01:36<00:00,  4.46it/s, train/loss=9.530]\nEpoch 0: |          | 431/? [01:36<00:00,  4.46it/s, train/loss=1.460]\nEpoch 0: |          | 432/? [01:36<00:00,  4.46it/s, train/loss=1.460]\nEpoch 0: |          | 432/? [01:36<00:00,  4.46it/s, train/loss=10.90]\nEpoch 0: |          | 433/? [01:36<00:00,  4.46it/s, train/loss=10.90]\nEpoch 0: |          | 433/? [01:36<00:00,  4.46it/s, train/loss=1.410]\nEpoch 0: |          | 434/? [01:37<00:00,  4.46it/s, train/loss=1.410]\nEpoch 0: |          | 434/? [01:37<00:00,  4.46it/s, train/loss=13.10]\nEpoch 0: |          | 435/? [01:37<00:00,  4.47it/s, train/loss=13.10]\nEpoch 0: |          | 435/? [01:37<00:00,  4.47it/s, train/loss=1.380]\nEpoch 0: |          | 436/? [01:37<00:00,  4.47it/s, train/loss=1.380]\nEpoch 0: |          | 436/? [01:37<00:00,  4.47it/s, train/loss=30.50]\nEpoch 0: |          | 437/? [01:37<00:00,  4.48it/s, train/loss=30.50]\nEpoch 0: |          | 437/? [01:37<00:00,  4.48it/s, train/loss=1.340]\nEpoch 0: |          | 438/? [01:37<00:00,  4.47it/s, train/loss=1.340]\nEpoch 0: |          | 438/? [01:37<00:00,  4.47it/s, train/loss=19.70]\nEpoch 0: |          | 439/? [01:37<00:00,  4.48it/s, train/loss=19.70]\nEpoch 0: |          | 439/? [01:37<00:00,  4.48it/s, train/loss=1.300]\nEpoch 0: |          | 440/? [01:38<00:00,  4.48it/s, train/loss=1.300]\nEpoch 0: |          | 440/? [01:38<00:00,  4.48it/s, train/loss=8.380]\nEpoch 0: |          | 441/? [01:38<00:00,  4.49it/s, train/loss=8.380]\nEpoch 0: |          | 441/? [01:38<00:00,  4.49it/s, train/loss=1.310]\nEpoch 0: |          | 442/? [01:38<00:00,  4.49it/s, train/loss=1.310]\nEpoch 0: |          | 442/? [01:38<00:00,  4.49it/s, train/loss=20.80]\nEpoch 0: |          | 443/? [01:38<00:00,  4.49it/s, train/loss=20.80]\nEpoch 0: |          | 443/? [01:38<00:00,  4.49it/s, train/loss=1.340]\nEpoch 0: |          | 444/? [01:38<00:00,  4.49it/s, train/loss=1.340]\nEpoch 0: |          | 444/? [01:38<00:00,  4.49it/s, train/loss=19.60]\nEpoch 0: |          | 445/? [01:38<00:00,  4.50it/s, train/loss=19.60]\nEpoch 0: |          | 445/? [01:38<00:00,  4.50it/s, train/loss=1.360]\nEpoch 0: |          | 446/? [01:39<00:00,  4.50it/s, train/loss=1.360]\nEpoch 0: |          | 446/? [01:39<00:00,  4.50it/s, train/loss=27.50]\nEpoch 0: |          | 447/? [01:39<00:00,  4.51it/s, train/loss=27.50]\nEpoch 0: |          | 447/? [01:39<00:00,  4.51it/s, train/loss=1.350]\nEpoch 0: |          | 448/? [01:39<00:00,  4.50it/s, train/loss=1.350]\nEpoch 0: |          | 448/? [01:39<00:00,  4.50it/s, train/loss=21.00]\nEpoch 0: |          | 449/? [01:39<00:00,  4.51it/s, train/loss=21.00]\nEpoch 0: |          | 449/? [01:39<00:00,  4.51it/s, train/loss=1.310]\nEpoch 0: |          | 450/? [01:39<00:00,  4.51it/s, train/loss=1.310]\nEpoch 0: |          | 450/? [01:39<00:00,  4.51it/s, train/loss=23.30]\nEpoch 0: |          | 451/? [01:39<00:00,  4.52it/s, train/loss=23.30]\nEpoch 0: |          | 451/? [01:39<00:00,  4.52it/s, train/loss=1.240]\nEpoch 0: |          | 452/? [01:40<00:00,  4.52it/s, train/loss=1.240]\nEpoch 0: |          | 452/? [01:40<00:00,  4.52it/s, train/loss=35.10]\nEpoch 0: |          | 453/? [01:40<00:00,  4.53it/s, train/loss=35.10]\nEpoch 0: |          | 453/? [01:40<00:00,  4.53it/s, train/loss=1.200]\nEpoch 0: |          | 454/? [01:40<00:00,  4.52it/s, train/loss=1.200]\nEpoch 0: |          | 454/? [01:40<00:00,  4.52it/s, train/loss=20.00]\nEpoch 0: |          | 455/? [01:40<00:00,  4.53it/s, train/loss=20.00]\nEpoch 0: |          | 455/? [01:40<00:00,  4.53it/s, train/loss=1.200]\nEpoch 0: |          | 456/? [01:40<00:00,  4.53it/s, train/loss=1.200]\nEpoch 0: |          | 456/? [01:40<00:00,  4.53it/s, train/loss=33.20]\nEpoch 0: |          | 457/? [01:40<00:00,  4.54it/s, train/loss=33.20]\nEpoch 0: |          | 457/? [01:40<00:00,  4.54it/s, train/loss=1.240]\nEpoch 0: |          | 458/? [01:41<00:00,  4.53it/s, train/loss=1.240]\nEpoch 0: |          | 458/? [01:41<00:00,  4.53it/s, train/loss=12.90]\nEpoch 0: |          | 459/? [01:41<00:00,  4.54it/s, train/loss=12.90]\nEpoch 0: |          | 459/? [01:41<00:00,  4.54it/s, train/loss=1.340]\nEpoch 0: |          | 460/? [01:41<00:00,  4.54it/s, train/loss=1.340]\nEpoch 0: |          | 460/? [01:41<00:00,  4.54it/s, train/loss=27.10]\nEpoch 0: |          | 461/? [01:41<00:00,  4.55it/s, train/loss=27.10]\nEpoch 0: |          | 461/? [01:41<00:00,  4.55it/s, train/loss=1.450]\nEpoch 0: |          | 462/? [01:41<00:00,  4.55it/s, train/loss=1.450]\nEpoch 0: |          | 462/? [01:41<00:00,  4.55it/s, train/loss=14.40]\nEpoch 0: |          | 463/? [01:41<00:00,  4.55it/s, train/loss=14.40]\nEpoch 0: |          | 463/? [01:41<00:00,  4.55it/s, train/loss=1.480]\nEpoch 0: |          | 464/? [01:41<00:00,  4.55it/s, train/loss=1.480]\nEpoch 0: |          | 464/? [01:41<00:00,  4.55it/s, train/loss=11.30]\nEpoch 0: |          | 465/? [01:41<00:00,  4.56it/s, train/loss=11.30]\nEpoch 0: |          | 465/? [01:41<00:00,  4.56it/s, train/loss=1.420]\nEpoch 0: |          | 466/? [01:42<00:00,  4.56it/s, train/loss=1.420]\nEpoch 0: |          | 466/? [01:42<00:00,  4.56it/s, train/loss=27.20]\nEpoch 0: |          | 467/? [01:42<00:00,  4.57it/s, train/loss=27.20]\nEpoch 0: |          | 467/? [01:42<00:00,  4.57it/s, train/loss=1.320]\nEpoch 0: |          | 468/? [01:42<00:00,  4.56it/s, train/loss=1.320]\nEpoch 0: |          | 468/? [01:42<00:00,  4.56it/s, train/loss=30.50]\nEpoch 0: |          | 469/? [01:42<00:00,  4.57it/s, train/loss=30.50]\nEpoch 0: |          | 469/? [01:42<00:00,  4.57it/s, train/loss=1.240]\nEpoch 0: |          | 470/? [01:42<00:00,  4.57it/s, train/loss=1.240]\nEpoch 0: |          | 470/? [01:42<00:00,  4.57it/s, train/loss=14.90]\nEpoch 0: |          | 471/? [01:42<00:00,  4.58it/s, train/loss=14.90]\nEpoch 0: |          | 471/? [01:42<00:00,  4.58it/s, train/loss=1.200]\nEpoch 0: |          | 472/? [01:43<00:00,  4.57it/s, train/loss=1.200]\nEpoch 0: |          | 472/? [01:43<00:00,  4.57it/s, train/loss=12.10]\nEpoch 0: |          | 473/? [01:43<00:00,  4.58it/s, train/loss=12.10]\nEpoch 0: |          | 473/? [01:43<00:00,  4.58it/s, train/loss=1.180]\nEpoch 0: |          | 474/? [01:43<00:00,  4.58it/s, train/loss=1.180]\nEpoch 0: |          | 474/? [01:43<00:00,  4.58it/s, train/loss=41.20]\nEpoch 0: |          | 475/? [01:43<00:00,  4.59it/s, train/loss=41.20]\nEpoch 0: |          | 475/? [01:43<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 476/? [01:43<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 476/? [01:43<00:00,  4.59it/s, train/loss=29.90]\nEpoch 0: |          | 477/? [01:43<00:00,  4.59it/s, train/loss=29.90]\nEpoch 0: |          | 477/? [01:43<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 478/? [01:44<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 478/? [01:44<00:00,  4.59it/s, train/loss=25.50]\nEpoch 0: |          | 479/? [01:44<00:00,  4.60it/s, train/loss=25.50]\nEpoch 0: |          | 479/? [01:44<00:00,  4.60it/s, train/loss=1.160]\nEpoch 0: |          | 480/? [01:44<00:00,  4.60it/s, train/loss=1.160]\nEpoch 0: |          | 480/? [01:44<00:00,  4.60it/s, train/loss=8.880]\nEpoch 0: |          | 481/? [01:44<00:00,  4.60it/s, train/loss=8.880]\nEpoch 0: |          | 481/? [01:44<00:00,  4.60it/s, train/loss=1.140]\nEpoch 0: |          | 482/? [01:44<00:00,  4.60it/s, train/loss=1.140]\nEpoch 0: |          | 482/? [01:44<00:00,  4.60it/s, train/loss=17.90]\nEpoch 0: |          | 483/? [01:44<00:00,  4.61it/s, train/loss=17.90]\nEpoch 0: |          | 483/? [01:44<00:00,  4.61it/s, train/loss=1.110]\nEpoch 0: |          | 484/? [01:45<00:00,  4.61it/s, train/loss=1.110]\nEpoch 0: |          | 484/? [01:45<00:00,  4.61it/s, train/loss=32.30]\nEpoch 0: |          | 485/? [01:45<00:00,  4.62it/s, train/loss=32.30]\nEpoch 0: |          | 485/? [01:45<00:00,  4.62it/s, train/loss=1.080]\nEpoch 0: |          | 486/? [01:45<00:00,  4.61it/s, train/loss=1.080]\nEpoch 0: |          | 486/? [01:45<00:00,  4.61it/s, train/loss=22.40]\nEpoch 0: |          | 487/? [01:45<00:00,  4.62it/s, train/loss=22.40]\nEpoch 0: |          | 487/? [01:45<00:00,  4.62it/s, train/loss=1.080]\nEpoch 0: |          | 488/? [01:45<00:00,  4.62it/s, train/loss=1.080]\nEpoch 0: |          | 488/? [01:45<00:00,  4.62it/s, train/loss=19.40]\nEpoch 0: |          | 489/? [01:45<00:00,  4.63it/s, train/loss=19.40]\nEpoch 0: |          | 489/? [01:45<00:00,  4.63it/s, train/loss=1.080]\nEpoch 0: |          | 490/? [01:45<00:00,  4.62it/s, train/loss=1.080]\nEpoch 0: |          | 490/? [01:45<00:00,  4.62it/s, train/loss=22.90]\nEpoch 0: |          | 491/? [01:46<00:00,  4.63it/s, train/loss=22.90]\nEpoch 0: |          | 491/? [01:46<00:00,  4.63it/s, train/loss=1.080]\nEpoch 0: |          | 492/? [01:46<00:00,  4.63it/s, train/loss=1.080]\nEpoch 0: |          | 492/? [01:46<00:00,  4.63it/s, train/loss=24.60]\nEpoch 0: |          | 493/? [01:46<00:00,  4.64it/s, train/loss=24.60]\nEpoch 0: |          | 493/? [01:46<00:00,  4.64it/s, train/loss=1.080]\nEpoch 0: |          | 494/? [01:46<00:00,  4.63it/s, train/loss=1.080]\nEpoch 0: |          | 494/? [01:46<00:00,  4.63it/s, train/loss=29.80]\nEpoch 0: |          | 495/? [01:46<00:00,  4.64it/s, train/loss=29.80]\nEpoch 0: |          | 495/? [01:46<00:00,  4.64it/s, train/loss=1.100]\nEpoch 0: |          | 496/? [01:46<00:00,  4.64it/s, train/loss=1.100]\nEpoch 0: |          | 496/? [01:46<00:00,  4.64it/s, train/loss=31.80]\nEpoch 0: |          | 497/? [01:46<00:00,  4.65it/s, train/loss=31.80]\nEpoch 0: |          | 497/? [01:46<00:00,  4.65it/s, train/loss=1.130]\nEpoch 0: |          | 498/? [01:47<00:00,  4.64it/s, train/loss=1.130]\nEpoch 0: |          | 498/? [01:47<00:00,  4.64it/s, train/loss=11.90]\nEpoch 0: |          | 499/? [01:47<00:00,  4.65it/s, train/loss=11.90]\nEpoch 0: |          | 499/? [01:47<00:00,  4.65it/s, train/loss=1.140]\nEpoch 0: |          | 500/? [01:47<00:00,  4.65it/s, train/loss=1.140]\nEpoch 0: |          | 500/? [01:47<00:00,  4.65it/s, train/loss=31.60]\nEpoch 0: |          | 501/? [01:47<00:00,  4.66it/s, train/loss=31.60]\nEpoch 0: |          | 501/? [01:47<00:00,  4.66it/s, train/loss=1.140]\nEpoch 0: |          | 502/? [01:47<00:00,  4.65it/s, train/loss=1.140]\nEpoch 0: |          | 502/? [01:47<00:00,  4.65it/s, train/loss=56.30]\nEpoch 0: |          | 503/? [01:47<00:00,  4.66it/s, train/loss=56.30]\nEpoch 0: |          | 503/? [01:47<00:00,  4.66it/s, train/loss=1.150]\nEpoch 0: |          | 504/? [01:48<00:00,  4.66it/s, train/loss=1.150]\nEpoch 0: |          | 504/? [01:48<00:00,  4.66it/s, train/loss=45.80]\nEpoch 0: |          | 505/? [01:48<00:00,  4.67it/s, train/loss=45.80]\nEpoch 0: |          | 505/? [01:48<00:00,  4.67it/s, train/loss=1.150]\nEpoch 0: |          | 506/? [01:48<00:00,  4.66it/s, train/loss=1.150]\nEpoch 0: |          | 506/? [01:48<00:00,  4.66it/s, train/loss=10.50]\nEpoch 0: |          | 507/? [01:48<00:00,  4.67it/s, train/loss=10.50]\nEpoch 0: |          | 507/? [01:48<00:00,  4.67it/s, train/loss=1.150]\nEpoch 0: |          | 508/? [01:48<00:00,  4.67it/s, train/loss=1.150]\nEpoch 0: |          | 508/? [01:48<00:00,  4.67it/s, train/loss=33.40]\nEpoch 0: |          | 509/? [01:48<00:00,  4.68it/s, train/loss=33.40]\nEpoch 0: |          | 509/? [01:48<00:00,  4.68it/s, train/loss=1.140]\nEpoch 0: |          | 510/? [01:49<00:00,  4.67it/s, train/loss=1.140]\nEpoch 0: |          | 510/? [01:49<00:00,  4.67it/s, train/loss=16.90]\nEpoch 0: |          | 511/? [01:49<00:00,  4.68it/s, train/loss=16.90]\nEpoch 0: |          | 511/? [01:49<00:00,  4.68it/s, train/loss=1.140]\nEpoch 0: |          | 512/? [01:49<00:00,  4.68it/s, train/loss=1.140]\nEpoch 0: |          | 512/? [01:49<00:00,  4.68it/s, train/loss=26.30]\nEpoch 0: |          | 513/? [01:49<00:00,  4.69it/s, train/loss=26.30]\nEpoch 0: |          | 513/? [01:49<00:00,  4.69it/s, train/loss=1.150]\nEpoch 0: |          | 514/? [01:49<00:00,  4.69it/s, train/loss=1.150]\nEpoch 0: |          | 514/? [01:49<00:00,  4.68it/s, train/loss=15.90]\nEpoch 0: |          | 515/? [01:49<00:00,  4.69it/s, train/loss=15.90]\nEpoch 0: |          | 515/? [01:49<00:00,  4.69it/s, train/loss=1.170]\nEpoch 0: |          | 516/? [01:50<00:00,  4.69it/s, train/loss=1.170]\nEpoch 0: |          | 516/? [01:50<00:00,  4.69it/s, train/loss=29.20]\nEpoch 0: |          | 517/? [01:50<00:00,  4.70it/s, train/loss=29.20]\nEpoch 0: |          | 517/? [01:50<00:00,  4.70it/s, train/loss=1.210]\nEpoch 0: |          | 518/? [01:50<00:00,  4.69it/s, train/loss=1.210]\nEpoch 0: |          | 518/? [01:50<00:00,  4.69it/s, train/loss=35.40]\nEpoch 0: |          | 519/? [01:50<00:00,  4.70it/s, train/loss=35.40]\nEpoch 0: |          | 519/? [01:50<00:00,  4.70it/s, train/loss=1.210]\nEpoch 0: |          | 520/? [01:50<00:00,  4.70it/s, train/loss=1.210]\nEpoch 0: |          | 520/? [01:50<00:00,  4.70it/s, train/loss=31.80]\nEpoch 0: |          | 521/? [01:50<00:00,  4.71it/s, train/loss=31.80]\nEpoch 0: |          | 521/? [01:50<00:00,  4.71it/s, train/loss=1.160]\nEpoch 0: |          | 522/? [01:50<00:00,  4.70it/s, train/loss=1.160]\nEpoch 0: |          | 522/? [01:50<00:00,  4.70it/s, train/loss=28.70]\nEpoch 0: |          | 523/? [01:50<00:00,  4.71it/s, train/loss=28.70]\nEpoch 0: |          | 523/? [01:50<00:00,  4.71it/s, train/loss=1.140]\nEpoch 0: |          | 524/? [01:51<00:00,  4.71it/s, train/loss=1.140]\nEpoch 0: |          | 524/? [01:51<00:00,  4.71it/s, train/loss=26.10]\nEpoch 0: |          | 525/? [01:51<00:00,  4.72it/s, train/loss=26.10]\nEpoch 0: |          | 525/? [01:51<00:00,  4.72it/s, train/loss=1.160]\nEpoch 0: |          | 526/? [01:51<00:00,  4.71it/s, train/loss=1.160]\nEpoch 0: |          | 526/? [01:51<00:00,  4.71it/s, train/loss=21.50]\nEpoch 0: |          | 527/? [01:51<00:00,  4.72it/s, train/loss=21.50]\nEpoch 0: |          | 527/? [01:51<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 528/? [01:51<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 528/? [01:51<00:00,  4.72it/s, train/loss=27.90]\nEpoch 0: |          | 529/? [01:51<00:00,  4.73it/s, train/loss=27.90]\nEpoch 0: |          | 529/? [01:51<00:00,  4.73it/s, train/loss=1.250]\nEpoch 0: |          | 530/? [01:52<00:00,  4.72it/s, train/loss=1.250]\nEpoch 0: |          | 530/? [01:52<00:00,  4.72it/s, train/loss=14.70]\nEpoch 0: |          | 531/? [01:52<00:00,  4.73it/s, train/loss=14.70]\nEpoch 0: |          | 531/? [01:52<00:00,  4.73it/s, train/loss=1.250]\nEpoch 0: |          | 532/? [01:52<00:00,  4.73it/s, train/loss=1.250]\nEpoch 0: |          | 532/? [01:52<00:00,  4.73it/s, train/loss=23.20]\nEpoch 0: |          | 533/? [01:52<00:00,  4.74it/s, train/loss=23.20]\nEpoch 0: |          | 533/? [01:52<00:00,  4.74it/s, train/loss=1.240]\nEpoch 0: |          | 534/? [01:52<00:00,  4.73it/s, train/loss=1.240]\nEpoch 0: |          | 534/? [01:52<00:00,  4.73it/s, train/loss=12.80]\nEpoch 0: |          | 535/? [01:52<00:00,  4.74it/s, train/loss=12.80]\nEpoch 0: |          | 535/? [01:52<00:00,  4.74it/s, train/loss=1.230]\nEpoch 0: |          | 536/? [01:53<00:00,  4.74it/s, train/loss=1.230]\nEpoch 0: |          | 536/? [01:53<00:00,  4.74it/s, train/loss=44.10]\nEpoch 0: |          | 537/? [01:53<00:00,  4.75it/s, train/loss=44.10]\nEpoch 0: |          | 537/? [01:53<00:00,  4.75it/s, train/loss=1.210]\nEpoch 0: |          | 538/? [01:53<00:00,  4.74it/s, train/loss=1.210]\nEpoch 0: |          | 538/? [01:53<00:00,  4.74it/s, train/loss=16.80]\nEpoch 0: |          | 539/? [01:53<00:00,  4.75it/s, train/loss=16.80]\nEpoch 0: |          | 539/? [01:53<00:00,  4.75it/s, train/loss=1.200]\nEpoch 0: |          | 540/? [01:53<00:00,  4.75it/s, train/loss=1.200]\nEpoch 0: |          | 540/? [01:53<00:00,  4.75it/s, train/loss=16.80]\nEpoch 0: |          | 541/? [01:53<00:00,  4.76it/s, train/loss=16.80]\nEpoch 0: |          | 541/? [01:53<00:00,  4.76it/s, train/loss=1.190]\nEpoch 0: |          | 542/? [01:54<00:00,  4.75it/s, train/loss=1.190]\nEpoch 0: |          | 542/? [01:54<00:00,  4.75it/s, train/loss=17.30]\nEpoch 0: |          | 543/? [01:54<00:00,  4.76it/s, train/loss=17.30]\nEpoch 0: |          | 543/? [01:54<00:00,  4.76it/s, train/loss=1.170]\nEpoch 0: |          | 544/? [01:54<00:00,  4.76it/s, train/loss=1.170]\nEpoch 0: |          | 544/? [01:54<00:00,  4.76it/s, train/loss=12.40]\nEpoch 0: |          | 545/? [01:54<00:00,  4.76it/s, train/loss=12.40]\nEpoch 0: |          | 545/? [01:54<00:00,  4.76it/s, train/loss=1.170]\nEpoch 0: |          | 546/? [01:54<00:00,  4.76it/s, train/loss=1.170]\nEpoch 0: |          | 546/? [01:54<00:00,  4.76it/s, train/loss=25.30]\nEpoch 0: |          | 547/? [01:54<00:00,  4.76it/s, train/loss=25.30]\nEpoch 0: |          | 547/? [01:54<00:00,  4.76it/s, train/loss=1.150]\nEpoch 0: |          | 548/? [01:55<00:00,  4.76it/s, train/loss=1.150]\nEpoch 0: |          | 548/? [01:55<00:00,  4.76it/s, train/loss=25.90]\nEpoch 0: |          | 549/? [01:55<00:00,  4.76it/s, train/loss=25.90]\nEpoch 0: |          | 549/? [01:55<00:00,  4.76it/s, train/loss=1.110]\nEpoch 0: |          | 550/? [01:55<00:00,  4.76it/s, train/loss=1.110]\nEpoch 0: |          | 550/? [01:55<00:00,  4.76it/s, train/loss=17.80]\nEpoch 0: |          | 551/? [01:55<00:00,  4.77it/s, train/loss=17.80]\nEpoch 0: |          | 551/? [01:55<00:00,  4.77it/s, train/loss=1.070]\nEpoch 0: |          | 552/? [01:55<00:00,  4.77it/s, train/loss=1.070]\nEpoch 0: |          | 552/? [01:55<00:00,  4.77it/s, train/loss=36.40]\nEpoch 0: |          | 553/? [01:55<00:00,  4.77it/s, train/loss=36.40]\nEpoch 0: |          | 553/? [01:55<00:00,  4.77it/s, train/loss=1.030]\nEpoch 0: |          | 554/? [01:56<00:00,  4.77it/s, train/loss=1.030]\nEpoch 0: |          | 554/? [01:56<00:00,  4.77it/s, train/loss=16.90]\nEpoch 0: |          | 555/? [01:56<00:00,  4.78it/s, train/loss=16.90]\nEpoch 0: |          | 555/? [01:56<00:00,  4.78it/s, train/loss=1.020]\nEpoch 0: |          | 556/? [01:56<00:00,  4.77it/s, train/loss=1.020]\nEpoch 0: |          | 556/? [01:56<00:00,  4.77it/s, train/loss=20.60]\nEpoch 0: |          | 557/? [01:56<00:00,  4.78it/s, train/loss=20.60]\nEpoch 0: |          | 557/? [01:56<00:00,  4.78it/s, train/loss=1.010]\nEpoch 0: |          | 558/? [01:56<00:00,  4.78it/s, train/loss=1.010]\nEpoch 0: |          | 558/? [01:56<00:00,  4.78it/s, train/loss=28.10]\nEpoch 0: |          | 559/? [01:56<00:00,  4.78it/s, train/loss=28.10]\nEpoch 0: |          | 559/? [01:56<00:00,  4.78it/s, train/loss=1.020]\nEpoch 0: |          | 560/? [01:57<00:00,  4.77it/s, train/loss=1.020]\nEpoch 0: |          | 560/? [01:57<00:00,  4.77it/s, train/loss=37.20]\nEpoch 0: |          | 561/? [01:57<00:00,  4.78it/s, train/loss=37.20]\nEpoch 0: |          | 561/? [01:57<00:00,  4.78it/s, train/loss=1.030]\nEpoch 0: |          | 562/? [01:57<00:00,  4.77it/s, train/loss=1.030]\nEpoch 0: |          | 562/? [01:57<00:00,  4.77it/s, train/loss=10.80]\nEpoch 0: |          | 563/? [01:57<00:00,  4.78it/s, train/loss=10.80]\nEpoch 0: |          | 563/? [01:57<00:00,  4.78it/s, train/loss=1.050]\nEpoch 0: |          | 564/? [01:58<00:00,  4.77it/s, train/loss=1.050]\nEpoch 0: |          | 564/? [01:58<00:00,  4.77it/s, train/loss=23.20]\nEpoch 0: |          | 565/? [01:58<00:00,  4.77it/s, train/loss=23.20]\nEpoch 0: |          | 565/? [01:58<00:00,  4.77it/s, train/loss=1.080]\nEpoch 0: |          | 566/? [01:58<00:00,  4.77it/s, train/loss=1.080]\nEpoch 0: |          | 566/? [01:58<00:00,  4.77it/s, train/loss=23.40]\nEpoch 0: |          | 567/? [01:58<00:00,  4.77it/s, train/loss=23.40]\nEpoch 0: |          | 567/? [01:58<00:00,  4.77it/s, train/loss=1.130]\nEpoch 0: |          | 568/? [01:59<00:00,  4.77it/s, train/loss=1.130]\nEpoch 0: |          | 568/? [01:59<00:00,  4.77it/s, train/loss=53.80]\nEpoch 0: |          | 569/? [01:59<00:00,  4.77it/s, train/loss=53.80]\nEpoch 0: |          | 569/? [01:59<00:00,  4.77it/s, train/loss=1.140]\nEpoch 0: |          | 570/? [01:59<00:00,  4.77it/s, train/loss=1.140]\nEpoch 0: |          | 570/? [01:59<00:00,  4.77it/s, train/loss=18.30]\nEpoch 0: |          | 571/? [01:59<00:00,  4.77it/s, train/loss=18.30]\nEpoch 0: |          | 571/? [01:59<00:00,  4.77it/s, train/loss=1.120]\nEpoch 0: |          | 572/? [02:00<00:00,  4.76it/s, train/loss=1.120]\nEpoch 0: |          | 572/? [02:00<00:00,  4.76it/s, train/loss=11.50]\nEpoch 0: |          | 573/? [02:00<00:00,  4.77it/s, train/loss=11.50]\nEpoch 0: |          | 573/? [02:00<00:00,  4.77it/s, train/loss=1.090]\nEpoch 0: |          | 574/? [02:00<00:00,  4.76it/s, train/loss=1.090]\nEpoch 0: |          | 574/? [02:00<00:00,  4.76it/s, train/loss=15.20]\nEpoch 0: |          | 575/? [02:00<00:00,  4.77it/s, train/loss=15.20]\nEpoch 0: |          | 575/? [02:00<00:00,  4.77it/s, train/loss=1.060]\nEpoch 0: |          | 576/? [02:00<00:00,  4.76it/s, train/loss=1.060]\nEpoch 0: |          | 576/? [02:00<00:00,  4.76it/s, train/loss=33.00]\nEpoch 0: |          | 577/? [02:01<00:00,  4.77it/s, train/loss=33.00]\nEpoch 0: |          | 577/? [02:01<00:00,  4.77it/s, train/loss=1.060]\nEpoch 0: |          | 578/? [02:01<00:00,  4.76it/s, train/loss=1.060]\nEpoch 0: |          | 578/? [02:01<00:00,  4.76it/s, train/loss=21.20]\nEpoch 0: |          | 579/? [02:01<00:00,  4.76it/s, train/loss=21.20]\nEpoch 0: |          | 579/? [02:01<00:00,  4.76it/s, train/loss=1.090]\nEpoch 0: |          | 580/? [02:01<00:00,  4.76it/s, train/loss=1.090]\nEpoch 0: |          | 580/? [02:01<00:00,  4.76it/s, train/loss=83.40]\nEpoch 0: |          | 581/? [02:02<00:00,  4.76it/s, train/loss=83.40]\nEpoch 0: |          | 581/? [02:02<00:00,  4.76it/s, train/loss=1.160]\nEpoch 0: |          | 582/? [02:02<00:00,  4.76it/s, train/loss=1.160]\nEpoch 0: |          | 582/? [02:02<00:00,  4.76it/s, train/loss=19.10]\nEpoch 0: |          | 583/? [02:02<00:00,  4.76it/s, train/loss=19.10]\nEpoch 0: |          | 583/? [02:02<00:00,  4.76it/s, train/loss=1.240]\nEpoch 0: |          | 584/? [02:02<00:00,  4.75it/s, train/loss=1.240]\nEpoch 0: |          | 584/? [02:02<00:00,  4.75it/s, train/loss=60.20]\nEpoch 0: |          | 585/? [02:02<00:00,  4.76it/s, train/loss=60.20]\nEpoch 0: |          | 585/? [02:02<00:00,  4.76it/s, train/loss=1.230]\nEpoch 0: |          | 586/? [02:03<00:00,  4.75it/s, train/loss=1.230]\nEpoch 0: |          | 586/? [02:03<00:00,  4.75it/s, train/loss=21.30]\nEpoch 0: |          | 587/? [02:03<00:00,  4.76it/s, train/loss=21.30]\nEpoch 0: |          | 587/? [02:03<00:00,  4.76it/s, train/loss=1.210]\nEpoch 0: |          | 588/? [02:03<00:00,  4.75it/s, train/loss=1.210]\nEpoch 0: |          | 588/? [02:03<00:00,  4.75it/s, train/loss=32.10]\nEpoch 0: |          | 589/? [02:03<00:00,  4.76it/s, train/loss=32.10]\nEpoch 0: |          | 589/? [02:03<00:00,  4.76it/s, train/loss=1.240]\nEpoch 0: |          | 590/? [02:04<00:00,  4.75it/s, train/loss=1.240]\nEpoch 0: |          | 590/? [02:04<00:00,  4.75it/s, train/loss=28.90]\nEpoch 0: |          | 591/? [02:04<00:00,  4.76it/s, train/loss=28.90]\nEpoch 0: |          | 591/? [02:04<00:00,  4.76it/s, train/loss=1.270]\nEpoch 0: |          | 592/? [02:04<00:00,  4.75it/s, train/loss=1.270]\nEpoch 0: |          | 592/? [02:04<00:00,  4.75it/s, train/loss=12.50]\nEpoch 0: |          | 593/? [02:04<00:00,  4.76it/s, train/loss=12.50]\nEpoch 0: |          | 593/? [02:04<00:00,  4.76it/s, train/loss=1.260]\nEpoch 0: |          | 594/? [02:04<00:00,  4.76it/s, train/loss=1.260]\nEpoch 0: |          | 594/? [02:04<00:00,  4.76it/s, train/loss=24.00]\nEpoch 0: |          | 595/? [02:04<00:00,  4.77it/s, train/loss=24.00]\nEpoch 0: |          | 595/? [02:04<00:00,  4.77it/s, train/loss=1.230]\nEpoch 0: |          | 596/? [02:05<00:00,  4.76it/s, train/loss=1.230]\nEpoch 0: |          | 596/? [02:05<00:00,  4.76it/s, train/loss=15.00]\nEpoch 0: |          | 597/? [02:05<00:00,  4.77it/s, train/loss=15.00]\nEpoch 0: |          | 597/? [02:05<00:00,  4.77it/s, train/loss=1.210]\nEpoch 0: |          | 598/? [02:05<00:00,  4.77it/s, train/loss=1.210]\nEpoch 0: |          | 598/? [02:05<00:00,  4.77it/s, train/loss=10.30]\nEpoch 0: |          | 599/? [02:05<00:00,  4.77it/s, train/loss=10.30]\nEpoch 0: |          | 599/? [02:05<00:00,  4.77it/s, train/loss=1.200]\nEpoch 0: |          | 600/? [02:05<00:00,  4.77it/s, train/loss=1.200]\nEpoch 0: |          | 600/? [02:05<00:00,  4.77it/s, train/loss=21.10]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:06,  5.79it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:06,  5.50it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:06,  5.39it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:06,  5.34it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:06,  5.42it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:01<00:06,  5.44it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:01<00:06,  5.47it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:01<00:05,  5.50it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:01<00:05,  5.53it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:01<00:05,  5.57it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:01<00:05,  5.60it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:02<00:04,  5.62it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:02<00:04,  5.60it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:02<00:04,  5.58it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:02<00:04,  5.55it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:02<00:04,  5.53it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:03<00:04,  5.51it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:03<00:04,  5.49it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:03<00:03,  5.48it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:03<00:03,  5.47it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:03<00:03,  5.46it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:04<00:03,  5.46it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:04<00:03,  5.47it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:04<00:02,  5.46it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:04<00:02,  5.46it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:04<00:02,  5.46it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:04<00:02,  5.45it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:05<00:02,  5.45it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:05<00:02,  5.45it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:05<00:01,  5.45it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:05<00:01,  5.45it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:05<00:01,  5.46it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:06<00:01,  5.46it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:06<00:01,  5.48it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:06<00:00,  5.49it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:06<00:00,  5.48it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:06<00:00,  5.48it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:06<00:00,  5.49it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:07<00:00,  5.50it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:07<00:00,  5.51it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 600/? [02:13<00:00,  4.48it/s, train/loss=21.10]\nEpoch 0: |          | 601/? [02:14<00:00,  4.47it/s, train/loss=21.10]\nEpoch 0: |          | 601/? [02:14<00:00,  4.47it/s, train/loss=1.190]\nEpoch 0: |          | 602/? [02:14<00:00,  4.47it/s, train/loss=1.190]\nEpoch 0: |          | 602/? [02:14<00:00,  4.47it/s, train/loss=34.40]\nEpoch 0: |          | 603/? [02:14<00:00,  4.48it/s, train/loss=34.40]\nEpoch 0: |          | 603/? [02:14<00:00,  4.48it/s, train/loss=1.200]\nEpoch 0: |          | 604/? [02:14<00:00,  4.47it/s, train/loss=1.200]\nEpoch 0: |          | 604/? [02:14<00:00,  4.47it/s, train/loss=17.70]\nEpoch 0: |          | 605/? [02:15<00:00,  4.48it/s, train/loss=17.70]\nEpoch 0: |          | 605/? [02:15<00:00,  4.48it/s, train/loss=1.220]\nEpoch 0: |          | 606/? [02:15<00:00,  4.48it/s, train/loss=1.220]\nEpoch 0: |          | 606/? [02:15<00:00,  4.48it/s, train/loss=21.60]\nEpoch 0: |          | 607/? [02:15<00:00,  4.49it/s, train/loss=21.60]\nEpoch 0: |          | 607/? [02:15<00:00,  4.49it/s, train/loss=1.190]\nEpoch 0: |          | 608/? [02:15<00:00,  4.48it/s, train/loss=1.190]\nEpoch 0: |          | 608/? [02:15<00:00,  4.48it/s, train/loss=21.10]\nEpoch 0: |          | 609/? [02:15<00:00,  4.49it/s, train/loss=21.10]\nEpoch 0: |          | 609/? [02:15<00:00,  4.49it/s, train/loss=1.120]\nEpoch 0: |          | 610/? [02:15<00:00,  4.49it/s, train/loss=1.120]\nEpoch 0: |          | 610/? [02:15<00:00,  4.49it/s, train/loss=23.20]\nEpoch 0: |          | 611/? [02:15<00:00,  4.49it/s, train/loss=23.20]\nEpoch 0: |          | 611/? [02:15<00:00,  4.49it/s, train/loss=1.070]\nEpoch 0: |          | 612/? [02:16<00:00,  4.49it/s, train/loss=1.070]\nEpoch 0: |          | 612/? [02:16<00:00,  4.49it/s, train/loss=24.80]\nEpoch 0: |          | 613/? [02:16<00:00,  4.50it/s, train/loss=24.80]\nEpoch 0: |          | 613/? [02:16<00:00,  4.50it/s, train/loss=1.040]\nEpoch 0: |          | 614/? [02:16<00:00,  4.50it/s, train/loss=1.040]\nEpoch 0: |          | 614/? [02:16<00:00,  4.50it/s, train/loss=12.10]\nEpoch 0: |          | 615/? [02:16<00:00,  4.50it/s, train/loss=12.10]\nEpoch 0: |          | 615/? [02:16<00:00,  4.50it/s, train/loss=1.030]\nEpoch 0: |          | 616/? [02:16<00:00,  4.50it/s, train/loss=1.030]\nEpoch 0: |          | 616/? [02:16<00:00,  4.50it/s, train/loss=43.70]\nEpoch 0: |          | 617/? [02:16<00:00,  4.51it/s, train/loss=43.70]\nEpoch 0: |          | 617/? [02:16<00:00,  4.51it/s, train/loss=1.050]\nEpoch 0: |          | 618/? [02:17<00:00,  4.51it/s, train/loss=1.050]\nEpoch 0: |          | 618/? [02:17<00:00,  4.51it/s, train/loss=19.50]\nEpoch 0: |          | 619/? [02:17<00:00,  4.51it/s, train/loss=19.50]\nEpoch 0: |          | 619/? [02:17<00:00,  4.51it/s, train/loss=1.090]\nEpoch 0: |          | 620/? [02:17<00:00,  4.51it/s, train/loss=1.090]\nEpoch 0: |          | 620/? [02:17<00:00,  4.51it/s, train/loss=31.00]\nEpoch 0: |          | 621/? [02:17<00:00,  4.52it/s, train/loss=31.00]\nEpoch 0: |          | 621/? [02:17<00:00,  4.52it/s, train/loss=1.130]\nEpoch 0: |          | 622/? [02:17<00:00,  4.52it/s, train/loss=1.130]\nEpoch 0: |          | 622/? [02:17<00:00,  4.52it/s, train/loss=18.60]\nEpoch 0: |          | 623/? [02:17<00:00,  4.52it/s, train/loss=18.60]\nEpoch 0: |          | 623/? [02:17<00:00,  4.52it/s, train/loss=1.170]\nEpoch 0: |          | 624/? [02:18<00:00,  4.52it/s, train/loss=1.170]\nEpoch 0: |          | 624/? [02:18<00:00,  4.52it/s, train/loss=16.00]\nEpoch 0: |          | 625/? [02:18<00:00,  4.53it/s, train/loss=16.00]\nEpoch 0: |          | 625/? [02:18<00:00,  4.53it/s, train/loss=1.190]\nEpoch 0: |          | 626/? [02:18<00:00,  4.52it/s, train/loss=1.190]\nEpoch 0: |          | 626/? [02:18<00:00,  4.52it/s, train/loss=38.30]\nEpoch 0: |          | 627/? [02:18<00:00,  4.53it/s, train/loss=38.30]\nEpoch 0: |          | 627/? [02:18<00:00,  4.53it/s, train/loss=1.220]\nEpoch 0: |          | 628/? [02:18<00:00,  4.53it/s, train/loss=1.220]\nEpoch 0: |          | 628/? [02:18<00:00,  4.53it/s, train/loss=27.00]\nEpoch 0: |          | 629/? [02:18<00:00,  4.53it/s, train/loss=27.00]\nEpoch 0: |          | 629/? [02:18<00:00,  4.53it/s, train/loss=1.220]\nEpoch 0: |          | 630/? [02:18<00:00,  4.53it/s, train/loss=1.220]\nEpoch 0: |          | 630/? [02:18<00:00,  4.53it/s, train/loss=23.60]\nEpoch 0: |          | 631/? [02:19<00:00,  4.54it/s, train/loss=23.60]\nEpoch 0: |          | 631/? [02:19<00:00,  4.54it/s, train/loss=1.170]\nEpoch 0: |          | 632/? [02:19<00:00,  4.54it/s, train/loss=1.170]\nEpoch 0: |          | 632/? [02:19<00:00,  4.54it/s, train/loss=9.630]\nEpoch 0: |          | 633/? [02:19<00:00,  4.54it/s, train/loss=9.630]\nEpoch 0: |          | 633/? [02:19<00:00,  4.54it/s, train/loss=1.140]\nEpoch 0: |          | 634/? [02:19<00:00,  4.54it/s, train/loss=1.140]\nEpoch 0: |          | 634/? [02:19<00:00,  4.54it/s, train/loss=78.00]\nEpoch 0: |          | 635/? [02:19<00:00,  4.55it/s, train/loss=78.00]\nEpoch 0: |          | 635/? [02:19<00:00,  4.55it/s, train/loss=1.120]\nEpoch 0: |          | 636/? [02:19<00:00,  4.55it/s, train/loss=1.120]\nEpoch 0: |          | 636/? [02:19<00:00,  4.55it/s, train/loss=11.30]\nEpoch 0: |          | 637/? [02:19<00:00,  4.55it/s, train/loss=11.30]\nEpoch 0: |          | 637/? [02:19<00:00,  4.55it/s, train/loss=1.110]\nEpoch 0: |          | 638/? [02:20<00:00,  4.55it/s, train/loss=1.110]\nEpoch 0: |          | 638/? [02:20<00:00,  4.55it/s, train/loss=18.90]\nEpoch 0: |          | 639/? [02:20<00:00,  4.56it/s, train/loss=18.90]\nEpoch 0: |          | 639/? [02:20<00:00,  4.56it/s, train/loss=1.110]\nEpoch 0: |          | 640/? [02:20<00:00,  4.55it/s, train/loss=1.110]\nEpoch 0: |          | 640/? [02:20<00:00,  4.55it/s, train/loss=26.10]\nEpoch 0: |          | 641/? [02:20<00:00,  4.56it/s, train/loss=26.10]\nEpoch 0: |          | 641/? [02:20<00:00,  4.56it/s, train/loss=1.100]\nEpoch 0: |          | 642/? [02:21<00:00,  4.55it/s, train/loss=1.100]\nEpoch 0: |          | 642/? [02:21<00:00,  4.55it/s, train/loss=14.20]\nEpoch 0: |          | 643/? [02:21<00:00,  4.56it/s, train/loss=14.20]\nEpoch 0: |          | 643/? [02:21<00:00,  4.56it/s, train/loss=1.080]\nEpoch 0: |          | 644/? [02:21<00:00,  4.55it/s, train/loss=1.080]\nEpoch 0: |          | 644/? [02:21<00:00,  4.55it/s, train/loss=40.70]\nEpoch 0: |          | 645/? [02:21<00:00,  4.56it/s, train/loss=40.70]\nEpoch 0: |          | 645/? [02:21<00:00,  4.56it/s, train/loss=1.070]\nEpoch 0: |          | 646/? [02:21<00:00,  4.55it/s, train/loss=1.070]\nEpoch 0: |          | 646/? [02:21<00:00,  4.55it/s, train/loss=32.30]\nEpoch 0: |          | 647/? [02:21<00:00,  4.56it/s, train/loss=32.30]\nEpoch 0: |          | 647/? [02:21<00:00,  4.56it/s, train/loss=1.080]\nEpoch 0: |          | 648/? [02:22<00:00,  4.56it/s, train/loss=1.080]\nEpoch 0: |          | 648/? [02:22<00:00,  4.56it/s, train/loss=38.60]\nEpoch 0: |          | 649/? [02:22<00:00,  4.56it/s, train/loss=38.60]\nEpoch 0: |          | 649/? [02:22<00:00,  4.56it/s, train/loss=1.080]\nEpoch 0: |          | 650/? [02:22<00:00,  4.56it/s, train/loss=1.080]\nEpoch 0: |          | 650/? [02:22<00:00,  4.56it/s, train/loss=26.00]\nEpoch 0: |          | 651/? [02:22<00:00,  4.57it/s, train/loss=26.00]\nEpoch 0: |          | 651/? [02:22<00:00,  4.57it/s, train/loss=1.080]\nEpoch 0: |          | 652/? [02:22<00:00,  4.57it/s, train/loss=1.080]\nEpoch 0: |          | 652/? [02:22<00:00,  4.57it/s, train/loss=40.00]\nEpoch 0: |          | 653/? [02:22<00:00,  4.57it/s, train/loss=40.00]\nEpoch 0: |          | 653/? [02:22<00:00,  4.57it/s, train/loss=1.080]\nEpoch 0: |          | 654/? [02:23<00:00,  4.57it/s, train/loss=1.080]\nEpoch 0: |          | 654/? [02:23<00:00,  4.57it/s, train/loss=32.60]\nEpoch 0: |          | 655/? [02:23<00:00,  4.58it/s, train/loss=32.60]\nEpoch 0: |          | 655/? [02:23<00:00,  4.58it/s, train/loss=1.110]\nEpoch 0: |          | 656/? [02:23<00:00,  4.57it/s, train/loss=1.110]\nEpoch 0: |          | 656/? [02:23<00:00,  4.57it/s, train/loss=13.30]\nEpoch 0: |          | 657/? [02:23<00:00,  4.58it/s, train/loss=13.30]\nEpoch 0: |          | 657/? [02:23<00:00,  4.58it/s, train/loss=1.140]\nEpoch 0: |          | 658/? [02:23<00:00,  4.58it/s, train/loss=1.140]\nEpoch 0: |          | 658/? [02:23<00:00,  4.58it/s, train/loss=41.00]\nEpoch 0: |          | 659/? [02:23<00:00,  4.58it/s, train/loss=41.00]\nEpoch 0: |          | 659/? [02:23<00:00,  4.58it/s, train/loss=1.150]\nEpoch 0: |          | 660/? [02:24<00:00,  4.58it/s, train/loss=1.150]\nEpoch 0: |          | 660/? [02:24<00:00,  4.58it/s, train/loss=13.90]\nEpoch 0: |          | 661/? [02:24<00:00,  4.59it/s, train/loss=13.90]\nEpoch 0: |          | 661/? [02:24<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 662/? [02:24<00:00,  4.59it/s, train/loss=1.170]\nEpoch 0: |          | 662/? [02:24<00:00,  4.59it/s, train/loss=81.40]\nEpoch 0: |          | 663/? [02:24<00:00,  4.59it/s, train/loss=81.40]\nEpoch 0: |          | 663/? [02:24<00:00,  4.59it/s, train/loss=1.220]\nEpoch 0: |          | 664/? [02:24<00:00,  4.59it/s, train/loss=1.220]\nEpoch 0: |          | 664/? [02:24<00:00,  4.59it/s, train/loss=12.20]\nEpoch 0: |          | 665/? [02:24<00:00,  4.60it/s, train/loss=12.20]\nEpoch 0: |          | 665/? [02:24<00:00,  4.60it/s, train/loss=1.240]\nEpoch 0: |          | 666/? [02:24<00:00,  4.59it/s, train/loss=1.240]\nEpoch 0: |          | 666/? [02:24<00:00,  4.59it/s, train/loss=26.10]\nEpoch 0: |          | 667/? [02:24<00:00,  4.60it/s, train/loss=26.10]\nEpoch 0: |          | 667/? [02:24<00:00,  4.60it/s, train/loss=1.150]\nEpoch 0: |          | 668/? [02:25<00:00,  4.60it/s, train/loss=1.150]\nEpoch 0: |          | 668/? [02:25<00:00,  4.60it/s, train/loss=38.30]\nEpoch 0: |          | 669/? [02:25<00:00,  4.60it/s, train/loss=38.30]\nEpoch 0: |          | 669/? [02:25<00:00,  4.60it/s, train/loss=1.090]\nEpoch 0: |          | 670/? [02:25<00:00,  4.60it/s, train/loss=1.090]\nEpoch 0: |          | 670/? [02:25<00:00,  4.60it/s, train/loss=25.60]\nEpoch 0: |          | 671/? [02:25<00:00,  4.61it/s, train/loss=25.60]\nEpoch 0: |          | 671/? [02:25<00:00,  4.61it/s, train/loss=1.060]\nEpoch 0: |          | 672/? [02:25<00:00,  4.61it/s, train/loss=1.060]\nEpoch 0: |          | 672/? [02:25<00:00,  4.61it/s, train/loss=14.40]\nEpoch 0: |          | 673/? [02:25<00:00,  4.61it/s, train/loss=14.40]\nEpoch 0: |          | 673/? [02:25<00:00,  4.61it/s, train/loss=1.060]\nEpoch 0: |          | 674/? [02:26<00:00,  4.61it/s, train/loss=1.060]\nEpoch 0: |          | 674/? [02:26<00:00,  4.61it/s, train/loss=20.00]\nEpoch 0: |          | 675/? [02:26<00:00,  4.62it/s, train/loss=20.00]\nEpoch 0: |          | 675/? [02:26<00:00,  4.62it/s, train/loss=1.060]\nEpoch 0: |          | 676/? [02:26<00:00,  4.61it/s, train/loss=1.060]\nEpoch 0: |          | 676/? [02:26<00:00,  4.61it/s, train/loss=18.30]\nEpoch 0: |          | 677/? [02:26<00:00,  4.62it/s, train/loss=18.30]\nEpoch 0: |          | 677/? [02:26<00:00,  4.62it/s, train/loss=1.060]\nEpoch 0: |          | 678/? [02:26<00:00,  4.62it/s, train/loss=1.060]\nEpoch 0: |          | 678/? [02:26<00:00,  4.62it/s, train/loss=46.40]\nEpoch 0: |          | 679/? [02:26<00:00,  4.62it/s, train/loss=46.40]\nEpoch 0: |          | 679/? [02:26<00:00,  4.62it/s, train/loss=1.050]\nEpoch 0: |          | 680/? [02:27<00:00,  4.62it/s, train/loss=1.050]\nEpoch 0: |          | 680/? [02:27<00:00,  4.62it/s, train/loss=14.70]\nEpoch 0: |          | 681/? [02:27<00:00,  4.63it/s, train/loss=14.70]\nEpoch 0: |          | 681/? [02:27<00:00,  4.63it/s, train/loss=1.050]\nEpoch 0: |          | 682/? [02:27<00:00,  4.63it/s, train/loss=1.050]\nEpoch 0: |          | 682/? [02:27<00:00,  4.63it/s, train/loss=29.90]\nEpoch 0: |          | 683/? [02:27<00:00,  4.63it/s, train/loss=29.90]\nEpoch 0: |          | 683/? [02:27<00:00,  4.63it/s, train/loss=1.050]\nEpoch 0: |          | 684/? [02:27<00:00,  4.63it/s, train/loss=1.050]\nEpoch 0: |          | 684/? [02:27<00:00,  4.63it/s, train/loss=20.00]\nEpoch 0: |          | 685/? [02:27<00:00,  4.64it/s, train/loss=20.00]\nEpoch 0: |          | 685/? [02:27<00:00,  4.64it/s, train/loss=1.030]\nEpoch 0: |          | 686/? [02:28<00:00,  4.63it/s, train/loss=1.030]\nEpoch 0: |          | 686/? [02:28<00:00,  4.63it/s, train/loss=23.60]\nEpoch 0: |          | 687/? [02:28<00:00,  4.64it/s, train/loss=23.60]\nEpoch 0: |          | 687/? [02:28<00:00,  4.64it/s, train/loss=1.010]\nEpoch 0: |          | 688/? [02:28<00:00,  4.64it/s, train/loss=1.010]\nEpoch 0: |          | 688/? [02:28<00:00,  4.64it/s, train/loss=18.60]\nEpoch 0: |          | 689/? [02:28<00:00,  4.64it/s, train/loss=18.60]\nEpoch 0: |          | 689/? [02:28<00:00,  4.64it/s, train/loss=0.995]\nEpoch 0: |          | 690/? [02:28<00:00,  4.64it/s, train/loss=0.995]\nEpoch 0: |          | 690/? [02:28<00:00,  4.64it/s, train/loss=21.90]\nEpoch 0: |          | 691/? [02:28<00:00,  4.65it/s, train/loss=21.90]\nEpoch 0: |          | 691/? [02:28<00:00,  4.65it/s, train/loss=0.975]\nEpoch 0: |          | 692/? [02:28<00:00,  4.65it/s, train/loss=0.975]\nEpoch 0: |          | 692/? [02:28<00:00,  4.65it/s, train/loss=37.90]\nEpoch 0: |          | 693/? [02:28<00:00,  4.65it/s, train/loss=37.90]\nEpoch 0: |          | 693/? [02:28<00:00,  4.65it/s, train/loss=0.958]\nEpoch 0: |          | 694/? [02:29<00:00,  4.65it/s, train/loss=0.958]\nEpoch 0: |          | 694/? [02:29<00:00,  4.65it/s, train/loss=23.10]\nEpoch 0: |          | 695/? [02:29<00:00,  4.66it/s, train/loss=23.10]\nEpoch 0: |          | 695/? [02:29<00:00,  4.66it/s, train/loss=0.954]\nEpoch 0: |          | 696/? [02:29<00:00,  4.65it/s, train/loss=0.954]\nEpoch 0: |          | 696/? [02:29<00:00,  4.65it/s, train/loss=32.60]\nEpoch 0: |          | 697/? [02:29<00:00,  4.66it/s, train/loss=32.60]\nEpoch 0: |          | 697/? [02:29<00:00,  4.66it/s, train/loss=0.965]\nEpoch 0: |          | 698/? [02:29<00:00,  4.66it/s, train/loss=0.965]\nEpoch 0: |          | 698/? [02:29<00:00,  4.66it/s, train/loss=23.20]\nEpoch 0: |          | 699/? [02:29<00:00,  4.66it/s, train/loss=23.20]\nEpoch 0: |          | 699/? [02:29<00:00,  4.66it/s, train/loss=0.967]\nEpoch 0: |          | 700/? [02:30<00:00,  4.66it/s, train/loss=0.967]\nEpoch 0: |          | 700/? [02:30<00:00,  4.66it/s, train/loss=41.20]\nEpoch 0: |          | 701/? [02:30<00:00,  4.67it/s, train/loss=41.20]\nEpoch 0: |          | 701/? [02:30<00:00,  4.67it/s, train/loss=0.955]\nEpoch 0: |          | 702/? [02:30<00:00,  4.67it/s, train/loss=0.955]\nEpoch 0: |          | 702/? [02:30<00:00,  4.67it/s, train/loss=24.60]\nEpoch 0: |          | 703/? [02:30<00:00,  4.67it/s, train/loss=24.60]\nEpoch 0: |          | 703/? [02:30<00:00,  4.67it/s, train/loss=0.931]\nEpoch 0: |          | 704/? [02:30<00:00,  4.67it/s, train/loss=0.931]\nEpoch 0: |          | 704/? [02:30<00:00,  4.67it/s, train/loss=8.580]\nEpoch 0: |          | 705/? [02:30<00:00,  4.68it/s, train/loss=8.580]\nEpoch 0: |          | 705/? [02:30<00:00,  4.68it/s, train/loss=0.905]\nEpoch 0: |          | 706/? [02:31<00:00,  4.67it/s, train/loss=0.905]\nEpoch 0: |          | 706/? [02:31<00:00,  4.67it/s, train/loss=20.60]\nEpoch 0: |          | 707/? [02:31<00:00,  4.68it/s, train/loss=20.60]\nEpoch 0: |          | 707/? [02:31<00:00,  4.68it/s, train/loss=0.894]\nEpoch 0: |          | 708/? [02:31<00:00,  4.68it/s, train/loss=0.894]\nEpoch 0: |          | 708/? [02:31<00:00,  4.68it/s, train/loss=23.60]\nEpoch 0: |          | 709/? [02:31<00:00,  4.68it/s, train/loss=23.60]\nEpoch 0: |          | 709/? [02:31<00:00,  4.68it/s, train/loss=0.883]\nEpoch 0: |          | 710/? [02:31<00:00,  4.68it/s, train/loss=0.883]\nEpoch 0: |          | 710/? [02:31<00:00,  4.68it/s, train/loss=14.50]\nEpoch 0: |          | 711/? [02:31<00:00,  4.68it/s, train/loss=14.50]\nEpoch 0: |          | 711/? [02:31<00:00,  4.68it/s, train/loss=0.874]\nEpoch 0: |          | 712/? [02:32<00:00,  4.68it/s, train/loss=0.874]\nEpoch 0: |          | 712/? [02:32<00:00,  4.68it/s, train/loss=16.80]\nEpoch 0: |          | 713/? [02:32<00:00,  4.68it/s, train/loss=16.80]\nEpoch 0: |          | 713/? [02:32<00:00,  4.68it/s, train/loss=0.883]\nEpoch 0: |          | 714/? [02:32<00:00,  4.68it/s, train/loss=0.883]\nEpoch 0: |          | 714/? [02:32<00:00,  4.68it/s, train/loss=28.60]\nEpoch 0: |          | 715/? [02:32<00:00,  4.68it/s, train/loss=28.60]\nEpoch 0: |          | 715/? [02:32<00:00,  4.68it/s, train/loss=0.896]\nEpoch 0: |          | 716/? [02:33<00:00,  4.68it/s, train/loss=0.896]\nEpoch 0: |          | 716/? [02:33<00:00,  4.68it/s, train/loss=13.50]\nEpoch 0: |          | 717/? [02:33<00:00,  4.68it/s, train/loss=13.50]\nEpoch 0: |          | 717/? [02:33<00:00,  4.68it/s, train/loss=0.912]\nEpoch 0: |          | 718/? [02:33<00:00,  4.68it/s, train/loss=0.912]\nEpoch 0: |          | 718/? [02:33<00:00,  4.68it/s, train/loss=24.30]\nEpoch 0: |          | 719/? [02:33<00:00,  4.69it/s, train/loss=24.30]\nEpoch 0: |          | 719/? [02:33<00:00,  4.69it/s, train/loss=0.939]\nEpoch 0: |          | 720/? [02:33<00:00,  4.68it/s, train/loss=0.939]\nEpoch 0: |          | 720/? [02:33<00:00,  4.68it/s, train/loss=27.00]\nEpoch 0: |          | 721/? [02:33<00:00,  4.69it/s, train/loss=27.00]\nEpoch 0: |          | 721/? [02:33<00:00,  4.69it/s, train/loss=0.974]\nEpoch 0: |          | 722/? [02:34<00:00,  4.69it/s, train/loss=0.974]\nEpoch 0: |          | 722/? [02:34<00:00,  4.69it/s, train/loss=36.20]\nEpoch 0: |          | 723/? [02:34<00:00,  4.69it/s, train/loss=36.20]\nEpoch 0: |          | 723/? [02:34<00:00,  4.69it/s, train/loss=0.974]\nEpoch 0: |          | 724/? [02:34<00:00,  4.69it/s, train/loss=0.974]\nEpoch 0: |          | 724/? [02:34<00:00,  4.69it/s, train/loss=20.80]\nEpoch 0: |          | 725/? [02:34<00:00,  4.70it/s, train/loss=20.80]\nEpoch 0: |          | 725/? [02:34<00:00,  4.70it/s, train/loss=0.970]\nEpoch 0: |          | 726/? [02:34<00:00,  4.69it/s, train/loss=0.970]\nEpoch 0: |          | 726/? [02:34<00:00,  4.69it/s, train/loss=20.00]\nEpoch 0: |          | 727/? [02:34<00:00,  4.70it/s, train/loss=20.00]\nEpoch 0: |          | 727/? [02:34<00:00,  4.70it/s, train/loss=0.968]\nEpoch 0: |          | 728/? [02:34<00:00,  4.70it/s, train/loss=0.968]\nEpoch 0: |          | 728/? [02:34<00:00,  4.70it/s, train/loss=12.10]\nEpoch 0: |          | 729/? [02:34<00:00,  4.70it/s, train/loss=12.10]\nEpoch 0: |          | 729/? [02:34<00:00,  4.70it/s, train/loss=0.960]\nEpoch 0: |          | 730/? [02:35<00:00,  4.70it/s, train/loss=0.960]\nEpoch 0: |          | 730/? [02:35<00:00,  4.70it/s, train/loss=19.20]\nEpoch 0: |          | 731/? [02:35<00:00,  4.71it/s, train/loss=19.20]\nEpoch 0: |          | 731/? [02:35<00:00,  4.71it/s, train/loss=0.948]\nEpoch 0: |          | 732/? [02:35<00:00,  4.71it/s, train/loss=0.948]\nEpoch 0: |          | 732/? [02:35<00:00,  4.71it/s, train/loss=18.60]\nEpoch 0: |          | 733/? [02:35<00:00,  4.71it/s, train/loss=18.60]\nEpoch 0: |          | 733/? [02:35<00:00,  4.71it/s, train/loss=0.951]\nEpoch 0: |          | 734/? [02:35<00:00,  4.71it/s, train/loss=0.951]\nEpoch 0: |          | 734/? [02:35<00:00,  4.71it/s, train/loss=12.20]\nEpoch 0: |          | 735/? [02:35<00:00,  4.71it/s, train/loss=12.20]\nEpoch 0: |          | 735/? [02:35<00:00,  4.71it/s, train/loss=0.977]\nEpoch 0: |          | 736/? [02:36<00:00,  4.71it/s, train/loss=0.977]\nEpoch 0: |          | 736/? [02:36<00:00,  4.71it/s, train/loss=37.10]\nEpoch 0: |          | 737/? [02:36<00:00,  4.72it/s, train/loss=37.10]\nEpoch 0: |          | 737/? [02:36<00:00,  4.72it/s, train/loss=1.170]\nEpoch 0: |          | 738/? [02:36<00:00,  4.72it/s, train/loss=1.170]\nEpoch 0: |          | 738/? [02:36<00:00,  4.72it/s, train/loss=22.80]\nEpoch 0: |          | 739/? [02:36<00:00,  4.72it/s, train/loss=22.80]\nEpoch 0: |          | 739/? [02:36<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 740/? [02:36<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 740/? [02:36<00:00,  4.72it/s, train/loss=29.60]\nEpoch 0: |          | 741/? [02:36<00:00,  4.72it/s, train/loss=29.60]\nEpoch 0: |          | 741/? [02:36<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 742/? [02:37<00:00,  4.72it/s, train/loss=1.210]\nEpoch 0: |          | 742/? [02:37<00:00,  4.72it/s, train/loss=35.50]\nEpoch 0: |          | 743/? [02:37<00:00,  4.73it/s, train/loss=35.50]\nEpoch 0: |          | 743/? [02:37<00:00,  4.73it/s, train/loss=1.200]\nEpoch 0: |          | 744/? [02:37<00:00,  4.73it/s, train/loss=1.200]\nEpoch 0: |          | 744/? [02:37<00:00,  4.73it/s, train/loss=42.00]\nEpoch 0: |          | 745/? [02:37<00:00,  4.73it/s, train/loss=42.00]\nEpoch 0: |          | 745/? [02:37<00:00,  4.73it/s, train/loss=1.180]\nEpoch 0: |          | 746/? [02:37<00:00,  4.73it/s, train/loss=1.180]\nEpoch 0: |          | 746/? [02:37<00:00,  4.73it/s, train/loss=34.50]\nEpoch 0: |          | 747/? [02:37<00:00,  4.74it/s, train/loss=34.50]\nEpoch 0: |          | 747/? [02:37<00:00,  4.74it/s, train/loss=1.170]\nEpoch 0: |          | 748/? [02:38<00:00,  4.73it/s, train/loss=1.170]\nEpoch 0: |          | 748/? [02:38<00:00,  4.73it/s, train/loss=29.70]\nEpoch 0: |          | 749/? [02:38<00:00,  4.74it/s, train/loss=29.70]\nEpoch 0: |          | 749/? [02:38<00:00,  4.74it/s, train/loss=1.180]\nEpoch 0: |          | 750/? [02:38<00:00,  4.74it/s, train/loss=1.180]\nEpoch 0: |          | 750/? [02:38<00:00,  4.74it/s, train/loss=29.00]\nEpoch 0: |          | 751/? [02:38<00:00,  4.74it/s, train/loss=29.00]\nEpoch 0: |          | 751/? [02:38<00:00,  4.74it/s, train/loss=1.190]\nEpoch 0: |          | 752/? [02:38<00:00,  4.74it/s, train/loss=1.190]\nEpoch 0: |          | 752/? [02:38<00:00,  4.74it/s, train/loss=17.00]\nEpoch 0: |          | 753/? [02:38<00:00,  4.75it/s, train/loss=17.00]\nEpoch 0: |          | 753/? [02:38<00:00,  4.75it/s, train/loss=1.210]\nEpoch 0: |          | 754/? [02:38<00:00,  4.74it/s, train/loss=1.210]\nEpoch 0: |          | 754/? [02:38<00:00,  4.74it/s, train/loss=7.800]\nEpoch 0: |          | 755/? [02:38<00:00,  4.75it/s, train/loss=7.800]\nEpoch 0: |          | 755/? [02:38<00:00,  4.75it/s, train/loss=1.220]\nEpoch 0: |          | 756/? [02:39<00:00,  4.75it/s, train/loss=1.220]\nEpoch 0: |          | 756/? [02:39<00:00,  4.75it/s, train/loss=35.00]\nEpoch 0: |          | 757/? [02:39<00:00,  4.75it/s, train/loss=35.00]\nEpoch 0: |          | 757/? [02:39<00:00,  4.75it/s, train/loss=1.220]\nEpoch 0: |          | 758/? [02:39<00:00,  4.75it/s, train/loss=1.220]\nEpoch 0: |          | 758/? [02:39<00:00,  4.75it/s, train/loss=15.80]\nEpoch 0: |          | 759/? [02:39<00:00,  4.76it/s, train/loss=15.80]\nEpoch 0: |          | 759/? [02:39<00:00,  4.76it/s, train/loss=1.210]\nEpoch 0: |          | 760/? [02:39<00:00,  4.75it/s, train/loss=1.210]\nEpoch 0: |          | 760/? [02:39<00:00,  4.75it/s, train/loss=19.90]\nEpoch 0: |          | 761/? [02:39<00:00,  4.76it/s, train/loss=19.90]\nEpoch 0: |          | 761/? [02:39<00:00,  4.76it/s, train/loss=1.190]\nEpoch 0: |          | 762/? [02:40<00:00,  4.76it/s, train/loss=1.190]\nEpoch 0: |          | 762/? [02:40<00:00,  4.76it/s, train/loss=27.10]\nEpoch 0: |          | 763/? [02:40<00:00,  4.76it/s, train/loss=27.10]\nEpoch 0: |          | 763/? [02:40<00:00,  4.76it/s, train/loss=1.160]\nEpoch 0: |          | 764/? [02:40<00:00,  4.76it/s, train/loss=1.160]\nEpoch 0: |          | 764/? [02:40<00:00,  4.76it/s, train/loss=19.60]\nEpoch 0: |          | 765/? [02:40<00:00,  4.77it/s, train/loss=19.60]\nEpoch 0: |          | 765/? [02:40<00:00,  4.77it/s, train/loss=1.150]\nEpoch 0: |          | 766/? [02:40<00:00,  4.76it/s, train/loss=1.150]\nEpoch 0: |          | 766/? [02:40<00:00,  4.76it/s, train/loss=23.80]\nEpoch 0: |          | 767/? [02:40<00:00,  4.77it/s, train/loss=23.80]\nEpoch 0: |          | 767/? [02:40<00:00,  4.77it/s, train/loss=1.170]\nEpoch 0: |          | 768/? [02:41<00:00,  4.77it/s, train/loss=1.170]\nEpoch 0: |          | 768/? [02:41<00:00,  4.77it/s, train/loss=35.60]\nEpoch 0: |          | 769/? [02:41<00:00,  4.77it/s, train/loss=35.60]\nEpoch 0: |          | 769/? [02:41<00:00,  4.77it/s, train/loss=1.140]\nEpoch 0: |          | 770/? [02:41<00:00,  4.77it/s, train/loss=1.140]\nEpoch 0: |          | 770/? [02:41<00:00,  4.77it/s, train/loss=41.80]\nEpoch 0: |          | 771/? [02:41<00:00,  4.78it/s, train/loss=41.80]\nEpoch 0: |          | 771/? [02:41<00:00,  4.78it/s, train/loss=1.090]\nEpoch 0: |          | 772/? [02:41<00:00,  4.77it/s, train/loss=1.090]\nEpoch 0: |          | 772/? [02:41<00:00,  4.77it/s, train/loss=15.80]\nEpoch 0: |          | 773/? [02:41<00:00,  4.78it/s, train/loss=15.80]\nEpoch 0: |          | 773/? [02:41<00:00,  4.78it/s, train/loss=1.070]\nEpoch 0: |          | 774/? [02:42<00:00,  4.78it/s, train/loss=1.070]\nEpoch 0: |          | 774/? [02:42<00:00,  4.78it/s, train/loss=16.30]\nEpoch 0: |          | 775/? [02:42<00:00,  4.78it/s, train/loss=16.30]\nEpoch 0: |          | 775/? [02:42<00:00,  4.78it/s, train/loss=1.070]\nEpoch 0: |          | 776/? [02:42<00:00,  4.78it/s, train/loss=1.070]\nEpoch 0: |          | 776/? [02:42<00:00,  4.78it/s, train/loss=22.50]\nEpoch 0: |          | 777/? [02:42<00:00,  4.79it/s, train/loss=22.50]\nEpoch 0: |          | 777/? [02:42<00:00,  4.79it/s, train/loss=1.070]\nEpoch 0: |          | 778/? [02:42<00:00,  4.78it/s, train/loss=1.070]\nEpoch 0: |          | 778/? [02:42<00:00,  4.78it/s, train/loss=15.30]\nEpoch 0: |          | 779/? [02:42<00:00,  4.78it/s, train/loss=15.30]\nEpoch 0: |          | 779/? [02:42<00:00,  4.78it/s, train/loss=1.080]\nEpoch 0: |          | 780/? [02:43<00:00,  4.78it/s, train/loss=1.080]\nEpoch 0: |          | 780/? [02:43<00:00,  4.78it/s, train/loss=7.950]\nEpoch 0: |          | 781/? [02:43<00:00,  4.78it/s, train/loss=7.950]\nEpoch 0: |          | 781/? [02:43<00:00,  4.78it/s, train/loss=1.080]\nEpoch 0: |          | 782/? [02:43<00:00,  4.78it/s, train/loss=1.080]\nEpoch 0: |          | 782/? [02:43<00:00,  4.78it/s, train/loss=11.60]\nEpoch 0: |          | 783/? [02:43<00:00,  4.79it/s, train/loss=11.60]\nEpoch 0: |          | 783/? [02:43<00:00,  4.79it/s, train/loss=1.090]\nEpoch 0: |          | 784/? [02:43<00:00,  4.78it/s, train/loss=1.090]\nEpoch 0: |          | 784/? [02:43<00:00,  4.78it/s, train/loss=52.90]\nEpoch 0: |          | 785/? [02:43<00:00,  4.79it/s, train/loss=52.90]\nEpoch 0: |          | 785/? [02:43<00:00,  4.79it/s, train/loss=1.100]\nEpoch 0: |          | 786/? [02:44<00:00,  4.79it/s, train/loss=1.100]\nEpoch 0: |          | 786/? [02:44<00:00,  4.79it/s, train/loss=25.70]\nEpoch 0: |          | 787/? [02:44<00:00,  4.79it/s, train/loss=25.70]\nEpoch 0: |          | 787/? [02:44<00:00,  4.79it/s, train/loss=1.110]\nEpoch 0: |          | 788/? [02:44<00:00,  4.79it/s, train/loss=1.110]\nEpoch 0: |          | 788/? [02:44<00:00,  4.79it/s, train/loss=15.70]\nEpoch 0: |          | 789/? [02:44<00:00,  4.79it/s, train/loss=15.70]\nEpoch 0: |          | 789/? [02:44<00:00,  4.79it/s, train/loss=1.110]\nEpoch 0: |          | 790/? [02:44<00:00,  4.79it/s, train/loss=1.110]\nEpoch 0: |          | 790/? [02:44<00:00,  4.79it/s, train/loss=15.20]\nEpoch 0: |          | 791/? [02:44<00:00,  4.80it/s, train/loss=15.20]\nEpoch 0: |          | 791/? [02:44<00:00,  4.80it/s, train/loss=1.100]\nEpoch 0: |          | 792/? [02:45<00:00,  4.79it/s, train/loss=1.100]\nEpoch 0: |          | 792/? [02:45<00:00,  4.79it/s, train/loss=21.60]\nEpoch 0: |          | 793/? [02:45<00:00,  4.80it/s, train/loss=21.60]\nEpoch 0: |          | 793/? [02:45<00:00,  4.80it/s, train/loss=1.090]\nEpoch 0: |          | 794/? [02:45<00:00,  4.80it/s, train/loss=1.090]\nEpoch 0: |          | 794/? [02:45<00:00,  4.80it/s, train/loss=11.20]\nEpoch 0: |          | 795/? [02:45<00:00,  4.80it/s, train/loss=11.20]\nEpoch 0: |          | 795/? [02:45<00:00,  4.80it/s, train/loss=1.090]\nEpoch 0: |          | 796/? [02:45<00:00,  4.80it/s, train/loss=1.090]\nEpoch 0: |          | 796/? [02:45<00:00,  4.80it/s, train/loss=8.000]\nEpoch 0: |          | 797/? [02:45<00:00,  4.80it/s, train/loss=8.000]\nEpoch 0: |          | 797/? [02:45<00:00,  4.80it/s, train/loss=1.060]\nEpoch 0: |          | 798/? [02:46<00:00,  4.80it/s, train/loss=1.060]\nEpoch 0: |          | 798/? [02:46<00:00,  4.80it/s, train/loss=19.90]\nEpoch 0: |          | 799/? [02:46<00:00,  4.81it/s, train/loss=19.90]\nEpoch 0: |          | 799/? [02:46<00:00,  4.81it/s, train/loss=1.020]\nEpoch 0: |          | 800/? [02:46<00:00,  4.81it/s, train/loss=1.020]\nEpoch 0: |          | 800/? [02:46<00:00,  4.81it/s, train/loss=19.30]\nValidation: |          | 0/? 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outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save\nRunning step 3: geometry refinement\n{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},\n'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},\n'data_type': 'dreamcraft3d-single-image-datamodule',\n'description': '',\n'exp_dir': 'outputs/dreamcraft3d-geometry',\n'exp_root_dir': 'outputs',\n'n_gpus': 1,\n'name': 'dreamcraft3d-geometry',\n 'resume': None,\n'seed': 0,\n'system': {'stage': 'geometry', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.02, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'accumulate', 'no_diff_steps': 0, 'guidance_eval': 0, 'n_rgb': 4}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_normal_consistency': 10.0, 'lambda_laplacian_smoothness': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.005, 'betas': [0.9, 0.99], 'eps': 1e-15}}, 'geometry_convert_from': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/ckpts/last.ckpt'},\n'system_type': 'dreamcraft3d-system',\n'tag': 'replicate_user',\n'timestamp': '@20240222-134756',\n'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32},\n'trial_dir': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756',\n'trial_name': 'replicate_user@20240222-134756',\n'use_timestamp': True}\nInitializing geometry from a given checkpoint ...\nLoading Deep Floyd ...\nCouldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d7509e-6347b4da73b31fa229296b6e;25483ae6-ebc7-4a7b-ac33-672d284154c2)\nCannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.\nRepo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..\nWill try to load from local cache.\nLoading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]\nLoading pipeline components...:  33%|███▎      | 1/3 [00:00<00:00,  5.14it/s]\nLoading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 13.15it/s]\nLoaded Deep Floyd!\nLoading Stable Zero123 ...\nget obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion\nLatentDiffusion: Running in eps-prediction mode\nDiffusionWrapper has 859.53 M params.\nKeeping EMAs of 688.\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\nLoaded Stable Zero123!\nUsing prompt [A green leafy plant in a striped terracotta pot] and negative prompt []\nUsing view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]\nloaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n| Name       | Type                 | Params\n----------------------------------------------------\n0 | geometry   | TetrahedraSDFGrid    | 13.7 M\n1 | material   | NoMaterial           | 0\n2 | background | SolidColorBackground | 0\n3 | renderer   | NVDiffRasterizer     | 0\n----------------------------------------------------\n13.7 M    Trainable params\n0         Non-trainable params\n13.7 M    Total params\n54.847    Total estimated model params size (MB)\nValidation results will be saved to outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\nTraining: |          | 0/? [00:00<?, ?it/s]\nTraining: |          | 0/? [00:00<?, ?it/s]\nEpoch 0: |          | 0/? [00:00<?, ?it/s] \nEpoch 0: |          | 1/? [00:00<00:00,  7.59it/s]\nEpoch 0: |          | 1/? [00:00<00:00,  7.51it/s, train/loss=21.80]\nEpoch 0: |          | 2/? [00:00<00:00,  3.74it/s, train/loss=21.80]\nEpoch 0: |          | 2/? [00:00<00:00,  3.73it/s, train/loss=32.90]\nEpoch 0: |          | 3/? [00:00<00:00,  3.50it/s, train/loss=32.90]\nEpoch 0: |          | 3/? 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[00:21<00:00,  3.10it/s, train/loss=23.90]\nEpoch 0: |          | 67/? [00:21<00:00,  3.10it/s, train/loss=23.90]\nEpoch 0: |          | 67/? [00:21<00:00,  3.10it/s, train/loss=14.50]\nEpoch 0: |          | 68/? [00:21<00:00,  3.10it/s, train/loss=14.50]\nEpoch 0: |          | 68/? [00:21<00:00,  3.10it/s, train/loss=29.40]\nEpoch 0: |          | 69/? [00:22<00:00,  3.10it/s, train/loss=29.40]\nEpoch 0: |          | 69/? [00:22<00:00,  3.10it/s, train/loss=38.10]\nEpoch 0: |          | 70/? [00:22<00:00,  3.10it/s, train/loss=38.10]\nEpoch 0: |          | 70/? [00:22<00:00,  3.10it/s, train/loss=39.80]\nEpoch 0: |          | 71/? [00:22<00:00,  3.10it/s, train/loss=39.80]\nEpoch 0: |          | 71/? [00:22<00:00,  3.10it/s, train/loss=22.10]\nEpoch 0: |          | 72/? [00:23<00:00,  3.10it/s, train/loss=22.10]\nEpoch 0: |          | 72/? [00:23<00:00,  3.10it/s, train/loss=25.50]\nEpoch 0: |          | 73/? [00:23<00:00,  3.10it/s, train/loss=25.50]\nEpoch 0: |          | 73/? [00:23<00:00,  3.10it/s, train/loss=25.70]\nEpoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=25.70]\nEpoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=18.70]\nEpoch 0: |          | 75/? [00:24<00:00,  3.10it/s, train/loss=18.70]\nEpoch 0: |          | 75/? [00:24<00:00,  3.10it/s, train/loss=25.40]\nEpoch 0: |          | 76/? [00:24<00:00,  3.10it/s, train/loss=25.40]\nEpoch 0: |          | 76/? [00:24<00:00,  3.10it/s, train/loss=22.10]\nEpoch 0: |          | 77/? [00:24<00:00,  3.10it/s, train/loss=22.10]\nEpoch 0: |          | 77/? [00:24<00:00,  3.10it/s, train/loss=33.50]\nEpoch 0: |          | 78/? [00:25<00:00,  3.08it/s, train/loss=33.50]\nEpoch 0: |          | 78/? [00:25<00:00,  3.08it/s, train/loss=13.40]\nEpoch 0: |          | 79/? [00:25<00:00,  3.06it/s, train/loss=13.40]\nEpoch 0: |          | 79/? [00:25<00:00,  3.06it/s, train/loss=9.540]\nEpoch 0: |          | 80/? [00:26<00:00,  3.05it/s, train/loss=9.540]\nEpoch 0: |          | 80/? [00:26<00:00,  3.05it/s, train/loss=13.70]\nEpoch 0: |          | 81/? [00:26<00:00,  3.04it/s, train/loss=13.70]\nEpoch 0: |          | 81/? [00:26<00:00,  3.04it/s, train/loss=32.00]\nEpoch 0: |          | 82/? [00:26<00:00,  3.04it/s, train/loss=32.00]\nEpoch 0: |          | 82/? [00:26<00:00,  3.04it/s, train/loss=23.60]\nEpoch 0: |          | 83/? [00:27<00:00,  3.05it/s, train/loss=23.60]\nEpoch 0: |          | 83/? [00:27<00:00,  3.05it/s, train/loss=27.50]\nEpoch 0: |          | 84/? [00:27<00:00,  3.05it/s, train/loss=27.50]\nEpoch 0: |          | 84/? [00:27<00:00,  3.05it/s, train/loss=41.20]\nEpoch 0: |          | 85/? [00:27<00:00,  3.04it/s, train/loss=41.20]\nEpoch 0: |          | 85/? [00:27<00:00,  3.04it/s, train/loss=31.90]\nEpoch 0: |          | 86/? [00:28<00:00,  3.05it/s, train/loss=31.90]\nEpoch 0: |          | 86/? [00:28<00:00,  3.05it/s, train/loss=10.30]\nEpoch 0: |          | 87/? [00:28<00:00,  3.05it/s, train/loss=10.30]\nEpoch 0: |          | 87/? [00:28<00:00,  3.05it/s, train/loss=30.40]\nEpoch 0: |          | 88/? [00:28<00:00,  3.05it/s, train/loss=30.40]\nEpoch 0: |          | 88/? [00:28<00:00,  3.05it/s, train/loss=27.20]\nEpoch 0: |          | 89/? [00:29<00:00,  3.05it/s, train/loss=27.20]\nEpoch 0: |          | 89/? [00:29<00:00,  3.05it/s, train/loss=36.90]\nEpoch 0: |          | 90/? [00:29<00:00,  3.04it/s, train/loss=36.90]\nEpoch 0: |          | 90/? [00:29<00:00,  3.04it/s, train/loss=15.30]\nEpoch 0: |          | 91/? [00:29<00:00,  3.04it/s, train/loss=15.30]\nEpoch 0: |          | 91/? [00:29<00:00,  3.04it/s, train/loss=25.40]\nEpoch 0: |          | 92/? [00:30<00:00,  3.04it/s, train/loss=25.40]\nEpoch 0: |          | 92/? [00:30<00:00,  3.04it/s, train/loss=18.00]\nEpoch 0: |          | 93/? [00:30<00:00,  3.04it/s, train/loss=18.00]\nEpoch 0: |          | 93/? [00:30<00:00,  3.04it/s, train/loss=30.60]\nEpoch 0: |          | 94/? [00:30<00:00,  3.04it/s, train/loss=30.60]\nEpoch 0: |          | 94/? [00:30<00:00,  3.04it/s, train/loss=22.00]\nEpoch 0: |          | 95/? [00:31<00:00,  3.04it/s, train/loss=22.00]\nEpoch 0: |          | 95/? [00:31<00:00,  3.04it/s, train/loss=13.20]\nEpoch 0: |          | 96/? [00:31<00:00,  3.05it/s, train/loss=13.20]\nEpoch 0: |          | 96/? [00:31<00:00,  3.05it/s, train/loss=28.90]\nEpoch 0: |          | 97/? [00:31<00:00,  3.04it/s, train/loss=28.90]\nEpoch 0: |          | 97/? [00:31<00:00,  3.04it/s, train/loss=43.10]\nEpoch 0: |          | 98/? [00:32<00:00,  3.04it/s, train/loss=43.10]\nEpoch 0: |          | 98/? [00:32<00:00,  3.04it/s, train/loss=24.10]\nEpoch 0: |          | 99/? [00:32<00:00,  3.04it/s, train/loss=24.10]\nEpoch 0: |          | 99/? [00:32<00:00,  3.04it/s, train/loss=35.90]\nEpoch 0: |          | 100/? [00:32<00:00,  3.04it/s, train/loss=35.90]\nEpoch 0: |          | 100/? [00:32<00:00,  3.04it/s, train/loss=54.40]\nEpoch 0: |          | 101/? [00:33<00:00,  3.04it/s, train/loss=54.40]\nEpoch 0: |          | 101/? [00:33<00:00,  3.04it/s, train/loss=39.20]\nEpoch 0: |          | 102/? [00:33<00:00,  3.02it/s, train/loss=39.20]\nEpoch 0: |          | 102/? [00:33<00:00,  3.02it/s, train/loss=26.30]\nEpoch 0: |          | 103/? [00:34<00:00,  3.01it/s, train/loss=26.30]\nEpoch 0: |          | 103/? [00:34<00:00,  3.01it/s, train/loss=11.30]\nEpoch 0: |          | 104/? [00:34<00:00,  3.00it/s, train/loss=11.30]\nEpoch 0: |          | 104/? [00:34<00:00,  3.00it/s, train/loss=16.80]\nEpoch 0: |          | 105/? [00:35<00:00,  2.99it/s, train/loss=16.80]\nEpoch 0: |          | 105/? [00:35<00:00,  2.99it/s, train/loss=28.70]\nEpoch 0: |          | 106/? [00:35<00:00,  2.98it/s, train/loss=28.70]\nEpoch 0: |          | 106/? [00:35<00:00,  2.98it/s, train/loss=24.10]\nEpoch 0: |          | 107/? [00:36<00:00,  2.97it/s, train/loss=24.10]\nEpoch 0: |          | 107/? [00:36<00:00,  2.97it/s, train/loss=25.80]\nEpoch 0: |          | 108/? [00:36<00:00,  2.95it/s, train/loss=25.80]\nEpoch 0: |          | 108/? [00:36<00:00,  2.95it/s, train/loss=35.10]\nEpoch 0: |          | 109/? [00:37<00:00,  2.94it/s, train/loss=35.10]\nEpoch 0: |          | 109/? [00:37<00:00,  2.94it/s, train/loss=34.00]\nEpoch 0: |          | 110/? [00:37<00:00,  2.95it/s, train/loss=34.00]\nEpoch 0: |          | 110/? [00:37<00:00,  2.95it/s, train/loss=10.00]\nEpoch 0: |          | 111/? [00:37<00:00,  2.95it/s, train/loss=10.00]\nEpoch 0: |          | 111/? [00:37<00:00,  2.95it/s, train/loss=18.90]\nEpoch 0: |          | 112/? [00:37<00:00,  2.95it/s, train/loss=18.90]\nEpoch 0: |          | 112/? [00:37<00:00,  2.95it/s, train/loss=16.30]\nEpoch 0: |          | 113/? [00:38<00:00,  2.95it/s, train/loss=16.30]\nEpoch 0: |          | 113/? [00:38<00:00,  2.95it/s, train/loss=26.50]\nEpoch 0: |          | 114/? [00:38<00:00,  2.95it/s, train/loss=26.50]\nEpoch 0: |          | 114/? [00:38<00:00,  2.95it/s, train/loss=23.80]\nEpoch 0: |          | 115/? [00:38<00:00,  2.95it/s, train/loss=23.80]\nEpoch 0: |          | 115/? [00:38<00:00,  2.95it/s, train/loss=19.70]\nEpoch 0: |          | 116/? [00:39<00:00,  2.95it/s, train/loss=19.70]\nEpoch 0: |          | 116/? [00:39<00:00,  2.95it/s, train/loss=28.20]\nEpoch 0: |          | 117/? [00:39<00:00,  2.95it/s, train/loss=28.20]\nEpoch 0: |          | 117/? [00:39<00:00,  2.95it/s, train/loss=26.90]\nEpoch 0: |          | 118/? [00:39<00:00,  2.95it/s, train/loss=26.90]\nEpoch 0: |          | 118/? [00:39<00:00,  2.95it/s, train/loss=12.40]\nEpoch 0: |          | 119/? [00:40<00:00,  2.95it/s, train/loss=12.40]\nEpoch 0: |          | 119/? [00:40<00:00,  2.95it/s, train/loss=25.70]\nEpoch 0: |          | 120/? [00:40<00:00,  2.96it/s, train/loss=25.70]\nEpoch 0: |          | 120/? [00:40<00:00,  2.96it/s, train/loss=15.50]\nEpoch 0: |          | 121/? [00:40<00:00,  2.96it/s, train/loss=15.50]\nEpoch 0: |          | 121/? [00:40<00:00,  2.96it/s, train/loss=33.20]\nEpoch 0: |          | 122/? [00:41<00:00,  2.96it/s, train/loss=33.20]\nEpoch 0: |          | 122/? [00:41<00:00,  2.96it/s, train/loss=29.20]\nEpoch 0: |          | 123/? [00:41<00:00,  2.96it/s, train/loss=29.20]\nEpoch 0: |          | 123/? [00:41<00:00,  2.96it/s, train/loss=14.80]\nEpoch 0: |          | 124/? [00:41<00:00,  2.96it/s, train/loss=14.80]\nEpoch 0: |          | 124/? [00:41<00:00,  2.96it/s, train/loss=19.00]\nEpoch 0: |          | 125/? [00:42<00:00,  2.96it/s, train/loss=19.00]\nEpoch 0: |          | 125/? [00:42<00:00,  2.96it/s, train/loss=35.50]\nEpoch 0: |          | 126/? [00:42<00:00,  2.96it/s, train/loss=35.50]\nEpoch 0: |          | 126/? [00:42<00:00,  2.96it/s, train/loss=30.20]\nEpoch 0: |          | 127/? [00:42<00:00,  2.96it/s, train/loss=30.20]\nEpoch 0: |          | 127/? [00:42<00:00,  2.96it/s, train/loss=11.70]\nEpoch 0: |          | 128/? [00:43<00:00,  2.96it/s, train/loss=11.70]\nEpoch 0: |          | 128/? [00:43<00:00,  2.96it/s, train/loss=33.50]\nEpoch 0: |          | 129/? [00:43<00:00,  2.96it/s, train/loss=33.50]\nEpoch 0: |          | 129/? [00:43<00:00,  2.96it/s, train/loss=21.60]\nEpoch 0: |          | 130/? [00:43<00:00,  2.96it/s, train/loss=21.60]\nEpoch 0: |          | 130/? [00:43<00:00,  2.96it/s, train/loss=31.00]\nEpoch 0: |          | 131/? [00:44<00:00,  2.96it/s, train/loss=31.00]\nEpoch 0: |          | 131/? [00:44<00:00,  2.96it/s, train/loss=7.040]\nEpoch 0: |          | 132/? [00:44<00:00,  2.96it/s, train/loss=7.040]\nEpoch 0: |          | 132/? [00:44<00:00,  2.96it/s, train/loss=18.30]\nEpoch 0: |          | 133/? [00:44<00:00,  2.96it/s, train/loss=18.30]\nEpoch 0: |          | 133/? [00:44<00:00,  2.96it/s, train/loss=50.90]\nEpoch 0: |          | 134/? [00:45<00:00,  2.96it/s, train/loss=50.90]\nEpoch 0: |          | 134/? [00:45<00:00,  2.96it/s, train/loss=36.30]\nEpoch 0: |          | 135/? [00:45<00:00,  2.96it/s, train/loss=36.30]\nEpoch 0: |          | 135/? [00:45<00:00,  2.96it/s, train/loss=16.50]\nEpoch 0: |          | 136/? [00:45<00:00,  2.96it/s, train/loss=16.50]\nEpoch 0: |          | 136/? [00:45<00:00,  2.96it/s, train/loss=37.00]\nEpoch 0: |          | 137/? [00:46<00:00,  2.96it/s, train/loss=37.00]\nEpoch 0: |          | 137/? [00:46<00:00,  2.96it/s, train/loss=30.50]\nEpoch 0: |          | 138/? [00:46<00:00,  2.96it/s, train/loss=30.50]\nEpoch 0: |          | 138/? [00:46<00:00,  2.96it/s, train/loss=9.030]\nEpoch 0: |          | 139/? [00:46<00:00,  2.96it/s, train/loss=9.030]\nEpoch 0: |          | 139/? [00:46<00:00,  2.96it/s, train/loss=64.00]\nEpoch 0: |          | 140/? [00:47<00:00,  2.97it/s, train/loss=64.00]\nEpoch 0: |          | 140/? [00:47<00:00,  2.97it/s, train/loss=21.90]\nEpoch 0: |          | 141/? [00:47<00:00,  2.97it/s, train/loss=21.90]\nEpoch 0: |          | 141/? [00:47<00:00,  2.97it/s, train/loss=20.40]\nEpoch 0: |          | 142/? [00:47<00:00,  2.97it/s, train/loss=20.40]\nEpoch 0: |          | 142/? [00:47<00:00,  2.97it/s, train/loss=23.60]\nEpoch 0: |          | 143/? [00:48<00:00,  2.97it/s, train/loss=23.60]\nEpoch 0: |          | 143/? [00:48<00:00,  2.97it/s, train/loss=9.380]\nEpoch 0: |          | 144/? [00:48<00:00,  2.97it/s, train/loss=9.380]\nEpoch 0: |          | 144/? [00:48<00:00,  2.97it/s, train/loss=28.20]\nEpoch 0: |          | 145/? [00:48<00:00,  2.97it/s, train/loss=28.20]\nEpoch 0: |          | 145/? [00:48<00:00,  2.97it/s, train/loss=49.70]\nEpoch 0: |          | 146/? [00:49<00:00,  2.97it/s, train/loss=49.70]\nEpoch 0: |          | 146/? [00:49<00:00,  2.97it/s, train/loss=22.60]\nEpoch 0: |          | 147/? [00:49<00:00,  2.97it/s, train/loss=22.60]\nEpoch 0: |          | 147/? [00:49<00:00,  2.97it/s, train/loss=31.20]\nEpoch 0: |          | 148/? [00:49<00:00,  2.97it/s, train/loss=31.20]\nEpoch 0: |          | 148/? [00:49<00:00,  2.97it/s, train/loss=12.40]\nEpoch 0: |          | 149/? [00:50<00:00,  2.97it/s, train/loss=12.40]\nEpoch 0: |          | 149/? [00:50<00:00,  2.97it/s, train/loss=26.90]\nEpoch 0: |          | 150/? [00:50<00:00,  2.97it/s, train/loss=26.90]\nEpoch 0: |          | 150/? [00:50<00:00,  2.97it/s, train/loss=29.40]\nEpoch 0: |          | 151/? [00:50<00:00,  2.97it/s, train/loss=29.40]\nEpoch 0: |          | 151/? [00:50<00:00,  2.97it/s, train/loss=15.90]\nEpoch 0: |          | 152/? [00:51<00:00,  2.97it/s, train/loss=15.90]\nEpoch 0: |          | 152/? [00:51<00:00,  2.97it/s, train/loss=34.20]\nEpoch 0: |          | 153/? [00:51<00:00,  2.97it/s, train/loss=34.20]\nEpoch 0: |          | 153/? [00:51<00:00,  2.97it/s, train/loss=27.00]\nEpoch 0: |          | 154/? [00:51<00:00,  2.97it/s, train/loss=27.00]\nEpoch 0: |          | 154/? [00:51<00:00,  2.97it/s, train/loss=20.90]\nEpoch 0: |          | 155/? [00:52<00:00,  2.97it/s, train/loss=20.90]\nEpoch 0: |          | 155/? [00:52<00:00,  2.97it/s, train/loss=28.60]\nEpoch 0: |          | 156/? [00:52<00:00,  2.97it/s, train/loss=28.60]\nEpoch 0: |          | 156/? [00:52<00:00,  2.97it/s, train/loss=15.00]\nEpoch 0: |          | 157/? [00:52<00:00,  2.97it/s, train/loss=15.00]\nEpoch 0: |          | 157/? [00:52<00:00,  2.97it/s, train/loss=18.70]\nEpoch 0: |          | 158/? [00:53<00:00,  2.98it/s, train/loss=18.70]\nEpoch 0: |          | 158/? [00:53<00:00,  2.98it/s, train/loss=21.40]\nEpoch 0: |          | 159/? [00:53<00:00,  2.98it/s, train/loss=21.40]\nEpoch 0: |          | 159/? [00:53<00:00,  2.98it/s, train/loss=37.80]\nEpoch 0: |          | 160/? [00:53<00:00,  2.98it/s, train/loss=37.80]\nEpoch 0: |          | 160/? [00:53<00:00,  2.98it/s, train/loss=16.10]\nEpoch 0: |          | 161/? [00:54<00:00,  2.98it/s, train/loss=16.10]\nEpoch 0: |          | 161/? [00:54<00:00,  2.98it/s, train/loss=29.40]\nEpoch 0: |          | 162/? [00:54<00:00,  2.98it/s, train/loss=29.40]\nEpoch 0: |          | 162/? [00:54<00:00,  2.98it/s, train/loss=27.00]\nEpoch 0: |          | 163/? [00:54<00:00,  2.98it/s, train/loss=27.00]\nEpoch 0: |          | 163/? [00:54<00:00,  2.98it/s, train/loss=30.00]\nEpoch 0: |          | 164/? [00:55<00:00,  2.98it/s, train/loss=30.00]\nEpoch 0: |          | 164/? [00:55<00:00,  2.98it/s, train/loss=23.00]\nEpoch 0: |          | 165/? [00:55<00:00,  2.98it/s, train/loss=23.00]\nEpoch 0: |          | 165/? [00:55<00:00,  2.98it/s, train/loss=19.30]\nEpoch 0: |          | 166/? [00:55<00:00,  2.98it/s, train/loss=19.30]\nEpoch 0: |          | 166/? [00:55<00:00,  2.98it/s, train/loss=7.840]\nEpoch 0: |          | 167/? [00:56<00:00,  2.98it/s, train/loss=7.840]\nEpoch 0: |          | 167/? [00:56<00:00,  2.98it/s, train/loss=23.30]\nEpoch 0: |          | 168/? [00:56<00:00,  2.98it/s, train/loss=23.30]\nEpoch 0: |          | 168/? [00:56<00:00,  2.98it/s, train/loss=28.90]\nEpoch 0: |          | 169/? [00:56<00:00,  2.98it/s, train/loss=28.90]\nEpoch 0: |          | 169/? [00:56<00:00,  2.98it/s, train/loss=41.70]\nEpoch 0: |          | 170/? [00:57<00:00,  2.98it/s, train/loss=41.70]\nEpoch 0: |          | 170/? [00:57<00:00,  2.98it/s, train/loss=25.60]\nEpoch 0: |          | 171/? [00:57<00:00,  2.98it/s, train/loss=25.60]\nEpoch 0: |          | 171/? [00:57<00:00,  2.98it/s, train/loss=9.550]\nEpoch 0: |          | 172/? [00:57<00:00,  2.98it/s, train/loss=9.550]\nEpoch 0: |          | 172/? [00:57<00:00,  2.98it/s, train/loss=8.980]\nEpoch 0: |          | 173/? [00:58<00:00,  2.98it/s, train/loss=8.980]\nEpoch 0: |          | 173/? [00:58<00:00,  2.98it/s, train/loss=41.40]\nEpoch 0: |          | 174/? [00:58<00:00,  2.97it/s, train/loss=41.40]\nEpoch 0: |          | 174/? [00:58<00:00,  2.97it/s, train/loss=14.10]\nEpoch 0: |          | 175/? [00:58<00:00,  2.97it/s, train/loss=14.10]\nEpoch 0: |          | 175/? [00:58<00:00,  2.97it/s, train/loss=42.50]\nEpoch 0: |          | 176/? [00:59<00:00,  2.97it/s, train/loss=42.50]\nEpoch 0: |          | 176/? [00:59<00:00,  2.97it/s, train/loss=18.90]\nEpoch 0: |          | 177/? [00:59<00:00,  2.97it/s, train/loss=18.90]\nEpoch 0: |          | 177/? [00:59<00:00,  2.97it/s, train/loss=52.70]\nEpoch 0: |          | 178/? [00:59<00:00,  2.97it/s, train/loss=52.70]\nEpoch 0: |          | 178/? [00:59<00:00,  2.97it/s, train/loss=21.30]\nEpoch 0: |          | 179/? [01:00<00:00,  2.97it/s, train/loss=21.30]\nEpoch 0: |          | 179/? [01:00<00:00,  2.97it/s, train/loss=26.90]\nEpoch 0: |          | 180/? [01:00<00:00,  2.97it/s, train/loss=26.90]\nEpoch 0: |          | 180/? [01:00<00:00,  2.97it/s, train/loss=43.90]\nEpoch 0: |          | 181/? [01:00<00:00,  2.97it/s, train/loss=43.90]\nEpoch 0: |          | 181/? [01:00<00:00,  2.97it/s, train/loss=30.30]\nEpoch 0: |          | 182/? [01:01<00:00,  2.97it/s, train/loss=30.30]\nEpoch 0: |          | 182/? [01:01<00:00,  2.97it/s, train/loss=14.80]\nEpoch 0: |          | 183/? [01:01<00:00,  2.97it/s, train/loss=14.80]\nEpoch 0: |          | 183/? [01:01<00:00,  2.97it/s, train/loss=9.860]\nEpoch 0: |          | 184/? [01:01<00:00,  2.97it/s, train/loss=9.860]\nEpoch 0: |          | 184/? [01:01<00:00,  2.97it/s, train/loss=40.60]\nEpoch 0: |          | 185/? [01:02<00:00,  2.97it/s, train/loss=40.60]\nEpoch 0: |          | 185/? [01:02<00:00,  2.97it/s, train/loss=17.30]\nEpoch 0: |          | 186/? [01:02<00:00,  2.97it/s, train/loss=17.30]\nEpoch 0: |          | 186/? [01:02<00:00,  2.97it/s, train/loss=17.20]\nEpoch 0: |          | 187/? [01:02<00:00,  2.97it/s, train/loss=17.20]\nEpoch 0: |          | 187/? [01:02<00:00,  2.97it/s, train/loss=30.70]\nEpoch 0: |          | 188/? [01:03<00:00,  2.97it/s, train/loss=30.70]\nEpoch 0: |          | 188/? [01:03<00:00,  2.97it/s, train/loss=30.50]\nEpoch 0: |          | 189/? [01:03<00:00,  2.97it/s, train/loss=30.50]\nEpoch 0: |          | 189/? [01:03<00:00,  2.97it/s, train/loss=34.40]\nEpoch 0: |          | 190/? [01:03<00:00,  2.97it/s, train/loss=34.40]\nEpoch 0: |          | 190/? [01:03<00:00,  2.97it/s, train/loss=18.50]\nEpoch 0: |          | 191/? [01:04<00:00,  2.97it/s, train/loss=18.50]\nEpoch 0: |          | 191/? [01:04<00:00,  2.97it/s, train/loss=10.70]\nEpoch 0: |          | 192/? [01:04<00:00,  2.98it/s, train/loss=10.70]\nEpoch 0: |          | 192/? [01:04<00:00,  2.98it/s, train/loss=10.90]\nEpoch 0: |          | 193/? [01:04<00:00,  2.98it/s, train/loss=10.90]\nEpoch 0: |          | 193/? [01:04<00:00,  2.98it/s, train/loss=42.30]\nEpoch 0: |          | 194/? [01:05<00:00,  2.98it/s, train/loss=42.30]\nEpoch 0: |          | 194/? [01:05<00:00,  2.98it/s, train/loss=15.00]\nEpoch 0: |          | 195/? [01:05<00:00,  2.98it/s, train/loss=15.00]\nEpoch 0: |          | 195/? [01:05<00:00,  2.98it/s, train/loss=24.30]\nEpoch 0: |          | 196/? [01:05<00:00,  2.98it/s, train/loss=24.30]\nEpoch 0: |          | 196/? [01:05<00:00,  2.98it/s, train/loss=23.80]\nEpoch 0: |          | 197/? [01:06<00:00,  2.98it/s, train/loss=23.80]\nEpoch 0: |          | 197/? [01:06<00:00,  2.98it/s, train/loss=23.20]\nEpoch 0: |          | 198/? [01:06<00:00,  2.98it/s, train/loss=23.20]\nEpoch 0: |          | 198/? [01:06<00:00,  2.98it/s, train/loss=9.060]\nEpoch 0: |          | 199/? [01:06<00:00,  2.98it/s, train/loss=9.060]\nEpoch 0: |          | 199/? [01:06<00:00,  2.98it/s, train/loss=24.10]\nEpoch 0: |          | 200/? [01:07<00:00,  2.98it/s, train/loss=24.10]\nEpoch 0: |          | 200/? [01:07<00:00,  2.98it/s, train/loss=19.50]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:03,  9.75it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:03, 10.64it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:03, 10.96it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:03, 11.13it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:03, 11.22it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:03, 11.32it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:02, 11.34it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:02, 11.39it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:02, 11.38it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:02, 11.46it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:02, 11.53it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:02, 11.59it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:02, 11.56it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02, 11.57it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02, 11.60it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02, 11.61it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:01, 11.63it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:01<00:01, 11.64it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:01<00:01, 11.65it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:01<00:01, 11.66it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:01<00:01, 11.65it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:01<00:01, 11.67it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:01<00:01, 11.68it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01, 11.66it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01, 11.65it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01, 11.64it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01, 11.64it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:02<00:01, 11.63it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:02<00:00, 11.65it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:02<00:00, 11.67it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:02<00:00, 11.67it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:02<00:00, 11.66it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:02<00:00, 11.67it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:02<00:00, 11.66it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00, 11.64it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:03<00:00, 11.62it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:03<00:00, 11.60it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:03<00:00, 11.59it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:03<00:00, 11.58it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.57it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 200/? [01:14<00:00,  2.70it/s, train/loss=19.50]\nEpoch 0: |          | 201/? [01:15<00:00,  2.68it/s, train/loss=19.50]\nEpoch 0: |          | 201/? [01:15<00:00,  2.68it/s, train/loss=18.40]\nEpoch 0: |          | 202/? [01:15<00:00,  2.68it/s, train/loss=18.40]\nEpoch 0: |          | 202/? [01:15<00:00,  2.68it/s, train/loss=21.90]\nEpoch 0: |          | 203/? [01:15<00:00,  2.68it/s, train/loss=21.90]\nEpoch 0: |          | 203/? [01:15<00:00,  2.68it/s, train/loss=24.70]\nEpoch 0: |          | 204/? [01:16<00:00,  2.68it/s, train/loss=24.70]\nEpoch 0: |          | 204/? [01:16<00:00,  2.68it/s, train/loss=20.40]\nEpoch 0: |          | 205/? [01:16<00:00,  2.68it/s, train/loss=20.40]\nEpoch 0: |          | 205/? [01:16<00:00,  2.68it/s, train/loss=24.10]\nEpoch 0: |          | 206/? [01:16<00:00,  2.68it/s, train/loss=24.10]\nEpoch 0: |          | 206/? [01:16<00:00,  2.68it/s, train/loss=29.90]\nEpoch 0: |          | 207/? [01:17<00:00,  2.68it/s, train/loss=29.90]\nEpoch 0: |          | 207/? [01:17<00:00,  2.68it/s, train/loss=9.750]\nEpoch 0: |          | 208/? [01:17<00:00,  2.68it/s, train/loss=9.750]\nEpoch 0: |          | 208/? [01:17<00:00,  2.68it/s, train/loss=20.60]\nEpoch 0: |          | 209/? [01:17<00:00,  2.68it/s, train/loss=20.60]\nEpoch 0: |          | 209/? [01:17<00:00,  2.68it/s, train/loss=31.50]\nEpoch 0: |          | 210/? [01:18<00:00,  2.69it/s, train/loss=31.50]\nEpoch 0: |          | 210/? [01:18<00:00,  2.69it/s, train/loss=26.50]\nEpoch 0: |          | 211/? [01:18<00:00,  2.69it/s, train/loss=26.50]\nEpoch 0: |          | 211/? [01:18<00:00,  2.69it/s, train/loss=44.80]\nEpoch 0: |          | 212/? [01:18<00:00,  2.69it/s, train/loss=44.80]\nEpoch 0: |          | 212/? [01:18<00:00,  2.69it/s, train/loss=12.50]\nEpoch 0: |          | 213/? [01:19<00:00,  2.69it/s, train/loss=12.50]\nEpoch 0: |          | 213/? [01:19<00:00,  2.69it/s, train/loss=22.50]\nEpoch 0: |          | 214/? [01:19<00:00,  2.69it/s, train/loss=22.50]\nEpoch 0: |          | 214/? [01:19<00:00,  2.69it/s, train/loss=22.90]\nEpoch 0: |          | 215/? [01:19<00:00,  2.69it/s, train/loss=22.90]\nEpoch 0: |          | 215/? [01:19<00:00,  2.69it/s, train/loss=12.00]\nEpoch 0: |          | 216/? [01:20<00:00,  2.70it/s, train/loss=12.00]\nEpoch 0: |          | 216/? [01:20<00:00,  2.70it/s, train/loss=22.50]\nEpoch 0: |          | 217/? [01:20<00:00,  2.70it/s, train/loss=22.50]\nEpoch 0: |          | 217/? [01:20<00:00,  2.70it/s, train/loss=22.90]\nEpoch 0: |          | 218/? [01:20<00:00,  2.70it/s, train/loss=22.90]\nEpoch 0: |          | 218/? [01:20<00:00,  2.70it/s, train/loss=26.30]\nEpoch 0: |          | 219/? [01:21<00:00,  2.70it/s, train/loss=26.30]\nEpoch 0: |          | 219/? [01:21<00:00,  2.70it/s, train/loss=12.70]\nEpoch 0: |          | 220/? [01:21<00:00,  2.70it/s, train/loss=12.70]\nEpoch 0: |          | 220/? [01:21<00:00,  2.70it/s, train/loss=12.20]\nEpoch 0: |          | 221/? [01:21<00:00,  2.70it/s, train/loss=12.20]\nEpoch 0: |          | 221/? [01:21<00:00,  2.70it/s, train/loss=33.90]\nEpoch 0: |          | 222/? [01:22<00:00,  2.70it/s, train/loss=33.90]\nEpoch 0: |          | 222/? [01:22<00:00,  2.70it/s, train/loss=21.90]\nEpoch 0: |          | 223/? [01:22<00:00,  2.70it/s, train/loss=21.90]\nEpoch 0: |          | 223/? [01:22<00:00,  2.70it/s, train/loss=9.470]\nEpoch 0: |          | 224/? [01:22<00:00,  2.70it/s, train/loss=9.470]\nEpoch 0: |          | 224/? [01:22<00:00,  2.70it/s, train/loss=29.10]\nEpoch 0: |          | 225/? [01:23<00:00,  2.70it/s, train/loss=29.10]\nEpoch 0: |          | 225/? [01:23<00:00,  2.70it/s, train/loss=34.40]\nEpoch 0: |          | 226/? [01:23<00:00,  2.71it/s, train/loss=34.40]\nEpoch 0: |          | 226/? [01:23<00:00,  2.71it/s, train/loss=17.00]\nEpoch 0: |          | 227/? [01:23<00:00,  2.71it/s, train/loss=17.00]\nEpoch 0: |          | 227/? [01:23<00:00,  2.71it/s, train/loss=23.90]\nEpoch 0: |          | 228/? [01:24<00:00,  2.71it/s, train/loss=23.90]\nEpoch 0: |          | 228/? [01:24<00:00,  2.71it/s, train/loss=12.90]\nEpoch 0: |          | 229/? [01:24<00:00,  2.70it/s, train/loss=12.90]\nEpoch 0: |          | 229/? [01:24<00:00,  2.70it/s, train/loss=27.10]\nEpoch 0: |          | 230/? [01:25<00:00,  2.70it/s, train/loss=27.10]\nEpoch 0: |          | 230/? [01:25<00:00,  2.70it/s, train/loss=18.10]\nEpoch 0: |          | 231/? [01:25<00:00,  2.70it/s, train/loss=18.10]\nEpoch 0: |          | 231/? [01:25<00:00,  2.70it/s, train/loss=23.10]\nEpoch 0: |          | 232/? [01:25<00:00,  2.70it/s, train/loss=23.10]\nEpoch 0: |          | 232/? [01:25<00:00,  2.70it/s, train/loss=32.00]\nEpoch 0: |          | 233/? [01:26<00:00,  2.70it/s, train/loss=32.00]\nEpoch 0: |          | 233/? [01:26<00:00,  2.70it/s, train/loss=39.00]\nEpoch 0: |          | 234/? [01:26<00:00,  2.70it/s, train/loss=39.00]\nEpoch 0: |          | 234/? [01:26<00:00,  2.70it/s, train/loss=17.50]\nEpoch 0: |          | 235/? [01:27<00:00,  2.70it/s, train/loss=17.50]\nEpoch 0: |          | 235/? [01:27<00:00,  2.70it/s, train/loss=27.30]\nEpoch 0: |          | 236/? [01:27<00:00,  2.70it/s, train/loss=27.30]\nEpoch 0: |          | 236/? [01:27<00:00,  2.70it/s, train/loss=17.20]\nEpoch 0: |          | 237/? [01:27<00:00,  2.70it/s, train/loss=17.20]\nEpoch 0: |          | 237/? [01:27<00:00,  2.70it/s, train/loss=21.60]\nEpoch 0: |          | 238/? [01:28<00:00,  2.70it/s, train/loss=21.60]\nEpoch 0: |          | 238/? [01:28<00:00,  2.70it/s, train/loss=27.00]\nEpoch 0: |          | 239/? [01:28<00:00,  2.70it/s, train/loss=27.00]\nEpoch 0: |          | 239/? [01:28<00:00,  2.70it/s, train/loss=24.70]\nEpoch 0: |          | 240/? [01:28<00:00,  2.71it/s, train/loss=24.70]\nEpoch 0: |          | 240/? [01:28<00:00,  2.71it/s, train/loss=19.30]\nEpoch 0: |          | 241/? [01:29<00:00,  2.71it/s, train/loss=19.30]\nEpoch 0: |          | 241/? [01:29<00:00,  2.71it/s, train/loss=31.30]\nEpoch 0: |          | 242/? [01:29<00:00,  2.71it/s, train/loss=31.30]\nEpoch 0: |          | 242/? [01:29<00:00,  2.71it/s, train/loss=33.00]\nEpoch 0: |          | 243/? [01:29<00:00,  2.71it/s, train/loss=33.00]\nEpoch 0: |          | 243/? [01:29<00:00,  2.71it/s, train/loss=36.70]\nEpoch 0: |          | 244/? [01:29<00:00,  2.71it/s, train/loss=36.70]\nEpoch 0: |          | 244/? [01:29<00:00,  2.71it/s, train/loss=11.30]\nEpoch 0: |          | 245/? [01:30<00:00,  2.71it/s, train/loss=11.30]\nEpoch 0: |          | 245/? [01:30<00:00,  2.71it/s, train/loss=29.30]\nEpoch 0: |          | 246/? [01:30<00:00,  2.71it/s, train/loss=29.30]\nEpoch 0: |          | 246/? [01:30<00:00,  2.71it/s, train/loss=29.50]\nEpoch 0: |          | 247/? [01:30<00:00,  2.72it/s, train/loss=29.50]\nEpoch 0: |          | 247/? [01:30<00:00,  2.71it/s, train/loss=38.30]\nEpoch 0: |          | 248/? [01:31<00:00,  2.72it/s, train/loss=38.30]\nEpoch 0: |          | 248/? [01:31<00:00,  2.72it/s, train/loss=31.60]\nEpoch 0: |          | 249/? [01:31<00:00,  2.72it/s, train/loss=31.60]\nEpoch 0: |          | 249/? [01:31<00:00,  2.72it/s, train/loss=25.80]\nEpoch 0: |          | 250/? [01:31<00:00,  2.72it/s, train/loss=25.80]\nEpoch 0: |          | 250/? [01:31<00:00,  2.72it/s, train/loss=22.20]\nEpoch 0: |          | 251/? [01:32<00:00,  2.72it/s, train/loss=22.20]\nEpoch 0: |          | 251/? [01:32<00:00,  2.72it/s, train/loss=20.50]\nEpoch 0: |          | 252/? [01:32<00:00,  2.72it/s, train/loss=20.50]\nEpoch 0: |          | 252/? [01:32<00:00,  2.72it/s, train/loss=12.90]\nEpoch 0: |          | 253/? [01:32<00:00,  2.72it/s, train/loss=12.90]\nEpoch 0: |          | 253/? [01:32<00:00,  2.72it/s, train/loss=34.50]\nEpoch 0: |          | 254/? [01:33<00:00,  2.72it/s, train/loss=34.50]\nEpoch 0: |          | 254/? [01:33<00:00,  2.72it/s, train/loss=21.40]\nEpoch 0: |          | 255/? [01:33<00:00,  2.72it/s, train/loss=21.40]\nEpoch 0: |          | 255/? [01:33<00:00,  2.72it/s, train/loss=20.10]\nEpoch 0: |          | 256/? [01:33<00:00,  2.73it/s, train/loss=20.10]\nEpoch 0: |          | 256/? [01:33<00:00,  2.73it/s, train/loss=9.920]\nEpoch 0: |          | 257/? [01:34<00:00,  2.73it/s, train/loss=9.920]\nEpoch 0: |          | 257/? [01:34<00:00,  2.73it/s, train/loss=26.10]\nEpoch 0: |          | 258/? [01:34<00:00,  2.73it/s, train/loss=26.10]\nEpoch 0: |          | 258/? [01:34<00:00,  2.73it/s, train/loss=22.30]\nEpoch 0: |          | 259/? [01:34<00:00,  2.73it/s, train/loss=22.30]\nEpoch 0: |          | 259/? [01:34<00:00,  2.73it/s, train/loss=22.70]\nEpoch 0: |          | 260/? [01:35<00:00,  2.73it/s, train/loss=22.70]\nEpoch 0: |          | 260/? [01:35<00:00,  2.73it/s, train/loss=10.50]\nEpoch 0: |          | 261/? [01:35<00:00,  2.73it/s, train/loss=10.50]\nEpoch 0: |          | 261/? [01:35<00:00,  2.73it/s, train/loss=19.80]\nEpoch 0: |          | 262/? [01:35<00:00,  2.73it/s, train/loss=19.80]\nEpoch 0: |          | 262/? [01:35<00:00,  2.73it/s, train/loss=26.50]\nEpoch 0: |          | 263/? [01:36<00:00,  2.73it/s, train/loss=26.50]\nEpoch 0: |          | 263/? [01:36<00:00,  2.73it/s, train/loss=15.90]\nEpoch 0: |          | 264/? [01:36<00:00,  2.73it/s, train/loss=15.90]\nEpoch 0: |          | 264/? [01:36<00:00,  2.73it/s, train/loss=83.00]\nEpoch 0: |          | 265/? [01:36<00:00,  2.73it/s, train/loss=83.00]\nEpoch 0: |          | 265/? [01:36<00:00,  2.73it/s, train/loss=19.80]\nEpoch 0: |          | 266/? [01:37<00:00,  2.74it/s, train/loss=19.80]\nEpoch 0: |          | 266/? [01:37<00:00,  2.74it/s, train/loss=27.80]\nEpoch 0: |          | 267/? [01:37<00:00,  2.74it/s, train/loss=27.80]\nEpoch 0: |          | 267/? [01:37<00:00,  2.74it/s, train/loss=12.90]\nEpoch 0: |          | 268/? [01:37<00:00,  2.74it/s, train/loss=12.90]\nEpoch 0: |          | 268/? [01:37<00:00,  2.74it/s, train/loss=37.60]\nEpoch 0: |          | 269/? [01:38<00:00,  2.74it/s, train/loss=37.60]\nEpoch 0: |          | 269/? [01:38<00:00,  2.74it/s, train/loss=18.00]\nEpoch 0: |          | 270/? [01:38<00:00,  2.74it/s, train/loss=18.00]\nEpoch 0: |          | 270/? [01:38<00:00,  2.74it/s, train/loss=30.10]\nEpoch 0: |          | 271/? [01:38<00:00,  2.74it/s, train/loss=30.10]\nEpoch 0: |          | 271/? [01:38<00:00,  2.74it/s, train/loss=26.90]\nEpoch 0: |          | 272/? [01:39<00:00,  2.74it/s, train/loss=26.90]\nEpoch 0: |          | 272/? [01:39<00:00,  2.74it/s, train/loss=24.70]\nEpoch 0: |          | 273/? [01:39<00:00,  2.74it/s, train/loss=24.70]\nEpoch 0: |          | 273/? [01:39<00:00,  2.74it/s, train/loss=30.30]\nEpoch 0: |          | 274/? [01:40<00:00,  2.73it/s, train/loss=30.30]\nEpoch 0: |          | 274/? [01:40<00:00,  2.73it/s, train/loss=23.30]\nEpoch 0: |          | 275/? [01:40<00:00,  2.74it/s, train/loss=23.30]\nEpoch 0: |          | 275/? [01:40<00:00,  2.74it/s, train/loss=19.70]\nEpoch 0: |          | 276/? [01:40<00:00,  2.74it/s, train/loss=19.70]\nEpoch 0: |          | 276/? [01:40<00:00,  2.74it/s, train/loss=25.70]\nEpoch 0: |          | 277/? [01:41<00:00,  2.74it/s, train/loss=25.70]\nEpoch 0: |          | 277/? [01:41<00:00,  2.74it/s, train/loss=43.30]\nEpoch 0: |          | 278/? [01:41<00:00,  2.74it/s, train/loss=43.30]\nEpoch 0: |          | 278/? [01:41<00:00,  2.74it/s, train/loss=29.50]\nEpoch 0: |          | 279/? [01:41<00:00,  2.74it/s, train/loss=29.50]\nEpoch 0: |          | 279/? [01:41<00:00,  2.74it/s, train/loss=25.80]\nEpoch 0: |          | 280/? [01:42<00:00,  2.74it/s, train/loss=25.80]\nEpoch 0: |          | 280/? [01:42<00:00,  2.74it/s, train/loss=73.00]\nEpoch 0: |          | 281/? [01:42<00:00,  2.74it/s, train/loss=73.00]\nEpoch 0: |          | 281/? [01:42<00:00,  2.74it/s, train/loss=34.10]\nEpoch 0: |          | 282/? [01:42<00:00,  2.74it/s, train/loss=34.10]\nEpoch 0: |          | 282/? [01:42<00:00,  2.74it/s, train/loss=16.80]\nEpoch 0: |          | 283/? [01:43<00:00,  2.74it/s, train/loss=16.80]\nEpoch 0: |          | 283/? [01:43<00:00,  2.74it/s, train/loss=23.70]\nEpoch 0: |          | 284/? [01:43<00:00,  2.73it/s, train/loss=23.70]\nEpoch 0: |          | 284/? [01:43<00:00,  2.73it/s, train/loss=42.90]\nEpoch 0: |          | 285/? [01:44<00:00,  2.74it/s, train/loss=42.90]\nEpoch 0: |          | 285/? [01:44<00:00,  2.73it/s, train/loss=18.10]\nEpoch 0: |          | 286/? [01:44<00:00,  2.74it/s, train/loss=18.10]\nEpoch 0: |          | 286/? [01:44<00:00,  2.74it/s, train/loss=16.30]\nEpoch 0: |          | 287/? [01:44<00:00,  2.74it/s, train/loss=16.30]\nEpoch 0: |          | 287/? [01:44<00:00,  2.74it/s, train/loss=24.40]\nEpoch 0: |          | 288/? [01:45<00:00,  2.74it/s, train/loss=24.40]\nEpoch 0: |          | 288/? [01:45<00:00,  2.74it/s, train/loss=18.90]\nEpoch 0: |          | 289/? [01:45<00:00,  2.74it/s, train/loss=18.90]\nEpoch 0: |          | 289/? [01:45<00:00,  2.74it/s, train/loss=29.20]\nEpoch 0: |          | 290/? [01:45<00:00,  2.74it/s, train/loss=29.20]\nEpoch 0: |          | 290/? [01:45<00:00,  2.74it/s, train/loss=15.30]\nEpoch 0: |          | 291/? [01:46<00:00,  2.74it/s, train/loss=15.30]\nEpoch 0: |          | 291/? [01:46<00:00,  2.74it/s, train/loss=48.50]\nEpoch 0: |          | 292/? [01:46<00:00,  2.74it/s, train/loss=48.50]\nEpoch 0: |          | 292/? [01:46<00:00,  2.74it/s, train/loss=17.30]\nEpoch 0: |          | 293/? [01:46<00:00,  2.74it/s, train/loss=17.30]\nEpoch 0: |          | 293/? [01:46<00:00,  2.74it/s, train/loss=32.00]\nEpoch 0: |          | 294/? [01:47<00:00,  2.74it/s, train/loss=32.00]\nEpoch 0: |          | 294/? [01:47<00:00,  2.74it/s, train/loss=15.80]\nEpoch 0: |          | 295/? [01:47<00:00,  2.74it/s, train/loss=15.80]\nEpoch 0: |          | 295/? [01:47<00:00,  2.74it/s, train/loss=11.20]\nEpoch 0: |          | 296/? [01:48<00:00,  2.74it/s, train/loss=11.20]\nEpoch 0: |          | 296/? [01:48<00:00,  2.74it/s, train/loss=13.20]\nEpoch 0: |          | 297/? [01:48<00:00,  2.74it/s, train/loss=13.20]\nEpoch 0: |          | 297/? [01:48<00:00,  2.74it/s, train/loss=17.20]\nEpoch 0: |          | 298/? [01:48<00:00,  2.74it/s, train/loss=17.20]\nEpoch 0: |          | 298/? [01:48<00:00,  2.74it/s, train/loss=16.80]\nEpoch 0: |          | 299/? [01:49<00:00,  2.74it/s, train/loss=16.80]\nEpoch 0: |          | 299/? [01:49<00:00,  2.74it/s, train/loss=20.00]\nEpoch 0: |          | 300/? [01:49<00:00,  2.74it/s, train/loss=20.00]\nEpoch 0: |          | 300/? [01:49<00:00,  2.74it/s, train/loss=17.50]\nEpoch 0: |          | 301/? [01:49<00:00,  2.74it/s, train/loss=17.50]\nEpoch 0: |          | 301/? [01:49<00:00,  2.74it/s, train/loss=31.60]\nEpoch 0: |          | 302/? [01:50<00:00,  2.74it/s, train/loss=31.60]\nEpoch 0: |          | 302/? [01:50<00:00,  2.74it/s, train/loss=17.70]\nEpoch 0: |          | 303/? [01:50<00:00,  2.74it/s, train/loss=17.70]\nEpoch 0: |          | 303/? [01:50<00:00,  2.74it/s, train/loss=6.190]\nEpoch 0: |          | 304/? [01:50<00:00,  2.74it/s, train/loss=6.190]\nEpoch 0: |          | 304/? [01:50<00:00,  2.74it/s, train/loss=22.80]\nEpoch 0: |          | 305/? [01:51<00:00,  2.74it/s, train/loss=22.80]\nEpoch 0: |          | 305/? [01:51<00:00,  2.74it/s, train/loss=20.90]\nEpoch 0: |          | 306/? [01:51<00:00,  2.74it/s, train/loss=20.90]\nEpoch 0: |          | 306/? [01:51<00:00,  2.74it/s, train/loss=26.30]\nEpoch 0: |          | 307/? [01:51<00:00,  2.74it/s, train/loss=26.30]\nEpoch 0: |          | 307/? [01:51<00:00,  2.74it/s, train/loss=24.20]\nEpoch 0: |          | 308/? [01:52<00:00,  2.74it/s, train/loss=24.20]\nEpoch 0: |          | 308/? [01:52<00:00,  2.74it/s, train/loss=14.50]\nEpoch 0: |          | 309/? [01:52<00:00,  2.74it/s, train/loss=14.50]\nEpoch 0: |          | 309/? [01:52<00:00,  2.74it/s, train/loss=28.30]\nEpoch 0: |          | 310/? [01:52<00:00,  2.74it/s, train/loss=28.30]\nEpoch 0: |          | 310/? [01:52<00:00,  2.74it/s, train/loss=28.40]\nEpoch 0: |          | 311/? [01:53<00:00,  2.74it/s, train/loss=28.40]\nEpoch 0: |          | 311/? [01:53<00:00,  2.74it/s, train/loss=25.70]\nEpoch 0: |          | 312/? [01:53<00:00,  2.75it/s, train/loss=25.70]\nEpoch 0: |          | 312/? [01:53<00:00,  2.75it/s, train/loss=43.80]\nEpoch 0: |          | 313/? [01:53<00:00,  2.75it/s, train/loss=43.80]\nEpoch 0: |          | 313/? [01:53<00:00,  2.75it/s, train/loss=20.80]\nEpoch 0: |          | 314/? [01:54<00:00,  2.75it/s, train/loss=20.80]\nEpoch 0: |          | 314/? [01:54<00:00,  2.75it/s, train/loss=41.50]\nEpoch 0: |          | 315/? [01:54<00:00,  2.75it/s, train/loss=41.50]\nEpoch 0: |          | 315/? [01:54<00:00,  2.75it/s, train/loss=18.30]\nEpoch 0: |          | 316/? [01:54<00:00,  2.75it/s, train/loss=18.30]\nEpoch 0: |          | 316/? [01:54<00:00,  2.75it/s, train/loss=16.40]\nEpoch 0: |          | 317/? [01:55<00:00,  2.75it/s, train/loss=16.40]\nEpoch 0: |          | 317/? [01:55<00:00,  2.75it/s, train/loss=21.20]\nEpoch 0: |          | 318/? [01:55<00:00,  2.75it/s, train/loss=21.20]\nEpoch 0: |          | 318/? [01:55<00:00,  2.75it/s, train/loss=32.10]\nEpoch 0: |          | 319/? [01:55<00:00,  2.75it/s, train/loss=32.10]\nEpoch 0: |          | 319/? [01:55<00:00,  2.75it/s, train/loss=21.10]\nEpoch 0: |          | 320/? [01:56<00:00,  2.75it/s, train/loss=21.10]\nEpoch 0: |          | 320/? [01:56<00:00,  2.75it/s, train/loss=17.00]\nEpoch 0: |          | 321/? [01:56<00:00,  2.75it/s, train/loss=17.00]\nEpoch 0: |          | 321/? [01:56<00:00,  2.75it/s, train/loss=23.70]\nEpoch 0: |          | 322/? [01:56<00:00,  2.75it/s, train/loss=23.70]\nEpoch 0: |          | 322/? [01:56<00:00,  2.75it/s, train/loss=26.10]\nEpoch 0: |          | 323/? [01:57<00:00,  2.76it/s, train/loss=26.10]\nEpoch 0: |          | 323/? [01:57<00:00,  2.76it/s, train/loss=24.10]\nEpoch 0: |          | 324/? [01:57<00:00,  2.76it/s, train/loss=24.10]\nEpoch 0: |          | 324/? [01:57<00:00,  2.76it/s, train/loss=17.70]\nEpoch 0: |          | 325/? [01:57<00:00,  2.76it/s, train/loss=17.70]\nEpoch 0: |          | 325/? [01:57<00:00,  2.76it/s, train/loss=33.40]\nEpoch 0: |          | 326/? [01:58<00:00,  2.76it/s, train/loss=33.40]\nEpoch 0: |          | 326/? [01:58<00:00,  2.76it/s, train/loss=22.60]\nEpoch 0: |          | 327/? [01:58<00:00,  2.76it/s, train/loss=22.60]\nEpoch 0: |          | 327/? [01:58<00:00,  2.76it/s, train/loss=14.40]\nEpoch 0: |          | 328/? [01:58<00:00,  2.76it/s, train/loss=14.40]\nEpoch 0: |          | 328/? [01:58<00:00,  2.76it/s, train/loss=23.20]\nEpoch 0: |          | 329/? [01:59<00:00,  2.76it/s, train/loss=23.20]\nEpoch 0: |          | 329/? [01:59<00:00,  2.76it/s, train/loss=32.80]\nEpoch 0: |          | 330/? [01:59<00:00,  2.76it/s, train/loss=32.80]\nEpoch 0: |          | 330/? [01:59<00:00,  2.76it/s, train/loss=25.70]\nEpoch 0: |          | 331/? [01:59<00:00,  2.76it/s, train/loss=25.70]\nEpoch 0: |          | 331/? [01:59<00:00,  2.76it/s, train/loss=10.00]\nEpoch 0: |          | 332/? [02:00<00:00,  2.76it/s, train/loss=10.00]\nEpoch 0: |          | 332/? [02:00<00:00,  2.76it/s, train/loss=13.80]\nEpoch 0: |          | 333/? [02:00<00:00,  2.76it/s, train/loss=13.80]\nEpoch 0: |          | 333/? [02:00<00:00,  2.76it/s, train/loss=14.90]\nEpoch 0: |          | 334/? [02:00<00:00,  2.76it/s, train/loss=14.90]\nEpoch 0: |          | 334/? [02:00<00:00,  2.76it/s, train/loss=25.70]\nEpoch 0: |          | 335/? [02:01<00:00,  2.77it/s, train/loss=25.70]\nEpoch 0: |          | 335/? [02:01<00:00,  2.77it/s, train/loss=28.00]\nEpoch 0: |          | 336/? [02:01<00:00,  2.77it/s, train/loss=28.00]\nEpoch 0: |          | 336/? [02:01<00:00,  2.77it/s, train/loss=8.200]\nEpoch 0: |          | 337/? [02:01<00:00,  2.77it/s, train/loss=8.200]\nEpoch 0: |          | 337/? [02:01<00:00,  2.77it/s, train/loss=28.30]\nEpoch 0: |          | 338/? [02:02<00:00,  2.77it/s, train/loss=28.30]\nEpoch 0: |          | 338/? [02:02<00:00,  2.77it/s, train/loss=18.60]\nEpoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=18.60]\nEpoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=31.30]\nEpoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=31.30]\nEpoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=33.80]\nEpoch 0: |          | 341/? [02:03<00:00,  2.77it/s, train/loss=33.80]\nEpoch 0: |          | 341/? [02:03<00:00,  2.77it/s, train/loss=27.80]\nEpoch 0: |          | 342/? [02:03<00:00,  2.77it/s, train/loss=27.80]\nEpoch 0: |          | 342/? [02:03<00:00,  2.77it/s, train/loss=25.80]\nEpoch 0: |          | 343/? [02:03<00:00,  2.77it/s, train/loss=25.80]\nEpoch 0: |          | 343/? [02:03<00:00,  2.77it/s, train/loss=10.80]\nEpoch 0: |          | 344/? [02:04<00:00,  2.77it/s, train/loss=10.80]\nEpoch 0: |          | 344/? [02:04<00:00,  2.77it/s, train/loss=21.40]\nEpoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=21.40]\nEpoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=27.50]\nEpoch 0: |          | 346/? [02:04<00:00,  2.77it/s, train/loss=27.50]\nEpoch 0: |          | 346/? [02:04<00:00,  2.77it/s, train/loss=26.90]\nEpoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=26.90]\nEpoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=9.160]\nEpoch 0: |          | 348/? [02:05<00:00,  2.78it/s, train/loss=9.160]\nEpoch 0: |          | 348/? [02:05<00:00,  2.78it/s, train/loss=16.30]\nEpoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=16.30]\nEpoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=18.30]\nEpoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=18.30]\nEpoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=27.30]\nEpoch 0: |          | 351/? [02:06<00:00,  2.78it/s, train/loss=27.30]\nEpoch 0: |          | 351/? [02:06<00:00,  2.78it/s, train/loss=20.10]\nEpoch 0: |          | 352/? [02:06<00:00,  2.78it/s, train/loss=20.10]\nEpoch 0: |          | 352/? [02:06<00:00,  2.78it/s, train/loss=10.80]\nEpoch 0: |          | 353/? [02:07<00:00,  2.78it/s, train/loss=10.80]\nEpoch 0: |          | 353/? [02:07<00:00,  2.78it/s, train/loss=39.30]\nEpoch 0: |          | 354/? [02:07<00:00,  2.78it/s, train/loss=39.30]\nEpoch 0: |          | 354/? [02:07<00:00,  2.78it/s, train/loss=38.70]\nEpoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=38.70]\nEpoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=32.30]\nEpoch 0: |          | 356/? [02:08<00:00,  2.78it/s, train/loss=32.30]\nEpoch 0: |          | 356/? [02:08<00:00,  2.78it/s, train/loss=16.10]\nEpoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=16.10]\nEpoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=33.00]\nEpoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=33.00]\nEpoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=28.10]\nEpoch 0: |          | 359/? [02:08<00:00,  2.78it/s, train/loss=28.10]\nEpoch 0: |          | 359/? [02:08<00:00,  2.78it/s, train/loss=9.550]\nEpoch 0: |          | 360/? [02:09<00:00,  2.78it/s, train/loss=9.550]\nEpoch 0: |          | 360/? [02:09<00:00,  2.78it/s, train/loss=16.10]\nEpoch 0: |          | 361/? [02:09<00:00,  2.78it/s, train/loss=16.10]\nEpoch 0: |          | 361/? [02:09<00:00,  2.78it/s, train/loss=33.40]\nEpoch 0: |          | 362/? [02:09<00:00,  2.79it/s, train/loss=33.40]\nEpoch 0: |          | 362/? [02:09<00:00,  2.79it/s, train/loss=12.90]\nEpoch 0: |          | 363/? [02:10<00:00,  2.79it/s, train/loss=12.90]\nEpoch 0: |          | 363/? [02:10<00:00,  2.79it/s, train/loss=7.820]\nEpoch 0: |          | 364/? [02:10<00:00,  2.79it/s, train/loss=7.820]\nEpoch 0: |          | 364/? [02:10<00:00,  2.79it/s, train/loss=31.80]\nEpoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=31.80]\nEpoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=23.70]\nEpoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=23.70]\nEpoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=30.10]\nEpoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=30.10]\nEpoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=60.60]\nEpoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=60.60]\nEpoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=17.70]\nEpoch 0: |          | 369/? [02:12<00:00,  2.79it/s, train/loss=17.70]\nEpoch 0: |          | 369/? [02:12<00:00,  2.79it/s, train/loss=22.10]\nEpoch 0: |          | 370/? [02:12<00:00,  2.78it/s, train/loss=22.10]\nEpoch 0: |          | 370/? [02:12<00:00,  2.78it/s, train/loss=32.60]\nEpoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=32.60]\nEpoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=19.20]\nEpoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=19.20]\nEpoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=21.30]\nEpoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=21.30]\nEpoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=56.40]\nEpoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=56.40]\nEpoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=7.560]\nEpoch 0: |          | 375/? [02:14<00:00,  2.79it/s, train/loss=7.560]\nEpoch 0: |          | 375/? [02:14<00:00,  2.79it/s, train/loss=25.50]\nEpoch 0: |          | 376/? [02:14<00:00,  2.79it/s, train/loss=25.50]\nEpoch 0: |          | 376/? [02:14<00:00,  2.79it/s, train/loss=12.80]\nEpoch 0: |          | 377/? [02:15<00:00,  2.79it/s, train/loss=12.80]\nEpoch 0: |          | 377/? [02:15<00:00,  2.79it/s, train/loss=71.40]\nEpoch 0: |          | 378/? [02:15<00:00,  2.79it/s, train/loss=71.40]\nEpoch 0: |          | 378/? [02:15<00:00,  2.79it/s, train/loss=49.30]\nEpoch 0: |          | 379/? [02:15<00:00,  2.79it/s, train/loss=49.30]\nEpoch 0: |          | 379/? [02:15<00:00,  2.79it/s, train/loss=35.50]\nEpoch 0: |          | 380/? [02:16<00:00,  2.79it/s, train/loss=35.50]\nEpoch 0: |          | 380/? [02:16<00:00,  2.79it/s, train/loss=8.540]\nEpoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=8.540]\nEpoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=16.60]\nEpoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=16.60]\nEpoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=19.50]\nEpoch 0: |          | 383/? [02:17<00:00,  2.79it/s, train/loss=19.50]\nEpoch 0: |          | 383/? [02:17<00:00,  2.79it/s, train/loss=10.60]\nEpoch 0: |          | 384/? [02:17<00:00,  2.79it/s, train/loss=10.60]\nEpoch 0: |          | 384/? [02:17<00:00,  2.79it/s, train/loss=25.00]\nEpoch 0: |          | 385/? [02:17<00:00,  2.79it/s, train/loss=25.00]\nEpoch 0: |          | 385/? [02:17<00:00,  2.79it/s, train/loss=31.50]\nEpoch 0: |          | 386/? [02:18<00:00,  2.79it/s, train/loss=31.50]\nEpoch 0: |          | 386/? [02:18<00:00,  2.79it/s, train/loss=34.80]\nEpoch 0: |          | 387/? [02:18<00:00,  2.79it/s, train/loss=34.80]\nEpoch 0: |          | 387/? [02:18<00:00,  2.79it/s, train/loss=9.860]\nEpoch 0: |          | 388/? [02:18<00:00,  2.80it/s, train/loss=9.860]\nEpoch 0: |          | 388/? [02:18<00:00,  2.80it/s, train/loss=19.40]\nEpoch 0: |          | 389/? [02:19<00:00,  2.80it/s, train/loss=19.40]\nEpoch 0: |          | 389/? [02:19<00:00,  2.80it/s, train/loss=23.50]\nEpoch 0: |          | 390/? [02:19<00:00,  2.80it/s, train/loss=23.50]\nEpoch 0: |          | 390/? [02:19<00:00,  2.80it/s, train/loss=10.40]\nEpoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=10.40]\nEpoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=13.90]\nEpoch 0: |          | 392/? [02:20<00:00,  2.80it/s, train/loss=13.90]\nEpoch 0: |          | 392/? [02:20<00:00,  2.80it/s, train/loss=13.50]\nEpoch 0: |          | 393/? [02:20<00:00,  2.80it/s, train/loss=13.50]\nEpoch 0: |          | 393/? [02:20<00:00,  2.80it/s, train/loss=27.80]\nEpoch 0: |          | 394/? [02:20<00:00,  2.80it/s, train/loss=27.80]\nEpoch 0: |          | 394/? [02:20<00:00,  2.80it/s, train/loss=15.40]\nEpoch 0: |          | 395/? [02:21<00:00,  2.80it/s, train/loss=15.40]\nEpoch 0: |          | 395/? [02:21<00:00,  2.80it/s, train/loss=36.60]\nEpoch 0: |          | 396/? [02:21<00:00,  2.80it/s, train/loss=36.60]\nEpoch 0: |          | 396/? [02:21<00:00,  2.80it/s, train/loss=37.40]\nEpoch 0: |          | 397/? [02:21<00:00,  2.80it/s, train/loss=37.40]\nEpoch 0: |          | 397/? [02:21<00:00,  2.80it/s, train/loss=25.60]\nEpoch 0: |          | 398/? [02:22<00:00,  2.80it/s, train/loss=25.60]\nEpoch 0: |          | 398/? [02:22<00:00,  2.80it/s, train/loss=30.60]\nEpoch 0: |          | 399/? [02:22<00:00,  2.80it/s, train/loss=30.60]\nEpoch 0: |          | 399/? [02:22<00:00,  2.80it/s, train/loss=33.70]\nEpoch 0: |          | 400/? [02:22<00:00,  2.80it/s, train/loss=33.70]\nEpoch 0: |          | 400/? [02:22<00:00,  2.80it/s, train/loss=13.20]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:03, 11.05it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:03, 10.99it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:03, 10.82it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:03, 10.85it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:03, 11.03it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:03, 11.14it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:02, 11.13it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:02, 11.05it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:02, 11.07it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:02, 11.11it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:02, 11.18it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:02, 11.28it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:02, 11.35it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02, 11.39it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02, 11.06it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02, 11.03it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:02, 11.08it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:01<00:01, 11.13it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:01<00:01, 11.17it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:01<00:01, 11.22it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:01<00:01, 11.26it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:01<00:01, 11.30it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:02<00:01, 11.33it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01, 11.36it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01, 11.39it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01, 11.41it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01, 11.45it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:02<00:01, 11.48it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:02<00:00, 11.48it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:02<00:00, 11.49it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:02<00:00, 11.52it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:02<00:00, 11.54it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:02<00:00, 11.56it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:02<00:00, 11.58it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00, 11.57it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:03<00:00, 11.58it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:03<00:00, 11.48it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:03<00:00, 11.36it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:03<00:00, 11.31it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.32it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 400/? [02:29<00:00,  2.67it/s, train/loss=13.20]\nEpoch 0: |          | 401/? [02:30<00:00,  2.66it/s, train/loss=13.20]\nEpoch 0: |          | 401/? [02:30<00:00,  2.66it/s, train/loss=30.60]\nEpoch 0: |          | 402/? [02:31<00:00,  2.66it/s, train/loss=30.60]\nEpoch 0: |          | 402/? [02:31<00:00,  2.66it/s, train/loss=26.40]\nEpoch 0: |          | 403/? [02:31<00:00,  2.66it/s, train/loss=26.40]\nEpoch 0: |          | 403/? [02:31<00:00,  2.66it/s, train/loss=13.50]\nEpoch 0: |          | 404/? [02:31<00:00,  2.66it/s, train/loss=13.50]\nEpoch 0: |          | 404/? [02:31<00:00,  2.66it/s, train/loss=16.60]\nEpoch 0: |          | 405/? [02:32<00:00,  2.66it/s, train/loss=16.60]\nEpoch 0: |          | 405/? [02:32<00:00,  2.66it/s, train/loss=27.20]\nEpoch 0: |          | 406/? [02:32<00:00,  2.66it/s, train/loss=27.20]\nEpoch 0: |          | 406/? [02:32<00:00,  2.66it/s, train/loss=18.70]\nEpoch 0: |          | 407/? [02:32<00:00,  2.66it/s, train/loss=18.70]\nEpoch 0: |          | 407/? [02:32<00:00,  2.66it/s, train/loss=27.70]\nEpoch 0: |          | 408/? [02:33<00:00,  2.66it/s, train/loss=27.70]\nEpoch 0: |          | 408/? [02:33<00:00,  2.66it/s, train/loss=30.20]\nEpoch 0: |          | 409/? [02:33<00:00,  2.66it/s, train/loss=30.20]\nEpoch 0: |          | 409/? [02:33<00:00,  2.66it/s, train/loss=51.20]\nEpoch 0: |          | 410/? [02:33<00:00,  2.66it/s, train/loss=51.20]\nEpoch 0: |          | 410/? [02:33<00:00,  2.66it/s, train/loss=16.80]\nEpoch 0: |          | 411/? [02:34<00:00,  2.67it/s, train/loss=16.80]\nEpoch 0: |          | 411/? [02:34<00:00,  2.67it/s, train/loss=18.90]\nEpoch 0: |          | 412/? [02:34<00:00,  2.67it/s, train/loss=18.90]\nEpoch 0: |          | 412/? [02:34<00:00,  2.67it/s, train/loss=58.30]\nEpoch 0: |          | 413/? [02:34<00:00,  2.67it/s, train/loss=58.30]\nEpoch 0: |          | 413/? [02:34<00:00,  2.67it/s, train/loss=42.70]\nEpoch 0: |          | 414/? [02:35<00:00,  2.67it/s, train/loss=42.70]\nEpoch 0: |          | 414/? [02:35<00:00,  2.67it/s, train/loss=64.70]\nEpoch 0: |          | 415/? [02:35<00:00,  2.67it/s, train/loss=64.70]\nEpoch 0: |          | 415/? [02:35<00:00,  2.67it/s, train/loss=19.50]\nEpoch 0: |          | 416/? [02:35<00:00,  2.67it/s, train/loss=19.50]\nEpoch 0: |          | 416/? [02:35<00:00,  2.67it/s, train/loss=24.70]\nEpoch 0: |          | 417/? [02:36<00:00,  2.67it/s, train/loss=24.70]\nEpoch 0: |          | 417/? [02:36<00:00,  2.67it/s, train/loss=18.20]\nEpoch 0: |          | 418/? [02:36<00:00,  2.67it/s, train/loss=18.20]\nEpoch 0: |          | 418/? [02:36<00:00,  2.67it/s, train/loss=17.60]\nEpoch 0: |          | 419/? [02:36<00:00,  2.67it/s, train/loss=17.60]\nEpoch 0: |          | 419/? [02:36<00:00,  2.67it/s, train/loss=17.90]\nEpoch 0: |          | 420/? [02:37<00:00,  2.67it/s, train/loss=17.90]\nEpoch 0: |          | 420/? [02:37<00:00,  2.67it/s, train/loss=18.60]\nEpoch 0: |          | 421/? [02:37<00:00,  2.67it/s, train/loss=18.60]\nEpoch 0: |          | 421/? [02:37<00:00,  2.67it/s, train/loss=24.80]\nEpoch 0: |          | 422/? [02:37<00:00,  2.67it/s, train/loss=24.80]\nEpoch 0: |          | 422/? [02:37<00:00,  2.67it/s, train/loss=16.30]\nEpoch 0: |          | 423/? [02:38<00:00,  2.67it/s, train/loss=16.30]\nEpoch 0: |          | 423/? [02:38<00:00,  2.67it/s, train/loss=30.70]\nEpoch 0: |          | 424/? [02:38<00:00,  2.67it/s, train/loss=30.70]\nEpoch 0: |          | 424/? [02:38<00:00,  2.67it/s, train/loss=20.60]\nEpoch 0: |          | 425/? [02:38<00:00,  2.67it/s, train/loss=20.60]\nEpoch 0: |          | 425/? [02:38<00:00,  2.67it/s, train/loss=52.60]\nEpoch 0: |          | 426/? [02:39<00:00,  2.68it/s, train/loss=52.60]\nEpoch 0: |          | 426/? [02:39<00:00,  2.68it/s, train/loss=13.80]\nEpoch 0: |          | 427/? [02:39<00:00,  2.68it/s, train/loss=13.80]\nEpoch 0: |          | 427/? [02:39<00:00,  2.68it/s, train/loss=21.80]\nEpoch 0: |          | 428/? [02:39<00:00,  2.68it/s, train/loss=21.80]\nEpoch 0: |          | 428/? [02:39<00:00,  2.68it/s, train/loss=15.70]\nEpoch 0: |          | 429/? [02:40<00:00,  2.68it/s, train/loss=15.70]\nEpoch 0: |          | 429/? [02:40<00:00,  2.68it/s, train/loss=33.00]\nEpoch 0: |          | 430/? [02:40<00:00,  2.68it/s, train/loss=33.00]\nEpoch 0: |          | 430/? [02:40<00:00,  2.68it/s, train/loss=13.50]\nEpoch 0: |          | 431/? [02:40<00:00,  2.68it/s, train/loss=13.50]\nEpoch 0: |          | 431/? [02:40<00:00,  2.68it/s, train/loss=12.40]\nEpoch 0: |          | 432/? [02:41<00:00,  2.68it/s, train/loss=12.40]\nEpoch 0: |          | 432/? [02:41<00:00,  2.68it/s, train/loss=30.90]\nEpoch 0: |          | 433/? [02:41<00:00,  2.68it/s, train/loss=30.90]\nEpoch 0: |          | 433/? [02:41<00:00,  2.68it/s, train/loss=26.90]\nEpoch 0: |          | 434/? [02:41<00:00,  2.68it/s, train/loss=26.90]\nEpoch 0: |          | 434/? [02:41<00:00,  2.68it/s, train/loss=17.60]\nEpoch 0: |          | 435/? [02:42<00:00,  2.68it/s, train/loss=17.60]\nEpoch 0: |          | 435/? [02:42<00:00,  2.68it/s, train/loss=16.60]\nEpoch 0: |          | 436/? [02:42<00:00,  2.68it/s, train/loss=16.60]\nEpoch 0: |          | 436/? [02:42<00:00,  2.68it/s, train/loss=14.60]\nEpoch 0: |          | 437/? [02:42<00:00,  2.68it/s, train/loss=14.60]\nEpoch 0: |          | 437/? [02:42<00:00,  2.68it/s, train/loss=25.70]\nEpoch 0: |          | 438/? [02:43<00:00,  2.68it/s, train/loss=25.70]\nEpoch 0: |          | 438/? [02:43<00:00,  2.68it/s, train/loss=9.540]\nEpoch 0: |          | 439/? [02:43<00:00,  2.68it/s, train/loss=9.540]\nEpoch 0: |          | 439/? [02:43<00:00,  2.68it/s, train/loss=8.600]\nEpoch 0: |          | 440/? [02:43<00:00,  2.69it/s, train/loss=8.600]\nEpoch 0: |          | 440/? [02:43<00:00,  2.69it/s, train/loss=35.50]\nEpoch 0: |          | 441/? [02:44<00:00,  2.69it/s, train/loss=35.50]\nEpoch 0: |          | 441/? [02:44<00:00,  2.69it/s, train/loss=35.10]\nEpoch 0: |          | 442/? [02:44<00:00,  2.69it/s, train/loss=35.10]\nEpoch 0: |          | 442/? [02:44<00:00,  2.69it/s, train/loss=17.60]\nEpoch 0: |          | 443/? [02:44<00:00,  2.69it/s, train/loss=17.60]\nEpoch 0: |          | 443/? [02:44<00:00,  2.69it/s, train/loss=23.50]\nEpoch 0: |          | 444/? [02:45<00:00,  2.69it/s, train/loss=23.50]\nEpoch 0: |          | 444/? [02:45<00:00,  2.69it/s, train/loss=7.570]\nEpoch 0: |          | 445/? [02:45<00:00,  2.69it/s, train/loss=7.570]\nEpoch 0: |          | 445/? [02:45<00:00,  2.69it/s, train/loss=40.90]\nEpoch 0: |          | 446/? [02:45<00:00,  2.69it/s, train/loss=40.90]\nEpoch 0: |          | 446/? [02:45<00:00,  2.69it/s, train/loss=12.80]\nEpoch 0: |          | 447/? [02:46<00:00,  2.69it/s, train/loss=12.80]\nEpoch 0: |          | 447/? [02:46<00:00,  2.69it/s, train/loss=17.70]\nEpoch 0: |          | 448/? [02:46<00:00,  2.69it/s, train/loss=17.70]\nEpoch 0: |          | 448/? [02:46<00:00,  2.69it/s, train/loss=6.630]\nEpoch 0: |          | 449/? [02:46<00:00,  2.69it/s, train/loss=6.630]\nEpoch 0: |          | 449/? [02:46<00:00,  2.69it/s, train/loss=36.00]\nEpoch 0: |          | 450/? [02:47<00:00,  2.69it/s, train/loss=36.00]\nEpoch 0: |          | 450/? [02:47<00:00,  2.69it/s, train/loss=18.80]\nEpoch 0: |          | 451/? [02:47<00:00,  2.69it/s, train/loss=18.80]\nEpoch 0: |          | 451/? [02:47<00:00,  2.69it/s, train/loss=14.00]\nEpoch 0: |          | 452/? [02:47<00:00,  2.69it/s, train/loss=14.00]\nEpoch 0: |          | 452/? [02:47<00:00,  2.69it/s, train/loss=83.80]\nEpoch 0: |          | 453/? [02:48<00:00,  2.69it/s, train/loss=83.80]\nEpoch 0: |          | 453/? [02:48<00:00,  2.69it/s, train/loss=43.40]\nEpoch 0: |          | 454/? [02:48<00:00,  2.70it/s, train/loss=43.40]\nEpoch 0: |          | 454/? [02:48<00:00,  2.70it/s, train/loss=20.80]\nEpoch 0: |          | 455/? [02:48<00:00,  2.70it/s, train/loss=20.80]\nEpoch 0: |          | 455/? [02:48<00:00,  2.70it/s, train/loss=9.980]\nEpoch 0: |          | 456/? [02:49<00:00,  2.70it/s, train/loss=9.980]\nEpoch 0: |          | 456/? [02:49<00:00,  2.70it/s, train/loss=17.70]\nEpoch 0: |          | 457/? [02:49<00:00,  2.70it/s, train/loss=17.70]\nEpoch 0: |          | 457/? [02:49<00:00,  2.70it/s, train/loss=30.30]\nEpoch 0: |          | 458/? [02:49<00:00,  2.70it/s, train/loss=30.30]\nEpoch 0: |          | 458/? [02:49<00:00,  2.70it/s, train/loss=46.60]\nEpoch 0: |          | 459/? [02:50<00:00,  2.70it/s, train/loss=46.60]\nEpoch 0: |          | 459/? [02:50<00:00,  2.70it/s, train/loss=34.10]\nEpoch 0: |          | 460/? [02:50<00:00,  2.70it/s, train/loss=34.10]\nEpoch 0: |          | 460/? [02:50<00:00,  2.70it/s, train/loss=17.40]\nEpoch 0: |          | 461/? [02:50<00:00,  2.70it/s, train/loss=17.40]\nEpoch 0: |          | 461/? [02:50<00:00,  2.70it/s, train/loss=47.60]\nEpoch 0: |          | 462/? [02:51<00:00,  2.70it/s, train/loss=47.60]\nEpoch 0: |          | 462/? [02:51<00:00,  2.70it/s, train/loss=28.80]\nEpoch 0: |          | 463/? [02:51<00:00,  2.70it/s, train/loss=28.80]\nEpoch 0: |          | 463/? [02:51<00:00,  2.70it/s, train/loss=17.10]\nEpoch 0: |          | 464/? [02:51<00:00,  2.70it/s, train/loss=17.10]\nEpoch 0: |          | 464/? [02:51<00:00,  2.70it/s, train/loss=9.830]\nEpoch 0: |          | 465/? [02:52<00:00,  2.70it/s, train/loss=9.830]\nEpoch 0: |          | 465/? [02:52<00:00,  2.70it/s, train/loss=44.80]\nEpoch 0: |          | 466/? [02:52<00:00,  2.70it/s, train/loss=44.80]\nEpoch 0: |          | 466/? [02:52<00:00,  2.70it/s, train/loss=7.480]\nEpoch 0: |          | 467/? [02:52<00:00,  2.70it/s, train/loss=7.480]\nEpoch 0: |          | 467/? [02:52<00:00,  2.70it/s, train/loss=9.460]\nEpoch 0: |          | 468/? [02:53<00:00,  2.70it/s, train/loss=9.460]\nEpoch 0: |          | 468/? [02:53<00:00,  2.70it/s, train/loss=12.20]\nEpoch 0: |          | 469/? [02:53<00:00,  2.70it/s, train/loss=12.20]\nEpoch 0: |          | 469/? [02:53<00:00,  2.70it/s, train/loss=51.10]\nEpoch 0: |          | 470/? [02:53<00:00,  2.70it/s, train/loss=51.10]\nEpoch 0: |          | 470/? [02:53<00:00,  2.70it/s, train/loss=27.10]\nEpoch 0: |          | 471/? [02:54<00:00,  2.70it/s, train/loss=27.10]\nEpoch 0: |          | 471/? [02:54<00:00,  2.70it/s, train/loss=44.90]\nEpoch 0: |          | 472/? [02:54<00:00,  2.70it/s, train/loss=44.90]\nEpoch 0: |          | 472/? [02:54<00:00,  2.70it/s, train/loss=16.30]\nEpoch 0: |          | 473/? [02:54<00:00,  2.70it/s, train/loss=16.30]\nEpoch 0: |          | 473/? [02:54<00:00,  2.70it/s, train/loss=41.40]\nEpoch 0: |          | 474/? [02:55<00:00,  2.70it/s, train/loss=41.40]\nEpoch 0: |          | 474/? [02:55<00:00,  2.70it/s, train/loss=14.00]\nEpoch 0: |          | 475/? [02:55<00:00,  2.71it/s, train/loss=14.00]\nEpoch 0: |          | 475/? [02:55<00:00,  2.71it/s, train/loss=8.040]\nEpoch 0: |          | 476/? [02:55<00:00,  2.71it/s, train/loss=8.040]\nEpoch 0: |          | 476/? [02:55<00:00,  2.71it/s, train/loss=29.40]\nEpoch 0: |          | 477/? [02:56<00:00,  2.71it/s, train/loss=29.40]\nEpoch 0: |          | 477/? [02:56<00:00,  2.71it/s, train/loss=49.00]\nEpoch 0: |          | 478/? [02:56<00:00,  2.71it/s, train/loss=49.00]\nEpoch 0: |          | 478/? [02:56<00:00,  2.71it/s, train/loss=18.30]\nEpoch 0: |          | 479/? [02:56<00:00,  2.71it/s, train/loss=18.30]\nEpoch 0: |          | 479/? [02:56<00:00,  2.71it/s, train/loss=10.50]\nEpoch 0: |          | 480/? [02:57<00:00,  2.71it/s, train/loss=10.50]\nEpoch 0: |          | 480/? [02:57<00:00,  2.71it/s, train/loss=29.50]\nEpoch 0: |          | 481/? [02:57<00:00,  2.71it/s, train/loss=29.50]\nEpoch 0: |          | 481/? [02:57<00:00,  2.71it/s, train/loss=14.10]\nEpoch 0: |          | 482/? [02:57<00:00,  2.71it/s, train/loss=14.10]\nEpoch 0: |          | 482/? [02:57<00:00,  2.71it/s, train/loss=24.80]\nEpoch 0: |          | 483/? [02:58<00:00,  2.71it/s, train/loss=24.80]\nEpoch 0: |          | 483/? [02:58<00:00,  2.71it/s, train/loss=8.920]\nEpoch 0: |          | 484/? [02:58<00:00,  2.71it/s, train/loss=8.920]\nEpoch 0: |          | 484/? [02:58<00:00,  2.71it/s, train/loss=26.50]\nEpoch 0: |          | 485/? [02:58<00:00,  2.71it/s, train/loss=26.50]\nEpoch 0: |          | 485/? [02:58<00:00,  2.71it/s, train/loss=29.00]\nEpoch 0: |          | 486/? [02:59<00:00,  2.71it/s, train/loss=29.00]\nEpoch 0: |          | 486/? [02:59<00:00,  2.71it/s, train/loss=27.30]\nEpoch 0: |          | 487/? [02:59<00:00,  2.71it/s, train/loss=27.30]\nEpoch 0: |          | 487/? [02:59<00:00,  2.71it/s, train/loss=14.50]\nEpoch 0: |          | 488/? [02:59<00:00,  2.71it/s, train/loss=14.50]\nEpoch 0: |          | 488/? [02:59<00:00,  2.71it/s, train/loss=15.10]\nEpoch 0: |          | 489/? [03:00<00:00,  2.71it/s, train/loss=15.10]\nEpoch 0: |          | 489/? [03:00<00:00,  2.71it/s, train/loss=42.50]\nEpoch 0: |          | 490/? [03:00<00:00,  2.71it/s, train/loss=42.50]\nEpoch 0: |          | 490/? [03:00<00:00,  2.71it/s, train/loss=16.70]\nEpoch 0: |          | 491/? [03:00<00:00,  2.72it/s, train/loss=16.70]\nEpoch 0: |          | 491/? [03:00<00:00,  2.72it/s, train/loss=15.50]\nEpoch 0: |          | 492/? [03:01<00:00,  2.72it/s, train/loss=15.50]\nEpoch 0: |          | 492/? [03:01<00:00,  2.72it/s, train/loss=14.40]\nEpoch 0: |          | 493/? [03:01<00:00,  2.72it/s, train/loss=14.40]\nEpoch 0: |          | 493/? [03:01<00:00,  2.72it/s, train/loss=44.80]\nEpoch 0: |          | 494/? [03:01<00:00,  2.72it/s, train/loss=44.80]\nEpoch 0: |          | 494/? [03:01<00:00,  2.72it/s, train/loss=22.20]\nEpoch 0: |          | 495/? [03:02<00:00,  2.72it/s, train/loss=22.20]\nEpoch 0: |          | 495/? [03:02<00:00,  2.72it/s, train/loss=17.40]\nEpoch 0: |          | 496/? [03:02<00:00,  2.72it/s, train/loss=17.40]\nEpoch 0: |          | 496/? [03:02<00:00,  2.72it/s, train/loss=25.70]\nEpoch 0: |          | 497/? [03:02<00:00,  2.72it/s, train/loss=25.70]\nEpoch 0: |          | 497/? [03:02<00:00,  2.72it/s, train/loss=29.50]\nEpoch 0: |          | 498/? [03:03<00:00,  2.72it/s, train/loss=29.50]\nEpoch 0: |          | 498/? [03:03<00:00,  2.72it/s, train/loss=37.70]\nEpoch 0: |          | 499/? [03:03<00:00,  2.72it/s, train/loss=37.70]\nEpoch 0: |          | 499/? [03:03<00:00,  2.72it/s, train/loss=7.640]\nEpoch 0: |          | 500/? [03:03<00:00,  2.72it/s, train/loss=7.640]\nEpoch 0: |          | 500/? [03:03<00:00,  2.72it/s, train/loss=14.00]\nEpoch 0: |          | 501/? [03:04<00:00,  2.72it/s, train/loss=14.00]\nEpoch 0: |          | 501/? [03:04<00:00,  2.72it/s, train/loss=40.30]\nEpoch 0: |          | 502/? [03:04<00:00,  2.72it/s, train/loss=40.30]\nEpoch 0: |          | 502/? [03:04<00:00,  2.72it/s, train/loss=32.80]\nEpoch 0: |          | 503/? [03:04<00:00,  2.72it/s, train/loss=32.80]\nEpoch 0: |          | 503/? [03:04<00:00,  2.72it/s, train/loss=20.80]\nEpoch 0: |          | 504/? [03:05<00:00,  2.72it/s, train/loss=20.80]\nEpoch 0: |          | 504/? [03:05<00:00,  2.72it/s, train/loss=39.40]\nEpoch 0: |          | 505/? [03:05<00:00,  2.72it/s, train/loss=39.40]\nEpoch 0: |          | 505/? [03:05<00:00,  2.72it/s, train/loss=22.80]\nEpoch 0: |          | 506/? [03:05<00:00,  2.72it/s, train/loss=22.80]\nEpoch 0: |          | 506/? [03:05<00:00,  2.72it/s, train/loss=22.80]\nEpoch 0: |          | 507/? [03:06<00:00,  2.72it/s, train/loss=22.80]\nEpoch 0: |          | 507/? [03:06<00:00,  2.72it/s, train/loss=21.10]\nEpoch 0: |          | 508/? [03:06<00:00,  2.72it/s, train/loss=21.10]\nEpoch 0: |          | 508/? [03:06<00:00,  2.72it/s, train/loss=8.100]\nEpoch 0: |          | 509/? [03:06<00:00,  2.73it/s, train/loss=8.100]\nEpoch 0: |          | 509/? [03:06<00:00,  2.73it/s, train/loss=21.00]\nEpoch 0: |          | 510/? [03:07<00:00,  2.73it/s, train/loss=21.00]\nEpoch 0: |          | 510/? [03:07<00:00,  2.73it/s, train/loss=10.50]\nEpoch 0: |          | 511/? [03:07<00:00,  2.73it/s, train/loss=10.50]\nEpoch 0: |          | 511/? [03:07<00:00,  2.73it/s, train/loss=32.80]\nEpoch 0: |          | 512/? [03:07<00:00,  2.73it/s, train/loss=32.80]\nEpoch 0: |          | 512/? [03:07<00:00,  2.73it/s, train/loss=10.10]\nEpoch 0: |          | 513/? [03:08<00:00,  2.73it/s, train/loss=10.10]\nEpoch 0: |          | 513/? [03:08<00:00,  2.73it/s, train/loss=34.70]\nEpoch 0: |          | 514/? [03:08<00:00,  2.73it/s, train/loss=34.70]\nEpoch 0: |          | 514/? [03:08<00:00,  2.73it/s, train/loss=12.70]\nEpoch 0: |          | 515/? [03:08<00:00,  2.73it/s, train/loss=12.70]\nEpoch 0: |          | 515/? [03:08<00:00,  2.73it/s, train/loss=8.430]\nEpoch 0: |          | 516/? [03:09<00:00,  2.73it/s, train/loss=8.430]\nEpoch 0: |          | 516/? [03:09<00:00,  2.73it/s, train/loss=16.00]\nEpoch 0: |          | 517/? [03:09<00:00,  2.73it/s, train/loss=16.00]\nEpoch 0: |          | 517/? [03:09<00:00,  2.73it/s, train/loss=25.90]\nEpoch 0: |          | 518/? [03:09<00:00,  2.73it/s, train/loss=25.90]\nEpoch 0: |          | 518/? [03:09<00:00,  2.73it/s, train/loss=13.20]\nEpoch 0: |          | 519/? [03:10<00:00,  2.73it/s, train/loss=13.20]\nEpoch 0: |          | 519/? [03:10<00:00,  2.73it/s, train/loss=30.10]\nEpoch 0: |          | 520/? [03:10<00:00,  2.73it/s, train/loss=30.10]\nEpoch 0: |          | 520/? [03:10<00:00,  2.73it/s, train/loss=26.40]\nEpoch 0: |          | 521/? [03:10<00:00,  2.73it/s, train/loss=26.40]\nEpoch 0: |          | 521/? [03:10<00:00,  2.73it/s, train/loss=28.50]\nEpoch 0: |          | 522/? [03:11<00:00,  2.73it/s, train/loss=28.50]\nEpoch 0: |          | 522/? [03:11<00:00,  2.73it/s, train/loss=29.50]\nEpoch 0: |          | 523/? [03:11<00:00,  2.73it/s, train/loss=29.50]\nEpoch 0: |          | 523/? [03:11<00:00,  2.73it/s, train/loss=23.70]\nEpoch 0: |          | 524/? [03:11<00:00,  2.73it/s, train/loss=23.70]\nEpoch 0: |          | 524/? [03:11<00:00,  2.73it/s, train/loss=14.50]\nEpoch 0: |          | 525/? [03:12<00:00,  2.73it/s, train/loss=14.50]\nEpoch 0: |          | 525/? [03:12<00:00,  2.73it/s, train/loss=25.00]\nEpoch 0: |          | 526/? [03:12<00:00,  2.73it/s, train/loss=25.00]\nEpoch 0: |          | 526/? [03:12<00:00,  2.73it/s, train/loss=35.40]\nEpoch 0: |          | 527/? [03:12<00:00,  2.73it/s, train/loss=35.40]\nEpoch 0: |          | 527/? [03:12<00:00,  2.73it/s, train/loss=29.80]\nEpoch 0: |          | 528/? [03:13<00:00,  2.73it/s, train/loss=29.80]\nEpoch 0: |          | 528/? [03:13<00:00,  2.73it/s, train/loss=24.20]\nEpoch 0: |          | 529/? [03:13<00:00,  2.73it/s, train/loss=24.20]\nEpoch 0: |          | 529/? [03:13<00:00,  2.73it/s, train/loss=28.20]\nEpoch 0: |          | 530/? [03:13<00:00,  2.73it/s, train/loss=28.20]\nEpoch 0: |          | 530/? [03:13<00:00,  2.73it/s, train/loss=19.10]\nEpoch 0: |          | 531/? [03:14<00:00,  2.74it/s, train/loss=19.10]\nEpoch 0: |          | 531/? [03:14<00:00,  2.74it/s, train/loss=20.40]\nEpoch 0: |          | 532/? [03:14<00:00,  2.74it/s, train/loss=20.40]\nEpoch 0: |          | 532/? [03:14<00:00,  2.74it/s, train/loss=30.20]\nEpoch 0: |          | 533/? [03:14<00:00,  2.74it/s, train/loss=30.20]\nEpoch 0: |          | 533/? [03:14<00:00,  2.74it/s, train/loss=19.40]\nEpoch 0: |          | 534/? [03:15<00:00,  2.74it/s, train/loss=19.40]\nEpoch 0: |          | 534/? [03:15<00:00,  2.74it/s, train/loss=21.10]\nEpoch 0: |          | 535/? [03:15<00:00,  2.74it/s, train/loss=21.10]\nEpoch 0: |          | 535/? [03:15<00:00,  2.74it/s, train/loss=15.40]\nEpoch 0: |          | 536/? [03:15<00:00,  2.74it/s, train/loss=15.40]\nEpoch 0: |          | 536/? [03:15<00:00,  2.74it/s, train/loss=27.50]\nEpoch 0: |          | 537/? [03:16<00:00,  2.74it/s, train/loss=27.50]\nEpoch 0: |          | 537/? [03:16<00:00,  2.74it/s, train/loss=20.20]\nEpoch 0: |          | 538/? [03:16<00:00,  2.74it/s, train/loss=20.20]\nEpoch 0: |          | 538/? [03:16<00:00,  2.74it/s, train/loss=9.040]\nEpoch 0: |          | 539/? [03:16<00:00,  2.74it/s, train/loss=9.040]\nEpoch 0: |          | 539/? [03:16<00:00,  2.74it/s, train/loss=19.20]\nEpoch 0: |          | 540/? [03:17<00:00,  2.74it/s, train/loss=19.20]\nEpoch 0: |          | 540/? [03:17<00:00,  2.74it/s, train/loss=23.50]\nEpoch 0: |          | 541/? [03:17<00:00,  2.74it/s, train/loss=23.50]\nEpoch 0: |          | 541/? [03:17<00:00,  2.74it/s, train/loss=18.80]\nEpoch 0: |          | 542/? [03:17<00:00,  2.74it/s, train/loss=18.80]\nEpoch 0: |          | 542/? [03:17<00:00,  2.74it/s, train/loss=12.30]\nEpoch 0: |          | 543/? [03:18<00:00,  2.74it/s, train/loss=12.30]\nEpoch 0: |          | 543/? [03:18<00:00,  2.74it/s, train/loss=31.00]\nEpoch 0: |          | 544/? [03:18<00:00,  2.74it/s, train/loss=31.00]\nEpoch 0: |          | 544/? [03:18<00:00,  2.74it/s, train/loss=12.90]\nEpoch 0: |          | 545/? [03:18<00:00,  2.74it/s, train/loss=12.90]\nEpoch 0: |          | 545/? [03:18<00:00,  2.74it/s, train/loss=16.30]\nEpoch 0: |          | 546/? [03:19<00:00,  2.74it/s, train/loss=16.30]\nEpoch 0: |          | 546/? [03:19<00:00,  2.74it/s, train/loss=18.80]\nEpoch 0: |          | 547/? [03:19<00:00,  2.74it/s, train/loss=18.80]\nEpoch 0: |          | 547/? [03:19<00:00,  2.74it/s, train/loss=19.40]\nEpoch 0: |          | 548/? [03:19<00:00,  2.74it/s, train/loss=19.40]\nEpoch 0: |          | 548/? [03:19<00:00,  2.74it/s, train/loss=21.10]\nEpoch 0: |          | 549/? [03:19<00:00,  2.75it/s, train/loss=21.10]\nEpoch 0: |          | 549/? [03:20<00:00,  2.74it/s, train/loss=28.20]\nEpoch 0: |          | 550/? [03:20<00:00,  2.75it/s, train/loss=28.20]\nEpoch 0: |          | 550/? [03:20<00:00,  2.75it/s, train/loss=28.10]\nEpoch 0: |          | 551/? [03:20<00:00,  2.75it/s, train/loss=28.10]\nEpoch 0: |          | 551/? [03:20<00:00,  2.75it/s, train/loss=48.30]\nEpoch 0: |          | 552/? [03:20<00:00,  2.75it/s, train/loss=48.30]\nEpoch 0: |          | 552/? [03:20<00:00,  2.75it/s, train/loss=24.20]\nEpoch 0: |          | 553/? [03:21<00:00,  2.75it/s, train/loss=24.20]\nEpoch 0: |          | 553/? [03:21<00:00,  2.75it/s, train/loss=31.10]\nEpoch 0: |          | 554/? [03:21<00:00,  2.75it/s, train/loss=31.10]\nEpoch 0: |          | 554/? [03:21<00:00,  2.75it/s, train/loss=24.40]\nEpoch 0: |          | 555/? [03:21<00:00,  2.75it/s, train/loss=24.40]\nEpoch 0: |          | 555/? [03:21<00:00,  2.75it/s, train/loss=19.50]\nEpoch 0: |          | 556/? [03:22<00:00,  2.75it/s, train/loss=19.50]\nEpoch 0: |          | 556/? [03:22<00:00,  2.75it/s, train/loss=25.60]\nEpoch 0: |          | 557/? [03:22<00:00,  2.75it/s, train/loss=25.60]\nEpoch 0: |          | 557/? [03:22<00:00,  2.75it/s, train/loss=23.50]\nEpoch 0: |          | 558/? [03:22<00:00,  2.75it/s, train/loss=23.50]\nEpoch 0: |          | 558/? [03:22<00:00,  2.75it/s, train/loss=19.50]\nEpoch 0: |          | 559/? [03:23<00:00,  2.75it/s, train/loss=19.50]\nEpoch 0: |          | 559/? [03:23<00:00,  2.75it/s, train/loss=19.30]\nEpoch 0: |          | 560/? [03:23<00:00,  2.75it/s, train/loss=19.30]\nEpoch 0: |          | 560/? [03:23<00:00,  2.75it/s, train/loss=10.50]\nEpoch 0: |          | 561/? [03:23<00:00,  2.75it/s, train/loss=10.50]\nEpoch 0: |          | 561/? [03:23<00:00,  2.75it/s, train/loss=27.50]\nEpoch 0: |          | 562/? [03:24<00:00,  2.75it/s, train/loss=27.50]\nEpoch 0: |          | 562/? [03:24<00:00,  2.75it/s, train/loss=27.70]\nEpoch 0: |          | 563/? [03:24<00:00,  2.75it/s, train/loss=27.70]\nEpoch 0: |          | 563/? [03:24<00:00,  2.75it/s, train/loss=17.00]\nEpoch 0: |          | 564/? [03:24<00:00,  2.75it/s, train/loss=17.00]\nEpoch 0: |          | 564/? [03:24<00:00,  2.75it/s, train/loss=13.70]\nEpoch 0: |          | 565/? [03:25<00:00,  2.75it/s, train/loss=13.70]\nEpoch 0: |          | 565/? [03:25<00:00,  2.75it/s, train/loss=25.20]\nEpoch 0: |          | 566/? [03:25<00:00,  2.75it/s, train/loss=25.20]\nEpoch 0: |          | 566/? [03:25<00:00,  2.75it/s, train/loss=20.40]\nEpoch 0: |          | 567/? [03:25<00:00,  2.75it/s, train/loss=20.40]\nEpoch 0: |          | 567/? [03:25<00:00,  2.75it/s, train/loss=22.20]\nEpoch 0: |          | 568/? [03:26<00:00,  2.75it/s, train/loss=22.20]\nEpoch 0: |          | 568/? [03:26<00:00,  2.75it/s, train/loss=22.10]\nEpoch 0: |          | 569/? [03:26<00:00,  2.75it/s, train/loss=22.10]\nEpoch 0: |          | 569/? [03:26<00:00,  2.75it/s, train/loss=18.20]\nEpoch 0: |          | 570/? [03:26<00:00,  2.75it/s, train/loss=18.20]\nEpoch 0: |          | 570/? [03:26<00:00,  2.75it/s, train/loss=28.90]\nEpoch 0: |          | 571/? [03:27<00:00,  2.76it/s, train/loss=28.90]\nEpoch 0: |          | 571/? [03:27<00:00,  2.75it/s, train/loss=35.40]\nEpoch 0: |          | 572/? [03:27<00:00,  2.76it/s, train/loss=35.40]\nEpoch 0: |          | 572/? [03:27<00:00,  2.76it/s, train/loss=10.30]\nEpoch 0: |          | 573/? [03:27<00:00,  2.76it/s, train/loss=10.30]\nEpoch 0: |          | 573/? [03:27<00:00,  2.76it/s, train/loss=21.20]\nEpoch 0: |          | 574/? [03:28<00:00,  2.76it/s, train/loss=21.20]\nEpoch 0: |          | 574/? [03:28<00:00,  2.76it/s, train/loss=38.30]\nEpoch 0: |          | 575/? [03:28<00:00,  2.76it/s, train/loss=38.30]\nEpoch 0: |          | 575/? [03:28<00:00,  2.76it/s, train/loss=6.780]\nEpoch 0: |          | 576/? [03:28<00:00,  2.76it/s, train/loss=6.780]\nEpoch 0: |          | 576/? [03:28<00:00,  2.76it/s, train/loss=9.820]\nEpoch 0: |          | 577/? [03:29<00:00,  2.76it/s, train/loss=9.820]\nEpoch 0: |          | 577/? [03:29<00:00,  2.76it/s, train/loss=19.20]\nEpoch 0: |          | 578/? [03:29<00:00,  2.76it/s, train/loss=19.20]\nEpoch 0: |          | 578/? [03:29<00:00,  2.76it/s, train/loss=18.50]\nEpoch 0: |          | 579/? [03:29<00:00,  2.76it/s, train/loss=18.50]\nEpoch 0: |          | 579/? [03:29<00:00,  2.76it/s, train/loss=16.60]\nEpoch 0: |          | 580/? [03:30<00:00,  2.76it/s, train/loss=16.60]\nEpoch 0: |          | 580/? [03:30<00:00,  2.76it/s, train/loss=41.70]\nEpoch 0: |          | 581/? [03:30<00:00,  2.76it/s, train/loss=41.70]\nEpoch 0: |          | 581/? [03:30<00:00,  2.76it/s, train/loss=16.80]\nEpoch 0: |          | 582/? [03:30<00:00,  2.76it/s, train/loss=16.80]\nEpoch 0: |          | 582/? [03:30<00:00,  2.76it/s, train/loss=13.50]\nEpoch 0: |          | 583/? [03:31<00:00,  2.76it/s, train/loss=13.50]\nEpoch 0: |          | 583/? [03:31<00:00,  2.76it/s, train/loss=12.60]\nEpoch 0: |          | 584/? [03:31<00:00,  2.76it/s, train/loss=12.60]\nEpoch 0: |          | 584/? [03:31<00:00,  2.76it/s, train/loss=8.210]\nEpoch 0: |          | 585/? [03:31<00:00,  2.76it/s, train/loss=8.210]\nEpoch 0: |          | 585/? [03:31<00:00,  2.76it/s, train/loss=25.00]\nEpoch 0: |          | 586/? [03:32<00:00,  2.76it/s, train/loss=25.00]\nEpoch 0: |          | 586/? [03:32<00:00,  2.76it/s, train/loss=21.70]\nEpoch 0: |          | 587/? [03:32<00:00,  2.76it/s, train/loss=21.70]\nEpoch 0: |          | 587/? [03:32<00:00,  2.76it/s, train/loss=22.60]\nEpoch 0: |          | 588/? [03:32<00:00,  2.76it/s, train/loss=22.60]\nEpoch 0: |          | 588/? [03:32<00:00,  2.76it/s, train/loss=33.70]\nEpoch 0: |          | 589/? [03:33<00:00,  2.76it/s, train/loss=33.70]\nEpoch 0: |          | 589/? [03:33<00:00,  2.76it/s, train/loss=23.50]\nEpoch 0: |          | 590/? [03:33<00:00,  2.76it/s, train/loss=23.50]\nEpoch 0: |          | 590/? [03:33<00:00,  2.76it/s, train/loss=24.20]\nEpoch 0: |          | 591/? [03:33<00:00,  2.76it/s, train/loss=24.20]\nEpoch 0: |          | 591/? [03:33<00:00,  2.76it/s, train/loss=16.40]\nEpoch 0: |          | 592/? [03:34<00:00,  2.76it/s, train/loss=16.40]\nEpoch 0: |          | 592/? [03:34<00:00,  2.76it/s, train/loss=30.10]\nEpoch 0: |          | 593/? [03:34<00:00,  2.76it/s, train/loss=30.10]\nEpoch 0: |          | 593/? [03:34<00:00,  2.76it/s, train/loss=15.80]\nEpoch 0: |          | 594/? [03:34<00:00,  2.76it/s, train/loss=15.80]\nEpoch 0: |          | 594/? [03:34<00:00,  2.76it/s, train/loss=28.50]\nEpoch 0: |          | 595/? [03:35<00:00,  2.76it/s, train/loss=28.50]\nEpoch 0: |          | 595/? [03:35<00:00,  2.76it/s, train/loss=42.00]\nEpoch 0: |          | 596/? [03:35<00:00,  2.76it/s, train/loss=42.00]\nEpoch 0: |          | 596/? [03:35<00:00,  2.76it/s, train/loss=25.40]\nEpoch 0: |          | 597/? [03:35<00:00,  2.77it/s, train/loss=25.40]\nEpoch 0: |          | 597/? [03:35<00:00,  2.77it/s, train/loss=51.90]\nEpoch 0: |          | 598/? [03:36<00:00,  2.77it/s, train/loss=51.90]\nEpoch 0: |          | 598/? [03:36<00:00,  2.77it/s, train/loss=34.00]\nEpoch 0: |          | 599/? [03:36<00:00,  2.77it/s, train/loss=34.00]\nEpoch 0: |          | 599/? [03:36<00:00,  2.77it/s, train/loss=31.20]\nEpoch 0: |          | 600/? [03:36<00:00,  2.77it/s, train/loss=31.20]\nEpoch 0: |          | 600/? [03:36<00:00,  2.77it/s, train/loss=20.80]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:03, 11.29it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:03, 11.44it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:03, 11.46it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:03, 11.58it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:03, 11.58it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:02, 11.64it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:02, 11.63it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:02, 11.72it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:02, 11.78it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:00<00:02, 11.79it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:00<00:02, 11.83it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:02, 11.78it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:02, 11.81it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02, 11.83it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02, 11.86it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02, 11.87it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:01, 11.83it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:01<00:01, 11.85it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:01<00:01, 11.87it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:01<00:01, 11.88it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:01<00:01, 11.90it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:01<00:01, 11.86it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:01<00:01, 11.88it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01, 11.88it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01, 11.85it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01, 11.85it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01, 11.88it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:02<00:01, 11.90it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:02<00:00, 11.92it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:02<00:00, 11.94it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:02<00:00, 11.94it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:02<00:00, 11.75it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:02<00:00, 11.73it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:02<00:00, 11.70it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:02<00:00, 11.71it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:03<00:00, 11.70it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:03<00:00, 11.70it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:03<00:00, 11.71it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:03<00:00, 11.72it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.73it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 600/? [03:43<00:00,  2.68it/s, train/loss=20.80]\nEpoch 0: |          | 601/? [03:44<00:00,  2.67it/s, train/loss=20.80]\nEpoch 0: |          | 601/? [03:44<00:00,  2.67it/s, train/loss=45.20]\nEpoch 0: |          | 602/? [03:45<00:00,  2.67it/s, train/loss=45.20]\nEpoch 0: |          | 602/? [03:45<00:00,  2.67it/s, train/loss=19.60]\nEpoch 0: |          | 603/? [03:45<00:00,  2.67it/s, train/loss=19.60]\nEpoch 0: |          | 603/? [03:45<00:00,  2.67it/s, train/loss=43.40]\nEpoch 0: |          | 604/? [03:45<00:00,  2.68it/s, train/loss=43.40]\nEpoch 0: |          | 604/? [03:45<00:00,  2.68it/s, train/loss=9.500]\nEpoch 0: |          | 605/? [03:46<00:00,  2.68it/s, train/loss=9.500]\nEpoch 0: |          | 605/? [03:46<00:00,  2.68it/s, train/loss=18.10]\nEpoch 0: |          | 606/? [03:46<00:00,  2.68it/s, train/loss=18.10]\nEpoch 0: |          | 606/? [03:46<00:00,  2.68it/s, train/loss=21.10]\nEpoch 0: |          | 607/? [03:46<00:00,  2.68it/s, train/loss=21.10]\nEpoch 0: |          | 607/? [03:46<00:00,  2.68it/s, train/loss=22.80]\nEpoch 0: |          | 608/? [03:47<00:00,  2.68it/s, train/loss=22.80]\nEpoch 0: |          | 608/? [03:47<00:00,  2.68it/s, train/loss=30.10]\nEpoch 0: |          | 609/? [03:47<00:00,  2.68it/s, train/loss=30.10]\nEpoch 0: |          | 609/? [03:47<00:00,  2.68it/s, train/loss=24.90]\nEpoch 0: |          | 610/? [03:47<00:00,  2.68it/s, train/loss=24.90]\nEpoch 0: |          | 610/? [03:47<00:00,  2.68it/s, train/loss=11.10]\nEpoch 0: |          | 611/? [03:48<00:00,  2.68it/s, train/loss=11.10]\nEpoch 0: |          | 611/? [03:48<00:00,  2.68it/s, train/loss=26.60]\nEpoch 0: |          | 612/? [03:48<00:00,  2.68it/s, train/loss=26.60]\nEpoch 0: |          | 612/? [03:48<00:00,  2.68it/s, train/loss=26.10]\nEpoch 0: |          | 613/? [03:48<00:00,  2.68it/s, train/loss=26.10]\nEpoch 0: |          | 613/? [03:48<00:00,  2.68it/s, train/loss=27.20]\nEpoch 0: |          | 614/? [03:49<00:00,  2.68it/s, train/loss=27.20]\nEpoch 0: |          | 614/? [03:49<00:00,  2.68it/s, train/loss=23.90]\nEpoch 0: |          | 615/? [03:49<00:00,  2.68it/s, train/loss=23.90]\nEpoch 0: |          | 615/? [03:49<00:00,  2.68it/s, train/loss=50.80]\nEpoch 0: |          | 616/? [03:49<00:00,  2.68it/s, train/loss=50.80]\nEpoch 0: |          | 616/? [03:49<00:00,  2.68it/s, train/loss=8.490]\nEpoch 0: |          | 617/? [03:50<00:00,  2.68it/s, train/loss=8.490]\nEpoch 0: |          | 617/? [03:50<00:00,  2.68it/s, train/loss=18.10]\nEpoch 0: |          | 618/? [03:50<00:00,  2.68it/s, train/loss=18.10]\nEpoch 0: |          | 618/? [03:50<00:00,  2.68it/s, train/loss=8.960]\nEpoch 0: |          | 619/? [03:50<00:00,  2.68it/s, train/loss=8.960]\nEpoch 0: |          | 619/? [03:50<00:00,  2.68it/s, train/loss=20.80]\nEpoch 0: |          | 620/? [03:51<00:00,  2.68it/s, train/loss=20.80]\nEpoch 0: |          | 620/? [03:51<00:00,  2.68it/s, train/loss=7.220]\nEpoch 0: |          | 621/? [03:51<00:00,  2.68it/s, train/loss=7.220]\nEpoch 0: |          | 621/? [03:51<00:00,  2.68it/s, train/loss=32.80]\nEpoch 0: |          | 622/? [03:51<00:00,  2.68it/s, train/loss=32.80]\nEpoch 0: |          | 622/? [03:51<00:00,  2.68it/s, train/loss=20.60]\nEpoch 0: |          | 623/? [03:51<00:00,  2.69it/s, train/loss=20.60]\nEpoch 0: |          | 623/? [03:51<00:00,  2.69it/s, train/loss=41.70]\nEpoch 0: |          | 624/? [03:52<00:00,  2.69it/s, train/loss=41.70]\nEpoch 0: |          | 624/? [03:52<00:00,  2.69it/s, train/loss=22.60]\nEpoch 0: |          | 625/? [03:52<00:00,  2.69it/s, train/loss=22.60]\nEpoch 0: |          | 625/? [03:52<00:00,  2.69it/s, train/loss=18.70]\nEpoch 0: |          | 626/? [03:52<00:00,  2.69it/s, train/loss=18.70]\nEpoch 0: |          | 626/? [03:52<00:00,  2.69it/s, train/loss=14.00]\nEpoch 0: |          | 627/? [03:53<00:00,  2.69it/s, train/loss=14.00]\nEpoch 0: |          | 627/? [03:53<00:00,  2.69it/s, train/loss=24.30]\nEpoch 0: |          | 628/? [03:53<00:00,  2.69it/s, train/loss=24.30]\nEpoch 0: |          | 628/? [03:53<00:00,  2.69it/s, train/loss=20.40]\nEpoch 0: |          | 629/? [03:53<00:00,  2.69it/s, train/loss=20.40]\nEpoch 0: |          | 629/? [03:53<00:00,  2.69it/s, train/loss=34.40]\nEpoch 0: |          | 630/? [03:54<00:00,  2.69it/s, train/loss=34.40]\nEpoch 0: |          | 630/? [03:54<00:00,  2.69it/s, train/loss=27.80]\nEpoch 0: |          | 631/? [03:54<00:00,  2.69it/s, train/loss=27.80]\nEpoch 0: |          | 631/? [03:54<00:00,  2.69it/s, train/loss=13.00]\nEpoch 0: |          | 632/? [03:54<00:00,  2.69it/s, train/loss=13.00]\nEpoch 0: |          | 632/? [03:54<00:00,  2.69it/s, train/loss=16.80]\nEpoch 0: |          | 633/? [03:55<00:00,  2.69it/s, train/loss=16.80]\nEpoch 0: |          | 633/? [03:55<00:00,  2.69it/s, train/loss=47.30]\nEpoch 0: |          | 634/? [03:55<00:00,  2.69it/s, train/loss=47.30]\nEpoch 0: |          | 634/? [03:55<00:00,  2.69it/s, train/loss=24.20]\nEpoch 0: |          | 635/? [03:55<00:00,  2.69it/s, train/loss=24.20]\nEpoch 0: |          | 635/? [03:55<00:00,  2.69it/s, train/loss=7.330]\nEpoch 0: |          | 636/? [03:56<00:00,  2.69it/s, train/loss=7.330]\nEpoch 0: |          | 636/? [03:56<00:00,  2.69it/s, train/loss=14.50]\nEpoch 0: |          | 637/? [03:56<00:00,  2.69it/s, train/loss=14.50]\nEpoch 0: |          | 637/? [03:56<00:00,  2.69it/s, train/loss=28.80]\nEpoch 0: |          | 638/? [03:56<00:00,  2.69it/s, train/loss=28.80]\nEpoch 0: |          | 638/? [03:56<00:00,  2.69it/s, train/loss=24.00]\nEpoch 0: |          | 639/? [03:57<00:00,  2.69it/s, train/loss=24.00]\nEpoch 0: |          | 639/? [03:57<00:00,  2.69it/s, train/loss=7.980]\nEpoch 0: |          | 640/? [03:57<00:00,  2.69it/s, train/loss=7.980]\nEpoch 0: |          | 640/? [03:57<00:00,  2.69it/s, train/loss=46.90]\nEpoch 0: |          | 641/? [03:57<00:00,  2.69it/s, train/loss=46.90]\nEpoch 0: |          | 641/? [03:57<00:00,  2.69it/s, train/loss=21.50]\nEpoch 0: |          | 642/? [03:58<00:00,  2.70it/s, train/loss=21.50]\nEpoch 0: |          | 642/? [03:58<00:00,  2.70it/s, train/loss=40.10]\nEpoch 0: |          | 643/? [03:58<00:00,  2.70it/s, train/loss=40.10]\nEpoch 0: |          | 643/? [03:58<00:00,  2.70it/s, train/loss=41.30]\nEpoch 0: |          | 644/? [03:58<00:00,  2.70it/s, train/loss=41.30]\nEpoch 0: |          | 644/? [03:58<00:00,  2.70it/s, train/loss=48.10]\nEpoch 0: |          | 645/? [03:59<00:00,  2.70it/s, train/loss=48.10]\nEpoch 0: |          | 645/? [03:59<00:00,  2.70it/s, train/loss=21.50]\nEpoch 0: |          | 646/? [03:59<00:00,  2.70it/s, train/loss=21.50]\nEpoch 0: |          | 646/? [03:59<00:00,  2.70it/s, train/loss=24.60]\nEpoch 0: |          | 647/? [03:59<00:00,  2.70it/s, train/loss=24.60]\nEpoch 0: |          | 647/? [03:59<00:00,  2.70it/s, train/loss=63.90]\nEpoch 0: |          | 648/? [04:00<00:00,  2.70it/s, train/loss=63.90]\nEpoch 0: |          | 648/? [04:00<00:00,  2.70it/s, train/loss=20.90]\nEpoch 0: |          | 649/? [04:00<00:00,  2.70it/s, train/loss=20.90]\nEpoch 0: |          | 649/? [04:00<00:00,  2.70it/s, train/loss=55.00]\nEpoch 0: |          | 650/? [04:00<00:00,  2.70it/s, train/loss=55.00]\nEpoch 0: |          | 650/? [04:00<00:00,  2.70it/s, train/loss=25.60]\nEpoch 0: |          | 651/? [04:01<00:00,  2.70it/s, train/loss=25.60]\nEpoch 0: |          | 651/? [04:01<00:00,  2.70it/s, train/loss=17.00]\nEpoch 0: |          | 652/? [04:01<00:00,  2.70it/s, train/loss=17.00]\nEpoch 0: |          | 652/? [04:01<00:00,  2.70it/s, train/loss=19.20]\nEpoch 0: |          | 653/? [04:01<00:00,  2.70it/s, train/loss=19.20]\nEpoch 0: |          | 653/? [04:01<00:00,  2.70it/s, train/loss=20.70]\nEpoch 0: |          | 654/? [04:02<00:00,  2.70it/s, train/loss=20.70]\nEpoch 0: |          | 654/? [04:02<00:00,  2.70it/s, train/loss=31.90]\nEpoch 0: |          | 655/? [04:02<00:00,  2.70it/s, train/loss=31.90]\nEpoch 0: |          | 655/? [04:02<00:00,  2.70it/s, train/loss=13.60]\nEpoch 0: |          | 656/? [04:03<00:00,  2.70it/s, train/loss=13.60]\nEpoch 0: |          | 656/? [04:03<00:00,  2.70it/s, train/loss=25.40]\nEpoch 0: |          | 657/? [04:03<00:00,  2.70it/s, train/loss=25.40]\nEpoch 0: |          | 657/? [04:03<00:00,  2.70it/s, train/loss=42.40]\nEpoch 0: |          | 658/? [04:03<00:00,  2.70it/s, train/loss=42.40]\nEpoch 0: |          | 658/? [04:03<00:00,  2.70it/s, train/loss=12.40]\nEpoch 0: |          | 659/? [04:04<00:00,  2.70it/s, train/loss=12.40]\nEpoch 0: |          | 659/? [04:04<00:00,  2.70it/s, train/loss=29.20]\nEpoch 0: |          | 660/? [04:04<00:00,  2.70it/s, train/loss=29.20]\nEpoch 0: |          | 660/? [04:04<00:00,  2.70it/s, train/loss=8.920]\nEpoch 0: |          | 661/? [04:04<00:00,  2.70it/s, train/loss=8.920]\nEpoch 0: |          | 661/? [04:04<00:00,  2.70it/s, train/loss=23.50]\nEpoch 0: |          | 662/? [04:05<00:00,  2.70it/s, train/loss=23.50]\nEpoch 0: |          | 662/? [04:05<00:00,  2.70it/s, train/loss=24.90]\nEpoch 0: |          | 663/? [04:05<00:00,  2.70it/s, train/loss=24.90]\nEpoch 0: |          | 663/? [04:05<00:00,  2.70it/s, train/loss=33.00]\nEpoch 0: |          | 664/? [04:05<00:00,  2.70it/s, train/loss=33.00]\nEpoch 0: |          | 664/? [04:05<00:00,  2.70it/s, train/loss=19.80]\nEpoch 0: |          | 665/? [04:05<00:00,  2.70it/s, train/loss=19.80]\nEpoch 0: |          | 665/? [04:05<00:00,  2.70it/s, train/loss=25.70]\nEpoch 0: |          | 666/? [04:06<00:00,  2.70it/s, train/loss=25.70]\nEpoch 0: |          | 666/? [04:06<00:00,  2.70it/s, train/loss=27.60]\nEpoch 0: |          | 667/? [04:06<00:00,  2.70it/s, train/loss=27.60]\nEpoch 0: |          | 667/? [04:06<00:00,  2.70it/s, train/loss=36.80]\nEpoch 0: |          | 668/? [04:06<00:00,  2.70it/s, train/loss=36.80]\nEpoch 0: |          | 668/? [04:06<00:00,  2.70it/s, train/loss=18.20]\nEpoch 0: |          | 669/? [04:07<00:00,  2.71it/s, train/loss=18.20]\nEpoch 0: |          | 669/? [04:07<00:00,  2.71it/s, train/loss=29.60]\nEpoch 0: |          | 670/? [04:07<00:00,  2.71it/s, train/loss=29.60]\nEpoch 0: |          | 670/? [04:07<00:00,  2.71it/s, train/loss=52.50]\nEpoch 0: |          | 671/? [04:07<00:00,  2.71it/s, train/loss=52.50]\nEpoch 0: |          | 671/? [04:07<00:00,  2.71it/s, train/loss=11.80]\nEpoch 0: |          | 672/? [04:08<00:00,  2.71it/s, train/loss=11.80]\nEpoch 0: |          | 672/? [04:08<00:00,  2.71it/s, train/loss=19.90]\nEpoch 0: |          | 673/? [04:08<00:00,  2.71it/s, train/loss=19.90]\nEpoch 0: |          | 673/? [04:08<00:00,  2.71it/s, train/loss=17.60]\nEpoch 0: |          | 674/? [04:08<00:00,  2.71it/s, train/loss=17.60]\nEpoch 0: |          | 674/? [04:08<00:00,  2.71it/s, train/loss=31.90]\nEpoch 0: |          | 675/? [04:09<00:00,  2.71it/s, train/loss=31.90]\nEpoch 0: |          | 675/? [04:09<00:00,  2.71it/s, train/loss=24.00]\nEpoch 0: |          | 676/? [04:09<00:00,  2.71it/s, train/loss=24.00]\nEpoch 0: |          | 676/? [04:09<00:00,  2.71it/s, train/loss=9.220]\nEpoch 0: |          | 677/? [04:09<00:00,  2.71it/s, train/loss=9.220]\nEpoch 0: |          | 677/? [04:09<00:00,  2.71it/s, train/loss=29.80]\nEpoch 0: |          | 678/? [04:10<00:00,  2.71it/s, train/loss=29.80]\nEpoch 0: |          | 678/? [04:10<00:00,  2.71it/s, train/loss=9.360]\nEpoch 0: |          | 679/? [04:10<00:00,  2.71it/s, train/loss=9.360]\nEpoch 0: |          | 679/? [04:10<00:00,  2.71it/s, train/loss=26.90]\nEpoch 0: |          | 680/? [04:10<00:00,  2.71it/s, train/loss=26.90]\nEpoch 0: |          | 680/? [04:10<00:00,  2.71it/s, train/loss=23.60]\nEpoch 0: |          | 681/? [04:11<00:00,  2.71it/s, train/loss=23.60]\nEpoch 0: |          | 681/? [04:11<00:00,  2.71it/s, train/loss=24.20]\nEpoch 0: |          | 682/? [04:11<00:00,  2.71it/s, train/loss=24.20]\nEpoch 0: |          | 682/? [04:11<00:00,  2.71it/s, train/loss=29.20]\nEpoch 0: |          | 683/? [04:11<00:00,  2.71it/s, train/loss=29.20]\nEpoch 0: |          | 683/? [04:11<00:00,  2.71it/s, train/loss=23.70]\nEpoch 0: |          | 684/? [04:12<00:00,  2.71it/s, train/loss=23.70]\nEpoch 0: |          | 684/? [04:12<00:00,  2.71it/s, train/loss=8.900]\nEpoch 0: |          | 685/? [04:12<00:00,  2.71it/s, train/loss=8.900]\nEpoch 0: |          | 685/? [04:12<00:00,  2.71it/s, train/loss=29.60]\nEpoch 0: |          | 686/? [04:12<00:00,  2.71it/s, train/loss=29.60]\nEpoch 0: |          | 686/? [04:12<00:00,  2.71it/s, train/loss=44.80]\nEpoch 0: |          | 687/? [04:13<00:00,  2.71it/s, train/loss=44.80]\nEpoch 0: |          | 687/? [04:13<00:00,  2.71it/s, train/loss=65.00]\nEpoch 0: |          | 688/? [04:13<00:00,  2.71it/s, train/loss=65.00]\nEpoch 0: |          | 688/? [04:13<00:00,  2.71it/s, train/loss=17.10]\nEpoch 0: |          | 689/? [04:13<00:00,  2.71it/s, train/loss=17.10]\nEpoch 0: |          | 689/? [04:13<00:00,  2.71it/s, train/loss=28.30]\nEpoch 0: |          | 690/? [04:14<00:00,  2.71it/s, train/loss=28.30]\nEpoch 0: |          | 690/? [04:14<00:00,  2.71it/s, train/loss=38.20]\nEpoch 0: |          | 691/? [04:14<00:00,  2.72it/s, train/loss=38.20]\nEpoch 0: |          | 691/? [04:14<00:00,  2.72it/s, train/loss=9.110]\nEpoch 0: |          | 692/? [04:14<00:00,  2.72it/s, train/loss=9.110]\nEpoch 0: |          | 692/? [04:14<00:00,  2.72it/s, train/loss=29.20]\nEpoch 0: |          | 693/? [04:15<00:00,  2.72it/s, train/loss=29.20]\nEpoch 0: |          | 693/? [04:15<00:00,  2.72it/s, train/loss=16.60]\nEpoch 0: |          | 694/? [04:15<00:00,  2.72it/s, train/loss=16.60]\nEpoch 0: |          | 694/? [04:15<00:00,  2.72it/s, train/loss=31.70]\nEpoch 0: |          | 695/? [04:15<00:00,  2.72it/s, train/loss=31.70]\nEpoch 0: |          | 695/? [04:15<00:00,  2.72it/s, train/loss=11.80]\nEpoch 0: |          | 696/? [04:16<00:00,  2.72it/s, train/loss=11.80]\nEpoch 0: |          | 696/? [04:16<00:00,  2.72it/s, train/loss=29.40]\nEpoch 0: |          | 697/? [04:16<00:00,  2.72it/s, train/loss=29.40]\nEpoch 0: |          | 697/? [04:16<00:00,  2.72it/s, train/loss=35.70]\nEpoch 0: |          | 698/? [04:16<00:00,  2.72it/s, train/loss=35.70]\nEpoch 0: |          | 698/? [04:16<00:00,  2.72it/s, train/loss=14.40]\nEpoch 0: |          | 699/? [04:17<00:00,  2.72it/s, train/loss=14.40]\nEpoch 0: |          | 699/? [04:17<00:00,  2.72it/s, train/loss=34.40]\nEpoch 0: |          | 700/? [04:17<00:00,  2.72it/s, train/loss=34.40]\nEpoch 0: |          | 700/? [04:17<00:00,  2.72it/s, train/loss=12.10]\nEpoch 0: |          | 701/? [04:17<00:00,  2.72it/s, train/loss=12.10]\nEpoch 0: |          | 701/? [04:17<00:00,  2.72it/s, train/loss=15.30]\nEpoch 0: |          | 702/? [04:18<00:00,  2.72it/s, train/loss=15.30]\nEpoch 0: |          | 702/? [04:18<00:00,  2.72it/s, train/loss=22.70]\nEpoch 0: |          | 703/? [04:18<00:00,  2.72it/s, train/loss=22.70]\nEpoch 0: |          | 703/? [04:18<00:00,  2.72it/s, train/loss=20.80]\nEpoch 0: |          | 704/? [04:18<00:00,  2.72it/s, train/loss=20.80]\nEpoch 0: |          | 704/? [04:18<00:00,  2.72it/s, train/loss=7.570]\nEpoch 0: |          | 705/? [04:19<00:00,  2.72it/s, train/loss=7.570]\nEpoch 0: |          | 705/? [04:19<00:00,  2.72it/s, train/loss=21.90]\nEpoch 0: |          | 706/? [04:19<00:00,  2.72it/s, train/loss=21.90]\nEpoch 0: |          | 706/? [04:19<00:00,  2.72it/s, train/loss=19.50]\nEpoch 0: |          | 707/? [04:19<00:00,  2.72it/s, train/loss=19.50]\nEpoch 0: |          | 707/? [04:19<00:00,  2.72it/s, train/loss=11.60]\nEpoch 0: |          | 708/? [04:20<00:00,  2.72it/s, train/loss=11.60]\nEpoch 0: |          | 708/? [04:20<00:00,  2.72it/s, train/loss=13.30]\nEpoch 0: |          | 709/? [04:20<00:00,  2.72it/s, train/loss=13.30]\nEpoch 0: |          | 709/? [04:20<00:00,  2.72it/s, train/loss=17.80]\nEpoch 0: |          | 710/? [04:20<00:00,  2.72it/s, train/loss=17.80]\nEpoch 0: |          | 710/? [04:20<00:00,  2.72it/s, train/loss=19.00]\nEpoch 0: |          | 711/? [04:21<00:00,  2.72it/s, train/loss=19.00]\nEpoch 0: |          | 711/? [04:21<00:00,  2.72it/s, train/loss=21.70]\nEpoch 0: |          | 712/? [04:21<00:00,  2.72it/s, train/loss=21.70]\nEpoch 0: |          | 712/? [04:21<00:00,  2.72it/s, train/loss=35.30]\nEpoch 0: |          | 713/? [04:21<00:00,  2.72it/s, train/loss=35.30]\nEpoch 0: |          | 713/? [04:21<00:00,  2.72it/s, train/loss=21.40]\nEpoch 0: |          | 714/? [04:22<00:00,  2.72it/s, train/loss=21.40]\nEpoch 0: |          | 714/? [04:22<00:00,  2.72it/s, train/loss=34.50]\nEpoch 0: |          | 715/? [04:22<00:00,  2.72it/s, train/loss=34.50]\nEpoch 0: |          | 715/? [04:22<00:00,  2.72it/s, train/loss=26.30]\nEpoch 0: |          | 716/? [04:22<00:00,  2.73it/s, train/loss=26.30]\nEpoch 0: |          | 716/? [04:22<00:00,  2.73it/s, train/loss=17.80]\nEpoch 0: |          | 717/? [04:23<00:00,  2.73it/s, train/loss=17.80]\nEpoch 0: |          | 717/? [04:23<00:00,  2.73it/s, train/loss=70.40]\nEpoch 0: |          | 718/? [04:23<00:00,  2.73it/s, train/loss=70.40]\nEpoch 0: |          | 718/? [04:23<00:00,  2.73it/s, train/loss=27.50]\nEpoch 0: |          | 719/? [04:23<00:00,  2.73it/s, train/loss=27.50]\nEpoch 0: |          | 719/? [04:23<00:00,  2.73it/s, train/loss=17.10]\nEpoch 0: |          | 720/? [04:24<00:00,  2.73it/s, train/loss=17.10]\nEpoch 0: |          | 720/? [04:24<00:00,  2.73it/s, train/loss=13.80]\nEpoch 0: |          | 721/? [04:24<00:00,  2.73it/s, train/loss=13.80]\nEpoch 0: |          | 721/? [04:24<00:00,  2.73it/s, train/loss=39.50]\nEpoch 0: |          | 722/? [04:24<00:00,  2.73it/s, train/loss=39.50]\nEpoch 0: |          | 722/? [04:24<00:00,  2.73it/s, train/loss=23.60]\nEpoch 0: |          | 723/? [04:25<00:00,  2.73it/s, train/loss=23.60]\nEpoch 0: |          | 723/? [04:25<00:00,  2.73it/s, train/loss=37.80]\nEpoch 0: |          | 724/? [04:25<00:00,  2.73it/s, train/loss=37.80]\nEpoch 0: |          | 724/? [04:25<00:00,  2.73it/s, train/loss=18.90]\nEpoch 0: |          | 725/? [04:25<00:00,  2.73it/s, train/loss=18.90]\nEpoch 0: |          | 725/? [04:25<00:00,  2.73it/s, train/loss=31.20]\nEpoch 0: |          | 726/? [04:25<00:00,  2.73it/s, train/loss=31.20]\nEpoch 0: |          | 726/? [04:25<00:00,  2.73it/s, train/loss=23.20]\nEpoch 0: |          | 727/? [04:26<00:00,  2.73it/s, train/loss=23.20]\nEpoch 0: |          | 727/? [04:26<00:00,  2.73it/s, train/loss=20.90]\nEpoch 0: |          | 728/? [04:26<00:00,  2.73it/s, train/loss=20.90]\nEpoch 0: |          | 728/? [04:26<00:00,  2.73it/s, train/loss=24.60]\nEpoch 0: |          | 729/? [04:26<00:00,  2.73it/s, train/loss=24.60]\nEpoch 0: |          | 729/? [04:26<00:00,  2.73it/s, train/loss=16.90]\nEpoch 0: |          | 730/? [04:27<00:00,  2.73it/s, train/loss=16.90]\nEpoch 0: |          | 730/? [04:27<00:00,  2.73it/s, train/loss=14.70]\nEpoch 0: |          | 731/? [04:27<00:00,  2.73it/s, train/loss=14.70]\nEpoch 0: |          | 731/? [04:27<00:00,  2.73it/s, train/loss=7.040]\nEpoch 0: |          | 732/? [04:27<00:00,  2.73it/s, train/loss=7.040]\nEpoch 0: |          | 732/? [04:27<00:00,  2.73it/s, train/loss=16.10]\nEpoch 0: |          | 733/? [04:28<00:00,  2.73it/s, train/loss=16.10]\nEpoch 0: |          | 733/? [04:28<00:00,  2.73it/s, train/loss=39.30]\nEpoch 0: |          | 734/? [04:28<00:00,  2.73it/s, train/loss=39.30]\nEpoch 0: |          | 734/? [04:28<00:00,  2.73it/s, train/loss=26.50]\nEpoch 0: |          | 735/? [04:28<00:00,  2.73it/s, train/loss=26.50]\nEpoch 0: |          | 735/? [04:28<00:00,  2.73it/s, train/loss=14.00]\nEpoch 0: |          | 736/? [04:29<00:00,  2.73it/s, train/loss=14.00]\nEpoch 0: |          | 736/? [04:29<00:00,  2.73it/s, train/loss=18.90]\nEpoch 0: |          | 737/? [04:29<00:00,  2.73it/s, train/loss=18.90]\nEpoch 0: |          | 737/? [04:29<00:00,  2.73it/s, train/loss=32.80]\nEpoch 0: |          | 738/? [04:29<00:00,  2.73it/s, train/loss=32.80]\nEpoch 0: |          | 738/? [04:29<00:00,  2.73it/s, train/loss=22.50]\nEpoch 0: |          | 739/? [04:30<00:00,  2.73it/s, train/loss=22.50]\nEpoch 0: |          | 739/? [04:30<00:00,  2.73it/s, train/loss=19.90]\nEpoch 0: |          | 740/? [04:30<00:00,  2.74it/s, train/loss=19.90]\nEpoch 0: |          | 740/? [04:30<00:00,  2.74it/s, train/loss=13.80]\nEpoch 0: |          | 741/? [04:30<00:00,  2.74it/s, train/loss=13.80]\nEpoch 0: |          | 741/? [04:30<00:00,  2.74it/s, train/loss=46.20]\nEpoch 0: |          | 742/? [04:31<00:00,  2.74it/s, train/loss=46.20]\nEpoch 0: |          | 742/? [04:31<00:00,  2.74it/s, train/loss=23.10]\nEpoch 0: |          | 743/? [04:31<00:00,  2.74it/s, train/loss=23.10]\nEpoch 0: |          | 743/? [04:31<00:00,  2.74it/s, train/loss=35.30]\nEpoch 0: |          | 744/? [04:31<00:00,  2.74it/s, train/loss=35.30]\nEpoch 0: |          | 744/? [04:31<00:00,  2.74it/s, train/loss=17.30]\nEpoch 0: |          | 745/? [04:32<00:00,  2.74it/s, train/loss=17.30]\nEpoch 0: |          | 745/? [04:32<00:00,  2.74it/s, train/loss=35.60]\nEpoch 0: |          | 746/? [04:32<00:00,  2.74it/s, train/loss=35.60]\nEpoch 0: |          | 746/? [04:32<00:00,  2.74it/s, train/loss=30.30]\nEpoch 0: |          | 747/? [04:32<00:00,  2.74it/s, train/loss=30.30]\nEpoch 0: |          | 747/? [04:32<00:00,  2.74it/s, train/loss=9.280]\nEpoch 0: |          | 748/? [04:33<00:00,  2.74it/s, train/loss=9.280]\nEpoch 0: |          | 748/? [04:33<00:00,  2.74it/s, train/loss=35.70]\nEpoch 0: |          | 749/? [04:33<00:00,  2.74it/s, train/loss=35.70]\nEpoch 0: |          | 749/? [04:33<00:00,  2.74it/s, train/loss=30.50]\nEpoch 0: |          | 750/? [04:33<00:00,  2.74it/s, train/loss=30.50]\nEpoch 0: |          | 750/? [04:33<00:00,  2.74it/s, train/loss=28.80]\nEpoch 0: |          | 751/? [04:34<00:00,  2.74it/s, train/loss=28.80]\nEpoch 0: |          | 751/? [04:34<00:00,  2.74it/s, train/loss=23.70]\nEpoch 0: |          | 752/? [04:34<00:00,  2.74it/s, train/loss=23.70]\nEpoch 0: |          | 752/? [04:34<00:00,  2.74it/s, train/loss=22.00]\nEpoch 0: |          | 753/? [04:34<00:00,  2.74it/s, train/loss=22.00]\nEpoch 0: |          | 753/? [04:34<00:00,  2.74it/s, train/loss=16.70]\nEpoch 0: |          | 754/? [04:35<00:00,  2.74it/s, train/loss=16.70]\nEpoch 0: |          | 754/? [04:35<00:00,  2.74it/s, train/loss=8.490]\nEpoch 0: |          | 755/? [04:35<00:00,  2.74it/s, train/loss=8.490]\nEpoch 0: |          | 755/? [04:35<00:00,  2.74it/s, train/loss=12.40]\nEpoch 0: |          | 756/? [04:35<00:00,  2.74it/s, train/loss=12.40]\nEpoch 0: |          | 756/? [04:35<00:00,  2.74it/s, train/loss=11.90]\nEpoch 0: |          | 757/? [04:36<00:00,  2.74it/s, train/loss=11.90]\nEpoch 0: |          | 757/? [04:36<00:00,  2.74it/s, train/loss=15.30]\nEpoch 0: |          | 758/? [04:36<00:00,  2.74it/s, train/loss=15.30]\nEpoch 0: |          | 758/? [04:36<00:00,  2.74it/s, train/loss=18.30]\nEpoch 0: |          | 759/? [04:36<00:00,  2.74it/s, train/loss=18.30]\nEpoch 0: |          | 759/? [04:36<00:00,  2.74it/s, train/loss=15.90]\nEpoch 0: |          | 760/? [04:37<00:00,  2.74it/s, train/loss=15.90]\nEpoch 0: |          | 760/? [04:37<00:00,  2.74it/s, train/loss=30.70]\nEpoch 0: |          | 761/? [04:37<00:00,  2.74it/s, train/loss=30.70]\nEpoch 0: |          | 761/? [04:37<00:00,  2.74it/s, train/loss=37.50]\nEpoch 0: |          | 762/? [04:37<00:00,  2.74it/s, train/loss=37.50]\nEpoch 0: |          | 762/? [04:37<00:00,  2.74it/s, train/loss=24.00]\nEpoch 0: |          | 763/? [04:38<00:00,  2.74it/s, train/loss=24.00]\nEpoch 0: |          | 763/? [04:38<00:00,  2.74it/s, train/loss=23.80]\nEpoch 0: |          | 764/? [04:38<00:00,  2.74it/s, train/loss=23.80]\nEpoch 0: |          | 764/? [04:38<00:00,  2.74it/s, train/loss=13.40]\nEpoch 0: |          | 765/? [04:38<00:00,  2.74it/s, train/loss=13.40]\nEpoch 0: |          | 765/? [04:38<00:00,  2.74it/s, train/loss=41.50]\nEpoch 0: |          | 766/? [04:39<00:00,  2.75it/s, train/loss=41.50]\nEpoch 0: |          | 766/? [04:39<00:00,  2.75it/s, train/loss=29.70]\nEpoch 0: |          | 767/? [04:39<00:00,  2.75it/s, train/loss=29.70]\nEpoch 0: |          | 767/? [04:39<00:00,  2.75it/s, train/loss=16.90]\nEpoch 0: |          | 768/? [04:39<00:00,  2.75it/s, train/loss=16.90]\nEpoch 0: |          | 768/? [04:39<00:00,  2.75it/s, train/loss=31.50]\nEpoch 0: |          | 769/? [04:40<00:00,  2.75it/s, train/loss=31.50]\nEpoch 0: |          | 769/? [04:40<00:00,  2.75it/s, train/loss=29.30]\nEpoch 0: |          | 770/? [04:40<00:00,  2.75it/s, train/loss=29.30]\nEpoch 0: |          | 770/? [04:40<00:00,  2.75it/s, train/loss=23.60]\nEpoch 0: |          | 771/? [04:40<00:00,  2.75it/s, train/loss=23.60]\nEpoch 0: |          | 771/? [04:40<00:00,  2.75it/s, train/loss=17.80]\nEpoch 0: |          | 772/? [04:40<00:00,  2.75it/s, train/loss=17.80]\nEpoch 0: |          | 772/? [04:40<00:00,  2.75it/s, train/loss=11.00]\nEpoch 0: |          | 773/? [04:41<00:00,  2.75it/s, train/loss=11.00]\nEpoch 0: |          | 773/? [04:41<00:00,  2.75it/s, train/loss=34.10]\nEpoch 0: |          | 774/? [04:41<00:00,  2.75it/s, train/loss=34.10]\nEpoch 0: |          | 774/? [04:41<00:00,  2.75it/s, train/loss=15.80]\nEpoch 0: |          | 775/? [04:41<00:00,  2.75it/s, train/loss=15.80]\nEpoch 0: |          | 775/? [04:41<00:00,  2.75it/s, train/loss=8.520]\nEpoch 0: |          | 776/? [04:42<00:00,  2.75it/s, train/loss=8.520]\nEpoch 0: |          | 776/? [04:42<00:00,  2.75it/s, train/loss=6.730]\nEpoch 0: |          | 777/? [04:42<00:00,  2.75it/s, train/loss=6.730]\nEpoch 0: |          | 777/? [04:42<00:00,  2.75it/s, train/loss=16.90]\nEpoch 0: |          | 778/? [04:42<00:00,  2.75it/s, train/loss=16.90]\nEpoch 0: |          | 778/? [04:42<00:00,  2.75it/s, train/loss=19.80]\nEpoch 0: |          | 779/? [04:43<00:00,  2.75it/s, train/loss=19.80]\nEpoch 0: |          | 779/? [04:43<00:00,  2.75it/s, train/loss=53.00]\nEpoch 0: |          | 780/? [04:43<00:00,  2.75it/s, train/loss=53.00]\nEpoch 0: |          | 780/? [04:43<00:00,  2.75it/s, train/loss=22.80]\nEpoch 0: |          | 781/? [04:44<00:00,  2.75it/s, train/loss=22.80]\nEpoch 0: |          | 781/? [04:44<00:00,  2.75it/s, train/loss=22.60]\nEpoch 0: |          | 782/? [04:44<00:00,  2.75it/s, train/loss=22.60]\nEpoch 0: |          | 782/? [04:44<00:00,  2.75it/s, train/loss=12.40]\nEpoch 0: |          | 783/? [04:44<00:00,  2.75it/s, train/loss=12.40]\nEpoch 0: |          | 783/? [04:44<00:00,  2.75it/s, train/loss=27.50]\nEpoch 0: |          | 784/? [04:45<00:00,  2.75it/s, train/loss=27.50]\nEpoch 0: |          | 784/? [04:45<00:00,  2.75it/s, train/loss=32.30]\nEpoch 0: |          | 785/? [04:45<00:00,  2.75it/s, train/loss=32.30]\nEpoch 0: |          | 785/? [04:45<00:00,  2.75it/s, train/loss=36.80]\nEpoch 0: |          | 786/? [04:45<00:00,  2.75it/s, train/loss=36.80]\nEpoch 0: |          | 786/? [04:45<00:00,  2.75it/s, train/loss=21.70]\nEpoch 0: |          | 787/? [04:46<00:00,  2.75it/s, train/loss=21.70]\nEpoch 0: |          | 787/? [04:46<00:00,  2.75it/s, train/loss=38.40]\nEpoch 0: |          | 788/? [04:46<00:00,  2.75it/s, train/loss=38.40]\nEpoch 0: |          | 788/? [04:46<00:00,  2.75it/s, train/loss=37.90]\nEpoch 0: |          | 789/? [04:46<00:00,  2.75it/s, train/loss=37.90]\nEpoch 0: |          | 789/? [04:46<00:00,  2.75it/s, train/loss=36.00]\nEpoch 0: |          | 790/? [04:47<00:00,  2.75it/s, train/loss=36.00]\nEpoch 0: |          | 790/? [04:47<00:00,  2.75it/s, train/loss=20.20]\nEpoch 0: |          | 791/? [04:47<00:00,  2.75it/s, train/loss=20.20]\nEpoch 0: |          | 791/? [04:47<00:00,  2.75it/s, train/loss=21.00]\nEpoch 0: |          | 792/? [04:47<00:00,  2.75it/s, train/loss=21.00]\nEpoch 0: |          | 792/? [04:47<00:00,  2.75it/s, train/loss=18.70]\nEpoch 0: |          | 793/? [04:48<00:00,  2.75it/s, train/loss=18.70]\nEpoch 0: |          | 793/? [04:48<00:00,  2.75it/s, train/loss=48.10]\nEpoch 0: |          | 794/? [04:48<00:00,  2.75it/s, train/loss=48.10]\nEpoch 0: |          | 794/? [04:48<00:00,  2.75it/s, train/loss=8.580]\nEpoch 0: |          | 795/? [04:48<00:00,  2.75it/s, train/loss=8.580]\nEpoch 0: |          | 795/? [04:48<00:00,  2.75it/s, train/loss=20.30]\nEpoch 0: |          | 796/? [04:49<00:00,  2.75it/s, train/loss=20.30]\nEpoch 0: |          | 796/? [04:49<00:00,  2.75it/s, train/loss=17.20]\nEpoch 0: |          | 797/? [04:49<00:00,  2.75it/s, train/loss=17.20]\nEpoch 0: |          | 797/? [04:49<00:00,  2.75it/s, train/loss=21.70]\nEpoch 0: |          | 798/? [04:49<00:00,  2.75it/s, train/loss=21.70]\nEpoch 0: |          | 798/? [04:49<00:00,  2.75it/s, train/loss=30.10]\nEpoch 0: |          | 799/? [04:50<00:00,  2.76it/s, train/loss=30.10]\nEpoch 0: |          | 799/? [04:50<00:00,  2.76it/s, train/loss=13.00]\nEpoch 0: |          | 800/? [04:50<00:00,  2.76it/s, train/loss=13.00]\nEpoch 0: |          | 800/? [04:50<00:00,  2.76it/s, train/loss=6.670]\nValidation: |          | 0/? 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[04:58<00:00,  2.68it/s, train/loss=6.670]\n`Trainer.fit` stopped: `max_steps=800` reached.\nEpoch 0: |          | 800/? [04:58<00:00,  2.68it/s, train/loss=6.670]\nEpoch 0: |          | 800/? [04:58<00:00,  2.68it/s, train/loss=6.670]\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\nTesting: |          | 0/? 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outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save\nRunning step 4: texture refinement\n{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},\n'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},\n'data_type': 'dreamcraft3d-single-image-datamodule',\n'description': '',\n'exp_dir': 'outputs/dreamcraft3d-texture',\n'exp_root_dir': 'outputs',\n'n_gpus': 1,\n'name': 'dreamcraft3d-texture',\n'resume': None,\n'seed': 0,\n'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt'},\n'system_type': 'dreamcraft3d-system',\n'tag': 'replicate_user',\n'timestamp': '@20240222-135357',\n'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0},\n'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357',\n'trial_name': 'replicate_user@20240222-135357',\n'use_timestamp': True}\nInitializing geometry from a given checkpoint ...\nLoading Stable Diffusion ...\nLoading pipeline components...:   0%|          | 0/4 [00:00<?, ?it/s]\nLoading pipeline components...:  25%|██▌       | 1/4 [00:00<00:01,  1.81it/s]\nLoading pipeline components...:  50%|█████     | 2/4 [00:00<00:00,  3.48it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:03<00:00,  1.11it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:03<00:00,  1.26it/s]\nLoading pipeline components...:   0%|          | 0/4 [00:00<?, ?it/s]\nLoading pipeline components...:  25%|██▌       | 1/4 [00:00<00:01,  1.83it/s]\nLoading pipeline components...:  50%|█████     | 2/4 [00:00<00:00,  3.52it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  4.19it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  3.73it/s]\nLoaded Stable Diffusion!\nLoading Stable Zero123 ...\nget obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion\nLatentDiffusion: Running in eps-prediction mode\nDiffusionWrapper has 859.53 M params.\nKeeping EMAs of 688.\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\nLoaded Stable Zero123!\nUsing prompt [A green leafy plant in a striped terracotta pot] and negative prompt []\nUsing view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.\nreturn register_model(fn_wrapper)\ntokenizer/tokenizer_config.json:   0%|          | 0.00/807 [00:00<?, ?B/s]\ntokenizer/tokenizer_config.json: 100%|██████████| 807/807 [00:00<00:00, 5.66MB/s]\ntokenizer/vocab.json:   0%|          | 0.00/1.06M [00:00<?, ?B/s]\ntokenizer/vocab.json: 100%|██████████| 1.06M/1.06M [00:00<00:00, 3.06MB/s]\ntokenizer/vocab.json: 100%|██████████| 1.06M/1.06M [00:00<00:00, 3.06MB/s]\ntokenizer/merges.txt:   0%|          | 0.00/525k [00:00<?, ?B/s]\ntokenizer/merges.txt: 100%|██████████| 525k/525k [00:00<00:00, 21.7MB/s]\ntokenizer/special_tokens_map.json:   0%|          | 0.00/460 [00:00<?, ?B/s]\ntokenizer/special_tokens_map.json: 100%|██████████| 460/460 [00:00<00:00, 2.77MB/s]\nloaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n| Name       | Type                       | Params\n----------------------------------------------------------\n0 | geometry   | TetrahedraSDFGrid          | 12.6 M\n1 | material   | NoMaterial                 | 0\n2 | background | SolidColorBackground       | 0\n3 | renderer   | NVDiffRasterizer           | 0\n4 | guidance   | StableDiffusionBSDGuidance | 870 M\n----------------------------------------------------------\n882 M     Trainable params\n0         Non-trainable params\n882 M     Total params\n3,530.663 Total estimated model params size (MB)\nValidation results will be saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save\nTraining: |          | 0/? [00:00<?, ?it/s]\nTraining: |          | 0/? [00:00<?, ?it/s]\nEpoch 0: |          | 0/? [00:00<?, ?it/s] \nEpoch 0: |          | 1/? [00:01<00:00,  0.61it/s]\nEpoch 0: |          | 1/? [00:01<00:00,  0.60it/s, train/loss=1.330]\nEpoch 0: |          | 2/? [00:01<00:00,  1.03it/s, train/loss=1.330]\nEpoch 0: |          | 2/? [00:02<00:00,  1.00it/s, train/loss=1.800]\nEpoch 0: |          | 3/? [00:02<00:00,  1.46it/s, train/loss=1.800]\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/diffusers/models/attention_processor.py:1746: FutureWarning: `LoRAAttnProcessor` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`\ndeprecate(\nEpoch 0: |          | 3/? [00:02<00:00,  1.46it/s, train/loss=20.90]\nEpoch 0: |          | 4/? 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[00:08<00:00,  2.89it/s, train/loss=2.070]\nEpoch 0: |          | 25/? [00:08<00:00,  2.89it/s, train/loss=17.30]\nEpoch 0: |          | 26/? [00:09<00:00,  2.88it/s, train/loss=17.30]\nEpoch 0: |          | 26/? [00:09<00:00,  2.88it/s, train/loss=1.730]\nEpoch 0: |          | 27/? [00:09<00:00,  2.97it/s, train/loss=1.730]\nEpoch 0: |          | 27/? [00:09<00:00,  2.97it/s, train/loss=17.00]\nEpoch 0: |          | 28/? [00:09<00:00,  2.96it/s, train/loss=17.00]\nEpoch 0: |          | 28/? [00:09<00:00,  2.96it/s, train/loss=2.510]\nEpoch 0: |          | 29/? [00:09<00:00,  3.05it/s, train/loss=2.510]\nEpoch 0: |          | 29/? [00:09<00:00,  3.05it/s, train/loss=16.80]\nEpoch 0: |          | 30/? [00:09<00:00,  3.03it/s, train/loss=16.80]\nEpoch 0: |          | 30/? [00:09<00:00,  3.03it/s, train/loss=3.290]\nEpoch 0: |          | 31/? [00:10<00:00,  2.87it/s, train/loss=3.290]\nEpoch 0: |          | 31/? [00:10<00:00,  2.86it/s, train/loss=2.080]\nEpoch 0: |          | 32/? [00:11<00:00,  2.88it/s, train/loss=2.080]\nEpoch 0: |          | 32/? [00:11<00:00,  2.86it/s, train/loss=0.979]\nEpoch 0: |          | 33/? [00:11<00:00,  2.94it/s, train/loss=0.979]\nEpoch 0: |          | 33/? [00:11<00:00,  2.94it/s, train/loss=16.30]\nEpoch 0: |          | 34/? [00:11<00:00,  2.93it/s, train/loss=16.30]\nEpoch 0: |          | 34/? [00:11<00:00,  2.93it/s, train/loss=1.400]\nEpoch 0: |          | 35/? [00:11<00:00,  3.00it/s, train/loss=1.400]\nEpoch 0: |          | 35/? [00:11<00:00,  3.00it/s, train/loss=16.10]\nEpoch 0: |          | 36/? [00:12<00:00,  2.99it/s, train/loss=16.10]\nEpoch 0: |          | 36/? [00:12<00:00,  2.99it/s, train/loss=2.130]\nEpoch 0: |          | 37/? [00:12<00:00,  3.06it/s, train/loss=2.130]\nEpoch 0: |          | 37/? [00:12<00:00,  3.05it/s, train/loss=15.80]\nEpoch 0: |          | 38/? [00:12<00:00,  3.04it/s, train/loss=15.80]\nEpoch 0: |          | 38/? [00:12<00:00,  3.04it/s, train/loss=2.690]\nEpoch 0: |          | 39/? [00:12<00:00,  3.11it/s, train/loss=2.690]\nEpoch 0: |          | 39/? [00:12<00:00,  3.11it/s, train/loss=15.60]\nEpoch 0: |          | 40/? [00:12<00:00,  3.09it/s, train/loss=15.60]\nEpoch 0: |          | 40/? [00:12<00:00,  3.09it/s, train/loss=0.976]\nEpoch 0: |          | 41/? [00:13<00:00,  2.97it/s, train/loss=0.976]\nEpoch 0: |          | 41/? [00:13<00:00,  2.95it/s, train/loss=1.850]\nEpoch 0: |          | 42/? [00:14<00:00,  2.97it/s, train/loss=1.850]\nEpoch 0: |          | 42/? [00:14<00:00,  2.95it/s, train/loss=0.784]\nEpoch 0: |          | 43/? [00:14<00:00,  3.01it/s, train/loss=0.784]\nEpoch 0: |          | 43/? [00:14<00:00,  3.01it/s, train/loss=15.20]\nEpoch 0: |          | 44/? [00:14<00:00,  3.00it/s, train/loss=15.20]\nEpoch 0: |          | 44/? [00:14<00:00,  3.00it/s, train/loss=1.540]\nEpoch 0: |          | 45/? [00:14<00:00,  3.06it/s, train/loss=1.540]\nEpoch 0: |          | 45/? [00:14<00:00,  3.06it/s, train/loss=15.00]\nEpoch 0: |          | 46/? [00:15<00:00,  3.04it/s, train/loss=15.00]\nEpoch 0: |          | 46/? [00:15<00:00,  3.04it/s, train/loss=1.380]\nEpoch 0: |          | 47/? [00:15<00:00,  3.10it/s, train/loss=1.380]\nEpoch 0: |          | 47/? [00:15<00:00,  3.10it/s, train/loss=14.80]\nEpoch 0: |          | 48/? [00:15<00:00,  3.09it/s, train/loss=14.80]\nEpoch 0: |          | 48/? [00:15<00:00,  3.09it/s, train/loss=2.230]\nEpoch 0: |          | 49/? [00:15<00:00,  3.14it/s, train/loss=2.230]\nEpoch 0: |          | 49/? [00:15<00:00,  3.14it/s, train/loss=14.50]\nEpoch 0: |          | 50/? [00:15<00:00,  3.13it/s, train/loss=14.50]\nEpoch 0: |          | 50/? [00:15<00:00,  3.13it/s, train/loss=3.040]\nEpoch 0: |          | 51/? [00:16<00:00,  3.02it/s, train/loss=3.040]\nEpoch 0: |          | 51/? [00:16<00:00,  3.01it/s, train/loss=0.739]\nEpoch 0: |          | 52/? [00:17<00:00,  3.02it/s, train/loss=0.739]\nEpoch 0: |          | 52/? [00:17<00:00,  3.01it/s, train/loss=3.670]\nEpoch 0: |          | 53/? [00:17<00:00,  3.06it/s, train/loss=3.670]\nEpoch 0: |          | 53/? [00:17<00:00,  3.06it/s, train/loss=14.20]\nEpoch 0: |          | 54/? [00:17<00:00,  3.05it/s, train/loss=14.20]\nEpoch 0: |          | 54/? [00:17<00:00,  3.05it/s, train/loss=1.620]\nEpoch 0: |          | 55/? [00:17<00:00,  3.10it/s, train/loss=1.620]\nEpoch 0: |          | 55/? [00:17<00:00,  3.10it/s, train/loss=14.00]\nEpoch 0: |          | 56/? [00:18<00:00,  3.08it/s, train/loss=14.00]\nEpoch 0: |          | 56/? [00:18<00:00,  3.08it/s, train/loss=2.510]\nEpoch 0: |          | 57/? [00:18<00:00,  3.13it/s, train/loss=2.510]\nEpoch 0: |          | 57/? [00:18<00:00,  3.13it/s, train/loss=13.80]\nEpoch 0: |          | 58/? [00:18<00:00,  3.12it/s, train/loss=13.80]\nEpoch 0: |          | 58/? [00:18<00:00,  3.12it/s, train/loss=3.540]\nEpoch 0: |          | 59/? [00:18<00:00,  3.16it/s, train/loss=3.540]\nEpoch 0: |          | 59/? [00:18<00:00,  3.16it/s, train/loss=13.60]\nEpoch 0: |          | 60/? [00:19<00:00,  3.15it/s, train/loss=13.60]\nEpoch 0: |          | 60/? [00:19<00:00,  3.15it/s, train/loss=3.700]\nEpoch 0: |          | 61/? [00:19<00:00,  3.06it/s, train/loss=3.700]\nEpoch 0: |          | 61/? [00:19<00:00,  3.05it/s, train/loss=0.619]\nEpoch 0: |          | 62/? [00:20<00:00,  3.06it/s, train/loss=0.619]\nEpoch 0: |          | 62/? [00:20<00:00,  3.05it/s, train/loss=2.010]\nEpoch 0: |          | 63/? [00:20<00:00,  3.09it/s, train/loss=2.010]\nEpoch 0: |          | 63/? [00:20<00:00,  3.09it/s, train/loss=13.30]\nEpoch 0: |          | 64/? [00:20<00:00,  3.08it/s, train/loss=13.30]\nEpoch 0: |          | 64/? [00:20<00:00,  3.08it/s, train/loss=1.010]\nEpoch 0: |          | 65/? [00:20<00:00,  3.12it/s, train/loss=1.010]\nEpoch 0: |          | 65/? [00:20<00:00,  3.12it/s, train/loss=13.10]\nEpoch 0: |          | 66/? [00:21<00:00,  3.11it/s, train/loss=13.10]\nEpoch 0: |          | 66/? [00:21<00:00,  3.11it/s, train/loss=3.870]\nEpoch 0: |          | 67/? [00:21<00:00,  3.15it/s, train/loss=3.870]\nEpoch 0: |          | 67/? [00:21<00:00,  3.15it/s, train/loss=12.90]\nEpoch 0: |          | 68/? [00:21<00:00,  3.14it/s, train/loss=12.90]\nEpoch 0: |          | 68/? [00:21<00:00,  3.14it/s, train/loss=2.660]\nEpoch 0: |          | 69/? [00:21<00:00,  3.17it/s, train/loss=2.660]\nEpoch 0: |          | 69/? [00:21<00:00,  3.17it/s, train/loss=12.70]\nEpoch 0: |          | 70/? [00:22<00:00,  3.16it/s, train/loss=12.70]\nEpoch 0: |          | 70/? [00:22<00:00,  3.16it/s, train/loss=3.440]\nEpoch 0: |          | 71/? [00:23<00:00,  3.09it/s, train/loss=3.440]\nEpoch 0: |          | 71/? [00:23<00:00,  3.08it/s, train/loss=0.751]\nEpoch 0: |          | 72/? [00:23<00:00,  3.09it/s, train/loss=0.751]\nEpoch 0: |          | 72/? [00:23<00:00,  3.08it/s, train/loss=2.930]\nEpoch 0: |          | 73/? [00:23<00:00,  3.11it/s, train/loss=2.930]\nEpoch 0: |          | 73/? [00:23<00:00,  3.11it/s, train/loss=12.40]\nEpoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=12.40]\nEpoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=2.180]\nEpoch 0: |          | 75/? [00:23<00:00,  3.14it/s, train/loss=2.180]\nEpoch 0: |          | 75/? [00:23<00:00,  3.14it/s, train/loss=12.20]\nEpoch 0: |          | 76/? [00:24<00:00,  3.13it/s, train/loss=12.20]\nEpoch 0: |          | 76/? [00:24<00:00,  3.13it/s, train/loss=2.370]\nEpoch 0: |          | 77/? [00:24<00:00,  3.17it/s, train/loss=2.370]\nEpoch 0: |          | 77/? [00:24<00:00,  3.17it/s, train/loss=12.00]\nEpoch 0: |          | 78/? [00:24<00:00,  3.16it/s, train/loss=12.00]\nEpoch 0: |          | 78/? [00:24<00:00,  3.16it/s, train/loss=2.250]\nEpoch 0: |          | 79/? [00:24<00:00,  3.19it/s, train/loss=2.250]\nEpoch 0: |          | 79/? [00:24<00:00,  3.19it/s, train/loss=11.80]\nEpoch 0: |          | 80/? [00:25<00:00,  3.18it/s, train/loss=11.80]\nEpoch 0: |          | 80/? [00:25<00:00,  3.18it/s, train/loss=2.530]\nEpoch 0: |          | 81/? [00:26<00:00,  3.11it/s, train/loss=2.530]\nEpoch 0: |          | 81/? [00:26<00:00,  3.10it/s, train/loss=2.030]\nEpoch 0: |          | 82/? [00:26<00:00,  3.11it/s, train/loss=2.030]\nEpoch 0: |          | 82/? [00:26<00:00,  3.10it/s, train/loss=0.990]\nEpoch 0: |          | 83/? [00:26<00:00,  3.14it/s, train/loss=0.990]\nEpoch 0: |          | 83/? [00:26<00:00,  3.13it/s, train/loss=11.50]\nEpoch 0: |          | 84/? [00:26<00:00,  3.13it/s, train/loss=11.50]\nEpoch 0: |          | 84/? [00:26<00:00,  3.13it/s, train/loss=2.540]\nEpoch 0: |          | 85/? [00:26<00:00,  3.16it/s, train/loss=2.540]\nEpoch 0: |          | 85/? [00:26<00:00,  3.16it/s, train/loss=11.40]\nEpoch 0: |          | 86/? [00:27<00:00,  3.15it/s, train/loss=11.40]\nEpoch 0: |          | 86/? [00:27<00:00,  3.15it/s, train/loss=2.830]\nEpoch 0: |          | 87/? [00:27<00:00,  3.18it/s, train/loss=2.830]\nEpoch 0: |          | 87/? [00:27<00:00,  3.18it/s, train/loss=11.20]\nEpoch 0: |          | 88/? [00:27<00:00,  3.17it/s, train/loss=11.20]\nEpoch 0: |          | 88/? [00:27<00:00,  3.17it/s, train/loss=1.430]\nEpoch 0: |          | 89/? [00:27<00:00,  3.20it/s, train/loss=1.430]\nEpoch 0: |          | 89/? [00:27<00:00,  3.20it/s, train/loss=11.10]\nEpoch 0: |          | 90/? [00:28<00:00,  3.19it/s, train/loss=11.10]\nEpoch 0: |          | 90/? [00:28<00:00,  3.19it/s, train/loss=1.880]\nEpoch 0: |          | 91/? [00:29<00:00,  3.13it/s, train/loss=1.880]\nEpoch 0: |          | 91/? [00:29<00:00,  3.12it/s, train/loss=1.450]\nEpoch 0: |          | 92/? [00:29<00:00,  3.13it/s, train/loss=1.450]\nEpoch 0: |          | 92/? [00:29<00:00,  3.12it/s, train/loss=1.310]\nEpoch 0: |          | 93/? [00:29<00:00,  3.15it/s, train/loss=1.310]\nEpoch 0: |          | 93/? [00:29<00:00,  3.15it/s, train/loss=10.80]\nEpoch 0: |          | 94/? [00:29<00:00,  3.14it/s, train/loss=10.80]\nEpoch 0: |          | 94/? [00:29<00:00,  3.14it/s, train/loss=0.665]\nEpoch 0: |          | 95/? [00:29<00:00,  3.17it/s, train/loss=0.665]\nEpoch 0: |          | 95/? [00:29<00:00,  3.17it/s, train/loss=10.70]\nEpoch 0: |          | 96/? [00:30<00:00,  3.16it/s, train/loss=10.70]\nEpoch 0: |          | 96/? [00:30<00:00,  3.16it/s, train/loss=2.050]\nEpoch 0: |          | 97/? [00:30<00:00,  3.19it/s, train/loss=2.050]\nEpoch 0: |          | 97/? [00:30<00:00,  3.19it/s, train/loss=10.50]\nEpoch 0: |          | 98/? [00:30<00:00,  3.18it/s, train/loss=10.50]\nEpoch 0: |          | 98/? [00:30<00:00,  3.18it/s, train/loss=2.290]\nEpoch 0: |          | 99/? [00:30<00:00,  3.21it/s, train/loss=2.290]\nEpoch 0: |          | 99/? [00:30<00:00,  3.21it/s, train/loss=10.40]\nEpoch 0: |          | 100/? [00:31<00:00,  3.20it/s, train/loss=10.40]\nEpoch 0: |          | 100/? [00:31<00:00,  3.20it/s, train/loss=1.910]\nEpoch 0: |          | 101/? [00:32<00:00,  3.15it/s, train/loss=1.910]\nEpoch 0: |          | 101/? [00:32<00:00,  3.14it/s, train/loss=1.090]\nEpoch 0: |          | 102/? [00:32<00:00,  3.15it/s, train/loss=1.090]\nEpoch 0: |          | 102/? [00:32<00:00,  3.14it/s, train/loss=2.970]\nEpoch 0: |          | 103/? [00:32<00:00,  3.17it/s, train/loss=2.970]\nEpoch 0: |          | 103/? [00:32<00:00,  3.17it/s, train/loss=10.10]\nEpoch 0: |          | 104/? [00:32<00:00,  3.16it/s, train/loss=10.10]\nEpoch 0: |          | 104/? [00:32<00:00,  3.16it/s, train/loss=2.400]\nEpoch 0: |          | 105/? [00:32<00:00,  3.18it/s, train/loss=2.400]\nEpoch 0: |          | 105/? [00:32<00:00,  3.18it/s, train/loss=10.00]\nEpoch 0: |          | 106/? [00:33<00:00,  3.18it/s, train/loss=10.00]\nEpoch 0: |          | 106/? [00:33<00:00,  3.18it/s, train/loss=2.730]\nEpoch 0: |          | 107/? [00:33<00:00,  3.20it/s, train/loss=2.730]\nEpoch 0: |          | 107/? [00:33<00:00,  3.20it/s, train/loss=9.900]\nEpoch 0: |          | 108/? [00:33<00:00,  3.20it/s, train/loss=9.900]\nEpoch 0: |          | 108/? [00:33<00:00,  3.20it/s, train/loss=2.430]\nEpoch 0: |          | 109/? [00:33<00:00,  3.22it/s, train/loss=2.430]\nEpoch 0: |          | 109/? [00:33<00:00,  3.22it/s, train/loss=9.770]\nEpoch 0: |          | 110/? [00:34<00:00,  3.21it/s, train/loss=9.770]\nEpoch 0: |          | 110/? [00:34<00:00,  3.21it/s, train/loss=1.070]\nEpoch 0: |          | 111/? [00:35<00:00,  3.16it/s, train/loss=1.070]\nEpoch 0: |          | 111/? [00:35<00:00,  3.15it/s, train/loss=2.210]\nEpoch 0: |          | 112/? [00:35<00:00,  3.16it/s, train/loss=2.210]\nEpoch 0: |          | 112/? [00:35<00:00,  3.15it/s, train/loss=0.631]\nEpoch 0: |          | 113/? [00:35<00:00,  3.18it/s, train/loss=0.631]\nEpoch 0: |          | 113/? [00:35<00:00,  3.18it/s, train/loss=9.550]\nEpoch 0: |          | 114/? [00:35<00:00,  3.17it/s, train/loss=9.550]\nEpoch 0: |          | 114/? [00:35<00:00,  3.17it/s, train/loss=1.270]\nEpoch 0: |          | 115/? [00:36<00:00,  3.19it/s, train/loss=1.270]\nEpoch 0: |          | 115/? [00:36<00:00,  3.19it/s, train/loss=9.450]\nEpoch 0: |          | 116/? [00:36<00:00,  3.19it/s, train/loss=9.450]\nEpoch 0: |          | 116/? [00:36<00:00,  3.19it/s, train/loss=1.790]\nEpoch 0: |          | 117/? [00:36<00:00,  3.21it/s, train/loss=1.790]\nEpoch 0: |          | 117/? [00:36<00:00,  3.21it/s, train/loss=9.340]\nEpoch 0: |          | 118/? [00:36<00:00,  3.20it/s, train/loss=9.340]\nEpoch 0: |          | 118/? [00:36<00:00,  3.20it/s, train/loss=2.310]\nEpoch 0: |          | 119/? [00:36<00:00,  3.23it/s, train/loss=2.310]\nEpoch 0: |          | 119/? [00:36<00:00,  3.23it/s, train/loss=9.220]\nEpoch 0: |          | 120/? [00:37<00:00,  3.22it/s, train/loss=9.220]\nEpoch 0: |          | 120/? [00:37<00:00,  3.22it/s, train/loss=2.210]\nEpoch 0: |          | 121/? [00:38<00:00,  3.17it/s, train/loss=2.210]\nEpoch 0: |          | 121/? [00:38<00:00,  3.17it/s, train/loss=6.350]\nEpoch 0: |          | 122/? [00:38<00:00,  3.17it/s, train/loss=6.350]\nEpoch 0: |          | 122/? [00:38<00:00,  3.16it/s, train/loss=2.140]\nEpoch 0: |          | 123/? [00:38<00:00,  3.19it/s, train/loss=2.140]\nEpoch 0: |          | 123/? [00:38<00:00,  3.19it/s, train/loss=9.020]\nEpoch 0: |          | 124/? [00:38<00:00,  3.18it/s, train/loss=9.020]\nEpoch 0: |          | 124/? [00:38<00:00,  3.18it/s, train/loss=2.490]\nEpoch 0: |          | 125/? [00:39<00:00,  3.20it/s, train/loss=2.490]\nEpoch 0: |          | 125/? [00:39<00:00,  3.20it/s, train/loss=8.930]\nEpoch 0: |          | 126/? [00:39<00:00,  3.20it/s, train/loss=8.930]\nEpoch 0: |          | 126/? [00:39<00:00,  3.20it/s, train/loss=0.836]\nEpoch 0: |          | 127/? [00:39<00:00,  3.22it/s, train/loss=0.836]\nEpoch 0: |          | 127/? [00:39<00:00,  3.22it/s, train/loss=8.830]\nEpoch 0: |          | 128/? [00:39<00:00,  3.21it/s, train/loss=8.830]\nEpoch 0: |          | 128/? [00:39<00:00,  3.21it/s, train/loss=1.060]\nEpoch 0: |          | 129/? [00:39<00:00,  3.23it/s, train/loss=1.060]\nEpoch 0: |          | 129/? [00:39<00:00,  3.23it/s, train/loss=8.730]\nEpoch 0: |          | 130/? [00:40<00:00,  3.23it/s, train/loss=8.730]\nEpoch 0: |          | 130/? [00:40<00:00,  3.23it/s, train/loss=2.120]\nEpoch 0: |          | 131/? [00:41<00:00,  3.18it/s, train/loss=2.120]\nEpoch 0: |          | 131/? [00:41<00:00,  3.18it/s, train/loss=4.420]\nEpoch 0: |          | 132/? [00:41<00:00,  3.18it/s, train/loss=4.420]\nEpoch 0: |          | 132/? [00:41<00:00,  3.17it/s, train/loss=2.920]\nEpoch 0: |          | 133/? [00:41<00:00,  3.19it/s, train/loss=2.920]\nEpoch 0: |          | 133/? [00:41<00:00,  3.19it/s, train/loss=8.560]\nEpoch 0: |          | 134/? [00:42<00:00,  3.19it/s, train/loss=8.560]\nEpoch 0: |          | 134/? [00:42<00:00,  3.19it/s, train/loss=1.740]\nEpoch 0: |          | 135/? [00:42<00:00,  3.21it/s, train/loss=1.740]\nEpoch 0: |          | 135/? [00:42<00:00,  3.21it/s, train/loss=8.480]\nEpoch 0: |          | 136/? [00:42<00:00,  3.20it/s, train/loss=8.480]\nEpoch 0: |          | 136/? [00:42<00:00,  3.20it/s, train/loss=5.630]\nEpoch 0: |          | 137/? [00:42<00:00,  3.22it/s, train/loss=5.630]\nEpoch 0: |          | 137/? [00:42<00:00,  3.22it/s, train/loss=8.390]\nEpoch 0: |          | 138/? [00:42<00:00,  3.22it/s, train/loss=8.390]\nEpoch 0: |          | 138/? [00:42<00:00,  3.22it/s, train/loss=2.640]\nEpoch 0: |          | 139/? [00:42<00:00,  3.24it/s, train/loss=2.640]\nEpoch 0: |          | 139/? [00:42<00:00,  3.24it/s, train/loss=8.310]\nEpoch 0: |          | 140/? [00:43<00:00,  3.23it/s, train/loss=8.310]\nEpoch 0: |          | 140/? [00:43<00:00,  3.23it/s, train/loss=1.650]\nEpoch 0: |          | 141/? [00:44<00:00,  3.19it/s, train/loss=1.650]\nEpoch 0: |          | 141/? [00:44<00:00,  3.18it/s, train/loss=1.890]\nEpoch 0: |          | 142/? [00:44<00:00,  3.19it/s, train/loss=1.890]\nEpoch 0: |          | 142/? [00:44<00:00,  3.18it/s, train/loss=1.700]\nEpoch 0: |          | 143/? [00:44<00:00,  3.20it/s, train/loss=1.700]\nEpoch 0: |          | 143/? [00:44<00:00,  3.20it/s, train/loss=8.180]\nEpoch 0: |          | 144/? [00:45<00:00,  3.20it/s, train/loss=8.180]\nEpoch 0: |          | 144/? [00:45<00:00,  3.20it/s, train/loss=2.450]\nEpoch 0: |          | 145/? [00:45<00:00,  3.21it/s, train/loss=2.450]\nEpoch 0: |          | 145/? [00:45<00:00,  3.21it/s, train/loss=8.110]\nEpoch 0: |          | 146/? [00:45<00:00,  3.21it/s, train/loss=8.110]\nEpoch 0: |          | 146/? [00:45<00:00,  3.21it/s, train/loss=1.610]\nEpoch 0: |          | 147/? [00:45<00:00,  3.22it/s, train/loss=1.610]\nEpoch 0: |          | 147/? [00:45<00:00,  3.22it/s, train/loss=8.040]\nEpoch 0: |          | 148/? [00:45<00:00,  3.22it/s, train/loss=8.040]\nEpoch 0: |          | 148/? [00:45<00:00,  3.22it/s, train/loss=2.790]\nEpoch 0: |          | 149/? [00:46<00:00,  3.24it/s, train/loss=2.790]\nEpoch 0: |          | 149/? [00:46<00:00,  3.23it/s, train/loss=7.960]\nEpoch 0: |          | 150/? [00:46<00:00,  3.23it/s, train/loss=7.960]\nEpoch 0: |          | 150/? [00:46<00:00,  3.23it/s, train/loss=2.020]\nEpoch 0: |          | 151/? [00:47<00:00,  3.19it/s, train/loss=2.020]\nEpoch 0: |          | 151/? [00:47<00:00,  3.19it/s, train/loss=1.330]\nEpoch 0: |          | 152/? [00:47<00:00,  3.18it/s, train/loss=1.330]\nEpoch 0: |          | 152/? [00:47<00:00,  3.18it/s, train/loss=2.790]\nEpoch 0: |          | 153/? [00:47<00:00,  3.20it/s, train/loss=2.790]\nEpoch 0: |          | 153/? [00:47<00:00,  3.20it/s, train/loss=7.830]\nEpoch 0: |          | 154/? [00:48<00:00,  3.19it/s, train/loss=7.830]\nEpoch 0: |          | 154/? [00:48<00:00,  3.19it/s, train/loss=3.220]\nEpoch 0: |          | 155/? [00:48<00:00,  3.21it/s, train/loss=3.220]\nEpoch 0: |          | 155/? [00:48<00:00,  3.21it/s, train/loss=7.760]\nEpoch 0: |          | 156/? [00:48<00:00,  3.20it/s, train/loss=7.760]\nEpoch 0: |          | 156/? [00:48<00:00,  3.20it/s, train/loss=2.120]\nEpoch 0: |          | 157/? [00:48<00:00,  3.22it/s, train/loss=2.120]\nEpoch 0: |          | 157/? [00:48<00:00,  3.22it/s, train/loss=7.700]\nEpoch 0: |          | 158/? [00:49<00:00,  3.20it/s, train/loss=7.700]\nEpoch 0: |          | 158/? [00:49<00:00,  3.20it/s, train/loss=1.940]\nEpoch 0: |          | 159/? [00:49<00:00,  3.21it/s, train/loss=1.940]\nEpoch 0: |          | 159/? [00:49<00:00,  3.21it/s, train/loss=7.640]\nEpoch 0: |          | 160/? [00:49<00:00,  3.20it/s, train/loss=7.640]\nEpoch 0: |          | 160/? [00:49<00:00,  3.20it/s, train/loss=1.960]\nEpoch 0: |          | 161/? [00:51<00:00,  3.15it/s, train/loss=1.960]\nEpoch 0: |          | 161/? [00:51<00:00,  3.15it/s, train/loss=0.607]\nEpoch 0: |          | 162/? [00:51<00:00,  3.14it/s, train/loss=0.607]\nEpoch 0: |          | 162/? [00:51<00:00,  3.14it/s, train/loss=0.631]\nEpoch 0: |          | 163/? [00:51<00:00,  3.15it/s, train/loss=0.631]\nEpoch 0: |          | 163/? [00:51<00:00,  3.15it/s, train/loss=7.540]\nEpoch 0: |          | 164/? [00:52<00:00,  3.14it/s, train/loss=7.540]\nEpoch 0: |          | 164/? [00:52<00:00,  3.14it/s, train/loss=2.620]\nEpoch 0: |          | 165/? [00:52<00:00,  3.15it/s, train/loss=2.620]\nEpoch 0: |          | 165/? [00:52<00:00,  3.15it/s, train/loss=7.500]\nEpoch 0: |          | 166/? [00:52<00:00,  3.15it/s, train/loss=7.500]\nEpoch 0: |          | 166/? [00:52<00:00,  3.15it/s, train/loss=2.730]\nEpoch 0: |          | 167/? [00:52<00:00,  3.16it/s, train/loss=2.730]\nEpoch 0: |          | 167/? [00:52<00:00,  3.16it/s, train/loss=7.450]\nEpoch 0: |          | 168/? [00:53<00:00,  3.16it/s, train/loss=7.450]\nEpoch 0: |          | 168/? [00:53<00:00,  3.16it/s, train/loss=1.880]\nEpoch 0: |          | 169/? [00:53<00:00,  3.17it/s, train/loss=1.880]\nEpoch 0: |          | 169/? [00:53<00:00,  3.17it/s, train/loss=7.390]\nEpoch 0: |          | 170/? [00:53<00:00,  3.17it/s, train/loss=7.390]\nEpoch 0: |          | 170/? [00:53<00:00,  3.17it/s, train/loss=1.330]\nEpoch 0: |          | 171/? [00:54<00:00,  3.13it/s, train/loss=1.330]\nEpoch 0: |          | 171/? [00:54<00:00,  3.13it/s, train/loss=1.980]\nEpoch 0: |          | 172/? [00:54<00:00,  3.13it/s, train/loss=1.980]\nEpoch 0: |          | 172/? [00:54<00:00,  3.13it/s, train/loss=0.843]\nEpoch 0: |          | 173/? [00:55<00:00,  3.14it/s, train/loss=0.843]\nEpoch 0: |          | 173/? [00:55<00:00,  3.14it/s, train/loss=7.300]\nEpoch 0: |          | 174/? [00:55<00:00,  3.14it/s, train/loss=7.300]\nEpoch 0: |          | 174/? [00:55<00:00,  3.14it/s, train/loss=3.970]\nEpoch 0: |          | 175/? [00:55<00:00,  3.15it/s, train/loss=3.970]\nEpoch 0: |          | 175/? [00:55<00:00,  3.15it/s, train/loss=7.240]\nEpoch 0: |          | 176/? [00:55<00:00,  3.15it/s, train/loss=7.240]\nEpoch 0: |          | 176/? [00:55<00:00,  3.15it/s, train/loss=1.490]\nEpoch 0: |          | 177/? [00:55<00:00,  3.16it/s, train/loss=1.490]\nEpoch 0: |          | 177/? [00:55<00:00,  3.16it/s, train/loss=7.180]\nEpoch 0: |          | 178/? [00:56<00:00,  3.16it/s, train/loss=7.180]\nEpoch 0: |          | 178/? [00:56<00:00,  3.16it/s, train/loss=2.410]\nEpoch 0: |          | 179/? [00:56<00:00,  3.18it/s, train/loss=2.410]\nEpoch 0: |          | 179/? [00:56<00:00,  3.18it/s, train/loss=7.130]\nEpoch 0: |          | 180/? [00:56<00:00,  3.17it/s, train/loss=7.130]\nEpoch 0: |          | 180/? [00:56<00:00,  3.17it/s, train/loss=4.450]\nEpoch 0: |          | 181/? [00:57<00:00,  3.14it/s, train/loss=4.450]\nEpoch 0: |          | 181/? [00:57<00:00,  3.13it/s, train/loss=2.640]\nEpoch 0: |          | 182/? [00:58<00:00,  3.13it/s, train/loss=2.640]\nEpoch 0: |          | 182/? [00:58<00:00,  3.12it/s, train/loss=1.290]\nEpoch 0: |          | 183/? [00:58<00:00,  3.13it/s, train/loss=1.290]\nEpoch 0: |          | 183/? [00:58<00:00,  3.13it/s, train/loss=7.040]\nEpoch 0: |          | 184/? [00:58<00:00,  3.12it/s, train/loss=7.040]\nEpoch 0: |          | 184/? [00:58<00:00,  3.12it/s, train/loss=1.280]\nEpoch 0: |          | 185/? [00:58<00:00,  3.14it/s, train/loss=1.280]\nEpoch 0: |          | 185/? [00:58<00:00,  3.14it/s, train/loss=6.990]\nEpoch 0: |          | 186/? [00:59<00:00,  3.14it/s, train/loss=6.990]\nEpoch 0: |          | 186/? [00:59<00:00,  3.14it/s, train/loss=1.760]\nEpoch 0: |          | 187/? [00:59<00:00,  3.15it/s, train/loss=1.760]\nEpoch 0: |          | 187/? [00:59<00:00,  3.15it/s, train/loss=6.940]\nEpoch 0: |          | 188/? [00:59<00:00,  3.15it/s, train/loss=6.940]\nEpoch 0: |          | 188/? [00:59<00:00,  3.15it/s, train/loss=1.270]\nEpoch 0: |          | 189/? [00:59<00:00,  3.16it/s, train/loss=1.270]\nEpoch 0: |          | 189/? [00:59<00:00,  3.16it/s, train/loss=6.890]\nEpoch 0: |          | 190/? [01:00<00:00,  3.16it/s, train/loss=6.890]\nEpoch 0: |          | 190/? [01:00<00:00,  3.16it/s, train/loss=0.835]\nEpoch 0: |          | 191/? [01:01<00:00,  3.12it/s, train/loss=0.835]\nEpoch 0: |          | 191/? [01:01<00:00,  3.12it/s, train/loss=1.100]\nEpoch 0: |          | 192/? [01:01<00:00,  3.12it/s, train/loss=1.100]\nEpoch 0: |          | 192/? [01:01<00:00,  3.12it/s, train/loss=1.180]\nEpoch 0: |          | 193/? [01:01<00:00,  3.13it/s, train/loss=1.180]\nEpoch 0: |          | 193/? [01:01<00:00,  3.13it/s, train/loss=6.810]\nEpoch 0: |          | 194/? [01:01<00:00,  3.13it/s, train/loss=6.810]\nEpoch 0: |          | 194/? [01:01<00:00,  3.13it/s, train/loss=3.430]\nEpoch 0: |          | 195/? [01:02<00:00,  3.14it/s, train/loss=3.430]\nEpoch 0: |          | 195/? [01:02<00:00,  3.14it/s, train/loss=6.770]\nEpoch 0: |          | 196/? [01:02<00:00,  3.14it/s, train/loss=6.770]\nEpoch 0: |          | 196/? [01:02<00:00,  3.14it/s, train/loss=2.480]\nEpoch 0: |          | 197/? [01:02<00:00,  3.15it/s, train/loss=2.480]\nEpoch 0: |          | 197/? [01:02<00:00,  3.15it/s, train/loss=6.720]\nEpoch 0: |          | 198/? [01:02<00:00,  3.15it/s, train/loss=6.720]\nEpoch 0: |          | 198/? [01:02<00:00,  3.15it/s, train/loss=1.160]\nEpoch 0: |          | 199/? [01:02<00:00,  3.16it/s, train/loss=1.160]\nEpoch 0: |          | 199/? [01:02<00:00,  3.16it/s, train/loss=6.670]\nEpoch 0: |          | 200/? [01:03<00:00,  3.16it/s, train/loss=6.670]\nEpoch 0: |          | 200/? [01:03<00:00,  3.16it/s, train/loss=2.950]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:04,  9.34it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:04,  8.52it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:04,  8.71it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:04,  8.76it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:03,  8.88it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:03,  8.96it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:03,  9.00it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:03,  9.05it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:03,  9.06it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:01<00:03,  9.09it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:01<00:03,  9.10it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:03,  9.12it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:02,  9.15it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02,  9.18it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02,  9.17it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02,  9.17it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:02,  9.16it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:01<00:02,  9.18it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:02<00:02,  9.19it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:02<00:02,  9.21it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:02<00:02,  9.23it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:02<00:01,  9.23it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:02<00:01,  9.25it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01,  9.26it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01,  9.26it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01,  9.27it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01,  9.28it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:03<00:01,  9.30it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:03<00:01,  9.33it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:03<00:01,  9.33it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:03<00:00,  9.35it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:03<00:00,  9.35it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:03<00:00,  9.37it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:03<00:00,  9.37it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00,  9.38it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:03<00:00,  9.38it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:03<00:00,  9.36it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:04<00:00,  9.35it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:04<00:00,  9.35it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00,  9.35it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 200/? [01:12<00:00,  2.76it/s, train/loss=2.950]\nEpoch 0: |          | 201/? [01:20<00:00,  2.51it/s, train/loss=2.950]\nEpoch 0: |          | 201/? [01:20<00:00,  2.51it/s, train/loss=1.330]\nEpoch 0: |          | 202/? [01:20<00:00,  2.51it/s, train/loss=1.330]\nEpoch 0: |          | 202/? [01:20<00:00,  2.51it/s, train/loss=0.757]\nEpoch 0: |          | 203/? [01:20<00:00,  2.52it/s, train/loss=0.757]\nEpoch 0: |          | 203/? [01:20<00:00,  2.52it/s, train/loss=6.590]\nEpoch 0: |          | 204/? [01:20<00:00,  2.52it/s, train/loss=6.590]\nEpoch 0: |          | 204/? [01:20<00:00,  2.52it/s, train/loss=1.360]\nEpoch 0: |          | 205/? [01:20<00:00,  2.53it/s, train/loss=1.360]\nEpoch 0: |          | 205/? [01:20<00:00,  2.53it/s, train/loss=6.550]\nEpoch 0: |          | 206/? [01:21<00:00,  2.53it/s, train/loss=6.550]\nEpoch 0: |          | 206/? [01:21<00:00,  2.53it/s, train/loss=3.090]\nEpoch 0: |          | 207/? [01:21<00:00,  2.55it/s, train/loss=3.090]\nEpoch 0: |          | 207/? [01:21<00:00,  2.55it/s, train/loss=6.500]\nEpoch 0: |          | 208/? [01:21<00:00,  2.55it/s, train/loss=6.500]\nEpoch 0: |          | 208/? [01:21<00:00,  2.55it/s, train/loss=3.700]\nEpoch 0: |          | 209/? [01:21<00:00,  2.56it/s, train/loss=3.700]\nEpoch 0: |          | 209/? [01:21<00:00,  2.56it/s, train/loss=6.450]\nEpoch 0: |          | 210/? [01:22<00:00,  2.56it/s, train/loss=6.450]\nEpoch 0: |          | 210/? [01:22<00:00,  2.56it/s, train/loss=2.180]\nEpoch 0: |          | 211/? [01:23<00:00,  2.54it/s, train/loss=2.180]\nEpoch 0: |          | 211/? [01:23<00:00,  2.54it/s, train/loss=2.080]\nEpoch 0: |          | 212/? [01:23<00:00,  2.54it/s, train/loss=2.080]\nEpoch 0: |          | 212/? [01:23<00:00,  2.54it/s, train/loss=1.330]\nEpoch 0: |          | 213/? [01:23<00:00,  2.55it/s, train/loss=1.330]\nEpoch 0: |          | 213/? [01:23<00:00,  2.55it/s, train/loss=6.370]\nEpoch 0: |          | 214/? [01:23<00:00,  2.55it/s, train/loss=6.370]\nEpoch 0: |          | 214/? [01:23<00:00,  2.55it/s, train/loss=6.390]\nEpoch 0: |          | 215/? [01:23<00:00,  2.56it/s, train/loss=6.390]\nEpoch 0: |          | 215/? [01:23<00:00,  2.56it/s, train/loss=6.320]\nEpoch 0: |          | 216/? [01:24<00:00,  2.56it/s, train/loss=6.320]\nEpoch 0: |          | 216/? [01:24<00:00,  2.56it/s, train/loss=2.420]\nEpoch 0: |          | 217/? [01:24<00:00,  2.57it/s, train/loss=2.420]\nEpoch 0: |          | 217/? [01:24<00:00,  2.57it/s, train/loss=6.280]\nEpoch 0: |          | 218/? [01:24<00:00,  2.57it/s, train/loss=6.280]\nEpoch 0: |          | 218/? [01:24<00:00,  2.57it/s, train/loss=0.810]\nEpoch 0: |          | 219/? [01:24<00:00,  2.58it/s, train/loss=0.810]\nEpoch 0: |          | 219/? [01:24<00:00,  2.58it/s, train/loss=6.250]\nEpoch 0: |          | 220/? [01:25<00:00,  2.58it/s, train/loss=6.250]\nEpoch 0: |          | 220/? [01:25<00:00,  2.58it/s, train/loss=2.580]\nEpoch 0: |          | 221/? [01:26<00:00,  2.57it/s, train/loss=2.580]\nEpoch 0: |          | 221/? [01:26<00:00,  2.56it/s, train/loss=1.950]\nEpoch 0: |          | 222/? [01:26<00:00,  2.57it/s, train/loss=1.950]\nEpoch 0: |          | 222/? [01:26<00:00,  2.57it/s, train/loss=2.630]\nEpoch 0: |          | 223/? [01:26<00:00,  2.58it/s, train/loss=2.630]\nEpoch 0: |          | 223/? [01:26<00:00,  2.58it/s, train/loss=6.190]\nEpoch 0: |          | 224/? [01:26<00:00,  2.58it/s, train/loss=6.190]\nEpoch 0: |          | 224/? [01:26<00:00,  2.58it/s, train/loss=1.390]\nEpoch 0: |          | 225/? [01:27<00:00,  2.59it/s, train/loss=1.390]\nEpoch 0: |          | 225/? [01:27<00:00,  2.59it/s, train/loss=6.140]\nEpoch 0: |          | 226/? [01:27<00:00,  2.59it/s, train/loss=6.140]\nEpoch 0: |          | 226/? [01:27<00:00,  2.59it/s, train/loss=1.380]\nEpoch 0: |          | 227/? [01:27<00:00,  2.60it/s, train/loss=1.380]\nEpoch 0: |          | 227/? [01:27<00:00,  2.60it/s, train/loss=6.100]\nEpoch 0: |          | 228/? [01:27<00:00,  2.60it/s, train/loss=6.100]\nEpoch 0: |          | 228/? [01:27<00:00,  2.60it/s, train/loss=3.490]\nEpoch 0: |          | 229/? [01:27<00:00,  2.61it/s, train/loss=3.490]\nEpoch 0: |          | 229/? [01:27<00:00,  2.61it/s, train/loss=6.060]\nEpoch 0: |          | 230/? [01:28<00:00,  2.61it/s, train/loss=6.060]\nEpoch 0: |          | 230/? [01:28<00:00,  2.61it/s, train/loss=1.660]\nEpoch 0: |          | 231/? [01:29<00:00,  2.59it/s, train/loss=1.660]\nEpoch 0: |          | 231/? [01:29<00:00,  2.59it/s, train/loss=1.780]\nEpoch 0: |          | 232/? [01:29<00:00,  2.59it/s, train/loss=1.780]\nEpoch 0: |          | 232/? [01:29<00:00,  2.59it/s, train/loss=1.100]\nEpoch 0: |          | 233/? [01:29<00:00,  2.60it/s, train/loss=1.100]\nEpoch 0: |          | 233/? [01:29<00:00,  2.60it/s, train/loss=6.010]\nEpoch 0: |          | 234/? [01:30<00:00,  2.60it/s, train/loss=6.010]\nEpoch 0: |          | 234/? [01:30<00:00,  2.60it/s, train/loss=2.180]\nEpoch 0: |          | 235/? [01:30<00:00,  2.61it/s, train/loss=2.180]\nEpoch 0: |          | 235/? [01:30<00:00,  2.61it/s, train/loss=5.970]\nEpoch 0: |          | 236/? [01:30<00:00,  2.61it/s, train/loss=5.970]\nEpoch 0: |          | 236/? [01:30<00:00,  2.61it/s, train/loss=2.190]\nEpoch 0: |          | 237/? [01:30<00:00,  2.62it/s, train/loss=2.190]\nEpoch 0: |          | 237/? [01:30<00:00,  2.62it/s, train/loss=5.920]\nEpoch 0: |          | 238/? [01:30<00:00,  2.62it/s, train/loss=5.920]\nEpoch 0: |          | 238/? [01:30<00:00,  2.62it/s, train/loss=2.410]\nEpoch 0: |          | 239/? [01:30<00:00,  2.63it/s, train/loss=2.410]\nEpoch 0: |          | 239/? [01:30<00:00,  2.63it/s, train/loss=5.900]\nEpoch 0: |          | 240/? [01:31<00:00,  2.63it/s, train/loss=5.900]\nEpoch 0: |          | 240/? [01:31<00:00,  2.63it/s, train/loss=3.740]\nEpoch 0: |          | 241/? [01:32<00:00,  2.61it/s, train/loss=3.740]\nEpoch 0: |          | 241/? [01:32<00:00,  2.61it/s, train/loss=0.724]\nEpoch 0: |          | 242/? [01:32<00:00,  2.61it/s, train/loss=0.724]\nEpoch 0: |          | 242/? [01:32<00:00,  2.61it/s, train/loss=2.850]\nEpoch 0: |          | 243/? [01:32<00:00,  2.62it/s, train/loss=2.850]\nEpoch 0: |          | 243/? [01:32<00:00,  2.62it/s, train/loss=5.900]\nEpoch 0: |          | 244/? [01:33<00:00,  2.62it/s, train/loss=5.900]\nEpoch 0: |          | 244/? [01:33<00:00,  2.62it/s, train/loss=2.430]\nEpoch 0: |          | 245/? [01:33<00:00,  2.62it/s, train/loss=2.430]\nEpoch 0: |          | 245/? [01:33<00:00,  2.62it/s, train/loss=5.900]\nEpoch 0: |          | 246/? [01:33<00:00,  2.62it/s, train/loss=5.900]\nEpoch 0: |          | 246/? [01:33<00:00,  2.62it/s, train/loss=1.230]\nEpoch 0: |          | 247/? [01:34<00:00,  2.63it/s, train/loss=1.230]\nEpoch 0: |          | 247/? [01:34<00:00,  2.63it/s, train/loss=5.870]\nEpoch 0: |          | 248/? [01:34<00:00,  2.63it/s, train/loss=5.870]\nEpoch 0: |          | 248/? [01:34<00:00,  2.63it/s, train/loss=2.390]\nEpoch 0: |          | 249/? [01:34<00:00,  2.63it/s, train/loss=2.390]\nEpoch 0: |          | 249/? [01:34<00:00,  2.63it/s, train/loss=5.860]\nEpoch 0: |          | 250/? [01:34<00:00,  2.63it/s, train/loss=5.860]\nEpoch 0: |          | 250/? [01:34<00:00,  2.63it/s, train/loss=1.140]\nEpoch 0: |          | 251/? [01:35<00:00,  2.62it/s, train/loss=1.140]\nEpoch 0: |          | 251/? [01:35<00:00,  2.62it/s, train/loss=2.820]\nEpoch 0: |          | 252/? [01:36<00:00,  2.62it/s, train/loss=2.820]\nEpoch 0: |          | 252/? [01:36<00:00,  2.62it/s, train/loss=1.120]\nEpoch 0: |          | 253/? [01:36<00:00,  2.63it/s, train/loss=1.120]\nEpoch 0: |          | 253/? [01:36<00:00,  2.63it/s, train/loss=5.850]\nEpoch 0: |          | 254/? [01:36<00:00,  2.63it/s, train/loss=5.850]\nEpoch 0: |          | 254/? [01:36<00:00,  2.63it/s, train/loss=1.020]\nEpoch 0: |          | 255/? [01:36<00:00,  2.64it/s, train/loss=1.020]\nEpoch 0: |          | 255/? [01:36<00:00,  2.64it/s, train/loss=5.830]\nEpoch 0: |          | 256/? [01:37<00:00,  2.64it/s, train/loss=5.830]\nEpoch 0: |          | 256/? [01:37<00:00,  2.64it/s, train/loss=1.290]\nEpoch 0: |          | 257/? [01:37<00:00,  2.65it/s, train/loss=1.290]\nEpoch 0: |          | 257/? [01:37<00:00,  2.65it/s, train/loss=5.800]\nEpoch 0: |          | 258/? [01:37<00:00,  2.65it/s, train/loss=5.800]\nEpoch 0: |          | 258/? [01:37<00:00,  2.65it/s, train/loss=1.870]\nEpoch 0: |          | 259/? [01:37<00:00,  2.65it/s, train/loss=1.870]\nEpoch 0: |          | 259/? [01:37<00:00,  2.65it/s, train/loss=5.770]\nEpoch 0: |          | 260/? [01:37<00:00,  2.65it/s, train/loss=5.770]\nEpoch 0: |          | 260/? [01:37<00:00,  2.65it/s, train/loss=1.200]\nEpoch 0: |          | 261/? [01:38<00:00,  2.64it/s, train/loss=1.200]\nEpoch 0: |          | 261/? [01:38<00:00,  2.64it/s, train/loss=2.530]\nEpoch 0: |          | 262/? [01:39<00:00,  2.64it/s, train/loss=2.530]\nEpoch 0: |          | 262/? [01:39<00:00,  2.64it/s, train/loss=3.570]\nEpoch 0: |          | 263/? [01:39<00:00,  2.65it/s, train/loss=3.570]\nEpoch 0: |          | 263/? [01:39<00:00,  2.65it/s, train/loss=5.770]\nEpoch 0: |          | 264/? [01:39<00:00,  2.65it/s, train/loss=5.770]\nEpoch 0: |          | 264/? [01:39<00:00,  2.65it/s, train/loss=0.946]\nEpoch 0: |          | 265/? [01:39<00:00,  2.66it/s, train/loss=0.946]\nEpoch 0: |          | 265/? [01:39<00:00,  2.66it/s, train/loss=5.760]\nEpoch 0: |          | 266/? [01:40<00:00,  2.65it/s, train/loss=5.760]\nEpoch 0: |          | 266/? [01:40<00:00,  2.65it/s, train/loss=1.480]\nEpoch 0: |          | 267/? [01:40<00:00,  2.66it/s, train/loss=1.480]\nEpoch 0: |          | 267/? [01:40<00:00,  2.66it/s, train/loss=5.740]\nEpoch 0: |          | 268/? [01:40<00:00,  2.65it/s, train/loss=5.740]\nEpoch 0: |          | 268/? [01:40<00:00,  2.65it/s, train/loss=3.570]\nEpoch 0: |          | 269/? [01:41<00:00,  2.66it/s, train/loss=3.570]\nEpoch 0: |          | 269/? [01:41<00:00,  2.66it/s, train/loss=5.720]\nEpoch 0: |          | 270/? [01:41<00:00,  2.66it/s, train/loss=5.720]\nEpoch 0: |          | 270/? [01:41<00:00,  2.66it/s, train/loss=2.580]\nEpoch 0: |          | 271/? [01:42<00:00,  2.65it/s, train/loss=2.580]\nEpoch 0: |          | 271/? [01:42<00:00,  2.65it/s, train/loss=2.380]\nEpoch 0: |          | 272/? [01:42<00:00,  2.65it/s, train/loss=2.380]\nEpoch 0: |          | 272/? [01:42<00:00,  2.65it/s, train/loss=0.554]\nEpoch 0: |          | 273/? [01:42<00:00,  2.66it/s, train/loss=0.554]\nEpoch 0: |          | 273/? [01:42<00:00,  2.66it/s, train/loss=5.690]\nEpoch 0: |          | 274/? [01:43<00:00,  2.66it/s, train/loss=5.690]\nEpoch 0: |          | 274/? [01:43<00:00,  2.66it/s, train/loss=1.810]\nEpoch 0: |          | 275/? [01:43<00:00,  2.67it/s, train/loss=1.810]\nEpoch 0: |          | 275/? [01:43<00:00,  2.67it/s, train/loss=5.660]\nEpoch 0: |          | 276/? [01:43<00:00,  2.66it/s, train/loss=5.660]\nEpoch 0: |          | 276/? [01:43<00:00,  2.66it/s, train/loss=3.710]\nEpoch 0: |          | 277/? [01:43<00:00,  2.67it/s, train/loss=3.710]\nEpoch 0: |          | 277/? [01:43<00:00,  2.67it/s, train/loss=5.640]\nEpoch 0: |          | 278/? [01:44<00:00,  2.67it/s, train/loss=5.640]\nEpoch 0: |          | 278/? [01:44<00:00,  2.67it/s, train/loss=2.730]\nEpoch 0: |          | 279/? [01:44<00:00,  2.68it/s, train/loss=2.730]\nEpoch 0: |          | 279/? [01:44<00:00,  2.68it/s, train/loss=5.610]\nEpoch 0: |          | 280/? [01:44<00:00,  2.68it/s, train/loss=5.610]\nEpoch 0: |          | 280/? [01:44<00:00,  2.68it/s, train/loss=1.710]\nEpoch 0: |          | 281/? [01:45<00:00,  2.67it/s, train/loss=1.710]\nEpoch 0: |          | 281/? [01:45<00:00,  2.67it/s, train/loss=2.830]\nEpoch 0: |          | 282/? [01:45<00:00,  2.67it/s, train/loss=2.830]\nEpoch 0: |          | 282/? [01:45<00:00,  2.67it/s, train/loss=4.200]\nEpoch 0: |          | 283/? [01:45<00:00,  2.67it/s, train/loss=4.200]\nEpoch 0: |          | 283/? [01:45<00:00,  2.67it/s, train/loss=5.560]\nEpoch 0: |          | 284/? [01:46<00:00,  2.67it/s, train/loss=5.560]\nEpoch 0: |          | 284/? [01:46<00:00,  2.67it/s, train/loss=2.860]\nEpoch 0: |          | 285/? [01:46<00:00,  2.68it/s, train/loss=2.860]\nEpoch 0: |          | 285/? [01:46<00:00,  2.68it/s, train/loss=5.520]\nEpoch 0: |          | 286/? [01:46<00:00,  2.68it/s, train/loss=5.520]\nEpoch 0: |          | 286/? [01:46<00:00,  2.68it/s, train/loss=3.260]\nEpoch 0: |          | 287/? [01:46<00:00,  2.69it/s, train/loss=3.260]\nEpoch 0: |          | 287/? [01:46<00:00,  2.69it/s, train/loss=5.480]\nEpoch 0: |          | 288/? [01:47<00:00,  2.69it/s, train/loss=5.480]\nEpoch 0: |          | 288/? [01:47<00:00,  2.69it/s, train/loss=2.080]\nEpoch 0: |          | 289/? [01:47<00:00,  2.70it/s, train/loss=2.080]\nEpoch 0: |          | 289/? [01:47<00:00,  2.70it/s, train/loss=5.440]\nEpoch 0: |          | 290/? [01:47<00:00,  2.70it/s, train/loss=5.440]\nEpoch 0: |          | 290/? [01:47<00:00,  2.70it/s, train/loss=2.980]\nEpoch 0: |          | 291/? [01:48<00:00,  2.68it/s, train/loss=2.980]\nEpoch 0: |          | 291/? [01:48<00:00,  2.68it/s, train/loss=1.650]\nEpoch 0: |          | 292/? [01:48<00:00,  2.69it/s, train/loss=1.650]\nEpoch 0: |          | 292/? [01:48<00:00,  2.68it/s, train/loss=1.700]\nEpoch 0: |          | 293/? [01:48<00:00,  2.69it/s, train/loss=1.700]\nEpoch 0: |          | 293/? [01:48<00:00,  2.69it/s, train/loss=5.400]\nEpoch 0: |          | 294/? [01:49<00:00,  2.69it/s, train/loss=5.400]\nEpoch 0: |          | 294/? [01:49<00:00,  2.69it/s, train/loss=3.030]\nEpoch 0: |          | 295/? [01:49<00:00,  2.70it/s, train/loss=3.030]\nEpoch 0: |          | 295/? [01:49<00:00,  2.70it/s, train/loss=5.380]\nEpoch 0: |          | 296/? [01:49<00:00,  2.70it/s, train/loss=5.380]\nEpoch 0: |          | 296/? [01:49<00:00,  2.70it/s, train/loss=2.820]\nEpoch 0: |          | 297/? [01:49<00:00,  2.71it/s, train/loss=2.820]\nEpoch 0: |          | 297/? [01:49<00:00,  2.71it/s, train/loss=5.350]\nEpoch 0: |          | 298/? [01:50<00:00,  2.71it/s, train/loss=5.350]\nEpoch 0: |          | 298/? [01:50<00:00,  2.71it/s, train/loss=1.420]\nEpoch 0: |          | 299/? [01:50<00:00,  2.71it/s, train/loss=1.420]\nEpoch 0: |          | 299/? [01:50<00:00,  2.71it/s, train/loss=5.320]\nEpoch 0: |          | 300/? [01:50<00:00,  2.71it/s, train/loss=5.320]\nEpoch 0: |          | 300/? [01:50<00:00,  2.71it/s, train/loss=1.020]\nEpoch 0: |          | 301/? [01:51<00:00,  2.70it/s, train/loss=1.020]\nEpoch 0: |          | 301/? [01:51<00:00,  2.70it/s, train/loss=0.883]\nEpoch 0: |          | 302/? [01:51<00:00,  2.70it/s, train/loss=0.883]\nEpoch 0: |          | 302/? [01:51<00:00,  2.70it/s, train/loss=3.050]\nEpoch 0: |          | 303/? [01:51<00:00,  2.71it/s, train/loss=3.050]\nEpoch 0: |          | 303/? [01:51<00:00,  2.71it/s, train/loss=5.280]\nEpoch 0: |          | 304/? [01:52<00:00,  2.71it/s, train/loss=5.280]\nEpoch 0: |          | 304/? [01:52<00:00,  2.71it/s, train/loss=2.640]\nEpoch 0: |          | 305/? [01:52<00:00,  2.72it/s, train/loss=2.640]\nEpoch 0: |          | 305/? [01:52<00:00,  2.72it/s, train/loss=5.260]\nEpoch 0: |          | 306/? [01:52<00:00,  2.71it/s, train/loss=5.260]\nEpoch 0: |          | 306/? [01:52<00:00,  2.71it/s, train/loss=1.430]\nEpoch 0: |          | 307/? [01:52<00:00,  2.72it/s, train/loss=1.430]\nEpoch 0: |          | 307/? [01:52<00:00,  2.72it/s, train/loss=5.230]\nEpoch 0: |          | 308/? [01:53<00:00,  2.72it/s, train/loss=5.230]\nEpoch 0: |          | 308/? [01:53<00:00,  2.72it/s, train/loss=2.380]\nEpoch 0: |          | 309/? [01:53<00:00,  2.73it/s, train/loss=2.380]\nEpoch 0: |          | 309/? [01:53<00:00,  2.73it/s, train/loss=5.200]\nEpoch 0: |          | 310/? [01:53<00:00,  2.73it/s, train/loss=5.200]\nEpoch 0: |          | 310/? [01:53<00:00,  2.73it/s, train/loss=1.700]\nEpoch 0: |          | 311/? [01:54<00:00,  2.72it/s, train/loss=1.700]\nEpoch 0: |          | 311/? [01:54<00:00,  2.71it/s, train/loss=2.040]\nEpoch 0: |          | 312/? [01:54<00:00,  2.72it/s, train/loss=2.040]\nEpoch 0: |          | 312/? [01:54<00:00,  2.71it/s, train/loss=0.999]\nEpoch 0: |          | 313/? [01:54<00:00,  2.72it/s, train/loss=0.999]\nEpoch 0: |          | 313/? [01:54<00:00,  2.72it/s, train/loss=5.190]\nEpoch 0: |          | 314/? [01:55<00:00,  2.72it/s, train/loss=5.190]\nEpoch 0: |          | 314/? [01:55<00:00,  2.72it/s, train/loss=1.130]\nEpoch 0: |          | 315/? [01:55<00:00,  2.73it/s, train/loss=1.130]\nEpoch 0: |          | 315/? [01:55<00:00,  2.73it/s, train/loss=5.190]\nEpoch 0: |          | 316/? [01:55<00:00,  2.73it/s, train/loss=5.190]\nEpoch 0: |          | 316/? [01:55<00:00,  2.73it/s, train/loss=3.310]\nEpoch 0: |          | 317/? [01:55<00:00,  2.74it/s, train/loss=3.310]\nEpoch 0: |          | 317/? [01:55<00:00,  2.74it/s, train/loss=5.170]\nEpoch 0: |          | 318/? [01:56<00:00,  2.73it/s, train/loss=5.170]\nEpoch 0: |          | 318/? [01:56<00:00,  2.73it/s, train/loss=1.810]\nEpoch 0: |          | 319/? [01:56<00:00,  2.74it/s, train/loss=1.810]\nEpoch 0: |          | 319/? [01:56<00:00,  2.74it/s, train/loss=5.160]\nEpoch 0: |          | 320/? [01:56<00:00,  2.74it/s, train/loss=5.160]\nEpoch 0: |          | 320/? [01:56<00:00,  2.74it/s, train/loss=2.270]\nEpoch 0: |          | 321/? [01:57<00:00,  2.73it/s, train/loss=2.270]\nEpoch 0: |          | 321/? [01:57<00:00,  2.73it/s, train/loss=1.920]\nEpoch 0: |          | 322/? [01:57<00:00,  2.73it/s, train/loss=1.920]\nEpoch 0: |          | 322/? [01:58<00:00,  2.73it/s, train/loss=1.600]\nEpoch 0: |          | 323/? [01:58<00:00,  2.73it/s, train/loss=1.600]\nEpoch 0: |          | 323/? [01:58<00:00,  2.73it/s, train/loss=5.150]\nEpoch 0: |          | 324/? [01:58<00:00,  2.73it/s, train/loss=5.150]\nEpoch 0: |          | 324/? [01:58<00:00,  2.73it/s, train/loss=3.730]\nEpoch 0: |          | 325/? [01:58<00:00,  2.74it/s, train/loss=3.730]\nEpoch 0: |          | 325/? [01:58<00:00,  2.74it/s, train/loss=5.150]\nEpoch 0: |          | 326/? [01:58<00:00,  2.74it/s, train/loss=5.150]\nEpoch 0: |          | 326/? [01:58<00:00,  2.74it/s, train/loss=2.220]\nEpoch 0: |          | 327/? [01:59<00:00,  2.75it/s, train/loss=2.220]\nEpoch 0: |          | 327/? [01:59<00:00,  2.75it/s, train/loss=5.130]\nEpoch 0: |          | 328/? [01:59<00:00,  2.75it/s, train/loss=5.130]\nEpoch 0: |          | 328/? [01:59<00:00,  2.75it/s, train/loss=1.950]\nEpoch 0: |          | 329/? [01:59<00:00,  2.75it/s, train/loss=1.950]\nEpoch 0: |          | 329/? [01:59<00:00,  2.75it/s, train/loss=5.100]\nEpoch 0: |          | 330/? [01:59<00:00,  2.75it/s, train/loss=5.100]\nEpoch 0: |          | 330/? [01:59<00:00,  2.75it/s, train/loss=5.410]\nEpoch 0: |          | 331/? [02:00<00:00,  2.74it/s, train/loss=5.410]\nEpoch 0: |          | 331/? [02:00<00:00,  2.74it/s, train/loss=2.210]\nEpoch 0: |          | 332/? [02:01<00:00,  2.74it/s, train/loss=2.210]\nEpoch 0: |          | 332/? [02:01<00:00,  2.74it/s, train/loss=1.130]\nEpoch 0: |          | 333/? [02:01<00:00,  2.75it/s, train/loss=1.130]\nEpoch 0: |          | 333/? [02:01<00:00,  2.75it/s, train/loss=5.080]\nEpoch 0: |          | 334/? [02:01<00:00,  2.75it/s, train/loss=5.080]\nEpoch 0: |          | 334/? [02:01<00:00,  2.75it/s, train/loss=2.390]\nEpoch 0: |          | 335/? [02:01<00:00,  2.75it/s, train/loss=2.390]\nEpoch 0: |          | 335/? [02:01<00:00,  2.75it/s, train/loss=5.060]\nEpoch 0: |          | 336/? [02:02<00:00,  2.75it/s, train/loss=5.060]\nEpoch 0: |          | 336/? [02:02<00:00,  2.75it/s, train/loss=3.190]\nEpoch 0: |          | 337/? [02:02<00:00,  2.76it/s, train/loss=3.190]\nEpoch 0: |          | 337/? [02:02<00:00,  2.76it/s, train/loss=5.040]\nEpoch 0: |          | 338/? [02:02<00:00,  2.76it/s, train/loss=5.040]\nEpoch 0: |          | 338/? [02:02<00:00,  2.76it/s, train/loss=0.746]\nEpoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=0.746]\nEpoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=5.020]\nEpoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=5.020]\nEpoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=1.340]\nEpoch 0: |          | 341/? [02:03<00:00,  2.75it/s, train/loss=1.340]\nEpoch 0: |          | 341/? [02:03<00:00,  2.75it/s, train/loss=1.570]\nEpoch 0: |          | 342/? [02:04<00:00,  2.75it/s, train/loss=1.570]\nEpoch 0: |          | 342/? [02:04<00:00,  2.75it/s, train/loss=2.380]\nEpoch 0: |          | 343/? [02:04<00:00,  2.76it/s, train/loss=2.380]\nEpoch 0: |          | 343/? [02:04<00:00,  2.76it/s, train/loss=5.000]\nEpoch 0: |          | 344/? [02:04<00:00,  2.76it/s, train/loss=5.000]\nEpoch 0: |          | 344/? [02:04<00:00,  2.76it/s, train/loss=4.760]\nEpoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=4.760]\nEpoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=4.980]\nEpoch 0: |          | 346/? [02:05<00:00,  2.77it/s, train/loss=4.980]\nEpoch 0: |          | 346/? [02:05<00:00,  2.77it/s, train/loss=3.570]\nEpoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=3.570]\nEpoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=4.940]\nEpoch 0: |          | 348/? [02:05<00:00,  2.77it/s, train/loss=4.940]\nEpoch 0: |          | 348/? [02:05<00:00,  2.77it/s, train/loss=2.680]\nEpoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=2.680]\nEpoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=4.940]\nEpoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=4.940]\nEpoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=1.490]\nEpoch 0: |          | 351/? [02:06<00:00,  2.77it/s, train/loss=1.490]\nEpoch 0: |          | 351/? [02:06<00:00,  2.76it/s, train/loss=2.270]\nEpoch 0: |          | 352/? [02:07<00:00,  2.77it/s, train/loss=2.270]\nEpoch 0: |          | 352/? [02:07<00:00,  2.77it/s, train/loss=1.580]\nEpoch 0: |          | 353/? [02:07<00:00,  2.77it/s, train/loss=1.580]\nEpoch 0: |          | 353/? [02:07<00:00,  2.77it/s, train/loss=4.990]\nEpoch 0: |          | 354/? [02:07<00:00,  2.77it/s, train/loss=4.990]\nEpoch 0: |          | 354/? [02:07<00:00,  2.77it/s, train/loss=0.693]\nEpoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=0.693]\nEpoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=4.980]\nEpoch 0: |          | 356/? [02:08<00:00,  2.77it/s, train/loss=4.980]\nEpoch 0: |          | 356/? [02:08<00:00,  2.77it/s, train/loss=2.220]\nEpoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=2.220]\nEpoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=4.950]\nEpoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=4.950]\nEpoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=0.770]\nEpoch 0: |          | 359/? [02:08<00:00,  2.79it/s, train/loss=0.770]\nEpoch 0: |          | 359/? [02:08<00:00,  2.79it/s, train/loss=4.930]\nEpoch 0: |          | 360/? [02:09<00:00,  2.79it/s, train/loss=4.930]\nEpoch 0: |          | 360/? [02:09<00:00,  2.79it/s, train/loss=3.010]\nEpoch 0: |          | 361/? [02:10<00:00,  2.77it/s, train/loss=3.010]\nEpoch 0: |          | 361/? [02:10<00:00,  2.77it/s, train/loss=0.704]\nEpoch 0: |          | 362/? [02:10<00:00,  2.78it/s, train/loss=0.704]\nEpoch 0: |          | 362/? [02:10<00:00,  2.77it/s, train/loss=2.000]\nEpoch 0: |          | 363/? [02:10<00:00,  2.78it/s, train/loss=2.000]\nEpoch 0: |          | 363/? [02:10<00:00,  2.78it/s, train/loss=4.930]\nEpoch 0: |          | 364/? [02:10<00:00,  2.78it/s, train/loss=4.930]\nEpoch 0: |          | 364/? [02:10<00:00,  2.78it/s, train/loss=2.770]\nEpoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=2.770]\nEpoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=4.920]\nEpoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=4.920]\nEpoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=1.270]\nEpoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=1.270]\nEpoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=4.900]\nEpoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=4.900]\nEpoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=2.370]\nEpoch 0: |          | 369/? [02:11<00:00,  2.80it/s, train/loss=2.370]\nEpoch 0: |          | 369/? [02:11<00:00,  2.80it/s, train/loss=4.890]\nEpoch 0: |          | 370/? [02:12<00:00,  2.80it/s, train/loss=4.890]\nEpoch 0: |          | 370/? [02:12<00:00,  2.80it/s, train/loss=1.150]\nEpoch 0: |          | 371/? [02:13<00:00,  2.79it/s, train/loss=1.150]\nEpoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=2.940]\nEpoch 0: |          | 372/? [02:13<00:00,  2.79it/s, train/loss=2.940]\nEpoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=1.090]\nEpoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=1.090]\nEpoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=4.880]\nEpoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=4.880]\nEpoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=3.940]\nEpoch 0: |          | 375/? [02:14<00:00,  2.80it/s, train/loss=3.940]\nEpoch 0: |          | 375/? [02:14<00:00,  2.80it/s, train/loss=4.870]\nEpoch 0: |          | 376/? [02:14<00:00,  2.80it/s, train/loss=4.870]\nEpoch 0: |          | 376/? [02:14<00:00,  2.80it/s, train/loss=2.950]\nEpoch 0: |          | 377/? [02:14<00:00,  2.80it/s, train/loss=2.950]\nEpoch 0: |          | 377/? [02:14<00:00,  2.80it/s, train/loss=4.840]\nEpoch 0: |          | 378/? [02:14<00:00,  2.80it/s, train/loss=4.840]\nEpoch 0: |          | 378/? [02:14<00:00,  2.80it/s, train/loss=2.900]\nEpoch 0: |          | 379/? [02:14<00:00,  2.81it/s, train/loss=2.900]\nEpoch 0: |          | 379/? [02:14<00:00,  2.81it/s, train/loss=4.820]\nEpoch 0: |          | 380/? [02:15<00:00,  2.81it/s, train/loss=4.820]\nEpoch 0: |          | 380/? [02:15<00:00,  2.81it/s, train/loss=2.240]\nEpoch 0: |          | 381/? [02:16<00:00,  2.80it/s, train/loss=2.240]\nEpoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=0.726]\nEpoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=0.726]\nEpoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=1.090]\nEpoch 0: |          | 383/? [02:16<00:00,  2.80it/s, train/loss=1.090]\nEpoch 0: |          | 383/? [02:16<00:00,  2.80it/s, train/loss=4.800]\nEpoch 0: |          | 384/? [02:17<00:00,  2.80it/s, train/loss=4.800]\nEpoch 0: |          | 384/? [02:17<00:00,  2.80it/s, train/loss=3.060]\nEpoch 0: |          | 385/? [02:17<00:00,  2.81it/s, train/loss=3.060]\nEpoch 0: |          | 385/? [02:17<00:00,  2.81it/s, train/loss=4.780]\nEpoch 0: |          | 386/? [02:17<00:00,  2.80it/s, train/loss=4.780]\nEpoch 0: |          | 386/? [02:17<00:00,  2.80it/s, train/loss=2.630]\nEpoch 0: |          | 387/? [02:17<00:00,  2.81it/s, train/loss=2.630]\nEpoch 0: |          | 387/? [02:17<00:00,  2.81it/s, train/loss=4.750]\nEpoch 0: |          | 388/? [02:18<00:00,  2.81it/s, train/loss=4.750]\nEpoch 0: |          | 388/? [02:18<00:00,  2.81it/s, train/loss=0.970]\nEpoch 0: |          | 389/? [02:18<00:00,  2.82it/s, train/loss=0.970]\nEpoch 0: |          | 389/? [02:18<00:00,  2.82it/s, train/loss=4.730]\nEpoch 0: |          | 390/? [02:18<00:00,  2.81it/s, train/loss=4.730]\nEpoch 0: |          | 390/? [02:18<00:00,  2.81it/s, train/loss=3.590]\nEpoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=3.590]\nEpoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=1.050]\nEpoch 0: |          | 392/? [02:19<00:00,  2.80it/s, train/loss=1.050]\nEpoch 0: |          | 392/? [02:19<00:00,  2.80it/s, train/loss=0.961]\nEpoch 0: |          | 393/? [02:19<00:00,  2.81it/s, train/loss=0.961]\nEpoch 0: |          | 393/? [02:19<00:00,  2.81it/s, train/loss=4.700]\nEpoch 0: |          | 394/? [02:20<00:00,  2.81it/s, train/loss=4.700]\nEpoch 0: |          | 394/? [02:20<00:00,  2.81it/s, train/loss=2.750]\nEpoch 0: |          | 395/? [02:20<00:00,  2.81it/s, train/loss=2.750]\nEpoch 0: |          | 395/? [02:20<00:00,  2.81it/s, train/loss=4.690]\nEpoch 0: |          | 396/? [02:20<00:00,  2.81it/s, train/loss=4.690]\nEpoch 0: |          | 396/? [02:20<00:00,  2.81it/s, train/loss=4.030]\nEpoch 0: |          | 397/? [02:20<00:00,  2.82it/s, train/loss=4.030]\nEpoch 0: |          | 397/? [02:20<00:00,  2.82it/s, train/loss=4.670]\nEpoch 0: |          | 398/? [02:21<00:00,  2.82it/s, train/loss=4.670]\nEpoch 0: |          | 398/? [02:21<00:00,  2.82it/s, train/loss=2.210]\nEpoch 0: |          | 399/? [02:21<00:00,  2.82it/s, train/loss=2.210]\nEpoch 0: |          | 399/? [02:21<00:00,  2.82it/s, train/loss=4.660]\nEpoch 0: |          | 400/? [02:21<00:00,  2.82it/s, train/loss=4.660]\nEpoch 0: |          | 400/? [02:21<00:00,  2.82it/s, train/loss=2.450]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:04,  8.57it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:04,  8.84it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:04,  8.95it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:04,  8.76it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:03,  8.82it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:03,  8.82it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:03,  8.89it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:03,  8.95it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:00<00:03,  9.01it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:01<00:03,  9.01it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:01<00:03,  9.03it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:03,  9.07it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:02,  9.10it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02,  9.10it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02,  9.09it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02,  9.06it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:02,  9.07it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:01<00:02,  9.07it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:02<00:02,  9.08it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:02<00:02,  9.06it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:02<00:02,  9.05it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:02<00:01,  9.06it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:02<00:01,  9.07it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01,  9.08it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01,  9.10it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01,  9.10it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01,  9.12it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:03<00:01,  9.13it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:03<00:01,  8.97it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:03<00:01,  8.92it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:03<00:01,  8.93it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:03<00:00,  8.95it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:03<00:00,  8.97it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:03<00:00,  8.97it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00,  8.98it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:04<00:00,  8.96it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:04<00:00,  8.96it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:04<00:00,  8.95it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:04<00:00,  8.95it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00,  8.95it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 400/? [02:30<00:00,  2.65it/s, train/loss=2.450]\nEpoch 0: |          | 401/? [02:50<00:00,  2.35it/s, train/loss=2.450]\nEpoch 0: |          | 401/? [02:51<00:00,  2.34it/s, train/loss=0.663]\nEpoch 0: |          | 402/? [02:51<00:00,  2.35it/s, train/loss=0.663]\nEpoch 0: |          | 402/? [02:51<00:00,  2.35it/s, train/loss=1.990]\nEpoch 0: |          | 403/? [02:51<00:00,  2.35it/s, train/loss=1.990]\nEpoch 0: |          | 403/? [02:51<00:00,  2.35it/s, train/loss=4.650]\nEpoch 0: |          | 404/? [02:51<00:00,  2.35it/s, train/loss=4.650]\nEpoch 0: |          | 404/? [02:51<00:00,  2.35it/s, train/loss=1.070]\nEpoch 0: |          | 405/? [02:51<00:00,  2.36it/s, train/loss=1.070]\nEpoch 0: |          | 405/? [02:51<00:00,  2.36it/s, train/loss=4.640]\nEpoch 0: |          | 406/? [02:52<00:00,  2.36it/s, train/loss=4.640]\nEpoch 0: |          | 406/? [02:52<00:00,  2.36it/s, train/loss=2.970]\nEpoch 0: |          | 407/? [02:52<00:00,  2.36it/s, train/loss=2.970]\nEpoch 0: |          | 407/? [02:52<00:00,  2.36it/s, train/loss=4.610]\nEpoch 0: |          | 408/? [02:52<00:00,  2.36it/s, train/loss=4.610]\nEpoch 0: |          | 408/? [02:52<00:00,  2.36it/s, train/loss=2.380]\nEpoch 0: |          | 409/? [02:52<00:00,  2.37it/s, train/loss=2.380]\nEpoch 0: |          | 409/? [02:52<00:00,  2.37it/s, train/loss=4.590]\nEpoch 0: |          | 410/? [02:53<00:00,  2.36it/s, train/loss=4.590]\nEpoch 0: |          | 410/? [02:53<00:00,  2.36it/s, train/loss=1.430]\nEpoch 0: |          | 411/? [02:54<00:00,  2.36it/s, train/loss=1.430]\nEpoch 0: |          | 411/? [02:54<00:00,  2.35it/s, train/loss=1.160]\nEpoch 0: |          | 412/? [02:54<00:00,  2.36it/s, train/loss=1.160]\nEpoch 0: |          | 412/? [02:54<00:00,  2.36it/s, train/loss=1.590]\nEpoch 0: |          | 413/? [02:54<00:00,  2.36it/s, train/loss=1.590]\nEpoch 0: |          | 413/? [02:54<00:00,  2.36it/s, train/loss=4.570]\nEpoch 0: |          | 414/? [02:55<00:00,  2.36it/s, train/loss=4.570]\nEpoch 0: |          | 414/? [02:55<00:00,  2.36it/s, train/loss=1.560]\nEpoch 0: |          | 415/? [02:55<00:00,  2.37it/s, train/loss=1.560]\nEpoch 0: |          | 415/? [02:55<00:00,  2.37it/s, train/loss=4.550]\nEpoch 0: |          | 416/? [02:55<00:00,  2.37it/s, train/loss=4.550]\nEpoch 0: |          | 416/? [02:55<00:00,  2.37it/s, train/loss=3.270]\nEpoch 0: |          | 417/? [02:55<00:00,  2.37it/s, train/loss=3.270]\nEpoch 0: |          | 417/? [02:55<00:00,  2.37it/s, train/loss=4.530]\nEpoch 0: |          | 418/? [02:56<00:00,  2.37it/s, train/loss=4.530]\nEpoch 0: |          | 418/? [02:56<00:00,  2.37it/s, train/loss=3.370]\nEpoch 0: |          | 419/? [02:56<00:00,  2.38it/s, train/loss=3.370]\nEpoch 0: |          | 419/? [02:56<00:00,  2.38it/s, train/loss=4.520]\nEpoch 0: |          | 420/? [02:56<00:00,  2.38it/s, train/loss=4.520]\nEpoch 0: |          | 420/? [02:56<00:00,  2.38it/s, train/loss=2.730]\nEpoch 0: |          | 421/? [02:57<00:00,  2.37it/s, train/loss=2.730]\nEpoch 0: |          | 421/? [02:57<00:00,  2.37it/s, train/loss=0.665]\nEpoch 0: |          | 422/? [02:58<00:00,  2.37it/s, train/loss=0.665]\nEpoch 0: |          | 422/? [02:58<00:00,  2.37it/s, train/loss=2.290]\nEpoch 0: |          | 423/? [02:58<00:00,  2.37it/s, train/loss=2.290]\nEpoch 0: |          | 423/? [02:58<00:00,  2.37it/s, train/loss=4.540]\nEpoch 0: |          | 424/? [02:58<00:00,  2.38it/s, train/loss=4.540]\nEpoch 0: |          | 424/? [02:58<00:00,  2.38it/s, train/loss=2.300]\nEpoch 0: |          | 425/? [02:58<00:00,  2.38it/s, train/loss=2.300]\nEpoch 0: |          | 425/? [02:58<00:00,  2.38it/s, train/loss=4.540]\nEpoch 0: |          | 426/? [02:58<00:00,  2.38it/s, train/loss=4.540]\nEpoch 0: |          | 426/? [02:58<00:00,  2.38it/s, train/loss=1.450]\nEpoch 0: |          | 427/? [02:59<00:00,  2.39it/s, train/loss=1.450]\nEpoch 0: |          | 427/? [02:59<00:00,  2.38it/s, train/loss=4.500]\nEpoch 0: |          | 428/? [02:59<00:00,  2.39it/s, train/loss=4.500]\nEpoch 0: |          | 428/? [02:59<00:00,  2.39it/s, train/loss=0.830]\nEpoch 0: |          | 429/? [02:59<00:00,  2.39it/s, train/loss=0.830]\nEpoch 0: |          | 429/? [02:59<00:00,  2.39it/s, train/loss=4.490]\nEpoch 0: |          | 430/? [02:59<00:00,  2.39it/s, train/loss=4.490]\nEpoch 0: |          | 430/? [02:59<00:00,  2.39it/s, train/loss=0.742]\nEpoch 0: |          | 431/? [03:00<00:00,  2.38it/s, train/loss=0.742]\nEpoch 0: |          | 431/? [03:00<00:00,  2.38it/s, train/loss=1.350]\nEpoch 0: |          | 432/? [03:01<00:00,  2.38it/s, train/loss=1.350]\nEpoch 0: |          | 432/? [03:01<00:00,  2.38it/s, train/loss=2.160]\nEpoch 0: |          | 433/? [03:01<00:00,  2.39it/s, train/loss=2.160]\nEpoch 0: |          | 433/? [03:01<00:00,  2.39it/s, train/loss=4.540]\nEpoch 0: |          | 434/? [03:01<00:00,  2.39it/s, train/loss=4.540]\nEpoch 0: |          | 434/? [03:01<00:00,  2.39it/s, train/loss=2.430]\nEpoch 0: |          | 435/? [03:01<00:00,  2.39it/s, train/loss=2.430]\nEpoch 0: |          | 435/? [03:01<00:00,  2.39it/s, train/loss=4.530]\nEpoch 0: |          | 436/? [03:02<00:00,  2.39it/s, train/loss=4.530]\nEpoch 0: |          | 436/? [03:02<00:00,  2.39it/s, train/loss=3.150]\nEpoch 0: |          | 437/? [03:02<00:00,  2.40it/s, train/loss=3.150]\nEpoch 0: |          | 437/? [03:02<00:00,  2.40it/s, train/loss=4.510]\nEpoch 0: |          | 438/? [03:02<00:00,  2.40it/s, train/loss=4.510]\nEpoch 0: |          | 438/? [03:02<00:00,  2.40it/s, train/loss=2.300]\nEpoch 0: |          | 439/? [03:02<00:00,  2.40it/s, train/loss=2.300]\nEpoch 0: |          | 439/? [03:02<00:00,  2.40it/s, train/loss=4.510]\nEpoch 0: |          | 440/? [03:03<00:00,  2.40it/s, train/loss=4.510]\nEpoch 0: |          | 440/? [03:03<00:00,  2.40it/s, train/loss=3.060]\nEpoch 0: |          | 441/? [03:03<00:00,  2.40it/s, train/loss=3.060]\nEpoch 0: |          | 441/? [03:03<00:00,  2.40it/s, train/loss=1.380]\nEpoch 0: |          | 442/? [03:04<00:00,  2.40it/s, train/loss=1.380]\nEpoch 0: |          | 442/? [03:04<00:00,  2.40it/s, train/loss=2.210]\nEpoch 0: |          | 443/? [03:04<00:00,  2.40it/s, train/loss=2.210]\nEpoch 0: |          | 443/? [03:04<00:00,  2.40it/s, train/loss=4.530]\nEpoch 0: |          | 444/? [03:04<00:00,  2.40it/s, train/loss=4.530]\nEpoch 0: |          | 444/? [03:04<00:00,  2.40it/s, train/loss=1.410]\nEpoch 0: |          | 445/? [03:04<00:00,  2.41it/s, train/loss=1.410]\nEpoch 0: |          | 445/? [03:04<00:00,  2.41it/s, train/loss=4.520]\nEpoch 0: |          | 446/? [03:05<00:00,  2.41it/s, train/loss=4.520]\nEpoch 0: |          | 446/? [03:05<00:00,  2.41it/s, train/loss=0.731]\nEpoch 0: |          | 447/? [03:05<00:00,  2.41it/s, train/loss=0.731]\nEpoch 0: |          | 447/? [03:05<00:00,  2.41it/s, train/loss=4.500]\nEpoch 0: |          | 448/? [03:05<00:00,  2.41it/s, train/loss=4.500]\nEpoch 0: |          | 448/? [03:05<00:00,  2.41it/s, train/loss=1.490]\nEpoch 0: |          | 449/? [03:05<00:00,  2.42it/s, train/loss=1.490]\nEpoch 0: |          | 449/? [03:05<00:00,  2.42it/s, train/loss=4.470]\nEpoch 0: |          | 450/? [03:06<00:00,  2.42it/s, train/loss=4.470]\nEpoch 0: |          | 450/? [03:06<00:00,  2.42it/s, train/loss=3.620]\nEpoch 0: |          | 451/? [03:07<00:00,  2.41it/s, train/loss=3.620]\nEpoch 0: |          | 451/? [03:07<00:00,  2.41it/s, train/loss=3.350]\nEpoch 0: |          | 452/? [03:07<00:00,  2.41it/s, train/loss=3.350]\nEpoch 0: |          | 452/? [03:07<00:00,  2.41it/s, train/loss=1.390]\nEpoch 0: |          | 453/? [03:07<00:00,  2.42it/s, train/loss=1.390]\nEpoch 0: |          | 453/? [03:07<00:00,  2.42it/s, train/loss=4.420]\nEpoch 0: |          | 454/? [03:07<00:00,  2.42it/s, train/loss=4.420]\nEpoch 0: |          | 454/? [03:07<00:00,  2.42it/s, train/loss=2.750]\nEpoch 0: |          | 455/? [03:07<00:00,  2.42it/s, train/loss=2.750]\nEpoch 0: |          | 455/? [03:07<00:00,  2.42it/s, train/loss=4.400]\nEpoch 0: |          | 456/? [03:08<00:00,  2.42it/s, train/loss=4.400]\nEpoch 0: |          | 456/? [03:08<00:00,  2.42it/s, train/loss=1.430]\nEpoch 0: |          | 457/? [03:08<00:00,  2.43it/s, train/loss=1.430]\nEpoch 0: |          | 457/? [03:08<00:00,  2.43it/s, train/loss=4.380]\nEpoch 0: |          | 458/? [03:08<00:00,  2.43it/s, train/loss=4.380]\nEpoch 0: |          | 458/? [03:08<00:00,  2.43it/s, train/loss=1.900]\nEpoch 0: |          | 459/? [03:08<00:00,  2.43it/s, train/loss=1.900]\nEpoch 0: |          | 459/? [03:08<00:00,  2.43it/s, train/loss=4.350]\nEpoch 0: |          | 460/? [03:09<00:00,  2.43it/s, train/loss=4.350]\nEpoch 0: |          | 460/? [03:09<00:00,  2.43it/s, train/loss=3.030]\nEpoch 0: |          | 461/? [03:10<00:00,  2.42it/s, train/loss=3.030]\nEpoch 0: |          | 461/? [03:10<00:00,  2.42it/s, train/loss=2.120]\nEpoch 0: |          | 462/? [03:10<00:00,  2.43it/s, train/loss=2.120]\nEpoch 0: |          | 462/? [03:10<00:00,  2.42it/s, train/loss=1.960]\nEpoch 0: |          | 463/? [03:10<00:00,  2.43it/s, train/loss=1.960]\nEpoch 0: |          | 463/? [03:10<00:00,  2.43it/s, train/loss=4.340]\nEpoch 0: |          | 464/? [03:10<00:00,  2.43it/s, train/loss=4.340]\nEpoch 0: |          | 464/? [03:10<00:00,  2.43it/s, train/loss=1.650]\nEpoch 0: |          | 465/? [03:11<00:00,  2.43it/s, train/loss=1.650]\nEpoch 0: |          | 465/? [03:11<00:00,  2.43it/s, train/loss=4.340]\nEpoch 0: |          | 466/? [03:11<00:00,  2.43it/s, train/loss=4.340]\nEpoch 0: |          | 466/? [03:11<00:00,  2.43it/s, train/loss=0.967]\nEpoch 0: |          | 467/? [03:11<00:00,  2.44it/s, train/loss=0.967]\nEpoch 0: |          | 467/? [03:11<00:00,  2.44it/s, train/loss=4.320]\nEpoch 0: |          | 468/? [03:11<00:00,  2.44it/s, train/loss=4.320]\nEpoch 0: |          | 468/? [03:11<00:00,  2.44it/s, train/loss=3.190]\nEpoch 0: |          | 469/? [03:11<00:00,  2.44it/s, train/loss=3.190]\nEpoch 0: |          | 469/? [03:11<00:00,  2.44it/s, train/loss=4.310]\nEpoch 0: |          | 470/? [03:12<00:00,  2.44it/s, train/loss=4.310]\nEpoch 0: |          | 470/? [03:12<00:00,  2.44it/s, train/loss=2.530]\nEpoch 0: |          | 471/? [03:13<00:00,  2.44it/s, train/loss=2.530]\nEpoch 0: |          | 471/? [03:13<00:00,  2.44it/s, train/loss=2.540]\nEpoch 0: |          | 472/? [03:13<00:00,  2.44it/s, train/loss=2.540]\nEpoch 0: |          | 472/? [03:13<00:00,  2.44it/s, train/loss=1.790]\nEpoch 0: |          | 473/? [03:13<00:00,  2.44it/s, train/loss=1.790]\nEpoch 0: |          | 473/? [03:13<00:00,  2.44it/s, train/loss=4.330]\nEpoch 0: |          | 474/? [03:14<00:00,  2.44it/s, train/loss=4.330]\nEpoch 0: |          | 474/? [03:14<00:00,  2.44it/s, train/loss=3.140]\nEpoch 0: |          | 475/? [03:14<00:00,  2.45it/s, train/loss=3.140]\nEpoch 0: |          | 475/? [03:14<00:00,  2.45it/s, train/loss=4.320]\nEpoch 0: |          | 476/? [03:14<00:00,  2.45it/s, train/loss=4.320]\nEpoch 0: |          | 476/? [03:14<00:00,  2.45it/s, train/loss=2.120]\nEpoch 0: |          | 477/? [03:14<00:00,  2.45it/s, train/loss=2.120]\nEpoch 0: |          | 477/? [03:14<00:00,  2.45it/s, train/loss=4.300]\nEpoch 0: |          | 478/? [03:15<00:00,  2.45it/s, train/loss=4.300]\nEpoch 0: |          | 478/? [03:15<00:00,  2.45it/s, train/loss=1.920]\nEpoch 0: |          | 479/? [03:15<00:00,  2.46it/s, train/loss=1.920]\nEpoch 0: |          | 479/? [03:15<00:00,  2.46it/s, train/loss=4.280]\nEpoch 0: |          | 480/? [03:15<00:00,  2.46it/s, train/loss=4.280]\nEpoch 0: |          | 480/? [03:15<00:00,  2.46it/s, train/loss=2.280]\nEpoch 0: |          | 481/? [03:16<00:00,  2.45it/s, train/loss=2.280]\nEpoch 0: |          | 481/? [03:16<00:00,  2.45it/s, train/loss=0.513]\nEpoch 0: |          | 482/? [03:16<00:00,  2.45it/s, train/loss=0.513]\nEpoch 0: |          | 482/? [03:16<00:00,  2.45it/s, train/loss=0.849]\nEpoch 0: |          | 483/? [03:16<00:00,  2.45it/s, train/loss=0.849]\nEpoch 0: |          | 483/? [03:16<00:00,  2.45it/s, train/loss=4.270]\nEpoch 0: |          | 484/? [03:17<00:00,  2.45it/s, train/loss=4.270]\nEpoch 0: |          | 484/? [03:17<00:00,  2.45it/s, train/loss=1.970]\nEpoch 0: |          | 485/? [03:17<00:00,  2.46it/s, train/loss=1.970]\nEpoch 0: |          | 485/? [03:17<00:00,  2.46it/s, train/loss=4.250]\nEpoch 0: |          | 486/? [03:17<00:00,  2.46it/s, train/loss=4.250]\nEpoch 0: |          | 486/? [03:17<00:00,  2.46it/s, train/loss=1.330]\nEpoch 0: |          | 487/? [03:17<00:00,  2.46it/s, train/loss=1.330]\nEpoch 0: |          | 487/? [03:17<00:00,  2.46it/s, train/loss=4.240]\nEpoch 0: |          | 488/? [03:18<00:00,  2.46it/s, train/loss=4.240]\nEpoch 0: |          | 488/? [03:18<00:00,  2.46it/s, train/loss=3.980]\nEpoch 0: |          | 489/? [03:18<00:00,  2.47it/s, train/loss=3.980]\nEpoch 0: |          | 489/? [03:18<00:00,  2.47it/s, train/loss=4.250]\nEpoch 0: |          | 490/? [03:18<00:00,  2.47it/s, train/loss=4.250]\nEpoch 0: |          | 490/? [03:18<00:00,  2.47it/s, train/loss=3.170]\nEpoch 0: |          | 491/? [03:19<00:00,  2.46it/s, train/loss=3.170]\nEpoch 0: |          | 491/? [03:19<00:00,  2.46it/s, train/loss=3.520]\nEpoch 0: |          | 492/? [03:19<00:00,  2.46it/s, train/loss=3.520]\nEpoch 0: |          | 492/? [03:19<00:00,  2.46it/s, train/loss=1.780]\nEpoch 0: |          | 493/? [03:19<00:00,  2.47it/s, train/loss=1.780]\nEpoch 0: |          | 493/? [03:19<00:00,  2.47it/s, train/loss=4.330]\nEpoch 0: |          | 494/? [03:20<00:00,  2.47it/s, train/loss=4.330]\nEpoch 0: |          | 494/? [03:20<00:00,  2.46it/s, train/loss=2.840]\nEpoch 0: |          | 495/? [03:20<00:00,  2.47it/s, train/loss=2.840]\nEpoch 0: |          | 495/? [03:20<00:00,  2.47it/s, train/loss=4.350]\nEpoch 0: |          | 496/? [03:20<00:00,  2.47it/s, train/loss=4.350]\nEpoch 0: |          | 496/? [03:20<00:00,  2.47it/s, train/loss=2.180]\nEpoch 0: |          | 497/? [03:21<00:00,  2.47it/s, train/loss=2.180]\nEpoch 0: |          | 497/? [03:21<00:00,  2.47it/s, train/loss=4.350]\nEpoch 0: |          | 498/? [03:21<00:00,  2.47it/s, train/loss=4.350]\nEpoch 0: |          | 498/? [03:21<00:00,  2.47it/s, train/loss=0.676]\nEpoch 0: |          | 499/? [03:21<00:00,  2.48it/s, train/loss=0.676]\nEpoch 0: |          | 499/? [03:21<00:00,  2.48it/s, train/loss=4.340]\nEpoch 0: |          | 500/? [03:21<00:00,  2.48it/s, train/loss=4.340]\nEpoch 0: |          | 500/? [03:21<00:00,  2.48it/s, train/loss=1.350]\nEpoch 0: |          | 501/? [03:22<00:00,  2.47it/s, train/loss=1.350]\nEpoch 0: |          | 501/? [03:22<00:00,  2.47it/s, train/loss=1.280]\nEpoch 0: |          | 502/? [03:23<00:00,  2.47it/s, train/loss=1.280]\nEpoch 0: |          | 502/? [03:23<00:00,  2.47it/s, train/loss=1.450]\nEpoch 0: |          | 503/? [03:23<00:00,  2.47it/s, train/loss=1.450]\nEpoch 0: |          | 503/? [03:23<00:00,  2.47it/s, train/loss=4.360]\nEpoch 0: |          | 504/? [03:23<00:00,  2.47it/s, train/loss=4.360]\nEpoch 0: |          | 504/? [03:23<00:00,  2.47it/s, train/loss=2.170]\nEpoch 0: |          | 505/? [03:23<00:00,  2.48it/s, train/loss=2.170]\nEpoch 0: |          | 505/? [03:23<00:00,  2.48it/s, train/loss=4.350]\nEpoch 0: |          | 506/? [03:24<00:00,  2.48it/s, train/loss=4.350]\nEpoch 0: |          | 506/? [03:24<00:00,  2.48it/s, train/loss=1.810]\nEpoch 0: |          | 507/? [03:24<00:00,  2.48it/s, train/loss=1.810]\nEpoch 0: |          | 507/? [03:24<00:00,  2.48it/s, train/loss=4.340]\nEpoch 0: |          | 508/? [03:24<00:00,  2.48it/s, train/loss=4.340]\nEpoch 0: |          | 508/? [03:24<00:00,  2.48it/s, train/loss=2.820]\nEpoch 0: |          | 509/? [03:24<00:00,  2.49it/s, train/loss=2.820]\nEpoch 0: |          | 509/? [03:24<00:00,  2.49it/s, train/loss=4.320]\nEpoch 0: |          | 510/? [03:25<00:00,  2.49it/s, train/loss=4.320]\nEpoch 0: |          | 510/? [03:25<00:00,  2.49it/s, train/loss=1.890]\nEpoch 0: |          | 511/? [03:25<00:00,  2.48it/s, train/loss=1.890]\nEpoch 0: |          | 511/? [03:26<00:00,  2.48it/s, train/loss=1.120]\nEpoch 0: |          | 512/? [03:26<00:00,  2.48it/s, train/loss=1.120]\nEpoch 0: |          | 512/? [03:26<00:00,  2.48it/s, train/loss=2.630]\nEpoch 0: |          | 513/? [03:26<00:00,  2.49it/s, train/loss=2.630]\nEpoch 0: |          | 513/? [03:26<00:00,  2.49it/s, train/loss=4.340]\nEpoch 0: |          | 514/? [03:26<00:00,  2.49it/s, train/loss=4.340]\nEpoch 0: |          | 514/? [03:26<00:00,  2.49it/s, train/loss=0.942]\nEpoch 0: |          | 515/? [03:26<00:00,  2.49it/s, train/loss=0.942]\nEpoch 0: |          | 515/? [03:26<00:00,  2.49it/s, train/loss=4.340]\nEpoch 0: |          | 516/? [03:27<00:00,  2.49it/s, train/loss=4.340]\nEpoch 0: |          | 516/? [03:27<00:00,  2.49it/s, train/loss=1.110]\nEpoch 0: |          | 517/? [03:27<00:00,  2.49it/s, train/loss=1.110]\nEpoch 0: |          | 517/? [03:27<00:00,  2.49it/s, train/loss=4.320]\nEpoch 0: |          | 518/? [03:27<00:00,  2.49it/s, train/loss=4.320]\nEpoch 0: |          | 518/? [03:27<00:00,  2.49it/s, train/loss=4.760]\nEpoch 0: |          | 519/? [03:27<00:00,  2.50it/s, train/loss=4.760]\nEpoch 0: |          | 519/? [03:27<00:00,  2.50it/s, train/loss=4.300]\nEpoch 0: |          | 520/? [03:28<00:00,  2.50it/s, train/loss=4.300]\nEpoch 0: |          | 520/? [03:28<00:00,  2.50it/s, train/loss=1.390]\nEpoch 0: |          | 521/? [03:29<00:00,  2.49it/s, train/loss=1.390]\nEpoch 0: |          | 521/? [03:29<00:00,  2.49it/s, train/loss=1.430]\nEpoch 0: |          | 522/? [03:29<00:00,  2.49it/s, train/loss=1.430]\nEpoch 0: |          | 522/? [03:29<00:00,  2.49it/s, train/loss=1.370]\nEpoch 0: |          | 523/? [03:29<00:00,  2.50it/s, train/loss=1.370]\nEpoch 0: |          | 523/? [03:29<00:00,  2.50it/s, train/loss=4.260]\nEpoch 0: |          | 524/? [03:29<00:00,  2.50it/s, train/loss=4.260]\nEpoch 0: |          | 524/? [03:29<00:00,  2.50it/s, train/loss=1.990]\nEpoch 0: |          | 525/? [03:29<00:00,  2.50it/s, train/loss=1.990]\nEpoch 0: |          | 525/? [03:29<00:00,  2.50it/s, train/loss=4.240]\nEpoch 0: |          | 526/? [03:30<00:00,  2.50it/s, train/loss=4.240]\nEpoch 0: |          | 526/? [03:30<00:00,  2.50it/s, train/loss=1.040]\nEpoch 0: |          | 527/? [03:30<00:00,  2.50it/s, train/loss=1.040]\nEpoch 0: |          | 527/? [03:30<00:00,  2.50it/s, train/loss=4.210]\nEpoch 0: |          | 528/? [03:30<00:00,  2.50it/s, train/loss=4.210]\nEpoch 0: |          | 528/? [03:30<00:00,  2.50it/s, train/loss=1.550]\nEpoch 0: |          | 529/? [03:30<00:00,  2.51it/s, train/loss=1.550]\nEpoch 0: |          | 529/? [03:30<00:00,  2.51it/s, train/loss=4.190]\nEpoch 0: |          | 530/? [03:31<00:00,  2.51it/s, train/loss=4.190]\nEpoch 0: |          | 530/? [03:31<00:00,  2.51it/s, train/loss=2.190]\nEpoch 0: |          | 531/? [03:32<00:00,  2.50it/s, train/loss=2.190]\nEpoch 0: |          | 531/? [03:32<00:00,  2.50it/s, train/loss=2.480]\nEpoch 0: |          | 532/? [03:32<00:00,  2.50it/s, train/loss=2.480]\nEpoch 0: |          | 532/? [03:32<00:00,  2.50it/s, train/loss=3.060]\nEpoch 0: |          | 533/? [03:32<00:00,  2.51it/s, train/loss=3.060]\nEpoch 0: |          | 533/? [03:32<00:00,  2.51it/s, train/loss=4.170]\nEpoch 0: |          | 534/? [03:33<00:00,  2.51it/s, train/loss=4.170]\nEpoch 0: |          | 534/? [03:33<00:00,  2.51it/s, train/loss=1.580]\nEpoch 0: |          | 535/? [03:33<00:00,  2.51it/s, train/loss=1.580]\nEpoch 0: |          | 535/? [03:33<00:00,  2.51it/s, train/loss=4.150]\nEpoch 0: |          | 536/? [03:33<00:00,  2.51it/s, train/loss=4.150]\nEpoch 0: |          | 536/? [03:33<00:00,  2.51it/s, train/loss=2.330]\nEpoch 0: |          | 537/? [03:33<00:00,  2.51it/s, train/loss=2.330]\nEpoch 0: |          | 537/? [03:33<00:00,  2.51it/s, train/loss=4.130]\nEpoch 0: |          | 538/? [03:33<00:00,  2.51it/s, train/loss=4.130]\nEpoch 0: |          | 538/? [03:33<00:00,  2.51it/s, train/loss=1.740]\nEpoch 0: |          | 539/? [03:34<00:00,  2.52it/s, train/loss=1.740]\nEpoch 0: |          | 539/? [03:34<00:00,  2.52it/s, train/loss=4.120]\nEpoch 0: |          | 540/? [03:34<00:00,  2.52it/s, train/loss=4.120]\nEpoch 0: |          | 540/? [03:34<00:00,  2.52it/s, train/loss=2.130]\nEpoch 0: |          | 541/? [03:35<00:00,  2.51it/s, train/loss=2.130]\nEpoch 0: |          | 541/? [03:35<00:00,  2.51it/s, train/loss=2.980]\nEpoch 0: |          | 542/? [03:35<00:00,  2.51it/s, train/loss=2.980]\nEpoch 0: |          | 542/? [03:35<00:00,  2.51it/s, train/loss=1.930]\nEpoch 0: |          | 543/? [03:35<00:00,  2.52it/s, train/loss=1.930]\nEpoch 0: |          | 543/? [03:35<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 544/? [03:36<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 544/? [03:36<00:00,  2.52it/s, train/loss=2.970]\nEpoch 0: |          | 545/? [03:36<00:00,  2.52it/s, train/loss=2.970]\nEpoch 0: |          | 545/? [03:36<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 546/? [03:36<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 546/? [03:36<00:00,  2.52it/s, train/loss=1.780]\nEpoch 0: |          | 547/? [03:36<00:00,  2.52it/s, train/loss=1.780]\nEpoch 0: |          | 547/? [03:36<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 548/? [03:37<00:00,  2.52it/s, train/loss=4.130]\nEpoch 0: |          | 548/? [03:37<00:00,  2.52it/s, train/loss=2.270]\nEpoch 0: |          | 549/? [03:37<00:00,  2.53it/s, train/loss=2.270]\nEpoch 0: |          | 549/? [03:37<00:00,  2.53it/s, train/loss=4.110]\nEpoch 0: |          | 550/? [03:37<00:00,  2.53it/s, train/loss=4.110]\nEpoch 0: |          | 550/? [03:37<00:00,  2.53it/s, train/loss=2.440]\nEpoch 0: |          | 551/? [03:38<00:00,  2.52it/s, train/loss=2.440]\nEpoch 0: |          | 551/? [03:38<00:00,  2.52it/s, train/loss=2.390]\nEpoch 0: |          | 552/? [03:38<00:00,  2.52it/s, train/loss=2.390]\nEpoch 0: |          | 552/? [03:38<00:00,  2.52it/s, train/loss=1.130]\nEpoch 0: |          | 553/? [03:38<00:00,  2.53it/s, train/loss=1.130]\nEpoch 0: |          | 553/? [03:38<00:00,  2.53it/s, train/loss=4.110]\nEpoch 0: |          | 554/? [03:39<00:00,  2.53it/s, train/loss=4.110]\nEpoch 0: |          | 554/? [03:39<00:00,  2.53it/s, train/loss=0.801]\nEpoch 0: |          | 555/? [03:39<00:00,  2.53it/s, train/loss=0.801]\nEpoch 0: |          | 555/? [03:39<00:00,  2.53it/s, train/loss=4.090]\nEpoch 0: |          | 556/? [03:39<00:00,  2.53it/s, train/loss=4.090]\nEpoch 0: |          | 556/? [03:39<00:00,  2.53it/s, train/loss=3.380]\nEpoch 0: |          | 557/? [03:39<00:00,  2.53it/s, train/loss=3.380]\nEpoch 0: |          | 557/? [03:39<00:00,  2.53it/s, train/loss=4.070]\nEpoch 0: |          | 558/? [03:40<00:00,  2.53it/s, train/loss=4.070]\nEpoch 0: |          | 558/? [03:40<00:00,  2.53it/s, train/loss=2.010]\nEpoch 0: |          | 559/? [03:40<00:00,  2.54it/s, train/loss=2.010]\nEpoch 0: |          | 559/? [03:40<00:00,  2.54it/s, train/loss=4.050]\nEpoch 0: |          | 560/? [03:40<00:00,  2.54it/s, train/loss=4.050]\nEpoch 0: |          | 560/? [03:40<00:00,  2.54it/s, train/loss=1.340]\nEpoch 0: |          | 561/? [03:41<00:00,  2.53it/s, train/loss=1.340]\nEpoch 0: |          | 561/? [03:41<00:00,  2.53it/s, train/loss=2.310]\nEpoch 0: |          | 562/? [03:42<00:00,  2.53it/s, train/loss=2.310]\nEpoch 0: |          | 562/? [03:42<00:00,  2.53it/s, train/loss=0.956]\nEpoch 0: |          | 563/? [03:42<00:00,  2.53it/s, train/loss=0.956]\nEpoch 0: |          | 563/? [03:42<00:00,  2.53it/s, train/loss=4.030]\nEpoch 0: |          | 564/? [03:42<00:00,  2.53it/s, train/loss=4.030]\nEpoch 0: |          | 564/? [03:42<00:00,  2.53it/s, train/loss=3.390]\nEpoch 0: |          | 565/? [03:42<00:00,  2.54it/s, train/loss=3.390]\nEpoch 0: |          | 565/? [03:42<00:00,  2.54it/s, train/loss=4.010]\nEpoch 0: |          | 566/? [03:43<00:00,  2.54it/s, train/loss=4.010]\nEpoch 0: |          | 566/? [03:43<00:00,  2.54it/s, train/loss=2.930]\nEpoch 0: |          | 567/? [03:43<00:00,  2.54it/s, train/loss=2.930]\nEpoch 0: |          | 567/? [03:43<00:00,  2.54it/s, train/loss=4.000]\nEpoch 0: |          | 568/? [03:43<00:00,  2.54it/s, train/loss=4.000]\nEpoch 0: |          | 568/? [03:43<00:00,  2.54it/s, train/loss=2.650]\nEpoch 0: |          | 569/? [03:43<00:00,  2.55it/s, train/loss=2.650]\nEpoch 0: |          | 569/? [03:43<00:00,  2.55it/s, train/loss=3.990]\nEpoch 0: |          | 570/? [03:43<00:00,  2.55it/s, train/loss=3.990]\nEpoch 0: |          | 570/? [03:43<00:00,  2.55it/s, train/loss=0.636]\nEpoch 0: |          | 571/? [03:44<00:00,  2.54it/s, train/loss=0.636]\nEpoch 0: |          | 571/? [03:44<00:00,  2.54it/s, train/loss=1.320]\nEpoch 0: |          | 572/? [03:45<00:00,  2.54it/s, train/loss=1.320]\nEpoch 0: |          | 572/? [03:45<00:00,  2.54it/s, train/loss=0.937]\nEpoch 0: |          | 573/? [03:45<00:00,  2.54it/s, train/loss=0.937]\nEpoch 0: |          | 573/? [03:45<00:00,  2.54it/s, train/loss=4.000]\nEpoch 0: |          | 574/? [03:45<00:00,  2.54it/s, train/loss=4.000]\nEpoch 0: |          | 574/? [03:45<00:00,  2.54it/s, train/loss=0.672]\nEpoch 0: |          | 575/? [03:45<00:00,  2.55it/s, train/loss=0.672]\nEpoch 0: |          | 575/? [03:45<00:00,  2.55it/s, train/loss=3.980]\nEpoch 0: |          | 576/? [03:46<00:00,  2.55it/s, train/loss=3.980]\nEpoch 0: |          | 576/? [03:46<00:00,  2.55it/s, train/loss=2.170]\nEpoch 0: |          | 577/? [03:46<00:00,  2.55it/s, train/loss=2.170]\nEpoch 0: |          | 577/? [03:46<00:00,  2.55it/s, train/loss=3.970]\nEpoch 0: |          | 578/? [03:46<00:00,  2.55it/s, train/loss=3.970]\nEpoch 0: |          | 578/? [03:46<00:00,  2.55it/s, train/loss=1.480]\nEpoch 0: |          | 579/? [03:46<00:00,  2.55it/s, train/loss=1.480]\nEpoch 0: |          | 579/? [03:46<00:00,  2.55it/s, train/loss=3.960]\nEpoch 0: |          | 580/? [03:47<00:00,  2.55it/s, train/loss=3.960]\nEpoch 0: |          | 580/? [03:47<00:00,  2.55it/s, train/loss=3.060]\nEpoch 0: |          | 581/? [03:47<00:00,  2.55it/s, train/loss=3.060]\nEpoch 0: |          | 581/? [03:48<00:00,  2.55it/s, train/loss=2.920]\nEpoch 0: |          | 582/? [03:48<00:00,  2.55it/s, train/loss=2.920]\nEpoch 0: |          | 582/? [03:48<00:00,  2.55it/s, train/loss=0.917]\nEpoch 0: |          | 583/? [03:48<00:00,  2.55it/s, train/loss=0.917]\nEpoch 0: |          | 583/? [03:48<00:00,  2.55it/s, train/loss=3.960]\nEpoch 0: |          | 584/? [03:48<00:00,  2.55it/s, train/loss=3.960]\nEpoch 0: |          | 584/? [03:48<00:00,  2.55it/s, train/loss=2.450]\nEpoch 0: |          | 585/? [03:49<00:00,  2.55it/s, train/loss=2.450]\nEpoch 0: |          | 585/? [03:49<00:00,  2.55it/s, train/loss=3.950]\nEpoch 0: |          | 586/? [03:49<00:00,  2.55it/s, train/loss=3.950]\nEpoch 0: |          | 586/? [03:49<00:00,  2.55it/s, train/loss=2.180]\nEpoch 0: |          | 587/? [03:49<00:00,  2.56it/s, train/loss=2.180]\nEpoch 0: |          | 587/? [03:49<00:00,  2.56it/s, train/loss=3.920]\nEpoch 0: |          | 588/? [03:49<00:00,  2.56it/s, train/loss=3.920]\nEpoch 0: |          | 588/? [03:49<00:00,  2.56it/s, train/loss=2.390]\nEpoch 0: |          | 589/? [03:49<00:00,  2.56it/s, train/loss=2.390]\nEpoch 0: |          | 589/? [03:49<00:00,  2.56it/s, train/loss=3.920]\nEpoch 0: |          | 590/? [03:50<00:00,  2.56it/s, train/loss=3.920]\nEpoch 0: |          | 590/? [03:50<00:00,  2.56it/s, train/loss=3.030]\nEpoch 0: |          | 591/? [03:51<00:00,  2.56it/s, train/loss=3.030]\nEpoch 0: |          | 591/? [03:51<00:00,  2.56it/s, train/loss=1.200]\nEpoch 0: |          | 592/? [03:51<00:00,  2.56it/s, train/loss=1.200]\nEpoch 0: |          | 592/? [03:51<00:00,  2.56it/s, train/loss=0.798]\nEpoch 0: |          | 593/? [03:51<00:00,  2.56it/s, train/loss=0.798]\nEpoch 0: |          | 593/? [03:51<00:00,  2.56it/s, train/loss=3.990]\nEpoch 0: |          | 594/? [03:52<00:00,  2.56it/s, train/loss=3.990]\nEpoch 0: |          | 594/? [03:52<00:00,  2.56it/s, train/loss=1.160]\nEpoch 0: |          | 595/? [03:52<00:00,  2.56it/s, train/loss=1.160]\nEpoch 0: |          | 595/? [03:52<00:00,  2.56it/s, train/loss=4.010]\nEpoch 0: |          | 596/? [03:52<00:00,  2.56it/s, train/loss=4.010]\nEpoch 0: |          | 596/? [03:52<00:00,  2.56it/s, train/loss=3.640]\nEpoch 0: |          | 597/? [03:52<00:00,  2.57it/s, train/loss=3.640]\nEpoch 0: |          | 597/? [03:52<00:00,  2.57it/s, train/loss=4.010]\nEpoch 0: |          | 598/? [03:53<00:00,  2.57it/s, train/loss=4.010]\nEpoch 0: |          | 598/? [03:53<00:00,  2.57it/s, train/loss=2.290]\nEpoch 0: |          | 599/? [03:53<00:00,  2.57it/s, train/loss=2.290]\nEpoch 0: |          | 599/? [03:53<00:00,  2.57it/s, train/loss=4.020]\nEpoch 0: |          | 600/? [03:53<00:00,  2.57it/s, train/loss=4.020]\nEpoch 0: |          | 600/? [03:53<00:00,  2.57it/s, train/loss=2.900]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:04,  8.54it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:04,  8.56it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:04,  8.57it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:04,  8.60it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:04,  8.62it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:03,  8.65it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:03,  8.68it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:03,  8.72it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:01<00:03,  8.75it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:01<00:03,  8.82it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:01<00:03,  8.86it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:03,  8.55it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:03,  8.54it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:03,  8.59it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02,  8.61it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02,  8.62it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:02,  8.63it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:02<00:02,  8.66it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:02<00:02,  8.69it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:02<00:02,  8.69it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:02<00:02,  8.71it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:02<00:02,  8.72it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:02<00:01,  8.75it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01,  8.78it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01,  8.78it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01,  8.80it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:03<00:01,  8.81it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:03<00:01,  8.82it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:03<00:01,  8.82it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:03<00:01,  8.83it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:03<00:01,  8.85it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:03<00:00,  8.86it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:03<00:00,  8.86it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:03<00:00,  8.88it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00,  8.87it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:04<00:00,  8.84it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:04<00:00,  8.83it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:04<00:00,  8.83it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:04<00:00,  8.83it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00,  8.82it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 600/? [04:04<00:00,  2.46it/s, train/loss=2.900]\nEpoch 0: |          | 601/? [04:19<00:00,  2.31it/s, train/loss=2.900]\nEpoch 0: |          | 601/? [04:19<00:00,  2.31it/s, train/loss=1.340]\nEpoch 0: |          | 602/? [04:19<00:00,  2.32it/s, train/loss=1.340]\nEpoch 0: |          | 602/? [04:20<00:00,  2.32it/s, train/loss=1.860]\nEpoch 0: |          | 603/? [04:20<00:00,  2.32it/s, train/loss=1.860]\nEpoch 0: |          | 603/? [04:20<00:00,  2.32it/s, train/loss=4.060]\nEpoch 0: |          | 604/? [04:20<00:00,  2.32it/s, train/loss=4.060]\nEpoch 0: |          | 604/? [04:20<00:00,  2.32it/s, train/loss=2.570]\nEpoch 0: |          | 605/? [04:20<00:00,  2.32it/s, train/loss=2.570]\nEpoch 0: |          | 605/? [04:20<00:00,  2.32it/s, train/loss=4.070]\nEpoch 0: |          | 606/? [04:20<00:00,  2.32it/s, train/loss=4.070]\nEpoch 0: |          | 606/? [04:20<00:00,  2.32it/s, train/loss=3.590]\nEpoch 0: |          | 607/? [04:20<00:00,  2.33it/s, train/loss=3.590]\nEpoch 0: |          | 607/? [04:20<00:00,  2.33it/s, train/loss=4.070]\nEpoch 0: |          | 608/? [04:21<00:00,  2.33it/s, train/loss=4.070]\nEpoch 0: |          | 608/? [04:21<00:00,  2.33it/s, train/loss=3.050]\nEpoch 0: |          | 609/? [04:21<00:00,  2.33it/s, train/loss=3.050]\nEpoch 0: |          | 609/? [04:21<00:00,  2.33it/s, train/loss=4.060]\nEpoch 0: |          | 610/? [04:21<00:00,  2.33it/s, train/loss=4.060]\nEpoch 0: |          | 610/? [04:21<00:00,  2.33it/s, train/loss=1.530]\nEpoch 0: |          | 611/? [04:22<00:00,  2.33it/s, train/loss=1.530]\nEpoch 0: |          | 611/? [04:22<00:00,  2.32it/s, train/loss=1.450]\nEpoch 0: |          | 612/? [04:23<00:00,  2.33it/s, train/loss=1.450]\nEpoch 0: |          | 612/? [04:23<00:00,  2.33it/s, train/loss=1.410]\nEpoch 0: |          | 613/? [04:23<00:00,  2.33it/s, train/loss=1.410]\nEpoch 0: |          | 613/? [04:23<00:00,  2.33it/s, train/loss=4.070]\nEpoch 0: |          | 614/? [04:23<00:00,  2.33it/s, train/loss=4.070]\nEpoch 0: |          | 614/? [04:23<00:00,  2.33it/s, train/loss=2.290]\nEpoch 0: |          | 615/? [04:23<00:00,  2.33it/s, train/loss=2.290]\nEpoch 0: |          | 615/? [04:23<00:00,  2.33it/s, train/loss=4.050]\nEpoch 0: |          | 616/? [04:24<00:00,  2.33it/s, train/loss=4.050]\nEpoch 0: |          | 616/? [04:24<00:00,  2.33it/s, train/loss=2.550]\nEpoch 0: |          | 617/? [04:24<00:00,  2.34it/s, train/loss=2.550]\nEpoch 0: |          | 617/? [04:24<00:00,  2.34it/s, train/loss=4.010]\nEpoch 0: |          | 618/? [04:24<00:00,  2.34it/s, train/loss=4.010]\nEpoch 0: |          | 618/? [04:24<00:00,  2.34it/s, train/loss=2.220]\nEpoch 0: |          | 619/? [04:24<00:00,  2.34it/s, train/loss=2.220]\nEpoch 0: |          | 619/? [04:24<00:00,  2.34it/s, train/loss=3.990]\nEpoch 0: |          | 620/? [04:25<00:00,  2.34it/s, train/loss=3.990]\nEpoch 0: |          | 620/? [04:25<00:00,  2.34it/s, train/loss=0.898]\nEpoch 0: |          | 621/? [04:25<00:00,  2.33it/s, train/loss=0.898]\nEpoch 0: |          | 621/? [04:26<00:00,  2.33it/s, train/loss=1.590]\nEpoch 0: |          | 622/? [04:26<00:00,  2.34it/s, train/loss=1.590]\nEpoch 0: |          | 622/? [04:26<00:00,  2.34it/s, train/loss=0.873]\nEpoch 0: |          | 623/? [04:26<00:00,  2.34it/s, train/loss=0.873]\nEpoch 0: |          | 623/? [04:26<00:00,  2.34it/s, train/loss=3.970]\nEpoch 0: |          | 624/? [04:26<00:00,  2.34it/s, train/loss=3.970]\nEpoch 0: |          | 624/? [04:26<00:00,  2.34it/s, train/loss=2.080]\nEpoch 0: |          | 625/? [04:26<00:00,  2.34it/s, train/loss=2.080]\nEpoch 0: |          | 625/? [04:26<00:00,  2.34it/s, train/loss=3.940]\nEpoch 0: |          | 626/? [04:27<00:00,  2.34it/s, train/loss=3.940]\nEpoch 0: |          | 626/? [04:27<00:00,  2.34it/s, train/loss=2.700]\nEpoch 0: |          | 627/? [04:27<00:00,  2.35it/s, train/loss=2.700]\nEpoch 0: |          | 627/? [04:27<00:00,  2.35it/s, train/loss=3.920]\nEpoch 0: |          | 628/? [04:27<00:00,  2.35it/s, train/loss=3.920]\nEpoch 0: |          | 628/? [04:27<00:00,  2.35it/s, train/loss=1.280]\nEpoch 0: |          | 629/? [04:27<00:00,  2.35it/s, train/loss=1.280]\nEpoch 0: |          | 629/? [04:27<00:00,  2.35it/s, train/loss=3.910]\nEpoch 0: |          | 630/? [04:28<00:00,  2.35it/s, train/loss=3.910]\nEpoch 0: |          | 630/? [04:28<00:00,  2.35it/s, train/loss=1.190]\nEpoch 0: |          | 631/? [04:29<00:00,  2.35it/s, train/loss=1.190]\nEpoch 0: |          | 631/? [04:29<00:00,  2.34it/s, train/loss=0.802]\nEpoch 0: |          | 632/? [04:29<00:00,  2.35it/s, train/loss=0.802]\nEpoch 0: |          | 632/? [04:29<00:00,  2.35it/s, train/loss=1.520]\nEpoch 0: |          | 633/? [04:29<00:00,  2.35it/s, train/loss=1.520]\nEpoch 0: |          | 633/? [04:29<00:00,  2.35it/s, train/loss=3.940]\nEpoch 0: |          | 634/? [04:29<00:00,  2.35it/s, train/loss=3.940]\nEpoch 0: |          | 634/? [04:29<00:00,  2.35it/s, train/loss=3.810]\nEpoch 0: |          | 635/? [04:29<00:00,  2.35it/s, train/loss=3.810]\nEpoch 0: |          | 635/? [04:29<00:00,  2.35it/s, train/loss=3.930]\nEpoch 0: |          | 636/? [04:30<00:00,  2.35it/s, train/loss=3.930]\nEpoch 0: |          | 636/? [04:30<00:00,  2.35it/s, train/loss=2.680]\nEpoch 0: |          | 637/? [04:30<00:00,  2.36it/s, train/loss=2.680]\nEpoch 0: |          | 637/? [04:30<00:00,  2.36it/s, train/loss=3.910]\nEpoch 0: |          | 638/? [04:30<00:00,  2.36it/s, train/loss=3.910]\nEpoch 0: |          | 638/? [04:30<00:00,  2.36it/s, train/loss=2.430]\nEpoch 0: |          | 639/? [04:30<00:00,  2.36it/s, train/loss=2.430]\nEpoch 0: |          | 639/? [04:30<00:00,  2.36it/s, train/loss=3.890]\nEpoch 0: |          | 640/? [04:31<00:00,  2.36it/s, train/loss=3.890]\nEpoch 0: |          | 640/? [04:31<00:00,  2.36it/s, train/loss=3.000]\nEpoch 0: |          | 641/? [04:32<00:00,  2.36it/s, train/loss=3.000]\nEpoch 0: |          | 641/? [04:32<00:00,  2.35it/s, train/loss=0.737]\nEpoch 0: |          | 642/? [04:32<00:00,  2.36it/s, train/loss=0.737]\nEpoch 0: |          | 642/? [04:32<00:00,  2.36it/s, train/loss=1.870]\nEpoch 0: |          | 643/? [04:32<00:00,  2.36it/s, train/loss=1.870]\nEpoch 0: |          | 643/? [04:32<00:00,  2.36it/s, train/loss=3.870]\nEpoch 0: |          | 644/? [04:33<00:00,  2.36it/s, train/loss=3.870]\nEpoch 0: |          | 644/? [04:33<00:00,  2.36it/s, train/loss=2.900]\nEpoch 0: |          | 645/? [04:33<00:00,  2.36it/s, train/loss=2.900]\nEpoch 0: |          | 645/? [04:33<00:00,  2.36it/s, train/loss=3.850]\nEpoch 0: |          | 646/? [04:33<00:00,  2.36it/s, train/loss=3.850]\nEpoch 0: |          | 646/? [04:33<00:00,  2.36it/s, train/loss=2.790]\nEpoch 0: |          | 647/? [04:33<00:00,  2.37it/s, train/loss=2.790]\nEpoch 0: |          | 647/? [04:33<00:00,  2.37it/s, train/loss=3.830]\nEpoch 0: |          | 648/? [04:33<00:00,  2.37it/s, train/loss=3.830]\nEpoch 0: |          | 648/? [04:33<00:00,  2.37it/s, train/loss=3.090]\nEpoch 0: |          | 649/? [04:33<00:00,  2.37it/s, train/loss=3.090]\nEpoch 0: |          | 649/? [04:34<00:00,  2.37it/s, train/loss=3.810]\nEpoch 0: |          | 650/? [04:34<00:00,  2.37it/s, train/loss=3.810]\nEpoch 0: |          | 650/? [04:34<00:00,  2.37it/s, train/loss=5.800]\nEpoch 0: |          | 651/? [04:35<00:00,  2.36it/s, train/loss=5.800]\nEpoch 0: |          | 651/? [04:35<00:00,  2.36it/s, train/loss=1.430]\nEpoch 0: |          | 652/? [04:35<00:00,  2.36it/s, train/loss=1.430]\nEpoch 0: |          | 652/? [04:35<00:00,  2.36it/s, train/loss=0.542]\nEpoch 0: |          | 653/? [04:35<00:00,  2.37it/s, train/loss=0.542]\nEpoch 0: |          | 653/? [04:35<00:00,  2.37it/s, train/loss=3.840]\nEpoch 0: |          | 654/? [04:36<00:00,  2.37it/s, train/loss=3.840]\nEpoch 0: |          | 654/? [04:36<00:00,  2.37it/s, train/loss=1.890]\nEpoch 0: |          | 655/? [04:36<00:00,  2.37it/s, train/loss=1.890]\nEpoch 0: |          | 655/? [04:36<00:00,  2.37it/s, train/loss=3.850]\nEpoch 0: |          | 656/? [04:36<00:00,  2.37it/s, train/loss=3.850]\nEpoch 0: |          | 656/? [04:36<00:00,  2.37it/s, train/loss=1.940]\nEpoch 0: |          | 657/? [04:36<00:00,  2.37it/s, train/loss=1.940]\nEpoch 0: |          | 657/? [04:36<00:00,  2.37it/s, train/loss=3.850]\nEpoch 0: |          | 658/? [04:37<00:00,  2.37it/s, train/loss=3.850]\nEpoch 0: |          | 658/? [04:37<00:00,  2.37it/s, train/loss=2.310]\nEpoch 0: |          | 659/? [04:37<00:00,  2.38it/s, train/loss=2.310]\nEpoch 0: |          | 659/? [04:37<00:00,  2.38it/s, train/loss=3.850]\nEpoch 0: |          | 660/? [04:37<00:00,  2.38it/s, train/loss=3.850]\nEpoch 0: |          | 660/? [04:37<00:00,  2.38it/s, train/loss=3.240]\nEpoch 0: |          | 661/? [04:38<00:00,  2.37it/s, train/loss=3.240]\nEpoch 0: |          | 661/? [04:38<00:00,  2.37it/s, train/loss=1.370]\nEpoch 0: |          | 662/? [04:38<00:00,  2.37it/s, train/loss=1.370]\nEpoch 0: |          | 662/? [04:38<00:00,  2.37it/s, train/loss=0.638]\nEpoch 0: |          | 663/? [04:38<00:00,  2.38it/s, train/loss=0.638]\nEpoch 0: |          | 663/? [04:38<00:00,  2.38it/s, train/loss=3.890]\nEpoch 0: |          | 664/? [04:39<00:00,  2.38it/s, train/loss=3.890]\nEpoch 0: |          | 664/? [04:39<00:00,  2.38it/s, train/loss=2.390]\nEpoch 0: |          | 665/? [04:39<00:00,  2.38it/s, train/loss=2.390]\nEpoch 0: |          | 665/? [04:39<00:00,  2.38it/s, train/loss=3.900]\nEpoch 0: |          | 666/? [04:39<00:00,  2.38it/s, train/loss=3.900]\nEpoch 0: |          | 666/? [04:39<00:00,  2.38it/s, train/loss=1.330]\nEpoch 0: |          | 667/? [04:39<00:00,  2.38it/s, train/loss=1.330]\nEpoch 0: |          | 667/? [04:39<00:00,  2.38it/s, train/loss=3.870]\nEpoch 0: |          | 668/? [04:40<00:00,  2.38it/s, train/loss=3.870]\nEpoch 0: |          | 668/? [04:40<00:00,  2.38it/s, train/loss=2.550]\nEpoch 0: |          | 669/? [04:40<00:00,  2.39it/s, train/loss=2.550]\nEpoch 0: |          | 669/? [04:40<00:00,  2.39it/s, train/loss=3.870]\nEpoch 0: |          | 670/? [04:40<00:00,  2.39it/s, train/loss=3.870]\nEpoch 0: |          | 670/? [04:40<00:00,  2.39it/s, train/loss=1.670]\nEpoch 0: |          | 671/? [04:41<00:00,  2.38it/s, train/loss=1.670]\nEpoch 0: |          | 671/? [04:41<00:00,  2.38it/s, train/loss=0.788]\nEpoch 0: |          | 672/? [04:41<00:00,  2.38it/s, train/loss=0.788]\nEpoch 0: |          | 672/? [04:42<00:00,  2.38it/s, train/loss=1.160]\nEpoch 0: |          | 673/? [04:42<00:00,  2.39it/s, train/loss=1.160]\nEpoch 0: |          | 673/? [04:42<00:00,  2.39it/s, train/loss=3.890]\nEpoch 0: |          | 674/? [04:42<00:00,  2.39it/s, train/loss=3.890]\nEpoch 0: |          | 674/? [04:42<00:00,  2.39it/s, train/loss=1.260]\nEpoch 0: |          | 675/? [04:42<00:00,  2.39it/s, train/loss=1.260]\nEpoch 0: |          | 675/? [04:42<00:00,  2.39it/s, train/loss=3.880]\nEpoch 0: |          | 676/? [04:42<00:00,  2.39it/s, train/loss=3.880]\nEpoch 0: |          | 676/? [04:42<00:00,  2.39it/s, train/loss=3.090]\nEpoch 0: |          | 677/? [04:43<00:00,  2.39it/s, train/loss=3.090]\nEpoch 0: |          | 677/? [04:43<00:00,  2.39it/s, train/loss=3.870]\nEpoch 0: |          | 678/? [04:43<00:00,  2.39it/s, train/loss=3.870]\nEpoch 0: |          | 678/? [04:43<00:00,  2.39it/s, train/loss=3.090]\nEpoch 0: |          | 679/? [04:43<00:00,  2.40it/s, train/loss=3.090]\nEpoch 0: |          | 679/? [04:43<00:00,  2.40it/s, train/loss=3.850]\nEpoch 0: |          | 680/? [04:43<00:00,  2.40it/s, train/loss=3.850]\nEpoch 0: |          | 680/? [04:43<00:00,  2.40it/s, train/loss=2.110]\nEpoch 0: |          | 681/? [04:44<00:00,  2.39it/s, train/loss=2.110]\nEpoch 0: |          | 681/? [04:44<00:00,  2.39it/s, train/loss=0.638]\nEpoch 0: |          | 682/? [04:45<00:00,  2.39it/s, train/loss=0.638]\nEpoch 0: |          | 682/? [04:45<00:00,  2.39it/s, train/loss=1.190]\nEpoch 0: |          | 683/? [04:45<00:00,  2.39it/s, train/loss=1.190]\nEpoch 0: |          | 683/? [04:45<00:00,  2.39it/s, train/loss=3.870]\nEpoch 0: |          | 684/? [04:45<00:00,  2.40it/s, train/loss=3.870]\nEpoch 0: |          | 684/? [04:45<00:00,  2.40it/s, train/loss=2.190]\nEpoch 0: |          | 685/? [04:45<00:00,  2.40it/s, train/loss=2.190]\nEpoch 0: |          | 685/? [04:45<00:00,  2.40it/s, train/loss=3.850]\nEpoch 0: |          | 686/? [04:46<00:00,  2.40it/s, train/loss=3.850]\nEpoch 0: |          | 686/? [04:46<00:00,  2.40it/s, train/loss=2.970]\nEpoch 0: |          | 687/? [04:46<00:00,  2.40it/s, train/loss=2.970]\nEpoch 0: |          | 687/? [04:46<00:00,  2.40it/s, train/loss=3.830]\nEpoch 0: |          | 688/? [04:46<00:00,  2.40it/s, train/loss=3.830]\nEpoch 0: |          | 688/? [04:46<00:00,  2.40it/s, train/loss=3.460]\nEpoch 0: |          | 689/? [04:46<00:00,  2.40it/s, train/loss=3.460]\nEpoch 0: |          | 689/? [04:46<00:00,  2.40it/s, train/loss=3.830]\nEpoch 0: |          | 690/? [04:46<00:00,  2.40it/s, train/loss=3.830]\nEpoch 0: |          | 690/? [04:46<00:00,  2.40it/s, train/loss=3.190]\nEpoch 0: |          | 691/? [04:47<00:00,  2.40it/s, train/loss=3.190]\nEpoch 0: |          | 691/? [04:47<00:00,  2.40it/s, train/loss=5.260]\nEpoch 0: |          | 692/? [04:48<00:00,  2.40it/s, train/loss=5.260]\nEpoch 0: |          | 692/? [04:48<00:00,  2.40it/s, train/loss=1.940]\nEpoch 0: |          | 693/? [04:48<00:00,  2.40it/s, train/loss=1.940]\nEpoch 0: |          | 693/? [04:48<00:00,  2.40it/s, train/loss=3.870]\nEpoch 0: |          | 694/? [04:48<00:00,  2.40it/s, train/loss=3.870]\nEpoch 0: |          | 694/? [04:48<00:00,  2.40it/s, train/loss=1.400]\nEpoch 0: |          | 695/? [04:48<00:00,  2.41it/s, train/loss=1.400]\nEpoch 0: |          | 695/? [04:48<00:00,  2.41it/s, train/loss=3.880]\nEpoch 0: |          | 696/? [04:49<00:00,  2.41it/s, train/loss=3.880]\nEpoch 0: |          | 696/? [04:49<00:00,  2.41it/s, train/loss=3.600]\nEpoch 0: |          | 697/? [04:49<00:00,  2.41it/s, train/loss=3.600]\nEpoch 0: |          | 697/? [04:49<00:00,  2.41it/s, train/loss=3.870]\nEpoch 0: |          | 698/? [04:49<00:00,  2.41it/s, train/loss=3.870]\nEpoch 0: |          | 698/? [04:49<00:00,  2.41it/s, train/loss=0.728]\nEpoch 0: |          | 699/? [04:49<00:00,  2.41it/s, train/loss=0.728]\nEpoch 0: |          | 699/? [04:49<00:00,  2.41it/s, train/loss=3.880]\nEpoch 0: |          | 700/? [04:50<00:00,  2.41it/s, train/loss=3.880]\nEpoch 0: |          | 700/? [04:50<00:00,  2.41it/s, train/loss=4.150]\nEpoch 0: |          | 701/? [04:50<00:00,  2.41it/s, train/loss=4.150]\nEpoch 0: |          | 701/? [04:51<00:00,  2.41it/s, train/loss=3.100]\nEpoch 0: |          | 702/? [04:51<00:00,  2.41it/s, train/loss=3.100]\nEpoch 0: |          | 702/? [04:51<00:00,  2.41it/s, train/loss=1.620]\nEpoch 0: |          | 703/? [04:51<00:00,  2.41it/s, train/loss=1.620]\nEpoch 0: |          | 703/? [04:51<00:00,  2.41it/s, train/loss=3.910]\nEpoch 0: |          | 704/? [04:51<00:00,  2.41it/s, train/loss=3.910]\nEpoch 0: |          | 704/? [04:51<00:00,  2.41it/s, train/loss=2.630]\nEpoch 0: |          | 705/? [04:51<00:00,  2.42it/s, train/loss=2.630]\nEpoch 0: |          | 705/? [04:51<00:00,  2.42it/s, train/loss=3.910]\nEpoch 0: |          | 706/? [04:52<00:00,  2.42it/s, train/loss=3.910]\nEpoch 0: |          | 706/? [04:52<00:00,  2.42it/s, train/loss=2.230]\nEpoch 0: |          | 707/? [04:52<00:00,  2.42it/s, train/loss=2.230]\nEpoch 0: |          | 707/? [04:52<00:00,  2.42it/s, train/loss=3.910]\nEpoch 0: |          | 708/? [04:52<00:00,  2.42it/s, train/loss=3.910]\nEpoch 0: |          | 708/? [04:52<00:00,  2.42it/s, train/loss=1.250]\nEpoch 0: |          | 709/? [04:52<00:00,  2.42it/s, train/loss=1.250]\nEpoch 0: |          | 709/? [04:52<00:00,  2.42it/s, train/loss=3.920]\nEpoch 0: |          | 710/? [04:53<00:00,  2.42it/s, train/loss=3.920]\nEpoch 0: |          | 710/? [04:53<00:00,  2.42it/s, train/loss=4.350]\nEpoch 0: |          | 711/? [04:54<00:00,  2.42it/s, train/loss=4.350]\nEpoch 0: |          | 711/? [04:54<00:00,  2.42it/s, train/loss=1.360]\nEpoch 0: |          | 712/? [04:54<00:00,  2.42it/s, train/loss=1.360]\nEpoch 0: |          | 712/? [04:54<00:00,  2.42it/s, train/loss=0.907]\nEpoch 0: |          | 713/? [04:54<00:00,  2.42it/s, train/loss=0.907]\nEpoch 0: |          | 713/? [04:54<00:00,  2.42it/s, train/loss=3.970]\nEpoch 0: |          | 714/? [04:54<00:00,  2.42it/s, train/loss=3.970]\nEpoch 0: |          | 714/? [04:54<00:00,  2.42it/s, train/loss=1.470]\nEpoch 0: |          | 715/? [04:54<00:00,  2.42it/s, train/loss=1.470]\nEpoch 0: |          | 715/? [04:54<00:00,  2.42it/s, train/loss=3.970]\nEpoch 0: |          | 716/? [04:55<00:00,  2.42it/s, train/loss=3.970]\nEpoch 0: |          | 716/? [04:55<00:00,  2.42it/s, train/loss=3.030]\nEpoch 0: |          | 717/? [04:55<00:00,  2.43it/s, train/loss=3.030]\nEpoch 0: |          | 717/? [04:55<00:00,  2.43it/s, train/loss=3.970]\nEpoch 0: |          | 718/? [04:55<00:00,  2.43it/s, train/loss=3.970]\nEpoch 0: |          | 718/? [04:55<00:00,  2.43it/s, train/loss=3.100]\nEpoch 0: |          | 719/? [04:55<00:00,  2.43it/s, train/loss=3.100]\nEpoch 0: |          | 719/? [04:55<00:00,  2.43it/s, train/loss=3.960]\nEpoch 0: |          | 720/? [04:56<00:00,  2.43it/s, train/loss=3.960]\nEpoch 0: |          | 720/? [04:56<00:00,  2.43it/s, train/loss=0.764]\nEpoch 0: |          | 721/? [04:57<00:00,  2.43it/s, train/loss=0.764]\nEpoch 0: |          | 721/? [04:57<00:00,  2.43it/s, train/loss=1.450]\nEpoch 0: |          | 722/? [04:57<00:00,  2.43it/s, train/loss=1.450]\nEpoch 0: |          | 722/? [04:57<00:00,  2.43it/s, train/loss=0.801]\nEpoch 0: |          | 723/? [04:57<00:00,  2.43it/s, train/loss=0.801]\nEpoch 0: |          | 723/? [04:57<00:00,  2.43it/s, train/loss=3.990]\nEpoch 0: |          | 724/? [04:58<00:00,  2.43it/s, train/loss=3.990]\nEpoch 0: |          | 724/? [04:58<00:00,  2.43it/s, train/loss=4.620]\nEpoch 0: |          | 725/? [04:58<00:00,  2.43it/s, train/loss=4.620]\nEpoch 0: |          | 725/? [04:58<00:00,  2.43it/s, train/loss=3.990]\nEpoch 0: |          | 726/? [04:58<00:00,  2.43it/s, train/loss=3.990]\nEpoch 0: |          | 726/? [04:58<00:00,  2.43it/s, train/loss=2.560]\nEpoch 0: |          | 727/? [04:58<00:00,  2.43it/s, train/loss=2.560]\nEpoch 0: |          | 727/? [04:58<00:00,  2.43it/s, train/loss=3.970]\nEpoch 0: |          | 728/? [04:58<00:00,  2.44it/s, train/loss=3.970]\nEpoch 0: |          | 728/? [04:58<00:00,  2.44it/s, train/loss=2.670]\nEpoch 0: |          | 729/? [04:59<00:00,  2.44it/s, train/loss=2.670]\nEpoch 0: |          | 729/? [04:59<00:00,  2.44it/s, train/loss=3.950]\nEpoch 0: |          | 730/? [04:59<00:00,  2.44it/s, train/loss=3.950]\nEpoch 0: |          | 730/? [04:59<00:00,  2.44it/s, train/loss=1.660]\nEpoch 0: |          | 731/? [05:00<00:00,  2.43it/s, train/loss=1.660]\nEpoch 0: |          | 731/? [05:00<00:00,  2.43it/s, train/loss=0.466]\nEpoch 0: |          | 732/? [05:00<00:00,  2.43it/s, train/loss=0.466]\nEpoch 0: |          | 732/? [05:00<00:00,  2.43it/s, train/loss=1.160]\nEpoch 0: |          | 733/? [05:00<00:00,  2.44it/s, train/loss=1.160]\nEpoch 0: |          | 733/? [05:00<00:00,  2.44it/s, train/loss=3.940]\nEpoch 0: |          | 734/? [05:01<00:00,  2.44it/s, train/loss=3.940]\nEpoch 0: |          | 734/? [05:01<00:00,  2.44it/s, train/loss=1.240]\nEpoch 0: |          | 735/? [05:01<00:00,  2.44it/s, train/loss=1.240]\nEpoch 0: |          | 735/? [05:01<00:00,  2.44it/s, train/loss=3.910]\nEpoch 0: |          | 736/? [05:01<00:00,  2.44it/s, train/loss=3.910]\nEpoch 0: |          | 736/? [05:01<00:00,  2.44it/s, train/loss=1.670]\nEpoch 0: |          | 737/? [05:01<00:00,  2.44it/s, train/loss=1.670]\nEpoch 0: |          | 737/? [05:01<00:00,  2.44it/s, train/loss=3.890]\nEpoch 0: |          | 738/? [05:02<00:00,  2.44it/s, train/loss=3.890]\nEpoch 0: |          | 738/? [05:02<00:00,  2.44it/s, train/loss=3.870]\nEpoch 0: |          | 739/? [05:02<00:00,  2.44it/s, train/loss=3.870]\nEpoch 0: |          | 739/? [05:02<00:00,  2.44it/s, train/loss=3.870]\nEpoch 0: |          | 740/? [05:02<00:00,  2.44it/s, train/loss=3.870]\nEpoch 0: |          | 740/? [05:02<00:00,  2.44it/s, train/loss=2.820]\nEpoch 0: |          | 741/? [05:03<00:00,  2.44it/s, train/loss=2.820]\nEpoch 0: |          | 741/? [05:03<00:00,  2.44it/s, train/loss=1.030]\nEpoch 0: |          | 742/? [05:03<00:00,  2.44it/s, train/loss=1.030]\nEpoch 0: |          | 742/? [05:03<00:00,  2.44it/s, train/loss=4.110]\nEpoch 0: |          | 743/? [05:04<00:00,  2.44it/s, train/loss=4.110]\nEpoch 0: |          | 743/? [05:04<00:00,  2.44it/s, train/loss=3.850]\nEpoch 0: |          | 744/? [05:04<00:00,  2.44it/s, train/loss=3.850]\nEpoch 0: |          | 744/? [05:04<00:00,  2.44it/s, train/loss=3.620]\nEpoch 0: |          | 745/? [05:04<00:00,  2.45it/s, train/loss=3.620]\nEpoch 0: |          | 745/? [05:04<00:00,  2.45it/s, train/loss=3.840]\nEpoch 0: |          | 746/? [05:04<00:00,  2.45it/s, train/loss=3.840]\nEpoch 0: |          | 746/? [05:04<00:00,  2.45it/s, train/loss=4.150]\nEpoch 0: |          | 747/? [05:04<00:00,  2.45it/s, train/loss=4.150]\nEpoch 0: |          | 747/? [05:04<00:00,  2.45it/s, train/loss=3.830]\nEpoch 0: |          | 748/? [05:05<00:00,  2.45it/s, train/loss=3.830]\nEpoch 0: |          | 748/? [05:05<00:00,  2.45it/s, train/loss=2.550]\nEpoch 0: |          | 749/? [05:05<00:00,  2.45it/s, train/loss=2.550]\nEpoch 0: |          | 749/? [05:05<00:00,  2.45it/s, train/loss=3.820]\nEpoch 0: |          | 750/? [05:05<00:00,  2.45it/s, train/loss=3.820]\nEpoch 0: |          | 750/? [05:05<00:00,  2.45it/s, train/loss=3.150]\nEpoch 0: |          | 751/? [05:06<00:00,  2.45it/s, train/loss=3.150]\nEpoch 0: |          | 751/? [05:06<00:00,  2.45it/s, train/loss=1.720]\nEpoch 0: |          | 752/? [05:07<00:00,  2.45it/s, train/loss=1.720]\nEpoch 0: |          | 752/? [05:07<00:00,  2.45it/s, train/loss=1.990]\nEpoch 0: |          | 753/? [05:07<00:00,  2.45it/s, train/loss=1.990]\nEpoch 0: |          | 753/? [05:07<00:00,  2.45it/s, train/loss=3.870]\nEpoch 0: |          | 754/? [05:07<00:00,  2.45it/s, train/loss=3.870]\nEpoch 0: |          | 754/? [05:07<00:00,  2.45it/s, train/loss=1.640]\nEpoch 0: |          | 755/? [05:07<00:00,  2.45it/s, train/loss=1.640]\nEpoch 0: |          | 755/? [05:07<00:00,  2.45it/s, train/loss=3.870]\nEpoch 0: |          | 756/? [05:07<00:00,  2.45it/s, train/loss=3.870]\nEpoch 0: |          | 756/? [05:07<00:00,  2.45it/s, train/loss=1.770]\nEpoch 0: |          | 757/? [05:08<00:00,  2.46it/s, train/loss=1.770]\nEpoch 0: |          | 757/? [05:08<00:00,  2.46it/s, train/loss=3.860]\nEpoch 0: |          | 758/? [05:08<00:00,  2.46it/s, train/loss=3.860]\nEpoch 0: |          | 758/? [05:08<00:00,  2.46it/s, train/loss=0.981]\nEpoch 0: |          | 759/? [05:08<00:00,  2.46it/s, train/loss=0.981]\nEpoch 0: |          | 759/? [05:08<00:00,  2.46it/s, train/loss=3.860]\nEpoch 0: |          | 760/? [05:08<00:00,  2.46it/s, train/loss=3.860]\nEpoch 0: |          | 760/? [05:08<00:00,  2.46it/s, train/loss=0.939]\nEpoch 0: |          | 761/? [05:09<00:00,  2.46it/s, train/loss=0.939]\nEpoch 0: |          | 761/? [05:09<00:00,  2.46it/s, train/loss=0.714]\nEpoch 0: |          | 762/? [05:10<00:00,  2.46it/s, train/loss=0.714]\nEpoch 0: |          | 762/? [05:10<00:00,  2.46it/s, train/loss=1.130]\nEpoch 0: |          | 763/? [05:10<00:00,  2.46it/s, train/loss=1.130]\nEpoch 0: |          | 763/? [05:10<00:00,  2.46it/s, train/loss=3.880]\nEpoch 0: |          | 764/? [05:10<00:00,  2.46it/s, train/loss=3.880]\nEpoch 0: |          | 764/? [05:10<00:00,  2.46it/s, train/loss=0.977]\nEpoch 0: |          | 765/? [05:10<00:00,  2.46it/s, train/loss=0.977]\nEpoch 0: |          | 765/? [05:10<00:00,  2.46it/s, train/loss=3.870]\nEpoch 0: |          | 766/? [05:11<00:00,  2.46it/s, train/loss=3.870]\nEpoch 0: |          | 766/? [05:11<00:00,  2.46it/s, train/loss=0.962]\nEpoch 0: |          | 767/? [05:11<00:00,  2.47it/s, train/loss=0.962]\nEpoch 0: |          | 767/? [05:11<00:00,  2.47it/s, train/loss=3.830]\nEpoch 0: |          | 768/? [05:11<00:00,  2.47it/s, train/loss=3.830]\nEpoch 0: |          | 768/? [05:11<00:00,  2.47it/s, train/loss=1.210]\nEpoch 0: |          | 769/? [05:11<00:00,  2.47it/s, train/loss=1.210]\nEpoch 0: |          | 769/? [05:11<00:00,  2.47it/s, train/loss=3.820]\nEpoch 0: |          | 770/? [05:11<00:00,  2.47it/s, train/loss=3.820]\nEpoch 0: |          | 770/? [05:11<00:00,  2.47it/s, train/loss=3.870]\nEpoch 0: |          | 771/? [05:12<00:00,  2.46it/s, train/loss=3.870]\nEpoch 0: |          | 771/? [05:12<00:00,  2.46it/s, train/loss=1.360]\nEpoch 0: |          | 772/? [05:13<00:00,  2.47it/s, train/loss=1.360]\nEpoch 0: |          | 772/? [05:13<00:00,  2.46it/s, train/loss=3.670]\nEpoch 0: |          | 773/? [05:13<00:00,  2.47it/s, train/loss=3.670]\nEpoch 0: |          | 773/? [05:13<00:00,  2.47it/s, train/loss=3.870]\nEpoch 0: |          | 774/? [05:13<00:00,  2.47it/s, train/loss=3.870]\nEpoch 0: |          | 774/? [05:13<00:00,  2.47it/s, train/loss=3.310]\nEpoch 0: |          | 775/? [05:13<00:00,  2.47it/s, train/loss=3.310]\nEpoch 0: |          | 775/? [05:13<00:00,  2.47it/s, train/loss=3.890]\nEpoch 0: |          | 776/? [05:14<00:00,  2.47it/s, train/loss=3.890]\nEpoch 0: |          | 776/? [05:14<00:00,  2.47it/s, train/loss=2.750]\nEpoch 0: |          | 777/? [05:14<00:00,  2.47it/s, train/loss=2.750]\nEpoch 0: |          | 777/? [05:14<00:00,  2.47it/s, train/loss=3.880]\nEpoch 0: |          | 778/? [05:14<00:00,  2.47it/s, train/loss=3.880]\nEpoch 0: |          | 778/? [05:14<00:00,  2.47it/s, train/loss=2.020]\nEpoch 0: |          | 779/? [05:14<00:00,  2.48it/s, train/loss=2.020]\nEpoch 0: |          | 779/? [05:14<00:00,  2.48it/s, train/loss=3.880]\nEpoch 0: |          | 780/? [05:15<00:00,  2.48it/s, train/loss=3.880]\nEpoch 0: |          | 780/? [05:15<00:00,  2.48it/s, train/loss=2.680]\nEpoch 0: |          | 781/? [05:15<00:00,  2.47it/s, train/loss=2.680]\nEpoch 0: |          | 781/? [05:15<00:00,  2.47it/s, train/loss=0.906]\nEpoch 0: |          | 782/? [05:16<00:00,  2.47it/s, train/loss=0.906]\nEpoch 0: |          | 782/? [05:16<00:00,  2.47it/s, train/loss=0.567]\nEpoch 0: |          | 783/? [05:16<00:00,  2.48it/s, train/loss=0.567]\nEpoch 0: |          | 783/? [05:16<00:00,  2.48it/s, train/loss=3.910]\nEpoch 0: |          | 784/? [05:16<00:00,  2.48it/s, train/loss=3.910]\nEpoch 0: |          | 784/? [05:16<00:00,  2.48it/s, train/loss=1.590]\nEpoch 0: |          | 785/? [05:16<00:00,  2.48it/s, train/loss=1.590]\nEpoch 0: |          | 785/? [05:16<00:00,  2.48it/s, train/loss=3.900]\nEpoch 0: |          | 786/? [05:17<00:00,  2.48it/s, train/loss=3.900]\nEpoch 0: |          | 786/? [05:17<00:00,  2.48it/s, train/loss=2.630]\nEpoch 0: |          | 787/? [05:17<00:00,  2.48it/s, train/loss=2.630]\nEpoch 0: |          | 787/? [05:17<00:00,  2.48it/s, train/loss=3.870]\nEpoch 0: |          | 788/? [05:17<00:00,  2.48it/s, train/loss=3.870]\nEpoch 0: |          | 788/? [05:17<00:00,  2.48it/s, train/loss=0.732]\nEpoch 0: |          | 789/? [05:17<00:00,  2.48it/s, train/loss=0.732]\nEpoch 0: |          | 789/? [05:17<00:00,  2.48it/s, train/loss=3.840]\nEpoch 0: |          | 790/? [05:18<00:00,  2.48it/s, train/loss=3.840]\nEpoch 0: |          | 790/? [05:18<00:00,  2.48it/s, train/loss=3.090]\nEpoch 0: |          | 791/? [05:19<00:00,  2.48it/s, train/loss=3.090]\nEpoch 0: |          | 791/? [05:19<00:00,  2.48it/s, train/loss=1.140]\nEpoch 0: |          | 792/? [05:19<00:00,  2.48it/s, train/loss=1.140]\nEpoch 0: |          | 792/? [05:19<00:00,  2.48it/s, train/loss=1.070]\nEpoch 0: |          | 793/? [05:19<00:00,  2.48it/s, train/loss=1.070]\nEpoch 0: |          | 793/? [05:19<00:00,  2.48it/s, train/loss=3.830]\nEpoch 0: |          | 794/? [05:19<00:00,  2.48it/s, train/loss=3.830]\nEpoch 0: |          | 794/? [05:19<00:00,  2.48it/s, train/loss=4.230]\nEpoch 0: |          | 795/? [05:19<00:00,  2.48it/s, train/loss=4.230]\nEpoch 0: |          | 795/? [05:19<00:00,  2.48it/s, train/loss=3.810]\nEpoch 0: |          | 796/? [05:20<00:00,  2.48it/s, train/loss=3.810]\nEpoch 0: |          | 796/? [05:20<00:00,  2.48it/s, train/loss=3.320]\nEpoch 0: |          | 797/? [05:20<00:00,  2.49it/s, train/loss=3.320]\nEpoch 0: |          | 797/? [05:20<00:00,  2.49it/s, train/loss=3.790]\nEpoch 0: |          | 798/? [05:20<00:00,  2.49it/s, train/loss=3.790]\nEpoch 0: |          | 798/? [05:20<00:00,  2.49it/s, train/loss=3.670]\nEpoch 0: |          | 799/? [05:20<00:00,  2.49it/s, train/loss=3.670]\nEpoch 0: |          | 799/? [05:20<00:00,  2.49it/s, train/loss=3.800]\nEpoch 0: |          | 800/? [05:21<00:00,  2.49it/s, train/loss=3.800]\nEpoch 0: |          | 800/? [05:21<00:00,  2.49it/s, train/loss=1.040]\nValidation: |          | 0/? [00:00<?, ?it/s]\u001b[A\nValidation:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   0%|          | 0/40 [00:00<?, ?it/s]\u001b[A\nValidation DataLoader 0:   2%|▎         | 1/40 [00:00<00:04,  8.90it/s]\u001b[A\nValidation DataLoader 0:   5%|▌         | 2/40 [00:00<00:04,  8.71it/s]\u001b[A\nValidation DataLoader 0:   8%|▊         | 3/40 [00:00<00:04,  8.12it/s]\u001b[A\nValidation DataLoader 0:  10%|█         | 4/40 [00:00<00:04,  8.12it/s]\u001b[A\nValidation DataLoader 0:  12%|█▎        | 5/40 [00:00<00:04,  8.32it/s]\u001b[A\nValidation DataLoader 0:  15%|█▌        | 6/40 [00:00<00:04,  8.34it/s]\u001b[A\nValidation DataLoader 0:  18%|█▊        | 7/40 [00:00<00:03,  8.46it/s]\u001b[A\nValidation DataLoader 0:  20%|██        | 8/40 [00:00<00:03,  8.52it/s]\u001b[A\nValidation DataLoader 0:  22%|██▎       | 9/40 [00:01<00:03,  8.57it/s]\u001b[A\nValidation DataLoader 0:  25%|██▌       | 10/40 [00:01<00:03,  8.66it/s]\u001b[A\nValidation DataLoader 0:  28%|██▊       | 11/40 [00:01<00:03,  8.64it/s]\u001b[A\nValidation DataLoader 0:  30%|███       | 12/40 [00:01<00:03,  8.72it/s]\u001b[A\nValidation DataLoader 0:  32%|███▎      | 13/40 [00:01<00:03,  8.78it/s]\u001b[A\nValidation DataLoader 0:  35%|███▌      | 14/40 [00:01<00:02,  8.81it/s]\u001b[A\nValidation DataLoader 0:  38%|███▊      | 15/40 [00:01<00:02,  8.83it/s]\u001b[A\nValidation DataLoader 0:  40%|████      | 16/40 [00:01<00:02,  8.85it/s]\u001b[A\nValidation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:02,  8.88it/s]\u001b[A\nValidation DataLoader 0:  45%|████▌     | 18/40 [00:02<00:02,  8.90it/s]\u001b[A\nValidation DataLoader 0:  48%|████▊     | 19/40 [00:02<00:02,  8.92it/s]\u001b[A\nValidation DataLoader 0:  50%|█████     | 20/40 [00:02<00:02,  8.94it/s]\u001b[A\nValidation DataLoader 0:  52%|█████▎    | 21/40 [00:02<00:02,  8.93it/s]\u001b[A\nValidation DataLoader 0:  55%|█████▌    | 22/40 [00:02<00:02,  8.95it/s]\u001b[A\nValidation DataLoader 0:  57%|█████▊    | 23/40 [00:02<00:01,  8.95it/s]\u001b[A\nValidation DataLoader 0:  60%|██████    | 24/40 [00:02<00:01,  8.97it/s]\u001b[A\nValidation DataLoader 0:  62%|██████▎   | 25/40 [00:02<00:01,  8.99it/s]\u001b[A\nValidation DataLoader 0:  65%|██████▌   | 26/40 [00:02<00:01,  8.99it/s]\u001b[A\nValidation DataLoader 0:  68%|██████▊   | 27/40 [00:02<00:01,  9.01it/s]\u001b[A\nValidation DataLoader 0:  70%|███████   | 28/40 [00:03<00:01,  9.03it/s]\u001b[A\nValidation DataLoader 0:  72%|███████▎  | 29/40 [00:03<00:01,  9.06it/s]\u001b[A\nValidation DataLoader 0:  75%|███████▌  | 30/40 [00:03<00:01,  9.08it/s]\u001b[A\nValidation DataLoader 0:  78%|███████▊  | 31/40 [00:03<00:00,  9.09it/s]\u001b[A\nValidation DataLoader 0:  80%|████████  | 32/40 [00:03<00:00,  9.11it/s]\u001b[A\nValidation DataLoader 0:  82%|████████▎ | 33/40 [00:03<00:00,  9.10it/s]\u001b[A\nValidation DataLoader 0:  85%|████████▌ | 34/40 [00:03<00:00,  9.10it/s]\u001b[A\nValidation DataLoader 0:  88%|████████▊ | 35/40 [00:03<00:00,  9.09it/s]\u001b[A\nValidation DataLoader 0:  90%|█████████ | 36/40 [00:03<00:00,  9.08it/s]\u001b[A\nValidation DataLoader 0:  92%|█████████▎| 37/40 [00:04<00:00,  9.07it/s]\u001b[A\nValidation DataLoader 0:  95%|█████████▌| 38/40 [00:04<00:00,  9.07it/s]\u001b[A\nValidation DataLoader 0:  98%|█████████▊| 39/40 [00:04<00:00,  9.07it/s]\u001b[A\nValidation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00,  9.06it/s]\u001b[A\n\u001b[A\nEpoch 0: |          | 800/? [05:57<00:00,  2.24it/s, train/loss=1.040]\n`Trainer.fit` stopped: `max_steps=800` reached.\nEpoch 0: |          | 800/? [05:57<00:00,  2.24it/s, train/loss=1.040]\nEpoch 0: |          | 800/? [05:57<00:00,  2.24it/s, train/loss=1.040]\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\nTesting: |          | 0/? 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outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save\nRunning step 5: Exporting meshes\n{'name': 'dreamcraft3d-texture', 'description': '', 'tag': 'replicate_user', 'seed': 0, 'use_timestamp': True, 'timestamp': '@20240222-135357', 'exp_root_dir': 'outputs', 'exp_dir': 'outputs/dreamcraft3d-texture', 'trial_name': 'replicate_user@20240222-135357', 'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357', 'n_gpus': 1, 'resume': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt', 'data_type': 'dreamcraft3d-single-image-datamodule', 'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}}, 'system_type': 'dreamcraft3d-system', 'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt', 'exporter_type': 'mesh-exporter', 'exporter': {'context_type': 'cuda'}}, 'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0}, 'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800}}\nLoading Stable Diffusion ...\nLoading pipeline components...:   0%|          | 0/4 [00:00<?, ?it/s]\nLoading pipeline components...:  25%|██▌       | 1/4 [00:01<00:04,  1.37s/it]\nLoading pipeline components...:  50%|█████     | 2/4 [00:01<00:01,  1.58it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  2.57it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  2.03it/s]\nLoading pipeline components...:   0%|          | 0/4 [00:00<?, ?it/s]\nLoading pipeline components...:  25%|██▌       | 1/4 [00:00<00:02,  1.05it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  3.13it/s]\nLoading pipeline components...: 100%|██████████| 4/4 [00:01<00:00,  2.72it/s]\nLoaded Stable Diffusion!\nLoading Stable Zero123 ...\nget obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion\nLatentDiffusion: Running in eps-prediction mode\nDiffusionWrapper has 859.53 M params.\nKeeping EMAs of 688.\nmaking attention of type 'vanilla' with 512 in_channels\nWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.\nmaking attention of type 'vanilla' with 512 in_channels\nLoaded Stable Zero123!\nUsing prompt [A green leafy plant in a striped terracotta pot] and negative prompt []\nUsing view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]\nloaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\nMissing logger folder: /src/lightning_logs\n[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])\nRestoring states from the checkpoint path at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt\nLOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\nLoaded model weights from the checkpoint at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'predict_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.\nPredicting: |          | 0/? 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[00:00<00:00, 133.18it/s]\nPredicting DataLoader 0:  96%|█████████▌| 115/120 [00:00<00:00, 133.22it/s]\nPredicting DataLoader 0:  97%|█████████▋| 116/120 [00:00<00:00, 133.28it/s]\nPredicting DataLoader 0:  98%|█████████▊| 117/120 [00:00<00:00, 133.36it/s]\nPredicting DataLoader 0:  98%|█████████▊| 118/120 [00:00<00:00, 133.44it/s]\nPredicting DataLoader 0:  99%|█████████▉| 119/120 [00:00<00:00, 133.47it/s]\nUsing xatlas to perform UV unwrapping, may take a while ...\nExporting textures ...\nPerform UV padding on texture maps to avoid seams, may take a while ...\nPredicting DataLoader 0: 100%|██████████| 120/120 [00:00<00:00, 133.53it/s]\nPredicting DataLoader 0: 100%|██████████| 120/120 [01:06<00:00,  1.81it/s]\nExport assets saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save",
  "metrics": {
    "predict_time": 1345.14856,
    "total_time": 1684.596898
  },
  "output": "https://replicate.delivery/pbxt/eJtMWubDJQyRf04ohkteeHIlkfe1TIGObHsMlWKQQnBRBGUmE/mesh.zip",
  "started_at": "2024-02-22T13:40:22.441105Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/6zgbl6lbf3ftxjuaawjwu7ak4a",
    "cancel": "https://api.replicate.com/v1/predictions/6zgbl6lbf3ftxjuaawjwu7ak4a/cancel"
  },
  "version": "cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30"
}

Generated in

22 minutes 25 seconds

Tweak it ShareReport

Using seed 3731177029
Seed set to 3731177029
Preprocessing image...
[INFO] background removal...
2024-02-22 13:40:23.104407995 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1831, index: 1, mask: {1, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.104414275 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1830, index: 0, mask: {48, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.104502865 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1832, index: 2, mask: {49, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.104535295 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1833, index: 3, mask: {2, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.104613524 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1834, index: 4, mask: {50, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.107023935 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1841, index: 11, mask: {6, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.107094724 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1842, index: 12, mask: {54, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.107029744 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1908, index: 78, mask: {87, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.107404823 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1844, index: 14, mask: {55, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.119497582 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1843, index: 13, mask: {7, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.107393863 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1914, index: 84, mask: {90, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.123661054 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1911, index: 81, mask: {41, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.123722614 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1909, index: 79, mask: {40, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.123701134 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1910, index: 80, mask: {88, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.127291970 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1916, index: 86, mask: {91, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.127624198 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1915, index: 85, mask: {43, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.130148067 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1912, index: 82, mask: {89, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.131521142 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1835, index: 5, mask: {3, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135786034 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1902, index: 72, mask: {84, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.142269357 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1836, index: 6, mask: {51, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.147488775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1919, index: 89, mask: {45, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.151492068 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1920, index: 90, mask: {93, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.151515108 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1845, index: 15, mask: {8, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.152578874 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1921, index: 91, mask: {46, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.155036124 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1922, index: 92, mask: {94, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.159492425 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1923, index: 93, mask: {47, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.159619344 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1847, index: 17, mask: {9, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.163491428 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1924, index: 94, mask: {95, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.167512541 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1848, index: 18, mask: {57, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.175204479 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1918, index: 88, mask: {92, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.175514908 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1849, index: 19, mask: {10, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.183547044 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1850, index: 20, mask: {58, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203673140 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1865, index: 35, mask: {18, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203714850 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1867, index: 37, mask: {19, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203730010 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1868, index: 38, mask: {67, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208804658 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1880, index: 50, mask: {73, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208933648 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1892, index: 62, mask: {79, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.211571717 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1896, index: 66, mask: {81, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.218757077 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1898, index: 68, mask: {82, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.219530623 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1899, index: 69, mask: {35, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.159503775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1846, index: 16, mask: {56, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208690009 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1872, index: 42, mask: {69, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135794754 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1903, index: 73, mask: {37, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208878768 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1887, index: 57, mask: {29, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208739099 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1876, index: 46, mask: {71, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135799404 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1904, index: 74, mask: {85, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208820138 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1882, index: 52, mask: {74, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208661999 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1871, index: 41, mask: {21, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.211522277 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1894, index: 64, mask: {80, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.211549267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1895, index: 65, mask: {33, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208761849 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1877, index: 47, mask: {24, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135804604 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1905, index: 75, mask: {38, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203705640 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1866, index: 36, mask: {66, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.211499897 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1893, index: 63, mask: {32, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135809804 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1906, index: 76, mask: {86, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208906798 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1889, index: 59, mask: {30, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208719959 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1874, index: 44, mask: {70, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.135814794 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1907, index: 77, mask: {39, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.208775729 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1879, index: 49, mask: {25, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203510801 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1855, index: 25, mask: {13, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203596991 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1917, index: 87, mask: {44, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.191524490 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1854, index: 24, mask: {60, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.203625340 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1862, index: 32, mask: {64, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.255050885 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1856, index: 26, mask: {61, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.226268595 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1853, index: 23, mask: {12, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.226295085 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1883, index: 53, mask: {27, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231529973 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1869, index: 39, mask: {20, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.235482157 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1864, index: 34, mask: {65, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.239481860 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1897, index: 67, mask: {34, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.247489267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1913, index: 83, mask: {42, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231551533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1878, index: 48, mask: {72, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.235490787 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1888, index: 58, mask: {77, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.235501267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1891, index: 61, mask: {31, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231560853 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1884, index: 54, mask: {75, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.235479747 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1885, index: 55, mask: {28, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.226300705 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1873, index: 43, mask: {22, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.226262175 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1863, index: 33, mask: {17, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231541763 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1875, index: 45, mask: {23, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231485533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1886, index: 56, mask: {76, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.231574443 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1890, index: 60, mask: {78, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.226293125 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1870, index: 40, mask: {68, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.255088475 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1881, index: 51, mask: {26, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.255135895 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1837, index: 7, mask: {4, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.287495189 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1901, index: 71, mask: {36, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
2024-02-22 13:40:23.295484056 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1900, index: 70, mask: {83, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.
[INFO] depth estimation...
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/timm/models/_factory.py:117: UserWarning: Mapping deprecated model name vit_base_resnet50_384 to current vit_base_r50_s16_384.orig_in21k_ft_in1k.
model = create_fn(
[INFO] normal estimation...
Running step 1: NeRF
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': [64, 128], 'width': [64, 128], 'resolution_milestones': [3000], 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': [64, 128], 'width': [64, 128], 'batch_size': [1, 1], 'resolution_milestones': [3000], 'eval_height': 128, 'eval_width': 128, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 200, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-coarse-nerf',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-coarse-nerf',
'resume': None,
'seed': 0,
'system': {'stage': 'coarse', 'geometry_type': 'implicit-volume', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'density_bias': 'blob_magic3d', 'density_activation': 'softplus', 'density_blob_scale': 10.0, 'density_blob_std': 0.5, 'pos_encoding_config': {'otype': 'ProgressiveBandHashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'nerf-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'return_normal_perturb': True, 'return_comp_normal': True}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 1.0, 'lambda_3d_normal_smooth': [1000, 5.0, 1.0, 1001], 'lambda_orient': [1000, 1.0, 10.0, 1001], 'lambda_sparsity': [1000, 0.1, 10.0, 1001], 'lambda_opaque': [1000, 0.1, 10.0, 1001], 'lambda_clip': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.01, 'betas': [0.9, 0.99], 'eps': 1e-08}}},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134035',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},
'trial_dir': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035',
'trial_name': 'replicate_user@20240222-134035',
'use_timestamp': True}
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74ed3-77c3833b6edb1358569cd2db;c0fe2e5f-e2c0-465b-af4c-23a1c171d42e)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]
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Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
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Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
Using 16bit Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
You are using a CUDA device ('NVIDIA A40') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name       | Type                 | Params
----------------------------------------------------
0 | geometry   | ImplicitVolume       | 12.6 M
1 | material   | NoMaterial           | 0
2 | background | SolidColorBackground | 0
3 | renderer   | NeRFVolumeRenderer   | 0
----------------------------------------------------
12.6 M    Trainable params
0         Non-trainable params
12.6 M    Total params
50.417    Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
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Epoch 0: |          | 32/? [00:06<00:00,  5.05it/s, train/loss=16.20]
Epoch 0: |          | 32/? [00:06<00:00,  5.05it/s, train/loss=41.90]
Epoch 0: |          | 33/? [00:06<00:00,  5.17it/s, train/loss=41.90]
Epoch 0: |          | 33/? [00:06<00:00,  5.17it/s, train/loss=15.50]
Epoch 0: |          | 34/? [00:06<00:00,  5.08it/s, train/loss=15.50]
Epoch 0: |          | 34/? [00:06<00:00,  5.08it/s, train/loss=47.50]
Epoch 0: |          | 35/? [00:06<00:00,  5.19it/s, train/loss=47.50]
Epoch 0: |          | 35/? [00:06<00:00,  5.18it/s, train/loss=14.20]
Epoch 0: |          | 36/? [00:07<00:00,  5.08it/s, train/loss=14.20]
Epoch 0: |          | 36/? [00:07<00:00,  5.08it/s, train/loss=41.60]
Epoch 0: |          | 37/? [00:07<00:00,  5.19it/s, train/loss=41.60]
Epoch 0: |          | 37/? [00:07<00:00,  5.19it/s, train/loss=12.90]
Epoch 0: |          | 38/? [00:07<00:00,  5.11it/s, train/loss=12.90]
Epoch 0: |          | 38/? [00:07<00:00,  5.11it/s, train/loss=50.40]
Epoch 0: |          | 39/? [00:07<00:00,  5.21it/s, train/loss=50.40]
Epoch 0: |          | 39/? [00:07<00:00,  5.21it/s, train/loss=11.80]
Epoch 0: |          | 40/? [00:07<00:00,  5.13it/s, train/loss=11.80]
Epoch 0: |          | 40/? [00:07<00:00,  5.13it/s, train/loss=82.60]
Epoch 0: |          | 41/? [00:07<00:00,  5.23it/s, train/loss=82.60]
Epoch 0: |          | 41/? [00:07<00:00,  5.23it/s, train/loss=10.90]
Epoch 0: |          | 42/? [00:08<00:00,  5.15it/s, train/loss=10.90]
Epoch 0: |          | 42/? [00:08<00:00,  5.15it/s, train/loss=63.40]
Epoch 0: |          | 43/? [00:08<00:00,  5.24it/s, train/loss=63.40]
Epoch 0: |          | 43/? [00:08<00:00,  5.24it/s, train/loss=10.30]
Epoch 0: |          | 44/? [00:08<00:00,  5.17it/s, train/loss=10.30]
Epoch 0: |          | 44/? [00:08<00:00,  5.17it/s, train/loss=70.20]
Epoch 0: |          | 45/? [00:08<00:00,  5.26it/s, train/loss=70.20]
Epoch 0: |          | 45/? [00:08<00:00,  5.26it/s, train/loss=10.00]
Epoch 0: |          | 46/? [00:08<00:00,  5.19it/s, train/loss=10.00]
Epoch 0: |          | 46/? [00:08<00:00,  5.19it/s, train/loss=60.70]
Epoch 0: |          | 47/? [00:08<00:00,  5.28it/s, train/loss=60.70]
Epoch 0: |          | 47/? [00:08<00:00,  5.28it/s, train/loss=9.830]
Epoch 0: |          | 48/? [00:09<00:00,  5.21it/s, train/loss=9.830]
Epoch 0: |          | 48/? [00:09<00:00,  5.21it/s, train/loss=61.30]
Epoch 0: |          | 49/? [00:09<00:00,  5.29it/s, train/loss=61.30]
Epoch 0: |          | 49/? [00:09<00:00,  5.29it/s, train/loss=9.610]
Epoch 0: |          | 50/? [00:09<00:00,  5.23it/s, train/loss=9.610]
Epoch 0: |          | 50/? [00:09<00:00,  5.23it/s, train/loss=61.80]
Epoch 0: |          | 51/? [00:09<00:00,  5.30it/s, train/loss=61.80]
Epoch 0: |          | 51/? [00:09<00:00,  5.30it/s, train/loss=9.420]
Epoch 0: |          | 52/? [00:09<00:00,  5.24it/s, train/loss=9.420]
Epoch 0: |          | 52/? [00:09<00:00,  5.24it/s, train/loss=38.50]
Epoch 0: |          | 53/? [00:09<00:00,  5.32it/s, train/loss=38.50]
Epoch 0: |          | 53/? [00:09<00:00,  5.32it/s, train/loss=9.250]
Epoch 0: |          | 54/? [00:10<00:00,  5.26it/s, train/loss=9.250]
Epoch 0: |          | 54/? [00:10<00:00,  5.26it/s, train/loss=43.80]
Epoch 0: |          | 55/? [00:10<00:00,  5.33it/s, train/loss=43.80]
Epoch 0: |          | 55/? [00:10<00:00,  5.33it/s, train/loss=9.020]
Epoch 0: |          | 56/? [00:10<00:00,  5.27it/s, train/loss=9.020]
Epoch 0: |          | 56/? [00:10<00:00,  5.27it/s, train/loss=88.30]
Epoch 0: |          | 57/? [00:10<00:00,  5.34it/s, train/loss=88.30]
Epoch 0: |          | 57/? [00:10<00:00,  5.34it/s, train/loss=8.820]
Epoch 0: |          | 58/? [00:10<00:00,  5.29it/s, train/loss=8.820]
Epoch 0: |          | 58/? [00:10<00:00,  5.29it/s, train/loss=65.20]
Epoch 0: |          | 59/? [00:11<00:00,  5.35it/s, train/loss=65.20]
Epoch 0: |          | 59/? [00:11<00:00,  5.35it/s, train/loss=8.700]
Epoch 0: |          | 60/? [00:11<00:00,  5.30it/s, train/loss=8.700]
Epoch 0: |          | 60/? [00:11<00:00,  5.30it/s, train/loss=48.50]
Epoch 0: |          | 61/? [00:11<00:00,  5.36it/s, train/loss=48.50]
Epoch 0: |          | 61/? [00:11<00:00,  5.36it/s, train/loss=8.640]
Epoch 0: |          | 62/? [00:11<00:00,  5.31it/s, train/loss=8.640]
Epoch 0: |          | 62/? [00:11<00:00,  5.30it/s, train/loss=63.30]
Epoch 0: |          | 63/? [00:11<00:00,  5.37it/s, train/loss=63.30]
Epoch 0: |          | 63/? [00:11<00:00,  5.37it/s, train/loss=8.580]
Epoch 0: |          | 64/? [00:12<00:00,  5.32it/s, train/loss=8.580]
Epoch 0: |          | 64/? [00:12<00:00,  5.31it/s, train/loss=73.00]
Epoch 0: |          | 65/? [00:12<00:00,  5.37it/s, train/loss=73.00]
Epoch 0: |          | 65/? [00:12<00:00,  5.37it/s, train/loss=8.530]
Epoch 0: |          | 66/? [00:12<00:00,  5.32it/s, train/loss=8.530]
Epoch 0: |          | 66/? [00:12<00:00,  5.32it/s, train/loss=114.0]
Epoch 0: |          | 67/? [00:12<00:00,  5.38it/s, train/loss=114.0]
Epoch 0: |          | 67/? [00:12<00:00,  5.38it/s, train/loss=8.480]
Epoch 0: |          | 68/? [00:12<00:00,  5.28it/s, train/loss=8.480]
Epoch 0: |          | 68/? [00:12<00:00,  5.28it/s, train/loss=47.50]
Epoch 0: |          | 69/? [00:12<00:00,  5.34it/s, train/loss=47.50]
Epoch 0: |          | 69/? [00:12<00:00,  5.34it/s, train/loss=8.460]
Epoch 0: |          | 70/? [00:13<00:00,  5.30it/s, train/loss=8.460]
Epoch 0: |          | 70/? [00:13<00:00,  5.30it/s, train/loss=71.40]
Epoch 0: |          | 71/? [00:13<00:00,  5.36it/s, train/loss=71.40]
Epoch 0: |          | 71/? [00:13<00:00,  5.35it/s, train/loss=8.390]
Epoch 0: |          | 72/? [00:13<00:00,  5.31it/s, train/loss=8.390]
Epoch 0: |          | 72/? [00:13<00:00,  5.31it/s, train/loss=54.80]
Epoch 0: |          | 73/? [00:13<00:00,  5.37it/s, train/loss=54.80]
Epoch 0: |          | 73/? [00:13<00:00,  5.37it/s, train/loss=8.210]
Epoch 0: |          | 74/? [00:13<00:00,  5.33it/s, train/loss=8.210]
Epoch 0: |          | 74/? [00:13<00:00,  5.33it/s, train/loss=46.20]
Epoch 0: |          | 75/? [00:13<00:00,  5.38it/s, train/loss=46.20]
Epoch 0: |          | 75/? [00:13<00:00,  5.38it/s, train/loss=8.040]
Epoch 0: |          | 76/? [00:14<00:00,  5.34it/s, train/loss=8.040]
Epoch 0: |          | 76/? [00:14<00:00,  5.34it/s, train/loss=79.50]
Epoch 0: |          | 77/? [00:14<00:00,  5.39it/s, train/loss=79.50]
Epoch 0: |          | 77/? [00:14<00:00,  5.39it/s, train/loss=7.990]
Epoch 0: |          | 78/? [00:14<00:00,  5.35it/s, train/loss=7.990]
Epoch 0: |          | 78/? [00:14<00:00,  5.35it/s, train/loss=41.70]
Epoch 0: |          | 79/? [00:14<00:00,  5.40it/s, train/loss=41.70]
Epoch 0: |          | 79/? [00:14<00:00,  5.40it/s, train/loss=8.030]
Epoch 0: |          | 80/? [00:14<00:00,  5.36it/s, train/loss=8.030]
Epoch 0: |          | 80/? [00:14<00:00,  5.36it/s, train/loss=64.90]
Epoch 0: |          | 81/? [00:14<00:00,  5.41it/s, train/loss=64.90]
Epoch 0: |          | 81/? [00:14<00:00,  5.41it/s, train/loss=8.050]
Epoch 0: |          | 82/? [00:15<00:00,  5.37it/s, train/loss=8.050]
Epoch 0: |          | 82/? [00:15<00:00,  5.37it/s, train/loss=62.00]
Epoch 0: |          | 83/? [00:15<00:00,  5.42it/s, train/loss=62.00]
Epoch 0: |          | 83/? [00:15<00:00,  5.42it/s, train/loss=8.020]
Epoch 0: |          | 84/? [00:15<00:00,  5.38it/s, train/loss=8.020]
Epoch 0: |          | 84/? [00:15<00:00,  5.38it/s, train/loss=45.70]
Epoch 0: |          | 85/? [00:15<00:00,  5.43it/s, train/loss=45.70]
Epoch 0: |          | 85/? [00:15<00:00,  5.43it/s, train/loss=7.980]
Epoch 0: |          | 86/? [00:15<00:00,  5.39it/s, train/loss=7.980]
Epoch 0: |          | 86/? [00:15<00:00,  5.39it/s, train/loss=61.90]
Epoch 0: |          | 87/? [00:16<00:00,  5.44it/s, train/loss=61.90]
Epoch 0: |          | 87/? [00:16<00:00,  5.44it/s, train/loss=7.940]
Epoch 0: |          | 88/? [00:16<00:00,  5.40it/s, train/loss=7.940]
Epoch 0: |          | 88/? [00:16<00:00,  5.40it/s, train/loss=72.20]
Epoch 0: |          | 89/? [00:16<00:00,  5.45it/s, train/loss=72.20]
Epoch 0: |          | 89/? [00:16<00:00,  5.45it/s, train/loss=7.930]
Epoch 0: |          | 90/? [00:16<00:00,  5.41it/s, train/loss=7.930]
Epoch 0: |          | 90/? [00:16<00:00,  5.41it/s, train/loss=70.50]
Epoch 0: |          | 91/? [00:16<00:00,  5.45it/s, train/loss=70.50]
Epoch 0: |          | 91/? [00:16<00:00,  5.45it/s, train/loss=7.950]
Epoch 0: |          | 92/? [00:16<00:00,  5.41it/s, train/loss=7.950]
Epoch 0: |          | 92/? [00:17<00:00,  5.41it/s, train/loss=55.00]
Epoch 0: |          | 93/? [00:17<00:00,  5.45it/s, train/loss=55.00]
Epoch 0: |          | 93/? [00:17<00:00,  5.45it/s, train/loss=7.930]
Epoch 0: |          | 94/? [00:17<00:00,  5.41it/s, train/loss=7.930]
Epoch 0: |          | 94/? [00:17<00:00,  5.41it/s, train/loss=47.60]
Epoch 0: |          | 95/? [00:17<00:00,  5.45it/s, train/loss=47.60]
Epoch 0: |          | 95/? [00:17<00:00,  5.45it/s, train/loss=7.880]
Epoch 0: |          | 96/? [00:17<00:00,  5.42it/s, train/loss=7.880]
Epoch 0: |          | 96/? [00:17<00:00,  5.42it/s, train/loss=53.40]
Epoch 0: |          | 97/? [00:17<00:00,  5.46it/s, train/loss=53.40]
Epoch 0: |          | 97/? [00:17<00:00,  5.46it/s, train/loss=7.830]
Epoch 0: |          | 98/? [00:18<00:00,  5.43it/s, train/loss=7.830]
Epoch 0: |          | 98/? [00:18<00:00,  5.43it/s, train/loss=52.20]
Epoch 0: |          | 99/? [00:18<00:00,  5.47it/s, train/loss=52.20]
Epoch 0: |          | 99/? [00:18<00:00,  5.47it/s, train/loss=7.710]
Epoch 0: |          | 100/? [00:18<00:00,  5.44it/s, train/loss=7.710]
Epoch 0: |          | 100/? [00:18<00:00,  5.44it/s, train/loss=46.20]
Epoch 0: |          | 101/? [00:18<00:00,  5.48it/s, train/loss=46.20]
Epoch 0: |          | 101/? [00:18<00:00,  5.48it/s, train/loss=7.540]
Epoch 0: |          | 102/? [00:18<00:00,  5.45it/s, train/loss=7.540]
Epoch 0: |          | 102/? [00:18<00:00,  5.45it/s, train/loss=63.90]
Epoch 0: |          | 103/? [00:18<00:00,  5.49it/s, train/loss=63.90]
Epoch 0: |          | 103/? [00:18<00:00,  5.49it/s, train/loss=7.310]
Epoch 0: |          | 104/? [00:19<00:00,  5.46it/s, train/loss=7.310]
Epoch 0: |          | 104/? [00:19<00:00,  5.46it/s, train/loss=70.90]
Epoch 0: |          | 105/? [00:19<00:00,  5.49it/s, train/loss=70.90]
Epoch 0: |          | 105/? [00:19<00:00,  5.49it/s, train/loss=7.160]
Epoch 0: |          | 106/? [00:19<00:00,  5.46it/s, train/loss=7.160]
Epoch 0: |          | 106/? [00:19<00:00,  5.46it/s, train/loss=59.10]
Epoch 0: |          | 107/? [00:19<00:00,  5.50it/s, train/loss=59.10]
Epoch 0: |          | 107/? [00:19<00:00,  5.50it/s, train/loss=7.080]
Epoch 0: |          | 108/? [00:19<00:00,  5.47it/s, train/loss=7.080]
Epoch 0: |          | 108/? [00:19<00:00,  5.47it/s, train/loss=57.80]
Epoch 0: |          | 109/? [00:19<00:00,  5.51it/s, train/loss=57.80]
Epoch 0: |          | 109/? [00:19<00:00,  5.51it/s, train/loss=7.080]
Epoch 0: |          | 110/? [00:20<00:00,  5.47it/s, train/loss=7.080]
Epoch 0: |          | 110/? [00:20<00:00,  5.47it/s, train/loss=41.90]
Epoch 0: |          | 111/? [00:20<00:00,  5.51it/s, train/loss=41.90]
Epoch 0: |          | 111/? [00:20<00:00,  5.51it/s, train/loss=7.140]
Epoch 0: |          | 112/? [00:20<00:00,  5.48it/s, train/loss=7.140]
Epoch 0: |          | 112/? [00:20<00:00,  5.48it/s, train/loss=56.10]
Epoch 0: |          | 113/? [00:20<00:00,  5.52it/s, train/loss=56.10]
Epoch 0: |          | 113/? [00:20<00:00,  5.52it/s, train/loss=7.250]
Epoch 0: |          | 114/? [00:20<00:00,  5.49it/s, train/loss=7.250]
Epoch 0: |          | 114/? [00:20<00:00,  5.49it/s, train/loss=48.80]
Epoch 0: |          | 115/? [00:20<00:00,  5.53it/s, train/loss=48.80]
Epoch 0: |          | 115/? [00:20<00:00,  5.53it/s, train/loss=7.310]
Epoch 0: |          | 116/? [00:21<00:00,  5.50it/s, train/loss=7.310]
Epoch 0: |          | 116/? [00:21<00:00,  5.50it/s, train/loss=51.80]
Epoch 0: |          | 117/? [00:21<00:00,  5.54it/s, train/loss=51.80]
Epoch 0: |          | 117/? [00:21<00:00,  5.54it/s, train/loss=7.300]
Epoch 0: |          | 118/? [00:21<00:00,  5.51it/s, train/loss=7.300]
Epoch 0: |          | 118/? [00:21<00:00,  5.51it/s, train/loss=47.40]
Epoch 0: |          | 119/? [00:21<00:00,  5.54it/s, train/loss=47.40]
Epoch 0: |          | 119/? [00:21<00:00,  5.54it/s, train/loss=7.190]
Epoch 0: |          | 120/? [00:21<00:00,  5.52it/s, train/loss=7.190]
Epoch 0: |          | 120/? [00:21<00:00,  5.52it/s, train/loss=49.40]
Epoch 0: |          | 121/? [00:21<00:00,  5.55it/s, train/loss=49.40]
Epoch 0: |          | 121/? [00:21<00:00,  5.55it/s, train/loss=7.070]
Epoch 0: |          | 122/? [00:22<00:00,  5.52it/s, train/loss=7.070]
Epoch 0: |          | 122/? [00:22<00:00,  5.52it/s, train/loss=48.40]
Epoch 0: |          | 123/? [00:22<00:00,  5.56it/s, train/loss=48.40]
Epoch 0: |          | 123/? [00:22<00:00,  5.56it/s, train/loss=6.940]
Epoch 0: |          | 124/? [00:22<00:00,  5.53it/s, train/loss=6.940]
Epoch 0: |          | 124/? [00:22<00:00,  5.53it/s, train/loss=98.00]
Epoch 0: |          | 125/? [00:22<00:00,  5.56it/s, train/loss=98.00]
Epoch 0: |          | 125/? [00:22<00:00,  5.56it/s, train/loss=6.790]
Epoch 0: |          | 126/? [00:22<00:00,  5.54it/s, train/loss=6.790]
Epoch 0: |          | 126/? [00:22<00:00,  5.54it/s, train/loss=34.70]
Epoch 0: |          | 127/? [00:22<00:00,  5.57it/s, train/loss=34.70]
Epoch 0: |          | 127/? [00:22<00:00,  5.57it/s, train/loss=6.770]
Epoch 0: |          | 128/? [00:23<00:00,  5.54it/s, train/loss=6.770]
Epoch 0: |          | 128/? [00:23<00:00,  5.54it/s, train/loss=24.60]
Epoch 0: |          | 129/? [00:23<00:00,  5.58it/s, train/loss=24.60]
Epoch 0: |          | 129/? [00:23<00:00,  5.58it/s, train/loss=6.750]
Epoch 0: |          | 130/? [00:23<00:00,  5.55it/s, train/loss=6.750]
Epoch 0: |          | 130/? [00:23<00:00,  5.55it/s, train/loss=42.10]
Epoch 0: |          | 131/? [00:23<00:00,  5.59it/s, train/loss=42.10]
Epoch 0: |          | 131/? [00:23<00:00,  5.59it/s, train/loss=6.640]
Epoch 0: |          | 132/? [00:23<00:00,  5.56it/s, train/loss=6.640]
Epoch 0: |          | 132/? [00:23<00:00,  5.56it/s, train/loss=64.70]
Epoch 0: |          | 133/? [00:23<00:00,  5.59it/s, train/loss=64.70]
Epoch 0: |          | 133/? [00:23<00:00,  5.59it/s, train/loss=6.450]
Epoch 0: |          | 134/? [00:24<00:00,  5.57it/s, train/loss=6.450]
Epoch 0: |          | 134/? [00:24<00:00,  5.57it/s, train/loss=47.10]
Epoch 0: |          | 135/? [00:24<00:00,  5.60it/s, train/loss=47.10]
Epoch 0: |          | 135/? [00:24<00:00,  5.60it/s, train/loss=6.330]
Epoch 0: |          | 136/? [00:24<00:00,  5.57it/s, train/loss=6.330]
Epoch 0: |          | 136/? [00:24<00:00,  5.57it/s, train/loss=42.00]
Epoch 0: |          | 137/? [00:24<00:00,  5.61it/s, train/loss=42.00]
Epoch 0: |          | 137/? [00:24<00:00,  5.61it/s, train/loss=6.280]
Epoch 0: |          | 138/? [00:24<00:00,  5.58it/s, train/loss=6.280]
Epoch 0: |          | 138/? [00:24<00:00,  5.58it/s, train/loss=46.60]
Epoch 0: |          | 139/? [00:24<00:00,  5.61it/s, train/loss=46.60]
Epoch 0: |          | 139/? [00:24<00:00,  5.61it/s, train/loss=6.390]
Epoch 0: |          | 140/? [00:25<00:00,  5.59it/s, train/loss=6.390]
Epoch 0: |          | 140/? [00:25<00:00,  5.59it/s, train/loss=33.50]
Epoch 0: |          | 141/? [00:25<00:00,  5.62it/s, train/loss=33.50]
Epoch 0: |          | 141/? [00:25<00:00,  5.62it/s, train/loss=6.580]
Epoch 0: |          | 142/? [00:25<00:00,  5.59it/s, train/loss=6.580]
Epoch 0: |          | 142/? [00:25<00:00,  5.59it/s, train/loss=30.50]
Epoch 0: |          | 143/? [00:25<00:00,  5.63it/s, train/loss=30.50]
Epoch 0: |          | 143/? [00:25<00:00,  5.63it/s, train/loss=6.660]
Epoch 0: |          | 144/? [00:25<00:00,  5.60it/s, train/loss=6.660]
Epoch 0: |          | 144/? [00:25<00:00,  5.60it/s, train/loss=38.60]
Epoch 0: |          | 145/? [00:25<00:00,  5.62it/s, train/loss=38.60]
Epoch 0: |          | 145/? [00:25<00:00,  5.62it/s, train/loss=6.590]
Epoch 0: |          | 146/? [00:26<00:00,  5.60it/s, train/loss=6.590]
Epoch 0: |          | 146/? [00:26<00:00,  5.60it/s, train/loss=34.10]
Epoch 0: |          | 147/? [00:26<00:00,  5.62it/s, train/loss=34.10]
Epoch 0: |          | 147/? [00:26<00:00,  5.62it/s, train/loss=6.380]
Epoch 0: |          | 148/? [00:26<00:00,  5.59it/s, train/loss=6.380]
Epoch 0: |          | 148/? [00:26<00:00,  5.59it/s, train/loss=64.90]
Epoch 0: |          | 149/? [00:26<00:00,  5.62it/s, train/loss=64.90]
Epoch 0: |          | 149/? [00:26<00:00,  5.62it/s, train/loss=6.170]
Epoch 0: |          | 150/? [00:26<00:00,  5.59it/s, train/loss=6.170]
Epoch 0: |          | 150/? [00:26<00:00,  5.59it/s, train/loss=38.60]
Epoch 0: |          | 151/? [00:26<00:00,  5.62it/s, train/loss=38.60]
Epoch 0: |          | 151/? [00:26<00:00,  5.62it/s, train/loss=6.060]
Epoch 0: |          | 152/? [00:27<00:00,  5.60it/s, train/loss=6.060]
Epoch 0: |          | 152/? [00:27<00:00,  5.60it/s, train/loss=45.40]
Epoch 0: |          | 153/? [00:27<00:00,  5.62it/s, train/loss=45.40]
Epoch 0: |          | 153/? [00:27<00:00,  5.62it/s, train/loss=5.980]
Epoch 0: |          | 154/? [00:27<00:00,  5.60it/s, train/loss=5.980]
Epoch 0: |          | 154/? [00:27<00:00,  5.60it/s, train/loss=33.70]
Epoch 0: |          | 155/? [00:27<00:00,  5.63it/s, train/loss=33.70]
Epoch 0: |          | 155/? [00:27<00:00,  5.63it/s, train/loss=5.930]
Epoch 0: |          | 156/? [00:27<00:00,  5.60it/s, train/loss=5.930]
Epoch 0: |          | 156/? [00:27<00:00,  5.60it/s, train/loss=35.70]
Epoch 0: |          | 157/? [00:27<00:00,  5.63it/s, train/loss=35.70]
Epoch 0: |          | 157/? [00:27<00:00,  5.63it/s, train/loss=5.870]
Epoch 0: |          | 158/? [00:28<00:00,  5.60it/s, train/loss=5.870]
Epoch 0: |          | 158/? [00:28<00:00,  5.60it/s, train/loss=26.40]
Epoch 0: |          | 159/? [00:28<00:00,  5.63it/s, train/loss=26.40]
Epoch 0: |          | 159/? [00:28<00:00,  5.63it/s, train/loss=5.840]
Epoch 0: |          | 160/? [00:28<00:00,  5.61it/s, train/loss=5.840]
Epoch 0: |          | 160/? [00:28<00:00,  5.61it/s, train/loss=49.70]
Epoch 0: |          | 161/? [00:28<00:00,  5.64it/s, train/loss=49.70]
Epoch 0: |          | 161/? [00:28<00:00,  5.64it/s, train/loss=5.760]
Epoch 0: |          | 162/? [00:28<00:00,  5.61it/s, train/loss=5.760]
Epoch 0: |          | 162/? [00:28<00:00,  5.61it/s, train/loss=51.80]
Epoch 0: |          | 163/? [00:28<00:00,  5.64it/s, train/loss=51.80]
Epoch 0: |          | 163/? [00:28<00:00,  5.64it/s, train/loss=5.590]
Epoch 0: |          | 164/? [00:29<00:00,  5.62it/s, train/loss=5.590]
Epoch 0: |          | 164/? [00:29<00:00,  5.62it/s, train/loss=25.90]
Epoch 0: |          | 165/? [00:29<00:00,  5.65it/s, train/loss=25.90]
Epoch 0: |          | 165/? [00:29<00:00,  5.65it/s, train/loss=5.480]
Epoch 0: |          | 166/? [00:29<00:00,  5.63it/s, train/loss=5.480]
Epoch 0: |          | 166/? [00:29<00:00,  5.62it/s, train/loss=44.60]
Epoch 0: |          | 167/? [00:29<00:00,  5.65it/s, train/loss=44.60]
Epoch 0: |          | 167/? [00:29<00:00,  5.65it/s, train/loss=5.450]
Epoch 0: |          | 168/? [00:29<00:00,  5.63it/s, train/loss=5.450]
Epoch 0: |          | 168/? [00:29<00:00,  5.63it/s, train/loss=28.10]
Epoch 0: |          | 169/? [00:29<00:00,  5.66it/s, train/loss=28.10]
Epoch 0: |          | 169/? [00:29<00:00,  5.66it/s, train/loss=5.520]
Epoch 0: |          | 170/? [00:30<00:00,  5.63it/s, train/loss=5.520]
Epoch 0: |          | 170/? [00:30<00:00,  5.63it/s, train/loss=40.30]
Epoch 0: |          | 171/? [00:30<00:00,  5.66it/s, train/loss=40.30]
Epoch 0: |          | 171/? [00:30<00:00,  5.66it/s, train/loss=5.610]
Epoch 0: |          | 172/? [00:30<00:00,  5.64it/s, train/loss=5.610]
Epoch 0: |          | 172/? [00:30<00:00,  5.64it/s, train/loss=31.20]
Epoch 0: |          | 173/? [00:30<00:00,  5.66it/s, train/loss=31.20]
Epoch 0: |          | 173/? [00:30<00:00,  5.66it/s, train/loss=5.690]
Epoch 0: |          | 174/? [00:30<00:00,  5.64it/s, train/loss=5.690]
Epoch 0: |          | 174/? [00:30<00:00,  5.64it/s, train/loss=22.80]
Epoch 0: |          | 175/? [00:30<00:00,  5.66it/s, train/loss=22.80]
Epoch 0: |          | 175/? [00:30<00:00,  5.66it/s, train/loss=5.640]
Epoch 0: |          | 176/? [00:31<00:00,  5.64it/s, train/loss=5.640]
Epoch 0: |          | 176/? [00:31<00:00,  5.64it/s, train/loss=38.40]
Epoch 0: |          | 177/? [00:31<00:00,  5.67it/s, train/loss=38.40]
Epoch 0: |          | 177/? [00:31<00:00,  5.66it/s, train/loss=5.450]
Epoch 0: |          | 178/? [00:31<00:00,  5.65it/s, train/loss=5.450]
Epoch 0: |          | 178/? [00:31<00:00,  5.64it/s, train/loss=25.80]
Epoch 0: |          | 179/? [00:31<00:00,  5.67it/s, train/loss=25.80]
Epoch 0: |          | 179/? [00:31<00:00,  5.67it/s, train/loss=5.300]
Epoch 0: |          | 180/? [00:31<00:00,  5.65it/s, train/loss=5.300]
Epoch 0: |          | 180/? [00:31<00:00,  5.65it/s, train/loss=46.20]
Epoch 0: |          | 181/? [00:31<00:00,  5.68it/s, train/loss=46.20]
Epoch 0: |          | 181/? [00:31<00:00,  5.68it/s, train/loss=5.170]
Epoch 0: |          | 182/? [00:32<00:00,  5.66it/s, train/loss=5.170]
Epoch 0: |          | 182/? [00:32<00:00,  5.66it/s, train/loss=28.60]
Epoch 0: |          | 183/? [00:32<00:00,  5.68it/s, train/loss=28.60]
Epoch 0: |          | 183/? [00:32<00:00,  5.68it/s, train/loss=5.060]
Epoch 0: |          | 184/? [00:32<00:00,  5.66it/s, train/loss=5.060]
Epoch 0: |          | 184/? [00:32<00:00,  5.66it/s, train/loss=25.50]
Epoch 0: |          | 185/? [00:32<00:00,  5.68it/s, train/loss=25.50]
Epoch 0: |          | 185/? [00:32<00:00,  5.68it/s, train/loss=5.020]
Epoch 0: |          | 186/? [00:32<00:00,  5.66it/s, train/loss=5.020]
Epoch 0: |          | 186/? [00:32<00:00,  5.66it/s, train/loss=20.50]
Epoch 0: |          | 187/? [00:32<00:00,  5.69it/s, train/loss=20.50]
Epoch 0: |          | 187/? [00:32<00:00,  5.69it/s, train/loss=4.970]
Epoch 0: |          | 188/? [00:33<00:00,  5.67it/s, train/loss=4.970]
Epoch 0: |          | 188/? [00:33<00:00,  5.67it/s, train/loss=21.20]
Epoch 0: |          | 189/? [00:33<00:00,  5.69it/s, train/loss=21.20]
Epoch 0: |          | 189/? [00:33<00:00,  5.69it/s, train/loss=4.920]
Epoch 0: |          | 190/? [00:33<00:00,  5.67it/s, train/loss=4.920]
Epoch 0: |          | 190/? [00:33<00:00,  5.67it/s, train/loss=31.50]
Epoch 0: |          | 191/? [00:33<00:00,  5.70it/s, train/loss=31.50]
Epoch 0: |          | 191/? [00:33<00:00,  5.70it/s, train/loss=4.870]
Epoch 0: |          | 192/? [00:33<00:00,  5.68it/s, train/loss=4.870]
Epoch 0: |          | 192/? [00:33<00:00,  5.68it/s, train/loss=65.00]
Epoch 0: |          | 193/? [00:33<00:00,  5.70it/s, train/loss=65.00]
Epoch 0: |          | 193/? [00:33<00:00,  5.70it/s, train/loss=4.860]
Epoch 0: |          | 194/? [00:34<00:00,  5.68it/s, train/loss=4.860]
Epoch 0: |          | 194/? [00:34<00:00,  5.68it/s, train/loss=19.90]
Epoch 0: |          | 195/? [00:34<00:00,  5.71it/s, train/loss=19.90]
Epoch 0: |          | 195/? [00:34<00:00,  5.71it/s, train/loss=4.850]
Epoch 0: |          | 196/? [00:34<00:00,  5.69it/s, train/loss=4.850]
Epoch 0: |          | 196/? [00:34<00:00,  5.69it/s, train/loss=25.90]
Epoch 0: |          | 197/? [00:34<00:00,  5.71it/s, train/loss=25.90]
Epoch 0: |          | 197/? [00:34<00:00,  5.71it/s, train/loss=4.860]
Epoch 0: |          | 198/? [00:34<00:00,  5.69it/s, train/loss=4.860]
Epoch 0: |          | 198/? [00:34<00:00,  5.69it/s, train/loss=41.40]
Epoch 0: |          | 199/? [00:34<00:00,  5.71it/s, train/loss=41.40]
Epoch 0: |          | 199/? [00:34<00:00,  5.71it/s, train/loss=4.860]
Epoch 0: |          | 200/? [00:35<00:00,  5.70it/s, train/loss=4.860]
Epoch 0: |          | 200/? [00:35<00:00,  5.70it/s, train/loss=22.20]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 53.95it/s]

Epoch 0: |          | 200/? [00:36<00:00,  5.50it/s, train/loss=22.20]
Epoch 0: |          | 201/? [00:36<00:00,  5.49it/s, train/loss=22.20]
Epoch 0: |          | 201/? [00:36<00:00,  5.49it/s, train/loss=4.850]
Epoch 0: |          | 202/? [00:36<00:00,  5.47it/s, train/loss=4.850]
Epoch 0: |          | 202/? [00:36<00:00,  5.47it/s, train/loss=16.20]
Epoch 0: |          | 203/? [00:36<00:00,  5.49it/s, train/loss=16.20]
Epoch 0: |          | 203/? [00:36<00:00,  5.49it/s, train/loss=4.840]
Epoch 0: |          | 204/? [00:37<00:00,  5.48it/s, train/loss=4.840]
Epoch 0: |          | 204/? [00:37<00:00,  5.48it/s, train/loss=40.60]
Epoch 0: |          | 205/? [00:37<00:00,  5.50it/s, train/loss=40.60]
Epoch 0: |          | 205/? [00:37<00:00,  5.50it/s, train/loss=4.810]
Epoch 0: |          | 206/? [00:37<00:00,  5.48it/s, train/loss=4.810]
Epoch 0: |          | 206/? [00:37<00:00,  5.48it/s, train/loss=15.70]
Epoch 0: |          | 207/? [00:37<00:00,  5.51it/s, train/loss=15.70]
Epoch 0: |          | 207/? [00:37<00:00,  5.51it/s, train/loss=4.780]
Epoch 0: |          | 208/? [00:37<00:00,  5.49it/s, train/loss=4.780]
Epoch 0: |          | 208/? [00:37<00:00,  5.49it/s, train/loss=10.70]
Epoch 0: |          | 209/? [00:37<00:00,  5.51it/s, train/loss=10.70]
Epoch 0: |          | 209/? [00:37<00:00,  5.51it/s, train/loss=4.740]
Epoch 0: |          | 210/? [00:38<00:00,  5.50it/s, train/loss=4.740]
Epoch 0: |          | 210/? [00:38<00:00,  5.50it/s, train/loss=34.00]
Epoch 0: |          | 211/? [00:38<00:00,  5.51it/s, train/loss=34.00]
Epoch 0: |          | 211/? [00:38<00:00,  5.51it/s, train/loss=4.660]
Epoch 0: |          | 212/? [00:38<00:00,  5.50it/s, train/loss=4.660]
Epoch 0: |          | 212/? [00:38<00:00,  5.50it/s, train/loss=30.70]
Epoch 0: |          | 213/? [00:38<00:00,  5.52it/s, train/loss=30.70]
Epoch 0: |          | 213/? [00:38<00:00,  5.52it/s, train/loss=4.570]
Epoch 0: |          | 214/? [00:38<00:00,  5.50it/s, train/loss=4.570]
Epoch 0: |          | 214/? [00:38<00:00,  5.50it/s, train/loss=15.90]
Epoch 0: |          | 215/? [00:38<00:00,  5.52it/s, train/loss=15.90]
Epoch 0: |          | 215/? [00:38<00:00,  5.52it/s, train/loss=4.540]
Epoch 0: |          | 216/? [00:39<00:00,  5.50it/s, train/loss=4.540]
Epoch 0: |          | 216/? [00:39<00:00,  5.50it/s, train/loss=25.80]
Epoch 0: |          | 217/? [00:39<00:00,  5.52it/s, train/loss=25.80]
Epoch 0: |          | 217/? [00:39<00:00,  5.52it/s, train/loss=4.500]
Epoch 0: |          | 218/? [00:39<00:00,  5.50it/s, train/loss=4.500]
Epoch 0: |          | 218/? [00:39<00:00,  5.50it/s, train/loss=30.50]
Epoch 0: |          | 219/? [00:39<00:00,  5.52it/s, train/loss=30.50]
Epoch 0: |          | 219/? [00:39<00:00,  5.52it/s, train/loss=4.460]
Epoch 0: |          | 220/? [00:39<00:00,  5.50it/s, train/loss=4.460]
Epoch 0: |          | 220/? [00:39<00:00,  5.50it/s, train/loss=67.90]
Epoch 0: |          | 221/? [00:40<00:00,  5.52it/s, train/loss=67.90]
Epoch 0: |          | 221/? [00:40<00:00,  5.52it/s, train/loss=4.400]
Epoch 0: |          | 222/? [00:40<00:00,  5.50it/s, train/loss=4.400]
Epoch 0: |          | 222/? [00:40<00:00,  5.50it/s, train/loss=21.40]
Epoch 0: |          | 223/? [00:40<00:00,  5.52it/s, train/loss=21.40]
Epoch 0: |          | 223/? [00:40<00:00,  5.52it/s, train/loss=4.370]
Epoch 0: |          | 224/? [00:40<00:00,  5.50it/s, train/loss=4.370]
Epoch 0: |          | 224/? [00:40<00:00,  5.50it/s, train/loss=37.50]
Epoch 0: |          | 225/? [00:40<00:00,  5.52it/s, train/loss=37.50]
Epoch 0: |          | 225/? [00:40<00:00,  5.52it/s, train/loss=4.340]
Epoch 0: |          | 226/? [00:41<00:00,  5.50it/s, train/loss=4.340]
Epoch 0: |          | 226/? [00:41<00:00,  5.50it/s, train/loss=8.740]
Epoch 0: |          | 227/? [00:41<00:00,  5.52it/s, train/loss=8.740]
Epoch 0: |          | 227/? [00:41<00:00,  5.52it/s, train/loss=4.320]
Epoch 0: |          | 228/? [00:41<00:00,  5.50it/s, train/loss=4.320]
Epoch 0: |          | 228/? [00:41<00:00,  5.50it/s, train/loss=11.40]
Epoch 0: |          | 229/? [00:41<00:00,  5.52it/s, train/loss=11.40]
Epoch 0: |          | 229/? [00:41<00:00,  5.52it/s, train/loss=4.270]
Epoch 0: |          | 230/? [00:41<00:00,  5.50it/s, train/loss=4.270]
Epoch 0: |          | 230/? [00:41<00:00,  5.50it/s, train/loss=16.20]
Epoch 0: |          | 231/? [00:41<00:00,  5.52it/s, train/loss=16.20]
Epoch 0: |          | 231/? [00:41<00:00,  5.52it/s, train/loss=4.210]
Epoch 0: |          | 232/? [00:42<00:00,  5.51it/s, train/loss=4.210]
Epoch 0: |          | 232/? [00:42<00:00,  5.51it/s, train/loss=14.70]
Epoch 0: |          | 233/? [00:42<00:00,  5.52it/s, train/loss=14.70]
Epoch 0: |          | 233/? [00:42<00:00,  5.52it/s, train/loss=4.140]
Epoch 0: |          | 234/? [00:42<00:00,  5.51it/s, train/loss=4.140]
Epoch 0: |          | 234/? [00:42<00:00,  5.51it/s, train/loss=13.80]
Epoch 0: |          | 235/? [00:42<00:00,  5.52it/s, train/loss=13.80]
Epoch 0: |          | 235/? [00:42<00:00,  5.52it/s, train/loss=4.070]
Epoch 0: |          | 236/? [00:42<00:00,  5.51it/s, train/loss=4.070]
Epoch 0: |          | 236/? [00:42<00:00,  5.51it/s, train/loss=21.90]
Epoch 0: |          | 237/? [00:42<00:00,  5.52it/s, train/loss=21.90]
Epoch 0: |          | 237/? [00:42<00:00,  5.52it/s, train/loss=3.970]
Epoch 0: |          | 238/? [00:43<00:00,  5.51it/s, train/loss=3.970]
Epoch 0: |          | 238/? [00:43<00:00,  5.51it/s, train/loss=30.50]
Epoch 0: |          | 239/? [00:43<00:00,  5.53it/s, train/loss=30.50]
Epoch 0: |          | 239/? [00:43<00:00,  5.53it/s, train/loss=3.910]
Epoch 0: |          | 240/? [00:43<00:00,  5.51it/s, train/loss=3.910]
Epoch 0: |          | 240/? [00:43<00:00,  5.51it/s, train/loss=12.20]
Epoch 0: |          | 241/? [00:43<00:00,  5.53it/s, train/loss=12.20]
Epoch 0: |          | 241/? [00:43<00:00,  5.53it/s, train/loss=3.890]
Epoch 0: |          | 242/? [00:43<00:00,  5.51it/s, train/loss=3.890]
Epoch 0: |          | 242/? [00:43<00:00,  5.51it/s, train/loss=52.70]
Epoch 0: |          | 243/? [00:43<00:00,  5.53it/s, train/loss=52.70]
Epoch 0: |          | 243/? [00:43<00:00,  5.53it/s, train/loss=3.820]
Epoch 0: |          | 244/? [00:44<00:00,  5.51it/s, train/loss=3.820]
Epoch 0: |          | 244/? [00:44<00:00,  5.51it/s, train/loss=12.60]
Epoch 0: |          | 245/? [00:44<00:00,  5.53it/s, train/loss=12.60]
Epoch 0: |          | 245/? [00:44<00:00,  5.53it/s, train/loss=3.750]
Epoch 0: |          | 246/? [00:44<00:00,  5.52it/s, train/loss=3.750]
Epoch 0: |          | 246/? [00:44<00:00,  5.52it/s, train/loss=22.40]
Epoch 0: |          | 247/? [00:44<00:00,  5.53it/s, train/loss=22.40]
Epoch 0: |          | 247/? [00:44<00:00,  5.53it/s, train/loss=3.740]
Epoch 0: |          | 248/? [00:44<00:00,  5.52it/s, train/loss=3.740]
Epoch 0: |          | 248/? [00:44<00:00,  5.52it/s, train/loss=31.60]
Epoch 0: |          | 249/? [00:44<00:00,  5.54it/s, train/loss=31.60]
Epoch 0: |          | 249/? [00:44<00:00,  5.54it/s, train/loss=3.760]
Epoch 0: |          | 250/? [00:45<00:00,  5.53it/s, train/loss=3.760]
Epoch 0: |          | 250/? [00:45<00:00,  5.53it/s, train/loss=9.880]
Epoch 0: |          | 251/? [00:45<00:00,  5.54it/s, train/loss=9.880]
Epoch 0: |          | 251/? [00:45<00:00,  5.54it/s, train/loss=3.770]
Epoch 0: |          | 252/? [00:45<00:00,  5.53it/s, train/loss=3.770]
Epoch 0: |          | 252/? [00:45<00:00,  5.53it/s, train/loss=28.30]
Epoch 0: |          | 253/? [00:45<00:00,  5.55it/s, train/loss=28.30]
Epoch 0: |          | 253/? [00:45<00:00,  5.55it/s, train/loss=3.730]
Epoch 0: |          | 254/? [00:45<00:00,  5.54it/s, train/loss=3.730]
Epoch 0: |          | 254/? [00:45<00:00,  5.54it/s, train/loss=11.40]
Epoch 0: |          | 255/? [00:45<00:00,  5.55it/s, train/loss=11.40]
Epoch 0: |          | 255/? [00:45<00:00,  5.55it/s, train/loss=3.640]
Epoch 0: |          | 256/? [00:46<00:00,  5.54it/s, train/loss=3.640]
Epoch 0: |          | 256/? [00:46<00:00,  5.54it/s, train/loss=24.80]
Epoch 0: |          | 257/? [00:46<00:00,  5.56it/s, train/loss=24.80]
Epoch 0: |          | 257/? [00:46<00:00,  5.56it/s, train/loss=3.570]
Epoch 0: |          | 258/? [00:46<00:00,  5.54it/s, train/loss=3.570]
Epoch 0: |          | 258/? [00:46<00:00,  5.54it/s, train/loss=37.10]
Epoch 0: |          | 259/? [00:46<00:00,  5.56it/s, train/loss=37.10]
Epoch 0: |          | 259/? [00:46<00:00,  5.56it/s, train/loss=3.530]
Epoch 0: |          | 260/? [00:46<00:00,  5.55it/s, train/loss=3.530]
Epoch 0: |          | 260/? [00:46<00:00,  5.55it/s, train/loss=23.60]
Epoch 0: |          | 261/? [00:46<00:00,  5.56it/s, train/loss=23.60]
Epoch 0: |          | 261/? [00:46<00:00,  5.56it/s, train/loss=3.540]
Epoch 0: |          | 262/? [00:47<00:00,  5.55it/s, train/loss=3.540]
Epoch 0: |          | 262/? [00:47<00:00,  5.55it/s, train/loss=45.00]
Epoch 0: |          | 263/? [00:47<00:00,  5.57it/s, train/loss=45.00]
Epoch 0: |          | 263/? [00:47<00:00,  5.57it/s, train/loss=3.530]
Epoch 0: |          | 264/? [00:47<00:00,  5.55it/s, train/loss=3.530]
Epoch 0: |          | 264/? [00:47<00:00,  5.55it/s, train/loss=10.10]
Epoch 0: |          | 265/? [00:47<00:00,  5.57it/s, train/loss=10.10]
Epoch 0: |          | 265/? [00:47<00:00,  5.57it/s, train/loss=3.530]
Epoch 0: |          | 266/? [00:47<00:00,  5.56it/s, train/loss=3.530]
Epoch 0: |          | 266/? [00:47<00:00,  5.56it/s, train/loss=12.90]
Epoch 0: |          | 267/? [00:47<00:00,  5.57it/s, train/loss=12.90]
Epoch 0: |          | 267/? [00:47<00:00,  5.57it/s, train/loss=3.530]
Epoch 0: |          | 268/? [00:48<00:00,  5.56it/s, train/loss=3.530]
Epoch 0: |          | 268/? [00:48<00:00,  5.56it/s, train/loss=32.20]
Epoch 0: |          | 269/? [00:48<00:00,  5.58it/s, train/loss=32.20]
Epoch 0: |          | 269/? [00:48<00:00,  5.58it/s, train/loss=3.480]
Epoch 0: |          | 270/? [00:48<00:00,  5.57it/s, train/loss=3.480]
Epoch 0: |          | 270/? [00:48<00:00,  5.57it/s, train/loss=10.20]
Epoch 0: |          | 271/? [00:48<00:00,  5.58it/s, train/loss=10.20]
Epoch 0: |          | 271/? [00:48<00:00,  5.58it/s, train/loss=3.440]
Epoch 0: |          | 272/? [00:48<00:00,  5.57it/s, train/loss=3.440]
Epoch 0: |          | 272/? [00:48<00:00,  5.57it/s, train/loss=9.860]
Epoch 0: |          | 273/? [00:48<00:00,  5.59it/s, train/loss=9.860]
Epoch 0: |          | 273/? [00:48<00:00,  5.59it/s, train/loss=3.400]
Epoch 0: |          | 274/? [00:49<00:00,  5.57it/s, train/loss=3.400]
Epoch 0: |          | 274/? [00:49<00:00,  5.57it/s, train/loss=25.90]
Epoch 0: |          | 275/? [00:49<00:00,  5.59it/s, train/loss=25.90]
Epoch 0: |          | 275/? [00:49<00:00,  5.59it/s, train/loss=3.400]
Epoch 0: |          | 276/? [00:49<00:00,  5.58it/s, train/loss=3.400]
Epoch 0: |          | 276/? [00:49<00:00,  5.58it/s, train/loss=37.60]
Epoch 0: |          | 277/? [00:49<00:00,  5.59it/s, train/loss=37.60]
Epoch 0: |          | 277/? [00:49<00:00,  5.59it/s, train/loss=3.430]
Epoch 0: |          | 278/? [00:49<00:00,  5.58it/s, train/loss=3.430]
Epoch 0: |          | 278/? [00:49<00:00,  5.58it/s, train/loss=18.80]
Epoch 0: |          | 279/? [00:49<00:00,  5.60it/s, train/loss=18.80]
Epoch 0: |          | 279/? [00:49<00:00,  5.60it/s, train/loss=3.440]
Epoch 0: |          | 280/? [00:50<00:00,  5.58it/s, train/loss=3.440]
Epoch 0: |          | 280/? [00:50<00:00,  5.58it/s, train/loss=28.50]
Epoch 0: |          | 281/? [00:50<00:00,  5.60it/s, train/loss=28.50]
Epoch 0: |          | 281/? [00:50<00:00,  5.60it/s, train/loss=3.410]
Epoch 0: |          | 282/? [00:50<00:00,  5.59it/s, train/loss=3.410]
Epoch 0: |          | 282/? [00:50<00:00,  5.59it/s, train/loss=9.970]
Epoch 0: |          | 283/? [00:50<00:00,  5.60it/s, train/loss=9.970]
Epoch 0: |          | 283/? [00:50<00:00,  5.60it/s, train/loss=3.390]
Epoch 0: |          | 284/? [00:50<00:00,  5.59it/s, train/loss=3.390]
Epoch 0: |          | 284/? [00:50<00:00,  5.59it/s, train/loss=40.30]
Epoch 0: |          | 285/? [00:50<00:00,  5.60it/s, train/loss=40.30]
Epoch 0: |          | 285/? [00:50<00:00,  5.60it/s, train/loss=3.380]
Epoch 0: |          | 286/? [00:51<00:00,  5.59it/s, train/loss=3.380]
Epoch 0: |          | 286/? [00:51<00:00,  5.59it/s, train/loss=31.70]
Epoch 0: |          | 287/? [00:51<00:00,  5.61it/s, train/loss=31.70]
Epoch 0: |          | 287/? [00:51<00:00,  5.61it/s, train/loss=3.400]
Epoch 0: |          | 288/? [00:51<00:00,  5.60it/s, train/loss=3.400]
Epoch 0: |          | 288/? [00:51<00:00,  5.60it/s, train/loss=15.20]
Epoch 0: |          | 289/? [00:51<00:00,  5.61it/s, train/loss=15.20]
Epoch 0: |          | 289/? [00:51<00:00,  5.61it/s, train/loss=3.410]
Epoch 0: |          | 290/? [00:51<00:00,  5.60it/s, train/loss=3.410]
Epoch 0: |          | 290/? [00:51<00:00,  5.60it/s, train/loss=14.10]
Epoch 0: |          | 291/? [00:51<00:00,  5.61it/s, train/loss=14.10]
Epoch 0: |          | 291/? [00:51<00:00,  5.61it/s, train/loss=3.420]
Epoch 0: |          | 292/? [00:52<00:00,  5.60it/s, train/loss=3.420]
Epoch 0: |          | 292/? [00:52<00:00,  5.60it/s, train/loss=19.10]
Epoch 0: |          | 293/? [00:52<00:00,  5.61it/s, train/loss=19.10]
Epoch 0: |          | 293/? [00:52<00:00,  5.61it/s, train/loss=3.400]
Epoch 0: |          | 294/? [00:52<00:00,  5.60it/s, train/loss=3.400]
Epoch 0: |          | 294/? [00:52<00:00,  5.60it/s, train/loss=24.80]
Epoch 0: |          | 295/? [00:52<00:00,  5.62it/s, train/loss=24.80]
Epoch 0: |          | 295/? [00:52<00:00,  5.62it/s, train/loss=3.340]
Epoch 0: |          | 296/? [00:52<00:00,  5.61it/s, train/loss=3.340]
Epoch 0: |          | 296/? [00:52<00:00,  5.60it/s, train/loss=39.10]
Epoch 0: |          | 297/? [00:52<00:00,  5.62it/s, train/loss=39.10]
Epoch 0: |          | 297/? [00:52<00:00,  5.62it/s, train/loss=3.290]
Epoch 0: |          | 298/? [00:53<00:00,  5.61it/s, train/loss=3.290]
Epoch 0: |          | 298/? [00:53<00:00,  5.61it/s, train/loss=8.320]
Epoch 0: |          | 299/? [00:53<00:00,  5.62it/s, train/loss=8.320]
Epoch 0: |          | 299/? [00:53<00:00,  5.62it/s, train/loss=3.340]
Epoch 0: |          | 300/? [00:53<00:00,  5.61it/s, train/loss=3.340]
Epoch 0: |          | 300/? [00:53<00:00,  5.61it/s, train/loss=19.60]
Epoch 0: |          | 301/? [00:53<00:00,  5.63it/s, train/loss=19.60]
Epoch 0: |          | 301/? [00:53<00:00,  5.63it/s, train/loss=3.370]
Epoch 0: |          | 302/? [00:53<00:00,  5.61it/s, train/loss=3.370]
Epoch 0: |          | 302/? [00:53<00:00,  5.61it/s, train/loss=28.90]
Epoch 0: |          | 303/? [00:53<00:00,  5.63it/s, train/loss=28.90]
Epoch 0: |          | 303/? [00:53<00:00,  5.63it/s, train/loss=3.270]
Epoch 0: |          | 304/? [00:54<00:00,  5.62it/s, train/loss=3.270]
Epoch 0: |          | 304/? [00:54<00:00,  5.62it/s, train/loss=24.00]
Epoch 0: |          | 305/? [00:54<00:00,  5.63it/s, train/loss=24.00]
Epoch 0: |          | 305/? [00:54<00:00,  5.63it/s, train/loss=3.110]
Epoch 0: |          | 306/? [00:54<00:00,  5.62it/s, train/loss=3.110]
Epoch 0: |          | 306/? [00:54<00:00,  5.62it/s, train/loss=18.70]
Epoch 0: |          | 307/? [00:54<00:00,  5.63it/s, train/loss=18.70]
Epoch 0: |          | 307/? [00:54<00:00,  5.63it/s, train/loss=3.060]
Epoch 0: |          | 308/? [00:54<00:00,  5.62it/s, train/loss=3.060]
Epoch 0: |          | 308/? [00:54<00:00,  5.62it/s, train/loss=24.10]
Epoch 0: |          | 309/? [00:54<00:00,  5.63it/s, train/loss=24.10]
Epoch 0: |          | 309/? [00:54<00:00,  5.63it/s, train/loss=3.140]
Epoch 0: |          | 310/? [00:55<00:00,  5.62it/s, train/loss=3.140]
Epoch 0: |          | 310/? [00:55<00:00,  5.62it/s, train/loss=24.70]
Epoch 0: |          | 311/? [00:55<00:00,  5.63it/s, train/loss=24.70]
Epoch 0: |          | 311/? [00:55<00:00,  5.63it/s, train/loss=3.210]
Epoch 0: |          | 312/? [00:55<00:00,  5.62it/s, train/loss=3.210]
Epoch 0: |          | 312/? [00:55<00:00,  5.62it/s, train/loss=15.20]
Epoch 0: |          | 313/? [00:55<00:00,  5.64it/s, train/loss=15.20]
Epoch 0: |          | 313/? [00:55<00:00,  5.64it/s, train/loss=3.240]
Epoch 0: |          | 314/? [00:55<00:00,  5.63it/s, train/loss=3.240]
Epoch 0: |          | 314/? [00:55<00:00,  5.63it/s, train/loss=31.30]
Epoch 0: |          | 315/? [00:55<00:00,  5.64it/s, train/loss=31.30]
Epoch 0: |          | 315/? [00:55<00:00,  5.64it/s, train/loss=3.230]
Epoch 0: |          | 316/? [00:56<00:00,  5.63it/s, train/loss=3.230]
Epoch 0: |          | 316/? [00:56<00:00,  5.63it/s, train/loss=16.70]
Epoch 0: |          | 317/? [00:56<00:00,  5.64it/s, train/loss=16.70]
Epoch 0: |          | 317/? [00:56<00:00,  5.64it/s, train/loss=3.200]
Epoch 0: |          | 318/? [00:56<00:00,  5.63it/s, train/loss=3.200]
Epoch 0: |          | 318/? [00:56<00:00,  5.63it/s, train/loss=18.80]
Epoch 0: |          | 319/? [00:56<00:00,  5.65it/s, train/loss=18.80]
Epoch 0: |          | 319/? [00:56<00:00,  5.65it/s, train/loss=3.190]
Epoch 0: |          | 320/? [00:56<00:00,  5.64it/s, train/loss=3.190]
Epoch 0: |          | 320/? [00:56<00:00,  5.64it/s, train/loss=37.10]
Epoch 0: |          | 321/? [00:56<00:00,  5.65it/s, train/loss=37.10]
Epoch 0: |          | 321/? [00:56<00:00,  5.65it/s, train/loss=3.160]
Epoch 0: |          | 322/? [00:57<00:00,  5.64it/s, train/loss=3.160]
Epoch 0: |          | 322/? [00:57<00:00,  5.64it/s, train/loss=29.70]
Epoch 0: |          | 323/? [00:57<00:00,  5.65it/s, train/loss=29.70]
Epoch 0: |          | 323/? [00:57<00:00,  5.65it/s, train/loss=3.120]
Epoch 0: |          | 324/? [00:57<00:00,  5.64it/s, train/loss=3.120]
Epoch 0: |          | 324/? [00:57<00:00,  5.64it/s, train/loss=22.20]
Epoch 0: |          | 325/? [00:57<00:00,  5.66it/s, train/loss=22.20]
Epoch 0: |          | 325/? [00:57<00:00,  5.66it/s, train/loss=3.130]
Epoch 0: |          | 326/? [00:57<00:00,  5.65it/s, train/loss=3.130]
Epoch 0: |          | 326/? [00:57<00:00,  5.65it/s, train/loss=23.50]
Epoch 0: |          | 327/? [00:57<00:00,  5.66it/s, train/loss=23.50]
Epoch 0: |          | 327/? [00:57<00:00,  5.66it/s, train/loss=3.110]
Epoch 0: |          | 328/? [00:58<00:00,  5.65it/s, train/loss=3.110]
Epoch 0: |          | 328/? [00:58<00:00,  5.65it/s, train/loss=37.80]
Epoch 0: |          | 329/? [00:58<00:00,  5.66it/s, train/loss=37.80]
Epoch 0: |          | 329/? [00:58<00:00,  5.66it/s, train/loss=3.010]
Epoch 0: |          | 330/? [00:58<00:00,  5.65it/s, train/loss=3.010]
Epoch 0: |          | 330/? [00:58<00:00,  5.65it/s, train/loss=30.40]
Epoch 0: |          | 331/? [00:58<00:00,  5.66it/s, train/loss=30.40]
Epoch 0: |          | 331/? [00:58<00:00,  5.66it/s, train/loss=2.920]
Epoch 0: |          | 332/? [00:58<00:00,  5.65it/s, train/loss=2.920]
Epoch 0: |          | 332/? [00:58<00:00,  5.65it/s, train/loss=20.70]
Epoch 0: |          | 333/? [00:58<00:00,  5.67it/s, train/loss=20.70]
Epoch 0: |          | 333/? [00:58<00:00,  5.67it/s, train/loss=2.860]
Epoch 0: |          | 334/? [00:59<00:00,  5.66it/s, train/loss=2.860]
Epoch 0: |          | 334/? [00:59<00:00,  5.66it/s, train/loss=10.10]
Epoch 0: |          | 335/? [00:59<00:00,  5.67it/s, train/loss=10.10]
Epoch 0: |          | 335/? [00:59<00:00,  5.67it/s, train/loss=2.800]
Epoch 0: |          | 336/? [00:59<00:00,  5.66it/s, train/loss=2.800]
Epoch 0: |          | 336/? [00:59<00:00,  5.66it/s, train/loss=38.50]
Epoch 0: |          | 337/? [00:59<00:00,  5.67it/s, train/loss=38.50]
Epoch 0: |          | 337/? [00:59<00:00,  5.67it/s, train/loss=2.760]
Epoch 0: |          | 338/? [00:59<00:00,  5.66it/s, train/loss=2.760]
Epoch 0: |          | 338/? [00:59<00:00,  5.66it/s, train/loss=17.30]
Epoch 0: |          | 339/? [00:59<00:00,  5.68it/s, train/loss=17.30]
Epoch 0: |          | 339/? [00:59<00:00,  5.68it/s, train/loss=2.760]
Epoch 0: |          | 340/? [01:00<00:00,  5.66it/s, train/loss=2.760]
Epoch 0: |          | 340/? [01:00<00:00,  5.66it/s, train/loss=30.30]
Epoch 0: |          | 341/? [01:00<00:00,  5.68it/s, train/loss=30.30]
Epoch 0: |          | 341/? [01:00<00:00,  5.68it/s, train/loss=2.770]
Epoch 0: |          | 342/? [01:00<00:00,  5.67it/s, train/loss=2.770]
Epoch 0: |          | 342/? [01:00<00:00,  5.67it/s, train/loss=40.10]
Epoch 0: |          | 343/? [01:00<00:00,  5.68it/s, train/loss=40.10]
Epoch 0: |          | 343/? [01:00<00:00,  5.68it/s, train/loss=2.790]
Epoch 0: |          | 344/? [01:00<00:00,  5.67it/s, train/loss=2.790]
Epoch 0: |          | 344/? [01:00<00:00,  5.67it/s, train/loss=7.000]
Epoch 0: |          | 345/? [01:00<00:00,  5.68it/s, train/loss=7.000]
Epoch 0: |          | 345/? [01:00<00:00,  5.68it/s, train/loss=2.850]
Epoch 0: |          | 346/? [01:00<00:00,  5.67it/s, train/loss=2.850]
Epoch 0: |          | 346/? [01:00<00:00,  5.67it/s, train/loss=23.60]
Epoch 0: |          | 347/? [01:01<00:00,  5.69it/s, train/loss=23.60]
Epoch 0: |          | 347/? [01:01<00:00,  5.69it/s, train/loss=2.880]
Epoch 0: |          | 348/? [01:01<00:00,  5.68it/s, train/loss=2.880]
Epoch 0: |          | 348/? [01:01<00:00,  5.68it/s, train/loss=57.60]
Epoch 0: |          | 349/? [01:01<00:00,  5.69it/s, train/loss=57.60]
Epoch 0: |          | 349/? [01:01<00:00,  5.69it/s, train/loss=2.860]
Epoch 0: |          | 350/? [01:01<00:00,  5.68it/s, train/loss=2.860]
Epoch 0: |          | 350/? [01:01<00:00,  5.68it/s, train/loss=14.50]
Epoch 0: |          | 351/? [01:01<00:00,  5.69it/s, train/loss=14.50]
Epoch 0: |          | 351/? [01:01<00:00,  5.69it/s, train/loss=2.870]
Epoch 0: |          | 352/? [01:01<00:00,  5.68it/s, train/loss=2.870]
Epoch 0: |          | 352/? [01:01<00:00,  5.68it/s, train/loss=11.60]
Epoch 0: |          | 353/? [01:01<00:00,  5.69it/s, train/loss=11.60]
Epoch 0: |          | 353/? [01:01<00:00,  5.69it/s, train/loss=2.890]
Epoch 0: |          | 354/? [01:02<00:00,  5.68it/s, train/loss=2.890]
Epoch 0: |          | 354/? [01:02<00:00,  5.68it/s, train/loss=49.20]
Epoch 0: |          | 355/? [01:02<00:00,  5.70it/s, train/loss=49.20]
Epoch 0: |          | 355/? [01:02<00:00,  5.70it/s, train/loss=2.900]
Epoch 0: |          | 356/? [01:02<00:00,  5.69it/s, train/loss=2.900]
Epoch 0: |          | 356/? [01:02<00:00,  5.69it/s, train/loss=7.090]
Epoch 0: |          | 357/? [01:02<00:00,  5.70it/s, train/loss=7.090]
Epoch 0: |          | 357/? [01:02<00:00,  5.70it/s, train/loss=2.930]
Epoch 0: |          | 358/? [01:02<00:00,  5.69it/s, train/loss=2.930]
Epoch 0: |          | 358/? [01:02<00:00,  5.69it/s, train/loss=68.30]
Epoch 0: |          | 359/? [01:02<00:00,  5.70it/s, train/loss=68.30]
Epoch 0: |          | 359/? [01:02<00:00,  5.70it/s, train/loss=3.030]
Epoch 0: |          | 360/? [01:03<00:00,  5.69it/s, train/loss=3.030]
Epoch 0: |          | 360/? [01:03<00:00,  5.69it/s, train/loss=14.50]
Epoch 0: |          | 361/? [01:03<00:00,  5.70it/s, train/loss=14.50]
Epoch 0: |          | 361/? [01:03<00:00,  5.70it/s, train/loss=3.160]
Epoch 0: |          | 362/? [01:03<00:00,  5.69it/s, train/loss=3.160]
Epoch 0: |          | 362/? [01:03<00:00,  5.69it/s, train/loss=9.390]
Epoch 0: |          | 363/? [01:03<00:00,  5.71it/s, train/loss=9.390]
Epoch 0: |          | 363/? [01:03<00:00,  5.71it/s, train/loss=3.190]
Epoch 0: |          | 364/? [01:03<00:00,  5.70it/s, train/loss=3.190]
Epoch 0: |          | 364/? [01:03<00:00,  5.70it/s, train/loss=34.60]
Epoch 0: |          | 365/? [01:03<00:00,  5.71it/s, train/loss=34.60]
Epoch 0: |          | 365/? [01:03<00:00,  5.71it/s, train/loss=3.110]
Epoch 0: |          | 366/? [01:04<00:00,  5.70it/s, train/loss=3.110]
Epoch 0: |          | 366/? [01:04<00:00,  5.70it/s, train/loss=13.80]
Epoch 0: |          | 367/? [01:04<00:00,  5.71it/s, train/loss=13.80]
Epoch 0: |          | 367/? [01:04<00:00,  5.71it/s, train/loss=2.990]
Epoch 0: |          | 368/? [01:04<00:00,  5.70it/s, train/loss=2.990]
Epoch 0: |          | 368/? [01:04<00:00,  5.70it/s, train/loss=24.20]
Epoch 0: |          | 369/? [01:04<00:00,  5.71it/s, train/loss=24.20]
Epoch 0: |          | 369/? [01:04<00:00,  5.71it/s, train/loss=2.900]
Epoch 0: |          | 370/? [01:04<00:00,  5.70it/s, train/loss=2.900]
Epoch 0: |          | 370/? [01:04<00:00,  5.70it/s, train/loss=19.60]
Epoch 0: |          | 371/? [01:04<00:00,  5.72it/s, train/loss=19.60]
Epoch 0: |          | 371/? [01:04<00:00,  5.72it/s, train/loss=2.840]
Epoch 0: |          | 372/? [01:05<00:00,  5.71it/s, train/loss=2.840]
Epoch 0: |          | 372/? [01:05<00:00,  5.71it/s, train/loss=24.40]
Epoch 0: |          | 373/? [01:05<00:00,  5.72it/s, train/loss=24.40]
Epoch 0: |          | 373/? [01:05<00:00,  5.72it/s, train/loss=2.810]
Epoch 0: |          | 374/? [01:05<00:00,  5.71it/s, train/loss=2.810]
Epoch 0: |          | 374/? [01:05<00:00,  5.71it/s, train/loss=10.40]
Epoch 0: |          | 375/? [01:05<00:00,  5.72it/s, train/loss=10.40]
Epoch 0: |          | 375/? [01:05<00:00,  5.72it/s, train/loss=2.780]
Epoch 0: |          | 376/? [01:05<00:00,  5.71it/s, train/loss=2.780]
Epoch 0: |          | 376/? [01:05<00:00,  5.71it/s, train/loss=34.00]
Epoch 0: |          | 377/? [01:05<00:00,  5.72it/s, train/loss=34.00]
Epoch 0: |          | 377/? [01:05<00:00,  5.72it/s, train/loss=2.710]
Epoch 0: |          | 378/? [01:06<00:00,  5.71it/s, train/loss=2.710]
Epoch 0: |          | 378/? [01:06<00:00,  5.71it/s, train/loss=24.10]
Epoch 0: |          | 379/? [01:06<00:00,  5.72it/s, train/loss=24.10]
Epoch 0: |          | 379/? [01:06<00:00,  5.72it/s, train/loss=2.650]
Epoch 0: |          | 380/? [01:06<00:00,  5.71it/s, train/loss=2.650]
Epoch 0: |          | 380/? [01:06<00:00,  5.71it/s, train/loss=17.60]
Epoch 0: |          | 381/? [01:06<00:00,  5.73it/s, train/loss=17.60]
Epoch 0: |          | 381/? [01:06<00:00,  5.73it/s, train/loss=2.650]
Epoch 0: |          | 382/? [01:06<00:00,  5.72it/s, train/loss=2.650]
Epoch 0: |          | 382/? [01:06<00:00,  5.72it/s, train/loss=31.10]
Epoch 0: |          | 383/? [01:06<00:00,  5.73it/s, train/loss=31.10]
Epoch 0: |          | 383/? [01:06<00:00,  5.73it/s, train/loss=2.690]
Epoch 0: |          | 384/? [01:07<00:00,  5.72it/s, train/loss=2.690]
Epoch 0: |          | 384/? [01:07<00:00,  5.72it/s, train/loss=27.60]
Epoch 0: |          | 385/? [01:07<00:00,  5.73it/s, train/loss=27.60]
Epoch 0: |          | 385/? [01:07<00:00,  5.73it/s, train/loss=2.720]
Epoch 0: |          | 386/? [01:07<00:00,  5.72it/s, train/loss=2.720]
Epoch 0: |          | 386/? [01:07<00:00,  5.72it/s, train/loss=19.10]
Epoch 0: |          | 387/? [01:07<00:00,  5.73it/s, train/loss=19.10]
Epoch 0: |          | 387/? [01:07<00:00,  5.73it/s, train/loss=2.690]
Epoch 0: |          | 388/? [01:07<00:00,  5.72it/s, train/loss=2.690]
Epoch 0: |          | 388/? [01:07<00:00,  5.72it/s, train/loss=9.580]
Epoch 0: |          | 389/? [01:07<00:00,  5.74it/s, train/loss=9.580]
Epoch 0: |          | 389/? [01:07<00:00,  5.74it/s, train/loss=2.640]
Epoch 0: |          | 390/? [01:08<00:00,  5.73it/s, train/loss=2.640]
Epoch 0: |          | 390/? [01:08<00:00,  5.73it/s, train/loss=16.10]
Epoch 0: |          | 391/? [01:08<00:00,  5.74it/s, train/loss=16.10]
Epoch 0: |          | 391/? [01:08<00:00,  5.74it/s, train/loss=2.580]
Epoch 0: |          | 392/? [01:08<00:00,  5.73it/s, train/loss=2.580]
Epoch 0: |          | 392/? [01:08<00:00,  5.73it/s, train/loss=37.50]
Epoch 0: |          | 393/? [01:08<00:00,  5.74it/s, train/loss=37.50]
Epoch 0: |          | 393/? [01:08<00:00,  5.74it/s, train/loss=2.530]
Epoch 0: |          | 394/? [01:08<00:00,  5.73it/s, train/loss=2.530]
Epoch 0: |          | 394/? [01:08<00:00,  5.73it/s, train/loss=15.50]
Epoch 0: |          | 395/? [01:08<00:00,  5.74it/s, train/loss=15.50]
Epoch 0: |          | 395/? [01:08<00:00,  5.74it/s, train/loss=2.500]
Epoch 0: |          | 396/? [01:09<00:00,  5.73it/s, train/loss=2.500]
Epoch 0: |          | 396/? [01:09<00:00,  5.73it/s, train/loss=19.40]
Epoch 0: |          | 397/? [01:09<00:00,  5.74it/s, train/loss=19.40]
Epoch 0: |          | 397/? [01:09<00:00,  5.74it/s, train/loss=2.490]
Epoch 0: |          | 398/? [01:09<00:00,  5.74it/s, train/loss=2.490]
Epoch 0: |          | 398/? [01:09<00:00,  5.73it/s, train/loss=19.80]
Epoch 0: |          | 399/? [01:09<00:00,  5.75it/s, train/loss=19.80]
Epoch 0: |          | 399/? [01:09<00:00,  5.75it/s, train/loss=2.490]
Epoch 0: |          | 400/? [01:09<00:00,  5.74it/s, train/loss=2.490]
Epoch 0: |          | 400/? [01:09<00:00,  5.74it/s, train/loss=34.10]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 62.45it/s]

Epoch 0: |          | 400/? [01:10<00:00,  5.65it/s, train/loss=34.10]
Epoch 0: |          | 401/? [01:11<00:00,  5.57it/s, train/loss=34.10]
Epoch 0: |          | 401/? [01:11<00:00,  5.57it/s, train/loss=2.480]
Epoch 0: |          | 402/? [01:12<00:00,  5.57it/s, train/loss=2.480]
Epoch 0: |          | 402/? [01:12<00:00,  5.57it/s, train/loss=15.00]
Epoch 0: |          | 403/? [01:12<00:00,  5.58it/s, train/loss=15.00]
Epoch 0: |          | 403/? [01:12<00:00,  5.58it/s, train/loss=2.480]
Epoch 0: |          | 404/? [01:12<00:00,  5.57it/s, train/loss=2.480]
Epoch 0: |          | 404/? [01:12<00:00,  5.57it/s, train/loss=23.00]
Epoch 0: |          | 405/? [01:12<00:00,  5.58it/s, train/loss=23.00]
Epoch 0: |          | 405/? [01:12<00:00,  5.58it/s, train/loss=2.470]
Epoch 0: |          | 406/? [01:12<00:00,  5.57it/s, train/loss=2.470]
Epoch 0: |          | 406/? [01:12<00:00,  5.57it/s, train/loss=9.820]
Epoch 0: |          | 407/? [01:12<00:00,  5.58it/s, train/loss=9.820]
Epoch 0: |          | 407/? [01:12<00:00,  5.58it/s, train/loss=2.460]
Epoch 0: |          | 408/? [01:13<00:00,  5.57it/s, train/loss=2.460]
Epoch 0: |          | 408/? [01:13<00:00,  5.57it/s, train/loss=18.50]
Epoch 0: |          | 409/? [01:13<00:00,  5.58it/s, train/loss=18.50]
Epoch 0: |          | 409/? [01:13<00:00,  5.58it/s, train/loss=2.450]
Epoch 0: |          | 410/? [01:13<00:00,  5.58it/s, train/loss=2.450]
Epoch 0: |          | 410/? [01:13<00:00,  5.58it/s, train/loss=21.70]
Epoch 0: |          | 411/? [01:13<00:00,  5.59it/s, train/loss=21.70]
Epoch 0: |          | 411/? [01:13<00:00,  5.59it/s, train/loss=2.470]
Epoch 0: |          | 412/? [01:13<00:00,  5.58it/s, train/loss=2.470]
Epoch 0: |          | 412/? [01:13<00:00,  5.58it/s, train/loss=25.70]
Epoch 0: |          | 413/? [01:13<00:00,  5.59it/s, train/loss=25.70]
Epoch 0: |          | 413/? [01:13<00:00,  5.59it/s, train/loss=2.480]
Epoch 0: |          | 414/? [01:14<00:00,  5.58it/s, train/loss=2.480]
Epoch 0: |          | 414/? [01:14<00:00,  5.58it/s, train/loss=49.00]
Epoch 0: |          | 415/? [01:14<00:00,  5.59it/s, train/loss=49.00]
Epoch 0: |          | 415/? [01:14<00:00,  5.59it/s, train/loss=2.460]
Epoch 0: |          | 416/? [01:14<00:00,  5.58it/s, train/loss=2.460]
Epoch 0: |          | 416/? [01:14<00:00,  5.58it/s, train/loss=14.30]
Epoch 0: |          | 417/? [01:14<00:00,  5.59it/s, train/loss=14.30]
Epoch 0: |          | 417/? [01:14<00:00,  5.59it/s, train/loss=2.490]
Epoch 0: |          | 418/? [01:14<00:00,  5.58it/s, train/loss=2.490]
Epoch 0: |          | 418/? [01:14<00:00,  5.58it/s, train/loss=12.00]
Epoch 0: |          | 419/? [01:14<00:00,  5.60it/s, train/loss=12.00]
Epoch 0: |          | 419/? [01:14<00:00,  5.60it/s, train/loss=2.520]
Epoch 0: |          | 420/? [01:15<00:00,  5.59it/s, train/loss=2.520]
Epoch 0: |          | 420/? [01:15<00:00,  5.59it/s, train/loss=10.10]
Epoch 0: |          | 421/? [01:15<00:00,  5.60it/s, train/loss=10.10]
Epoch 0: |          | 421/? [01:15<00:00,  5.60it/s, train/loss=2.520]
Epoch 0: |          | 422/? [01:15<00:00,  5.59it/s, train/loss=2.520]
Epoch 0: |          | 422/? [01:15<00:00,  5.59it/s, train/loss=27.00]
Epoch 0: |          | 423/? [01:15<00:00,  5.60it/s, train/loss=27.00]
Epoch 0: |          | 423/? [01:15<00:00,  5.60it/s, train/loss=2.470]
Epoch 0: |          | 424/? [01:15<00:00,  5.59it/s, train/loss=2.470]
Epoch 0: |          | 424/? [01:15<00:00,  5.59it/s, train/loss=22.70]
Epoch 0: |          | 425/? [01:15<00:00,  5.60it/s, train/loss=22.70]
Epoch 0: |          | 425/? [01:15<00:00,  5.60it/s, train/loss=2.420]
Epoch 0: |          | 426/? [01:16<00:00,  5.60it/s, train/loss=2.420]
Epoch 0: |          | 426/? [01:16<00:00,  5.60it/s, train/loss=9.020]
Epoch 0: |          | 427/? [01:16<00:00,  5.61it/s, train/loss=9.020]
Epoch 0: |          | 427/? [01:16<00:00,  5.61it/s, train/loss=2.360]
Epoch 0: |          | 428/? [01:16<00:00,  5.60it/s, train/loss=2.360]
Epoch 0: |          | 428/? [01:16<00:00,  5.60it/s, train/loss=41.80]
Epoch 0: |          | 429/? [01:16<00:00,  5.61it/s, train/loss=41.80]
Epoch 0: |          | 429/? [01:16<00:00,  5.61it/s, train/loss=2.330]
Epoch 0: |          | 430/? [01:16<00:00,  5.60it/s, train/loss=2.330]
Epoch 0: |          | 430/? [01:16<00:00,  5.60it/s, train/loss=36.30]
Epoch 0: |          | 431/? [01:16<00:00,  5.61it/s, train/loss=36.30]
Epoch 0: |          | 431/? [01:16<00:00,  5.61it/s, train/loss=2.320]
Epoch 0: |          | 432/? [01:17<00:00,  5.60it/s, train/loss=2.320]
Epoch 0: |          | 432/? [01:17<00:00,  5.60it/s, train/loss=16.50]
Epoch 0: |          | 433/? [01:17<00:00,  5.61it/s, train/loss=16.50]
Epoch 0: |          | 433/? [01:17<00:00,  5.61it/s, train/loss=2.340]
Epoch 0: |          | 434/? [01:17<00:00,  5.61it/s, train/loss=2.340]
Epoch 0: |          | 434/? [01:17<00:00,  5.61it/s, train/loss=23.30]
Epoch 0: |          | 435/? [01:17<00:00,  5.62it/s, train/loss=23.30]
Epoch 0: |          | 435/? [01:17<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 436/? [01:17<00:00,  5.61it/s, train/loss=2.350]
Epoch 0: |          | 436/? [01:17<00:00,  5.61it/s, train/loss=32.70]
Epoch 0: |          | 437/? [01:17<00:00,  5.62it/s, train/loss=32.70]
Epoch 0: |          | 437/? [01:17<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 438/? [01:18<00:00,  5.61it/s, train/loss=2.350]
Epoch 0: |          | 438/? [01:18<00:00,  5.61it/s, train/loss=33.70]
Epoch 0: |          | 439/? [01:18<00:00,  5.62it/s, train/loss=33.70]
Epoch 0: |          | 439/? [01:18<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 440/? [01:18<00:00,  5.61it/s, train/loss=2.350]
Epoch 0: |          | 440/? [01:18<00:00,  5.61it/s, train/loss=12.70]
Epoch 0: |          | 441/? [01:18<00:00,  5.62it/s, train/loss=12.70]
Epoch 0: |          | 441/? [01:18<00:00,  5.62it/s, train/loss=2.360]
Epoch 0: |          | 442/? [01:18<00:00,  5.62it/s, train/loss=2.360]
Epoch 0: |          | 442/? [01:18<00:00,  5.62it/s, train/loss=16.30]
Epoch 0: |          | 443/? [01:18<00:00,  5.63it/s, train/loss=16.30]
Epoch 0: |          | 443/? [01:18<00:00,  5.63it/s, train/loss=2.330]
Epoch 0: |          | 444/? [01:19<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 444/? [01:19<00:00,  5.62it/s, train/loss=21.40]
Epoch 0: |          | 445/? [01:19<00:00,  5.63it/s, train/loss=21.40]
Epoch 0: |          | 445/? [01:19<00:00,  5.63it/s, train/loss=2.320]
Epoch 0: |          | 446/? [01:19<00:00,  5.62it/s, train/loss=2.320]
Epoch 0: |          | 446/? [01:19<00:00,  5.62it/s, train/loss=19.00]
Epoch 0: |          | 447/? [01:19<00:00,  5.63it/s, train/loss=19.00]
Epoch 0: |          | 447/? [01:19<00:00,  5.63it/s, train/loss=2.330]
Epoch 0: |          | 448/? [01:19<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 448/? [01:19<00:00,  5.62it/s, train/loss=16.60]
Epoch 0: |          | 449/? [01:19<00:00,  5.63it/s, train/loss=16.60]
Epoch 0: |          | 449/? [01:19<00:00,  5.63it/s, train/loss=2.320]
Epoch 0: |          | 450/? [01:20<00:00,  5.62it/s, train/loss=2.320]
Epoch 0: |          | 450/? [01:20<00:00,  5.62it/s, train/loss=18.70]
Epoch 0: |          | 451/? [01:20<00:00,  5.63it/s, train/loss=18.70]
Epoch 0: |          | 451/? [01:20<00:00,  5.63it/s, train/loss=2.290]
Epoch 0: |          | 452/? [01:20<00:00,  5.62it/s, train/loss=2.290]
Epoch 0: |          | 452/? [01:20<00:00,  5.62it/s, train/loss=10.30]
Epoch 0: |          | 453/? [01:20<00:00,  5.63it/s, train/loss=10.30]
Epoch 0: |          | 453/? [01:20<00:00,  5.63it/s, train/loss=2.250]
Epoch 0: |          | 454/? [01:20<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 454/? [01:20<00:00,  5.62it/s, train/loss=25.40]
Epoch 0: |          | 455/? [01:20<00:00,  5.63it/s, train/loss=25.40]
Epoch 0: |          | 455/? [01:20<00:00,  5.63it/s, train/loss=2.210]
Epoch 0: |          | 456/? [01:21<00:00,  5.62it/s, train/loss=2.210]
Epoch 0: |          | 456/? [01:21<00:00,  5.62it/s, train/loss=8.850]
Epoch 0: |          | 457/? [01:21<00:00,  5.63it/s, train/loss=8.850]
Epoch 0: |          | 457/? [01:21<00:00,  5.63it/s, train/loss=2.160]
Epoch 0: |          | 458/? [01:21<00:00,  5.62it/s, train/loss=2.160]
Epoch 0: |          | 458/? [01:21<00:00,  5.62it/s, train/loss=13.90]
Epoch 0: |          | 459/? [01:21<00:00,  5.63it/s, train/loss=13.90]
Epoch 0: |          | 459/? [01:21<00:00,  5.63it/s, train/loss=2.120]
Epoch 0: |          | 460/? [01:21<00:00,  5.62it/s, train/loss=2.120]
Epoch 0: |          | 460/? [01:21<00:00,  5.62it/s, train/loss=32.80]
Epoch 0: |          | 461/? [01:21<00:00,  5.63it/s, train/loss=32.80]
Epoch 0: |          | 461/? [01:21<00:00,  5.63it/s, train/loss=2.120]
Epoch 0: |          | 462/? [01:22<00:00,  5.62it/s, train/loss=2.120]
Epoch 0: |          | 462/? [01:22<00:00,  5.62it/s, train/loss=12.30]
Epoch 0: |          | 463/? [01:22<00:00,  5.63it/s, train/loss=12.30]
Epoch 0: |          | 463/? [01:22<00:00,  5.63it/s, train/loss=2.140]
Epoch 0: |          | 464/? [01:22<00:00,  5.62it/s, train/loss=2.140]
Epoch 0: |          | 464/? [01:22<00:00,  5.62it/s, train/loss=24.00]
Epoch 0: |          | 465/? [01:22<00:00,  5.63it/s, train/loss=24.00]
Epoch 0: |          | 465/? [01:22<00:00,  5.63it/s, train/loss=2.120]
Epoch 0: |          | 466/? [01:22<00:00,  5.62it/s, train/loss=2.120]
Epoch 0: |          | 466/? [01:22<00:00,  5.62it/s, train/loss=28.10]
Epoch 0: |          | 467/? [01:22<00:00,  5.63it/s, train/loss=28.10]
Epoch 0: |          | 467/? [01:22<00:00,  5.63it/s, train/loss=2.070]
Epoch 0: |          | 468/? [01:23<00:00,  5.62it/s, train/loss=2.070]
Epoch 0: |          | 468/? [01:23<00:00,  5.62it/s, train/loss=12.20]
Epoch 0: |          | 469/? [01:23<00:00,  5.63it/s, train/loss=12.20]
Epoch 0: |          | 469/? [01:23<00:00,  5.63it/s, train/loss=2.060]
Epoch 0: |          | 470/? [01:23<00:00,  5.62it/s, train/loss=2.060]
Epoch 0: |          | 470/? [01:23<00:00,  5.62it/s, train/loss=20.10]
Epoch 0: |          | 471/? [01:23<00:00,  5.63it/s, train/loss=20.10]
Epoch 0: |          | 471/? [01:23<00:00,  5.63it/s, train/loss=2.090]
Epoch 0: |          | 472/? [01:24<00:00,  5.62it/s, train/loss=2.090]
Epoch 0: |          | 472/? [01:24<00:00,  5.62it/s, train/loss=16.70]
Epoch 0: |          | 473/? [01:24<00:00,  5.63it/s, train/loss=16.70]
Epoch 0: |          | 473/? [01:24<00:00,  5.63it/s, train/loss=2.170]
Epoch 0: |          | 474/? [01:24<00:00,  5.62it/s, train/loss=2.170]
Epoch 0: |          | 474/? [01:24<00:00,  5.62it/s, train/loss=36.50]
Epoch 0: |          | 475/? [01:24<00:00,  5.63it/s, train/loss=36.50]
Epoch 0: |          | 475/? [01:24<00:00,  5.63it/s, train/loss=2.250]
Epoch 0: |          | 476/? [01:24<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 476/? [01:24<00:00,  5.62it/s, train/loss=45.30]
Epoch 0: |          | 477/? [01:24<00:00,  5.63it/s, train/loss=45.30]
Epoch 0: |          | 477/? [01:24<00:00,  5.63it/s, train/loss=2.370]
Epoch 0: |          | 478/? [01:25<00:00,  5.62it/s, train/loss=2.370]
Epoch 0: |          | 478/? [01:25<00:00,  5.62it/s, train/loss=29.20]
Epoch 0: |          | 479/? [01:25<00:00,  5.63it/s, train/loss=29.20]
Epoch 0: |          | 479/? [01:25<00:00,  5.63it/s, train/loss=2.420]
Epoch 0: |          | 480/? [01:25<00:00,  5.62it/s, train/loss=2.420]
Epoch 0: |          | 480/? [01:25<00:00,  5.62it/s, train/loss=20.70]
Epoch 0: |          | 481/? [01:25<00:00,  5.63it/s, train/loss=20.70]
Epoch 0: |          | 481/? [01:25<00:00,  5.63it/s, train/loss=2.400]
Epoch 0: |          | 482/? [01:25<00:00,  5.62it/s, train/loss=2.400]
Epoch 0: |          | 482/? [01:25<00:00,  5.62it/s, train/loss=24.80]
Epoch 0: |          | 483/? [01:25<00:00,  5.62it/s, train/loss=24.80]
Epoch 0: |          | 483/? [01:25<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 484/? [01:26<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 484/? [01:26<00:00,  5.62it/s, train/loss=17.00]
Epoch 0: |          | 485/? [01:26<00:00,  5.62it/s, train/loss=17.00]
Epoch 0: |          | 485/? [01:26<00:00,  5.62it/s, train/loss=2.290]
Epoch 0: |          | 486/? [01:26<00:00,  5.62it/s, train/loss=2.290]
Epoch 0: |          | 486/? [01:26<00:00,  5.62it/s, train/loss=29.70]
Epoch 0: |          | 487/? [01:26<00:00,  5.62it/s, train/loss=29.70]
Epoch 0: |          | 487/? [01:26<00:00,  5.62it/s, train/loss=2.260]
Epoch 0: |          | 488/? [01:26<00:00,  5.62it/s, train/loss=2.260]
Epoch 0: |          | 488/? [01:26<00:00,  5.62it/s, train/loss=24.80]
Epoch 0: |          | 489/? [01:26<00:00,  5.62it/s, train/loss=24.80]
Epoch 0: |          | 489/? [01:26<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 490/? [01:27<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 490/? [01:27<00:00,  5.62it/s, train/loss=34.60]
Epoch 0: |          | 491/? [01:27<00:00,  5.62it/s, train/loss=34.60]
Epoch 0: |          | 491/? [01:27<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 492/? [01:27<00:00,  5.62it/s, train/loss=2.250]
Epoch 0: |          | 492/? [01:27<00:00,  5.62it/s, train/loss=27.40]
Epoch 0: |          | 493/? [01:27<00:00,  5.62it/s, train/loss=27.40]
Epoch 0: |          | 493/? [01:27<00:00,  5.62it/s, train/loss=2.270]
Epoch 0: |          | 494/? [01:27<00:00,  5.62it/s, train/loss=2.270]
Epoch 0: |          | 494/? [01:27<00:00,  5.62it/s, train/loss=17.20]
Epoch 0: |          | 495/? [01:28<00:00,  5.62it/s, train/loss=17.20]
Epoch 0: |          | 495/? [01:28<00:00,  5.62it/s, train/loss=2.320]
Epoch 0: |          | 496/? [01:28<00:00,  5.62it/s, train/loss=2.320]
Epoch 0: |          | 496/? [01:28<00:00,  5.62it/s, train/loss=31.80]
Epoch 0: |          | 497/? [01:28<00:00,  5.62it/s, train/loss=31.80]
Epoch 0: |          | 497/? [01:28<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 498/? [01:28<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 498/? [01:28<00:00,  5.62it/s, train/loss=33.30]
Epoch 0: |          | 499/? [01:28<00:00,  5.62it/s, train/loss=33.30]
Epoch 0: |          | 499/? [01:28<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 500/? [01:29<00:00,  5.62it/s, train/loss=2.350]
Epoch 0: |          | 500/? [01:29<00:00,  5.62it/s, train/loss=15.50]
Epoch 0: |          | 501/? [01:29<00:00,  5.62it/s, train/loss=15.50]
Epoch 0: |          | 501/? [01:29<00:00,  5.62it/s, train/loss=2.380]
Epoch 0: |          | 502/? [01:29<00:00,  5.62it/s, train/loss=2.380]
Epoch 0: |          | 502/? [01:29<00:00,  5.62it/s, train/loss=11.30]
Epoch 0: |          | 503/? [01:29<00:00,  5.62it/s, train/loss=11.30]
Epoch 0: |          | 503/? [01:29<00:00,  5.62it/s, train/loss=2.360]
Epoch 0: |          | 504/? [01:29<00:00,  5.62it/s, train/loss=2.360]
Epoch 0: |          | 504/? [01:29<00:00,  5.62it/s, train/loss=9.480]
Epoch 0: |          | 505/? [01:29<00:00,  5.62it/s, train/loss=9.480]
Epoch 0: |          | 505/? [01:29<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 506/? [01:30<00:00,  5.62it/s, train/loss=2.330]
Epoch 0: |          | 506/? [01:30<00:00,  5.62it/s, train/loss=15.00]
Epoch 0: |          | 507/? [01:30<00:00,  5.62it/s, train/loss=15.00]
Epoch 0: |          | 507/? [01:30<00:00,  5.62it/s, train/loss=2.290]
Epoch 0: |          | 508/? [01:30<00:00,  5.62it/s, train/loss=2.290]
Epoch 0: |          | 508/? [01:30<00:00,  5.62it/s, train/loss=9.350]
Epoch 0: |          | 509/? [01:30<00:00,  5.62it/s, train/loss=9.350]
Epoch 0: |          | 509/? [01:30<00:00,  5.62it/s, train/loss=2.240]
Epoch 0: |          | 510/? [01:30<00:00,  5.62it/s, train/loss=2.240]
Epoch 0: |          | 510/? [01:30<00:00,  5.62it/s, train/loss=21.50]
Epoch 0: |          | 511/? [01:30<00:00,  5.63it/s, train/loss=21.50]
Epoch 0: |          | 511/? [01:30<00:00,  5.63it/s, train/loss=2.190]
Epoch 0: |          | 512/? [01:31<00:00,  5.62it/s, train/loss=2.190]
Epoch 0: |          | 512/? [01:31<00:00,  5.62it/s, train/loss=24.70]
Epoch 0: |          | 513/? [01:31<00:00,  5.63it/s, train/loss=24.70]
Epoch 0: |          | 513/? [01:31<00:00,  5.63it/s, train/loss=2.150]
Epoch 0: |          | 514/? [01:31<00:00,  5.62it/s, train/loss=2.150]
Epoch 0: |          | 514/? [01:31<00:00,  5.62it/s, train/loss=27.40]
Epoch 0: |          | 515/? [01:31<00:00,  5.63it/s, train/loss=27.40]
Epoch 0: |          | 515/? [01:31<00:00,  5.63it/s, train/loss=2.130]
Epoch 0: |          | 516/? [01:31<00:00,  5.62it/s, train/loss=2.130]
Epoch 0: |          | 516/? [01:31<00:00,  5.62it/s, train/loss=33.50]
Epoch 0: |          | 517/? [01:31<00:00,  5.63it/s, train/loss=33.50]
Epoch 0: |          | 517/? [01:31<00:00,  5.63it/s, train/loss=2.140]
Epoch 0: |          | 518/? [01:32<00:00,  5.63it/s, train/loss=2.140]
Epoch 0: |          | 518/? [01:32<00:00,  5.62it/s, train/loss=14.40]
Epoch 0: |          | 519/? [01:32<00:00,  5.63it/s, train/loss=14.40]
Epoch 0: |          | 519/? [01:32<00:00,  5.63it/s, train/loss=2.180]
Epoch 0: |          | 520/? [01:32<00:00,  5.63it/s, train/loss=2.180]
Epoch 0: |          | 520/? [01:32<00:00,  5.63it/s, train/loss=60.00]
Epoch 0: |          | 521/? [01:32<00:00,  5.64it/s, train/loss=60.00]
Epoch 0: |          | 521/? [01:32<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 522/? [01:32<00:00,  5.63it/s, train/loss=2.210]
Epoch 0: |          | 522/? [01:32<00:00,  5.63it/s, train/loss=20.10]
Epoch 0: |          | 523/? [01:32<00:00,  5.64it/s, train/loss=20.10]
Epoch 0: |          | 523/? [01:32<00:00,  5.64it/s, train/loss=2.260]
Epoch 0: |          | 524/? [01:33<00:00,  5.63it/s, train/loss=2.260]
Epoch 0: |          | 524/? [01:33<00:00,  5.63it/s, train/loss=32.00]
Epoch 0: |          | 525/? [01:33<00:00,  5.64it/s, train/loss=32.00]
Epoch 0: |          | 525/? [01:33<00:00,  5.64it/s, train/loss=2.300]
Epoch 0: |          | 526/? [01:33<00:00,  5.63it/s, train/loss=2.300]
Epoch 0: |          | 526/? [01:33<00:00,  5.63it/s, train/loss=32.60]
Epoch 0: |          | 527/? [01:33<00:00,  5.64it/s, train/loss=32.60]
Epoch 0: |          | 527/? [01:33<00:00,  5.64it/s, train/loss=2.300]
Epoch 0: |          | 528/? [01:33<00:00,  5.63it/s, train/loss=2.300]
Epoch 0: |          | 528/? [01:33<00:00,  5.63it/s, train/loss=29.10]
Epoch 0: |          | 529/? [01:33<00:00,  5.64it/s, train/loss=29.10]
Epoch 0: |          | 529/? [01:33<00:00,  5.64it/s, train/loss=2.290]
Epoch 0: |          | 530/? [01:34<00:00,  5.63it/s, train/loss=2.290]
Epoch 0: |          | 530/? [01:34<00:00,  5.63it/s, train/loss=37.40]
Epoch 0: |          | 531/? [01:34<00:00,  5.64it/s, train/loss=37.40]
Epoch 0: |          | 531/? [01:34<00:00,  5.64it/s, train/loss=2.250]
Epoch 0: |          | 532/? [01:34<00:00,  5.64it/s, train/loss=2.250]
Epoch 0: |          | 532/? [01:34<00:00,  5.64it/s, train/loss=50.00]
Epoch 0: |          | 533/? [01:34<00:00,  5.64it/s, train/loss=50.00]
Epoch 0: |          | 533/? [01:34<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 534/? [01:34<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 534/? [01:34<00:00,  5.64it/s, train/loss=18.50]
Epoch 0: |          | 535/? [01:34<00:00,  5.65it/s, train/loss=18.50]
Epoch 0: |          | 535/? [01:34<00:00,  5.65it/s, train/loss=2.210]
Epoch 0: |          | 536/? [01:35<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 536/? [01:35<00:00,  5.64it/s, train/loss=15.60]
Epoch 0: |          | 537/? [01:35<00:00,  5.65it/s, train/loss=15.60]
Epoch 0: |          | 537/? [01:35<00:00,  5.65it/s, train/loss=2.220]
Epoch 0: |          | 538/? [01:35<00:00,  5.64it/s, train/loss=2.220]
Epoch 0: |          | 538/? [01:35<00:00,  5.64it/s, train/loss=10.90]
Epoch 0: |          | 539/? [01:35<00:00,  5.65it/s, train/loss=10.90]
Epoch 0: |          | 539/? [01:35<00:00,  5.65it/s, train/loss=2.210]
Epoch 0: |          | 540/? [01:35<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 540/? [01:35<00:00,  5.64it/s, train/loss=46.40]
Epoch 0: |          | 541/? [01:35<00:00,  5.65it/s, train/loss=46.40]
Epoch 0: |          | 541/? [01:35<00:00,  5.65it/s, train/loss=2.180]
Epoch 0: |          | 542/? [01:36<00:00,  5.64it/s, train/loss=2.180]
Epoch 0: |          | 542/? [01:36<00:00,  5.64it/s, train/loss=11.40]
Epoch 0: |          | 543/? [01:36<00:00,  5.65it/s, train/loss=11.40]
Epoch 0: |          | 543/? [01:36<00:00,  5.65it/s, train/loss=2.160]
Epoch 0: |          | 544/? [01:36<00:00,  5.65it/s, train/loss=2.160]
Epoch 0: |          | 544/? [01:36<00:00,  5.65it/s, train/loss=48.70]
Epoch 0: |          | 545/? [01:36<00:00,  5.65it/s, train/loss=48.70]
Epoch 0: |          | 545/? [01:36<00:00,  5.65it/s, train/loss=2.150]
Epoch 0: |          | 546/? [01:36<00:00,  5.65it/s, train/loss=2.150]
Epoch 0: |          | 546/? [01:36<00:00,  5.65it/s, train/loss=22.10]
Epoch 0: |          | 547/? [01:36<00:00,  5.66it/s, train/loss=22.10]
Epoch 0: |          | 547/? [01:36<00:00,  5.65it/s, train/loss=2.240]
Epoch 0: |          | 548/? [01:37<00:00,  5.65it/s, train/loss=2.240]
Epoch 0: |          | 548/? [01:37<00:00,  5.65it/s, train/loss=29.10]
Epoch 0: |          | 549/? [01:37<00:00,  5.66it/s, train/loss=29.10]
Epoch 0: |          | 549/? [01:37<00:00,  5.66it/s, train/loss=2.350]
Epoch 0: |          | 550/? [01:37<00:00,  5.65it/s, train/loss=2.350]
Epoch 0: |          | 550/? [01:37<00:00,  5.65it/s, train/loss=12.00]
Epoch 0: |          | 551/? [01:37<00:00,  5.66it/s, train/loss=12.00]
Epoch 0: |          | 551/? [01:37<00:00,  5.66it/s, train/loss=2.400]
Epoch 0: |          | 552/? [01:37<00:00,  5.65it/s, train/loss=2.400]
Epoch 0: |          | 552/? [01:37<00:00,  5.65it/s, train/loss=17.40]
Epoch 0: |          | 553/? [01:37<00:00,  5.66it/s, train/loss=17.40]
Epoch 0: |          | 553/? [01:37<00:00,  5.66it/s, train/loss=2.390]
Epoch 0: |          | 554/? [01:37<00:00,  5.65it/s, train/loss=2.390]
Epoch 0: |          | 554/? [01:37<00:00,  5.65it/s, train/loss=17.00]
Epoch 0: |          | 555/? [01:38<00:00,  5.66it/s, train/loss=17.00]
Epoch 0: |          | 555/? [01:38<00:00,  5.66it/s, train/loss=2.330]
Epoch 0: |          | 556/? [01:38<00:00,  5.66it/s, train/loss=2.330]
Epoch 0: |          | 556/? [01:38<00:00,  5.66it/s, train/loss=19.20]
Epoch 0: |          | 557/? [01:38<00:00,  5.66it/s, train/loss=19.20]
Epoch 0: |          | 557/? [01:38<00:00,  5.66it/s, train/loss=2.260]
Epoch 0: |          | 558/? [01:38<00:00,  5.66it/s, train/loss=2.260]
Epoch 0: |          | 558/? [01:38<00:00,  5.66it/s, train/loss=24.90]
Epoch 0: |          | 559/? [01:38<00:00,  5.66it/s, train/loss=24.90]
Epoch 0: |          | 559/? [01:38<00:00,  5.66it/s, train/loss=2.240]
Epoch 0: |          | 560/? [01:38<00:00,  5.66it/s, train/loss=2.240]
Epoch 0: |          | 560/? [01:38<00:00,  5.66it/s, train/loss=37.70]
Epoch 0: |          | 561/? [01:39<00:00,  5.67it/s, train/loss=37.70]
Epoch 0: |          | 561/? [01:39<00:00,  5.67it/s, train/loss=2.240]
Epoch 0: |          | 562/? [01:39<00:00,  5.66it/s, train/loss=2.240]
Epoch 0: |          | 562/? [01:39<00:00,  5.66it/s, train/loss=29.60]
Epoch 0: |          | 563/? [01:39<00:00,  5.67it/s, train/loss=29.60]
Epoch 0: |          | 563/? [01:39<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 564/? [01:39<00:00,  5.66it/s, train/loss=2.200]
Epoch 0: |          | 564/? [01:39<00:00,  5.66it/s, train/loss=13.10]
Epoch 0: |          | 565/? [01:39<00:00,  5.67it/s, train/loss=13.10]
Epoch 0: |          | 565/? [01:39<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 566/? [01:39<00:00,  5.66it/s, train/loss=2.180]
Epoch 0: |          | 566/? [01:39<00:00,  5.66it/s, train/loss=14.70]
Epoch 0: |          | 567/? [01:39<00:00,  5.67it/s, train/loss=14.70]
Epoch 0: |          | 567/? [01:39<00:00,  5.67it/s, train/loss=2.170]
Epoch 0: |          | 568/? [01:40<00:00,  5.66it/s, train/loss=2.170]
Epoch 0: |          | 568/? [01:40<00:00,  5.66it/s, train/loss=25.70]
Epoch 0: |          | 569/? [01:40<00:00,  5.67it/s, train/loss=25.70]
Epoch 0: |          | 569/? [01:40<00:00,  5.67it/s, train/loss=2.150]
Epoch 0: |          | 570/? [01:40<00:00,  5.67it/s, train/loss=2.150]
Epoch 0: |          | 570/? [01:40<00:00,  5.67it/s, train/loss=20.20]
Epoch 0: |          | 571/? [01:40<00:00,  5.67it/s, train/loss=20.20]
Epoch 0: |          | 571/? [01:40<00:00,  5.67it/s, train/loss=2.120]
Epoch 0: |          | 572/? [01:40<00:00,  5.66it/s, train/loss=2.120]
Epoch 0: |          | 572/? [01:40<00:00,  5.66it/s, train/loss=24.90]
Epoch 0: |          | 573/? [01:41<00:00,  5.67it/s, train/loss=24.90]
Epoch 0: |          | 573/? [01:41<00:00,  5.67it/s, train/loss=2.140]
Epoch 0: |          | 574/? [01:41<00:00,  5.67it/s, train/loss=2.140]
Epoch 0: |          | 574/? [01:41<00:00,  5.67it/s, train/loss=19.00]
Epoch 0: |          | 575/? [01:41<00:00,  5.67it/s, train/loss=19.00]
Epoch 0: |          | 575/? [01:41<00:00,  5.67it/s, train/loss=2.190]
Epoch 0: |          | 576/? [01:41<00:00,  5.67it/s, train/loss=2.190]
Epoch 0: |          | 576/? [01:41<00:00,  5.67it/s, train/loss=11.50]
Epoch 0: |          | 577/? [01:41<00:00,  5.67it/s, train/loss=11.50]
Epoch 0: |          | 577/? [01:41<00:00,  5.67it/s, train/loss=2.240]
Epoch 0: |          | 578/? [01:41<00:00,  5.67it/s, train/loss=2.240]
Epoch 0: |          | 578/? [01:41<00:00,  5.67it/s, train/loss=19.60]
Epoch 0: |          | 579/? [01:42<00:00,  5.68it/s, train/loss=19.60]
Epoch 0: |          | 579/? [01:42<00:00,  5.68it/s, train/loss=2.230]
Epoch 0: |          | 580/? [01:42<00:00,  5.67it/s, train/loss=2.230]
Epoch 0: |          | 580/? [01:42<00:00,  5.67it/s, train/loss=39.90]
Epoch 0: |          | 581/? [01:42<00:00,  5.68it/s, train/loss=39.90]
Epoch 0: |          | 581/? [01:42<00:00,  5.68it/s, train/loss=2.140]
Epoch 0: |          | 582/? [01:42<00:00,  5.67it/s, train/loss=2.140]
Epoch 0: |          | 582/? [01:42<00:00,  5.67it/s, train/loss=14.50]
Epoch 0: |          | 583/? [01:42<00:00,  5.68it/s, train/loss=14.50]
Epoch 0: |          | 583/? [01:42<00:00,  5.68it/s, train/loss=2.050]
Epoch 0: |          | 584/? [01:42<00:00,  5.67it/s, train/loss=2.050]
Epoch 0: |          | 584/? [01:42<00:00,  5.67it/s, train/loss=28.80]
Epoch 0: |          | 585/? [01:43<00:00,  5.68it/s, train/loss=28.80]
Epoch 0: |          | 585/? [01:43<00:00,  5.68it/s, train/loss=2.020]
Epoch 0: |          | 586/? [01:43<00:00,  5.67it/s, train/loss=2.020]
Epoch 0: |          | 586/? [01:43<00:00,  5.67it/s, train/loss=32.90]
Epoch 0: |          | 587/? [01:43<00:00,  5.68it/s, train/loss=32.90]
Epoch 0: |          | 587/? [01:43<00:00,  5.68it/s, train/loss=2.000]
Epoch 0: |          | 588/? [01:43<00:00,  5.67it/s, train/loss=2.000]
Epoch 0: |          | 588/? [01:43<00:00,  5.67it/s, train/loss=26.10]
Epoch 0: |          | 589/? [01:43<00:00,  5.68it/s, train/loss=26.10]
Epoch 0: |          | 589/? [01:43<00:00,  5.68it/s, train/loss=2.020]
Epoch 0: |          | 590/? [01:43<00:00,  5.68it/s, train/loss=2.020]
Epoch 0: |          | 590/? [01:43<00:00,  5.68it/s, train/loss=37.00]
Epoch 0: |          | 591/? [01:43<00:00,  5.68it/s, train/loss=37.00]
Epoch 0: |          | 591/? [01:43<00:00,  5.68it/s, train/loss=2.080]
Epoch 0: |          | 592/? [01:44<00:00,  5.68it/s, train/loss=2.080]
Epoch 0: |          | 592/? [01:44<00:00,  5.68it/s, train/loss=17.80]
Epoch 0: |          | 593/? [01:44<00:00,  5.68it/s, train/loss=17.80]
Epoch 0: |          | 593/? [01:44<00:00,  5.68it/s, train/loss=2.140]
Epoch 0: |          | 594/? [01:44<00:00,  5.68it/s, train/loss=2.140]
Epoch 0: |          | 594/? [01:44<00:00,  5.68it/s, train/loss=27.40]
Epoch 0: |          | 595/? [01:44<00:00,  5.69it/s, train/loss=27.40]
Epoch 0: |          | 595/? [01:44<00:00,  5.69it/s, train/loss=2.160]
Epoch 0: |          | 596/? [01:44<00:00,  5.68it/s, train/loss=2.160]
Epoch 0: |          | 596/? [01:44<00:00,  5.68it/s, train/loss=26.80]
Epoch 0: |          | 597/? [01:44<00:00,  5.69it/s, train/loss=26.80]
Epoch 0: |          | 597/? [01:44<00:00,  5.69it/s, train/loss=2.160]
Epoch 0: |          | 598/? [01:45<00:00,  5.68it/s, train/loss=2.160]
Epoch 0: |          | 598/? [01:45<00:00,  5.68it/s, train/loss=32.30]
Epoch 0: |          | 599/? [01:45<00:00,  5.69it/s, train/loss=32.30]
Epoch 0: |          | 599/? [01:45<00:00,  5.69it/s, train/loss=2.180]
Epoch 0: |          | 600/? [01:45<00:00,  5.68it/s, train/loss=2.180]
Epoch 0: |          | 600/? [01:45<00:00,  5.68it/s, train/loss=27.90]
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Epoch 0: |          | 600/? [01:46<00:00,  5.62it/s, train/loss=27.90]
Epoch 0: |          | 601/? [01:47<00:00,  5.60it/s, train/loss=27.90]
Epoch 0: |          | 601/? [01:47<00:00,  5.60it/s, train/loss=2.240]
Epoch 0: |          | 602/? [01:47<00:00,  5.60it/s, train/loss=2.240]
Epoch 0: |          | 602/? [01:47<00:00,  5.60it/s, train/loss=27.10]
Epoch 0: |          | 603/? [01:47<00:00,  5.61it/s, train/loss=27.10]
Epoch 0: |          | 603/? [01:47<00:00,  5.61it/s, train/loss=2.310]
Epoch 0: |          | 604/? [01:47<00:00,  5.60it/s, train/loss=2.310]
Epoch 0: |          | 604/? [01:47<00:00,  5.60it/s, train/loss=33.40]
Epoch 0: |          | 605/? [01:47<00:00,  5.61it/s, train/loss=33.40]
Epoch 0: |          | 605/? [01:47<00:00,  5.61it/s, train/loss=2.350]
Epoch 0: |          | 606/? [01:48<00:00,  5.60it/s, train/loss=2.350]
Epoch 0: |          | 606/? [01:48<00:00,  5.60it/s, train/loss=13.90]
Epoch 0: |          | 607/? [01:48<00:00,  5.61it/s, train/loss=13.90]
Epoch 0: |          | 607/? [01:48<00:00,  5.61it/s, train/loss=2.310]
Epoch 0: |          | 608/? [01:48<00:00,  5.60it/s, train/loss=2.310]
Epoch 0: |          | 608/? [01:48<00:00,  5.60it/s, train/loss=19.40]
Epoch 0: |          | 609/? [01:48<00:00,  5.61it/s, train/loss=19.40]
Epoch 0: |          | 609/? [01:48<00:00,  5.61it/s, train/loss=2.240]
Epoch 0: |          | 610/? [01:48<00:00,  5.60it/s, train/loss=2.240]
Epoch 0: |          | 610/? [01:48<00:00,  5.60it/s, train/loss=10.60]
Epoch 0: |          | 611/? [01:48<00:00,  5.61it/s, train/loss=10.60]
Epoch 0: |          | 611/? [01:48<00:00,  5.61it/s, train/loss=2.180]
Epoch 0: |          | 612/? [01:49<00:00,  5.61it/s, train/loss=2.180]
Epoch 0: |          | 612/? [01:49<00:00,  5.61it/s, train/loss=23.00]
Epoch 0: |          | 613/? [01:49<00:00,  5.61it/s, train/loss=23.00]
Epoch 0: |          | 613/? [01:49<00:00,  5.61it/s, train/loss=2.130]
Epoch 0: |          | 614/? [01:49<00:00,  5.61it/s, train/loss=2.130]
Epoch 0: |          | 614/? [01:49<00:00,  5.61it/s, train/loss=15.30]
Epoch 0: |          | 615/? [01:49<00:00,  5.61it/s, train/loss=15.30]
Epoch 0: |          | 615/? [01:49<00:00,  5.61it/s, train/loss=2.090]
Epoch 0: |          | 616/? [01:49<00:00,  5.61it/s, train/loss=2.090]
Epoch 0: |          | 616/? [01:49<00:00,  5.61it/s, train/loss=34.00]
Epoch 0: |          | 617/? [01:49<00:00,  5.62it/s, train/loss=34.00]
Epoch 0: |          | 617/? [01:49<00:00,  5.62it/s, train/loss=2.060]
Epoch 0: |          | 618/? [01:50<00:00,  5.61it/s, train/loss=2.060]
Epoch 0: |          | 618/? [01:50<00:00,  5.61it/s, train/loss=10.70]
Epoch 0: |          | 619/? [01:50<00:00,  5.62it/s, train/loss=10.70]
Epoch 0: |          | 619/? [01:50<00:00,  5.62it/s, train/loss=2.020]
Epoch 0: |          | 620/? [01:50<00:00,  5.61it/s, train/loss=2.020]
Epoch 0: |          | 620/? [01:50<00:00,  5.61it/s, train/loss=12.90]
Epoch 0: |          | 621/? [01:50<00:00,  5.62it/s, train/loss=12.90]
Epoch 0: |          | 621/? [01:50<00:00,  5.62it/s, train/loss=1.970]
Epoch 0: |          | 622/? [01:50<00:00,  5.61it/s, train/loss=1.970]
Epoch 0: |          | 622/? [01:50<00:00,  5.61it/s, train/loss=21.60]
Epoch 0: |          | 623/? [01:50<00:00,  5.62it/s, train/loss=21.60]
Epoch 0: |          | 623/? [01:50<00:00,  5.62it/s, train/loss=1.930]
Epoch 0: |          | 624/? [01:51<00:00,  5.61it/s, train/loss=1.930]
Epoch 0: |          | 624/? [01:51<00:00,  5.61it/s, train/loss=36.80]
Epoch 0: |          | 625/? [01:51<00:00,  5.62it/s, train/loss=36.80]
Epoch 0: |          | 625/? [01:51<00:00,  5.62it/s, train/loss=1.920]
Epoch 0: |          | 626/? [01:51<00:00,  5.62it/s, train/loss=1.920]
Epoch 0: |          | 626/? [01:51<00:00,  5.62it/s, train/loss=26.50]
Epoch 0: |          | 627/? [01:51<00:00,  5.62it/s, train/loss=26.50]
Epoch 0: |          | 627/? [01:51<00:00,  5.62it/s, train/loss=1.930]
Epoch 0: |          | 628/? [01:51<00:00,  5.62it/s, train/loss=1.930]
Epoch 0: |          | 628/? [01:51<00:00,  5.62it/s, train/loss=28.90]
Epoch 0: |          | 629/? [01:51<00:00,  5.62it/s, train/loss=28.90]
Epoch 0: |          | 629/? [01:51<00:00,  5.62it/s, train/loss=1.910]
Epoch 0: |          | 630/? [01:52<00:00,  5.62it/s, train/loss=1.910]
Epoch 0: |          | 630/? [01:52<00:00,  5.62it/s, train/loss=35.60]
Epoch 0: |          | 631/? [01:52<00:00,  5.63it/s, train/loss=35.60]
Epoch 0: |          | 631/? [01:52<00:00,  5.63it/s, train/loss=1.900]
Epoch 0: |          | 632/? [01:52<00:00,  5.62it/s, train/loss=1.900]
Epoch 0: |          | 632/? [01:52<00:00,  5.62it/s, train/loss=15.00]
Epoch 0: |          | 633/? [01:52<00:00,  5.63it/s, train/loss=15.00]
Epoch 0: |          | 633/? [01:52<00:00,  5.63it/s, train/loss=1.970]
Epoch 0: |          | 634/? [01:52<00:00,  5.62it/s, train/loss=1.970]
Epoch 0: |          | 634/? [01:52<00:00,  5.62it/s, train/loss=19.70]
Epoch 0: |          | 635/? [01:52<00:00,  5.63it/s, train/loss=19.70]
Epoch 0: |          | 635/? [01:52<00:00,  5.63it/s, train/loss=2.050]
Epoch 0: |          | 636/? [01:53<00:00,  5.62it/s, train/loss=2.050]
Epoch 0: |          | 636/? [01:53<00:00,  5.62it/s, train/loss=33.90]
Epoch 0: |          | 637/? [01:53<00:00,  5.63it/s, train/loss=33.90]
Epoch 0: |          | 637/? [01:53<00:00,  5.63it/s, train/loss=2.140]
Epoch 0: |          | 638/? [01:53<00:00,  5.63it/s, train/loss=2.140]
Epoch 0: |          | 638/? [01:53<00:00,  5.62it/s, train/loss=30.40]
Epoch 0: |          | 639/? [01:53<00:00,  5.63it/s, train/loss=30.40]
Epoch 0: |          | 639/? [01:53<00:00,  5.63it/s, train/loss=2.220]
Epoch 0: |          | 640/? [01:53<00:00,  5.63it/s, train/loss=2.220]
Epoch 0: |          | 640/? [01:53<00:00,  5.63it/s, train/loss=25.00]
Epoch 0: |          | 641/? [01:53<00:00,  5.63it/s, train/loss=25.00]
Epoch 0: |          | 641/? [01:53<00:00,  5.63it/s, train/loss=2.240]
Epoch 0: |          | 642/? [01:54<00:00,  5.63it/s, train/loss=2.240]
Epoch 0: |          | 642/? [01:54<00:00,  5.63it/s, train/loss=10.00]
Epoch 0: |          | 643/? [01:54<00:00,  5.63it/s, train/loss=10.00]
Epoch 0: |          | 643/? [01:54<00:00,  5.63it/s, train/loss=2.220]
Epoch 0: |          | 644/? [01:54<00:00,  5.63it/s, train/loss=2.220]
Epoch 0: |          | 644/? [01:54<00:00,  5.63it/s, train/loss=22.80]
Epoch 0: |          | 645/? [01:54<00:00,  5.63it/s, train/loss=22.80]
Epoch 0: |          | 645/? [01:54<00:00,  5.63it/s, train/loss=2.190]
Epoch 0: |          | 646/? [01:54<00:00,  5.63it/s, train/loss=2.190]
Epoch 0: |          | 646/? [01:54<00:00,  5.63it/s, train/loss=22.90]
Epoch 0: |          | 647/? [01:54<00:00,  5.64it/s, train/loss=22.90]
Epoch 0: |          | 647/? [01:54<00:00,  5.64it/s, train/loss=2.190]
Epoch 0: |          | 648/? [01:55<00:00,  5.63it/s, train/loss=2.190]
Epoch 0: |          | 648/? [01:55<00:00,  5.63it/s, train/loss=42.40]
Epoch 0: |          | 649/? [01:55<00:00,  5.64it/s, train/loss=42.40]
Epoch 0: |          | 649/? [01:55<00:00,  5.64it/s, train/loss=2.190]
Epoch 0: |          | 650/? [01:55<00:00,  5.63it/s, train/loss=2.190]
Epoch 0: |          | 650/? [01:55<00:00,  5.63it/s, train/loss=61.90]
Epoch 0: |          | 651/? [01:55<00:00,  5.64it/s, train/loss=61.90]
Epoch 0: |          | 651/? [01:55<00:00,  5.64it/s, train/loss=2.180]
Epoch 0: |          | 652/? [01:55<00:00,  5.63it/s, train/loss=2.180]
Epoch 0: |          | 652/? [01:55<00:00,  5.63it/s, train/loss=38.10]
Epoch 0: |          | 653/? [01:55<00:00,  5.64it/s, train/loss=38.10]
Epoch 0: |          | 653/? [01:55<00:00,  5.64it/s, train/loss=2.180]
Epoch 0: |          | 654/? [01:56<00:00,  5.63it/s, train/loss=2.180]
Epoch 0: |          | 654/? [01:56<00:00,  5.63it/s, train/loss=20.60]
Epoch 0: |          | 655/? [01:56<00:00,  5.64it/s, train/loss=20.60]
Epoch 0: |          | 655/? [01:56<00:00,  5.64it/s, train/loss=2.230]
Epoch 0: |          | 656/? [01:56<00:00,  5.64it/s, train/loss=2.230]
Epoch 0: |          | 656/? [01:56<00:00,  5.64it/s, train/loss=18.20]
Epoch 0: |          | 657/? [01:56<00:00,  5.64it/s, train/loss=18.20]
Epoch 0: |          | 657/? [01:56<00:00,  5.64it/s, train/loss=2.270]
Epoch 0: |          | 658/? [01:56<00:00,  5.64it/s, train/loss=2.270]
Epoch 0: |          | 658/? [01:56<00:00,  5.64it/s, train/loss=17.30]
Epoch 0: |          | 659/? [01:56<00:00,  5.64it/s, train/loss=17.30]
Epoch 0: |          | 659/? [01:56<00:00,  5.64it/s, train/loss=2.290]
Epoch 0: |          | 660/? [01:57<00:00,  5.64it/s, train/loss=2.290]
Epoch 0: |          | 660/? [01:57<00:00,  5.64it/s, train/loss=11.40]
Epoch 0: |          | 661/? [01:57<00:00,  5.64it/s, train/loss=11.40]
Epoch 0: |          | 661/? [01:57<00:00,  5.64it/s, train/loss=2.270]
Epoch 0: |          | 662/? [01:57<00:00,  5.64it/s, train/loss=2.270]
Epoch 0: |          | 662/? [01:57<00:00,  5.64it/s, train/loss=14.50]
Epoch 0: |          | 663/? [01:57<00:00,  5.65it/s, train/loss=14.50]
Epoch 0: |          | 663/? [01:57<00:00,  5.65it/s, train/loss=2.210]
Epoch 0: |          | 664/? [01:57<00:00,  5.64it/s, train/loss=2.210]
Epoch 0: |          | 664/? [01:57<00:00,  5.64it/s, train/loss=24.50]
Epoch 0: |          | 665/? [01:57<00:00,  5.65it/s, train/loss=24.50]
Epoch 0: |          | 665/? [01:57<00:00,  5.65it/s, train/loss=2.100]
Epoch 0: |          | 666/? [01:58<00:00,  5.64it/s, train/loss=2.100]
Epoch 0: |          | 666/? [01:58<00:00,  5.64it/s, train/loss=29.30]
Epoch 0: |          | 667/? [01:58<00:00,  5.65it/s, train/loss=29.30]
Epoch 0: |          | 667/? [01:58<00:00,  5.65it/s, train/loss=2.000]
Epoch 0: |          | 668/? [01:58<00:00,  5.64it/s, train/loss=2.000]
Epoch 0: |          | 668/? [01:58<00:00,  5.64it/s, train/loss=24.10]
Epoch 0: |          | 669/? [01:58<00:00,  5.65it/s, train/loss=24.10]
Epoch 0: |          | 669/? [01:58<00:00,  5.65it/s, train/loss=1.960]
Epoch 0: |          | 670/? [01:58<00:00,  5.64it/s, train/loss=1.960]
Epoch 0: |          | 670/? [01:58<00:00,  5.64it/s, train/loss=32.10]
Epoch 0: |          | 671/? [01:58<00:00,  5.65it/s, train/loss=32.10]
Epoch 0: |          | 671/? [01:58<00:00,  5.65it/s, train/loss=1.950]
Epoch 0: |          | 672/? [01:59<00:00,  5.65it/s, train/loss=1.950]
Epoch 0: |          | 672/? [01:59<00:00,  5.65it/s, train/loss=21.70]
Epoch 0: |          | 673/? [01:59<00:00,  5.65it/s, train/loss=21.70]
Epoch 0: |          | 673/? [01:59<00:00,  5.65it/s, train/loss=1.960]
Epoch 0: |          | 674/? [01:59<00:00,  5.65it/s, train/loss=1.960]
Epoch 0: |          | 674/? [01:59<00:00,  5.65it/s, train/loss=31.20]
Epoch 0: |          | 675/? [01:59<00:00,  5.65it/s, train/loss=31.20]
Epoch 0: |          | 675/? [01:59<00:00,  5.65it/s, train/loss=1.980]
Epoch 0: |          | 676/? [01:59<00:00,  5.65it/s, train/loss=1.980]
Epoch 0: |          | 676/? [01:59<00:00,  5.65it/s, train/loss=10.90]
Epoch 0: |          | 677/? [01:59<00:00,  5.65it/s, train/loss=10.90]
Epoch 0: |          | 677/? [01:59<00:00,  5.65it/s, train/loss=2.000]
Epoch 0: |          | 678/? [02:00<00:00,  5.65it/s, train/loss=2.000]
Epoch 0: |          | 678/? [02:00<00:00,  5.65it/s, train/loss=11.30]
Epoch 0: |          | 679/? [02:00<00:00,  5.66it/s, train/loss=11.30]
Epoch 0: |          | 679/? [02:00<00:00,  5.66it/s, train/loss=2.020]
Epoch 0: |          | 680/? [02:00<00:00,  5.65it/s, train/loss=2.020]
Epoch 0: |          | 680/? [02:00<00:00,  5.65it/s, train/loss=26.00]
Epoch 0: |          | 681/? [02:00<00:00,  5.66it/s, train/loss=26.00]
Epoch 0: |          | 681/? [02:00<00:00,  5.66it/s, train/loss=2.000]
Epoch 0: |          | 682/? [02:00<00:00,  5.65it/s, train/loss=2.000]
Epoch 0: |          | 682/? [02:00<00:00,  5.65it/s, train/loss=26.70]
Epoch 0: |          | 683/? [02:00<00:00,  5.66it/s, train/loss=26.70]
Epoch 0: |          | 683/? [02:00<00:00,  5.66it/s, train/loss=1.980]
Epoch 0: |          | 684/? [02:01<00:00,  5.65it/s, train/loss=1.980]
Epoch 0: |          | 684/? [02:01<00:00,  5.65it/s, train/loss=8.930]
Epoch 0: |          | 685/? [02:01<00:00,  5.66it/s, train/loss=8.930]
Epoch 0: |          | 685/? [02:01<00:00,  5.66it/s, train/loss=1.980]
Epoch 0: |          | 686/? [02:01<00:00,  5.65it/s, train/loss=1.980]
Epoch 0: |          | 686/? [02:01<00:00,  5.65it/s, train/loss=37.30]
Epoch 0: |          | 687/? [02:01<00:00,  5.66it/s, train/loss=37.30]
Epoch 0: |          | 687/? [02:01<00:00,  5.66it/s, train/loss=1.970]
Epoch 0: |          | 688/? [02:01<00:00,  5.65it/s, train/loss=1.970]
Epoch 0: |          | 688/? [02:01<00:00,  5.65it/s, train/loss=30.80]
Epoch 0: |          | 689/? [02:01<00:00,  5.66it/s, train/loss=30.80]
Epoch 0: |          | 689/? [02:01<00:00,  5.66it/s, train/loss=2.160]
Epoch 0: |          | 690/? [02:02<00:00,  5.65it/s, train/loss=2.160]
Epoch 0: |          | 690/? [02:02<00:00,  5.65it/s, train/loss=32.70]
Epoch 0: |          | 691/? [02:02<00:00,  5.66it/s, train/loss=32.70]
Epoch 0: |          | 691/? [02:02<00:00,  5.66it/s, train/loss=2.230]
Epoch 0: |          | 692/? [02:02<00:00,  5.65it/s, train/loss=2.230]
Epoch 0: |          | 692/? [02:02<00:00,  5.65it/s, train/loss=22.50]
Epoch 0: |          | 693/? [02:02<00:00,  5.66it/s, train/loss=22.50]
Epoch 0: |          | 693/? [02:02<00:00,  5.66it/s, train/loss=2.280]
Epoch 0: |          | 694/? [02:02<00:00,  5.65it/s, train/loss=2.280]
Epoch 0: |          | 694/? [02:02<00:00,  5.65it/s, train/loss=23.20]
Epoch 0: |          | 695/? [02:02<00:00,  5.66it/s, train/loss=23.20]
Epoch 0: |          | 695/? [02:02<00:00,  5.66it/s, train/loss=2.250]
Epoch 0: |          | 696/? [02:03<00:00,  5.65it/s, train/loss=2.250]
Epoch 0: |          | 696/? [02:03<00:00,  5.65it/s, train/loss=40.20]
Epoch 0: |          | 697/? [02:03<00:00,  5.66it/s, train/loss=40.20]
Epoch 0: |          | 697/? [02:03<00:00,  5.66it/s, train/loss=2.170]
Epoch 0: |          | 698/? [02:03<00:00,  5.66it/s, train/loss=2.170]
Epoch 0: |          | 698/? [02:03<00:00,  5.66it/s, train/loss=16.40]
Epoch 0: |          | 699/? [02:03<00:00,  5.66it/s, train/loss=16.40]
Epoch 0: |          | 699/? [02:03<00:00,  5.66it/s, train/loss=2.140]
Epoch 0: |          | 700/? [02:03<00:00,  5.66it/s, train/loss=2.140]
Epoch 0: |          | 700/? [02:03<00:00,  5.66it/s, train/loss=13.90]
Epoch 0: |          | 701/? [02:03<00:00,  5.66it/s, train/loss=13.90]
Epoch 0: |          | 701/? [02:03<00:00,  5.66it/s, train/loss=2.160]
Epoch 0: |          | 702/? [02:04<00:00,  5.66it/s, train/loss=2.160]
Epoch 0: |          | 702/? [02:04<00:00,  5.66it/s, train/loss=18.10]
Epoch 0: |          | 703/? [02:04<00:00,  5.67it/s, train/loss=18.10]
Epoch 0: |          | 703/? [02:04<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 704/? [02:04<00:00,  5.66it/s, train/loss=2.180]
Epoch 0: |          | 704/? [02:04<00:00,  5.66it/s, train/loss=23.20]
Epoch 0: |          | 705/? [02:04<00:00,  5.67it/s, train/loss=23.20]
Epoch 0: |          | 705/? [02:04<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 706/? [02:04<00:00,  5.66it/s, train/loss=2.180]
Epoch 0: |          | 706/? [02:04<00:00,  5.66it/s, train/loss=31.30]
Epoch 0: |          | 707/? [02:04<00:00,  5.67it/s, train/loss=31.30]
Epoch 0: |          | 707/? [02:04<00:00,  5.67it/s, train/loss=2.160]
Epoch 0: |          | 708/? [02:04<00:00,  5.66it/s, train/loss=2.160]
Epoch 0: |          | 708/? [02:04<00:00,  5.66it/s, train/loss=19.40]
Epoch 0: |          | 709/? [02:05<00:00,  5.67it/s, train/loss=19.40]
Epoch 0: |          | 709/? [02:05<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 710/? [02:05<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 710/? [02:05<00:00,  5.67it/s, train/loss=31.20]
Epoch 0: |          | 711/? [02:05<00:00,  5.67it/s, train/loss=31.20]
Epoch 0: |          | 711/? [02:05<00:00,  5.67it/s, train/loss=2.220]
Epoch 0: |          | 712/? [02:05<00:00,  5.67it/s, train/loss=2.220]
Epoch 0: |          | 712/? [02:05<00:00,  5.67it/s, train/loss=46.40]
Epoch 0: |          | 713/? [02:05<00:00,  5.67it/s, train/loss=46.40]
Epoch 0: |          | 713/? [02:05<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 714/? [02:06<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 714/? [02:06<00:00,  5.67it/s, train/loss=31.40]
Epoch 0: |          | 715/? [02:06<00:00,  5.67it/s, train/loss=31.40]
Epoch 0: |          | 715/? [02:06<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 716/? [02:06<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 716/? [02:06<00:00,  5.67it/s, train/loss=35.10]
Epoch 0: |          | 717/? [02:06<00:00,  5.67it/s, train/loss=35.10]
Epoch 0: |          | 717/? [02:06<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 718/? [02:06<00:00,  5.67it/s, train/loss=2.200]
Epoch 0: |          | 718/? [02:06<00:00,  5.67it/s, train/loss=23.40]
Epoch 0: |          | 719/? [02:06<00:00,  5.67it/s, train/loss=23.40]
Epoch 0: |          | 719/? [02:06<00:00,  5.67it/s, train/loss=2.210]
Epoch 0: |          | 720/? [02:07<00:00,  5.67it/s, train/loss=2.210]
Epoch 0: |          | 720/? [02:07<00:00,  5.67it/s, train/loss=16.20]
Epoch 0: |          | 721/? [02:07<00:00,  5.67it/s, train/loss=16.20]
Epoch 0: |          | 721/? [02:07<00:00,  5.67it/s, train/loss=2.210]
Epoch 0: |          | 722/? [02:07<00:00,  5.67it/s, train/loss=2.210]
Epoch 0: |          | 722/? [02:07<00:00,  5.67it/s, train/loss=22.00]
Epoch 0: |          | 723/? [02:07<00:00,  5.67it/s, train/loss=22.00]
Epoch 0: |          | 723/? [02:07<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 724/? [02:07<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 724/? [02:07<00:00,  5.67it/s, train/loss=50.60]
Epoch 0: |          | 725/? [02:07<00:00,  5.68it/s, train/loss=50.60]
Epoch 0: |          | 725/? [02:07<00:00,  5.68it/s, train/loss=2.160]
Epoch 0: |          | 726/? [02:08<00:00,  5.67it/s, train/loss=2.160]
Epoch 0: |          | 726/? [02:08<00:00,  5.67it/s, train/loss=44.00]
Epoch 0: |          | 727/? [02:08<00:00,  5.68it/s, train/loss=44.00]
Epoch 0: |          | 727/? [02:08<00:00,  5.68it/s, train/loss=2.180]
Epoch 0: |          | 728/? [02:08<00:00,  5.67it/s, train/loss=2.180]
Epoch 0: |          | 728/? [02:08<00:00,  5.67it/s, train/loss=33.60]
Epoch 0: |          | 729/? [02:08<00:00,  5.68it/s, train/loss=33.60]
Epoch 0: |          | 729/? [02:08<00:00,  5.68it/s, train/loss=2.210]
Epoch 0: |          | 730/? [02:08<00:00,  5.67it/s, train/loss=2.210]
Epoch 0: |          | 730/? [02:08<00:00,  5.67it/s, train/loss=20.70]
Epoch 0: |          | 731/? [02:08<00:00,  5.68it/s, train/loss=20.70]
Epoch 0: |          | 731/? [02:08<00:00,  5.68it/s, train/loss=2.210]
Epoch 0: |          | 732/? [02:08<00:00,  5.68it/s, train/loss=2.210]
Epoch 0: |          | 732/? [02:08<00:00,  5.68it/s, train/loss=19.10]
Epoch 0: |          | 733/? [02:09<00:00,  5.68it/s, train/loss=19.10]
Epoch 0: |          | 733/? [02:09<00:00,  5.68it/s, train/loss=2.180]
Epoch 0: |          | 734/? [02:09<00:00,  5.68it/s, train/loss=2.180]
Epoch 0: |          | 734/? [02:09<00:00,  5.68it/s, train/loss=17.30]
Epoch 0: |          | 735/? [02:09<00:00,  5.68it/s, train/loss=17.30]
Epoch 0: |          | 735/? [02:09<00:00,  5.68it/s, train/loss=2.130]
Epoch 0: |          | 736/? [02:09<00:00,  5.68it/s, train/loss=2.130]
Epoch 0: |          | 736/? [02:09<00:00,  5.68it/s, train/loss=32.90]
Epoch 0: |          | 737/? [02:09<00:00,  5.68it/s, train/loss=32.90]
Epoch 0: |          | 737/? [02:09<00:00,  5.68it/s, train/loss=2.070]
Epoch 0: |          | 738/? [02:09<00:00,  5.68it/s, train/loss=2.070]
Epoch 0: |          | 738/? [02:09<00:00,  5.68it/s, train/loss=25.10]
Epoch 0: |          | 739/? [02:09<00:00,  5.69it/s, train/loss=25.10]
Epoch 0: |          | 739/? [02:09<00:00,  5.69it/s, train/loss=2.010]
Epoch 0: |          | 740/? [02:10<00:00,  5.68it/s, train/loss=2.010]
Epoch 0: |          | 740/? [02:10<00:00,  5.68it/s, train/loss=26.20]
Epoch 0: |          | 741/? [02:10<00:00,  5.69it/s, train/loss=26.20]
Epoch 0: |          | 741/? [02:10<00:00,  5.69it/s, train/loss=1.970]
Epoch 0: |          | 742/? [02:10<00:00,  5.68it/s, train/loss=1.970]
Epoch 0: |          | 742/? [02:10<00:00,  5.68it/s, train/loss=38.50]
Epoch 0: |          | 743/? [02:10<00:00,  5.69it/s, train/loss=38.50]
Epoch 0: |          | 743/? [02:10<00:00,  5.69it/s, train/loss=1.960]
Epoch 0: |          | 744/? [02:10<00:00,  5.68it/s, train/loss=1.960]
Epoch 0: |          | 744/? [02:10<00:00,  5.68it/s, train/loss=26.20]
Epoch 0: |          | 745/? [02:10<00:00,  5.69it/s, train/loss=26.20]
Epoch 0: |          | 745/? [02:10<00:00,  5.69it/s, train/loss=1.960]
Epoch 0: |          | 746/? [02:11<00:00,  5.68it/s, train/loss=1.960]
Epoch 0: |          | 746/? [02:11<00:00,  5.68it/s, train/loss=29.00]
Epoch 0: |          | 747/? [02:11<00:00,  5.69it/s, train/loss=29.00]
Epoch 0: |          | 747/? [02:11<00:00,  5.69it/s, train/loss=1.990]
Epoch 0: |          | 748/? [02:11<00:00,  5.69it/s, train/loss=1.990]
Epoch 0: |          | 748/? [02:11<00:00,  5.69it/s, train/loss=15.30]
Epoch 0: |          | 749/? [02:11<00:00,  5.69it/s, train/loss=15.30]
Epoch 0: |          | 749/? [02:11<00:00,  5.69it/s, train/loss=2.030]
Epoch 0: |          | 750/? [02:11<00:00,  5.69it/s, train/loss=2.030]
Epoch 0: |          | 750/? [02:11<00:00,  5.69it/s, train/loss=52.50]
Epoch 0: |          | 751/? [02:11<00:00,  5.69it/s, train/loss=52.50]
Epoch 0: |          | 751/? [02:11<00:00,  5.69it/s, train/loss=2.080]
Epoch 0: |          | 752/? [02:12<00:00,  5.69it/s, train/loss=2.080]
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`Trainer.fit` stopped: `max_steps=800` reached.
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[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
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Test results saved to outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save
Running step 2: NeuS
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 128, 'width': 128, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': 128, 'width': 128, 'batch_size': 1, 'eval_height': 256, 'eval_width': 256, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-coarse-neus',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-coarse-neus',
'resume': None,
'seed': 0,
'system': {'stage': 'coarse', 'geometry_type': 'implicit-sdf', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'sdf_bias': 'sphere', 'sdf_bias_params': 0.5, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'neus-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'cos_anneal_end_steps': 800, 'eval_chunk_size': 8192}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_orient': 10.0, 'lambda_sparsity': 0.1, 'lambda_opaque': 0.1, 'lambda_clip': 0.0, 'lambda_eikonal': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'betas': [0.9, 0.99], 'eps': 1e-15}, 'params': {'geometry.encoding': {'lr': 0.01}, 'geometry.sdf_network': {'lr': 0.001}, 'geometry.feature_network': {'lr': 0.001}, 'renderer': {'lr': 0.001}}}, 'weights': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134422',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},
'trial_dir': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422',
'trial_name': 'replicate_user@20240222-134422',
'use_timestamp': True}
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74fb6-298d8d076e9d29f944cbc198;0e1233af-4a94-4850-a984-d00aa82f1e06)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]
Loading pipeline components...:  33%|███▎      | 1/3 [00:00<00:00,  4.81it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 12.46it/s]
Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
Using 16bit Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name       | Type                 | Params
----------------------------------------------------
0 | geometry   | ImplicitSDF          | 12.6 M
1 | material   | NoMaterial           | 0
2 | background | SolidColorBackground | 0
3 | renderer   | NeuSVolumeRenderer   | 1
----------------------------------------------------
12.6 M    Trainable params
0         Non-trainable params
12.6 M    Total params
50.417    Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save
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Epoch 0: |          | 53/? [00:11<00:00,  4.78it/s, train/loss=24.50]
Epoch 0: |          | 53/? [00:11<00:00,  4.78it/s, train/loss=8.860]
Epoch 0: |          | 54/? [00:11<00:00,  4.74it/s, train/loss=8.860]
Epoch 0: |          | 54/? [00:11<00:00,  4.74it/s, train/loss=22.90]
Epoch 0: |          | 55/? [00:11<00:00,  4.81it/s, train/loss=22.90]
Epoch 0: |          | 55/? [00:11<00:00,  4.81it/s, train/loss=8.610]
Epoch 0: |          | 56/? [00:11<00:00,  4.77it/s, train/loss=8.610]
Epoch 0: |          | 56/? [00:11<00:00,  4.77it/s, train/loss=50.00]
Epoch 0: |          | 57/? [00:11<00:00,  4.83it/s, train/loss=50.00]
Epoch 0: |          | 57/? [00:11<00:00,  4.83it/s, train/loss=8.320]
Epoch 0: |          | 58/? [00:12<00:00,  4.79it/s, train/loss=8.320]
Epoch 0: |          | 58/? [00:12<00:00,  4.79it/s, train/loss=10.20]
Epoch 0: |          | 59/? [00:12<00:00,  4.86it/s, train/loss=10.20]
Epoch 0: |          | 59/? [00:12<00:00,  4.86it/s, train/loss=8.120]
Epoch 0: |          | 60/? [00:12<00:00,  4.82it/s, train/loss=8.120]
Epoch 0: |          | 60/? [00:12<00:00,  4.82it/s, train/loss=25.00]
Epoch 0: |          | 61/? [00:12<00:00,  4.88it/s, train/loss=25.00]
Epoch 0: |          | 61/? [00:12<00:00,  4.88it/s, train/loss=7.890]
Epoch 0: |          | 62/? [00:12<00:00,  4.85it/s, train/loss=7.890]
Epoch 0: |          | 62/? [00:12<00:00,  4.85it/s, train/loss=39.10]
Epoch 0: |          | 63/? [00:12<00:00,  4.91it/s, train/loss=39.10]
Epoch 0: |          | 63/? [00:12<00:00,  4.91it/s, train/loss=7.680]
Epoch 0: |          | 64/? [00:13<00:00,  4.87it/s, train/loss=7.680]
Epoch 0: |          | 64/? [00:13<00:00,  4.87it/s, train/loss=19.80]
Epoch 0: |          | 65/? [00:13<00:00,  4.93it/s, train/loss=19.80]
Epoch 0: |          | 65/? [00:13<00:00,  4.93it/s, train/loss=7.520]
Epoch 0: |          | 66/? [00:13<00:00,  4.89it/s, train/loss=7.520]
Epoch 0: |          | 66/? [00:13<00:00,  4.89it/s, train/loss=25.30]
Epoch 0: |          | 67/? [00:13<00:00,  4.95it/s, train/loss=25.30]
Epoch 0: |          | 67/? [00:13<00:00,  4.95it/s, train/loss=7.340]
Epoch 0: |          | 68/? [00:13<00:00,  4.92it/s, train/loss=7.340]
Epoch 0: |          | 68/? [00:13<00:00,  4.92it/s, train/loss=26.40]
Epoch 0: |          | 69/? [00:13<00:00,  4.97it/s, train/loss=26.40]
Epoch 0: |          | 69/? [00:13<00:00,  4.97it/s, train/loss=7.160]
Epoch 0: |          | 70/? [00:14<00:00,  4.94it/s, train/loss=7.160]
Epoch 0: |          | 70/? [00:14<00:00,  4.94it/s, train/loss=28.30]
Epoch 0: |          | 71/? [00:14<00:00,  4.99it/s, train/loss=28.30]
Epoch 0: |          | 71/? [00:14<00:00,  4.99it/s, train/loss=6.960]
Epoch 0: |          | 72/? [00:14<00:00,  4.96it/s, train/loss=6.960]
Epoch 0: |          | 72/? [00:14<00:00,  4.96it/s, train/loss=19.70]
Epoch 0: |          | 73/? [00:14<00:00,  5.01it/s, train/loss=19.70]
Epoch 0: |          | 73/? [00:14<00:00,  5.01it/s, train/loss=6.810]
Epoch 0: |          | 74/? [00:14<00:00,  4.98it/s, train/loss=6.810]
Epoch 0: |          | 74/? [00:14<00:00,  4.98it/s, train/loss=25.40]
Epoch 0: |          | 75/? [00:14<00:00,  5.03it/s, train/loss=25.40]
Epoch 0: |          | 75/? [00:14<00:00,  5.03it/s, train/loss=6.630]
Epoch 0: |          | 76/? [00:15<00:00,  5.00it/s, train/loss=6.630]
Epoch 0: |          | 76/? [00:15<00:00,  5.00it/s, train/loss=38.60]
Epoch 0: |          | 77/? [00:15<00:00,  5.05it/s, train/loss=38.60]
Epoch 0: |          | 77/? [00:15<00:00,  5.05it/s, train/loss=6.480]
Epoch 0: |          | 78/? [00:15<00:00,  5.02it/s, train/loss=6.480]
Epoch 0: |          | 78/? [00:15<00:00,  5.02it/s, train/loss=13.70]
Epoch 0: |          | 79/? [00:15<00:00,  5.07it/s, train/loss=13.70]
Epoch 0: |          | 79/? [00:15<00:00,  5.07it/s, train/loss=6.330]
Epoch 0: |          | 80/? [00:15<00:00,  5.04it/s, train/loss=6.330]
Epoch 0: |          | 80/? [00:15<00:00,  5.03it/s, train/loss=32.80]
Epoch 0: |          | 81/? [00:15<00:00,  5.08it/s, train/loss=32.80]
Epoch 0: |          | 81/? [00:15<00:00,  5.08it/s, train/loss=6.160]
Epoch 0: |          | 82/? [00:16<00:00,  5.05it/s, train/loss=6.160]
Epoch 0: |          | 82/? [00:16<00:00,  5.05it/s, train/loss=79.20]
Epoch 0: |          | 83/? [00:16<00:00,  5.10it/s, train/loss=79.20]
Epoch 0: |          | 83/? [00:16<00:00,  5.10it/s, train/loss=6.010]
Epoch 0: |          | 84/? [00:16<00:00,  5.07it/s, train/loss=6.010]
Epoch 0: |          | 84/? [00:16<00:00,  5.07it/s, train/loss=9.970]
Epoch 0: |          | 85/? [00:16<00:00,  5.11it/s, train/loss=9.970]
Epoch 0: |          | 85/? [00:16<00:00,  5.11it/s, train/loss=6.020]
Epoch 0: |          | 86/? [00:16<00:00,  5.08it/s, train/loss=6.020]
Epoch 0: |          | 86/? [00:16<00:00,  5.08it/s, train/loss=9.380]
Epoch 0: |          | 87/? [00:16<00:00,  5.13it/s, train/loss=9.380]
Epoch 0: |          | 87/? [00:16<00:00,  5.13it/s, train/loss=5.970]
Epoch 0: |          | 88/? [00:17<00:00,  5.10it/s, train/loss=5.970]
Epoch 0: |          | 88/? [00:17<00:00,  5.10it/s, train/loss=43.40]
Epoch 0: |          | 89/? [00:17<00:00,  5.14it/s, train/loss=43.40]
Epoch 0: |          | 89/? [00:17<00:00,  5.14it/s, train/loss=5.850]
Epoch 0: |          | 90/? [00:17<00:00,  5.11it/s, train/loss=5.850]
Epoch 0: |          | 90/? [00:17<00:00,  5.11it/s, train/loss=31.80]
Epoch 0: |          | 91/? [00:17<00:00,  5.16it/s, train/loss=31.80]
Epoch 0: |          | 91/? [00:17<00:00,  5.16it/s, train/loss=5.750]
Epoch 0: |          | 92/? [00:17<00:00,  5.13it/s, train/loss=5.750]
Epoch 0: |          | 92/? [00:17<00:00,  5.13it/s, train/loss=30.60]
Epoch 0: |          | 93/? [00:17<00:00,  5.17it/s, train/loss=30.60]
Epoch 0: |          | 93/? [00:17<00:00,  5.17it/s, train/loss=5.680]
Epoch 0: |          | 94/? [00:18<00:00,  5.14it/s, train/loss=5.680]
Epoch 0: |          | 94/? [00:18<00:00,  5.14it/s, train/loss=7.830]
Epoch 0: |          | 95/? [00:18<00:00,  5.18it/s, train/loss=7.830]
Epoch 0: |          | 95/? [00:18<00:00,  5.18it/s, train/loss=5.570]
Epoch 0: |          | 96/? [00:18<00:00,  5.16it/s, train/loss=5.570]
Epoch 0: |          | 96/? [00:18<00:00,  5.16it/s, train/loss=74.70]
Epoch 0: |          | 97/? [00:18<00:00,  5.20it/s, train/loss=74.70]
Epoch 0: |          | 97/? [00:18<00:00,  5.20it/s, train/loss=5.550]
Epoch 0: |          | 98/? [00:18<00:00,  5.17it/s, train/loss=5.550]
Epoch 0: |          | 98/? [00:18<00:00,  5.17it/s, train/loss=28.10]
Epoch 0: |          | 99/? [00:18<00:00,  5.21it/s, train/loss=28.10]
Epoch 0: |          | 99/? [00:18<00:00,  5.21it/s, train/loss=5.500]
Epoch 0: |          | 100/? [00:19<00:00,  5.18it/s, train/loss=5.500]
Epoch 0: |          | 100/? [00:19<00:00,  5.18it/s, train/loss=26.30]
Epoch 0: |          | 101/? [00:19<00:00,  5.22it/s, train/loss=26.30]
Epoch 0: |          | 101/? [00:19<00:00,  5.22it/s, train/loss=5.460]
Epoch 0: |          | 102/? [00:19<00:00,  5.20it/s, train/loss=5.460]
Epoch 0: |          | 102/? [00:19<00:00,  5.20it/s, train/loss=18.60]
Epoch 0: |          | 103/? [00:19<00:00,  5.24it/s, train/loss=18.60]
Epoch 0: |          | 103/? [00:19<00:00,  5.24it/s, train/loss=5.390]
Epoch 0: |          | 104/? [00:19<00:00,  5.21it/s, train/loss=5.390]
Epoch 0: |          | 104/? [00:19<00:00,  5.21it/s, train/loss=35.60]
Epoch 0: |          | 105/? [00:20<00:00,  5.25it/s, train/loss=35.60]
Epoch 0: |          | 105/? [00:20<00:00,  5.25it/s, train/loss=5.390]
Epoch 0: |          | 106/? [00:20<00:00,  5.22it/s, train/loss=5.390]
Epoch 0: |          | 106/? [00:20<00:00,  5.22it/s, train/loss=27.10]
Epoch 0: |          | 107/? [00:20<00:00,  5.26it/s, train/loss=27.10]
Epoch 0: |          | 107/? [00:20<00:00,  5.26it/s, train/loss=5.360]
Epoch 0: |          | 108/? [00:20<00:00,  5.23it/s, train/loss=5.360]
Epoch 0: |          | 108/? [00:20<00:00,  5.23it/s, train/loss=19.40]
Epoch 0: |          | 109/? [00:20<00:00,  5.27it/s, train/loss=19.40]
Epoch 0: |          | 109/? [00:20<00:00,  5.27it/s, train/loss=5.320]
Epoch 0: |          | 110/? [00:20<00:00,  5.24it/s, train/loss=5.320]
Epoch 0: |          | 110/? [00:20<00:00,  5.24it/s, train/loss=11.00]
Epoch 0: |          | 111/? [00:21<00:00,  5.28it/s, train/loss=11.00]
Epoch 0: |          | 111/? [00:21<00:00,  5.28it/s, train/loss=5.210]
Epoch 0: |          | 112/? [00:21<00:00,  5.25it/s, train/loss=5.210]
Epoch 0: |          | 112/? [00:21<00:00,  5.25it/s, train/loss=31.30]
Epoch 0: |          | 113/? [00:21<00:00,  5.29it/s, train/loss=31.30]
Epoch 0: |          | 113/? [00:21<00:00,  5.29it/s, train/loss=5.080]
Epoch 0: |          | 114/? [00:21<00:00,  5.27it/s, train/loss=5.080]
Epoch 0: |          | 114/? [00:21<00:00,  5.26it/s, train/loss=13.40]
Epoch 0: |          | 115/? [00:21<00:00,  5.30it/s, train/loss=13.40]
Epoch 0: |          | 115/? [00:21<00:00,  5.30it/s, train/loss=5.000]
Epoch 0: |          | 116/? [00:21<00:00,  5.28it/s, train/loss=5.000]
Epoch 0: |          | 116/? [00:21<00:00,  5.28it/s, train/loss=21.70]
Epoch 0: |          | 117/? [00:22<00:00,  5.31it/s, train/loss=21.70]
Epoch 0: |          | 117/? [00:22<00:00,  5.31it/s, train/loss=4.900]
Epoch 0: |          | 118/? [00:22<00:00,  5.29it/s, train/loss=4.900]
Epoch 0: |          | 118/? [00:22<00:00,  5.29it/s, train/loss=29.80]
Epoch 0: |          | 119/? [00:22<00:00,  5.32it/s, train/loss=29.80]
Epoch 0: |          | 119/? [00:22<00:00,  5.32it/s, train/loss=4.820]
Epoch 0: |          | 120/? [00:22<00:00,  5.30it/s, train/loss=4.820]
Epoch 0: |          | 120/? [00:22<00:00,  5.30it/s, train/loss=16.00]
Epoch 0: |          | 121/? [00:22<00:00,  5.33it/s, train/loss=16.00]
Epoch 0: |          | 121/? [00:22<00:00,  5.33it/s, train/loss=4.760]
Epoch 0: |          | 122/? [00:22<00:00,  5.31it/s, train/loss=4.760]
Epoch 0: |          | 122/? [00:22<00:00,  5.31it/s, train/loss=9.140]
Epoch 0: |          | 123/? [00:23<00:00,  5.34it/s, train/loss=9.140]
Epoch 0: |          | 123/? [00:23<00:00,  5.34it/s, train/loss=4.590]
Epoch 0: |          | 124/? [00:23<00:00,  5.31it/s, train/loss=4.590]
Epoch 0: |          | 124/? [00:23<00:00,  5.31it/s, train/loss=15.00]
Epoch 0: |          | 125/? [00:23<00:00,  5.35it/s, train/loss=15.00]
Epoch 0: |          | 125/? [00:23<00:00,  5.35it/s, train/loss=4.540]
Epoch 0: |          | 126/? [00:23<00:00,  5.33it/s, train/loss=4.540]
Epoch 0: |          | 126/? [00:23<00:00,  5.32it/s, train/loss=29.10]
Epoch 0: |          | 127/? [00:23<00:00,  5.36it/s, train/loss=29.10]
Epoch 0: |          | 127/? [00:23<00:00,  5.36it/s, train/loss=4.470]
Epoch 0: |          | 128/? [00:23<00:00,  5.33it/s, train/loss=4.470]
Epoch 0: |          | 128/? [00:23<00:00,  5.33it/s, train/loss=14.60]
Epoch 0: |          | 129/? [00:24<00:00,  5.37it/s, train/loss=14.60]
Epoch 0: |          | 129/? [00:24<00:00,  5.37it/s, train/loss=4.440]
Epoch 0: |          | 130/? [00:24<00:00,  5.34it/s, train/loss=4.440]
Epoch 0: |          | 130/? [00:24<00:00,  5.34it/s, train/loss=53.50]
Epoch 0: |          | 131/? [00:24<00:00,  5.38it/s, train/loss=53.50]
Epoch 0: |          | 131/? [00:24<00:00,  5.38it/s, train/loss=4.370]
Epoch 0: |          | 132/? [00:24<00:00,  5.35it/s, train/loss=4.370]
Epoch 0: |          | 132/? [00:24<00:00,  5.35it/s, train/loss=21.30]
Epoch 0: |          | 133/? [00:24<00:00,  5.39it/s, train/loss=21.30]
Epoch 0: |          | 133/? [00:24<00:00,  5.38it/s, train/loss=4.300]
Epoch 0: |          | 134/? [00:24<00:00,  5.36it/s, train/loss=4.300]
Epoch 0: |          | 134/? [00:24<00:00,  5.36it/s, train/loss=41.60]
Epoch 0: |          | 135/? [00:25<00:00,  5.39it/s, train/loss=41.60]
Epoch 0: |          | 135/? [00:25<00:00,  5.39it/s, train/loss=4.300]
Epoch 0: |          | 136/? [00:25<00:00,  5.37it/s, train/loss=4.300]
Epoch 0: |          | 136/? [00:25<00:00,  5.37it/s, train/loss=56.40]
Epoch 0: |          | 137/? [00:25<00:00,  5.40it/s, train/loss=56.40]
Epoch 0: |          | 137/? [00:25<00:00,  5.40it/s, train/loss=4.250]
Epoch 0: |          | 138/? [00:25<00:00,  5.38it/s, train/loss=4.250]
Epoch 0: |          | 138/? [00:25<00:00,  5.38it/s, train/loss=27.90]
Epoch 0: |          | 139/? [00:25<00:00,  5.41it/s, train/loss=27.90]
Epoch 0: |          | 139/? [00:25<00:00,  5.41it/s, train/loss=4.200]
Epoch 0: |          | 140/? [00:25<00:00,  5.39it/s, train/loss=4.200]
Epoch 0: |          | 140/? [00:25<00:00,  5.39it/s, train/loss=23.60]
Epoch 0: |          | 141/? [00:26<00:00,  5.42it/s, train/loss=23.60]
Epoch 0: |          | 141/? [00:26<00:00,  5.42it/s, train/loss=4.210]
Epoch 0: |          | 142/? [00:26<00:00,  5.39it/s, train/loss=4.210]
Epoch 0: |          | 142/? [00:26<00:00,  5.39it/s, train/loss=34.30]
Epoch 0: |          | 143/? [00:26<00:00,  5.42it/s, train/loss=34.30]
Epoch 0: |          | 143/? [00:26<00:00,  5.42it/s, train/loss=4.270]
Epoch 0: |          | 144/? [00:26<00:00,  5.40it/s, train/loss=4.270]
Epoch 0: |          | 144/? [00:26<00:00,  5.40it/s, train/loss=11.00]
Epoch 0: |          | 145/? [00:26<00:00,  5.43it/s, train/loss=11.00]
Epoch 0: |          | 145/? [00:26<00:00,  5.43it/s, train/loss=4.260]
Epoch 0: |          | 146/? [00:26<00:00,  5.41it/s, train/loss=4.260]
Epoch 0: |          | 146/? [00:26<00:00,  5.41it/s, train/loss=16.60]
Epoch 0: |          | 147/? [00:27<00:00,  5.44it/s, train/loss=16.60]
Epoch 0: |          | 147/? [00:27<00:00,  5.44it/s, train/loss=4.250]
Epoch 0: |          | 148/? [00:27<00:00,  5.42it/s, train/loss=4.250]
Epoch 0: |          | 148/? [00:27<00:00,  5.42it/s, train/loss=56.10]
Epoch 0: |          | 149/? [00:27<00:00,  5.45it/s, train/loss=56.10]
Epoch 0: |          | 149/? [00:27<00:00,  5.45it/s, train/loss=4.270]
Epoch 0: |          | 150/? [00:27<00:00,  5.43it/s, train/loss=4.270]
Epoch 0: |          | 150/? [00:27<00:00,  5.43it/s, train/loss=17.70]
Epoch 0: |          | 151/? [00:27<00:00,  5.46it/s, train/loss=17.70]
Epoch 0: |          | 151/? [00:27<00:00,  5.46it/s, train/loss=4.270]
Epoch 0: |          | 152/? [00:27<00:00,  5.44it/s, train/loss=4.270]
Epoch 0: |          | 152/? [00:27<00:00,  5.44it/s, train/loss=29.20]
Epoch 0: |          | 153/? [00:28<00:00,  5.46it/s, train/loss=29.20]
Epoch 0: |          | 153/? [00:28<00:00,  5.46it/s, train/loss=4.220]
Epoch 0: |          | 154/? [00:28<00:00,  5.44it/s, train/loss=4.220]
Epoch 0: |          | 154/? [00:28<00:00,  5.44it/s, train/loss=24.70]
Epoch 0: |          | 155/? [00:28<00:00,  5.47it/s, train/loss=24.70]
Epoch 0: |          | 155/? [00:28<00:00,  5.47it/s, train/loss=4.170]
Epoch 0: |          | 156/? [00:28<00:00,  5.45it/s, train/loss=4.170]
Epoch 0: |          | 156/? [00:28<00:00,  5.45it/s, train/loss=32.10]
Epoch 0: |          | 157/? [00:28<00:00,  5.48it/s, train/loss=32.10]
Epoch 0: |          | 157/? [00:28<00:00,  5.48it/s, train/loss=4.130]
Epoch 0: |          | 158/? [00:28<00:00,  5.46it/s, train/loss=4.130]
Epoch 0: |          | 158/? [00:28<00:00,  5.46it/s, train/loss=50.40]
Epoch 0: |          | 159/? [00:29<00:00,  5.47it/s, train/loss=50.40]
Epoch 0: |          | 159/? [00:29<00:00,  5.47it/s, train/loss=4.160]
Epoch 0: |          | 160/? [00:29<00:00,  5.45it/s, train/loss=4.160]
Epoch 0: |          | 160/? [00:29<00:00,  5.45it/s, train/loss=39.00]
Epoch 0: |          | 161/? [00:29<00:00,  5.47it/s, train/loss=39.00]
Epoch 0: |          | 161/? [00:29<00:00,  5.47it/s, train/loss=4.080]
Epoch 0: |          | 162/? [00:29<00:00,  5.45it/s, train/loss=4.080]
Epoch 0: |          | 162/? [00:29<00:00,  5.45it/s, train/loss=23.90]
Epoch 0: |          | 163/? [00:29<00:00,  5.48it/s, train/loss=23.90]
Epoch 0: |          | 163/? [00:29<00:00,  5.48it/s, train/loss=4.140]
Epoch 0: |          | 164/? [00:30<00:00,  5.46it/s, train/loss=4.140]
Epoch 0: |          | 164/? [00:30<00:00,  5.46it/s, train/loss=20.70]
Epoch 0: |          | 165/? [00:30<00:00,  5.48it/s, train/loss=20.70]
Epoch 0: |          | 165/? [00:30<00:00,  5.48it/s, train/loss=3.990]
Epoch 0: |          | 166/? [00:30<00:00,  5.46it/s, train/loss=3.990]
Epoch 0: |          | 166/? [00:30<00:00,  5.46it/s, train/loss=46.60]
Epoch 0: |          | 167/? [00:30<00:00,  5.49it/s, train/loss=46.60]
Epoch 0: |          | 167/? [00:30<00:00,  5.49it/s, train/loss=4.030]
Epoch 0: |          | 168/? [00:30<00:00,  5.47it/s, train/loss=4.030]
Epoch 0: |          | 168/? [00:30<00:00,  5.47it/s, train/loss=31.20]
Epoch 0: |          | 169/? [00:30<00:00,  5.50it/s, train/loss=31.20]
Epoch 0: |          | 169/? [00:30<00:00,  5.50it/s, train/loss=3.920]
Epoch 0: |          | 170/? [00:31<00:00,  5.48it/s, train/loss=3.920]
Epoch 0: |          | 170/? [00:31<00:00,  5.48it/s, train/loss=24.30]
Epoch 0: |          | 171/? [00:31<00:00,  5.49it/s, train/loss=24.30]
Epoch 0: |          | 171/? [00:31<00:00,  5.49it/s, train/loss=3.860]
Epoch 0: |          | 172/? [00:31<00:00,  5.47it/s, train/loss=3.860]
Epoch 0: |          | 172/? [00:31<00:00,  5.47it/s, train/loss=48.80]
Epoch 0: |          | 173/? [00:31<00:00,  5.49it/s, train/loss=48.80]
Epoch 0: |          | 173/? [00:31<00:00,  5.49it/s, train/loss=3.870]
Epoch 0: |          | 174/? [00:31<00:00,  5.45it/s, train/loss=3.870]
Epoch 0: |          | 174/? [00:31<00:00,  5.45it/s, train/loss=29.00]
Epoch 0: |          | 175/? [00:31<00:00,  5.47it/s, train/loss=29.00]
Epoch 0: |          | 175/? [00:31<00:00,  5.47it/s, train/loss=3.860]
Epoch 0: |          | 176/? [00:32<00:00,  5.45it/s, train/loss=3.860]
Epoch 0: |          | 176/? [00:32<00:00,  5.45it/s, train/loss=28.10]
Epoch 0: |          | 177/? [00:32<00:00,  5.47it/s, train/loss=28.10]
Epoch 0: |          | 177/? [00:32<00:00,  5.47it/s, train/loss=3.830]
Epoch 0: |          | 178/? [00:32<00:00,  5.45it/s, train/loss=3.830]
Epoch 0: |          | 178/? [00:32<00:00,  5.45it/s, train/loss=29.80]
Epoch 0: |          | 179/? [00:32<00:00,  5.48it/s, train/loss=29.80]
Epoch 0: |          | 179/? [00:32<00:00,  5.48it/s, train/loss=3.810]
Epoch 0: |          | 180/? [00:32<00:00,  5.46it/s, train/loss=3.810]
Epoch 0: |          | 180/? [00:32<00:00,  5.46it/s, train/loss=22.60]
Epoch 0: |          | 181/? [00:32<00:00,  5.49it/s, train/loss=22.60]
Epoch 0: |          | 181/? [00:32<00:00,  5.49it/s, train/loss=3.810]
Epoch 0: |          | 182/? [00:33<00:00,  5.47it/s, train/loss=3.810]
Epoch 0: |          | 182/? [00:33<00:00,  5.47it/s, train/loss=17.40]
Epoch 0: |          | 183/? [00:33<00:00,  5.49it/s, train/loss=17.40]
Epoch 0: |          | 183/? [00:33<00:00,  5.49it/s, train/loss=3.830]
Epoch 0: |          | 184/? [00:33<00:00,  5.47it/s, train/loss=3.830]
Epoch 0: |          | 184/? [00:33<00:00,  5.47it/s, train/loss=26.80]
Epoch 0: |          | 185/? [00:33<00:00,  5.50it/s, train/loss=26.80]
Epoch 0: |          | 185/? [00:33<00:00,  5.50it/s, train/loss=3.770]
Epoch 0: |          | 186/? [00:33<00:00,  5.48it/s, train/loss=3.770]
Epoch 0: |          | 186/? [00:33<00:00,  5.48it/s, train/loss=24.20]
Epoch 0: |          | 187/? [00:33<00:00,  5.51it/s, train/loss=24.20]
Epoch 0: |          | 187/? [00:33<00:00,  5.51it/s, train/loss=3.750]
Epoch 0: |          | 188/? [00:34<00:00,  5.49it/s, train/loss=3.750]
Epoch 0: |          | 188/? [00:34<00:00,  5.49it/s, train/loss=24.00]
Epoch 0: |          | 189/? [00:34<00:00,  5.51it/s, train/loss=24.00]
Epoch 0: |          | 189/? [00:34<00:00,  5.51it/s, train/loss=3.690]
Epoch 0: |          | 190/? [00:34<00:00,  5.50it/s, train/loss=3.690]
Epoch 0: |          | 190/? [00:34<00:00,  5.50it/s, train/loss=21.50]
Epoch 0: |          | 191/? [00:34<00:00,  5.52it/s, train/loss=21.50]
Epoch 0: |          | 191/? [00:34<00:00,  5.52it/s, train/loss=3.680]
Epoch 0: |          | 192/? [00:34<00:00,  5.50it/s, train/loss=3.680]
Epoch 0: |          | 192/? [00:34<00:00,  5.50it/s, train/loss=36.10]
Epoch 0: |          | 193/? [00:34<00:00,  5.53it/s, train/loss=36.10]
Epoch 0: |          | 193/? [00:34<00:00,  5.52it/s, train/loss=3.640]
Epoch 0: |          | 194/? [00:35<00:00,  5.51it/s, train/loss=3.640]
Epoch 0: |          | 194/? [00:35<00:00,  5.51it/s, train/loss=13.30]
Epoch 0: |          | 195/? [00:35<00:00,  5.53it/s, train/loss=13.30]
Epoch 0: |          | 195/? [00:35<00:00,  5.53it/s, train/loss=3.600]
Epoch 0: |          | 196/? [00:35<00:00,  5.51it/s, train/loss=3.600]
Epoch 0: |          | 196/? [00:35<00:00,  5.51it/s, train/loss=33.60]
Epoch 0: |          | 197/? [00:35<00:00,  5.53it/s, train/loss=33.60]
Epoch 0: |          | 197/? [00:35<00:00,  5.52it/s, train/loss=3.520]
Epoch 0: |          | 198/? [00:36<00:00,  5.50it/s, train/loss=3.520]
Epoch 0: |          | 198/? [00:36<00:00,  5.50it/s, train/loss=35.50]
Epoch 0: |          | 199/? [00:36<00:00,  5.51it/s, train/loss=35.50]
Epoch 0: |          | 199/? [00:36<00:00,  5.51it/s, train/loss=3.470]
Epoch 0: |          | 200/? [00:36<00:00,  5.48it/s, train/loss=3.470]
Epoch 0: |          | 200/? [00:36<00:00,  5.48it/s, train/loss=14.60]
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Epoch 0: |          | 200/? [00:47<00:00,  4.18it/s, train/loss=14.60]
Epoch 0: |          | 201/? [00:48<00:00,  4.17it/s, train/loss=14.60]
Epoch 0: |          | 201/? [00:48<00:00,  4.17it/s, train/loss=3.450]
Epoch 0: |          | 202/? [00:48<00:00,  4.16it/s, train/loss=3.450]
Epoch 0: |          | 202/? [00:48<00:00,  4.16it/s, train/loss=29.70]
Epoch 0: |          | 203/? [00:48<00:00,  4.17it/s, train/loss=29.70]
Epoch 0: |          | 203/? [00:48<00:00,  4.17it/s, train/loss=3.370]
Epoch 0: |          | 204/? [00:49<00:00,  4.16it/s, train/loss=3.370]
Epoch 0: |          | 204/? [00:49<00:00,  4.16it/s, train/loss=36.30]
Epoch 0: |          | 205/? [00:49<00:00,  4.17it/s, train/loss=36.30]
Epoch 0: |          | 205/? [00:49<00:00,  4.17it/s, train/loss=3.240]
Epoch 0: |          | 206/? [00:49<00:00,  4.17it/s, train/loss=3.240]
Epoch 0: |          | 206/? [00:49<00:00,  4.17it/s, train/loss=20.20]
Epoch 0: |          | 207/? [00:49<00:00,  4.19it/s, train/loss=20.20]
Epoch 0: |          | 207/? [00:49<00:00,  4.19it/s, train/loss=3.100]
Epoch 0: |          | 208/? [00:49<00:00,  4.18it/s, train/loss=3.100]
Epoch 0: |          | 208/? [00:49<00:00,  4.18it/s, train/loss=30.20]
Epoch 0: |          | 209/? [00:49<00:00,  4.20it/s, train/loss=30.20]
Epoch 0: |          | 209/? [00:49<00:00,  4.20it/s, train/loss=2.980]
Epoch 0: |          | 210/? [00:50<00:00,  4.20it/s, train/loss=2.980]
Epoch 0: |          | 210/? [00:50<00:00,  4.20it/s, train/loss=22.10]
Epoch 0: |          | 211/? [00:50<00:00,  4.21it/s, train/loss=22.10]
Epoch 0: |          | 211/? [00:50<00:00,  4.21it/s, train/loss=2.870]
Epoch 0: |          | 212/? [00:50<00:00,  4.21it/s, train/loss=2.870]
Epoch 0: |          | 212/? [00:50<00:00,  4.21it/s, train/loss=31.50]
Epoch 0: |          | 213/? [00:50<00:00,  4.22it/s, train/loss=31.50]
Epoch 0: |          | 213/? [00:50<00:00,  4.22it/s, train/loss=2.790]
Epoch 0: |          | 214/? [00:50<00:00,  4.22it/s, train/loss=2.790]
Epoch 0: |          | 214/? [00:50<00:00,  4.22it/s, train/loss=20.80]
Epoch 0: |          | 215/? [00:50<00:00,  4.24it/s, train/loss=20.80]
Epoch 0: |          | 215/? [00:50<00:00,  4.24it/s, train/loss=2.730]
Epoch 0: |          | 216/? [00:51<00:00,  4.23it/s, train/loss=2.730]
Epoch 0: |          | 216/? [00:51<00:00,  4.23it/s, train/loss=65.60]
Epoch 0: |          | 217/? [00:51<00:00,  4.25it/s, train/loss=65.60]
Epoch 0: |          | 217/? [00:51<00:00,  4.25it/s, train/loss=2.680]
Epoch 0: |          | 218/? [00:51<00:00,  4.25it/s, train/loss=2.680]
Epoch 0: |          | 218/? [00:51<00:00,  4.25it/s, train/loss=23.40]
Epoch 0: |          | 219/? [00:51<00:00,  4.26it/s, train/loss=23.40]
Epoch 0: |          | 219/? [00:51<00:00,  4.26it/s, train/loss=2.660]
Epoch 0: |          | 220/? [00:51<00:00,  4.26it/s, train/loss=2.660]
Epoch 0: |          | 220/? [00:51<00:00,  4.26it/s, train/loss=27.50]
Epoch 0: |          | 221/? [00:51<00:00,  4.28it/s, train/loss=27.50]
Epoch 0: |          | 221/? [00:51<00:00,  4.28it/s, train/loss=2.650]
Epoch 0: |          | 222/? [00:51<00:00,  4.27it/s, train/loss=2.650]
Epoch 0: |          | 222/? [00:51<00:00,  4.27it/s, train/loss=89.30]
Epoch 0: |          | 223/? [00:52<00:00,  4.29it/s, train/loss=89.30]
Epoch 0: |          | 223/? [00:52<00:00,  4.29it/s, train/loss=2.650]
Epoch 0: |          | 224/? [00:52<00:00,  4.28it/s, train/loss=2.650]
Epoch 0: |          | 224/? [00:52<00:00,  4.28it/s, train/loss=46.50]
Epoch 0: |          | 225/? [00:52<00:00,  4.30it/s, train/loss=46.50]
Epoch 0: |          | 225/? [00:52<00:00,  4.30it/s, train/loss=2.650]
Epoch 0: |          | 226/? [00:52<00:00,  4.29it/s, train/loss=2.650]
Epoch 0: |          | 226/? [00:52<00:00,  4.29it/s, train/loss=24.20]
Epoch 0: |          | 227/? [00:52<00:00,  4.31it/s, train/loss=24.20]
Epoch 0: |          | 227/? [00:52<00:00,  4.31it/s, train/loss=2.630]
Epoch 0: |          | 228/? [00:52<00:00,  4.30it/s, train/loss=2.630]
Epoch 0: |          | 228/? [00:52<00:00,  4.30it/s, train/loss=21.20]
Epoch 0: |          | 229/? [00:52<00:00,  4.32it/s, train/loss=21.20]
Epoch 0: |          | 229/? [00:52<00:00,  4.32it/s, train/loss=2.570]
Epoch 0: |          | 230/? [00:53<00:00,  4.32it/s, train/loss=2.570]
Epoch 0: |          | 230/? [00:53<00:00,  4.32it/s, train/loss=28.80]
Epoch 0: |          | 231/? [00:53<00:00,  4.33it/s, train/loss=28.80]
Epoch 0: |          | 231/? [00:53<00:00,  4.33it/s, train/loss=2.490]
Epoch 0: |          | 232/? [00:53<00:00,  4.33it/s, train/loss=2.490]
Epoch 0: |          | 232/? [00:53<00:00,  4.33it/s, train/loss=18.90]
Epoch 0: |          | 233/? [00:53<00:00,  4.34it/s, train/loss=18.90]
Epoch 0: |          | 233/? [00:53<00:00,  4.34it/s, train/loss=2.410]
Epoch 0: |          | 234/? [00:53<00:00,  4.34it/s, train/loss=2.410]
Epoch 0: |          | 234/? [00:53<00:00,  4.34it/s, train/loss=27.70]
Epoch 0: |          | 235/? [00:53<00:00,  4.35it/s, train/loss=27.70]
Epoch 0: |          | 235/? [00:53<00:00,  4.35it/s, train/loss=2.350]
Epoch 0: |          | 236/? [00:54<00:00,  4.35it/s, train/loss=2.350]
Epoch 0: |          | 236/? [00:54<00:00,  4.35it/s, train/loss=26.80]
Epoch 0: |          | 237/? [00:54<00:00,  4.36it/s, train/loss=26.80]
Epoch 0: |          | 237/? [00:54<00:00,  4.36it/s, train/loss=2.300]
Epoch 0: |          | 238/? [00:54<00:00,  4.36it/s, train/loss=2.300]
Epoch 0: |          | 238/? [00:54<00:00,  4.36it/s, train/loss=21.90]
Epoch 0: |          | 239/? [00:54<00:00,  4.38it/s, train/loss=21.90]
Epoch 0: |          | 239/? [00:54<00:00,  4.37it/s, train/loss=2.240]
Epoch 0: |          | 240/? [00:54<00:00,  4.37it/s, train/loss=2.240]
Epoch 0: |          | 240/? [00:54<00:00,  4.37it/s, train/loss=6.910]
Epoch 0: |          | 241/? [00:54<00:00,  4.39it/s, train/loss=6.910]
Epoch 0: |          | 241/? [00:54<00:00,  4.39it/s, train/loss=2.190]
Epoch 0: |          | 242/? [00:55<00:00,  4.38it/s, train/loss=2.190]
Epoch 0: |          | 242/? [00:55<00:00,  4.38it/s, train/loss=20.40]
Epoch 0: |          | 243/? [00:55<00:00,  4.40it/s, train/loss=20.40]
Epoch 0: |          | 243/? [00:55<00:00,  4.40it/s, train/loss=2.140]
Epoch 0: |          | 244/? [00:55<00:00,  4.39it/s, train/loss=2.140]
Epoch 0: |          | 244/? [00:55<00:00,  4.39it/s, train/loss=27.40]
Epoch 0: |          | 245/? [00:55<00:00,  4.41it/s, train/loss=27.40]
Epoch 0: |          | 245/? [00:55<00:00,  4.41it/s, train/loss=2.100]
Epoch 0: |          | 246/? [00:55<00:00,  4.40it/s, train/loss=2.100]
Epoch 0: |          | 246/? [00:55<00:00,  4.40it/s, train/loss=21.10]
Epoch 0: |          | 247/? [00:55<00:00,  4.42it/s, train/loss=21.10]
Epoch 0: |          | 247/? [00:55<00:00,  4.42it/s, train/loss=2.060]
Epoch 0: |          | 248/? [00:56<00:00,  4.41it/s, train/loss=2.060]
Epoch 0: |          | 248/? [00:56<00:00,  4.41it/s, train/loss=12.50]
Epoch 0: |          | 249/? [00:56<00:00,  4.43it/s, train/loss=12.50]
Epoch 0: |          | 249/? [00:56<00:00,  4.43it/s, train/loss=2.020]
Epoch 0: |          | 250/? [00:56<00:00,  4.42it/s, train/loss=2.020]
Epoch 0: |          | 250/? [00:56<00:00,  4.42it/s, train/loss=24.50]
Epoch 0: |          | 251/? [00:56<00:00,  4.43it/s, train/loss=24.50]
Epoch 0: |          | 251/? [00:56<00:00,  4.43it/s, train/loss=1.990]
Epoch 0: |          | 252/? [00:56<00:00,  4.43it/s, train/loss=1.990]
Epoch 0: |          | 252/? [00:56<00:00,  4.43it/s, train/loss=10.80]
Epoch 0: |          | 253/? [00:56<00:00,  4.44it/s, train/loss=10.80]
Epoch 0: |          | 253/? [00:56<00:00,  4.44it/s, train/loss=1.960]
Epoch 0: |          | 254/? [00:57<00:00,  4.44it/s, train/loss=1.960]
Epoch 0: |          | 254/? [00:57<00:00,  4.44it/s, train/loss=44.30]
Epoch 0: |          | 255/? [00:57<00:00,  4.45it/s, train/loss=44.30]
Epoch 0: |          | 255/? [00:57<00:00,  4.45it/s, train/loss=1.930]
Epoch 0: |          | 256/? [00:57<00:00,  4.45it/s, train/loss=1.930]
Epoch 0: |          | 256/? [00:57<00:00,  4.45it/s, train/loss=34.80]
Epoch 0: |          | 257/? [00:57<00:00,  4.46it/s, train/loss=34.80]
Epoch 0: |          | 257/? [00:57<00:00,  4.46it/s, train/loss=1.910]
Epoch 0: |          | 258/? [00:57<00:00,  4.46it/s, train/loss=1.910]
Epoch 0: |          | 258/? [00:57<00:00,  4.46it/s, train/loss=30.50]
Epoch 0: |          | 259/? [00:57<00:00,  4.47it/s, train/loss=30.50]
Epoch 0: |          | 259/? [00:57<00:00,  4.47it/s, train/loss=1.900]
Epoch 0: |          | 260/? [00:58<00:00,  4.47it/s, train/loss=1.900]
Epoch 0: |          | 260/? [00:58<00:00,  4.47it/s, train/loss=37.80]
Epoch 0: |          | 261/? [00:58<00:00,  4.48it/s, train/loss=37.80]
Epoch 0: |          | 261/? [00:58<00:00,  4.48it/s, train/loss=1.890]
Epoch 0: |          | 262/? [00:58<00:00,  4.48it/s, train/loss=1.890]
Epoch 0: |          | 262/? [00:58<00:00,  4.48it/s, train/loss=24.40]
Epoch 0: |          | 263/? [00:58<00:00,  4.49it/s, train/loss=24.40]
Epoch 0: |          | 263/? [00:58<00:00,  4.49it/s, train/loss=1.900]
Epoch 0: |          | 264/? [00:58<00:00,  4.49it/s, train/loss=1.900]
Epoch 0: |          | 264/? [00:58<00:00,  4.49it/s, train/loss=36.50]
Epoch 0: |          | 265/? [00:58<00:00,  4.50it/s, train/loss=36.50]
Epoch 0: |          | 265/? [00:58<00:00,  4.50it/s, train/loss=1.930]
Epoch 0: |          | 266/? [00:59<00:00,  4.50it/s, train/loss=1.930]
Epoch 0: |          | 266/? [00:59<00:00,  4.50it/s, train/loss=40.20]
Epoch 0: |          | 267/? [00:59<00:00,  4.51it/s, train/loss=40.20]
Epoch 0: |          | 267/? [00:59<00:00,  4.51it/s, train/loss=1.960]
Epoch 0: |          | 268/? [00:59<00:00,  4.51it/s, train/loss=1.960]
Epoch 0: |          | 268/? [00:59<00:00,  4.51it/s, train/loss=15.30]
Epoch 0: |          | 269/? [00:59<00:00,  4.52it/s, train/loss=15.30]
Epoch 0: |          | 269/? [00:59<00:00,  4.52it/s, train/loss=1.980]
Epoch 0: |          | 270/? [00:59<00:00,  4.52it/s, train/loss=1.980]
Epoch 0: |          | 270/? [00:59<00:00,  4.52it/s, train/loss=11.80]
Epoch 0: |          | 271/? [00:59<00:00,  4.53it/s, train/loss=11.80]
Epoch 0: |          | 271/? [00:59<00:00,  4.53it/s, train/loss=1.980]
Epoch 0: |          | 272/? [01:00<00:00,  4.53it/s, train/loss=1.980]
Epoch 0: |          | 272/? [01:00<00:00,  4.53it/s, train/loss=37.30]
Epoch 0: |          | 273/? [01:00<00:00,  4.54it/s, train/loss=37.30]
Epoch 0: |          | 273/? [01:00<00:00,  4.54it/s, train/loss=1.930]
Epoch 0: |          | 274/? [01:00<00:00,  4.53it/s, train/loss=1.930]
Epoch 0: |          | 274/? [01:00<00:00,  4.53it/s, train/loss=20.50]
Epoch 0: |          | 275/? [01:00<00:00,  4.55it/s, train/loss=20.50]
Epoch 0: |          | 275/? [01:00<00:00,  4.55it/s, train/loss=1.890]
Epoch 0: |          | 276/? [01:00<00:00,  4.54it/s, train/loss=1.890]
Epoch 0: |          | 276/? [01:00<00:00,  4.54it/s, train/loss=15.60]
Epoch 0: |          | 277/? [01:00<00:00,  4.55it/s, train/loss=15.60]
Epoch 0: |          | 277/? [01:00<00:00,  4.55it/s, train/loss=1.880]
Epoch 0: |          | 278/? [01:01<00:00,  4.54it/s, train/loss=1.880]
Epoch 0: |          | 278/? [01:01<00:00,  4.54it/s, train/loss=51.20]
Epoch 0: |          | 279/? [01:01<00:00,  4.56it/s, train/loss=51.20]
Epoch 0: |          | 279/? [01:01<00:00,  4.56it/s, train/loss=1.880]
Epoch 0: |          | 280/? [01:01<00:00,  4.55it/s, train/loss=1.880]
Epoch 0: |          | 280/? [01:01<00:00,  4.55it/s, train/loss=22.40]
Epoch 0: |          | 281/? [01:01<00:00,  4.56it/s, train/loss=22.40]
Epoch 0: |          | 281/? [01:01<00:00,  4.56it/s, train/loss=1.880]
Epoch 0: |          | 282/? [01:01<00:00,  4.56it/s, train/loss=1.880]
Epoch 0: |          | 282/? [01:01<00:00,  4.56it/s, train/loss=12.20]
Epoch 0: |          | 283/? [01:01<00:00,  4.57it/s, train/loss=12.20]
Epoch 0: |          | 283/? [01:01<00:00,  4.57it/s, train/loss=1.850]
Epoch 0: |          | 284/? [01:02<00:00,  4.57it/s, train/loss=1.850]
Epoch 0: |          | 284/? [01:02<00:00,  4.57it/s, train/loss=26.80]
Epoch 0: |          | 285/? [01:02<00:00,  4.58it/s, train/loss=26.80]
Epoch 0: |          | 285/? [01:02<00:00,  4.58it/s, train/loss=1.800]
Epoch 0: |          | 286/? [01:02<00:00,  4.58it/s, train/loss=1.800]
Epoch 0: |          | 286/? [01:02<00:00,  4.58it/s, train/loss=19.70]
Epoch 0: |          | 287/? [01:02<00:00,  4.59it/s, train/loss=19.70]
Epoch 0: |          | 287/? [01:02<00:00,  4.59it/s, train/loss=1.770]
Epoch 0: |          | 288/? [01:02<00:00,  4.58it/s, train/loss=1.770]
Epoch 0: |          | 288/? [01:02<00:00,  4.58it/s, train/loss=27.50]
Epoch 0: |          | 289/? [01:02<00:00,  4.60it/s, train/loss=27.50]
Epoch 0: |          | 289/? [01:02<00:00,  4.60it/s, train/loss=1.740]
Epoch 0: |          | 290/? [01:03<00:00,  4.59it/s, train/loss=1.740]
Epoch 0: |          | 290/? [01:03<00:00,  4.59it/s, train/loss=35.80]
Epoch 0: |          | 291/? [01:03<00:00,  4.61it/s, train/loss=35.80]
Epoch 0: |          | 291/? [01:03<00:00,  4.61it/s, train/loss=1.740]
Epoch 0: |          | 292/? [01:03<00:00,  4.60it/s, train/loss=1.740]
Epoch 0: |          | 292/? [01:03<00:00,  4.60it/s, train/loss=28.60]
Epoch 0: |          | 293/? [01:03<00:00,  4.61it/s, train/loss=28.60]
Epoch 0: |          | 293/? [01:03<00:00,  4.61it/s, train/loss=1.750]
Epoch 0: |          | 294/? [01:03<00:00,  4.61it/s, train/loss=1.750]
Epoch 0: |          | 294/? [01:03<00:00,  4.61it/s, train/loss=33.70]
Epoch 0: |          | 295/? [01:03<00:00,  4.62it/s, train/loss=33.70]
Epoch 0: |          | 295/? [01:03<00:00,  4.62it/s, train/loss=1.760]
Epoch 0: |          | 296/? [01:04<00:00,  4.62it/s, train/loss=1.760]
Epoch 0: |          | 296/? [01:04<00:00,  4.62it/s, train/loss=36.40]
Epoch 0: |          | 297/? [01:04<00:00,  4.63it/s, train/loss=36.40]
Epoch 0: |          | 297/? [01:04<00:00,  4.63it/s, train/loss=1.760]
Epoch 0: |          | 298/? [01:04<00:00,  4.62it/s, train/loss=1.760]
Epoch 0: |          | 298/? [01:04<00:00,  4.62it/s, train/loss=9.910]
Epoch 0: |          | 299/? [01:04<00:00,  4.64it/s, train/loss=9.910]
Epoch 0: |          | 299/? [01:04<00:00,  4.64it/s, train/loss=1.740]
Epoch 0: |          | 300/? [01:04<00:00,  4.63it/s, train/loss=1.740]
Epoch 0: |          | 300/? [01:04<00:00,  4.63it/s, train/loss=11.90]
Epoch 0: |          | 301/? [01:04<00:00,  4.65it/s, train/loss=11.90]
Epoch 0: |          | 301/? [01:04<00:00,  4.65it/s, train/loss=1.710]
Epoch 0: |          | 302/? [01:05<00:00,  4.64it/s, train/loss=1.710]
Epoch 0: |          | 302/? [01:05<00:00,  4.64it/s, train/loss=31.00]
Epoch 0: |          | 303/? [01:05<00:00,  4.65it/s, train/loss=31.00]
Epoch 0: |          | 303/? [01:05<00:00,  4.65it/s, train/loss=1.710]
Epoch 0: |          | 304/? [01:05<00:00,  4.65it/s, train/loss=1.710]
Epoch 0: |          | 304/? [01:05<00:00,  4.65it/s, train/loss=23.80]
Epoch 0: |          | 305/? [01:05<00:00,  4.66it/s, train/loss=23.80]
Epoch 0: |          | 305/? [01:05<00:00,  4.66it/s, train/loss=1.760]
Epoch 0: |          | 306/? [01:05<00:00,  4.66it/s, train/loss=1.760]
Epoch 0: |          | 306/? [01:05<00:00,  4.66it/s, train/loss=13.10]
Epoch 0: |          | 307/? [01:05<00:00,  4.67it/s, train/loss=13.10]
Epoch 0: |          | 307/? [01:05<00:00,  4.67it/s, train/loss=1.800]
Epoch 0: |          | 308/? [01:06<00:00,  4.67it/s, train/loss=1.800]
Epoch 0: |          | 308/? [01:06<00:00,  4.67it/s, train/loss=20.90]
Epoch 0: |          | 309/? [01:06<00:00,  4.68it/s, train/loss=20.90]
Epoch 0: |          | 309/? [01:06<00:00,  4.68it/s, train/loss=1.770]
Epoch 0: |          | 310/? [01:06<00:00,  4.67it/s, train/loss=1.770]
Epoch 0: |          | 310/? [01:06<00:00,  4.67it/s, train/loss=36.20]
Epoch 0: |          | 311/? [01:06<00:00,  4.69it/s, train/loss=36.20]
Epoch 0: |          | 311/? [01:06<00:00,  4.68it/s, train/loss=1.700]
Epoch 0: |          | 312/? [01:06<00:00,  4.68it/s, train/loss=1.700]
Epoch 0: |          | 312/? [01:06<00:00,  4.68it/s, train/loss=29.00]
Epoch 0: |          | 313/? [01:06<00:00,  4.69it/s, train/loss=29.00]
Epoch 0: |          | 313/? [01:06<00:00,  4.69it/s, train/loss=1.640]
Epoch 0: |          | 314/? [01:06<00:00,  4.69it/s, train/loss=1.640]
Epoch 0: |          | 314/? [01:06<00:00,  4.69it/s, train/loss=12.90]
Epoch 0: |          | 315/? [01:07<00:00,  4.70it/s, train/loss=12.90]
Epoch 0: |          | 315/? [01:07<00:00,  4.70it/s, train/loss=1.620]
Epoch 0: |          | 316/? [01:07<00:00,  4.70it/s, train/loss=1.620]
Epoch 0: |          | 316/? [01:07<00:00,  4.70it/s, train/loss=19.40]
Epoch 0: |          | 317/? [01:07<00:00,  4.71it/s, train/loss=19.40]
Epoch 0: |          | 317/? [01:07<00:00,  4.71it/s, train/loss=1.590]
Epoch 0: |          | 318/? [01:07<00:00,  4.70it/s, train/loss=1.590]
Epoch 0: |          | 318/? [01:07<00:00,  4.70it/s, train/loss=17.20]
Epoch 0: |          | 319/? [01:07<00:00,  4.72it/s, train/loss=17.20]
Epoch 0: |          | 319/? [01:07<00:00,  4.71it/s, train/loss=1.570]
Epoch 0: |          | 320/? [01:07<00:00,  4.71it/s, train/loss=1.570]
Epoch 0: |          | 320/? [01:07<00:00,  4.71it/s, train/loss=8.480]
Epoch 0: |          | 321/? [01:07<00:00,  4.72it/s, train/loss=8.480]
Epoch 0: |          | 321/? [01:07<00:00,  4.72it/s, train/loss=1.620]
Epoch 0: |          | 322/? [01:08<00:00,  4.72it/s, train/loss=1.620]
Epoch 0: |          | 322/? [01:08<00:00,  4.72it/s, train/loss=20.80]
Epoch 0: |          | 323/? [01:08<00:00,  4.73it/s, train/loss=20.80]
Epoch 0: |          | 323/? [01:08<00:00,  4.73it/s, train/loss=1.580]
Epoch 0: |          | 324/? [01:08<00:00,  4.72it/s, train/loss=1.580]
Epoch 0: |          | 324/? [01:08<00:00,  4.72it/s, train/loss=12.70]
Epoch 0: |          | 325/? [01:08<00:00,  4.74it/s, train/loss=12.70]
Epoch 0: |          | 325/? [01:08<00:00,  4.74it/s, train/loss=1.560]
Epoch 0: |          | 326/? [01:08<00:00,  4.73it/s, train/loss=1.560]
Epoch 0: |          | 326/? [01:08<00:00,  4.73it/s, train/loss=28.90]
Epoch 0: |          | 327/? [01:08<00:00,  4.74it/s, train/loss=28.90]
Epoch 0: |          | 327/? [01:08<00:00,  4.74it/s, train/loss=1.540]
Epoch 0: |          | 328/? [01:09<00:00,  4.74it/s, train/loss=1.540]
Epoch 0: |          | 328/? [01:09<00:00,  4.74it/s, train/loss=24.00]
Epoch 0: |          | 329/? [01:09<00:00,  4.75it/s, train/loss=24.00]
Epoch 0: |          | 329/? [01:09<00:00,  4.75it/s, train/loss=1.520]
Epoch 0: |          | 330/? [01:09<00:00,  4.75it/s, train/loss=1.520]
Epoch 0: |          | 330/? [01:09<00:00,  4.75it/s, train/loss=21.20]
Epoch 0: |          | 331/? [01:09<00:00,  4.76it/s, train/loss=21.20]
Epoch 0: |          | 331/? [01:09<00:00,  4.76it/s, train/loss=1.510]
Epoch 0: |          | 332/? [01:09<00:00,  4.75it/s, train/loss=1.510]
Epoch 0: |          | 332/? [01:09<00:00,  4.75it/s, train/loss=71.20]
Epoch 0: |          | 333/? [01:09<00:00,  4.76it/s, train/loss=71.20]
Epoch 0: |          | 333/? [01:09<00:00,  4.76it/s, train/loss=1.500]
Epoch 0: |          | 334/? [01:10<00:00,  4.76it/s, train/loss=1.500]
Epoch 0: |          | 334/? [01:10<00:00,  4.76it/s, train/loss=15.70]
Epoch 0: |          | 335/? [01:10<00:00,  4.77it/s, train/loss=15.70]
Epoch 0: |          | 335/? [01:10<00:00,  4.77it/s, train/loss=1.510]
Epoch 0: |          | 336/? [01:10<00:00,  4.77it/s, train/loss=1.510]
Epoch 0: |          | 336/? [01:10<00:00,  4.77it/s, train/loss=40.90]
Epoch 0: |          | 337/? [01:10<00:00,  4.78it/s, train/loss=40.90]
Epoch 0: |          | 337/? [01:10<00:00,  4.78it/s, train/loss=1.530]
Epoch 0: |          | 338/? [01:10<00:00,  4.77it/s, train/loss=1.530]
Epoch 0: |          | 338/? [01:10<00:00,  4.77it/s, train/loss=52.10]
Epoch 0: |          | 339/? [01:10<00:00,  4.79it/s, train/loss=52.10]
Epoch 0: |          | 339/? [01:10<00:00,  4.79it/s, train/loss=1.570]
Epoch 0: |          | 340/? [01:11<00:00,  4.78it/s, train/loss=1.570]
Epoch 0: |          | 340/? [01:11<00:00,  4.78it/s, train/loss=13.10]
Epoch 0: |          | 341/? [01:11<00:00,  4.79it/s, train/loss=13.10]
Epoch 0: |          | 341/? [01:11<00:00,  4.79it/s, train/loss=1.650]
Epoch 0: |          | 342/? [01:11<00:00,  4.79it/s, train/loss=1.650]
Epoch 0: |          | 342/? [01:11<00:00,  4.79it/s, train/loss=35.70]
Epoch 0: |          | 343/? [01:11<00:00,  4.80it/s, train/loss=35.70]
Epoch 0: |          | 343/? [01:11<00:00,  4.80it/s, train/loss=1.690]
Epoch 0: |          | 344/? [01:11<00:00,  4.79it/s, train/loss=1.690]
Epoch 0: |          | 344/? [01:11<00:00,  4.79it/s, train/loss=37.80]
Epoch 0: |          | 345/? [01:11<00:00,  4.81it/s, train/loss=37.80]
Epoch 0: |          | 345/? [01:11<00:00,  4.81it/s, train/loss=1.700]
Epoch 0: |          | 346/? [01:12<00:00,  4.80it/s, train/loss=1.700]
Epoch 0: |          | 346/? [01:12<00:00,  4.80it/s, train/loss=14.10]
Epoch 0: |          | 347/? [01:12<00:00,  4.81it/s, train/loss=14.10]
Epoch 0: |          | 347/? [01:12<00:00,  4.81it/s, train/loss=1.700]
Epoch 0: |          | 348/? [01:12<00:00,  4.81it/s, train/loss=1.700]
Epoch 0: |          | 348/? [01:12<00:00,  4.81it/s, train/loss=43.30]
Epoch 0: |          | 349/? [01:12<00:00,  4.82it/s, train/loss=43.30]
Epoch 0: |          | 349/? [01:12<00:00,  4.82it/s, train/loss=1.670]
Epoch 0: |          | 350/? [01:12<00:00,  4.81it/s, train/loss=1.670]
Epoch 0: |          | 350/? [01:12<00:00,  4.81it/s, train/loss=21.80]
Epoch 0: |          | 351/? [01:12<00:00,  4.82it/s, train/loss=21.80]
Epoch 0: |          | 351/? [01:12<00:00,  4.82it/s, train/loss=1.620]
Epoch 0: |          | 352/? [01:13<00:00,  4.82it/s, train/loss=1.620]
Epoch 0: |          | 352/? [01:13<00:00,  4.82it/s, train/loss=38.20]
Epoch 0: |          | 353/? [01:13<00:00,  4.83it/s, train/loss=38.20]
Epoch 0: |          | 353/? [01:13<00:00,  4.83it/s, train/loss=1.580]
Epoch 0: |          | 354/? [01:13<00:00,  4.83it/s, train/loss=1.580]
Epoch 0: |          | 354/? [01:13<00:00,  4.83it/s, train/loss=14.50]
Epoch 0: |          | 355/? [01:13<00:00,  4.84it/s, train/loss=14.50]
Epoch 0: |          | 355/? [01:13<00:00,  4.84it/s, train/loss=1.550]
Epoch 0: |          | 356/? [01:13<00:00,  4.83it/s, train/loss=1.550]
Epoch 0: |          | 356/? [01:13<00:00,  4.83it/s, train/loss=27.10]
Epoch 0: |          | 357/? [01:13<00:00,  4.84it/s, train/loss=27.10]
Epoch 0: |          | 357/? [01:13<00:00,  4.84it/s, train/loss=1.530]
Epoch 0: |          | 358/? [01:13<00:00,  4.84it/s, train/loss=1.530]
Epoch 0: |          | 358/? [01:13<00:00,  4.84it/s, train/loss=22.20]
Epoch 0: |          | 359/? [01:14<00:00,  4.85it/s, train/loss=22.20]
Epoch 0: |          | 359/? [01:14<00:00,  4.85it/s, train/loss=1.510]
Epoch 0: |          | 360/? [01:14<00:00,  4.84it/s, train/loss=1.510]
Epoch 0: |          | 360/? [01:14<00:00,  4.84it/s, train/loss=16.60]
Epoch 0: |          | 361/? [01:14<00:00,  4.86it/s, train/loss=16.60]
Epoch 0: |          | 361/? [01:14<00:00,  4.86it/s, train/loss=1.510]
Epoch 0: |          | 362/? [01:14<00:00,  4.85it/s, train/loss=1.510]
Epoch 0: |          | 362/? [01:14<00:00,  4.85it/s, train/loss=29.70]
Epoch 0: |          | 363/? [01:14<00:00,  4.86it/s, train/loss=29.70]
Epoch 0: |          | 363/? [01:14<00:00,  4.86it/s, train/loss=1.500]
Epoch 0: |          | 364/? [01:14<00:00,  4.86it/s, train/loss=1.500]
Epoch 0: |          | 364/? [01:14<00:00,  4.86it/s, train/loss=34.00]
Epoch 0: |          | 365/? [01:14<00:00,  4.87it/s, train/loss=34.00]
Epoch 0: |          | 365/? [01:14<00:00,  4.87it/s, train/loss=1.500]
Epoch 0: |          | 366/? [01:15<00:00,  4.86it/s, train/loss=1.500]
Epoch 0: |          | 366/? [01:15<00:00,  4.86it/s, train/loss=15.00]
Epoch 0: |          | 367/? [01:15<00:00,  4.87it/s, train/loss=15.00]
Epoch 0: |          | 367/? [01:15<00:00,  4.87it/s, train/loss=1.490]
Epoch 0: |          | 368/? [01:15<00:00,  4.86it/s, train/loss=1.490]
Epoch 0: |          | 368/? [01:15<00:00,  4.86it/s, train/loss=24.70]
Epoch 0: |          | 369/? [01:15<00:00,  4.86it/s, train/loss=24.70]
Epoch 0: |          | 369/? [01:15<00:00,  4.86it/s, train/loss=1.630]
Epoch 0: |          | 370/? [01:16<00:00,  4.85it/s, train/loss=1.630]
Epoch 0: |          | 370/? [01:16<00:00,  4.85it/s, train/loss=30.90]
Epoch 0: |          | 371/? [01:16<00:00,  4.86it/s, train/loss=30.90]
Epoch 0: |          | 371/? [01:16<00:00,  4.86it/s, train/loss=1.620]
Epoch 0: |          | 372/? [01:16<00:00,  4.85it/s, train/loss=1.620]
Epoch 0: |          | 372/? [01:16<00:00,  4.85it/s, train/loss=26.20]
Epoch 0: |          | 373/? [01:16<00:00,  4.86it/s, train/loss=26.20]
Epoch 0: |          | 373/? [01:16<00:00,  4.86it/s, train/loss=1.610]
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Epoch 0: |          | 374/? [01:17<00:00,  4.85it/s, train/loss=15.60]
Epoch 0: |          | 375/? [01:17<00:00,  4.85it/s, train/loss=15.60]
Epoch 0: |          | 375/? [01:17<00:00,  4.85it/s, train/loss=1.600]
Epoch 0: |          | 376/? [01:17<00:00,  4.85it/s, train/loss=1.600]
Epoch 0: |          | 376/? [01:17<00:00,  4.85it/s, train/loss=30.70]
Epoch 0: |          | 377/? [01:17<00:00,  4.86it/s, train/loss=30.70]
Epoch 0: |          | 377/? [01:17<00:00,  4.86it/s, train/loss=1.590]
Epoch 0: |          | 378/? [01:17<00:00,  4.85it/s, train/loss=1.590]
Epoch 0: |          | 378/? [01:17<00:00,  4.85it/s, train/loss=28.90]
Epoch 0: |          | 379/? [01:17<00:00,  4.86it/s, train/loss=28.90]
Epoch 0: |          | 379/? [01:17<00:00,  4.86it/s, train/loss=1.580]
Epoch 0: |          | 380/? [01:18<00:00,  4.86it/s, train/loss=1.580]
Epoch 0: |          | 380/? [01:18<00:00,  4.86it/s, train/loss=39.10]
Epoch 0: |          | 381/? [01:18<00:00,  4.87it/s, train/loss=39.10]
Epoch 0: |          | 381/? [01:18<00:00,  4.87it/s, train/loss=1.600]
Epoch 0: |          | 382/? [01:18<00:00,  4.86it/s, train/loss=1.600]
Epoch 0: |          | 382/? [01:18<00:00,  4.86it/s, train/loss=20.10]
Epoch 0: |          | 383/? [01:18<00:00,  4.87it/s, train/loss=20.10]
Epoch 0: |          | 383/? [01:18<00:00,  4.87it/s, train/loss=1.660]
Epoch 0: |          | 384/? [01:18<00:00,  4.87it/s, train/loss=1.660]
Epoch 0: |          | 384/? [01:18<00:00,  4.87it/s, train/loss=39.30]
Epoch 0: |          | 385/? [01:18<00:00,  4.88it/s, train/loss=39.30]
Epoch 0: |          | 385/? [01:18<00:00,  4.88it/s, train/loss=1.710]
Epoch 0: |          | 386/? [01:19<00:00,  4.87it/s, train/loss=1.710]
Epoch 0: |          | 386/? [01:19<00:00,  4.87it/s, train/loss=9.900]
Epoch 0: |          | 387/? [01:19<00:00,  4.88it/s, train/loss=9.900]
Epoch 0: |          | 387/? [01:19<00:00,  4.88it/s, train/loss=1.710]
Epoch 0: |          | 388/? [01:19<00:00,  4.88it/s, train/loss=1.710]
Epoch 0: |          | 388/? [01:19<00:00,  4.88it/s, train/loss=27.30]
Epoch 0: |          | 389/? [01:19<00:00,  4.89it/s, train/loss=27.30]
Epoch 0: |          | 389/? [01:19<00:00,  4.89it/s, train/loss=1.700]
Epoch 0: |          | 390/? [01:19<00:00,  4.89it/s, train/loss=1.700]
Epoch 0: |          | 390/? [01:19<00:00,  4.89it/s, train/loss=23.70]
Epoch 0: |          | 391/? [01:19<00:00,  4.90it/s, train/loss=23.70]
Epoch 0: |          | 391/? [01:19<00:00,  4.90it/s, train/loss=1.670]
Epoch 0: |          | 392/? [01:20<00:00,  4.89it/s, train/loss=1.670]
Epoch 0: |          | 392/? [01:20<00:00,  4.89it/s, train/loss=22.80]
Epoch 0: |          | 393/? [01:20<00:00,  4.90it/s, train/loss=22.80]
Epoch 0: |          | 393/? [01:20<00:00,  4.90it/s, train/loss=1.640]
Epoch 0: |          | 394/? [01:20<00:00,  4.90it/s, train/loss=1.640]
Epoch 0: |          | 394/? [01:20<00:00,  4.90it/s, train/loss=26.00]
Epoch 0: |          | 395/? [01:20<00:00,  4.91it/s, train/loss=26.00]
Epoch 0: |          | 395/? [01:20<00:00,  4.91it/s, train/loss=1.640]
Epoch 0: |          | 396/? [01:20<00:00,  4.90it/s, train/loss=1.640]
Epoch 0: |          | 396/? [01:20<00:00,  4.90it/s, train/loss=9.660]
Epoch 0: |          | 397/? [01:20<00:00,  4.91it/s, train/loss=9.660]
Epoch 0: |          | 397/? [01:20<00:00,  4.91it/s, train/loss=1.630]
Epoch 0: |          | 398/? [01:21<00:00,  4.91it/s, train/loss=1.630]
Epoch 0: |          | 398/? [01:21<00:00,  4.91it/s, train/loss=12.90]
Epoch 0: |          | 399/? [01:21<00:00,  4.92it/s, train/loss=12.90]
Epoch 0: |          | 399/? [01:21<00:00,  4.92it/s, train/loss=1.610]
Epoch 0: |          | 400/? [01:21<00:00,  4.91it/s, train/loss=1.610]
Epoch 0: |          | 400/? [01:21<00:00,  4.91it/s, train/loss=37.30]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:08<00:00,  4.63it/s]

Epoch 0: |          | 400/? [01:30<00:00,  4.40it/s, train/loss=37.30]
Epoch 0: |          | 401/? [01:31<00:00,  4.36it/s, train/loss=37.30]
Epoch 0: |          | 401/? [01:31<00:00,  4.36it/s, train/loss=1.570]
Epoch 0: |          | 402/? [01:32<00:00,  4.36it/s, train/loss=1.570]
Epoch 0: |          | 402/? [01:32<00:00,  4.36it/s, train/loss=12.40]
Epoch 0: |          | 403/? [01:32<00:00,  4.37it/s, train/loss=12.40]
Epoch 0: |          | 403/? [01:32<00:00,  4.37it/s, train/loss=1.540]
Epoch 0: |          | 404/? [01:32<00:00,  4.37it/s, train/loss=1.540]
Epoch 0: |          | 404/? [01:32<00:00,  4.37it/s, train/loss=18.20]
Epoch 0: |          | 405/? [01:32<00:00,  4.37it/s, train/loss=18.20]
Epoch 0: |          | 405/? [01:32<00:00,  4.37it/s, train/loss=1.510]
Epoch 0: |          | 406/? [01:32<00:00,  4.37it/s, train/loss=1.510]
Epoch 0: |          | 406/? [01:32<00:00,  4.37it/s, train/loss=23.10]
Epoch 0: |          | 407/? [01:32<00:00,  4.38it/s, train/loss=23.10]
Epoch 0: |          | 407/? [01:32<00:00,  4.38it/s, train/loss=1.500]
Epoch 0: |          | 408/? [01:33<00:00,  4.38it/s, train/loss=1.500]
Epoch 0: |          | 408/? [01:33<00:00,  4.38it/s, train/loss=16.30]
Epoch 0: |          | 409/? [01:33<00:00,  4.39it/s, train/loss=16.30]
Epoch 0: |          | 409/? [01:33<00:00,  4.39it/s, train/loss=1.490]
Epoch 0: |          | 410/? [01:33<00:00,  4.38it/s, train/loss=1.490]
Epoch 0: |          | 410/? [01:33<00:00,  4.38it/s, train/loss=27.70]
Epoch 0: |          | 411/? [01:33<00:00,  4.39it/s, train/loss=27.70]
Epoch 0: |          | 411/? [01:33<00:00,  4.39it/s, train/loss=1.500]
Epoch 0: |          | 412/? [01:33<00:00,  4.39it/s, train/loss=1.500]
Epoch 0: |          | 412/? [01:33<00:00,  4.39it/s, train/loss=11.30]
Epoch 0: |          | 413/? [01:33<00:00,  4.40it/s, train/loss=11.30]
Epoch 0: |          | 413/? [01:33<00:00,  4.40it/s, train/loss=1.490]
Epoch 0: |          | 414/? [01:34<00:00,  4.40it/s, train/loss=1.490]
Epoch 0: |          | 414/? [01:34<00:00,  4.40it/s, train/loss=11.10]
Epoch 0: |          | 415/? [01:34<00:00,  4.41it/s, train/loss=11.10]
Epoch 0: |          | 415/? [01:34<00:00,  4.41it/s, train/loss=1.480]
Epoch 0: |          | 416/? [01:34<00:00,  4.40it/s, train/loss=1.480]
Epoch 0: |          | 416/? [01:34<00:00,  4.40it/s, train/loss=21.90]
Epoch 0: |          | 417/? [01:34<00:00,  4.41it/s, train/loss=21.90]
Epoch 0: |          | 417/? [01:34<00:00,  4.41it/s, train/loss=1.460]
Epoch 0: |          | 418/? [01:34<00:00,  4.41it/s, train/loss=1.460]
Epoch 0: |          | 418/? [01:34<00:00,  4.41it/s, train/loss=35.50]
Epoch 0: |          | 419/? [01:34<00:00,  4.42it/s, train/loss=35.50]
Epoch 0: |          | 419/? [01:34<00:00,  4.42it/s, train/loss=1.440]
Epoch 0: |          | 420/? [01:35<00:00,  4.42it/s, train/loss=1.440]
Epoch 0: |          | 420/? [01:35<00:00,  4.42it/s, train/loss=40.30]
Epoch 0: |          | 421/? [01:35<00:00,  4.43it/s, train/loss=40.30]
Epoch 0: |          | 421/? [01:35<00:00,  4.43it/s, train/loss=1.400]
Epoch 0: |          | 422/? [01:35<00:00,  4.42it/s, train/loss=1.400]
Epoch 0: |          | 422/? [01:35<00:00,  4.42it/s, train/loss=23.00]
Epoch 0: |          | 423/? [01:35<00:00,  4.43it/s, train/loss=23.00]
Epoch 0: |          | 423/? [01:35<00:00,  4.43it/s, train/loss=1.370]
Epoch 0: |          | 424/? [01:35<00:00,  4.43it/s, train/loss=1.370]
Epoch 0: |          | 424/? [01:35<00:00,  4.43it/s, train/loss=17.50]
Epoch 0: |          | 425/? [01:35<00:00,  4.44it/s, train/loss=17.50]
Epoch 0: |          | 425/? [01:35<00:00,  4.44it/s, train/loss=1.360]
Epoch 0: |          | 426/? [01:36<00:00,  4.44it/s, train/loss=1.360]
Epoch 0: |          | 426/? [01:36<00:00,  4.44it/s, train/loss=26.50]
Epoch 0: |          | 427/? [01:36<00:00,  4.45it/s, train/loss=26.50]
Epoch 0: |          | 427/? [01:36<00:00,  4.45it/s, train/loss=1.370]
Epoch 0: |          | 428/? [01:36<00:00,  4.44it/s, train/loss=1.370]
Epoch 0: |          | 428/? [01:36<00:00,  4.44it/s, train/loss=40.60]
Epoch 0: |          | 429/? [01:36<00:00,  4.45it/s, train/loss=40.60]
Epoch 0: |          | 429/? [01:36<00:00,  4.45it/s, train/loss=1.410]
Epoch 0: |          | 430/? [01:36<00:00,  4.45it/s, train/loss=1.410]
Epoch 0: |          | 430/? [01:36<00:00,  4.45it/s, train/loss=9.530]
Epoch 0: |          | 431/? [01:36<00:00,  4.46it/s, train/loss=9.530]
Epoch 0: |          | 431/? [01:36<00:00,  4.46it/s, train/loss=1.460]
Epoch 0: |          | 432/? [01:36<00:00,  4.46it/s, train/loss=1.460]
Epoch 0: |          | 432/? [01:36<00:00,  4.46it/s, train/loss=10.90]
Epoch 0: |          | 433/? [01:36<00:00,  4.46it/s, train/loss=10.90]
Epoch 0: |          | 433/? [01:36<00:00,  4.46it/s, train/loss=1.410]
Epoch 0: |          | 434/? [01:37<00:00,  4.46it/s, train/loss=1.410]
Epoch 0: |          | 434/? [01:37<00:00,  4.46it/s, train/loss=13.10]
Epoch 0: |          | 435/? [01:37<00:00,  4.47it/s, train/loss=13.10]
Epoch 0: |          | 435/? [01:37<00:00,  4.47it/s, train/loss=1.380]
Epoch 0: |          | 436/? [01:37<00:00,  4.47it/s, train/loss=1.380]
Epoch 0: |          | 436/? [01:37<00:00,  4.47it/s, train/loss=30.50]
Epoch 0: |          | 437/? [01:37<00:00,  4.48it/s, train/loss=30.50]
Epoch 0: |          | 437/? [01:37<00:00,  4.48it/s, train/loss=1.340]
Epoch 0: |          | 438/? [01:37<00:00,  4.47it/s, train/loss=1.340]
Epoch 0: |          | 438/? [01:37<00:00,  4.47it/s, train/loss=19.70]
Epoch 0: |          | 439/? [01:37<00:00,  4.48it/s, train/loss=19.70]
Epoch 0: |          | 439/? [01:37<00:00,  4.48it/s, train/loss=1.300]
Epoch 0: |          | 440/? [01:38<00:00,  4.48it/s, train/loss=1.300]
Epoch 0: |          | 440/? [01:38<00:00,  4.48it/s, train/loss=8.380]
Epoch 0: |          | 441/? [01:38<00:00,  4.49it/s, train/loss=8.380]
Epoch 0: |          | 441/? [01:38<00:00,  4.49it/s, train/loss=1.310]
Epoch 0: |          | 442/? [01:38<00:00,  4.49it/s, train/loss=1.310]
Epoch 0: |          | 442/? [01:38<00:00,  4.49it/s, train/loss=20.80]
Epoch 0: |          | 443/? [01:38<00:00,  4.49it/s, train/loss=20.80]
Epoch 0: |          | 443/? [01:38<00:00,  4.49it/s, train/loss=1.340]
Epoch 0: |          | 444/? [01:38<00:00,  4.49it/s, train/loss=1.340]
Epoch 0: |          | 444/? [01:38<00:00,  4.49it/s, train/loss=19.60]
Epoch 0: |          | 445/? [01:38<00:00,  4.50it/s, train/loss=19.60]
Epoch 0: |          | 445/? [01:38<00:00,  4.50it/s, train/loss=1.360]
Epoch 0: |          | 446/? [01:39<00:00,  4.50it/s, train/loss=1.360]
Epoch 0: |          | 446/? [01:39<00:00,  4.50it/s, train/loss=27.50]
Epoch 0: |          | 447/? [01:39<00:00,  4.51it/s, train/loss=27.50]
Epoch 0: |          | 447/? [01:39<00:00,  4.51it/s, train/loss=1.350]
Epoch 0: |          | 448/? [01:39<00:00,  4.50it/s, train/loss=1.350]
Epoch 0: |          | 448/? [01:39<00:00,  4.50it/s, train/loss=21.00]
Epoch 0: |          | 449/? [01:39<00:00,  4.51it/s, train/loss=21.00]
Epoch 0: |          | 449/? [01:39<00:00,  4.51it/s, train/loss=1.310]
Epoch 0: |          | 450/? [01:39<00:00,  4.51it/s, train/loss=1.310]
Epoch 0: |          | 450/? [01:39<00:00,  4.51it/s, train/loss=23.30]
Epoch 0: |          | 451/? [01:39<00:00,  4.52it/s, train/loss=23.30]
Epoch 0: |          | 451/? [01:39<00:00,  4.52it/s, train/loss=1.240]
Epoch 0: |          | 452/? [01:40<00:00,  4.52it/s, train/loss=1.240]
Epoch 0: |          | 452/? [01:40<00:00,  4.52it/s, train/loss=35.10]
Epoch 0: |          | 453/? [01:40<00:00,  4.53it/s, train/loss=35.10]
Epoch 0: |          | 453/? [01:40<00:00,  4.53it/s, train/loss=1.200]
Epoch 0: |          | 454/? [01:40<00:00,  4.52it/s, train/loss=1.200]
Epoch 0: |          | 454/? [01:40<00:00,  4.52it/s, train/loss=20.00]
Epoch 0: |          | 455/? [01:40<00:00,  4.53it/s, train/loss=20.00]
Epoch 0: |          | 455/? [01:40<00:00,  4.53it/s, train/loss=1.200]
Epoch 0: |          | 456/? [01:40<00:00,  4.53it/s, train/loss=1.200]
Epoch 0: |          | 456/? [01:40<00:00,  4.53it/s, train/loss=33.20]
Epoch 0: |          | 457/? [01:40<00:00,  4.54it/s, train/loss=33.20]
Epoch 0: |          | 457/? [01:40<00:00,  4.54it/s, train/loss=1.240]
Epoch 0: |          | 458/? [01:41<00:00,  4.53it/s, train/loss=1.240]
Epoch 0: |          | 458/? [01:41<00:00,  4.53it/s, train/loss=12.90]
Epoch 0: |          | 459/? [01:41<00:00,  4.54it/s, train/loss=12.90]
Epoch 0: |          | 459/? [01:41<00:00,  4.54it/s, train/loss=1.340]
Epoch 0: |          | 460/? [01:41<00:00,  4.54it/s, train/loss=1.340]
Epoch 0: |          | 460/? [01:41<00:00,  4.54it/s, train/loss=27.10]
Epoch 0: |          | 461/? [01:41<00:00,  4.55it/s, train/loss=27.10]
Epoch 0: |          | 461/? [01:41<00:00,  4.55it/s, train/loss=1.450]
Epoch 0: |          | 462/? [01:41<00:00,  4.55it/s, train/loss=1.450]
Epoch 0: |          | 462/? [01:41<00:00,  4.55it/s, train/loss=14.40]
Epoch 0: |          | 463/? [01:41<00:00,  4.55it/s, train/loss=14.40]
Epoch 0: |          | 463/? [01:41<00:00,  4.55it/s, train/loss=1.480]
Epoch 0: |          | 464/? [01:41<00:00,  4.55it/s, train/loss=1.480]
Epoch 0: |          | 464/? [01:41<00:00,  4.55it/s, train/loss=11.30]
Epoch 0: |          | 465/? [01:41<00:00,  4.56it/s, train/loss=11.30]
Epoch 0: |          | 465/? [01:41<00:00,  4.56it/s, train/loss=1.420]
Epoch 0: |          | 466/? [01:42<00:00,  4.56it/s, train/loss=1.420]
Epoch 0: |          | 466/? [01:42<00:00,  4.56it/s, train/loss=27.20]
Epoch 0: |          | 467/? [01:42<00:00,  4.57it/s, train/loss=27.20]
Epoch 0: |          | 467/? [01:42<00:00,  4.57it/s, train/loss=1.320]
Epoch 0: |          | 468/? [01:42<00:00,  4.56it/s, train/loss=1.320]
Epoch 0: |          | 468/? [01:42<00:00,  4.56it/s, train/loss=30.50]
Epoch 0: |          | 469/? [01:42<00:00,  4.57it/s, train/loss=30.50]
Epoch 0: |          | 469/? [01:42<00:00,  4.57it/s, train/loss=1.240]
Epoch 0: |          | 470/? [01:42<00:00,  4.57it/s, train/loss=1.240]
Epoch 0: |          | 470/? [01:42<00:00,  4.57it/s, train/loss=14.90]
Epoch 0: |          | 471/? [01:42<00:00,  4.58it/s, train/loss=14.90]
Epoch 0: |          | 471/? [01:42<00:00,  4.58it/s, train/loss=1.200]
Epoch 0: |          | 472/? [01:43<00:00,  4.57it/s, train/loss=1.200]
Epoch 0: |          | 472/? [01:43<00:00,  4.57it/s, train/loss=12.10]
Epoch 0: |          | 473/? [01:43<00:00,  4.58it/s, train/loss=12.10]
Epoch 0: |          | 473/? [01:43<00:00,  4.58it/s, train/loss=1.180]
Epoch 0: |          | 474/? [01:43<00:00,  4.58it/s, train/loss=1.180]
Epoch 0: |          | 474/? [01:43<00:00,  4.58it/s, train/loss=41.20]
Epoch 0: |          | 475/? [01:43<00:00,  4.59it/s, train/loss=41.20]
Epoch 0: |          | 475/? [01:43<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 476/? [01:43<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 476/? [01:43<00:00,  4.59it/s, train/loss=29.90]
Epoch 0: |          | 477/? [01:43<00:00,  4.59it/s, train/loss=29.90]
Epoch 0: |          | 477/? [01:43<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 478/? [01:44<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 478/? [01:44<00:00,  4.59it/s, train/loss=25.50]
Epoch 0: |          | 479/? [01:44<00:00,  4.60it/s, train/loss=25.50]
Epoch 0: |          | 479/? [01:44<00:00,  4.60it/s, train/loss=1.160]
Epoch 0: |          | 480/? [01:44<00:00,  4.60it/s, train/loss=1.160]
Epoch 0: |          | 480/? [01:44<00:00,  4.60it/s, train/loss=8.880]
Epoch 0: |          | 481/? [01:44<00:00,  4.60it/s, train/loss=8.880]
Epoch 0: |          | 481/? [01:44<00:00,  4.60it/s, train/loss=1.140]
Epoch 0: |          | 482/? [01:44<00:00,  4.60it/s, train/loss=1.140]
Epoch 0: |          | 482/? [01:44<00:00,  4.60it/s, train/loss=17.90]
Epoch 0: |          | 483/? [01:44<00:00,  4.61it/s, train/loss=17.90]
Epoch 0: |          | 483/? [01:44<00:00,  4.61it/s, train/loss=1.110]
Epoch 0: |          | 484/? [01:45<00:00,  4.61it/s, train/loss=1.110]
Epoch 0: |          | 484/? [01:45<00:00,  4.61it/s, train/loss=32.30]
Epoch 0: |          | 485/? [01:45<00:00,  4.62it/s, train/loss=32.30]
Epoch 0: |          | 485/? [01:45<00:00,  4.62it/s, train/loss=1.080]
Epoch 0: |          | 486/? [01:45<00:00,  4.61it/s, train/loss=1.080]
Epoch 0: |          | 486/? [01:45<00:00,  4.61it/s, train/loss=22.40]
Epoch 0: |          | 487/? [01:45<00:00,  4.62it/s, train/loss=22.40]
Epoch 0: |          | 487/? [01:45<00:00,  4.62it/s, train/loss=1.080]
Epoch 0: |          | 488/? [01:45<00:00,  4.62it/s, train/loss=1.080]
Epoch 0: |          | 488/? [01:45<00:00,  4.62it/s, train/loss=19.40]
Epoch 0: |          | 489/? [01:45<00:00,  4.63it/s, train/loss=19.40]
Epoch 0: |          | 489/? [01:45<00:00,  4.63it/s, train/loss=1.080]
Epoch 0: |          | 490/? [01:45<00:00,  4.62it/s, train/loss=1.080]
Epoch 0: |          | 490/? [01:45<00:00,  4.62it/s, train/loss=22.90]
Epoch 0: |          | 491/? [01:46<00:00,  4.63it/s, train/loss=22.90]
Epoch 0: |          | 491/? [01:46<00:00,  4.63it/s, train/loss=1.080]
Epoch 0: |          | 492/? [01:46<00:00,  4.63it/s, train/loss=1.080]
Epoch 0: |          | 492/? [01:46<00:00,  4.63it/s, train/loss=24.60]
Epoch 0: |          | 493/? [01:46<00:00,  4.64it/s, train/loss=24.60]
Epoch 0: |          | 493/? [01:46<00:00,  4.64it/s, train/loss=1.080]
Epoch 0: |          | 494/? [01:46<00:00,  4.63it/s, train/loss=1.080]
Epoch 0: |          | 494/? [01:46<00:00,  4.63it/s, train/loss=29.80]
Epoch 0: |          | 495/? [01:46<00:00,  4.64it/s, train/loss=29.80]
Epoch 0: |          | 495/? [01:46<00:00,  4.64it/s, train/loss=1.100]
Epoch 0: |          | 496/? [01:46<00:00,  4.64it/s, train/loss=1.100]
Epoch 0: |          | 496/? [01:46<00:00,  4.64it/s, train/loss=31.80]
Epoch 0: |          | 497/? [01:46<00:00,  4.65it/s, train/loss=31.80]
Epoch 0: |          | 497/? [01:46<00:00,  4.65it/s, train/loss=1.130]
Epoch 0: |          | 498/? [01:47<00:00,  4.64it/s, train/loss=1.130]
Epoch 0: |          | 498/? [01:47<00:00,  4.64it/s, train/loss=11.90]
Epoch 0: |          | 499/? [01:47<00:00,  4.65it/s, train/loss=11.90]
Epoch 0: |          | 499/? [01:47<00:00,  4.65it/s, train/loss=1.140]
Epoch 0: |          | 500/? [01:47<00:00,  4.65it/s, train/loss=1.140]
Epoch 0: |          | 500/? [01:47<00:00,  4.65it/s, train/loss=31.60]
Epoch 0: |          | 501/? [01:47<00:00,  4.66it/s, train/loss=31.60]
Epoch 0: |          | 501/? [01:47<00:00,  4.66it/s, train/loss=1.140]
Epoch 0: |          | 502/? [01:47<00:00,  4.65it/s, train/loss=1.140]
Epoch 0: |          | 502/? [01:47<00:00,  4.65it/s, train/loss=56.30]
Epoch 0: |          | 503/? [01:47<00:00,  4.66it/s, train/loss=56.30]
Epoch 0: |          | 503/? [01:47<00:00,  4.66it/s, train/loss=1.150]
Epoch 0: |          | 504/? [01:48<00:00,  4.66it/s, train/loss=1.150]
Epoch 0: |          | 504/? [01:48<00:00,  4.66it/s, train/loss=45.80]
Epoch 0: |          | 505/? [01:48<00:00,  4.67it/s, train/loss=45.80]
Epoch 0: |          | 505/? [01:48<00:00,  4.67it/s, train/loss=1.150]
Epoch 0: |          | 506/? [01:48<00:00,  4.66it/s, train/loss=1.150]
Epoch 0: |          | 506/? [01:48<00:00,  4.66it/s, train/loss=10.50]
Epoch 0: |          | 507/? [01:48<00:00,  4.67it/s, train/loss=10.50]
Epoch 0: |          | 507/? [01:48<00:00,  4.67it/s, train/loss=1.150]
Epoch 0: |          | 508/? [01:48<00:00,  4.67it/s, train/loss=1.150]
Epoch 0: |          | 508/? [01:48<00:00,  4.67it/s, train/loss=33.40]
Epoch 0: |          | 509/? [01:48<00:00,  4.68it/s, train/loss=33.40]
Epoch 0: |          | 509/? [01:48<00:00,  4.68it/s, train/loss=1.140]
Epoch 0: |          | 510/? [01:49<00:00,  4.67it/s, train/loss=1.140]
Epoch 0: |          | 510/? [01:49<00:00,  4.67it/s, train/loss=16.90]
Epoch 0: |          | 511/? [01:49<00:00,  4.68it/s, train/loss=16.90]
Epoch 0: |          | 511/? [01:49<00:00,  4.68it/s, train/loss=1.140]
Epoch 0: |          | 512/? [01:49<00:00,  4.68it/s, train/loss=1.140]
Epoch 0: |          | 512/? [01:49<00:00,  4.68it/s, train/loss=26.30]
Epoch 0: |          | 513/? [01:49<00:00,  4.69it/s, train/loss=26.30]
Epoch 0: |          | 513/? [01:49<00:00,  4.69it/s, train/loss=1.150]
Epoch 0: |          | 514/? [01:49<00:00,  4.69it/s, train/loss=1.150]
Epoch 0: |          | 514/? [01:49<00:00,  4.68it/s, train/loss=15.90]
Epoch 0: |          | 515/? [01:49<00:00,  4.69it/s, train/loss=15.90]
Epoch 0: |          | 515/? [01:49<00:00,  4.69it/s, train/loss=1.170]
Epoch 0: |          | 516/? [01:50<00:00,  4.69it/s, train/loss=1.170]
Epoch 0: |          | 516/? [01:50<00:00,  4.69it/s, train/loss=29.20]
Epoch 0: |          | 517/? [01:50<00:00,  4.70it/s, train/loss=29.20]
Epoch 0: |          | 517/? [01:50<00:00,  4.70it/s, train/loss=1.210]
Epoch 0: |          | 518/? [01:50<00:00,  4.69it/s, train/loss=1.210]
Epoch 0: |          | 518/? [01:50<00:00,  4.69it/s, train/loss=35.40]
Epoch 0: |          | 519/? [01:50<00:00,  4.70it/s, train/loss=35.40]
Epoch 0: |          | 519/? [01:50<00:00,  4.70it/s, train/loss=1.210]
Epoch 0: |          | 520/? [01:50<00:00,  4.70it/s, train/loss=1.210]
Epoch 0: |          | 520/? [01:50<00:00,  4.70it/s, train/loss=31.80]
Epoch 0: |          | 521/? [01:50<00:00,  4.71it/s, train/loss=31.80]
Epoch 0: |          | 521/? [01:50<00:00,  4.71it/s, train/loss=1.160]
Epoch 0: |          | 522/? [01:50<00:00,  4.70it/s, train/loss=1.160]
Epoch 0: |          | 522/? [01:50<00:00,  4.70it/s, train/loss=28.70]
Epoch 0: |          | 523/? [01:50<00:00,  4.71it/s, train/loss=28.70]
Epoch 0: |          | 523/? [01:50<00:00,  4.71it/s, train/loss=1.140]
Epoch 0: |          | 524/? [01:51<00:00,  4.71it/s, train/loss=1.140]
Epoch 0: |          | 524/? [01:51<00:00,  4.71it/s, train/loss=26.10]
Epoch 0: |          | 525/? [01:51<00:00,  4.72it/s, train/loss=26.10]
Epoch 0: |          | 525/? [01:51<00:00,  4.72it/s, train/loss=1.160]
Epoch 0: |          | 526/? [01:51<00:00,  4.71it/s, train/loss=1.160]
Epoch 0: |          | 526/? [01:51<00:00,  4.71it/s, train/loss=21.50]
Epoch 0: |          | 527/? [01:51<00:00,  4.72it/s, train/loss=21.50]
Epoch 0: |          | 527/? [01:51<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 528/? [01:51<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 528/? [01:51<00:00,  4.72it/s, train/loss=27.90]
Epoch 0: |          | 529/? [01:51<00:00,  4.73it/s, train/loss=27.90]
Epoch 0: |          | 529/? [01:51<00:00,  4.73it/s, train/loss=1.250]
Epoch 0: |          | 530/? [01:52<00:00,  4.72it/s, train/loss=1.250]
Epoch 0: |          | 530/? [01:52<00:00,  4.72it/s, train/loss=14.70]
Epoch 0: |          | 531/? [01:52<00:00,  4.73it/s, train/loss=14.70]
Epoch 0: |          | 531/? [01:52<00:00,  4.73it/s, train/loss=1.250]
Epoch 0: |          | 532/? [01:52<00:00,  4.73it/s, train/loss=1.250]
Epoch 0: |          | 532/? [01:52<00:00,  4.73it/s, train/loss=23.20]
Epoch 0: |          | 533/? [01:52<00:00,  4.74it/s, train/loss=23.20]
Epoch 0: |          | 533/? [01:52<00:00,  4.74it/s, train/loss=1.240]
Epoch 0: |          | 534/? [01:52<00:00,  4.73it/s, train/loss=1.240]
Epoch 0: |          | 534/? [01:52<00:00,  4.73it/s, train/loss=12.80]
Epoch 0: |          | 535/? [01:52<00:00,  4.74it/s, train/loss=12.80]
Epoch 0: |          | 535/? [01:52<00:00,  4.74it/s, train/loss=1.230]
Epoch 0: |          | 536/? [01:53<00:00,  4.74it/s, train/loss=1.230]
Epoch 0: |          | 536/? [01:53<00:00,  4.74it/s, train/loss=44.10]
Epoch 0: |          | 537/? [01:53<00:00,  4.75it/s, train/loss=44.10]
Epoch 0: |          | 537/? [01:53<00:00,  4.75it/s, train/loss=1.210]
Epoch 0: |          | 538/? [01:53<00:00,  4.74it/s, train/loss=1.210]
Epoch 0: |          | 538/? [01:53<00:00,  4.74it/s, train/loss=16.80]
Epoch 0: |          | 539/? [01:53<00:00,  4.75it/s, train/loss=16.80]
Epoch 0: |          | 539/? [01:53<00:00,  4.75it/s, train/loss=1.200]
Epoch 0: |          | 540/? [01:53<00:00,  4.75it/s, train/loss=1.200]
Epoch 0: |          | 540/? [01:53<00:00,  4.75it/s, train/loss=16.80]
Epoch 0: |          | 541/? [01:53<00:00,  4.76it/s, train/loss=16.80]
Epoch 0: |          | 541/? [01:53<00:00,  4.76it/s, train/loss=1.190]
Epoch 0: |          | 542/? [01:54<00:00,  4.75it/s, train/loss=1.190]
Epoch 0: |          | 542/? [01:54<00:00,  4.75it/s, train/loss=17.30]
Epoch 0: |          | 543/? [01:54<00:00,  4.76it/s, train/loss=17.30]
Epoch 0: |          | 543/? [01:54<00:00,  4.76it/s, train/loss=1.170]
Epoch 0: |          | 544/? [01:54<00:00,  4.76it/s, train/loss=1.170]
Epoch 0: |          | 544/? [01:54<00:00,  4.76it/s, train/loss=12.40]
Epoch 0: |          | 545/? [01:54<00:00,  4.76it/s, train/loss=12.40]
Epoch 0: |          | 545/? [01:54<00:00,  4.76it/s, train/loss=1.170]
Epoch 0: |          | 546/? [01:54<00:00,  4.76it/s, train/loss=1.170]
Epoch 0: |          | 546/? [01:54<00:00,  4.76it/s, train/loss=25.30]
Epoch 0: |          | 547/? [01:54<00:00,  4.76it/s, train/loss=25.30]
Epoch 0: |          | 547/? [01:54<00:00,  4.76it/s, train/loss=1.150]
Epoch 0: |          | 548/? [01:55<00:00,  4.76it/s, train/loss=1.150]
Epoch 0: |          | 548/? [01:55<00:00,  4.76it/s, train/loss=25.90]
Epoch 0: |          | 549/? [01:55<00:00,  4.76it/s, train/loss=25.90]
Epoch 0: |          | 549/? [01:55<00:00,  4.76it/s, train/loss=1.110]
Epoch 0: |          | 550/? [01:55<00:00,  4.76it/s, train/loss=1.110]
Epoch 0: |          | 550/? [01:55<00:00,  4.76it/s, train/loss=17.80]
Epoch 0: |          | 551/? [01:55<00:00,  4.77it/s, train/loss=17.80]
Epoch 0: |          | 551/? [01:55<00:00,  4.77it/s, train/loss=1.070]
Epoch 0: |          | 552/? [01:55<00:00,  4.77it/s, train/loss=1.070]
Epoch 0: |          | 552/? [01:55<00:00,  4.77it/s, train/loss=36.40]
Epoch 0: |          | 553/? [01:55<00:00,  4.77it/s, train/loss=36.40]
Epoch 0: |          | 553/? [01:55<00:00,  4.77it/s, train/loss=1.030]
Epoch 0: |          | 554/? [01:56<00:00,  4.77it/s, train/loss=1.030]
Epoch 0: |          | 554/? [01:56<00:00,  4.77it/s, train/loss=16.90]
Epoch 0: |          | 555/? [01:56<00:00,  4.78it/s, train/loss=16.90]
Epoch 0: |          | 555/? [01:56<00:00,  4.78it/s, train/loss=1.020]
Epoch 0: |          | 556/? [01:56<00:00,  4.77it/s, train/loss=1.020]
Epoch 0: |          | 556/? [01:56<00:00,  4.77it/s, train/loss=20.60]
Epoch 0: |          | 557/? [01:56<00:00,  4.78it/s, train/loss=20.60]
Epoch 0: |          | 557/? [01:56<00:00,  4.78it/s, train/loss=1.010]
Epoch 0: |          | 558/? [01:56<00:00,  4.78it/s, train/loss=1.010]
Epoch 0: |          | 558/? [01:56<00:00,  4.78it/s, train/loss=28.10]
Epoch 0: |          | 559/? [01:56<00:00,  4.78it/s, train/loss=28.10]
Epoch 0: |          | 559/? [01:56<00:00,  4.78it/s, train/loss=1.020]
Epoch 0: |          | 560/? [01:57<00:00,  4.77it/s, train/loss=1.020]
Epoch 0: |          | 560/? [01:57<00:00,  4.77it/s, train/loss=37.20]
Epoch 0: |          | 561/? [01:57<00:00,  4.78it/s, train/loss=37.20]
Epoch 0: |          | 561/? [01:57<00:00,  4.78it/s, train/loss=1.030]
Epoch 0: |          | 562/? [01:57<00:00,  4.77it/s, train/loss=1.030]
Epoch 0: |          | 562/? [01:57<00:00,  4.77it/s, train/loss=10.80]
Epoch 0: |          | 563/? [01:57<00:00,  4.78it/s, train/loss=10.80]
Epoch 0: |          | 563/? [01:57<00:00,  4.78it/s, train/loss=1.050]
Epoch 0: |          | 564/? [01:58<00:00,  4.77it/s, train/loss=1.050]
Epoch 0: |          | 564/? [01:58<00:00,  4.77it/s, train/loss=23.20]
Epoch 0: |          | 565/? [01:58<00:00,  4.77it/s, train/loss=23.20]
Epoch 0: |          | 565/? [01:58<00:00,  4.77it/s, train/loss=1.080]
Epoch 0: |          | 566/? [01:58<00:00,  4.77it/s, train/loss=1.080]
Epoch 0: |          | 566/? [01:58<00:00,  4.77it/s, train/loss=23.40]
Epoch 0: |          | 567/? [01:58<00:00,  4.77it/s, train/loss=23.40]
Epoch 0: |          | 567/? [01:58<00:00,  4.77it/s, train/loss=1.130]
Epoch 0: |          | 568/? [01:59<00:00,  4.77it/s, train/loss=1.130]
Epoch 0: |          | 568/? [01:59<00:00,  4.77it/s, train/loss=53.80]
Epoch 0: |          | 569/? [01:59<00:00,  4.77it/s, train/loss=53.80]
Epoch 0: |          | 569/? [01:59<00:00,  4.77it/s, train/loss=1.140]
Epoch 0: |          | 570/? [01:59<00:00,  4.77it/s, train/loss=1.140]
Epoch 0: |          | 570/? [01:59<00:00,  4.77it/s, train/loss=18.30]
Epoch 0: |          | 571/? [01:59<00:00,  4.77it/s, train/loss=18.30]
Epoch 0: |          | 571/? [01:59<00:00,  4.77it/s, train/loss=1.120]
Epoch 0: |          | 572/? [02:00<00:00,  4.76it/s, train/loss=1.120]
Epoch 0: |          | 572/? [02:00<00:00,  4.76it/s, train/loss=11.50]
Epoch 0: |          | 573/? [02:00<00:00,  4.77it/s, train/loss=11.50]
Epoch 0: |          | 573/? [02:00<00:00,  4.77it/s, train/loss=1.090]
Epoch 0: |          | 574/? [02:00<00:00,  4.76it/s, train/loss=1.090]
Epoch 0: |          | 574/? [02:00<00:00,  4.76it/s, train/loss=15.20]
Epoch 0: |          | 575/? [02:00<00:00,  4.77it/s, train/loss=15.20]
Epoch 0: |          | 575/? [02:00<00:00,  4.77it/s, train/loss=1.060]
Epoch 0: |          | 576/? [02:00<00:00,  4.76it/s, train/loss=1.060]
Epoch 0: |          | 576/? [02:00<00:00,  4.76it/s, train/loss=33.00]
Epoch 0: |          | 577/? [02:01<00:00,  4.77it/s, train/loss=33.00]
Epoch 0: |          | 577/? [02:01<00:00,  4.77it/s, train/loss=1.060]
Epoch 0: |          | 578/? [02:01<00:00,  4.76it/s, train/loss=1.060]
Epoch 0: |          | 578/? [02:01<00:00,  4.76it/s, train/loss=21.20]
Epoch 0: |          | 579/? [02:01<00:00,  4.76it/s, train/loss=21.20]
Epoch 0: |          | 579/? [02:01<00:00,  4.76it/s, train/loss=1.090]
Epoch 0: |          | 580/? [02:01<00:00,  4.76it/s, train/loss=1.090]
Epoch 0: |          | 580/? [02:01<00:00,  4.76it/s, train/loss=83.40]
Epoch 0: |          | 581/? [02:02<00:00,  4.76it/s, train/loss=83.40]
Epoch 0: |          | 581/? [02:02<00:00,  4.76it/s, train/loss=1.160]
Epoch 0: |          | 582/? [02:02<00:00,  4.76it/s, train/loss=1.160]
Epoch 0: |          | 582/? [02:02<00:00,  4.76it/s, train/loss=19.10]
Epoch 0: |          | 583/? [02:02<00:00,  4.76it/s, train/loss=19.10]
Epoch 0: |          | 583/? [02:02<00:00,  4.76it/s, train/loss=1.240]
Epoch 0: |          | 584/? [02:02<00:00,  4.75it/s, train/loss=1.240]
Epoch 0: |          | 584/? [02:02<00:00,  4.75it/s, train/loss=60.20]
Epoch 0: |          | 585/? [02:02<00:00,  4.76it/s, train/loss=60.20]
Epoch 0: |          | 585/? [02:02<00:00,  4.76it/s, train/loss=1.230]
Epoch 0: |          | 586/? [02:03<00:00,  4.75it/s, train/loss=1.230]
Epoch 0: |          | 586/? [02:03<00:00,  4.75it/s, train/loss=21.30]
Epoch 0: |          | 587/? [02:03<00:00,  4.76it/s, train/loss=21.30]
Epoch 0: |          | 587/? [02:03<00:00,  4.76it/s, train/loss=1.210]
Epoch 0: |          | 588/? [02:03<00:00,  4.75it/s, train/loss=1.210]
Epoch 0: |          | 588/? [02:03<00:00,  4.75it/s, train/loss=32.10]
Epoch 0: |          | 589/? [02:03<00:00,  4.76it/s, train/loss=32.10]
Epoch 0: |          | 589/? [02:03<00:00,  4.76it/s, train/loss=1.240]
Epoch 0: |          | 590/? [02:04<00:00,  4.75it/s, train/loss=1.240]
Epoch 0: |          | 590/? [02:04<00:00,  4.75it/s, train/loss=28.90]
Epoch 0: |          | 591/? [02:04<00:00,  4.76it/s, train/loss=28.90]
Epoch 0: |          | 591/? [02:04<00:00,  4.76it/s, train/loss=1.270]
Epoch 0: |          | 592/? [02:04<00:00,  4.75it/s, train/loss=1.270]
Epoch 0: |          | 592/? [02:04<00:00,  4.75it/s, train/loss=12.50]
Epoch 0: |          | 593/? [02:04<00:00,  4.76it/s, train/loss=12.50]
Epoch 0: |          | 593/? [02:04<00:00,  4.76it/s, train/loss=1.260]
Epoch 0: |          | 594/? [02:04<00:00,  4.76it/s, train/loss=1.260]
Epoch 0: |          | 594/? [02:04<00:00,  4.76it/s, train/loss=24.00]
Epoch 0: |          | 595/? [02:04<00:00,  4.77it/s, train/loss=24.00]
Epoch 0: |          | 595/? [02:04<00:00,  4.77it/s, train/loss=1.230]
Epoch 0: |          | 596/? [02:05<00:00,  4.76it/s, train/loss=1.230]
Epoch 0: |          | 596/? [02:05<00:00,  4.76it/s, train/loss=15.00]
Epoch 0: |          | 597/? [02:05<00:00,  4.77it/s, train/loss=15.00]
Epoch 0: |          | 597/? [02:05<00:00,  4.77it/s, train/loss=1.210]
Epoch 0: |          | 598/? [02:05<00:00,  4.77it/s, train/loss=1.210]
Epoch 0: |          | 598/? [02:05<00:00,  4.77it/s, train/loss=10.30]
Epoch 0: |          | 599/? [02:05<00:00,  4.77it/s, train/loss=10.30]
Epoch 0: |          | 599/? [02:05<00:00,  4.77it/s, train/loss=1.200]
Epoch 0: |          | 600/? [02:05<00:00,  4.77it/s, train/loss=1.200]
Epoch 0: |          | 600/? [02:05<00:00,  4.77it/s, train/loss=21.10]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:07<00:00,  5.51it/s]

Epoch 0: |          | 600/? [02:13<00:00,  4.48it/s, train/loss=21.10]
Epoch 0: |          | 601/? [02:14<00:00,  4.47it/s, train/loss=21.10]
Epoch 0: |          | 601/? [02:14<00:00,  4.47it/s, train/loss=1.190]
Epoch 0: |          | 602/? [02:14<00:00,  4.47it/s, train/loss=1.190]
Epoch 0: |          | 602/? [02:14<00:00,  4.47it/s, train/loss=34.40]
Epoch 0: |          | 603/? [02:14<00:00,  4.48it/s, train/loss=34.40]
Epoch 0: |          | 603/? [02:14<00:00,  4.48it/s, train/loss=1.200]
Epoch 0: |          | 604/? [02:14<00:00,  4.47it/s, train/loss=1.200]
Epoch 0: |          | 604/? [02:14<00:00,  4.47it/s, train/loss=17.70]
Epoch 0: |          | 605/? [02:15<00:00,  4.48it/s, train/loss=17.70]
Epoch 0: |          | 605/? [02:15<00:00,  4.48it/s, train/loss=1.220]
Epoch 0: |          | 606/? [02:15<00:00,  4.48it/s, train/loss=1.220]
Epoch 0: |          | 606/? [02:15<00:00,  4.48it/s, train/loss=21.60]
Epoch 0: |          | 607/? [02:15<00:00,  4.49it/s, train/loss=21.60]
Epoch 0: |          | 607/? [02:15<00:00,  4.49it/s, train/loss=1.190]
Epoch 0: |          | 608/? [02:15<00:00,  4.48it/s, train/loss=1.190]
Epoch 0: |          | 608/? [02:15<00:00,  4.48it/s, train/loss=21.10]
Epoch 0: |          | 609/? [02:15<00:00,  4.49it/s, train/loss=21.10]
Epoch 0: |          | 609/? [02:15<00:00,  4.49it/s, train/loss=1.120]
Epoch 0: |          | 610/? [02:15<00:00,  4.49it/s, train/loss=1.120]
Epoch 0: |          | 610/? [02:15<00:00,  4.49it/s, train/loss=23.20]
Epoch 0: |          | 611/? [02:15<00:00,  4.49it/s, train/loss=23.20]
Epoch 0: |          | 611/? [02:15<00:00,  4.49it/s, train/loss=1.070]
Epoch 0: |          | 612/? [02:16<00:00,  4.49it/s, train/loss=1.070]
Epoch 0: |          | 612/? [02:16<00:00,  4.49it/s, train/loss=24.80]
Epoch 0: |          | 613/? [02:16<00:00,  4.50it/s, train/loss=24.80]
Epoch 0: |          | 613/? [02:16<00:00,  4.50it/s, train/loss=1.040]
Epoch 0: |          | 614/? [02:16<00:00,  4.50it/s, train/loss=1.040]
Epoch 0: |          | 614/? [02:16<00:00,  4.50it/s, train/loss=12.10]
Epoch 0: |          | 615/? [02:16<00:00,  4.50it/s, train/loss=12.10]
Epoch 0: |          | 615/? [02:16<00:00,  4.50it/s, train/loss=1.030]
Epoch 0: |          | 616/? [02:16<00:00,  4.50it/s, train/loss=1.030]
Epoch 0: |          | 616/? [02:16<00:00,  4.50it/s, train/loss=43.70]
Epoch 0: |          | 617/? [02:16<00:00,  4.51it/s, train/loss=43.70]
Epoch 0: |          | 617/? [02:16<00:00,  4.51it/s, train/loss=1.050]
Epoch 0: |          | 618/? [02:17<00:00,  4.51it/s, train/loss=1.050]
Epoch 0: |          | 618/? [02:17<00:00,  4.51it/s, train/loss=19.50]
Epoch 0: |          | 619/? [02:17<00:00,  4.51it/s, train/loss=19.50]
Epoch 0: |          | 619/? [02:17<00:00,  4.51it/s, train/loss=1.090]
Epoch 0: |          | 620/? [02:17<00:00,  4.51it/s, train/loss=1.090]
Epoch 0: |          | 620/? [02:17<00:00,  4.51it/s, train/loss=31.00]
Epoch 0: |          | 621/? [02:17<00:00,  4.52it/s, train/loss=31.00]
Epoch 0: |          | 621/? [02:17<00:00,  4.52it/s, train/loss=1.130]
Epoch 0: |          | 622/? [02:17<00:00,  4.52it/s, train/loss=1.130]
Epoch 0: |          | 622/? [02:17<00:00,  4.52it/s, train/loss=18.60]
Epoch 0: |          | 623/? [02:17<00:00,  4.52it/s, train/loss=18.60]
Epoch 0: |          | 623/? [02:17<00:00,  4.52it/s, train/loss=1.170]
Epoch 0: |          | 624/? [02:18<00:00,  4.52it/s, train/loss=1.170]
Epoch 0: |          | 624/? [02:18<00:00,  4.52it/s, train/loss=16.00]
Epoch 0: |          | 625/? [02:18<00:00,  4.53it/s, train/loss=16.00]
Epoch 0: |          | 625/? [02:18<00:00,  4.53it/s, train/loss=1.190]
Epoch 0: |          | 626/? [02:18<00:00,  4.52it/s, train/loss=1.190]
Epoch 0: |          | 626/? [02:18<00:00,  4.52it/s, train/loss=38.30]
Epoch 0: |          | 627/? [02:18<00:00,  4.53it/s, train/loss=38.30]
Epoch 0: |          | 627/? [02:18<00:00,  4.53it/s, train/loss=1.220]
Epoch 0: |          | 628/? [02:18<00:00,  4.53it/s, train/loss=1.220]
Epoch 0: |          | 628/? [02:18<00:00,  4.53it/s, train/loss=27.00]
Epoch 0: |          | 629/? [02:18<00:00,  4.53it/s, train/loss=27.00]
Epoch 0: |          | 629/? [02:18<00:00,  4.53it/s, train/loss=1.220]
Epoch 0: |          | 630/? [02:18<00:00,  4.53it/s, train/loss=1.220]
Epoch 0: |          | 630/? [02:18<00:00,  4.53it/s, train/loss=23.60]
Epoch 0: |          | 631/? [02:19<00:00,  4.54it/s, train/loss=23.60]
Epoch 0: |          | 631/? [02:19<00:00,  4.54it/s, train/loss=1.170]
Epoch 0: |          | 632/? [02:19<00:00,  4.54it/s, train/loss=1.170]
Epoch 0: |          | 632/? [02:19<00:00,  4.54it/s, train/loss=9.630]
Epoch 0: |          | 633/? [02:19<00:00,  4.54it/s, train/loss=9.630]
Epoch 0: |          | 633/? [02:19<00:00,  4.54it/s, train/loss=1.140]
Epoch 0: |          | 634/? [02:19<00:00,  4.54it/s, train/loss=1.140]
Epoch 0: |          | 634/? [02:19<00:00,  4.54it/s, train/loss=78.00]
Epoch 0: |          | 635/? [02:19<00:00,  4.55it/s, train/loss=78.00]
Epoch 0: |          | 635/? [02:19<00:00,  4.55it/s, train/loss=1.120]
Epoch 0: |          | 636/? [02:19<00:00,  4.55it/s, train/loss=1.120]
Epoch 0: |          | 636/? [02:19<00:00,  4.55it/s, train/loss=11.30]
Epoch 0: |          | 637/? [02:19<00:00,  4.55it/s, train/loss=11.30]
Epoch 0: |          | 637/? [02:19<00:00,  4.55it/s, train/loss=1.110]
Epoch 0: |          | 638/? [02:20<00:00,  4.55it/s, train/loss=1.110]
Epoch 0: |          | 638/? [02:20<00:00,  4.55it/s, train/loss=18.90]
Epoch 0: |          | 639/? [02:20<00:00,  4.56it/s, train/loss=18.90]
Epoch 0: |          | 639/? [02:20<00:00,  4.56it/s, train/loss=1.110]
Epoch 0: |          | 640/? [02:20<00:00,  4.55it/s, train/loss=1.110]
Epoch 0: |          | 640/? [02:20<00:00,  4.55it/s, train/loss=26.10]
Epoch 0: |          | 641/? [02:20<00:00,  4.56it/s, train/loss=26.10]
Epoch 0: |          | 641/? [02:20<00:00,  4.56it/s, train/loss=1.100]
Epoch 0: |          | 642/? [02:21<00:00,  4.55it/s, train/loss=1.100]
Epoch 0: |          | 642/? [02:21<00:00,  4.55it/s, train/loss=14.20]
Epoch 0: |          | 643/? [02:21<00:00,  4.56it/s, train/loss=14.20]
Epoch 0: |          | 643/? [02:21<00:00,  4.56it/s, train/loss=1.080]
Epoch 0: |          | 644/? [02:21<00:00,  4.55it/s, train/loss=1.080]
Epoch 0: |          | 644/? [02:21<00:00,  4.55it/s, train/loss=40.70]
Epoch 0: |          | 645/? [02:21<00:00,  4.56it/s, train/loss=40.70]
Epoch 0: |          | 645/? [02:21<00:00,  4.56it/s, train/loss=1.070]
Epoch 0: |          | 646/? [02:21<00:00,  4.55it/s, train/loss=1.070]
Epoch 0: |          | 646/? [02:21<00:00,  4.55it/s, train/loss=32.30]
Epoch 0: |          | 647/? [02:21<00:00,  4.56it/s, train/loss=32.30]
Epoch 0: |          | 647/? [02:21<00:00,  4.56it/s, train/loss=1.080]
Epoch 0: |          | 648/? [02:22<00:00,  4.56it/s, train/loss=1.080]
Epoch 0: |          | 648/? [02:22<00:00,  4.56it/s, train/loss=38.60]
Epoch 0: |          | 649/? [02:22<00:00,  4.56it/s, train/loss=38.60]
Epoch 0: |          | 649/? [02:22<00:00,  4.56it/s, train/loss=1.080]
Epoch 0: |          | 650/? [02:22<00:00,  4.56it/s, train/loss=1.080]
Epoch 0: |          | 650/? [02:22<00:00,  4.56it/s, train/loss=26.00]
Epoch 0: |          | 651/? [02:22<00:00,  4.57it/s, train/loss=26.00]
Epoch 0: |          | 651/? [02:22<00:00,  4.57it/s, train/loss=1.080]
Epoch 0: |          | 652/? [02:22<00:00,  4.57it/s, train/loss=1.080]
Epoch 0: |          | 652/? [02:22<00:00,  4.57it/s, train/loss=40.00]
Epoch 0: |          | 653/? [02:22<00:00,  4.57it/s, train/loss=40.00]
Epoch 0: |          | 653/? [02:22<00:00,  4.57it/s, train/loss=1.080]
Epoch 0: |          | 654/? [02:23<00:00,  4.57it/s, train/loss=1.080]
Epoch 0: |          | 654/? [02:23<00:00,  4.57it/s, train/loss=32.60]
Epoch 0: |          | 655/? [02:23<00:00,  4.58it/s, train/loss=32.60]
Epoch 0: |          | 655/? [02:23<00:00,  4.58it/s, train/loss=1.110]
Epoch 0: |          | 656/? [02:23<00:00,  4.57it/s, train/loss=1.110]
Epoch 0: |          | 656/? [02:23<00:00,  4.57it/s, train/loss=13.30]
Epoch 0: |          | 657/? [02:23<00:00,  4.58it/s, train/loss=13.30]
Epoch 0: |          | 657/? [02:23<00:00,  4.58it/s, train/loss=1.140]
Epoch 0: |          | 658/? [02:23<00:00,  4.58it/s, train/loss=1.140]
Epoch 0: |          | 658/? [02:23<00:00,  4.58it/s, train/loss=41.00]
Epoch 0: |          | 659/? [02:23<00:00,  4.58it/s, train/loss=41.00]
Epoch 0: |          | 659/? [02:23<00:00,  4.58it/s, train/loss=1.150]
Epoch 0: |          | 660/? [02:24<00:00,  4.58it/s, train/loss=1.150]
Epoch 0: |          | 660/? [02:24<00:00,  4.58it/s, train/loss=13.90]
Epoch 0: |          | 661/? [02:24<00:00,  4.59it/s, train/loss=13.90]
Epoch 0: |          | 661/? [02:24<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 662/? [02:24<00:00,  4.59it/s, train/loss=1.170]
Epoch 0: |          | 662/? [02:24<00:00,  4.59it/s, train/loss=81.40]
Epoch 0: |          | 663/? [02:24<00:00,  4.59it/s, train/loss=81.40]
Epoch 0: |          | 663/? [02:24<00:00,  4.59it/s, train/loss=1.220]
Epoch 0: |          | 664/? [02:24<00:00,  4.59it/s, train/loss=1.220]
Epoch 0: |          | 664/? [02:24<00:00,  4.59it/s, train/loss=12.20]
Epoch 0: |          | 665/? [02:24<00:00,  4.60it/s, train/loss=12.20]
Epoch 0: |          | 665/? [02:24<00:00,  4.60it/s, train/loss=1.240]
Epoch 0: |          | 666/? [02:24<00:00,  4.59it/s, train/loss=1.240]
Epoch 0: |          | 666/? [02:24<00:00,  4.59it/s, train/loss=26.10]
Epoch 0: |          | 667/? [02:24<00:00,  4.60it/s, train/loss=26.10]
Epoch 0: |          | 667/? [02:24<00:00,  4.60it/s, train/loss=1.150]
Epoch 0: |          | 668/? [02:25<00:00,  4.60it/s, train/loss=1.150]
Epoch 0: |          | 668/? [02:25<00:00,  4.60it/s, train/loss=38.30]
Epoch 0: |          | 669/? [02:25<00:00,  4.60it/s, train/loss=38.30]
Epoch 0: |          | 669/? [02:25<00:00,  4.60it/s, train/loss=1.090]
Epoch 0: |          | 670/? [02:25<00:00,  4.60it/s, train/loss=1.090]
Epoch 0: |          | 670/? [02:25<00:00,  4.60it/s, train/loss=25.60]
Epoch 0: |          | 671/? [02:25<00:00,  4.61it/s, train/loss=25.60]
Epoch 0: |          | 671/? [02:25<00:00,  4.61it/s, train/loss=1.060]
Epoch 0: |          | 672/? [02:25<00:00,  4.61it/s, train/loss=1.060]
Epoch 0: |          | 672/? [02:25<00:00,  4.61it/s, train/loss=14.40]
Epoch 0: |          | 673/? [02:25<00:00,  4.61it/s, train/loss=14.40]
Epoch 0: |          | 673/? [02:25<00:00,  4.61it/s, train/loss=1.060]
Epoch 0: |          | 674/? [02:26<00:00,  4.61it/s, train/loss=1.060]
Epoch 0: |          | 674/? [02:26<00:00,  4.61it/s, train/loss=20.00]
Epoch 0: |          | 675/? [02:26<00:00,  4.62it/s, train/loss=20.00]
Epoch 0: |          | 675/? [02:26<00:00,  4.62it/s, train/loss=1.060]
Epoch 0: |          | 676/? [02:26<00:00,  4.61it/s, train/loss=1.060]
Epoch 0: |          | 676/? [02:26<00:00,  4.61it/s, train/loss=18.30]
Epoch 0: |          | 677/? [02:26<00:00,  4.62it/s, train/loss=18.30]
Epoch 0: |          | 677/? [02:26<00:00,  4.62it/s, train/loss=1.060]
Epoch 0: |          | 678/? [02:26<00:00,  4.62it/s, train/loss=1.060]
Epoch 0: |          | 678/? [02:26<00:00,  4.62it/s, train/loss=46.40]
Epoch 0: |          | 679/? [02:26<00:00,  4.62it/s, train/loss=46.40]
Epoch 0: |          | 679/? [02:26<00:00,  4.62it/s, train/loss=1.050]
Epoch 0: |          | 680/? [02:27<00:00,  4.62it/s, train/loss=1.050]
Epoch 0: |          | 680/? [02:27<00:00,  4.62it/s, train/loss=14.70]
Epoch 0: |          | 681/? [02:27<00:00,  4.63it/s, train/loss=14.70]
Epoch 0: |          | 681/? [02:27<00:00,  4.63it/s, train/loss=1.050]
Epoch 0: |          | 682/? [02:27<00:00,  4.63it/s, train/loss=1.050]
Epoch 0: |          | 682/? [02:27<00:00,  4.63it/s, train/loss=29.90]
Epoch 0: |          | 683/? [02:27<00:00,  4.63it/s, train/loss=29.90]
Epoch 0: |          | 683/? [02:27<00:00,  4.63it/s, train/loss=1.050]
Epoch 0: |          | 684/? [02:27<00:00,  4.63it/s, train/loss=1.050]
Epoch 0: |          | 684/? [02:27<00:00,  4.63it/s, train/loss=20.00]
Epoch 0: |          | 685/? [02:27<00:00,  4.64it/s, train/loss=20.00]
Epoch 0: |          | 685/? [02:27<00:00,  4.64it/s, train/loss=1.030]
Epoch 0: |          | 686/? [02:28<00:00,  4.63it/s, train/loss=1.030]
Epoch 0: |          | 686/? [02:28<00:00,  4.63it/s, train/loss=23.60]
Epoch 0: |          | 687/? [02:28<00:00,  4.64it/s, train/loss=23.60]
Epoch 0: |          | 687/? [02:28<00:00,  4.64it/s, train/loss=1.010]
Epoch 0: |          | 688/? [02:28<00:00,  4.64it/s, train/loss=1.010]
Epoch 0: |          | 688/? [02:28<00:00,  4.64it/s, train/loss=18.60]
Epoch 0: |          | 689/? [02:28<00:00,  4.64it/s, train/loss=18.60]
Epoch 0: |          | 689/? [02:28<00:00,  4.64it/s, train/loss=0.995]
Epoch 0: |          | 690/? [02:28<00:00,  4.64it/s, train/loss=0.995]
Epoch 0: |          | 690/? [02:28<00:00,  4.64it/s, train/loss=21.90]
Epoch 0: |          | 691/? [02:28<00:00,  4.65it/s, train/loss=21.90]
Epoch 0: |          | 691/? [02:28<00:00,  4.65it/s, train/loss=0.975]
Epoch 0: |          | 692/? [02:28<00:00,  4.65it/s, train/loss=0.975]
Epoch 0: |          | 692/? [02:28<00:00,  4.65it/s, train/loss=37.90]
Epoch 0: |          | 693/? [02:28<00:00,  4.65it/s, train/loss=37.90]
Epoch 0: |          | 693/? [02:28<00:00,  4.65it/s, train/loss=0.958]
Epoch 0: |          | 694/? [02:29<00:00,  4.65it/s, train/loss=0.958]
Epoch 0: |          | 694/? [02:29<00:00,  4.65it/s, train/loss=23.10]
Epoch 0: |          | 695/? [02:29<00:00,  4.66it/s, train/loss=23.10]
Epoch 0: |          | 695/? [02:29<00:00,  4.66it/s, train/loss=0.954]
Epoch 0: |          | 696/? [02:29<00:00,  4.65it/s, train/loss=0.954]
Epoch 0: |          | 696/? [02:29<00:00,  4.65it/s, train/loss=32.60]
Epoch 0: |          | 697/? [02:29<00:00,  4.66it/s, train/loss=32.60]
Epoch 0: |          | 697/? [02:29<00:00,  4.66it/s, train/loss=0.965]
Epoch 0: |          | 698/? [02:29<00:00,  4.66it/s, train/loss=0.965]
Epoch 0: |          | 698/? [02:29<00:00,  4.66it/s, train/loss=23.20]
Epoch 0: |          | 699/? [02:29<00:00,  4.66it/s, train/loss=23.20]
Epoch 0: |          | 699/? [02:29<00:00,  4.66it/s, train/loss=0.967]
Epoch 0: |          | 700/? [02:30<00:00,  4.66it/s, train/loss=0.967]
Epoch 0: |          | 700/? [02:30<00:00,  4.66it/s, train/loss=41.20]
Epoch 0: |          | 701/? [02:30<00:00,  4.67it/s, train/loss=41.20]
Epoch 0: |          | 701/? [02:30<00:00,  4.67it/s, train/loss=0.955]
Epoch 0: |          | 702/? [02:30<00:00,  4.67it/s, train/loss=0.955]
Epoch 0: |          | 702/? [02:30<00:00,  4.67it/s, train/loss=24.60]
Epoch 0: |          | 703/? [02:30<00:00,  4.67it/s, train/loss=24.60]
Epoch 0: |          | 703/? [02:30<00:00,  4.67it/s, train/loss=0.931]
Epoch 0: |          | 704/? [02:30<00:00,  4.67it/s, train/loss=0.931]
Epoch 0: |          | 704/? [02:30<00:00,  4.67it/s, train/loss=8.580]
Epoch 0: |          | 705/? [02:30<00:00,  4.68it/s, train/loss=8.580]
Epoch 0: |          | 705/? [02:30<00:00,  4.68it/s, train/loss=0.905]
Epoch 0: |          | 706/? [02:31<00:00,  4.67it/s, train/loss=0.905]
Epoch 0: |          | 706/? [02:31<00:00,  4.67it/s, train/loss=20.60]
Epoch 0: |          | 707/? [02:31<00:00,  4.68it/s, train/loss=20.60]
Epoch 0: |          | 707/? [02:31<00:00,  4.68it/s, train/loss=0.894]
Epoch 0: |          | 708/? [02:31<00:00,  4.68it/s, train/loss=0.894]
Epoch 0: |          | 708/? [02:31<00:00,  4.68it/s, train/loss=23.60]
Epoch 0: |          | 709/? [02:31<00:00,  4.68it/s, train/loss=23.60]
Epoch 0: |          | 709/? [02:31<00:00,  4.68it/s, train/loss=0.883]
Epoch 0: |          | 710/? [02:31<00:00,  4.68it/s, train/loss=0.883]
Epoch 0: |          | 710/? [02:31<00:00,  4.68it/s, train/loss=14.50]
Epoch 0: |          | 711/? [02:31<00:00,  4.68it/s, train/loss=14.50]
Epoch 0: |          | 711/? [02:31<00:00,  4.68it/s, train/loss=0.874]
Epoch 0: |          | 712/? [02:32<00:00,  4.68it/s, train/loss=0.874]
Epoch 0: |          | 712/? [02:32<00:00,  4.68it/s, train/loss=16.80]
Epoch 0: |          | 713/? [02:32<00:00,  4.68it/s, train/loss=16.80]
Epoch 0: |          | 713/? [02:32<00:00,  4.68it/s, train/loss=0.883]
Epoch 0: |          | 714/? [02:32<00:00,  4.68it/s, train/loss=0.883]
Epoch 0: |          | 714/? [02:32<00:00,  4.68it/s, train/loss=28.60]
Epoch 0: |          | 715/? [02:32<00:00,  4.68it/s, train/loss=28.60]
Epoch 0: |          | 715/? [02:32<00:00,  4.68it/s, train/loss=0.896]
Epoch 0: |          | 716/? [02:33<00:00,  4.68it/s, train/loss=0.896]
Epoch 0: |          | 716/? [02:33<00:00,  4.68it/s, train/loss=13.50]
Epoch 0: |          | 717/? [02:33<00:00,  4.68it/s, train/loss=13.50]
Epoch 0: |          | 717/? [02:33<00:00,  4.68it/s, train/loss=0.912]
Epoch 0: |          | 718/? [02:33<00:00,  4.68it/s, train/loss=0.912]
Epoch 0: |          | 718/? [02:33<00:00,  4.68it/s, train/loss=24.30]
Epoch 0: |          | 719/? [02:33<00:00,  4.69it/s, train/loss=24.30]
Epoch 0: |          | 719/? [02:33<00:00,  4.69it/s, train/loss=0.939]
Epoch 0: |          | 720/? [02:33<00:00,  4.68it/s, train/loss=0.939]
Epoch 0: |          | 720/? [02:33<00:00,  4.68it/s, train/loss=27.00]
Epoch 0: |          | 721/? [02:33<00:00,  4.69it/s, train/loss=27.00]
Epoch 0: |          | 721/? [02:33<00:00,  4.69it/s, train/loss=0.974]
Epoch 0: |          | 722/? [02:34<00:00,  4.69it/s, train/loss=0.974]
Epoch 0: |          | 722/? [02:34<00:00,  4.69it/s, train/loss=36.20]
Epoch 0: |          | 723/? [02:34<00:00,  4.69it/s, train/loss=36.20]
Epoch 0: |          | 723/? [02:34<00:00,  4.69it/s, train/loss=0.974]
Epoch 0: |          | 724/? [02:34<00:00,  4.69it/s, train/loss=0.974]
Epoch 0: |          | 724/? [02:34<00:00,  4.69it/s, train/loss=20.80]
Epoch 0: |          | 725/? [02:34<00:00,  4.70it/s, train/loss=20.80]
Epoch 0: |          | 725/? [02:34<00:00,  4.70it/s, train/loss=0.970]
Epoch 0: |          | 726/? [02:34<00:00,  4.69it/s, train/loss=0.970]
Epoch 0: |          | 726/? [02:34<00:00,  4.69it/s, train/loss=20.00]
Epoch 0: |          | 727/? [02:34<00:00,  4.70it/s, train/loss=20.00]
Epoch 0: |          | 727/? [02:34<00:00,  4.70it/s, train/loss=0.968]
Epoch 0: |          | 728/? [02:34<00:00,  4.70it/s, train/loss=0.968]
Epoch 0: |          | 728/? [02:34<00:00,  4.70it/s, train/loss=12.10]
Epoch 0: |          | 729/? [02:34<00:00,  4.70it/s, train/loss=12.10]
Epoch 0: |          | 729/? [02:34<00:00,  4.70it/s, train/loss=0.960]
Epoch 0: |          | 730/? [02:35<00:00,  4.70it/s, train/loss=0.960]
Epoch 0: |          | 730/? [02:35<00:00,  4.70it/s, train/loss=19.20]
Epoch 0: |          | 731/? [02:35<00:00,  4.71it/s, train/loss=19.20]
Epoch 0: |          | 731/? [02:35<00:00,  4.71it/s, train/loss=0.948]
Epoch 0: |          | 732/? [02:35<00:00,  4.71it/s, train/loss=0.948]
Epoch 0: |          | 732/? [02:35<00:00,  4.71it/s, train/loss=18.60]
Epoch 0: |          | 733/? [02:35<00:00,  4.71it/s, train/loss=18.60]
Epoch 0: |          | 733/? [02:35<00:00,  4.71it/s, train/loss=0.951]
Epoch 0: |          | 734/? [02:35<00:00,  4.71it/s, train/loss=0.951]
Epoch 0: |          | 734/? [02:35<00:00,  4.71it/s, train/loss=12.20]
Epoch 0: |          | 735/? [02:35<00:00,  4.71it/s, train/loss=12.20]
Epoch 0: |          | 735/? [02:35<00:00,  4.71it/s, train/loss=0.977]
Epoch 0: |          | 736/? [02:36<00:00,  4.71it/s, train/loss=0.977]
Epoch 0: |          | 736/? [02:36<00:00,  4.71it/s, train/loss=37.10]
Epoch 0: |          | 737/? [02:36<00:00,  4.72it/s, train/loss=37.10]
Epoch 0: |          | 737/? [02:36<00:00,  4.72it/s, train/loss=1.170]
Epoch 0: |          | 738/? [02:36<00:00,  4.72it/s, train/loss=1.170]
Epoch 0: |          | 738/? [02:36<00:00,  4.72it/s, train/loss=22.80]
Epoch 0: |          | 739/? [02:36<00:00,  4.72it/s, train/loss=22.80]
Epoch 0: |          | 739/? [02:36<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 740/? [02:36<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 740/? [02:36<00:00,  4.72it/s, train/loss=29.60]
Epoch 0: |          | 741/? [02:36<00:00,  4.72it/s, train/loss=29.60]
Epoch 0: |          | 741/? [02:36<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 742/? [02:37<00:00,  4.72it/s, train/loss=1.210]
Epoch 0: |          | 742/? [02:37<00:00,  4.72it/s, train/loss=35.50]
Epoch 0: |          | 743/? [02:37<00:00,  4.73it/s, train/loss=35.50]
Epoch 0: |          | 743/? [02:37<00:00,  4.73it/s, train/loss=1.200]
Epoch 0: |          | 744/? [02:37<00:00,  4.73it/s, train/loss=1.200]
Epoch 0: |          | 744/? [02:37<00:00,  4.73it/s, train/loss=42.00]
Epoch 0: |          | 745/? [02:37<00:00,  4.73it/s, train/loss=42.00]
Epoch 0: |          | 745/? [02:37<00:00,  4.73it/s, train/loss=1.180]
Epoch 0: |          | 746/? [02:37<00:00,  4.73it/s, train/loss=1.180]
Epoch 0: |          | 746/? [02:37<00:00,  4.73it/s, train/loss=34.50]
Epoch 0: |          | 747/? [02:37<00:00,  4.74it/s, train/loss=34.50]
Epoch 0: |          | 747/? [02:37<00:00,  4.74it/s, train/loss=1.170]
Epoch 0: |          | 748/? [02:38<00:00,  4.73it/s, train/loss=1.170]
Epoch 0: |          | 748/? [02:38<00:00,  4.73it/s, train/loss=29.70]
Epoch 0: |          | 749/? [02:38<00:00,  4.74it/s, train/loss=29.70]
Epoch 0: |          | 749/? [02:38<00:00,  4.74it/s, train/loss=1.180]
Epoch 0: |          | 750/? [02:38<00:00,  4.74it/s, train/loss=1.180]
Epoch 0: |          | 750/? [02:38<00:00,  4.74it/s, train/loss=29.00]
Epoch 0: |          | 751/? [02:38<00:00,  4.74it/s, train/loss=29.00]
Epoch 0: |          | 751/? [02:38<00:00,  4.74it/s, train/loss=1.190]
Epoch 0: |          | 752/? [02:38<00:00,  4.74it/s, train/loss=1.190]
Epoch 0: |          | 752/? [02:38<00:00,  4.74it/s, train/loss=17.00]
Epoch 0: |          | 753/? [02:38<00:00,  4.75it/s, train/loss=17.00]
Epoch 0: |          | 753/? [02:38<00:00,  4.75it/s, train/loss=1.210]
Epoch 0: |          | 754/? [02:38<00:00,  4.74it/s, train/loss=1.210]
Epoch 0: |          | 754/? [02:38<00:00,  4.74it/s, train/loss=7.800]
Epoch 0: |          | 755/? [02:38<00:00,  4.75it/s, train/loss=7.800]
Epoch 0: |          | 755/? [02:38<00:00,  4.75it/s, train/loss=1.220]
Epoch 0: |          | 756/? [02:39<00:00,  4.75it/s, train/loss=1.220]
Epoch 0: |          | 756/? [02:39<00:00,  4.75it/s, train/loss=35.00]
Epoch 0: |          | 757/? [02:39<00:00,  4.75it/s, train/loss=35.00]
Epoch 0: |          | 757/? [02:39<00:00,  4.75it/s, train/loss=1.220]
Epoch 0: |          | 758/? [02:39<00:00,  4.75it/s, train/loss=1.220]
Epoch 0: |          | 758/? [02:39<00:00,  4.75it/s, train/loss=15.80]
Epoch 0: |          | 759/? [02:39<00:00,  4.76it/s, train/loss=15.80]
Epoch 0: |          | 759/? [02:39<00:00,  4.76it/s, train/loss=1.210]
Epoch 0: |          | 760/? [02:39<00:00,  4.75it/s, train/loss=1.210]
Epoch 0: |          | 760/? [02:39<00:00,  4.75it/s, train/loss=19.90]
Epoch 0: |          | 761/? [02:39<00:00,  4.76it/s, train/loss=19.90]
Epoch 0: |          | 761/? [02:39<00:00,  4.76it/s, train/loss=1.190]
Epoch 0: |          | 762/? [02:40<00:00,  4.76it/s, train/loss=1.190]
Epoch 0: |          | 762/? [02:40<00:00,  4.76it/s, train/loss=27.10]
Epoch 0: |          | 763/? [02:40<00:00,  4.76it/s, train/loss=27.10]
Epoch 0: |          | 763/? [02:40<00:00,  4.76it/s, train/loss=1.160]
Epoch 0: |          | 764/? [02:40<00:00,  4.76it/s, train/loss=1.160]
Epoch 0: |          | 764/? [02:40<00:00,  4.76it/s, train/loss=19.60]
Epoch 0: |          | 765/? [02:40<00:00,  4.77it/s, train/loss=19.60]
Epoch 0: |          | 765/? [02:40<00:00,  4.77it/s, train/loss=1.150]
Epoch 0: |          | 766/? [02:40<00:00,  4.76it/s, train/loss=1.150]
Epoch 0: |          | 766/? [02:40<00:00,  4.76it/s, train/loss=23.80]
Epoch 0: |          | 767/? [02:40<00:00,  4.77it/s, train/loss=23.80]
Epoch 0: |          | 767/? [02:40<00:00,  4.77it/s, train/loss=1.170]
Epoch 0: |          | 768/? [02:41<00:00,  4.77it/s, train/loss=1.170]
Epoch 0: |          | 768/? [02:41<00:00,  4.77it/s, train/loss=35.60]
Epoch 0: |          | 769/? [02:41<00:00,  4.77it/s, train/loss=35.60]
Epoch 0: |          | 769/? [02:41<00:00,  4.77it/s, train/loss=1.140]
Epoch 0: |          | 770/? [02:41<00:00,  4.77it/s, train/loss=1.140]
Epoch 0: |          | 770/? [02:41<00:00,  4.77it/s, train/loss=41.80]
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Epoch 0: |          | 800/? [02:53<00:00,  4.60it/s, train/loss=19.30]
`Trainer.fit` stopped: `max_steps=800` reached.
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Epoch 0: |          | 800/? [02:53<00:00,  4.60it/s, train/loss=19.30]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
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Test results saved to outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save
Running step 3: geometry refinement
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-geometry',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-geometry',
 'resume': None,
'seed': 0,
'system': {'stage': 'geometry', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.02, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'accumulate', 'no_diff_steps': 0, 'guidance_eval': 0, 'n_rgb': 4}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_normal_consistency': 10.0, 'lambda_laplacian_smoothness': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.005, 'betas': [0.9, 0.99], 'eps': 1e-15}}, 'geometry_convert_from': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134756',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32},
'trial_dir': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756',
'trial_name': 'replicate_user@20240222-134756',
'use_timestamp': True}
Initializing geometry from a given checkpoint ...
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d7509e-6347b4da73b31fa229296b6e;25483ae6-ebc7-4a7b-ac33-672d284154c2)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...:   0%|          | 0/3 [00:00<?, ?it/s]
Loading pipeline components...:  33%|███▎      | 1/3 [00:00<00:00,  5.14it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 13.15it/s]
Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name       | Type                 | Params
----------------------------------------------------
0 | geometry   | TetrahedraSDFGrid    | 13.7 M
1 | material   | NoMaterial           | 0
2 | background | SolidColorBackground | 0
3 | renderer   | NVDiffRasterizer     | 0
----------------------------------------------------
13.7 M    Trainable params
0         Non-trainable params
13.7 M    Total params
54.847    Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
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Epoch 0: |          | 73/? [00:23<00:00,  3.10it/s, train/loss=25.50]
Epoch 0: |          | 73/? [00:23<00:00,  3.10it/s, train/loss=25.70]
Epoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=25.70]
Epoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=18.70]
Epoch 0: |          | 75/? [00:24<00:00,  3.10it/s, train/loss=18.70]
Epoch 0: |          | 75/? [00:24<00:00,  3.10it/s, train/loss=25.40]
Epoch 0: |          | 76/? [00:24<00:00,  3.10it/s, train/loss=25.40]
Epoch 0: |          | 76/? [00:24<00:00,  3.10it/s, train/loss=22.10]
Epoch 0: |          | 77/? [00:24<00:00,  3.10it/s, train/loss=22.10]
Epoch 0: |          | 77/? [00:24<00:00,  3.10it/s, train/loss=33.50]
Epoch 0: |          | 78/? [00:25<00:00,  3.08it/s, train/loss=33.50]
Epoch 0: |          | 78/? [00:25<00:00,  3.08it/s, train/loss=13.40]
Epoch 0: |          | 79/? [00:25<00:00,  3.06it/s, train/loss=13.40]
Epoch 0: |          | 79/? [00:25<00:00,  3.06it/s, train/loss=9.540]
Epoch 0: |          | 80/? [00:26<00:00,  3.05it/s, train/loss=9.540]
Epoch 0: |          | 80/? [00:26<00:00,  3.05it/s, train/loss=13.70]
Epoch 0: |          | 81/? [00:26<00:00,  3.04it/s, train/loss=13.70]
Epoch 0: |          | 81/? [00:26<00:00,  3.04it/s, train/loss=32.00]
Epoch 0: |          | 82/? [00:26<00:00,  3.04it/s, train/loss=32.00]
Epoch 0: |          | 82/? [00:26<00:00,  3.04it/s, train/loss=23.60]
Epoch 0: |          | 83/? [00:27<00:00,  3.05it/s, train/loss=23.60]
Epoch 0: |          | 83/? [00:27<00:00,  3.05it/s, train/loss=27.50]
Epoch 0: |          | 84/? [00:27<00:00,  3.05it/s, train/loss=27.50]
Epoch 0: |          | 84/? [00:27<00:00,  3.05it/s, train/loss=41.20]
Epoch 0: |          | 85/? [00:27<00:00,  3.04it/s, train/loss=41.20]
Epoch 0: |          | 85/? [00:27<00:00,  3.04it/s, train/loss=31.90]
Epoch 0: |          | 86/? [00:28<00:00,  3.05it/s, train/loss=31.90]
Epoch 0: |          | 86/? [00:28<00:00,  3.05it/s, train/loss=10.30]
Epoch 0: |          | 87/? [00:28<00:00,  3.05it/s, train/loss=10.30]
Epoch 0: |          | 87/? [00:28<00:00,  3.05it/s, train/loss=30.40]
Epoch 0: |          | 88/? [00:28<00:00,  3.05it/s, train/loss=30.40]
Epoch 0: |          | 88/? [00:28<00:00,  3.05it/s, train/loss=27.20]
Epoch 0: |          | 89/? [00:29<00:00,  3.05it/s, train/loss=27.20]
Epoch 0: |          | 89/? [00:29<00:00,  3.05it/s, train/loss=36.90]
Epoch 0: |          | 90/? [00:29<00:00,  3.04it/s, train/loss=36.90]
Epoch 0: |          | 90/? [00:29<00:00,  3.04it/s, train/loss=15.30]
Epoch 0: |          | 91/? [00:29<00:00,  3.04it/s, train/loss=15.30]
Epoch 0: |          | 91/? [00:29<00:00,  3.04it/s, train/loss=25.40]
Epoch 0: |          | 92/? [00:30<00:00,  3.04it/s, train/loss=25.40]
Epoch 0: |          | 92/? [00:30<00:00,  3.04it/s, train/loss=18.00]
Epoch 0: |          | 93/? [00:30<00:00,  3.04it/s, train/loss=18.00]
Epoch 0: |          | 93/? [00:30<00:00,  3.04it/s, train/loss=30.60]
Epoch 0: |          | 94/? [00:30<00:00,  3.04it/s, train/loss=30.60]
Epoch 0: |          | 94/? [00:30<00:00,  3.04it/s, train/loss=22.00]
Epoch 0: |          | 95/? [00:31<00:00,  3.04it/s, train/loss=22.00]
Epoch 0: |          | 95/? [00:31<00:00,  3.04it/s, train/loss=13.20]
Epoch 0: |          | 96/? [00:31<00:00,  3.05it/s, train/loss=13.20]
Epoch 0: |          | 96/? [00:31<00:00,  3.05it/s, train/loss=28.90]
Epoch 0: |          | 97/? [00:31<00:00,  3.04it/s, train/loss=28.90]
Epoch 0: |          | 97/? [00:31<00:00,  3.04it/s, train/loss=43.10]
Epoch 0: |          | 98/? [00:32<00:00,  3.04it/s, train/loss=43.10]
Epoch 0: |          | 98/? [00:32<00:00,  3.04it/s, train/loss=24.10]
Epoch 0: |          | 99/? [00:32<00:00,  3.04it/s, train/loss=24.10]
Epoch 0: |          | 99/? [00:32<00:00,  3.04it/s, train/loss=35.90]
Epoch 0: |          | 100/? [00:32<00:00,  3.04it/s, train/loss=35.90]
Epoch 0: |          | 100/? [00:32<00:00,  3.04it/s, train/loss=54.40]
Epoch 0: |          | 101/? [00:33<00:00,  3.04it/s, train/loss=54.40]
Epoch 0: |          | 101/? [00:33<00:00,  3.04it/s, train/loss=39.20]
Epoch 0: |          | 102/? [00:33<00:00,  3.02it/s, train/loss=39.20]
Epoch 0: |          | 102/? [00:33<00:00,  3.02it/s, train/loss=26.30]
Epoch 0: |          | 103/? [00:34<00:00,  3.01it/s, train/loss=26.30]
Epoch 0: |          | 103/? [00:34<00:00,  3.01it/s, train/loss=11.30]
Epoch 0: |          | 104/? [00:34<00:00,  3.00it/s, train/loss=11.30]
Epoch 0: |          | 104/? [00:34<00:00,  3.00it/s, train/loss=16.80]
Epoch 0: |          | 105/? [00:35<00:00,  2.99it/s, train/loss=16.80]
Epoch 0: |          | 105/? [00:35<00:00,  2.99it/s, train/loss=28.70]
Epoch 0: |          | 106/? [00:35<00:00,  2.98it/s, train/loss=28.70]
Epoch 0: |          | 106/? [00:35<00:00,  2.98it/s, train/loss=24.10]
Epoch 0: |          | 107/? [00:36<00:00,  2.97it/s, train/loss=24.10]
Epoch 0: |          | 107/? [00:36<00:00,  2.97it/s, train/loss=25.80]
Epoch 0: |          | 108/? [00:36<00:00,  2.95it/s, train/loss=25.80]
Epoch 0: |          | 108/? [00:36<00:00,  2.95it/s, train/loss=35.10]
Epoch 0: |          | 109/? [00:37<00:00,  2.94it/s, train/loss=35.10]
Epoch 0: |          | 109/? [00:37<00:00,  2.94it/s, train/loss=34.00]
Epoch 0: |          | 110/? [00:37<00:00,  2.95it/s, train/loss=34.00]
Epoch 0: |          | 110/? [00:37<00:00,  2.95it/s, train/loss=10.00]
Epoch 0: |          | 111/? [00:37<00:00,  2.95it/s, train/loss=10.00]
Epoch 0: |          | 111/? [00:37<00:00,  2.95it/s, train/loss=18.90]
Epoch 0: |          | 112/? [00:37<00:00,  2.95it/s, train/loss=18.90]
Epoch 0: |          | 112/? [00:37<00:00,  2.95it/s, train/loss=16.30]
Epoch 0: |          | 113/? [00:38<00:00,  2.95it/s, train/loss=16.30]
Epoch 0: |          | 113/? [00:38<00:00,  2.95it/s, train/loss=26.50]
Epoch 0: |          | 114/? [00:38<00:00,  2.95it/s, train/loss=26.50]
Epoch 0: |          | 114/? [00:38<00:00,  2.95it/s, train/loss=23.80]
Epoch 0: |          | 115/? [00:38<00:00,  2.95it/s, train/loss=23.80]
Epoch 0: |          | 115/? [00:38<00:00,  2.95it/s, train/loss=19.70]
Epoch 0: |          | 116/? [00:39<00:00,  2.95it/s, train/loss=19.70]
Epoch 0: |          | 116/? [00:39<00:00,  2.95it/s, train/loss=28.20]
Epoch 0: |          | 117/? [00:39<00:00,  2.95it/s, train/loss=28.20]
Epoch 0: |          | 117/? [00:39<00:00,  2.95it/s, train/loss=26.90]
Epoch 0: |          | 118/? [00:39<00:00,  2.95it/s, train/loss=26.90]
Epoch 0: |          | 118/? [00:39<00:00,  2.95it/s, train/loss=12.40]
Epoch 0: |          | 119/? [00:40<00:00,  2.95it/s, train/loss=12.40]
Epoch 0: |          | 119/? [00:40<00:00,  2.95it/s, train/loss=25.70]
Epoch 0: |          | 120/? [00:40<00:00,  2.96it/s, train/loss=25.70]
Epoch 0: |          | 120/? [00:40<00:00,  2.96it/s, train/loss=15.50]
Epoch 0: |          | 121/? [00:40<00:00,  2.96it/s, train/loss=15.50]
Epoch 0: |          | 121/? [00:40<00:00,  2.96it/s, train/loss=33.20]
Epoch 0: |          | 122/? [00:41<00:00,  2.96it/s, train/loss=33.20]
Epoch 0: |          | 122/? [00:41<00:00,  2.96it/s, train/loss=29.20]
Epoch 0: |          | 123/? [00:41<00:00,  2.96it/s, train/loss=29.20]
Epoch 0: |          | 123/? [00:41<00:00,  2.96it/s, train/loss=14.80]
Epoch 0: |          | 124/? [00:41<00:00,  2.96it/s, train/loss=14.80]
Epoch 0: |          | 124/? [00:41<00:00,  2.96it/s, train/loss=19.00]
Epoch 0: |          | 125/? [00:42<00:00,  2.96it/s, train/loss=19.00]
Epoch 0: |          | 125/? [00:42<00:00,  2.96it/s, train/loss=35.50]
Epoch 0: |          | 126/? [00:42<00:00,  2.96it/s, train/loss=35.50]
Epoch 0: |          | 126/? [00:42<00:00,  2.96it/s, train/loss=30.20]
Epoch 0: |          | 127/? [00:42<00:00,  2.96it/s, train/loss=30.20]
Epoch 0: |          | 127/? [00:42<00:00,  2.96it/s, train/loss=11.70]
Epoch 0: |          | 128/? [00:43<00:00,  2.96it/s, train/loss=11.70]
Epoch 0: |          | 128/? [00:43<00:00,  2.96it/s, train/loss=33.50]
Epoch 0: |          | 129/? [00:43<00:00,  2.96it/s, train/loss=33.50]
Epoch 0: |          | 129/? [00:43<00:00,  2.96it/s, train/loss=21.60]
Epoch 0: |          | 130/? [00:43<00:00,  2.96it/s, train/loss=21.60]
Epoch 0: |          | 130/? [00:43<00:00,  2.96it/s, train/loss=31.00]
Epoch 0: |          | 131/? [00:44<00:00,  2.96it/s, train/loss=31.00]
Epoch 0: |          | 131/? [00:44<00:00,  2.96it/s, train/loss=7.040]
Epoch 0: |          | 132/? [00:44<00:00,  2.96it/s, train/loss=7.040]
Epoch 0: |          | 132/? [00:44<00:00,  2.96it/s, train/loss=18.30]
Epoch 0: |          | 133/? [00:44<00:00,  2.96it/s, train/loss=18.30]
Epoch 0: |          | 133/? [00:44<00:00,  2.96it/s, train/loss=50.90]
Epoch 0: |          | 134/? [00:45<00:00,  2.96it/s, train/loss=50.90]
Epoch 0: |          | 134/? [00:45<00:00,  2.96it/s, train/loss=36.30]
Epoch 0: |          | 135/? [00:45<00:00,  2.96it/s, train/loss=36.30]
Epoch 0: |          | 135/? [00:45<00:00,  2.96it/s, train/loss=16.50]
Epoch 0: |          | 136/? [00:45<00:00,  2.96it/s, train/loss=16.50]
Epoch 0: |          | 136/? [00:45<00:00,  2.96it/s, train/loss=37.00]
Epoch 0: |          | 137/? [00:46<00:00,  2.96it/s, train/loss=37.00]
Epoch 0: |          | 137/? [00:46<00:00,  2.96it/s, train/loss=30.50]
Epoch 0: |          | 138/? [00:46<00:00,  2.96it/s, train/loss=30.50]
Epoch 0: |          | 138/? [00:46<00:00,  2.96it/s, train/loss=9.030]
Epoch 0: |          | 139/? [00:46<00:00,  2.96it/s, train/loss=9.030]
Epoch 0: |          | 139/? [00:46<00:00,  2.96it/s, train/loss=64.00]
Epoch 0: |          | 140/? [00:47<00:00,  2.97it/s, train/loss=64.00]
Epoch 0: |          | 140/? [00:47<00:00,  2.97it/s, train/loss=21.90]
Epoch 0: |          | 141/? [00:47<00:00,  2.97it/s, train/loss=21.90]
Epoch 0: |          | 141/? [00:47<00:00,  2.97it/s, train/loss=20.40]
Epoch 0: |          | 142/? [00:47<00:00,  2.97it/s, train/loss=20.40]
Epoch 0: |          | 142/? [00:47<00:00,  2.97it/s, train/loss=23.60]
Epoch 0: |          | 143/? [00:48<00:00,  2.97it/s, train/loss=23.60]
Epoch 0: |          | 143/? [00:48<00:00,  2.97it/s, train/loss=9.380]
Epoch 0: |          | 144/? [00:48<00:00,  2.97it/s, train/loss=9.380]
Epoch 0: |          | 144/? [00:48<00:00,  2.97it/s, train/loss=28.20]
Epoch 0: |          | 145/? [00:48<00:00,  2.97it/s, train/loss=28.20]
Epoch 0: |          | 145/? [00:48<00:00,  2.97it/s, train/loss=49.70]
Epoch 0: |          | 146/? [00:49<00:00,  2.97it/s, train/loss=49.70]
Epoch 0: |          | 146/? [00:49<00:00,  2.97it/s, train/loss=22.60]
Epoch 0: |          | 147/? [00:49<00:00,  2.97it/s, train/loss=22.60]
Epoch 0: |          | 147/? [00:49<00:00,  2.97it/s, train/loss=31.20]
Epoch 0: |          | 148/? [00:49<00:00,  2.97it/s, train/loss=31.20]
Epoch 0: |          | 148/? [00:49<00:00,  2.97it/s, train/loss=12.40]
Epoch 0: |          | 149/? [00:50<00:00,  2.97it/s, train/loss=12.40]
Epoch 0: |          | 149/? [00:50<00:00,  2.97it/s, train/loss=26.90]
Epoch 0: |          | 150/? [00:50<00:00,  2.97it/s, train/loss=26.90]
Epoch 0: |          | 150/? [00:50<00:00,  2.97it/s, train/loss=29.40]
Epoch 0: |          | 151/? [00:50<00:00,  2.97it/s, train/loss=29.40]
Epoch 0: |          | 151/? [00:50<00:00,  2.97it/s, train/loss=15.90]
Epoch 0: |          | 152/? [00:51<00:00,  2.97it/s, train/loss=15.90]
Epoch 0: |          | 152/? [00:51<00:00,  2.97it/s, train/loss=34.20]
Epoch 0: |          | 153/? [00:51<00:00,  2.97it/s, train/loss=34.20]
Epoch 0: |          | 153/? [00:51<00:00,  2.97it/s, train/loss=27.00]
Epoch 0: |          | 154/? [00:51<00:00,  2.97it/s, train/loss=27.00]
Epoch 0: |          | 154/? [00:51<00:00,  2.97it/s, train/loss=20.90]
Epoch 0: |          | 155/? [00:52<00:00,  2.97it/s, train/loss=20.90]
Epoch 0: |          | 155/? [00:52<00:00,  2.97it/s, train/loss=28.60]
Epoch 0: |          | 156/? [00:52<00:00,  2.97it/s, train/loss=28.60]
Epoch 0: |          | 156/? [00:52<00:00,  2.97it/s, train/loss=15.00]
Epoch 0: |          | 157/? [00:52<00:00,  2.97it/s, train/loss=15.00]
Epoch 0: |          | 157/? [00:52<00:00,  2.97it/s, train/loss=18.70]
Epoch 0: |          | 158/? [00:53<00:00,  2.98it/s, train/loss=18.70]
Epoch 0: |          | 158/? [00:53<00:00,  2.98it/s, train/loss=21.40]
Epoch 0: |          | 159/? [00:53<00:00,  2.98it/s, train/loss=21.40]
Epoch 0: |          | 159/? [00:53<00:00,  2.98it/s, train/loss=37.80]
Epoch 0: |          | 160/? [00:53<00:00,  2.98it/s, train/loss=37.80]
Epoch 0: |          | 160/? [00:53<00:00,  2.98it/s, train/loss=16.10]
Epoch 0: |          | 161/? [00:54<00:00,  2.98it/s, train/loss=16.10]
Epoch 0: |          | 161/? [00:54<00:00,  2.98it/s, train/loss=29.40]
Epoch 0: |          | 162/? [00:54<00:00,  2.98it/s, train/loss=29.40]
Epoch 0: |          | 162/? [00:54<00:00,  2.98it/s, train/loss=27.00]
Epoch 0: |          | 163/? [00:54<00:00,  2.98it/s, train/loss=27.00]
Epoch 0: |          | 163/? [00:54<00:00,  2.98it/s, train/loss=30.00]
Epoch 0: |          | 164/? [00:55<00:00,  2.98it/s, train/loss=30.00]
Epoch 0: |          | 164/? [00:55<00:00,  2.98it/s, train/loss=23.00]
Epoch 0: |          | 165/? [00:55<00:00,  2.98it/s, train/loss=23.00]
Epoch 0: |          | 165/? [00:55<00:00,  2.98it/s, train/loss=19.30]
Epoch 0: |          | 166/? [00:55<00:00,  2.98it/s, train/loss=19.30]
Epoch 0: |          | 166/? [00:55<00:00,  2.98it/s, train/loss=7.840]
Epoch 0: |          | 167/? [00:56<00:00,  2.98it/s, train/loss=7.840]
Epoch 0: |          | 167/? [00:56<00:00,  2.98it/s, train/loss=23.30]
Epoch 0: |          | 168/? [00:56<00:00,  2.98it/s, train/loss=23.30]
Epoch 0: |          | 168/? [00:56<00:00,  2.98it/s, train/loss=28.90]
Epoch 0: |          | 169/? [00:56<00:00,  2.98it/s, train/loss=28.90]
Epoch 0: |          | 169/? [00:56<00:00,  2.98it/s, train/loss=41.70]
Epoch 0: |          | 170/? [00:57<00:00,  2.98it/s, train/loss=41.70]
Epoch 0: |          | 170/? [00:57<00:00,  2.98it/s, train/loss=25.60]
Epoch 0: |          | 171/? [00:57<00:00,  2.98it/s, train/loss=25.60]
Epoch 0: |          | 171/? [00:57<00:00,  2.98it/s, train/loss=9.550]
Epoch 0: |          | 172/? [00:57<00:00,  2.98it/s, train/loss=9.550]
Epoch 0: |          | 172/? [00:57<00:00,  2.98it/s, train/loss=8.980]
Epoch 0: |          | 173/? [00:58<00:00,  2.98it/s, train/loss=8.980]
Epoch 0: |          | 173/? [00:58<00:00,  2.98it/s, train/loss=41.40]
Epoch 0: |          | 174/? [00:58<00:00,  2.97it/s, train/loss=41.40]
Epoch 0: |          | 174/? [00:58<00:00,  2.97it/s, train/loss=14.10]
Epoch 0: |          | 175/? [00:58<00:00,  2.97it/s, train/loss=14.10]
Epoch 0: |          | 175/? [00:58<00:00,  2.97it/s, train/loss=42.50]
Epoch 0: |          | 176/? [00:59<00:00,  2.97it/s, train/loss=42.50]
Epoch 0: |          | 176/? [00:59<00:00,  2.97it/s, train/loss=18.90]
Epoch 0: |          | 177/? [00:59<00:00,  2.97it/s, train/loss=18.90]
Epoch 0: |          | 177/? [00:59<00:00,  2.97it/s, train/loss=52.70]
Epoch 0: |          | 178/? [00:59<00:00,  2.97it/s, train/loss=52.70]
Epoch 0: |          | 178/? [00:59<00:00,  2.97it/s, train/loss=21.30]
Epoch 0: |          | 179/? [01:00<00:00,  2.97it/s, train/loss=21.30]
Epoch 0: |          | 179/? [01:00<00:00,  2.97it/s, train/loss=26.90]
Epoch 0: |          | 180/? [01:00<00:00,  2.97it/s, train/loss=26.90]
Epoch 0: |          | 180/? [01:00<00:00,  2.97it/s, train/loss=43.90]
Epoch 0: |          | 181/? [01:00<00:00,  2.97it/s, train/loss=43.90]
Epoch 0: |          | 181/? [01:00<00:00,  2.97it/s, train/loss=30.30]
Epoch 0: |          | 182/? [01:01<00:00,  2.97it/s, train/loss=30.30]
Epoch 0: |          | 182/? [01:01<00:00,  2.97it/s, train/loss=14.80]
Epoch 0: |          | 183/? [01:01<00:00,  2.97it/s, train/loss=14.80]
Epoch 0: |          | 183/? [01:01<00:00,  2.97it/s, train/loss=9.860]
Epoch 0: |          | 184/? [01:01<00:00,  2.97it/s, train/loss=9.860]
Epoch 0: |          | 184/? [01:01<00:00,  2.97it/s, train/loss=40.60]
Epoch 0: |          | 185/? [01:02<00:00,  2.97it/s, train/loss=40.60]
Epoch 0: |          | 185/? [01:02<00:00,  2.97it/s, train/loss=17.30]
Epoch 0: |          | 186/? [01:02<00:00,  2.97it/s, train/loss=17.30]
Epoch 0: |          | 186/? [01:02<00:00,  2.97it/s, train/loss=17.20]
Epoch 0: |          | 187/? [01:02<00:00,  2.97it/s, train/loss=17.20]
Epoch 0: |          | 187/? [01:02<00:00,  2.97it/s, train/loss=30.70]
Epoch 0: |          | 188/? [01:03<00:00,  2.97it/s, train/loss=30.70]
Epoch 0: |          | 188/? [01:03<00:00,  2.97it/s, train/loss=30.50]
Epoch 0: |          | 189/? [01:03<00:00,  2.97it/s, train/loss=30.50]
Epoch 0: |          | 189/? [01:03<00:00,  2.97it/s, train/loss=34.40]
Epoch 0: |          | 190/? [01:03<00:00,  2.97it/s, train/loss=34.40]
Epoch 0: |          | 190/? [01:03<00:00,  2.97it/s, train/loss=18.50]
Epoch 0: |          | 191/? [01:04<00:00,  2.97it/s, train/loss=18.50]
Epoch 0: |          | 191/? [01:04<00:00,  2.97it/s, train/loss=10.70]
Epoch 0: |          | 192/? [01:04<00:00,  2.98it/s, train/loss=10.70]
Epoch 0: |          | 192/? [01:04<00:00,  2.98it/s, train/loss=10.90]
Epoch 0: |          | 193/? [01:04<00:00,  2.98it/s, train/loss=10.90]
Epoch 0: |          | 193/? [01:04<00:00,  2.98it/s, train/loss=42.30]
Epoch 0: |          | 194/? [01:05<00:00,  2.98it/s, train/loss=42.30]
Epoch 0: |          | 194/? [01:05<00:00,  2.98it/s, train/loss=15.00]
Epoch 0: |          | 195/? [01:05<00:00,  2.98it/s, train/loss=15.00]
Epoch 0: |          | 195/? [01:05<00:00,  2.98it/s, train/loss=24.30]
Epoch 0: |          | 196/? [01:05<00:00,  2.98it/s, train/loss=24.30]
Epoch 0: |          | 196/? [01:05<00:00,  2.98it/s, train/loss=23.80]
Epoch 0: |          | 197/? [01:06<00:00,  2.98it/s, train/loss=23.80]
Epoch 0: |          | 197/? [01:06<00:00,  2.98it/s, train/loss=23.20]
Epoch 0: |          | 198/? [01:06<00:00,  2.98it/s, train/loss=23.20]
Epoch 0: |          | 198/? [01:06<00:00,  2.98it/s, train/loss=9.060]
Epoch 0: |          | 199/? [01:06<00:00,  2.98it/s, train/loss=9.060]
Epoch 0: |          | 199/? [01:06<00:00,  2.98it/s, train/loss=24.10]
Epoch 0: |          | 200/? [01:07<00:00,  2.98it/s, train/loss=24.10]
Epoch 0: |          | 200/? [01:07<00:00,  2.98it/s, train/loss=19.50]
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Validation DataLoader 0:  42%|████▎     | 17/40 [00:01<00:01, 11.63it/s]
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Validation DataLoader 0:  48%|████▊     | 19/40 [00:01<00:01, 11.65it/s]
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Validation DataLoader 0:  55%|█████▌    | 22/40 [00:01<00:01, 11.67it/s]
Validation DataLoader 0:  57%|█████▊    | 23/40 [00:01<00:01, 11.68it/s]
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Validation DataLoader 0:  72%|███████▎  | 29/40 [00:02<00:00, 11.65it/s]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.57it/s]

Epoch 0: |          | 200/? [01:14<00:00,  2.70it/s, train/loss=19.50]
Epoch 0: |          | 201/? [01:15<00:00,  2.68it/s, train/loss=19.50]
Epoch 0: |          | 201/? [01:15<00:00,  2.68it/s, train/loss=18.40]
Epoch 0: |          | 202/? [01:15<00:00,  2.68it/s, train/loss=18.40]
Epoch 0: |          | 202/? [01:15<00:00,  2.68it/s, train/loss=21.90]
Epoch 0: |          | 203/? [01:15<00:00,  2.68it/s, train/loss=21.90]
Epoch 0: |          | 203/? [01:15<00:00,  2.68it/s, train/loss=24.70]
Epoch 0: |          | 204/? [01:16<00:00,  2.68it/s, train/loss=24.70]
Epoch 0: |          | 204/? [01:16<00:00,  2.68it/s, train/loss=20.40]
Epoch 0: |          | 205/? [01:16<00:00,  2.68it/s, train/loss=20.40]
Epoch 0: |          | 205/? [01:16<00:00,  2.68it/s, train/loss=24.10]
Epoch 0: |          | 206/? [01:16<00:00,  2.68it/s, train/loss=24.10]
Epoch 0: |          | 206/? [01:16<00:00,  2.68it/s, train/loss=29.90]
Epoch 0: |          | 207/? [01:17<00:00,  2.68it/s, train/loss=29.90]
Epoch 0: |          | 207/? [01:17<00:00,  2.68it/s, train/loss=9.750]
Epoch 0: |          | 208/? [01:17<00:00,  2.68it/s, train/loss=9.750]
Epoch 0: |          | 208/? [01:17<00:00,  2.68it/s, train/loss=20.60]
Epoch 0: |          | 209/? [01:17<00:00,  2.68it/s, train/loss=20.60]
Epoch 0: |          | 209/? [01:17<00:00,  2.68it/s, train/loss=31.50]
Epoch 0: |          | 210/? [01:18<00:00,  2.69it/s, train/loss=31.50]
Epoch 0: |          | 210/? [01:18<00:00,  2.69it/s, train/loss=26.50]
Epoch 0: |          | 211/? [01:18<00:00,  2.69it/s, train/loss=26.50]
Epoch 0: |          | 211/? [01:18<00:00,  2.69it/s, train/loss=44.80]
Epoch 0: |          | 212/? [01:18<00:00,  2.69it/s, train/loss=44.80]
Epoch 0: |          | 212/? [01:18<00:00,  2.69it/s, train/loss=12.50]
Epoch 0: |          | 213/? [01:19<00:00,  2.69it/s, train/loss=12.50]
Epoch 0: |          | 213/? [01:19<00:00,  2.69it/s, train/loss=22.50]
Epoch 0: |          | 214/? [01:19<00:00,  2.69it/s, train/loss=22.50]
Epoch 0: |          | 214/? [01:19<00:00,  2.69it/s, train/loss=22.90]
Epoch 0: |          | 215/? [01:19<00:00,  2.69it/s, train/loss=22.90]
Epoch 0: |          | 215/? [01:19<00:00,  2.69it/s, train/loss=12.00]
Epoch 0: |          | 216/? [01:20<00:00,  2.70it/s, train/loss=12.00]
Epoch 0: |          | 216/? [01:20<00:00,  2.70it/s, train/loss=22.50]
Epoch 0: |          | 217/? [01:20<00:00,  2.70it/s, train/loss=22.50]
Epoch 0: |          | 217/? [01:20<00:00,  2.70it/s, train/loss=22.90]
Epoch 0: |          | 218/? [01:20<00:00,  2.70it/s, train/loss=22.90]
Epoch 0: |          | 218/? [01:20<00:00,  2.70it/s, train/loss=26.30]
Epoch 0: |          | 219/? [01:21<00:00,  2.70it/s, train/loss=26.30]
Epoch 0: |          | 219/? [01:21<00:00,  2.70it/s, train/loss=12.70]
Epoch 0: |          | 220/? [01:21<00:00,  2.70it/s, train/loss=12.70]
Epoch 0: |          | 220/? [01:21<00:00,  2.70it/s, train/loss=12.20]
Epoch 0: |          | 221/? [01:21<00:00,  2.70it/s, train/loss=12.20]
Epoch 0: |          | 221/? [01:21<00:00,  2.70it/s, train/loss=33.90]
Epoch 0: |          | 222/? [01:22<00:00,  2.70it/s, train/loss=33.90]
Epoch 0: |          | 222/? [01:22<00:00,  2.70it/s, train/loss=21.90]
Epoch 0: |          | 223/? [01:22<00:00,  2.70it/s, train/loss=21.90]
Epoch 0: |          | 223/? [01:22<00:00,  2.70it/s, train/loss=9.470]
Epoch 0: |          | 224/? [01:22<00:00,  2.70it/s, train/loss=9.470]
Epoch 0: |          | 224/? [01:22<00:00,  2.70it/s, train/loss=29.10]
Epoch 0: |          | 225/? [01:23<00:00,  2.70it/s, train/loss=29.10]
Epoch 0: |          | 225/? [01:23<00:00,  2.70it/s, train/loss=34.40]
Epoch 0: |          | 226/? [01:23<00:00,  2.71it/s, train/loss=34.40]
Epoch 0: |          | 226/? [01:23<00:00,  2.71it/s, train/loss=17.00]
Epoch 0: |          | 227/? [01:23<00:00,  2.71it/s, train/loss=17.00]
Epoch 0: |          | 227/? [01:23<00:00,  2.71it/s, train/loss=23.90]
Epoch 0: |          | 228/? [01:24<00:00,  2.71it/s, train/loss=23.90]
Epoch 0: |          | 228/? [01:24<00:00,  2.71it/s, train/loss=12.90]
Epoch 0: |          | 229/? [01:24<00:00,  2.70it/s, train/loss=12.90]
Epoch 0: |          | 229/? [01:24<00:00,  2.70it/s, train/loss=27.10]
Epoch 0: |          | 230/? [01:25<00:00,  2.70it/s, train/loss=27.10]
Epoch 0: |          | 230/? [01:25<00:00,  2.70it/s, train/loss=18.10]
Epoch 0: |          | 231/? [01:25<00:00,  2.70it/s, train/loss=18.10]
Epoch 0: |          | 231/? [01:25<00:00,  2.70it/s, train/loss=23.10]
Epoch 0: |          | 232/? [01:25<00:00,  2.70it/s, train/loss=23.10]
Epoch 0: |          | 232/? [01:25<00:00,  2.70it/s, train/loss=32.00]
Epoch 0: |          | 233/? [01:26<00:00,  2.70it/s, train/loss=32.00]
Epoch 0: |          | 233/? [01:26<00:00,  2.70it/s, train/loss=39.00]
Epoch 0: |          | 234/? [01:26<00:00,  2.70it/s, train/loss=39.00]
Epoch 0: |          | 234/? [01:26<00:00,  2.70it/s, train/loss=17.50]
Epoch 0: |          | 235/? [01:27<00:00,  2.70it/s, train/loss=17.50]
Epoch 0: |          | 235/? [01:27<00:00,  2.70it/s, train/loss=27.30]
Epoch 0: |          | 236/? [01:27<00:00,  2.70it/s, train/loss=27.30]
Epoch 0: |          | 236/? [01:27<00:00,  2.70it/s, train/loss=17.20]
Epoch 0: |          | 237/? [01:27<00:00,  2.70it/s, train/loss=17.20]
Epoch 0: |          | 237/? [01:27<00:00,  2.70it/s, train/loss=21.60]
Epoch 0: |          | 238/? [01:28<00:00,  2.70it/s, train/loss=21.60]
Epoch 0: |          | 238/? [01:28<00:00,  2.70it/s, train/loss=27.00]
Epoch 0: |          | 239/? [01:28<00:00,  2.70it/s, train/loss=27.00]
Epoch 0: |          | 239/? [01:28<00:00,  2.70it/s, train/loss=24.70]
Epoch 0: |          | 240/? [01:28<00:00,  2.71it/s, train/loss=24.70]
Epoch 0: |          | 240/? [01:28<00:00,  2.71it/s, train/loss=19.30]
Epoch 0: |          | 241/? [01:29<00:00,  2.71it/s, train/loss=19.30]
Epoch 0: |          | 241/? [01:29<00:00,  2.71it/s, train/loss=31.30]
Epoch 0: |          | 242/? [01:29<00:00,  2.71it/s, train/loss=31.30]
Epoch 0: |          | 242/? [01:29<00:00,  2.71it/s, train/loss=33.00]
Epoch 0: |          | 243/? [01:29<00:00,  2.71it/s, train/loss=33.00]
Epoch 0: |          | 243/? [01:29<00:00,  2.71it/s, train/loss=36.70]
Epoch 0: |          | 244/? [01:29<00:00,  2.71it/s, train/loss=36.70]
Epoch 0: |          | 244/? [01:29<00:00,  2.71it/s, train/loss=11.30]
Epoch 0: |          | 245/? [01:30<00:00,  2.71it/s, train/loss=11.30]
Epoch 0: |          | 245/? [01:30<00:00,  2.71it/s, train/loss=29.30]
Epoch 0: |          | 246/? [01:30<00:00,  2.71it/s, train/loss=29.30]
Epoch 0: |          | 246/? [01:30<00:00,  2.71it/s, train/loss=29.50]
Epoch 0: |          | 247/? [01:30<00:00,  2.72it/s, train/loss=29.50]
Epoch 0: |          | 247/? [01:30<00:00,  2.71it/s, train/loss=38.30]
Epoch 0: |          | 248/? [01:31<00:00,  2.72it/s, train/loss=38.30]
Epoch 0: |          | 248/? [01:31<00:00,  2.72it/s, train/loss=31.60]
Epoch 0: |          | 249/? [01:31<00:00,  2.72it/s, train/loss=31.60]
Epoch 0: |          | 249/? [01:31<00:00,  2.72it/s, train/loss=25.80]
Epoch 0: |          | 250/? [01:31<00:00,  2.72it/s, train/loss=25.80]
Epoch 0: |          | 250/? [01:31<00:00,  2.72it/s, train/loss=22.20]
Epoch 0: |          | 251/? [01:32<00:00,  2.72it/s, train/loss=22.20]
Epoch 0: |          | 251/? [01:32<00:00,  2.72it/s, train/loss=20.50]
Epoch 0: |          | 252/? [01:32<00:00,  2.72it/s, train/loss=20.50]
Epoch 0: |          | 252/? [01:32<00:00,  2.72it/s, train/loss=12.90]
Epoch 0: |          | 253/? [01:32<00:00,  2.72it/s, train/loss=12.90]
Epoch 0: |          | 253/? [01:32<00:00,  2.72it/s, train/loss=34.50]
Epoch 0: |          | 254/? [01:33<00:00,  2.72it/s, train/loss=34.50]
Epoch 0: |          | 254/? [01:33<00:00,  2.72it/s, train/loss=21.40]
Epoch 0: |          | 255/? [01:33<00:00,  2.72it/s, train/loss=21.40]
Epoch 0: |          | 255/? [01:33<00:00,  2.72it/s, train/loss=20.10]
Epoch 0: |          | 256/? [01:33<00:00,  2.73it/s, train/loss=20.10]
Epoch 0: |          | 256/? [01:33<00:00,  2.73it/s, train/loss=9.920]
Epoch 0: |          | 257/? [01:34<00:00,  2.73it/s, train/loss=9.920]
Epoch 0: |          | 257/? [01:34<00:00,  2.73it/s, train/loss=26.10]
Epoch 0: |          | 258/? [01:34<00:00,  2.73it/s, train/loss=26.10]
Epoch 0: |          | 258/? [01:34<00:00,  2.73it/s, train/loss=22.30]
Epoch 0: |          | 259/? [01:34<00:00,  2.73it/s, train/loss=22.30]
Epoch 0: |          | 259/? [01:34<00:00,  2.73it/s, train/loss=22.70]
Epoch 0: |          | 260/? [01:35<00:00,  2.73it/s, train/loss=22.70]
Epoch 0: |          | 260/? [01:35<00:00,  2.73it/s, train/loss=10.50]
Epoch 0: |          | 261/? [01:35<00:00,  2.73it/s, train/loss=10.50]
Epoch 0: |          | 261/? [01:35<00:00,  2.73it/s, train/loss=19.80]
Epoch 0: |          | 262/? [01:35<00:00,  2.73it/s, train/loss=19.80]
Epoch 0: |          | 262/? [01:35<00:00,  2.73it/s, train/loss=26.50]
Epoch 0: |          | 263/? [01:36<00:00,  2.73it/s, train/loss=26.50]
Epoch 0: |          | 263/? [01:36<00:00,  2.73it/s, train/loss=15.90]
Epoch 0: |          | 264/? [01:36<00:00,  2.73it/s, train/loss=15.90]
Epoch 0: |          | 264/? [01:36<00:00,  2.73it/s, train/loss=83.00]
Epoch 0: |          | 265/? [01:36<00:00,  2.73it/s, train/loss=83.00]
Epoch 0: |          | 265/? [01:36<00:00,  2.73it/s, train/loss=19.80]
Epoch 0: |          | 266/? [01:37<00:00,  2.74it/s, train/loss=19.80]
Epoch 0: |          | 266/? [01:37<00:00,  2.74it/s, train/loss=27.80]
Epoch 0: |          | 267/? [01:37<00:00,  2.74it/s, train/loss=27.80]
Epoch 0: |          | 267/? [01:37<00:00,  2.74it/s, train/loss=12.90]
Epoch 0: |          | 268/? [01:37<00:00,  2.74it/s, train/loss=12.90]
Epoch 0: |          | 268/? [01:37<00:00,  2.74it/s, train/loss=37.60]
Epoch 0: |          | 269/? [01:38<00:00,  2.74it/s, train/loss=37.60]
Epoch 0: |          | 269/? [01:38<00:00,  2.74it/s, train/loss=18.00]
Epoch 0: |          | 270/? [01:38<00:00,  2.74it/s, train/loss=18.00]
Epoch 0: |          | 270/? [01:38<00:00,  2.74it/s, train/loss=30.10]
Epoch 0: |          | 271/? [01:38<00:00,  2.74it/s, train/loss=30.10]
Epoch 0: |          | 271/? [01:38<00:00,  2.74it/s, train/loss=26.90]
Epoch 0: |          | 272/? [01:39<00:00,  2.74it/s, train/loss=26.90]
Epoch 0: |          | 272/? [01:39<00:00,  2.74it/s, train/loss=24.70]
Epoch 0: |          | 273/? [01:39<00:00,  2.74it/s, train/loss=24.70]
Epoch 0: |          | 273/? [01:39<00:00,  2.74it/s, train/loss=30.30]
Epoch 0: |          | 274/? [01:40<00:00,  2.73it/s, train/loss=30.30]
Epoch 0: |          | 274/? [01:40<00:00,  2.73it/s, train/loss=23.30]
Epoch 0: |          | 275/? [01:40<00:00,  2.74it/s, train/loss=23.30]
Epoch 0: |          | 275/? [01:40<00:00,  2.74it/s, train/loss=19.70]
Epoch 0: |          | 276/? [01:40<00:00,  2.74it/s, train/loss=19.70]
Epoch 0: |          | 276/? [01:40<00:00,  2.74it/s, train/loss=25.70]
Epoch 0: |          | 277/? [01:41<00:00,  2.74it/s, train/loss=25.70]
Epoch 0: |          | 277/? [01:41<00:00,  2.74it/s, train/loss=43.30]
Epoch 0: |          | 278/? [01:41<00:00,  2.74it/s, train/loss=43.30]
Epoch 0: |          | 278/? [01:41<00:00,  2.74it/s, train/loss=29.50]
Epoch 0: |          | 279/? [01:41<00:00,  2.74it/s, train/loss=29.50]
Epoch 0: |          | 279/? [01:41<00:00,  2.74it/s, train/loss=25.80]
Epoch 0: |          | 280/? [01:42<00:00,  2.74it/s, train/loss=25.80]
Epoch 0: |          | 280/? [01:42<00:00,  2.74it/s, train/loss=73.00]
Epoch 0: |          | 281/? [01:42<00:00,  2.74it/s, train/loss=73.00]
Epoch 0: |          | 281/? [01:42<00:00,  2.74it/s, train/loss=34.10]
Epoch 0: |          | 282/? [01:42<00:00,  2.74it/s, train/loss=34.10]
Epoch 0: |          | 282/? [01:42<00:00,  2.74it/s, train/loss=16.80]
Epoch 0: |          | 283/? [01:43<00:00,  2.74it/s, train/loss=16.80]
Epoch 0: |          | 283/? [01:43<00:00,  2.74it/s, train/loss=23.70]
Epoch 0: |          | 284/? [01:43<00:00,  2.73it/s, train/loss=23.70]
Epoch 0: |          | 284/? [01:43<00:00,  2.73it/s, train/loss=42.90]
Epoch 0: |          | 285/? [01:44<00:00,  2.74it/s, train/loss=42.90]
Epoch 0: |          | 285/? [01:44<00:00,  2.73it/s, train/loss=18.10]
Epoch 0: |          | 286/? [01:44<00:00,  2.74it/s, train/loss=18.10]
Epoch 0: |          | 286/? [01:44<00:00,  2.74it/s, train/loss=16.30]
Epoch 0: |          | 287/? [01:44<00:00,  2.74it/s, train/loss=16.30]
Epoch 0: |          | 287/? [01:44<00:00,  2.74it/s, train/loss=24.40]
Epoch 0: |          | 288/? [01:45<00:00,  2.74it/s, train/loss=24.40]
Epoch 0: |          | 288/? [01:45<00:00,  2.74it/s, train/loss=18.90]
Epoch 0: |          | 289/? [01:45<00:00,  2.74it/s, train/loss=18.90]
Epoch 0: |          | 289/? [01:45<00:00,  2.74it/s, train/loss=29.20]
Epoch 0: |          | 290/? [01:45<00:00,  2.74it/s, train/loss=29.20]
Epoch 0: |          | 290/? [01:45<00:00,  2.74it/s, train/loss=15.30]
Epoch 0: |          | 291/? [01:46<00:00,  2.74it/s, train/loss=15.30]
Epoch 0: |          | 291/? [01:46<00:00,  2.74it/s, train/loss=48.50]
Epoch 0: |          | 292/? [01:46<00:00,  2.74it/s, train/loss=48.50]
Epoch 0: |          | 292/? [01:46<00:00,  2.74it/s, train/loss=17.30]
Epoch 0: |          | 293/? [01:46<00:00,  2.74it/s, train/loss=17.30]
Epoch 0: |          | 293/? [01:46<00:00,  2.74it/s, train/loss=32.00]
Epoch 0: |          | 294/? [01:47<00:00,  2.74it/s, train/loss=32.00]
Epoch 0: |          | 294/? [01:47<00:00,  2.74it/s, train/loss=15.80]
Epoch 0: |          | 295/? [01:47<00:00,  2.74it/s, train/loss=15.80]
Epoch 0: |          | 295/? [01:47<00:00,  2.74it/s, train/loss=11.20]
Epoch 0: |          | 296/? [01:48<00:00,  2.74it/s, train/loss=11.20]
Epoch 0: |          | 296/? [01:48<00:00,  2.74it/s, train/loss=13.20]
Epoch 0: |          | 297/? [01:48<00:00,  2.74it/s, train/loss=13.20]
Epoch 0: |          | 297/? [01:48<00:00,  2.74it/s, train/loss=17.20]
Epoch 0: |          | 298/? [01:48<00:00,  2.74it/s, train/loss=17.20]
Epoch 0: |          | 298/? [01:48<00:00,  2.74it/s, train/loss=16.80]
Epoch 0: |          | 299/? [01:49<00:00,  2.74it/s, train/loss=16.80]
Epoch 0: |          | 299/? [01:49<00:00,  2.74it/s, train/loss=20.00]
Epoch 0: |          | 300/? [01:49<00:00,  2.74it/s, train/loss=20.00]
Epoch 0: |          | 300/? [01:49<00:00,  2.74it/s, train/loss=17.50]
Epoch 0: |          | 301/? [01:49<00:00,  2.74it/s, train/loss=17.50]
Epoch 0: |          | 301/? [01:49<00:00,  2.74it/s, train/loss=31.60]
Epoch 0: |          | 302/? [01:50<00:00,  2.74it/s, train/loss=31.60]
Epoch 0: |          | 302/? [01:50<00:00,  2.74it/s, train/loss=17.70]
Epoch 0: |          | 303/? [01:50<00:00,  2.74it/s, train/loss=17.70]
Epoch 0: |          | 303/? [01:50<00:00,  2.74it/s, train/loss=6.190]
Epoch 0: |          | 304/? [01:50<00:00,  2.74it/s, train/loss=6.190]
Epoch 0: |          | 304/? [01:50<00:00,  2.74it/s, train/loss=22.80]
Epoch 0: |          | 305/? [01:51<00:00,  2.74it/s, train/loss=22.80]
Epoch 0: |          | 305/? [01:51<00:00,  2.74it/s, train/loss=20.90]
Epoch 0: |          | 306/? [01:51<00:00,  2.74it/s, train/loss=20.90]
Epoch 0: |          | 306/? [01:51<00:00,  2.74it/s, train/loss=26.30]
Epoch 0: |          | 307/? [01:51<00:00,  2.74it/s, train/loss=26.30]
Epoch 0: |          | 307/? [01:51<00:00,  2.74it/s, train/loss=24.20]
Epoch 0: |          | 308/? [01:52<00:00,  2.74it/s, train/loss=24.20]
Epoch 0: |          | 308/? [01:52<00:00,  2.74it/s, train/loss=14.50]
Epoch 0: |          | 309/? [01:52<00:00,  2.74it/s, train/loss=14.50]
Epoch 0: |          | 309/? [01:52<00:00,  2.74it/s, train/loss=28.30]
Epoch 0: |          | 310/? [01:52<00:00,  2.74it/s, train/loss=28.30]
Epoch 0: |          | 310/? [01:52<00:00,  2.74it/s, train/loss=28.40]
Epoch 0: |          | 311/? [01:53<00:00,  2.74it/s, train/loss=28.40]
Epoch 0: |          | 311/? [01:53<00:00,  2.74it/s, train/loss=25.70]
Epoch 0: |          | 312/? [01:53<00:00,  2.75it/s, train/loss=25.70]
Epoch 0: |          | 312/? [01:53<00:00,  2.75it/s, train/loss=43.80]
Epoch 0: |          | 313/? [01:53<00:00,  2.75it/s, train/loss=43.80]
Epoch 0: |          | 313/? [01:53<00:00,  2.75it/s, train/loss=20.80]
Epoch 0: |          | 314/? [01:54<00:00,  2.75it/s, train/loss=20.80]
Epoch 0: |          | 314/? [01:54<00:00,  2.75it/s, train/loss=41.50]
Epoch 0: |          | 315/? [01:54<00:00,  2.75it/s, train/loss=41.50]
Epoch 0: |          | 315/? [01:54<00:00,  2.75it/s, train/loss=18.30]
Epoch 0: |          | 316/? [01:54<00:00,  2.75it/s, train/loss=18.30]
Epoch 0: |          | 316/? [01:54<00:00,  2.75it/s, train/loss=16.40]
Epoch 0: |          | 317/? [01:55<00:00,  2.75it/s, train/loss=16.40]
Epoch 0: |          | 317/? [01:55<00:00,  2.75it/s, train/loss=21.20]
Epoch 0: |          | 318/? [01:55<00:00,  2.75it/s, train/loss=21.20]
Epoch 0: |          | 318/? [01:55<00:00,  2.75it/s, train/loss=32.10]
Epoch 0: |          | 319/? [01:55<00:00,  2.75it/s, train/loss=32.10]
Epoch 0: |          | 319/? [01:55<00:00,  2.75it/s, train/loss=21.10]
Epoch 0: |          | 320/? [01:56<00:00,  2.75it/s, train/loss=21.10]
Epoch 0: |          | 320/? [01:56<00:00,  2.75it/s, train/loss=17.00]
Epoch 0: |          | 321/? [01:56<00:00,  2.75it/s, train/loss=17.00]
Epoch 0: |          | 321/? [01:56<00:00,  2.75it/s, train/loss=23.70]
Epoch 0: |          | 322/? [01:56<00:00,  2.75it/s, train/loss=23.70]
Epoch 0: |          | 322/? [01:56<00:00,  2.75it/s, train/loss=26.10]
Epoch 0: |          | 323/? [01:57<00:00,  2.76it/s, train/loss=26.10]
Epoch 0: |          | 323/? [01:57<00:00,  2.76it/s, train/loss=24.10]
Epoch 0: |          | 324/? [01:57<00:00,  2.76it/s, train/loss=24.10]
Epoch 0: |          | 324/? [01:57<00:00,  2.76it/s, train/loss=17.70]
Epoch 0: |          | 325/? [01:57<00:00,  2.76it/s, train/loss=17.70]
Epoch 0: |          | 325/? [01:57<00:00,  2.76it/s, train/loss=33.40]
Epoch 0: |          | 326/? [01:58<00:00,  2.76it/s, train/loss=33.40]
Epoch 0: |          | 326/? [01:58<00:00,  2.76it/s, train/loss=22.60]
Epoch 0: |          | 327/? [01:58<00:00,  2.76it/s, train/loss=22.60]
Epoch 0: |          | 327/? [01:58<00:00,  2.76it/s, train/loss=14.40]
Epoch 0: |          | 328/? [01:58<00:00,  2.76it/s, train/loss=14.40]
Epoch 0: |          | 328/? [01:58<00:00,  2.76it/s, train/loss=23.20]
Epoch 0: |          | 329/? [01:59<00:00,  2.76it/s, train/loss=23.20]
Epoch 0: |          | 329/? [01:59<00:00,  2.76it/s, train/loss=32.80]
Epoch 0: |          | 330/? [01:59<00:00,  2.76it/s, train/loss=32.80]
Epoch 0: |          | 330/? [01:59<00:00,  2.76it/s, train/loss=25.70]
Epoch 0: |          | 331/? [01:59<00:00,  2.76it/s, train/loss=25.70]
Epoch 0: |          | 331/? [01:59<00:00,  2.76it/s, train/loss=10.00]
Epoch 0: |          | 332/? [02:00<00:00,  2.76it/s, train/loss=10.00]
Epoch 0: |          | 332/? [02:00<00:00,  2.76it/s, train/loss=13.80]
Epoch 0: |          | 333/? [02:00<00:00,  2.76it/s, train/loss=13.80]
Epoch 0: |          | 333/? [02:00<00:00,  2.76it/s, train/loss=14.90]
Epoch 0: |          | 334/? [02:00<00:00,  2.76it/s, train/loss=14.90]
Epoch 0: |          | 334/? [02:00<00:00,  2.76it/s, train/loss=25.70]
Epoch 0: |          | 335/? [02:01<00:00,  2.77it/s, train/loss=25.70]
Epoch 0: |          | 335/? [02:01<00:00,  2.77it/s, train/loss=28.00]
Epoch 0: |          | 336/? [02:01<00:00,  2.77it/s, train/loss=28.00]
Epoch 0: |          | 336/? [02:01<00:00,  2.77it/s, train/loss=8.200]
Epoch 0: |          | 337/? [02:01<00:00,  2.77it/s, train/loss=8.200]
Epoch 0: |          | 337/? [02:01<00:00,  2.77it/s, train/loss=28.30]
Epoch 0: |          | 338/? [02:02<00:00,  2.77it/s, train/loss=28.30]
Epoch 0: |          | 338/? [02:02<00:00,  2.77it/s, train/loss=18.60]
Epoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=18.60]
Epoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=31.30]
Epoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=31.30]
Epoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=33.80]
Epoch 0: |          | 341/? [02:03<00:00,  2.77it/s, train/loss=33.80]
Epoch 0: |          | 341/? [02:03<00:00,  2.77it/s, train/loss=27.80]
Epoch 0: |          | 342/? [02:03<00:00,  2.77it/s, train/loss=27.80]
Epoch 0: |          | 342/? [02:03<00:00,  2.77it/s, train/loss=25.80]
Epoch 0: |          | 343/? [02:03<00:00,  2.77it/s, train/loss=25.80]
Epoch 0: |          | 343/? [02:03<00:00,  2.77it/s, train/loss=10.80]
Epoch 0: |          | 344/? [02:04<00:00,  2.77it/s, train/loss=10.80]
Epoch 0: |          | 344/? [02:04<00:00,  2.77it/s, train/loss=21.40]
Epoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=21.40]
Epoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=27.50]
Epoch 0: |          | 346/? [02:04<00:00,  2.77it/s, train/loss=27.50]
Epoch 0: |          | 346/? [02:04<00:00,  2.77it/s, train/loss=26.90]
Epoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=26.90]
Epoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=9.160]
Epoch 0: |          | 348/? [02:05<00:00,  2.78it/s, train/loss=9.160]
Epoch 0: |          | 348/? [02:05<00:00,  2.78it/s, train/loss=16.30]
Epoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=16.30]
Epoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=18.30]
Epoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=18.30]
Epoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=27.30]
Epoch 0: |          | 351/? [02:06<00:00,  2.78it/s, train/loss=27.30]
Epoch 0: |          | 351/? [02:06<00:00,  2.78it/s, train/loss=20.10]
Epoch 0: |          | 352/? [02:06<00:00,  2.78it/s, train/loss=20.10]
Epoch 0: |          | 352/? [02:06<00:00,  2.78it/s, train/loss=10.80]
Epoch 0: |          | 353/? [02:07<00:00,  2.78it/s, train/loss=10.80]
Epoch 0: |          | 353/? [02:07<00:00,  2.78it/s, train/loss=39.30]
Epoch 0: |          | 354/? [02:07<00:00,  2.78it/s, train/loss=39.30]
Epoch 0: |          | 354/? [02:07<00:00,  2.78it/s, train/loss=38.70]
Epoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=38.70]
Epoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=32.30]
Epoch 0: |          | 356/? [02:08<00:00,  2.78it/s, train/loss=32.30]
Epoch 0: |          | 356/? [02:08<00:00,  2.78it/s, train/loss=16.10]
Epoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=16.10]
Epoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=33.00]
Epoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=33.00]
Epoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=28.10]
Epoch 0: |          | 359/? [02:08<00:00,  2.78it/s, train/loss=28.10]
Epoch 0: |          | 359/? [02:08<00:00,  2.78it/s, train/loss=9.550]
Epoch 0: |          | 360/? [02:09<00:00,  2.78it/s, train/loss=9.550]
Epoch 0: |          | 360/? [02:09<00:00,  2.78it/s, train/loss=16.10]
Epoch 0: |          | 361/? [02:09<00:00,  2.78it/s, train/loss=16.10]
Epoch 0: |          | 361/? [02:09<00:00,  2.78it/s, train/loss=33.40]
Epoch 0: |          | 362/? [02:09<00:00,  2.79it/s, train/loss=33.40]
Epoch 0: |          | 362/? [02:09<00:00,  2.79it/s, train/loss=12.90]
Epoch 0: |          | 363/? [02:10<00:00,  2.79it/s, train/loss=12.90]
Epoch 0: |          | 363/? [02:10<00:00,  2.79it/s, train/loss=7.820]
Epoch 0: |          | 364/? [02:10<00:00,  2.79it/s, train/loss=7.820]
Epoch 0: |          | 364/? [02:10<00:00,  2.79it/s, train/loss=31.80]
Epoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=31.80]
Epoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=23.70]
Epoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=23.70]
Epoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=30.10]
Epoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=30.10]
Epoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=60.60]
Epoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=60.60]
Epoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=17.70]
Epoch 0: |          | 369/? [02:12<00:00,  2.79it/s, train/loss=17.70]
Epoch 0: |          | 369/? [02:12<00:00,  2.79it/s, train/loss=22.10]
Epoch 0: |          | 370/? [02:12<00:00,  2.78it/s, train/loss=22.10]
Epoch 0: |          | 370/? [02:12<00:00,  2.78it/s, train/loss=32.60]
Epoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=32.60]
Epoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=19.20]
Epoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=19.20]
Epoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=21.30]
Epoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=21.30]
Epoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=56.40]
Epoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=56.40]
Epoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=7.560]
Epoch 0: |          | 375/? [02:14<00:00,  2.79it/s, train/loss=7.560]
Epoch 0: |          | 375/? [02:14<00:00,  2.79it/s, train/loss=25.50]
Epoch 0: |          | 376/? [02:14<00:00,  2.79it/s, train/loss=25.50]
Epoch 0: |          | 376/? [02:14<00:00,  2.79it/s, train/loss=12.80]
Epoch 0: |          | 377/? [02:15<00:00,  2.79it/s, train/loss=12.80]
Epoch 0: |          | 377/? [02:15<00:00,  2.79it/s, train/loss=71.40]
Epoch 0: |          | 378/? [02:15<00:00,  2.79it/s, train/loss=71.40]
Epoch 0: |          | 378/? [02:15<00:00,  2.79it/s, train/loss=49.30]
Epoch 0: |          | 379/? [02:15<00:00,  2.79it/s, train/loss=49.30]
Epoch 0: |          | 379/? [02:15<00:00,  2.79it/s, train/loss=35.50]
Epoch 0: |          | 380/? [02:16<00:00,  2.79it/s, train/loss=35.50]
Epoch 0: |          | 380/? [02:16<00:00,  2.79it/s, train/loss=8.540]
Epoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=8.540]
Epoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=16.60]
Epoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=16.60]
Epoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=19.50]
Epoch 0: |          | 383/? [02:17<00:00,  2.79it/s, train/loss=19.50]
Epoch 0: |          | 383/? [02:17<00:00,  2.79it/s, train/loss=10.60]
Epoch 0: |          | 384/? [02:17<00:00,  2.79it/s, train/loss=10.60]
Epoch 0: |          | 384/? [02:17<00:00,  2.79it/s, train/loss=25.00]
Epoch 0: |          | 385/? [02:17<00:00,  2.79it/s, train/loss=25.00]
Epoch 0: |          | 385/? [02:17<00:00,  2.79it/s, train/loss=31.50]
Epoch 0: |          | 386/? [02:18<00:00,  2.79it/s, train/loss=31.50]
Epoch 0: |          | 386/? [02:18<00:00,  2.79it/s, train/loss=34.80]
Epoch 0: |          | 387/? [02:18<00:00,  2.79it/s, train/loss=34.80]
Epoch 0: |          | 387/? [02:18<00:00,  2.79it/s, train/loss=9.860]
Epoch 0: |          | 388/? [02:18<00:00,  2.80it/s, train/loss=9.860]
Epoch 0: |          | 388/? [02:18<00:00,  2.80it/s, train/loss=19.40]
Epoch 0: |          | 389/? [02:19<00:00,  2.80it/s, train/loss=19.40]
Epoch 0: |          | 389/? [02:19<00:00,  2.80it/s, train/loss=23.50]
Epoch 0: |          | 390/? [02:19<00:00,  2.80it/s, train/loss=23.50]
Epoch 0: |          | 390/? [02:19<00:00,  2.80it/s, train/loss=10.40]
Epoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=10.40]
Epoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=13.90]
Epoch 0: |          | 392/? [02:20<00:00,  2.80it/s, train/loss=13.90]
Epoch 0: |          | 392/? [02:20<00:00,  2.80it/s, train/loss=13.50]
Epoch 0: |          | 393/? [02:20<00:00,  2.80it/s, train/loss=13.50]
Epoch 0: |          | 393/? [02:20<00:00,  2.80it/s, train/loss=27.80]
Epoch 0: |          | 394/? [02:20<00:00,  2.80it/s, train/loss=27.80]
Epoch 0: |          | 394/? [02:20<00:00,  2.80it/s, train/loss=15.40]
Epoch 0: |          | 395/? [02:21<00:00,  2.80it/s, train/loss=15.40]
Epoch 0: |          | 395/? [02:21<00:00,  2.80it/s, train/loss=36.60]
Epoch 0: |          | 396/? [02:21<00:00,  2.80it/s, train/loss=36.60]
Epoch 0: |          | 396/? [02:21<00:00,  2.80it/s, train/loss=37.40]
Epoch 0: |          | 397/? [02:21<00:00,  2.80it/s, train/loss=37.40]
Epoch 0: |          | 397/? [02:21<00:00,  2.80it/s, train/loss=25.60]
Epoch 0: |          | 398/? [02:22<00:00,  2.80it/s, train/loss=25.60]
Epoch 0: |          | 398/? [02:22<00:00,  2.80it/s, train/loss=30.60]
Epoch 0: |          | 399/? [02:22<00:00,  2.80it/s, train/loss=30.60]
Epoch 0: |          | 399/? [02:22<00:00,  2.80it/s, train/loss=33.70]
Epoch 0: |          | 400/? [02:22<00:00,  2.80it/s, train/loss=33.70]
Epoch 0: |          | 400/? [02:22<00:00,  2.80it/s, train/loss=13.20]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.32it/s]

Epoch 0: |          | 400/? [02:29<00:00,  2.67it/s, train/loss=13.20]
Epoch 0: |          | 401/? [02:30<00:00,  2.66it/s, train/loss=13.20]
Epoch 0: |          | 401/? [02:30<00:00,  2.66it/s, train/loss=30.60]
Epoch 0: |          | 402/? [02:31<00:00,  2.66it/s, train/loss=30.60]
Epoch 0: |          | 402/? [02:31<00:00,  2.66it/s, train/loss=26.40]
Epoch 0: |          | 403/? [02:31<00:00,  2.66it/s, train/loss=26.40]
Epoch 0: |          | 403/? [02:31<00:00,  2.66it/s, train/loss=13.50]
Epoch 0: |          | 404/? [02:31<00:00,  2.66it/s, train/loss=13.50]
Epoch 0: |          | 404/? [02:31<00:00,  2.66it/s, train/loss=16.60]
Epoch 0: |          | 405/? [02:32<00:00,  2.66it/s, train/loss=16.60]
Epoch 0: |          | 405/? [02:32<00:00,  2.66it/s, train/loss=27.20]
Epoch 0: |          | 406/? [02:32<00:00,  2.66it/s, train/loss=27.20]
Epoch 0: |          | 406/? [02:32<00:00,  2.66it/s, train/loss=18.70]
Epoch 0: |          | 407/? [02:32<00:00,  2.66it/s, train/loss=18.70]
Epoch 0: |          | 407/? [02:32<00:00,  2.66it/s, train/loss=27.70]
Epoch 0: |          | 408/? [02:33<00:00,  2.66it/s, train/loss=27.70]
Epoch 0: |          | 408/? [02:33<00:00,  2.66it/s, train/loss=30.20]
Epoch 0: |          | 409/? [02:33<00:00,  2.66it/s, train/loss=30.20]
Epoch 0: |          | 409/? [02:33<00:00,  2.66it/s, train/loss=51.20]
Epoch 0: |          | 410/? [02:33<00:00,  2.66it/s, train/loss=51.20]
Epoch 0: |          | 410/? [02:33<00:00,  2.66it/s, train/loss=16.80]
Epoch 0: |          | 411/? [02:34<00:00,  2.67it/s, train/loss=16.80]
Epoch 0: |          | 411/? [02:34<00:00,  2.67it/s, train/loss=18.90]
Epoch 0: |          | 412/? [02:34<00:00,  2.67it/s, train/loss=18.90]
Epoch 0: |          | 412/? [02:34<00:00,  2.67it/s, train/loss=58.30]
Epoch 0: |          | 413/? [02:34<00:00,  2.67it/s, train/loss=58.30]
Epoch 0: |          | 413/? [02:34<00:00,  2.67it/s, train/loss=42.70]
Epoch 0: |          | 414/? [02:35<00:00,  2.67it/s, train/loss=42.70]
Epoch 0: |          | 414/? [02:35<00:00,  2.67it/s, train/loss=64.70]
Epoch 0: |          | 415/? [02:35<00:00,  2.67it/s, train/loss=64.70]
Epoch 0: |          | 415/? [02:35<00:00,  2.67it/s, train/loss=19.50]
Epoch 0: |          | 416/? [02:35<00:00,  2.67it/s, train/loss=19.50]
Epoch 0: |          | 416/? [02:35<00:00,  2.67it/s, train/loss=24.70]
Epoch 0: |          | 417/? [02:36<00:00,  2.67it/s, train/loss=24.70]
Epoch 0: |          | 417/? [02:36<00:00,  2.67it/s, train/loss=18.20]
Epoch 0: |          | 418/? [02:36<00:00,  2.67it/s, train/loss=18.20]
Epoch 0: |          | 418/? [02:36<00:00,  2.67it/s, train/loss=17.60]
Epoch 0: |          | 419/? [02:36<00:00,  2.67it/s, train/loss=17.60]
Epoch 0: |          | 419/? [02:36<00:00,  2.67it/s, train/loss=17.90]
Epoch 0: |          | 420/? [02:37<00:00,  2.67it/s, train/loss=17.90]
Epoch 0: |          | 420/? [02:37<00:00,  2.67it/s, train/loss=18.60]
Epoch 0: |          | 421/? [02:37<00:00,  2.67it/s, train/loss=18.60]
Epoch 0: |          | 421/? [02:37<00:00,  2.67it/s, train/loss=24.80]
Epoch 0: |          | 422/? [02:37<00:00,  2.67it/s, train/loss=24.80]
Epoch 0: |          | 422/? [02:37<00:00,  2.67it/s, train/loss=16.30]
Epoch 0: |          | 423/? [02:38<00:00,  2.67it/s, train/loss=16.30]
Epoch 0: |          | 423/? [02:38<00:00,  2.67it/s, train/loss=30.70]
Epoch 0: |          | 424/? [02:38<00:00,  2.67it/s, train/loss=30.70]
Epoch 0: |          | 424/? [02:38<00:00,  2.67it/s, train/loss=20.60]
Epoch 0: |          | 425/? [02:38<00:00,  2.67it/s, train/loss=20.60]
Epoch 0: |          | 425/? [02:38<00:00,  2.67it/s, train/loss=52.60]
Epoch 0: |          | 426/? [02:39<00:00,  2.68it/s, train/loss=52.60]
Epoch 0: |          | 426/? [02:39<00:00,  2.68it/s, train/loss=13.80]
Epoch 0: |          | 427/? [02:39<00:00,  2.68it/s, train/loss=13.80]
Epoch 0: |          | 427/? [02:39<00:00,  2.68it/s, train/loss=21.80]
Epoch 0: |          | 428/? [02:39<00:00,  2.68it/s, train/loss=21.80]
Epoch 0: |          | 428/? [02:39<00:00,  2.68it/s, train/loss=15.70]
Epoch 0: |          | 429/? [02:40<00:00,  2.68it/s, train/loss=15.70]
Epoch 0: |          | 429/? [02:40<00:00,  2.68it/s, train/loss=33.00]
Epoch 0: |          | 430/? [02:40<00:00,  2.68it/s, train/loss=33.00]
Epoch 0: |          | 430/? [02:40<00:00,  2.68it/s, train/loss=13.50]
Epoch 0: |          | 431/? [02:40<00:00,  2.68it/s, train/loss=13.50]
Epoch 0: |          | 431/? [02:40<00:00,  2.68it/s, train/loss=12.40]
Epoch 0: |          | 432/? [02:41<00:00,  2.68it/s, train/loss=12.40]
Epoch 0: |          | 432/? [02:41<00:00,  2.68it/s, train/loss=30.90]
Epoch 0: |          | 433/? [02:41<00:00,  2.68it/s, train/loss=30.90]
Epoch 0: |          | 433/? [02:41<00:00,  2.68it/s, train/loss=26.90]
Epoch 0: |          | 434/? [02:41<00:00,  2.68it/s, train/loss=26.90]
Epoch 0: |          | 434/? [02:41<00:00,  2.68it/s, train/loss=17.60]
Epoch 0: |          | 435/? [02:42<00:00,  2.68it/s, train/loss=17.60]
Epoch 0: |          | 435/? [02:42<00:00,  2.68it/s, train/loss=16.60]
Epoch 0: |          | 436/? [02:42<00:00,  2.68it/s, train/loss=16.60]
Epoch 0: |          | 436/? [02:42<00:00,  2.68it/s, train/loss=14.60]
Epoch 0: |          | 437/? [02:42<00:00,  2.68it/s, train/loss=14.60]
Epoch 0: |          | 437/? [02:42<00:00,  2.68it/s, train/loss=25.70]
Epoch 0: |          | 438/? [02:43<00:00,  2.68it/s, train/loss=25.70]
Epoch 0: |          | 438/? [02:43<00:00,  2.68it/s, train/loss=9.540]
Epoch 0: |          | 439/? [02:43<00:00,  2.68it/s, train/loss=9.540]
Epoch 0: |          | 439/? [02:43<00:00,  2.68it/s, train/loss=8.600]
Epoch 0: |          | 440/? [02:43<00:00,  2.69it/s, train/loss=8.600]
Epoch 0: |          | 440/? [02:43<00:00,  2.69it/s, train/loss=35.50]
Epoch 0: |          | 441/? [02:44<00:00,  2.69it/s, train/loss=35.50]
Epoch 0: |          | 441/? [02:44<00:00,  2.69it/s, train/loss=35.10]
Epoch 0: |          | 442/? [02:44<00:00,  2.69it/s, train/loss=35.10]
Epoch 0: |          | 442/? [02:44<00:00,  2.69it/s, train/loss=17.60]
Epoch 0: |          | 443/? [02:44<00:00,  2.69it/s, train/loss=17.60]
Epoch 0: |          | 443/? [02:44<00:00,  2.69it/s, train/loss=23.50]
Epoch 0: |          | 444/? [02:45<00:00,  2.69it/s, train/loss=23.50]
Epoch 0: |          | 444/? [02:45<00:00,  2.69it/s, train/loss=7.570]
Epoch 0: |          | 445/? [02:45<00:00,  2.69it/s, train/loss=7.570]
Epoch 0: |          | 445/? [02:45<00:00,  2.69it/s, train/loss=40.90]
Epoch 0: |          | 446/? [02:45<00:00,  2.69it/s, train/loss=40.90]
Epoch 0: |          | 446/? [02:45<00:00,  2.69it/s, train/loss=12.80]
Epoch 0: |          | 447/? [02:46<00:00,  2.69it/s, train/loss=12.80]
Epoch 0: |          | 447/? [02:46<00:00,  2.69it/s, train/loss=17.70]
Epoch 0: |          | 448/? [02:46<00:00,  2.69it/s, train/loss=17.70]
Epoch 0: |          | 448/? [02:46<00:00,  2.69it/s, train/loss=6.630]
Epoch 0: |          | 449/? [02:46<00:00,  2.69it/s, train/loss=6.630]
Epoch 0: |          | 449/? [02:46<00:00,  2.69it/s, train/loss=36.00]
Epoch 0: |          | 450/? [02:47<00:00,  2.69it/s, train/loss=36.00]
Epoch 0: |          | 450/? [02:47<00:00,  2.69it/s, train/loss=18.80]
Epoch 0: |          | 451/? [02:47<00:00,  2.69it/s, train/loss=18.80]
Epoch 0: |          | 451/? [02:47<00:00,  2.69it/s, train/loss=14.00]
Epoch 0: |          | 452/? [02:47<00:00,  2.69it/s, train/loss=14.00]
Epoch 0: |          | 452/? [02:47<00:00,  2.69it/s, train/loss=83.80]
Epoch 0: |          | 453/? [02:48<00:00,  2.69it/s, train/loss=83.80]
Epoch 0: |          | 453/? [02:48<00:00,  2.69it/s, train/loss=43.40]
Epoch 0: |          | 454/? [02:48<00:00,  2.70it/s, train/loss=43.40]
Epoch 0: |          | 454/? [02:48<00:00,  2.70it/s, train/loss=20.80]
Epoch 0: |          | 455/? [02:48<00:00,  2.70it/s, train/loss=20.80]
Epoch 0: |          | 455/? [02:48<00:00,  2.70it/s, train/loss=9.980]
Epoch 0: |          | 456/? [02:49<00:00,  2.70it/s, train/loss=9.980]
Epoch 0: |          | 456/? [02:49<00:00,  2.70it/s, train/loss=17.70]
Epoch 0: |          | 457/? [02:49<00:00,  2.70it/s, train/loss=17.70]
Epoch 0: |          | 457/? [02:49<00:00,  2.70it/s, train/loss=30.30]
Epoch 0: |          | 458/? [02:49<00:00,  2.70it/s, train/loss=30.30]
Epoch 0: |          | 458/? [02:49<00:00,  2.70it/s, train/loss=46.60]
Epoch 0: |          | 459/? [02:50<00:00,  2.70it/s, train/loss=46.60]
Epoch 0: |          | 459/? [02:50<00:00,  2.70it/s, train/loss=34.10]
Epoch 0: |          | 460/? [02:50<00:00,  2.70it/s, train/loss=34.10]
Epoch 0: |          | 460/? [02:50<00:00,  2.70it/s, train/loss=17.40]
Epoch 0: |          | 461/? [02:50<00:00,  2.70it/s, train/loss=17.40]
Epoch 0: |          | 461/? [02:50<00:00,  2.70it/s, train/loss=47.60]
Epoch 0: |          | 462/? [02:51<00:00,  2.70it/s, train/loss=47.60]
Epoch 0: |          | 462/? [02:51<00:00,  2.70it/s, train/loss=28.80]
Epoch 0: |          | 463/? [02:51<00:00,  2.70it/s, train/loss=28.80]
Epoch 0: |          | 463/? [02:51<00:00,  2.70it/s, train/loss=17.10]
Epoch 0: |          | 464/? [02:51<00:00,  2.70it/s, train/loss=17.10]
Epoch 0: |          | 464/? [02:51<00:00,  2.70it/s, train/loss=9.830]
Epoch 0: |          | 465/? [02:52<00:00,  2.70it/s, train/loss=9.830]
Epoch 0: |          | 465/? [02:52<00:00,  2.70it/s, train/loss=44.80]
Epoch 0: |          | 466/? [02:52<00:00,  2.70it/s, train/loss=44.80]
Epoch 0: |          | 466/? [02:52<00:00,  2.70it/s, train/loss=7.480]
Epoch 0: |          | 467/? [02:52<00:00,  2.70it/s, train/loss=7.480]
Epoch 0: |          | 467/? [02:52<00:00,  2.70it/s, train/loss=9.460]
Epoch 0: |          | 468/? [02:53<00:00,  2.70it/s, train/loss=9.460]
Epoch 0: |          | 468/? [02:53<00:00,  2.70it/s, train/loss=12.20]
Epoch 0: |          | 469/? [02:53<00:00,  2.70it/s, train/loss=12.20]
Epoch 0: |          | 469/? [02:53<00:00,  2.70it/s, train/loss=51.10]
Epoch 0: |          | 470/? [02:53<00:00,  2.70it/s, train/loss=51.10]
Epoch 0: |          | 470/? [02:53<00:00,  2.70it/s, train/loss=27.10]
Epoch 0: |          | 471/? [02:54<00:00,  2.70it/s, train/loss=27.10]
Epoch 0: |          | 471/? [02:54<00:00,  2.70it/s, train/loss=44.90]
Epoch 0: |          | 472/? [02:54<00:00,  2.70it/s, train/loss=44.90]
Epoch 0: |          | 472/? [02:54<00:00,  2.70it/s, train/loss=16.30]
Epoch 0: |          | 473/? [02:54<00:00,  2.70it/s, train/loss=16.30]
Epoch 0: |          | 473/? [02:54<00:00,  2.70it/s, train/loss=41.40]
Epoch 0: |          | 474/? [02:55<00:00,  2.70it/s, train/loss=41.40]
Epoch 0: |          | 474/? [02:55<00:00,  2.70it/s, train/loss=14.00]
Epoch 0: |          | 475/? [02:55<00:00,  2.71it/s, train/loss=14.00]
Epoch 0: |          | 475/? [02:55<00:00,  2.71it/s, train/loss=8.040]
Epoch 0: |          | 476/? [02:55<00:00,  2.71it/s, train/loss=8.040]
Epoch 0: |          | 476/? [02:55<00:00,  2.71it/s, train/loss=29.40]
Epoch 0: |          | 477/? [02:56<00:00,  2.71it/s, train/loss=29.40]
Epoch 0: |          | 477/? [02:56<00:00,  2.71it/s, train/loss=49.00]
Epoch 0: |          | 478/? [02:56<00:00,  2.71it/s, train/loss=49.00]
Epoch 0: |          | 478/? [02:56<00:00,  2.71it/s, train/loss=18.30]
Epoch 0: |          | 479/? [02:56<00:00,  2.71it/s, train/loss=18.30]
Epoch 0: |          | 479/? [02:56<00:00,  2.71it/s, train/loss=10.50]
Epoch 0: |          | 480/? [02:57<00:00,  2.71it/s, train/loss=10.50]
Epoch 0: |          | 480/? [02:57<00:00,  2.71it/s, train/loss=29.50]
Epoch 0: |          | 481/? [02:57<00:00,  2.71it/s, train/loss=29.50]
Epoch 0: |          | 481/? [02:57<00:00,  2.71it/s, train/loss=14.10]
Epoch 0: |          | 482/? [02:57<00:00,  2.71it/s, train/loss=14.10]
Epoch 0: |          | 482/? [02:57<00:00,  2.71it/s, train/loss=24.80]
Epoch 0: |          | 483/? [02:58<00:00,  2.71it/s, train/loss=24.80]
Epoch 0: |          | 483/? [02:58<00:00,  2.71it/s, train/loss=8.920]
Epoch 0: |          | 484/? [02:58<00:00,  2.71it/s, train/loss=8.920]
Epoch 0: |          | 484/? [02:58<00:00,  2.71it/s, train/loss=26.50]
Epoch 0: |          | 485/? [02:58<00:00,  2.71it/s, train/loss=26.50]
Epoch 0: |          | 485/? [02:58<00:00,  2.71it/s, train/loss=29.00]
Epoch 0: |          | 486/? [02:59<00:00,  2.71it/s, train/loss=29.00]
Epoch 0: |          | 486/? [02:59<00:00,  2.71it/s, train/loss=27.30]
Epoch 0: |          | 487/? [02:59<00:00,  2.71it/s, train/loss=27.30]
Epoch 0: |          | 487/? [02:59<00:00,  2.71it/s, train/loss=14.50]
Epoch 0: |          | 488/? [02:59<00:00,  2.71it/s, train/loss=14.50]
Epoch 0: |          | 488/? [02:59<00:00,  2.71it/s, train/loss=15.10]
Epoch 0: |          | 489/? [03:00<00:00,  2.71it/s, train/loss=15.10]
Epoch 0: |          | 489/? [03:00<00:00,  2.71it/s, train/loss=42.50]
Epoch 0: |          | 490/? [03:00<00:00,  2.71it/s, train/loss=42.50]
Epoch 0: |          | 490/? [03:00<00:00,  2.71it/s, train/loss=16.70]
Epoch 0: |          | 491/? [03:00<00:00,  2.72it/s, train/loss=16.70]
Epoch 0: |          | 491/? [03:00<00:00,  2.72it/s, train/loss=15.50]
Epoch 0: |          | 492/? [03:01<00:00,  2.72it/s, train/loss=15.50]
Epoch 0: |          | 492/? [03:01<00:00,  2.72it/s, train/loss=14.40]
Epoch 0: |          | 493/? [03:01<00:00,  2.72it/s, train/loss=14.40]
Epoch 0: |          | 493/? [03:01<00:00,  2.72it/s, train/loss=44.80]
Epoch 0: |          | 494/? [03:01<00:00,  2.72it/s, train/loss=44.80]
Epoch 0: |          | 494/? [03:01<00:00,  2.72it/s, train/loss=22.20]
Epoch 0: |          | 495/? [03:02<00:00,  2.72it/s, train/loss=22.20]
Epoch 0: |          | 495/? [03:02<00:00,  2.72it/s, train/loss=17.40]
Epoch 0: |          | 496/? [03:02<00:00,  2.72it/s, train/loss=17.40]
Epoch 0: |          | 496/? [03:02<00:00,  2.72it/s, train/loss=25.70]
Epoch 0: |          | 497/? [03:02<00:00,  2.72it/s, train/loss=25.70]
Epoch 0: |          | 497/? [03:02<00:00,  2.72it/s, train/loss=29.50]
Epoch 0: |          | 498/? [03:03<00:00,  2.72it/s, train/loss=29.50]
Epoch 0: |          | 498/? [03:03<00:00,  2.72it/s, train/loss=37.70]
Epoch 0: |          | 499/? [03:03<00:00,  2.72it/s, train/loss=37.70]
Epoch 0: |          | 499/? [03:03<00:00,  2.72it/s, train/loss=7.640]
Epoch 0: |          | 500/? [03:03<00:00,  2.72it/s, train/loss=7.640]
Epoch 0: |          | 500/? [03:03<00:00,  2.72it/s, train/loss=14.00]
Epoch 0: |          | 501/? [03:04<00:00,  2.72it/s, train/loss=14.00]
Epoch 0: |          | 501/? [03:04<00:00,  2.72it/s, train/loss=40.30]
Epoch 0: |          | 502/? [03:04<00:00,  2.72it/s, train/loss=40.30]
Epoch 0: |          | 502/? [03:04<00:00,  2.72it/s, train/loss=32.80]
Epoch 0: |          | 503/? [03:04<00:00,  2.72it/s, train/loss=32.80]
Epoch 0: |          | 503/? [03:04<00:00,  2.72it/s, train/loss=20.80]
Epoch 0: |          | 504/? [03:05<00:00,  2.72it/s, train/loss=20.80]
Epoch 0: |          | 504/? [03:05<00:00,  2.72it/s, train/loss=39.40]
Epoch 0: |          | 505/? [03:05<00:00,  2.72it/s, train/loss=39.40]
Epoch 0: |          | 505/? [03:05<00:00,  2.72it/s, train/loss=22.80]
Epoch 0: |          | 506/? [03:05<00:00,  2.72it/s, train/loss=22.80]
Epoch 0: |          | 506/? [03:05<00:00,  2.72it/s, train/loss=22.80]
Epoch 0: |          | 507/? [03:06<00:00,  2.72it/s, train/loss=22.80]
Epoch 0: |          | 507/? [03:06<00:00,  2.72it/s, train/loss=21.10]
Epoch 0: |          | 508/? [03:06<00:00,  2.72it/s, train/loss=21.10]
Epoch 0: |          | 508/? [03:06<00:00,  2.72it/s, train/loss=8.100]
Epoch 0: |          | 509/? [03:06<00:00,  2.73it/s, train/loss=8.100]
Epoch 0: |          | 509/? [03:06<00:00,  2.73it/s, train/loss=21.00]
Epoch 0: |          | 510/? [03:07<00:00,  2.73it/s, train/loss=21.00]
Epoch 0: |          | 510/? [03:07<00:00,  2.73it/s, train/loss=10.50]
Epoch 0: |          | 511/? [03:07<00:00,  2.73it/s, train/loss=10.50]
Epoch 0: |          | 511/? [03:07<00:00,  2.73it/s, train/loss=32.80]
Epoch 0: |          | 512/? [03:07<00:00,  2.73it/s, train/loss=32.80]
Epoch 0: |          | 512/? [03:07<00:00,  2.73it/s, train/loss=10.10]
Epoch 0: |          | 513/? [03:08<00:00,  2.73it/s, train/loss=10.10]
Epoch 0: |          | 513/? [03:08<00:00,  2.73it/s, train/loss=34.70]
Epoch 0: |          | 514/? [03:08<00:00,  2.73it/s, train/loss=34.70]
Epoch 0: |          | 514/? [03:08<00:00,  2.73it/s, train/loss=12.70]
Epoch 0: |          | 515/? [03:08<00:00,  2.73it/s, train/loss=12.70]
Epoch 0: |          | 515/? [03:08<00:00,  2.73it/s, train/loss=8.430]
Epoch 0: |          | 516/? [03:09<00:00,  2.73it/s, train/loss=8.430]
Epoch 0: |          | 516/? [03:09<00:00,  2.73it/s, train/loss=16.00]
Epoch 0: |          | 517/? [03:09<00:00,  2.73it/s, train/loss=16.00]
Epoch 0: |          | 517/? [03:09<00:00,  2.73it/s, train/loss=25.90]
Epoch 0: |          | 518/? [03:09<00:00,  2.73it/s, train/loss=25.90]
Epoch 0: |          | 518/? [03:09<00:00,  2.73it/s, train/loss=13.20]
Epoch 0: |          | 519/? [03:10<00:00,  2.73it/s, train/loss=13.20]
Epoch 0: |          | 519/? [03:10<00:00,  2.73it/s, train/loss=30.10]
Epoch 0: |          | 520/? [03:10<00:00,  2.73it/s, train/loss=30.10]
Epoch 0: |          | 520/? [03:10<00:00,  2.73it/s, train/loss=26.40]
Epoch 0: |          | 521/? [03:10<00:00,  2.73it/s, train/loss=26.40]
Epoch 0: |          | 521/? [03:10<00:00,  2.73it/s, train/loss=28.50]
Epoch 0: |          | 522/? [03:11<00:00,  2.73it/s, train/loss=28.50]
Epoch 0: |          | 522/? [03:11<00:00,  2.73it/s, train/loss=29.50]
Epoch 0: |          | 523/? [03:11<00:00,  2.73it/s, train/loss=29.50]
Epoch 0: |          | 523/? [03:11<00:00,  2.73it/s, train/loss=23.70]
Epoch 0: |          | 524/? [03:11<00:00,  2.73it/s, train/loss=23.70]
Epoch 0: |          | 524/? [03:11<00:00,  2.73it/s, train/loss=14.50]
Epoch 0: |          | 525/? [03:12<00:00,  2.73it/s, train/loss=14.50]
Epoch 0: |          | 525/? [03:12<00:00,  2.73it/s, train/loss=25.00]
Epoch 0: |          | 526/? [03:12<00:00,  2.73it/s, train/loss=25.00]
Epoch 0: |          | 526/? [03:12<00:00,  2.73it/s, train/loss=35.40]
Epoch 0: |          | 527/? [03:12<00:00,  2.73it/s, train/loss=35.40]
Epoch 0: |          | 527/? [03:12<00:00,  2.73it/s, train/loss=29.80]
Epoch 0: |          | 528/? [03:13<00:00,  2.73it/s, train/loss=29.80]
Epoch 0: |          | 528/? [03:13<00:00,  2.73it/s, train/loss=24.20]
Epoch 0: |          | 529/? [03:13<00:00,  2.73it/s, train/loss=24.20]
Epoch 0: |          | 529/? [03:13<00:00,  2.73it/s, train/loss=28.20]
Epoch 0: |          | 530/? [03:13<00:00,  2.73it/s, train/loss=28.20]
Epoch 0: |          | 530/? [03:13<00:00,  2.73it/s, train/loss=19.10]
Epoch 0: |          | 531/? [03:14<00:00,  2.74it/s, train/loss=19.10]
Epoch 0: |          | 531/? [03:14<00:00,  2.74it/s, train/loss=20.40]
Epoch 0: |          | 532/? [03:14<00:00,  2.74it/s, train/loss=20.40]
Epoch 0: |          | 532/? [03:14<00:00,  2.74it/s, train/loss=30.20]
Epoch 0: |          | 533/? [03:14<00:00,  2.74it/s, train/loss=30.20]
Epoch 0: |          | 533/? [03:14<00:00,  2.74it/s, train/loss=19.40]
Epoch 0: |          | 534/? [03:15<00:00,  2.74it/s, train/loss=19.40]
Epoch 0: |          | 534/? [03:15<00:00,  2.74it/s, train/loss=21.10]
Epoch 0: |          | 535/? [03:15<00:00,  2.74it/s, train/loss=21.10]
Epoch 0: |          | 535/? [03:15<00:00,  2.74it/s, train/loss=15.40]
Epoch 0: |          | 536/? [03:15<00:00,  2.74it/s, train/loss=15.40]
Epoch 0: |          | 536/? [03:15<00:00,  2.74it/s, train/loss=27.50]
Epoch 0: |          | 537/? [03:16<00:00,  2.74it/s, train/loss=27.50]
Epoch 0: |          | 537/? [03:16<00:00,  2.74it/s, train/loss=20.20]
Epoch 0: |          | 538/? [03:16<00:00,  2.74it/s, train/loss=20.20]
Epoch 0: |          | 538/? [03:16<00:00,  2.74it/s, train/loss=9.040]
Epoch 0: |          | 539/? [03:16<00:00,  2.74it/s, train/loss=9.040]
Epoch 0: |          | 539/? [03:16<00:00,  2.74it/s, train/loss=19.20]
Epoch 0: |          | 540/? [03:17<00:00,  2.74it/s, train/loss=19.20]
Epoch 0: |          | 540/? [03:17<00:00,  2.74it/s, train/loss=23.50]
Epoch 0: |          | 541/? [03:17<00:00,  2.74it/s, train/loss=23.50]
Epoch 0: |          | 541/? [03:17<00:00,  2.74it/s, train/loss=18.80]
Epoch 0: |          | 542/? [03:17<00:00,  2.74it/s, train/loss=18.80]
Epoch 0: |          | 542/? [03:17<00:00,  2.74it/s, train/loss=12.30]
Epoch 0: |          | 543/? [03:18<00:00,  2.74it/s, train/loss=12.30]
Epoch 0: |          | 543/? [03:18<00:00,  2.74it/s, train/loss=31.00]
Epoch 0: |          | 544/? [03:18<00:00,  2.74it/s, train/loss=31.00]
Epoch 0: |          | 544/? [03:18<00:00,  2.74it/s, train/loss=12.90]
Epoch 0: |          | 545/? [03:18<00:00,  2.74it/s, train/loss=12.90]
Epoch 0: |          | 545/? [03:18<00:00,  2.74it/s, train/loss=16.30]
Epoch 0: |          | 546/? [03:19<00:00,  2.74it/s, train/loss=16.30]
Epoch 0: |          | 546/? [03:19<00:00,  2.74it/s, train/loss=18.80]
Epoch 0: |          | 547/? [03:19<00:00,  2.74it/s, train/loss=18.80]
Epoch 0: |          | 547/? [03:19<00:00,  2.74it/s, train/loss=19.40]
Epoch 0: |          | 548/? [03:19<00:00,  2.74it/s, train/loss=19.40]
Epoch 0: |          | 548/? [03:19<00:00,  2.74it/s, train/loss=21.10]
Epoch 0: |          | 549/? [03:19<00:00,  2.75it/s, train/loss=21.10]
Epoch 0: |          | 549/? [03:20<00:00,  2.74it/s, train/loss=28.20]
Epoch 0: |          | 550/? [03:20<00:00,  2.75it/s, train/loss=28.20]
Epoch 0: |          | 550/? [03:20<00:00,  2.75it/s, train/loss=28.10]
Epoch 0: |          | 551/? [03:20<00:00,  2.75it/s, train/loss=28.10]
Epoch 0: |          | 551/? [03:20<00:00,  2.75it/s, train/loss=48.30]
Epoch 0: |          | 552/? [03:20<00:00,  2.75it/s, train/loss=48.30]
Epoch 0: |          | 552/? [03:20<00:00,  2.75it/s, train/loss=24.20]
Epoch 0: |          | 553/? [03:21<00:00,  2.75it/s, train/loss=24.20]
Epoch 0: |          | 553/? [03:21<00:00,  2.75it/s, train/loss=31.10]
Epoch 0: |          | 554/? [03:21<00:00,  2.75it/s, train/loss=31.10]
Epoch 0: |          | 554/? [03:21<00:00,  2.75it/s, train/loss=24.40]
Epoch 0: |          | 555/? [03:21<00:00,  2.75it/s, train/loss=24.40]
Epoch 0: |          | 555/? [03:21<00:00,  2.75it/s, train/loss=19.50]
Epoch 0: |          | 556/? [03:22<00:00,  2.75it/s, train/loss=19.50]
Epoch 0: |          | 556/? [03:22<00:00,  2.75it/s, train/loss=25.60]
Epoch 0: |          | 557/? [03:22<00:00,  2.75it/s, train/loss=25.60]
Epoch 0: |          | 557/? [03:22<00:00,  2.75it/s, train/loss=23.50]
Epoch 0: |          | 558/? [03:22<00:00,  2.75it/s, train/loss=23.50]
Epoch 0: |          | 558/? [03:22<00:00,  2.75it/s, train/loss=19.50]
Epoch 0: |          | 559/? [03:23<00:00,  2.75it/s, train/loss=19.50]
Epoch 0: |          | 559/? [03:23<00:00,  2.75it/s, train/loss=19.30]
Epoch 0: |          | 560/? [03:23<00:00,  2.75it/s, train/loss=19.30]
Epoch 0: |          | 560/? [03:23<00:00,  2.75it/s, train/loss=10.50]
Epoch 0: |          | 561/? [03:23<00:00,  2.75it/s, train/loss=10.50]
Epoch 0: |          | 561/? [03:23<00:00,  2.75it/s, train/loss=27.50]
Epoch 0: |          | 562/? [03:24<00:00,  2.75it/s, train/loss=27.50]
Epoch 0: |          | 562/? [03:24<00:00,  2.75it/s, train/loss=27.70]
Epoch 0: |          | 563/? [03:24<00:00,  2.75it/s, train/loss=27.70]
Epoch 0: |          | 563/? [03:24<00:00,  2.75it/s, train/loss=17.00]
Epoch 0: |          | 564/? [03:24<00:00,  2.75it/s, train/loss=17.00]
Epoch 0: |          | 564/? [03:24<00:00,  2.75it/s, train/loss=13.70]
Epoch 0: |          | 565/? [03:25<00:00,  2.75it/s, train/loss=13.70]
Epoch 0: |          | 565/? [03:25<00:00,  2.75it/s, train/loss=25.20]
Epoch 0: |          | 566/? [03:25<00:00,  2.75it/s, train/loss=25.20]
Epoch 0: |          | 566/? [03:25<00:00,  2.75it/s, train/loss=20.40]
Epoch 0: |          | 567/? [03:25<00:00,  2.75it/s, train/loss=20.40]
Epoch 0: |          | 567/? [03:25<00:00,  2.75it/s, train/loss=22.20]
Epoch 0: |          | 568/? [03:26<00:00,  2.75it/s, train/loss=22.20]
Epoch 0: |          | 568/? [03:26<00:00,  2.75it/s, train/loss=22.10]
Epoch 0: |          | 569/? [03:26<00:00,  2.75it/s, train/loss=22.10]
Epoch 0: |          | 569/? [03:26<00:00,  2.75it/s, train/loss=18.20]
Epoch 0: |          | 570/? [03:26<00:00,  2.75it/s, train/loss=18.20]
Epoch 0: |          | 570/? [03:26<00:00,  2.75it/s, train/loss=28.90]
Epoch 0: |          | 571/? [03:27<00:00,  2.76it/s, train/loss=28.90]
Epoch 0: |          | 571/? [03:27<00:00,  2.75it/s, train/loss=35.40]
Epoch 0: |          | 572/? [03:27<00:00,  2.76it/s, train/loss=35.40]
Epoch 0: |          | 572/? [03:27<00:00,  2.76it/s, train/loss=10.30]
Epoch 0: |          | 573/? [03:27<00:00,  2.76it/s, train/loss=10.30]
Epoch 0: |          | 573/? [03:27<00:00,  2.76it/s, train/loss=21.20]
Epoch 0: |          | 574/? [03:28<00:00,  2.76it/s, train/loss=21.20]
Epoch 0: |          | 574/? [03:28<00:00,  2.76it/s, train/loss=38.30]
Epoch 0: |          | 575/? [03:28<00:00,  2.76it/s, train/loss=38.30]
Epoch 0: |          | 575/? [03:28<00:00,  2.76it/s, train/loss=6.780]
Epoch 0: |          | 576/? [03:28<00:00,  2.76it/s, train/loss=6.780]
Epoch 0: |          | 576/? [03:28<00:00,  2.76it/s, train/loss=9.820]
Epoch 0: |          | 577/? [03:29<00:00,  2.76it/s, train/loss=9.820]
Epoch 0: |          | 577/? [03:29<00:00,  2.76it/s, train/loss=19.20]
Epoch 0: |          | 578/? [03:29<00:00,  2.76it/s, train/loss=19.20]
Epoch 0: |          | 578/? [03:29<00:00,  2.76it/s, train/loss=18.50]
Epoch 0: |          | 579/? [03:29<00:00,  2.76it/s, train/loss=18.50]
Epoch 0: |          | 579/? [03:29<00:00,  2.76it/s, train/loss=16.60]
Epoch 0: |          | 580/? [03:30<00:00,  2.76it/s, train/loss=16.60]
Epoch 0: |          | 580/? [03:30<00:00,  2.76it/s, train/loss=41.70]
Epoch 0: |          | 581/? [03:30<00:00,  2.76it/s, train/loss=41.70]
Epoch 0: |          | 581/? [03:30<00:00,  2.76it/s, train/loss=16.80]
Epoch 0: |          | 582/? [03:30<00:00,  2.76it/s, train/loss=16.80]
Epoch 0: |          | 582/? [03:30<00:00,  2.76it/s, train/loss=13.50]
Epoch 0: |          | 583/? [03:31<00:00,  2.76it/s, train/loss=13.50]
Epoch 0: |          | 583/? [03:31<00:00,  2.76it/s, train/loss=12.60]
Epoch 0: |          | 584/? [03:31<00:00,  2.76it/s, train/loss=12.60]
Epoch 0: |          | 584/? [03:31<00:00,  2.76it/s, train/loss=8.210]
Epoch 0: |          | 585/? [03:31<00:00,  2.76it/s, train/loss=8.210]
Epoch 0: |          | 585/? [03:31<00:00,  2.76it/s, train/loss=25.00]
Epoch 0: |          | 586/? [03:32<00:00,  2.76it/s, train/loss=25.00]
Epoch 0: |          | 586/? [03:32<00:00,  2.76it/s, train/loss=21.70]
Epoch 0: |          | 587/? [03:32<00:00,  2.76it/s, train/loss=21.70]
Epoch 0: |          | 587/? [03:32<00:00,  2.76it/s, train/loss=22.60]
Epoch 0: |          | 588/? [03:32<00:00,  2.76it/s, train/loss=22.60]
Epoch 0: |          | 588/? [03:32<00:00,  2.76it/s, train/loss=33.70]
Epoch 0: |          | 589/? [03:33<00:00,  2.76it/s, train/loss=33.70]
Epoch 0: |          | 589/? [03:33<00:00,  2.76it/s, train/loss=23.50]
Epoch 0: |          | 590/? [03:33<00:00,  2.76it/s, train/loss=23.50]
Epoch 0: |          | 590/? [03:33<00:00,  2.76it/s, train/loss=24.20]
Epoch 0: |          | 591/? [03:33<00:00,  2.76it/s, train/loss=24.20]
Epoch 0: |          | 591/? [03:33<00:00,  2.76it/s, train/loss=16.40]
Epoch 0: |          | 592/? [03:34<00:00,  2.76it/s, train/loss=16.40]
Epoch 0: |          | 592/? [03:34<00:00,  2.76it/s, train/loss=30.10]
Epoch 0: |          | 593/? [03:34<00:00,  2.76it/s, train/loss=30.10]
Epoch 0: |          | 593/? [03:34<00:00,  2.76it/s, train/loss=15.80]
Epoch 0: |          | 594/? [03:34<00:00,  2.76it/s, train/loss=15.80]
Epoch 0: |          | 594/? [03:34<00:00,  2.76it/s, train/loss=28.50]
Epoch 0: |          | 595/? [03:35<00:00,  2.76it/s, train/loss=28.50]
Epoch 0: |          | 595/? [03:35<00:00,  2.76it/s, train/loss=42.00]
Epoch 0: |          | 596/? [03:35<00:00,  2.76it/s, train/loss=42.00]
Epoch 0: |          | 596/? [03:35<00:00,  2.76it/s, train/loss=25.40]
Epoch 0: |          | 597/? [03:35<00:00,  2.77it/s, train/loss=25.40]
Epoch 0: |          | 597/? [03:35<00:00,  2.77it/s, train/loss=51.90]
Epoch 0: |          | 598/? [03:36<00:00,  2.77it/s, train/loss=51.90]
Epoch 0: |          | 598/? [03:36<00:00,  2.77it/s, train/loss=34.00]
Epoch 0: |          | 599/? [03:36<00:00,  2.77it/s, train/loss=34.00]
Epoch 0: |          | 599/? [03:36<00:00,  2.77it/s, train/loss=31.20]
Epoch 0: |          | 600/? [03:36<00:00,  2.77it/s, train/loss=31.20]
Epoch 0: |          | 600/? [03:36<00:00,  2.77it/s, train/loss=20.80]
Validation: |          | 0/? [00:00<?, ?it/s]
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Validation DataLoader 0:  75%|███████▌  | 30/40 [00:02<00:00, 11.94it/s]
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Validation DataLoader 0:  85%|████████▌ | 34/40 [00:02<00:00, 11.70it/s]
Validation DataLoader 0:  88%|████████▊ | 35/40 [00:02<00:00, 11.71it/s]
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Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.73it/s]

Epoch 0: |          | 600/? [03:43<00:00,  2.68it/s, train/loss=20.80]
Epoch 0: |          | 601/? [03:44<00:00,  2.67it/s, train/loss=20.80]
Epoch 0: |          | 601/? [03:44<00:00,  2.67it/s, train/loss=45.20]
Epoch 0: |          | 602/? [03:45<00:00,  2.67it/s, train/loss=45.20]
Epoch 0: |          | 602/? [03:45<00:00,  2.67it/s, train/loss=19.60]
Epoch 0: |          | 603/? [03:45<00:00,  2.67it/s, train/loss=19.60]
Epoch 0: |          | 603/? [03:45<00:00,  2.67it/s, train/loss=43.40]
Epoch 0: |          | 604/? [03:45<00:00,  2.68it/s, train/loss=43.40]
Epoch 0: |          | 604/? [03:45<00:00,  2.68it/s, train/loss=9.500]
Epoch 0: |          | 605/? [03:46<00:00,  2.68it/s, train/loss=9.500]
Epoch 0: |          | 605/? [03:46<00:00,  2.68it/s, train/loss=18.10]
Epoch 0: |          | 606/? [03:46<00:00,  2.68it/s, train/loss=18.10]
Epoch 0: |          | 606/? [03:46<00:00,  2.68it/s, train/loss=21.10]
Epoch 0: |          | 607/? [03:46<00:00,  2.68it/s, train/loss=21.10]
Epoch 0: |          | 607/? [03:46<00:00,  2.68it/s, train/loss=22.80]
Epoch 0: |          | 608/? [03:47<00:00,  2.68it/s, train/loss=22.80]
Epoch 0: |          | 608/? [03:47<00:00,  2.68it/s, train/loss=30.10]
Epoch 0: |          | 609/? [03:47<00:00,  2.68it/s, train/loss=30.10]
Epoch 0: |          | 609/? [03:47<00:00,  2.68it/s, train/loss=24.90]
Epoch 0: |          | 610/? [03:47<00:00,  2.68it/s, train/loss=24.90]
Epoch 0: |          | 610/? [03:47<00:00,  2.68it/s, train/loss=11.10]
Epoch 0: |          | 611/? [03:48<00:00,  2.68it/s, train/loss=11.10]
Epoch 0: |          | 611/? [03:48<00:00,  2.68it/s, train/loss=26.60]
Epoch 0: |          | 612/? [03:48<00:00,  2.68it/s, train/loss=26.60]
Epoch 0: |          | 612/? [03:48<00:00,  2.68it/s, train/loss=26.10]
Epoch 0: |          | 613/? [03:48<00:00,  2.68it/s, train/loss=26.10]
Epoch 0: |          | 613/? [03:48<00:00,  2.68it/s, train/loss=27.20]
Epoch 0: |          | 614/? [03:49<00:00,  2.68it/s, train/loss=27.20]
Epoch 0: |          | 614/? [03:49<00:00,  2.68it/s, train/loss=23.90]
Epoch 0: |          | 615/? [03:49<00:00,  2.68it/s, train/loss=23.90]
Epoch 0: |          | 615/? [03:49<00:00,  2.68it/s, train/loss=50.80]
Epoch 0: |          | 616/? [03:49<00:00,  2.68it/s, train/loss=50.80]
Epoch 0: |          | 616/? [03:49<00:00,  2.68it/s, train/loss=8.490]
Epoch 0: |          | 617/? [03:50<00:00,  2.68it/s, train/loss=8.490]
Epoch 0: |          | 617/? [03:50<00:00,  2.68it/s, train/loss=18.10]
Epoch 0: |          | 618/? [03:50<00:00,  2.68it/s, train/loss=18.10]
Epoch 0: |          | 618/? [03:50<00:00,  2.68it/s, train/loss=8.960]
Epoch 0: |          | 619/? [03:50<00:00,  2.68it/s, train/loss=8.960]
Epoch 0: |          | 619/? [03:50<00:00,  2.68it/s, train/loss=20.80]
Epoch 0: |          | 620/? [03:51<00:00,  2.68it/s, train/loss=20.80]
Epoch 0: |          | 620/? [03:51<00:00,  2.68it/s, train/loss=7.220]
Epoch 0: |          | 621/? [03:51<00:00,  2.68it/s, train/loss=7.220]
Epoch 0: |          | 621/? [03:51<00:00,  2.68it/s, train/loss=32.80]
Epoch 0: |          | 622/? [03:51<00:00,  2.68it/s, train/loss=32.80]
Epoch 0: |          | 622/? [03:51<00:00,  2.68it/s, train/loss=20.60]
Epoch 0: |          | 623/? [03:51<00:00,  2.69it/s, train/loss=20.60]
Epoch 0: |          | 623/? [03:51<00:00,  2.69it/s, train/loss=41.70]
Epoch 0: |          | 624/? [03:52<00:00,  2.69it/s, train/loss=41.70]
Epoch 0: |          | 624/? [03:52<00:00,  2.69it/s, train/loss=22.60]
Epoch 0: |          | 625/? [03:52<00:00,  2.69it/s, train/loss=22.60]
Epoch 0: |          | 625/? [03:52<00:00,  2.69it/s, train/loss=18.70]
Epoch 0: |          | 626/? [03:52<00:00,  2.69it/s, train/loss=18.70]
Epoch 0: |          | 626/? [03:52<00:00,  2.69it/s, train/loss=14.00]
Epoch 0: |          | 627/? [03:53<00:00,  2.69it/s, train/loss=14.00]
Epoch 0: |          | 627/? [03:53<00:00,  2.69it/s, train/loss=24.30]
Epoch 0: |          | 628/? [03:53<00:00,  2.69it/s, train/loss=24.30]
Epoch 0: |          | 628/? [03:53<00:00,  2.69it/s, train/loss=20.40]
Epoch 0: |          | 629/? [03:53<00:00,  2.69it/s, train/loss=20.40]
Epoch 0: |          | 629/? [03:53<00:00,  2.69it/s, train/loss=34.40]
Epoch 0: |          | 630/? [03:54<00:00,  2.69it/s, train/loss=34.40]
Epoch 0: |          | 630/? [03:54<00:00,  2.69it/s, train/loss=27.80]
Epoch 0: |          | 631/? [03:54<00:00,  2.69it/s, train/loss=27.80]
Epoch 0: |          | 631/? [03:54<00:00,  2.69it/s, train/loss=13.00]
Epoch 0: |          | 632/? [03:54<00:00,  2.69it/s, train/loss=13.00]
Epoch 0: |          | 632/? [03:54<00:00,  2.69it/s, train/loss=16.80]
Epoch 0: |          | 633/? [03:55<00:00,  2.69it/s, train/loss=16.80]
Epoch 0: |          | 633/? [03:55<00:00,  2.69it/s, train/loss=47.30]
Epoch 0: |          | 634/? [03:55<00:00,  2.69it/s, train/loss=47.30]
Epoch 0: |          | 634/? [03:55<00:00,  2.69it/s, train/loss=24.20]
Epoch 0: |          | 635/? [03:55<00:00,  2.69it/s, train/loss=24.20]
Epoch 0: |          | 635/? [03:55<00:00,  2.69it/s, train/loss=7.330]
Epoch 0: |          | 636/? [03:56<00:00,  2.69it/s, train/loss=7.330]
Epoch 0: |          | 636/? [03:56<00:00,  2.69it/s, train/loss=14.50]
Epoch 0: |          | 637/? [03:56<00:00,  2.69it/s, train/loss=14.50]
Epoch 0: |          | 637/? [03:56<00:00,  2.69it/s, train/loss=28.80]
Epoch 0: |          | 638/? [03:56<00:00,  2.69it/s, train/loss=28.80]
Epoch 0: |          | 638/? [03:56<00:00,  2.69it/s, train/loss=24.00]
Epoch 0: |          | 639/? [03:57<00:00,  2.69it/s, train/loss=24.00]
Epoch 0: |          | 639/? [03:57<00:00,  2.69it/s, train/loss=7.980]
Epoch 0: |          | 640/? [03:57<00:00,  2.69it/s, train/loss=7.980]
Epoch 0: |          | 640/? [03:57<00:00,  2.69it/s, train/loss=46.90]
Epoch 0: |          | 641/? [03:57<00:00,  2.69it/s, train/loss=46.90]
Epoch 0: |          | 641/? [03:57<00:00,  2.69it/s, train/loss=21.50]
Epoch 0: |          | 642/? [03:58<00:00,  2.70it/s, train/loss=21.50]
Epoch 0: |          | 642/? [03:58<00:00,  2.70it/s, train/loss=40.10]
Epoch 0: |          | 643/? [03:58<00:00,  2.70it/s, train/loss=40.10]
Epoch 0: |          | 643/? [03:58<00:00,  2.70it/s, train/loss=41.30]
Epoch 0: |          | 644/? [03:58<00:00,  2.70it/s, train/loss=41.30]
Epoch 0: |          | 644/? [03:58<00:00,  2.70it/s, train/loss=48.10]
Epoch 0: |          | 645/? [03:59<00:00,  2.70it/s, train/loss=48.10]
Epoch 0: |          | 645/? [03:59<00:00,  2.70it/s, train/loss=21.50]
Epoch 0: |          | 646/? [03:59<00:00,  2.70it/s, train/loss=21.50]
Epoch 0: |          | 646/? [03:59<00:00,  2.70it/s, train/loss=24.60]
Epoch 0: |          | 647/? [03:59<00:00,  2.70it/s, train/loss=24.60]
Epoch 0: |          | 647/? [03:59<00:00,  2.70it/s, train/loss=63.90]
Epoch 0: |          | 648/? [04:00<00:00,  2.70it/s, train/loss=63.90]
Epoch 0: |          | 648/? [04:00<00:00,  2.70it/s, train/loss=20.90]
Epoch 0: |          | 649/? [04:00<00:00,  2.70it/s, train/loss=20.90]
Epoch 0: |          | 649/? [04:00<00:00,  2.70it/s, train/loss=55.00]
Epoch 0: |          | 650/? [04:00<00:00,  2.70it/s, train/loss=55.00]
Epoch 0: |          | 650/? [04:00<00:00,  2.70it/s, train/loss=25.60]
Epoch 0: |          | 651/? [04:01<00:00,  2.70it/s, train/loss=25.60]
Epoch 0: |          | 651/? [04:01<00:00,  2.70it/s, train/loss=17.00]
Epoch 0: |          | 652/? [04:01<00:00,  2.70it/s, train/loss=17.00]
Epoch 0: |          | 652/? [04:01<00:00,  2.70it/s, train/loss=19.20]
Epoch 0: |          | 653/? [04:01<00:00,  2.70it/s, train/loss=19.20]
Epoch 0: |          | 653/? [04:01<00:00,  2.70it/s, train/loss=20.70]
Epoch 0: |          | 654/? [04:02<00:00,  2.70it/s, train/loss=20.70]
Epoch 0: |          | 654/? [04:02<00:00,  2.70it/s, train/loss=31.90]
Epoch 0: |          | 655/? [04:02<00:00,  2.70it/s, train/loss=31.90]
Epoch 0: |          | 655/? [04:02<00:00,  2.70it/s, train/loss=13.60]
Epoch 0: |          | 656/? [04:03<00:00,  2.70it/s, train/loss=13.60]
Epoch 0: |          | 656/? [04:03<00:00,  2.70it/s, train/loss=25.40]
Epoch 0: |          | 657/? [04:03<00:00,  2.70it/s, train/loss=25.40]
Epoch 0: |          | 657/? [04:03<00:00,  2.70it/s, train/loss=42.40]
Epoch 0: |          | 658/? [04:03<00:00,  2.70it/s, train/loss=42.40]
Epoch 0: |          | 658/? [04:03<00:00,  2.70it/s, train/loss=12.40]
Epoch 0: |          | 659/? [04:04<00:00,  2.70it/s, train/loss=12.40]
Epoch 0: |          | 659/? [04:04<00:00,  2.70it/s, train/loss=29.20]
Epoch 0: |          | 660/? [04:04<00:00,  2.70it/s, train/loss=29.20]
Epoch 0: |          | 660/? [04:04<00:00,  2.70it/s, train/loss=8.920]
Epoch 0: |          | 661/? [04:04<00:00,  2.70it/s, train/loss=8.920]
Epoch 0: |          | 661/? [04:04<00:00,  2.70it/s, train/loss=23.50]
Epoch 0: |          | 662/? [04:05<00:00,  2.70it/s, train/loss=23.50]
Epoch 0: |          | 662/? [04:05<00:00,  2.70it/s, train/loss=24.90]
Epoch 0: |          | 663/? [04:05<00:00,  2.70it/s, train/loss=24.90]
Epoch 0: |          | 663/? [04:05<00:00,  2.70it/s, train/loss=33.00]
Epoch 0: |          | 664/? [04:05<00:00,  2.70it/s, train/loss=33.00]
Epoch 0: |          | 664/? [04:05<00:00,  2.70it/s, train/loss=19.80]
Epoch 0: |          | 665/? [04:05<00:00,  2.70it/s, train/loss=19.80]
Epoch 0: |          | 665/? [04:05<00:00,  2.70it/s, train/loss=25.70]
Epoch 0: |          | 666/? [04:06<00:00,  2.70it/s, train/loss=25.70]
Epoch 0: |          | 666/? [04:06<00:00,  2.70it/s, train/loss=27.60]
Epoch 0: |          | 667/? [04:06<00:00,  2.70it/s, train/loss=27.60]
Epoch 0: |          | 667/? [04:06<00:00,  2.70it/s, train/loss=36.80]
Epoch 0: |          | 668/? [04:06<00:00,  2.70it/s, train/loss=36.80]
Epoch 0: |          | 668/? [04:06<00:00,  2.70it/s, train/loss=18.20]
Epoch 0: |          | 669/? [04:07<00:00,  2.71it/s, train/loss=18.20]
Epoch 0: |          | 669/? [04:07<00:00,  2.71it/s, train/loss=29.60]
Epoch 0: |          | 670/? [04:07<00:00,  2.71it/s, train/loss=29.60]
Epoch 0: |          | 670/? [04:07<00:00,  2.71it/s, train/loss=52.50]
Epoch 0: |          | 671/? [04:07<00:00,  2.71it/s, train/loss=52.50]
Epoch 0: |          | 671/? [04:07<00:00,  2.71it/s, train/loss=11.80]
Epoch 0: |          | 672/? [04:08<00:00,  2.71it/s, train/loss=11.80]
Epoch 0: |          | 672/? [04:08<00:00,  2.71it/s, train/loss=19.90]
Epoch 0: |          | 673/? [04:08<00:00,  2.71it/s, train/loss=19.90]
Epoch 0: |          | 673/? [04:08<00:00,  2.71it/s, train/loss=17.60]
Epoch 0: |          | 674/? [04:08<00:00,  2.71it/s, train/loss=17.60]
Epoch 0: |          | 674/? [04:08<00:00,  2.71it/s, train/loss=31.90]
Epoch 0: |          | 675/? [04:09<00:00,  2.71it/s, train/loss=31.90]
Epoch 0: |          | 675/? [04:09<00:00,  2.71it/s, train/loss=24.00]
Epoch 0: |          | 676/? [04:09<00:00,  2.71it/s, train/loss=24.00]
Epoch 0: |          | 676/? [04:09<00:00,  2.71it/s, train/loss=9.220]
Epoch 0: |          | 677/? [04:09<00:00,  2.71it/s, train/loss=9.220]
Epoch 0: |          | 677/? [04:09<00:00,  2.71it/s, train/loss=29.80]
Epoch 0: |          | 678/? [04:10<00:00,  2.71it/s, train/loss=29.80]
Epoch 0: |          | 678/? [04:10<00:00,  2.71it/s, train/loss=9.360]
Epoch 0: |          | 679/? [04:10<00:00,  2.71it/s, train/loss=9.360]
Epoch 0: |          | 679/? [04:10<00:00,  2.71it/s, train/loss=26.90]
Epoch 0: |          | 680/? [04:10<00:00,  2.71it/s, train/loss=26.90]
Epoch 0: |          | 680/? [04:10<00:00,  2.71it/s, train/loss=23.60]
Epoch 0: |          | 681/? [04:11<00:00,  2.71it/s, train/loss=23.60]
Epoch 0: |          | 681/? [04:11<00:00,  2.71it/s, train/loss=24.20]
Epoch 0: |          | 682/? [04:11<00:00,  2.71it/s, train/loss=24.20]
Epoch 0: |          | 682/? [04:11<00:00,  2.71it/s, train/loss=29.20]
Epoch 0: |          | 683/? [04:11<00:00,  2.71it/s, train/loss=29.20]
Epoch 0: |          | 683/? [04:11<00:00,  2.71it/s, train/loss=23.70]
Epoch 0: |          | 684/? [04:12<00:00,  2.71it/s, train/loss=23.70]
Epoch 0: |          | 684/? [04:12<00:00,  2.71it/s, train/loss=8.900]
Epoch 0: |          | 685/? [04:12<00:00,  2.71it/s, train/loss=8.900]
Epoch 0: |          | 685/? [04:12<00:00,  2.71it/s, train/loss=29.60]
Epoch 0: |          | 686/? [04:12<00:00,  2.71it/s, train/loss=29.60]
Epoch 0: |          | 686/? [04:12<00:00,  2.71it/s, train/loss=44.80]
Epoch 0: |          | 687/? [04:13<00:00,  2.71it/s, train/loss=44.80]
Epoch 0: |          | 687/? [04:13<00:00,  2.71it/s, train/loss=65.00]
Epoch 0: |          | 688/? [04:13<00:00,  2.71it/s, train/loss=65.00]
Epoch 0: |          | 688/? [04:13<00:00,  2.71it/s, train/loss=17.10]
Epoch 0: |          | 689/? [04:13<00:00,  2.71it/s, train/loss=17.10]
Epoch 0: |          | 689/? [04:13<00:00,  2.71it/s, train/loss=28.30]
Epoch 0: |          | 690/? [04:14<00:00,  2.71it/s, train/loss=28.30]
Epoch 0: |          | 690/? [04:14<00:00,  2.71it/s, train/loss=38.20]
Epoch 0: |          | 691/? [04:14<00:00,  2.72it/s, train/loss=38.20]
Epoch 0: |          | 691/? [04:14<00:00,  2.72it/s, train/loss=9.110]
Epoch 0: |          | 692/? [04:14<00:00,  2.72it/s, train/loss=9.110]
Epoch 0: |          | 692/? [04:14<00:00,  2.72it/s, train/loss=29.20]
Epoch 0: |          | 693/? [04:15<00:00,  2.72it/s, train/loss=29.20]
Epoch 0: |          | 693/? [04:15<00:00,  2.72it/s, train/loss=16.60]
Epoch 0: |          | 694/? [04:15<00:00,  2.72it/s, train/loss=16.60]
Epoch 0: |          | 694/? [04:15<00:00,  2.72it/s, train/loss=31.70]
Epoch 0: |          | 695/? [04:15<00:00,  2.72it/s, train/loss=31.70]
Epoch 0: |          | 695/? [04:15<00:00,  2.72it/s, train/loss=11.80]
Epoch 0: |          | 696/? [04:16<00:00,  2.72it/s, train/loss=11.80]
Epoch 0: |          | 696/? [04:16<00:00,  2.72it/s, train/loss=29.40]
Epoch 0: |          | 697/? [04:16<00:00,  2.72it/s, train/loss=29.40]
Epoch 0: |          | 697/? [04:16<00:00,  2.72it/s, train/loss=35.70]
Epoch 0: |          | 698/? [04:16<00:00,  2.72it/s, train/loss=35.70]
Epoch 0: |          | 698/? [04:16<00:00,  2.72it/s, train/loss=14.40]
Epoch 0: |          | 699/? [04:17<00:00,  2.72it/s, train/loss=14.40]
Epoch 0: |          | 699/? [04:17<00:00,  2.72it/s, train/loss=34.40]
Epoch 0: |          | 700/? [04:17<00:00,  2.72it/s, train/loss=34.40]
Epoch 0: |          | 700/? [04:17<00:00,  2.72it/s, train/loss=12.10]
Epoch 0: |          | 701/? [04:17<00:00,  2.72it/s, train/loss=12.10]
Epoch 0: |          | 701/? [04:17<00:00,  2.72it/s, train/loss=15.30]
Epoch 0: |          | 702/? [04:18<00:00,  2.72it/s, train/loss=15.30]
Epoch 0: |          | 702/? [04:18<00:00,  2.72it/s, train/loss=22.70]
Epoch 0: |          | 703/? [04:18<00:00,  2.72it/s, train/loss=22.70]
Epoch 0: |          | 703/? [04:18<00:00,  2.72it/s, train/loss=20.80]
Epoch 0: |          | 704/? [04:18<00:00,  2.72it/s, train/loss=20.80]
Epoch 0: |          | 704/? [04:18<00:00,  2.72it/s, train/loss=7.570]
Epoch 0: |          | 705/? [04:19<00:00,  2.72it/s, train/loss=7.570]
Epoch 0: |          | 705/? [04:19<00:00,  2.72it/s, train/loss=21.90]
Epoch 0: |          | 706/? [04:19<00:00,  2.72it/s, train/loss=21.90]
Epoch 0: |          | 706/? [04:19<00:00,  2.72it/s, train/loss=19.50]
Epoch 0: |          | 707/? [04:19<00:00,  2.72it/s, train/loss=19.50]
Epoch 0: |          | 707/? [04:19<00:00,  2.72it/s, train/loss=11.60]
Epoch 0: |          | 708/? [04:20<00:00,  2.72it/s, train/loss=11.60]
Epoch 0: |          | 708/? [04:20<00:00,  2.72it/s, train/loss=13.30]
Epoch 0: |          | 709/? [04:20<00:00,  2.72it/s, train/loss=13.30]
Epoch 0: |          | 709/? [04:20<00:00,  2.72it/s, train/loss=17.80]
Epoch 0: |          | 710/? [04:20<00:00,  2.72it/s, train/loss=17.80]
Epoch 0: |          | 710/? [04:20<00:00,  2.72it/s, train/loss=19.00]
Epoch 0: |          | 711/? [04:21<00:00,  2.72it/s, train/loss=19.00]
Epoch 0: |          | 711/? [04:21<00:00,  2.72it/s, train/loss=21.70]
Epoch 0: |          | 712/? [04:21<00:00,  2.72it/s, train/loss=21.70]
Epoch 0: |          | 712/? [04:21<00:00,  2.72it/s, train/loss=35.30]
Epoch 0: |          | 713/? [04:21<00:00,  2.72it/s, train/loss=35.30]
Epoch 0: |          | 713/? [04:21<00:00,  2.72it/s, train/loss=21.40]
Epoch 0: |          | 714/? [04:22<00:00,  2.72it/s, train/loss=21.40]
Epoch 0: |          | 714/? [04:22<00:00,  2.72it/s, train/loss=34.50]
Epoch 0: |          | 715/? [04:22<00:00,  2.72it/s, train/loss=34.50]
Epoch 0: |          | 715/? [04:22<00:00,  2.72it/s, train/loss=26.30]
Epoch 0: |          | 716/? [04:22<00:00,  2.73it/s, train/loss=26.30]
Epoch 0: |          | 716/? [04:22<00:00,  2.73it/s, train/loss=17.80]
Epoch 0: |          | 717/? [04:23<00:00,  2.73it/s, train/loss=17.80]
Epoch 0: |          | 717/? [04:23<00:00,  2.73it/s, train/loss=70.40]
Epoch 0: |          | 718/? [04:23<00:00,  2.73it/s, train/loss=70.40]
Epoch 0: |          | 718/? [04:23<00:00,  2.73it/s, train/loss=27.50]
Epoch 0: |          | 719/? [04:23<00:00,  2.73it/s, train/loss=27.50]
Epoch 0: |          | 719/? [04:23<00:00,  2.73it/s, train/loss=17.10]
Epoch 0: |          | 720/? [04:24<00:00,  2.73it/s, train/loss=17.10]
Epoch 0: |          | 720/? [04:24<00:00,  2.73it/s, train/loss=13.80]
Epoch 0: |          | 721/? [04:24<00:00,  2.73it/s, train/loss=13.80]
Epoch 0: |          | 721/? [04:24<00:00,  2.73it/s, train/loss=39.50]
Epoch 0: |          | 722/? [04:24<00:00,  2.73it/s, train/loss=39.50]
Epoch 0: |          | 722/? [04:24<00:00,  2.73it/s, train/loss=23.60]
Epoch 0: |          | 723/? [04:25<00:00,  2.73it/s, train/loss=23.60]
Epoch 0: |          | 723/? [04:25<00:00,  2.73it/s, train/loss=37.80]
Epoch 0: |          | 724/? [04:25<00:00,  2.73it/s, train/loss=37.80]
Epoch 0: |          | 724/? [04:25<00:00,  2.73it/s, train/loss=18.90]
Epoch 0: |          | 725/? [04:25<00:00,  2.73it/s, train/loss=18.90]
Epoch 0: |          | 725/? [04:25<00:00,  2.73it/s, train/loss=31.20]
Epoch 0: |          | 726/? [04:25<00:00,  2.73it/s, train/loss=31.20]
Epoch 0: |          | 726/? [04:25<00:00,  2.73it/s, train/loss=23.20]
Epoch 0: |          | 727/? [04:26<00:00,  2.73it/s, train/loss=23.20]
Epoch 0: |          | 727/? [04:26<00:00,  2.73it/s, train/loss=20.90]
Epoch 0: |          | 728/? [04:26<00:00,  2.73it/s, train/loss=20.90]
Epoch 0: |          | 728/? [04:26<00:00,  2.73it/s, train/loss=24.60]
Epoch 0: |          | 729/? [04:26<00:00,  2.73it/s, train/loss=24.60]
Epoch 0: |          | 729/? [04:26<00:00,  2.73it/s, train/loss=16.90]
Epoch 0: |          | 730/? [04:27<00:00,  2.73it/s, train/loss=16.90]
Epoch 0: |          | 730/? [04:27<00:00,  2.73it/s, train/loss=14.70]
Epoch 0: |          | 731/? [04:27<00:00,  2.73it/s, train/loss=14.70]
Epoch 0: |          | 731/? [04:27<00:00,  2.73it/s, train/loss=7.040]
Epoch 0: |          | 732/? [04:27<00:00,  2.73it/s, train/loss=7.040]
Epoch 0: |          | 732/? [04:27<00:00,  2.73it/s, train/loss=16.10]
Epoch 0: |          | 733/? [04:28<00:00,  2.73it/s, train/loss=16.10]
Epoch 0: |          | 733/? [04:28<00:00,  2.73it/s, train/loss=39.30]
Epoch 0: |          | 734/? [04:28<00:00,  2.73it/s, train/loss=39.30]
Epoch 0: |          | 734/? [04:28<00:00,  2.73it/s, train/loss=26.50]
Epoch 0: |          | 735/? [04:28<00:00,  2.73it/s, train/loss=26.50]
Epoch 0: |          | 735/? [04:28<00:00,  2.73it/s, train/loss=14.00]
Epoch 0: |          | 736/? [04:29<00:00,  2.73it/s, train/loss=14.00]
Epoch 0: |          | 736/? [04:29<00:00,  2.73it/s, train/loss=18.90]
Epoch 0: |          | 737/? [04:29<00:00,  2.73it/s, train/loss=18.90]
Epoch 0: |          | 737/? [04:29<00:00,  2.73it/s, train/loss=32.80]
Epoch 0: |          | 738/? [04:29<00:00,  2.73it/s, train/loss=32.80]
Epoch 0: |          | 738/? [04:29<00:00,  2.73it/s, train/loss=22.50]
Epoch 0: |          | 739/? [04:30<00:00,  2.73it/s, train/loss=22.50]
Epoch 0: |          | 739/? [04:30<00:00,  2.73it/s, train/loss=19.90]
Epoch 0: |          | 740/? [04:30<00:00,  2.74it/s, train/loss=19.90]
Epoch 0: |          | 740/? [04:30<00:00,  2.74it/s, train/loss=13.80]
Epoch 0: |          | 741/? [04:30<00:00,  2.74it/s, train/loss=13.80]
Epoch 0: |          | 741/? [04:30<00:00,  2.74it/s, train/loss=46.20]
Epoch 0: |          | 742/? [04:31<00:00,  2.74it/s, train/loss=46.20]
Epoch 0: |          | 742/? [04:31<00:00,  2.74it/s, train/loss=23.10]
Epoch 0: |          | 743/? [04:31<00:00,  2.74it/s, train/loss=23.10]
Epoch 0: |          | 743/? [04:31<00:00,  2.74it/s, train/loss=35.30]
Epoch 0: |          | 744/? [04:31<00:00,  2.74it/s, train/loss=35.30]
Epoch 0: |          | 744/? [04:31<00:00,  2.74it/s, train/loss=17.30]
Epoch 0: |          | 745/? [04:32<00:00,  2.74it/s, train/loss=17.30]
Epoch 0: |          | 745/? [04:32<00:00,  2.74it/s, train/loss=35.60]
Epoch 0: |          | 746/? [04:32<00:00,  2.74it/s, train/loss=35.60]
Epoch 0: |          | 746/? [04:32<00:00,  2.74it/s, train/loss=30.30]
Epoch 0: |          | 747/? [04:32<00:00,  2.74it/s, train/loss=30.30]
Epoch 0: |          | 747/? [04:32<00:00,  2.74it/s, train/loss=9.280]
Epoch 0: |          | 748/? [04:33<00:00,  2.74it/s, train/loss=9.280]
Epoch 0: |          | 748/? [04:33<00:00,  2.74it/s, train/loss=35.70]
Epoch 0: |          | 749/? [04:33<00:00,  2.74it/s, train/loss=35.70]
Epoch 0: |          | 749/? [04:33<00:00,  2.74it/s, train/loss=30.50]
Epoch 0: |          | 750/? [04:33<00:00,  2.74it/s, train/loss=30.50]
Epoch 0: |          | 750/? [04:33<00:00,  2.74it/s, train/loss=28.80]
Epoch 0: |          | 751/? [04:34<00:00,  2.74it/s, train/loss=28.80]
Epoch 0: |          | 751/? [04:34<00:00,  2.74it/s, train/loss=23.70]
Epoch 0: |          | 752/? [04:34<00:00,  2.74it/s, train/loss=23.70]
Epoch 0: |          | 752/? [04:34<00:00,  2.74it/s, train/loss=22.00]
Epoch 0: |          | 753/? [04:34<00:00,  2.74it/s, train/loss=22.00]
Epoch 0: |          | 753/? [04:34<00:00,  2.74it/s, train/loss=16.70]
Epoch 0: |          | 754/? [04:35<00:00,  2.74it/s, train/loss=16.70]
Epoch 0: |          | 754/? [04:35<00:00,  2.74it/s, train/loss=8.490]
Epoch 0: |          | 755/? [04:35<00:00,  2.74it/s, train/loss=8.490]
Epoch 0: |          | 755/? [04:35<00:00,  2.74it/s, train/loss=12.40]
Epoch 0: |          | 756/? [04:35<00:00,  2.74it/s, train/loss=12.40]
Epoch 0: |          | 756/? [04:35<00:00,  2.74it/s, train/loss=11.90]
Epoch 0: |          | 757/? [04:36<00:00,  2.74it/s, train/loss=11.90]
Epoch 0: |          | 757/? [04:36<00:00,  2.74it/s, train/loss=15.30]
Epoch 0: |          | 758/? [04:36<00:00,  2.74it/s, train/loss=15.30]
Epoch 0: |          | 758/? [04:36<00:00,  2.74it/s, train/loss=18.30]
Epoch 0: |          | 759/? [04:36<00:00,  2.74it/s, train/loss=18.30]
Epoch 0: |          | 759/? [04:36<00:00,  2.74it/s, train/loss=15.90]
Epoch 0: |          | 760/? [04:37<00:00,  2.74it/s, train/loss=15.90]
Epoch 0: |          | 760/? [04:37<00:00,  2.74it/s, train/loss=30.70]
Epoch 0: |          | 761/? [04:37<00:00,  2.74it/s, train/loss=30.70]
Epoch 0: |          | 761/? [04:37<00:00,  2.74it/s, train/loss=37.50]
Epoch 0: |          | 762/? [04:37<00:00,  2.74it/s, train/loss=37.50]
Epoch 0: |          | 762/? [04:37<00:00,  2.74it/s, train/loss=24.00]
Epoch 0: |          | 763/? [04:38<00:00,  2.74it/s, train/loss=24.00]
Epoch 0: |          | 763/? [04:38<00:00,  2.74it/s, train/loss=23.80]
Epoch 0: |          | 764/? [04:38<00:00,  2.74it/s, train/loss=23.80]
Epoch 0: |          | 764/? [04:38<00:00,  2.74it/s, train/loss=13.40]
Epoch 0: |          | 765/? [04:38<00:00,  2.74it/s, train/loss=13.40]
Epoch 0: |          | 765/? [04:38<00:00,  2.74it/s, train/loss=41.50]
Epoch 0: |          | 766/? [04:39<00:00,  2.75it/s, train/loss=41.50]
Epoch 0: |          | 766/? [04:39<00:00,  2.75it/s, train/loss=29.70]
Epoch 0: |          | 767/? [04:39<00:00,  2.75it/s, train/loss=29.70]
Epoch 0: |          | 767/? [04:39<00:00,  2.75it/s, train/loss=16.90]
Epoch 0: |          | 768/? [04:39<00:00,  2.75it/s, train/loss=16.90]
Epoch 0: |          | 768/? [04:39<00:00,  2.75it/s, train/loss=31.50]
Epoch 0: |          | 769/? [04:40<00:00,  2.75it/s, train/loss=31.50]
Epoch 0: |          | 769/? [04:40<00:00,  2.75it/s, train/loss=29.30]
Epoch 0: |          | 770/? [04:40<00:00,  2.75it/s, train/loss=29.30]
Epoch 0: |          | 770/? [04:40<00:00,  2.75it/s, train/loss=23.60]
Epoch 0: |          | 771/? [04:40<00:00,  2.75it/s, train/loss=23.60]
Epoch 0: |          | 771/? [04:40<00:00,  2.75it/s, train/loss=17.80]
Epoch 0: |          | 772/? [04:40<00:00,  2.75it/s, train/loss=17.80]
Epoch 0: |          | 772/? [04:40<00:00,  2.75it/s, train/loss=11.00]
Epoch 0: |          | 773/? [04:41<00:00,  2.75it/s, train/loss=11.00]
Epoch 0: |          | 773/? [04:41<00:00,  2.75it/s, train/loss=34.10]
Epoch 0: |          | 774/? [04:41<00:00,  2.75it/s, train/loss=34.10]
Epoch 0: |          | 774/? [04:41<00:00,  2.75it/s, train/loss=15.80]
Epoch 0: |          | 775/? [04:41<00:00,  2.75it/s, train/loss=15.80]
Epoch 0: |          | 775/? [04:41<00:00,  2.75it/s, train/loss=8.520]
Epoch 0: |          | 776/? [04:42<00:00,  2.75it/s, train/loss=8.520]
Epoch 0: |          | 776/? [04:42<00:00,  2.75it/s, train/loss=6.730]
Epoch 0: |          | 777/? [04:42<00:00,  2.75it/s, train/loss=6.730]
Epoch 0: |          | 777/? [04:42<00:00,  2.75it/s, train/loss=16.90]
Epoch 0: |          | 778/? [04:42<00:00,  2.75it/s, train/loss=16.90]
Epoch 0: |          | 778/? [04:42<00:00,  2.75it/s, train/loss=19.80]
Epoch 0: |          | 779/? [04:43<00:00,  2.75it/s, train/loss=19.80]
Epoch 0: |          | 779/? [04:43<00:00,  2.75it/s, train/loss=53.00]
Epoch 0: |          | 780/? [04:43<00:00,  2.75it/s, train/loss=53.00]
Epoch 0: |          | 780/? [04:43<00:00,  2.75it/s, train/loss=22.80]
Epoch 0: |          | 781/? [04:44<00:00,  2.75it/s, train/loss=22.80]
Epoch 0: |          | 781/? [04:44<00:00,  2.75it/s, train/loss=22.60]
Epoch 0: |          | 782/? [04:44<00:00,  2.75it/s, train/loss=22.60]
Epoch 0: |          | 782/? [04:44<00:00,  2.75it/s, train/loss=12.40]
Epoch 0: |          | 783/? [04:44<00:00,  2.75it/s, train/loss=12.40]
Epoch 0: |          | 783/? [04:44<00:00,  2.75it/s, train/loss=27.50]
Epoch 0: |          | 784/? [04:45<00:00,  2.75it/s, train/loss=27.50]
Epoch 0: |          | 784/? [04:45<00:00,  2.75it/s, train/loss=32.30]
Epoch 0: |          | 785/? [04:45<00:00,  2.75it/s, train/loss=32.30]
Epoch 0: |          | 785/? [04:45<00:00,  2.75it/s, train/loss=36.80]
Epoch 0: |          | 786/? [04:45<00:00,  2.75it/s, train/loss=36.80]
Epoch 0: |          | 786/? [04:45<00:00,  2.75it/s, train/loss=21.70]
Epoch 0: |          | 787/? [04:46<00:00,  2.75it/s, train/loss=21.70]
Epoch 0: |          | 787/? [04:46<00:00,  2.75it/s, train/loss=38.40]
Epoch 0: |          | 788/? [04:46<00:00,  2.75it/s, train/loss=38.40]
Epoch 0: |          | 788/? [04:46<00:00,  2.75it/s, train/loss=37.90]
Epoch 0: |          | 789/? [04:46<00:00,  2.75it/s, train/loss=37.90]
Epoch 0: |          | 789/? [04:46<00:00,  2.75it/s, train/loss=36.00]
Epoch 0: |          | 790/? [04:47<00:00,  2.75it/s, train/loss=36.00]
Epoch 0: |          | 790/? [04:47<00:00,  2.75it/s, train/loss=20.20]
Epoch 0: |          | 791/? [04:47<00:00,  2.75it/s, train/loss=20.20]
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`Trainer.fit` stopped: `max_steps=800` reached.
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[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
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Test results saved to outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save
Running step 4: texture refinement
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-texture',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-texture',
'resume': None,
'seed': 0,
'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-135357',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0},
'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357',
'trial_name': 'replicate_user@20240222-135357',
'use_timestamp': True}
Initializing geometry from a given checkpoint ...
Loading Stable Diffusion ...
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Loaded Stable Diffusion!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
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loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name       | Type                       | Params
----------------------------------------------------------
0 | geometry   | TetrahedraSDFGrid          | 12.6 M
1 | material   | NoMaterial                 | 0
2 | background | SolidColorBackground       | 0
3 | renderer   | NVDiffRasterizer           | 0
4 | guidance   | StableDiffusionBSDGuidance | 870 M
----------------------------------------------------------
882 M     Trainable params
0         Non-trainable params
882 M     Total params
3,530.663 Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save
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/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/diffusers/models/attention_processor.py:1746: FutureWarning: `LoRAAttnProcessor` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`
deprecate(
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Epoch 0: |          | 68/? [00:21<00:00,  3.14it/s, train/loss=12.90]
Epoch 0: |          | 68/? [00:21<00:00,  3.14it/s, train/loss=2.660]
Epoch 0: |          | 69/? [00:21<00:00,  3.17it/s, train/loss=2.660]
Epoch 0: |          | 69/? [00:21<00:00,  3.17it/s, train/loss=12.70]
Epoch 0: |          | 70/? [00:22<00:00,  3.16it/s, train/loss=12.70]
Epoch 0: |          | 70/? [00:22<00:00,  3.16it/s, train/loss=3.440]
Epoch 0: |          | 71/? [00:23<00:00,  3.09it/s, train/loss=3.440]
Epoch 0: |          | 71/? [00:23<00:00,  3.08it/s, train/loss=0.751]
Epoch 0: |          | 72/? [00:23<00:00,  3.09it/s, train/loss=0.751]
Epoch 0: |          | 72/? [00:23<00:00,  3.08it/s, train/loss=2.930]
Epoch 0: |          | 73/? [00:23<00:00,  3.11it/s, train/loss=2.930]
Epoch 0: |          | 73/? [00:23<00:00,  3.11it/s, train/loss=12.40]
Epoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=12.40]
Epoch 0: |          | 74/? [00:23<00:00,  3.10it/s, train/loss=2.180]
Epoch 0: |          | 75/? [00:23<00:00,  3.14it/s, train/loss=2.180]
Epoch 0: |          | 75/? [00:23<00:00,  3.14it/s, train/loss=12.20]
Epoch 0: |          | 76/? [00:24<00:00,  3.13it/s, train/loss=12.20]
Epoch 0: |          | 76/? [00:24<00:00,  3.13it/s, train/loss=2.370]
Epoch 0: |          | 77/? [00:24<00:00,  3.17it/s, train/loss=2.370]
Epoch 0: |          | 77/? [00:24<00:00,  3.17it/s, train/loss=12.00]
Epoch 0: |          | 78/? [00:24<00:00,  3.16it/s, train/loss=12.00]
Epoch 0: |          | 78/? [00:24<00:00,  3.16it/s, train/loss=2.250]
Epoch 0: |          | 79/? [00:24<00:00,  3.19it/s, train/loss=2.250]
Epoch 0: |          | 79/? [00:24<00:00,  3.19it/s, train/loss=11.80]
Epoch 0: |          | 80/? [00:25<00:00,  3.18it/s, train/loss=11.80]
Epoch 0: |          | 80/? [00:25<00:00,  3.18it/s, train/loss=2.530]
Epoch 0: |          | 81/? [00:26<00:00,  3.11it/s, train/loss=2.530]
Epoch 0: |          | 81/? [00:26<00:00,  3.10it/s, train/loss=2.030]
Epoch 0: |          | 82/? [00:26<00:00,  3.11it/s, train/loss=2.030]
Epoch 0: |          | 82/? [00:26<00:00,  3.10it/s, train/loss=0.990]
Epoch 0: |          | 83/? [00:26<00:00,  3.14it/s, train/loss=0.990]
Epoch 0: |          | 83/? [00:26<00:00,  3.13it/s, train/loss=11.50]
Epoch 0: |          | 84/? [00:26<00:00,  3.13it/s, train/loss=11.50]
Epoch 0: |          | 84/? [00:26<00:00,  3.13it/s, train/loss=2.540]
Epoch 0: |          | 85/? [00:26<00:00,  3.16it/s, train/loss=2.540]
Epoch 0: |          | 85/? [00:26<00:00,  3.16it/s, train/loss=11.40]
Epoch 0: |          | 86/? [00:27<00:00,  3.15it/s, train/loss=11.40]
Epoch 0: |          | 86/? [00:27<00:00,  3.15it/s, train/loss=2.830]
Epoch 0: |          | 87/? [00:27<00:00,  3.18it/s, train/loss=2.830]
Epoch 0: |          | 87/? [00:27<00:00,  3.18it/s, train/loss=11.20]
Epoch 0: |          | 88/? [00:27<00:00,  3.17it/s, train/loss=11.20]
Epoch 0: |          | 88/? [00:27<00:00,  3.17it/s, train/loss=1.430]
Epoch 0: |          | 89/? [00:27<00:00,  3.20it/s, train/loss=1.430]
Epoch 0: |          | 89/? [00:27<00:00,  3.20it/s, train/loss=11.10]
Epoch 0: |          | 90/? [00:28<00:00,  3.19it/s, train/loss=11.10]
Epoch 0: |          | 90/? [00:28<00:00,  3.19it/s, train/loss=1.880]
Epoch 0: |          | 91/? [00:29<00:00,  3.13it/s, train/loss=1.880]
Epoch 0: |          | 91/? [00:29<00:00,  3.12it/s, train/loss=1.450]
Epoch 0: |          | 92/? [00:29<00:00,  3.13it/s, train/loss=1.450]
Epoch 0: |          | 92/? [00:29<00:00,  3.12it/s, train/loss=1.310]
Epoch 0: |          | 93/? [00:29<00:00,  3.15it/s, train/loss=1.310]
Epoch 0: |          | 93/? [00:29<00:00,  3.15it/s, train/loss=10.80]
Epoch 0: |          | 94/? [00:29<00:00,  3.14it/s, train/loss=10.80]
Epoch 0: |          | 94/? [00:29<00:00,  3.14it/s, train/loss=0.665]
Epoch 0: |          | 95/? [00:29<00:00,  3.17it/s, train/loss=0.665]
Epoch 0: |          | 95/? [00:29<00:00,  3.17it/s, train/loss=10.70]
Epoch 0: |          | 96/? [00:30<00:00,  3.16it/s, train/loss=10.70]
Epoch 0: |          | 96/? [00:30<00:00,  3.16it/s, train/loss=2.050]
Epoch 0: |          | 97/? [00:30<00:00,  3.19it/s, train/loss=2.050]
Epoch 0: |          | 97/? [00:30<00:00,  3.19it/s, train/loss=10.50]
Epoch 0: |          | 98/? [00:30<00:00,  3.18it/s, train/loss=10.50]
Epoch 0: |          | 98/? [00:30<00:00,  3.18it/s, train/loss=2.290]
Epoch 0: |          | 99/? [00:30<00:00,  3.21it/s, train/loss=2.290]
Epoch 0: |          | 99/? [00:30<00:00,  3.21it/s, train/loss=10.40]
Epoch 0: |          | 100/? [00:31<00:00,  3.20it/s, train/loss=10.40]
Epoch 0: |          | 100/? [00:31<00:00,  3.20it/s, train/loss=1.910]
Epoch 0: |          | 101/? [00:32<00:00,  3.15it/s, train/loss=1.910]
Epoch 0: |          | 101/? [00:32<00:00,  3.14it/s, train/loss=1.090]
Epoch 0: |          | 102/? [00:32<00:00,  3.15it/s, train/loss=1.090]
Epoch 0: |          | 102/? [00:32<00:00,  3.14it/s, train/loss=2.970]
Epoch 0: |          | 103/? [00:32<00:00,  3.17it/s, train/loss=2.970]
Epoch 0: |          | 103/? [00:32<00:00,  3.17it/s, train/loss=10.10]
Epoch 0: |          | 104/? [00:32<00:00,  3.16it/s, train/loss=10.10]
Epoch 0: |          | 104/? [00:32<00:00,  3.16it/s, train/loss=2.400]
Epoch 0: |          | 105/? [00:32<00:00,  3.18it/s, train/loss=2.400]
Epoch 0: |          | 105/? [00:32<00:00,  3.18it/s, train/loss=10.00]
Epoch 0: |          | 106/? [00:33<00:00,  3.18it/s, train/loss=10.00]
Epoch 0: |          | 106/? [00:33<00:00,  3.18it/s, train/loss=2.730]
Epoch 0: |          | 107/? [00:33<00:00,  3.20it/s, train/loss=2.730]
Epoch 0: |          | 107/? [00:33<00:00,  3.20it/s, train/loss=9.900]
Epoch 0: |          | 108/? [00:33<00:00,  3.20it/s, train/loss=9.900]
Epoch 0: |          | 108/? [00:33<00:00,  3.20it/s, train/loss=2.430]
Epoch 0: |          | 109/? [00:33<00:00,  3.22it/s, train/loss=2.430]
Epoch 0: |          | 109/? [00:33<00:00,  3.22it/s, train/loss=9.770]
Epoch 0: |          | 110/? [00:34<00:00,  3.21it/s, train/loss=9.770]
Epoch 0: |          | 110/? [00:34<00:00,  3.21it/s, train/loss=1.070]
Epoch 0: |          | 111/? [00:35<00:00,  3.16it/s, train/loss=1.070]
Epoch 0: |          | 111/? [00:35<00:00,  3.15it/s, train/loss=2.210]
Epoch 0: |          | 112/? [00:35<00:00,  3.16it/s, train/loss=2.210]
Epoch 0: |          | 112/? [00:35<00:00,  3.15it/s, train/loss=0.631]
Epoch 0: |          | 113/? [00:35<00:00,  3.18it/s, train/loss=0.631]
Epoch 0: |          | 113/? [00:35<00:00,  3.18it/s, train/loss=9.550]
Epoch 0: |          | 114/? [00:35<00:00,  3.17it/s, train/loss=9.550]
Epoch 0: |          | 114/? [00:35<00:00,  3.17it/s, train/loss=1.270]
Epoch 0: |          | 115/? [00:36<00:00,  3.19it/s, train/loss=1.270]
Epoch 0: |          | 115/? [00:36<00:00,  3.19it/s, train/loss=9.450]
Epoch 0: |          | 116/? [00:36<00:00,  3.19it/s, train/loss=9.450]
Epoch 0: |          | 116/? [00:36<00:00,  3.19it/s, train/loss=1.790]
Epoch 0: |          | 117/? [00:36<00:00,  3.21it/s, train/loss=1.790]
Epoch 0: |          | 117/? [00:36<00:00,  3.21it/s, train/loss=9.340]
Epoch 0: |          | 118/? [00:36<00:00,  3.20it/s, train/loss=9.340]
Epoch 0: |          | 118/? [00:36<00:00,  3.20it/s, train/loss=2.310]
Epoch 0: |          | 119/? [00:36<00:00,  3.23it/s, train/loss=2.310]
Epoch 0: |          | 119/? [00:36<00:00,  3.23it/s, train/loss=9.220]
Epoch 0: |          | 120/? [00:37<00:00,  3.22it/s, train/loss=9.220]
Epoch 0: |          | 120/? [00:37<00:00,  3.22it/s, train/loss=2.210]
Epoch 0: |          | 121/? [00:38<00:00,  3.17it/s, train/loss=2.210]
Epoch 0: |          | 121/? [00:38<00:00,  3.17it/s, train/loss=6.350]
Epoch 0: |          | 122/? [00:38<00:00,  3.17it/s, train/loss=6.350]
Epoch 0: |          | 122/? [00:38<00:00,  3.16it/s, train/loss=2.140]
Epoch 0: |          | 123/? [00:38<00:00,  3.19it/s, train/loss=2.140]
Epoch 0: |          | 123/? [00:38<00:00,  3.19it/s, train/loss=9.020]
Epoch 0: |          | 124/? [00:38<00:00,  3.18it/s, train/loss=9.020]
Epoch 0: |          | 124/? [00:38<00:00,  3.18it/s, train/loss=2.490]
Epoch 0: |          | 125/? [00:39<00:00,  3.20it/s, train/loss=2.490]
Epoch 0: |          | 125/? [00:39<00:00,  3.20it/s, train/loss=8.930]
Epoch 0: |          | 126/? [00:39<00:00,  3.20it/s, train/loss=8.930]
Epoch 0: |          | 126/? [00:39<00:00,  3.20it/s, train/loss=0.836]
Epoch 0: |          | 127/? [00:39<00:00,  3.22it/s, train/loss=0.836]
Epoch 0: |          | 127/? [00:39<00:00,  3.22it/s, train/loss=8.830]
Epoch 0: |          | 128/? [00:39<00:00,  3.21it/s, train/loss=8.830]
Epoch 0: |          | 128/? [00:39<00:00,  3.21it/s, train/loss=1.060]
Epoch 0: |          | 129/? [00:39<00:00,  3.23it/s, train/loss=1.060]
Epoch 0: |          | 129/? [00:39<00:00,  3.23it/s, train/loss=8.730]
Epoch 0: |          | 130/? [00:40<00:00,  3.23it/s, train/loss=8.730]
Epoch 0: |          | 130/? [00:40<00:00,  3.23it/s, train/loss=2.120]
Epoch 0: |          | 131/? [00:41<00:00,  3.18it/s, train/loss=2.120]
Epoch 0: |          | 131/? [00:41<00:00,  3.18it/s, train/loss=4.420]
Epoch 0: |          | 132/? [00:41<00:00,  3.18it/s, train/loss=4.420]
Epoch 0: |          | 132/? [00:41<00:00,  3.17it/s, train/loss=2.920]
Epoch 0: |          | 133/? [00:41<00:00,  3.19it/s, train/loss=2.920]
Epoch 0: |          | 133/? [00:41<00:00,  3.19it/s, train/loss=8.560]
Epoch 0: |          | 134/? [00:42<00:00,  3.19it/s, train/loss=8.560]
Epoch 0: |          | 134/? [00:42<00:00,  3.19it/s, train/loss=1.740]
Epoch 0: |          | 135/? [00:42<00:00,  3.21it/s, train/loss=1.740]
Epoch 0: |          | 135/? [00:42<00:00,  3.21it/s, train/loss=8.480]
Epoch 0: |          | 136/? [00:42<00:00,  3.20it/s, train/loss=8.480]
Epoch 0: |          | 136/? [00:42<00:00,  3.20it/s, train/loss=5.630]
Epoch 0: |          | 137/? [00:42<00:00,  3.22it/s, train/loss=5.630]
Epoch 0: |          | 137/? [00:42<00:00,  3.22it/s, train/loss=8.390]
Epoch 0: |          | 138/? [00:42<00:00,  3.22it/s, train/loss=8.390]
Epoch 0: |          | 138/? [00:42<00:00,  3.22it/s, train/loss=2.640]
Epoch 0: |          | 139/? [00:42<00:00,  3.24it/s, train/loss=2.640]
Epoch 0: |          | 139/? [00:42<00:00,  3.24it/s, train/loss=8.310]
Epoch 0: |          | 140/? [00:43<00:00,  3.23it/s, train/loss=8.310]
Epoch 0: |          | 140/? [00:43<00:00,  3.23it/s, train/loss=1.650]
Epoch 0: |          | 141/? [00:44<00:00,  3.19it/s, train/loss=1.650]
Epoch 0: |          | 141/? [00:44<00:00,  3.18it/s, train/loss=1.890]
Epoch 0: |          | 142/? [00:44<00:00,  3.19it/s, train/loss=1.890]
Epoch 0: |          | 142/? [00:44<00:00,  3.18it/s, train/loss=1.700]
Epoch 0: |          | 143/? [00:44<00:00,  3.20it/s, train/loss=1.700]
Epoch 0: |          | 143/? [00:44<00:00,  3.20it/s, train/loss=8.180]
Epoch 0: |          | 144/? [00:45<00:00,  3.20it/s, train/loss=8.180]
Epoch 0: |          | 144/? [00:45<00:00,  3.20it/s, train/loss=2.450]
Epoch 0: |          | 145/? [00:45<00:00,  3.21it/s, train/loss=2.450]
Epoch 0: |          | 145/? [00:45<00:00,  3.21it/s, train/loss=8.110]
Epoch 0: |          | 146/? [00:45<00:00,  3.21it/s, train/loss=8.110]
Epoch 0: |          | 146/? [00:45<00:00,  3.21it/s, train/loss=1.610]
Epoch 0: |          | 147/? [00:45<00:00,  3.22it/s, train/loss=1.610]
Epoch 0: |          | 147/? [00:45<00:00,  3.22it/s, train/loss=8.040]
Epoch 0: |          | 148/? [00:45<00:00,  3.22it/s, train/loss=8.040]
Epoch 0: |          | 148/? [00:45<00:00,  3.22it/s, train/loss=2.790]
Epoch 0: |          | 149/? [00:46<00:00,  3.24it/s, train/loss=2.790]
Epoch 0: |          | 149/? [00:46<00:00,  3.23it/s, train/loss=7.960]
Epoch 0: |          | 150/? [00:46<00:00,  3.23it/s, train/loss=7.960]
Epoch 0: |          | 150/? [00:46<00:00,  3.23it/s, train/loss=2.020]
Epoch 0: |          | 151/? [00:47<00:00,  3.19it/s, train/loss=2.020]
Epoch 0: |          | 151/? [00:47<00:00,  3.19it/s, train/loss=1.330]
Epoch 0: |          | 152/? [00:47<00:00,  3.18it/s, train/loss=1.330]
Epoch 0: |          | 152/? [00:47<00:00,  3.18it/s, train/loss=2.790]
Epoch 0: |          | 153/? [00:47<00:00,  3.20it/s, train/loss=2.790]
Epoch 0: |          | 153/? [00:47<00:00,  3.20it/s, train/loss=7.830]
Epoch 0: |          | 154/? [00:48<00:00,  3.19it/s, train/loss=7.830]
Epoch 0: |          | 154/? [00:48<00:00,  3.19it/s, train/loss=3.220]
Epoch 0: |          | 155/? [00:48<00:00,  3.21it/s, train/loss=3.220]
Epoch 0: |          | 155/? [00:48<00:00,  3.21it/s, train/loss=7.760]
Epoch 0: |          | 156/? [00:48<00:00,  3.20it/s, train/loss=7.760]
Epoch 0: |          | 156/? [00:48<00:00,  3.20it/s, train/loss=2.120]
Epoch 0: |          | 157/? [00:48<00:00,  3.22it/s, train/loss=2.120]
Epoch 0: |          | 157/? [00:48<00:00,  3.22it/s, train/loss=7.700]
Epoch 0: |          | 158/? [00:49<00:00,  3.20it/s, train/loss=7.700]
Epoch 0: |          | 158/? [00:49<00:00,  3.20it/s, train/loss=1.940]
Epoch 0: |          | 159/? [00:49<00:00,  3.21it/s, train/loss=1.940]
Epoch 0: |          | 159/? [00:49<00:00,  3.21it/s, train/loss=7.640]
Epoch 0: |          | 160/? [00:49<00:00,  3.20it/s, train/loss=7.640]
Epoch 0: |          | 160/? [00:49<00:00,  3.20it/s, train/loss=1.960]
Epoch 0: |          | 161/? [00:51<00:00,  3.15it/s, train/loss=1.960]
Epoch 0: |          | 161/? [00:51<00:00,  3.15it/s, train/loss=0.607]
Epoch 0: |          | 162/? [00:51<00:00,  3.14it/s, train/loss=0.607]
Epoch 0: |          | 162/? [00:51<00:00,  3.14it/s, train/loss=0.631]
Epoch 0: |          | 163/? [00:51<00:00,  3.15it/s, train/loss=0.631]
Epoch 0: |          | 163/? [00:51<00:00,  3.15it/s, train/loss=7.540]
Epoch 0: |          | 164/? [00:52<00:00,  3.14it/s, train/loss=7.540]
Epoch 0: |          | 164/? [00:52<00:00,  3.14it/s, train/loss=2.620]
Epoch 0: |          | 165/? [00:52<00:00,  3.15it/s, train/loss=2.620]
Epoch 0: |          | 165/? [00:52<00:00,  3.15it/s, train/loss=7.500]
Epoch 0: |          | 166/? [00:52<00:00,  3.15it/s, train/loss=7.500]
Epoch 0: |          | 166/? [00:52<00:00,  3.15it/s, train/loss=2.730]
Epoch 0: |          | 167/? [00:52<00:00,  3.16it/s, train/loss=2.730]
Epoch 0: |          | 167/? [00:52<00:00,  3.16it/s, train/loss=7.450]
Epoch 0: |          | 168/? [00:53<00:00,  3.16it/s, train/loss=7.450]
Epoch 0: |          | 168/? [00:53<00:00,  3.16it/s, train/loss=1.880]
Epoch 0: |          | 169/? [00:53<00:00,  3.17it/s, train/loss=1.880]
Epoch 0: |          | 169/? [00:53<00:00,  3.17it/s, train/loss=7.390]
Epoch 0: |          | 170/? [00:53<00:00,  3.17it/s, train/loss=7.390]
Epoch 0: |          | 170/? [00:53<00:00,  3.17it/s, train/loss=1.330]
Epoch 0: |          | 171/? [00:54<00:00,  3.13it/s, train/loss=1.330]
Epoch 0: |          | 171/? [00:54<00:00,  3.13it/s, train/loss=1.980]
Epoch 0: |          | 172/? [00:54<00:00,  3.13it/s, train/loss=1.980]
Epoch 0: |          | 172/? [00:54<00:00,  3.13it/s, train/loss=0.843]
Epoch 0: |          | 173/? [00:55<00:00,  3.14it/s, train/loss=0.843]
Epoch 0: |          | 173/? [00:55<00:00,  3.14it/s, train/loss=7.300]
Epoch 0: |          | 174/? [00:55<00:00,  3.14it/s, train/loss=7.300]
Epoch 0: |          | 174/? [00:55<00:00,  3.14it/s, train/loss=3.970]
Epoch 0: |          | 175/? [00:55<00:00,  3.15it/s, train/loss=3.970]
Epoch 0: |          | 175/? [00:55<00:00,  3.15it/s, train/loss=7.240]
Epoch 0: |          | 176/? [00:55<00:00,  3.15it/s, train/loss=7.240]
Epoch 0: |          | 176/? [00:55<00:00,  3.15it/s, train/loss=1.490]
Epoch 0: |          | 177/? [00:55<00:00,  3.16it/s, train/loss=1.490]
Epoch 0: |          | 177/? [00:55<00:00,  3.16it/s, train/loss=7.180]
Epoch 0: |          | 178/? [00:56<00:00,  3.16it/s, train/loss=7.180]
Epoch 0: |          | 178/? [00:56<00:00,  3.16it/s, train/loss=2.410]
Epoch 0: |          | 179/? [00:56<00:00,  3.18it/s, train/loss=2.410]
Epoch 0: |          | 179/? [00:56<00:00,  3.18it/s, train/loss=7.130]
Epoch 0: |          | 180/? [00:56<00:00,  3.17it/s, train/loss=7.130]
Epoch 0: |          | 180/? [00:56<00:00,  3.17it/s, train/loss=4.450]
Epoch 0: |          | 181/? [00:57<00:00,  3.14it/s, train/loss=4.450]
Epoch 0: |          | 181/? [00:57<00:00,  3.13it/s, train/loss=2.640]
Epoch 0: |          | 182/? [00:58<00:00,  3.13it/s, train/loss=2.640]
Epoch 0: |          | 182/? [00:58<00:00,  3.12it/s, train/loss=1.290]
Epoch 0: |          | 183/? [00:58<00:00,  3.13it/s, train/loss=1.290]
Epoch 0: |          | 183/? [00:58<00:00,  3.13it/s, train/loss=7.040]
Epoch 0: |          | 184/? [00:58<00:00,  3.12it/s, train/loss=7.040]
Epoch 0: |          | 184/? [00:58<00:00,  3.12it/s, train/loss=1.280]
Epoch 0: |          | 185/? [00:58<00:00,  3.14it/s, train/loss=1.280]
Epoch 0: |          | 185/? [00:58<00:00,  3.14it/s, train/loss=6.990]
Epoch 0: |          | 186/? [00:59<00:00,  3.14it/s, train/loss=6.990]
Epoch 0: |          | 186/? [00:59<00:00,  3.14it/s, train/loss=1.760]
Epoch 0: |          | 187/? [00:59<00:00,  3.15it/s, train/loss=1.760]
Epoch 0: |          | 187/? [00:59<00:00,  3.15it/s, train/loss=6.940]
Epoch 0: |          | 188/? [00:59<00:00,  3.15it/s, train/loss=6.940]
Epoch 0: |          | 188/? [00:59<00:00,  3.15it/s, train/loss=1.270]
Epoch 0: |          | 189/? [00:59<00:00,  3.16it/s, train/loss=1.270]
Epoch 0: |          | 189/? [00:59<00:00,  3.16it/s, train/loss=6.890]
Epoch 0: |          | 190/? [01:00<00:00,  3.16it/s, train/loss=6.890]
Epoch 0: |          | 190/? [01:00<00:00,  3.16it/s, train/loss=0.835]
Epoch 0: |          | 191/? [01:01<00:00,  3.12it/s, train/loss=0.835]
Epoch 0: |          | 191/? [01:01<00:00,  3.12it/s, train/loss=1.100]
Epoch 0: |          | 192/? [01:01<00:00,  3.12it/s, train/loss=1.100]
Epoch 0: |          | 192/? [01:01<00:00,  3.12it/s, train/loss=1.180]
Epoch 0: |          | 193/? [01:01<00:00,  3.13it/s, train/loss=1.180]
Epoch 0: |          | 193/? [01:01<00:00,  3.13it/s, train/loss=6.810]
Epoch 0: |          | 194/? [01:01<00:00,  3.13it/s, train/loss=6.810]
Epoch 0: |          | 194/? [01:01<00:00,  3.13it/s, train/loss=3.430]
Epoch 0: |          | 195/? [01:02<00:00,  3.14it/s, train/loss=3.430]
Epoch 0: |          | 195/? [01:02<00:00,  3.14it/s, train/loss=6.770]
Epoch 0: |          | 196/? [01:02<00:00,  3.14it/s, train/loss=6.770]
Epoch 0: |          | 196/? [01:02<00:00,  3.14it/s, train/loss=2.480]
Epoch 0: |          | 197/? [01:02<00:00,  3.15it/s, train/loss=2.480]
Epoch 0: |          | 197/? [01:02<00:00,  3.15it/s, train/loss=6.720]
Epoch 0: |          | 198/? [01:02<00:00,  3.15it/s, train/loss=6.720]
Epoch 0: |          | 198/? [01:02<00:00,  3.15it/s, train/loss=1.160]
Epoch 0: |          | 199/? [01:02<00:00,  3.16it/s, train/loss=1.160]
Epoch 0: |          | 199/? [01:02<00:00,  3.16it/s, train/loss=6.670]
Epoch 0: |          | 200/? [01:03<00:00,  3.16it/s, train/loss=6.670]
Epoch 0: |          | 200/? [01:03<00:00,  3.16it/s, train/loss=2.950]
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Epoch 0: |          | 200/? [01:12<00:00,  2.76it/s, train/loss=2.950]
Epoch 0: |          | 201/? [01:20<00:00,  2.51it/s, train/loss=2.950]
Epoch 0: |          | 201/? [01:20<00:00,  2.51it/s, train/loss=1.330]
Epoch 0: |          | 202/? [01:20<00:00,  2.51it/s, train/loss=1.330]
Epoch 0: |          | 202/? [01:20<00:00,  2.51it/s, train/loss=0.757]
Epoch 0: |          | 203/? [01:20<00:00,  2.52it/s, train/loss=0.757]
Epoch 0: |          | 203/? [01:20<00:00,  2.52it/s, train/loss=6.590]
Epoch 0: |          | 204/? [01:20<00:00,  2.52it/s, train/loss=6.590]
Epoch 0: |          | 204/? [01:20<00:00,  2.52it/s, train/loss=1.360]
Epoch 0: |          | 205/? [01:20<00:00,  2.53it/s, train/loss=1.360]
Epoch 0: |          | 205/? [01:20<00:00,  2.53it/s, train/loss=6.550]
Epoch 0: |          | 206/? [01:21<00:00,  2.53it/s, train/loss=6.550]
Epoch 0: |          | 206/? [01:21<00:00,  2.53it/s, train/loss=3.090]
Epoch 0: |          | 207/? [01:21<00:00,  2.55it/s, train/loss=3.090]
Epoch 0: |          | 207/? [01:21<00:00,  2.55it/s, train/loss=6.500]
Epoch 0: |          | 208/? [01:21<00:00,  2.55it/s, train/loss=6.500]
Epoch 0: |          | 208/? [01:21<00:00,  2.55it/s, train/loss=3.700]
Epoch 0: |          | 209/? [01:21<00:00,  2.56it/s, train/loss=3.700]
Epoch 0: |          | 209/? [01:21<00:00,  2.56it/s, train/loss=6.450]
Epoch 0: |          | 210/? [01:22<00:00,  2.56it/s, train/loss=6.450]
Epoch 0: |          | 210/? [01:22<00:00,  2.56it/s, train/loss=2.180]
Epoch 0: |          | 211/? [01:23<00:00,  2.54it/s, train/loss=2.180]
Epoch 0: |          | 211/? [01:23<00:00,  2.54it/s, train/loss=2.080]
Epoch 0: |          | 212/? [01:23<00:00,  2.54it/s, train/loss=2.080]
Epoch 0: |          | 212/? [01:23<00:00,  2.54it/s, train/loss=1.330]
Epoch 0: |          | 213/? [01:23<00:00,  2.55it/s, train/loss=1.330]
Epoch 0: |          | 213/? [01:23<00:00,  2.55it/s, train/loss=6.370]
Epoch 0: |          | 214/? [01:23<00:00,  2.55it/s, train/loss=6.370]
Epoch 0: |          | 214/? [01:23<00:00,  2.55it/s, train/loss=6.390]
Epoch 0: |          | 215/? [01:23<00:00,  2.56it/s, train/loss=6.390]
Epoch 0: |          | 215/? [01:23<00:00,  2.56it/s, train/loss=6.320]
Epoch 0: |          | 216/? [01:24<00:00,  2.56it/s, train/loss=6.320]
Epoch 0: |          | 216/? [01:24<00:00,  2.56it/s, train/loss=2.420]
Epoch 0: |          | 217/? [01:24<00:00,  2.57it/s, train/loss=2.420]
Epoch 0: |          | 217/? [01:24<00:00,  2.57it/s, train/loss=6.280]
Epoch 0: |          | 218/? [01:24<00:00,  2.57it/s, train/loss=6.280]
Epoch 0: |          | 218/? [01:24<00:00,  2.57it/s, train/loss=0.810]
Epoch 0: |          | 219/? [01:24<00:00,  2.58it/s, train/loss=0.810]
Epoch 0: |          | 219/? [01:24<00:00,  2.58it/s, train/loss=6.250]
Epoch 0: |          | 220/? [01:25<00:00,  2.58it/s, train/loss=6.250]
Epoch 0: |          | 220/? [01:25<00:00,  2.58it/s, train/loss=2.580]
Epoch 0: |          | 221/? [01:26<00:00,  2.57it/s, train/loss=2.580]
Epoch 0: |          | 221/? [01:26<00:00,  2.56it/s, train/loss=1.950]
Epoch 0: |          | 222/? [01:26<00:00,  2.57it/s, train/loss=1.950]
Epoch 0: |          | 222/? [01:26<00:00,  2.57it/s, train/loss=2.630]
Epoch 0: |          | 223/? [01:26<00:00,  2.58it/s, train/loss=2.630]
Epoch 0: |          | 223/? [01:26<00:00,  2.58it/s, train/loss=6.190]
Epoch 0: |          | 224/? [01:26<00:00,  2.58it/s, train/loss=6.190]
Epoch 0: |          | 224/? [01:26<00:00,  2.58it/s, train/loss=1.390]
Epoch 0: |          | 225/? [01:27<00:00,  2.59it/s, train/loss=1.390]
Epoch 0: |          | 225/? [01:27<00:00,  2.59it/s, train/loss=6.140]
Epoch 0: |          | 226/? [01:27<00:00,  2.59it/s, train/loss=6.140]
Epoch 0: |          | 226/? [01:27<00:00,  2.59it/s, train/loss=1.380]
Epoch 0: |          | 227/? [01:27<00:00,  2.60it/s, train/loss=1.380]
Epoch 0: |          | 227/? [01:27<00:00,  2.60it/s, train/loss=6.100]
Epoch 0: |          | 228/? [01:27<00:00,  2.60it/s, train/loss=6.100]
Epoch 0: |          | 228/? [01:27<00:00,  2.60it/s, train/loss=3.490]
Epoch 0: |          | 229/? [01:27<00:00,  2.61it/s, train/loss=3.490]
Epoch 0: |          | 229/? [01:27<00:00,  2.61it/s, train/loss=6.060]
Epoch 0: |          | 230/? [01:28<00:00,  2.61it/s, train/loss=6.060]
Epoch 0: |          | 230/? [01:28<00:00,  2.61it/s, train/loss=1.660]
Epoch 0: |          | 231/? [01:29<00:00,  2.59it/s, train/loss=1.660]
Epoch 0: |          | 231/? [01:29<00:00,  2.59it/s, train/loss=1.780]
Epoch 0: |          | 232/? [01:29<00:00,  2.59it/s, train/loss=1.780]
Epoch 0: |          | 232/? [01:29<00:00,  2.59it/s, train/loss=1.100]
Epoch 0: |          | 233/? [01:29<00:00,  2.60it/s, train/loss=1.100]
Epoch 0: |          | 233/? [01:29<00:00,  2.60it/s, train/loss=6.010]
Epoch 0: |          | 234/? [01:30<00:00,  2.60it/s, train/loss=6.010]
Epoch 0: |          | 234/? [01:30<00:00,  2.60it/s, train/loss=2.180]
Epoch 0: |          | 235/? [01:30<00:00,  2.61it/s, train/loss=2.180]
Epoch 0: |          | 235/? [01:30<00:00,  2.61it/s, train/loss=5.970]
Epoch 0: |          | 236/? [01:30<00:00,  2.61it/s, train/loss=5.970]
Epoch 0: |          | 236/? [01:30<00:00,  2.61it/s, train/loss=2.190]
Epoch 0: |          | 237/? [01:30<00:00,  2.62it/s, train/loss=2.190]
Epoch 0: |          | 237/? [01:30<00:00,  2.62it/s, train/loss=5.920]
Epoch 0: |          | 238/? [01:30<00:00,  2.62it/s, train/loss=5.920]
Epoch 0: |          | 238/? [01:30<00:00,  2.62it/s, train/loss=2.410]
Epoch 0: |          | 239/? [01:30<00:00,  2.63it/s, train/loss=2.410]
Epoch 0: |          | 239/? [01:30<00:00,  2.63it/s, train/loss=5.900]
Epoch 0: |          | 240/? [01:31<00:00,  2.63it/s, train/loss=5.900]
Epoch 0: |          | 240/? [01:31<00:00,  2.63it/s, train/loss=3.740]
Epoch 0: |          | 241/? [01:32<00:00,  2.61it/s, train/loss=3.740]
Epoch 0: |          | 241/? [01:32<00:00,  2.61it/s, train/loss=0.724]
Epoch 0: |          | 242/? [01:32<00:00,  2.61it/s, train/loss=0.724]
Epoch 0: |          | 242/? [01:32<00:00,  2.61it/s, train/loss=2.850]
Epoch 0: |          | 243/? [01:32<00:00,  2.62it/s, train/loss=2.850]
Epoch 0: |          | 243/? [01:32<00:00,  2.62it/s, train/loss=5.900]
Epoch 0: |          | 244/? [01:33<00:00,  2.62it/s, train/loss=5.900]
Epoch 0: |          | 244/? [01:33<00:00,  2.62it/s, train/loss=2.430]
Epoch 0: |          | 245/? [01:33<00:00,  2.62it/s, train/loss=2.430]
Epoch 0: |          | 245/? [01:33<00:00,  2.62it/s, train/loss=5.900]
Epoch 0: |          | 246/? [01:33<00:00,  2.62it/s, train/loss=5.900]
Epoch 0: |          | 246/? [01:33<00:00,  2.62it/s, train/loss=1.230]
Epoch 0: |          | 247/? [01:34<00:00,  2.63it/s, train/loss=1.230]
Epoch 0: |          | 247/? [01:34<00:00,  2.63it/s, train/loss=5.870]
Epoch 0: |          | 248/? [01:34<00:00,  2.63it/s, train/loss=5.870]
Epoch 0: |          | 248/? [01:34<00:00,  2.63it/s, train/loss=2.390]
Epoch 0: |          | 249/? [01:34<00:00,  2.63it/s, train/loss=2.390]
Epoch 0: |          | 249/? [01:34<00:00,  2.63it/s, train/loss=5.860]
Epoch 0: |          | 250/? [01:34<00:00,  2.63it/s, train/loss=5.860]
Epoch 0: |          | 250/? [01:34<00:00,  2.63it/s, train/loss=1.140]
Epoch 0: |          | 251/? [01:35<00:00,  2.62it/s, train/loss=1.140]
Epoch 0: |          | 251/? [01:35<00:00,  2.62it/s, train/loss=2.820]
Epoch 0: |          | 252/? [01:36<00:00,  2.62it/s, train/loss=2.820]
Epoch 0: |          | 252/? [01:36<00:00,  2.62it/s, train/loss=1.120]
Epoch 0: |          | 253/? [01:36<00:00,  2.63it/s, train/loss=1.120]
Epoch 0: |          | 253/? [01:36<00:00,  2.63it/s, train/loss=5.850]
Epoch 0: |          | 254/? [01:36<00:00,  2.63it/s, train/loss=5.850]
Epoch 0: |          | 254/? [01:36<00:00,  2.63it/s, train/loss=1.020]
Epoch 0: |          | 255/? [01:36<00:00,  2.64it/s, train/loss=1.020]
Epoch 0: |          | 255/? [01:36<00:00,  2.64it/s, train/loss=5.830]
Epoch 0: |          | 256/? [01:37<00:00,  2.64it/s, train/loss=5.830]
Epoch 0: |          | 256/? [01:37<00:00,  2.64it/s, train/loss=1.290]
Epoch 0: |          | 257/? [01:37<00:00,  2.65it/s, train/loss=1.290]
Epoch 0: |          | 257/? [01:37<00:00,  2.65it/s, train/loss=5.800]
Epoch 0: |          | 258/? [01:37<00:00,  2.65it/s, train/loss=5.800]
Epoch 0: |          | 258/? [01:37<00:00,  2.65it/s, train/loss=1.870]
Epoch 0: |          | 259/? [01:37<00:00,  2.65it/s, train/loss=1.870]
Epoch 0: |          | 259/? [01:37<00:00,  2.65it/s, train/loss=5.770]
Epoch 0: |          | 260/? [01:37<00:00,  2.65it/s, train/loss=5.770]
Epoch 0: |          | 260/? [01:37<00:00,  2.65it/s, train/loss=1.200]
Epoch 0: |          | 261/? [01:38<00:00,  2.64it/s, train/loss=1.200]
Epoch 0: |          | 261/? [01:38<00:00,  2.64it/s, train/loss=2.530]
Epoch 0: |          | 262/? [01:39<00:00,  2.64it/s, train/loss=2.530]
Epoch 0: |          | 262/? [01:39<00:00,  2.64it/s, train/loss=3.570]
Epoch 0: |          | 263/? [01:39<00:00,  2.65it/s, train/loss=3.570]
Epoch 0: |          | 263/? [01:39<00:00,  2.65it/s, train/loss=5.770]
Epoch 0: |          | 264/? [01:39<00:00,  2.65it/s, train/loss=5.770]
Epoch 0: |          | 264/? [01:39<00:00,  2.65it/s, train/loss=0.946]
Epoch 0: |          | 265/? [01:39<00:00,  2.66it/s, train/loss=0.946]
Epoch 0: |          | 265/? [01:39<00:00,  2.66it/s, train/loss=5.760]
Epoch 0: |          | 266/? [01:40<00:00,  2.65it/s, train/loss=5.760]
Epoch 0: |          | 266/? [01:40<00:00,  2.65it/s, train/loss=1.480]
Epoch 0: |          | 267/? [01:40<00:00,  2.66it/s, train/loss=1.480]
Epoch 0: |          | 267/? [01:40<00:00,  2.66it/s, train/loss=5.740]
Epoch 0: |          | 268/? [01:40<00:00,  2.65it/s, train/loss=5.740]
Epoch 0: |          | 268/? [01:40<00:00,  2.65it/s, train/loss=3.570]
Epoch 0: |          | 269/? [01:41<00:00,  2.66it/s, train/loss=3.570]
Epoch 0: |          | 269/? [01:41<00:00,  2.66it/s, train/loss=5.720]
Epoch 0: |          | 270/? [01:41<00:00,  2.66it/s, train/loss=5.720]
Epoch 0: |          | 270/? [01:41<00:00,  2.66it/s, train/loss=2.580]
Epoch 0: |          | 271/? [01:42<00:00,  2.65it/s, train/loss=2.580]
Epoch 0: |          | 271/? [01:42<00:00,  2.65it/s, train/loss=2.380]
Epoch 0: |          | 272/? [01:42<00:00,  2.65it/s, train/loss=2.380]
Epoch 0: |          | 272/? [01:42<00:00,  2.65it/s, train/loss=0.554]
Epoch 0: |          | 273/? [01:42<00:00,  2.66it/s, train/loss=0.554]
Epoch 0: |          | 273/? [01:42<00:00,  2.66it/s, train/loss=5.690]
Epoch 0: |          | 274/? [01:43<00:00,  2.66it/s, train/loss=5.690]
Epoch 0: |          | 274/? [01:43<00:00,  2.66it/s, train/loss=1.810]
Epoch 0: |          | 275/? [01:43<00:00,  2.67it/s, train/loss=1.810]
Epoch 0: |          | 275/? [01:43<00:00,  2.67it/s, train/loss=5.660]
Epoch 0: |          | 276/? [01:43<00:00,  2.66it/s, train/loss=5.660]
Epoch 0: |          | 276/? [01:43<00:00,  2.66it/s, train/loss=3.710]
Epoch 0: |          | 277/? [01:43<00:00,  2.67it/s, train/loss=3.710]
Epoch 0: |          | 277/? [01:43<00:00,  2.67it/s, train/loss=5.640]
Epoch 0: |          | 278/? [01:44<00:00,  2.67it/s, train/loss=5.640]
Epoch 0: |          | 278/? [01:44<00:00,  2.67it/s, train/loss=2.730]
Epoch 0: |          | 279/? [01:44<00:00,  2.68it/s, train/loss=2.730]
Epoch 0: |          | 279/? [01:44<00:00,  2.68it/s, train/loss=5.610]
Epoch 0: |          | 280/? [01:44<00:00,  2.68it/s, train/loss=5.610]
Epoch 0: |          | 280/? [01:44<00:00,  2.68it/s, train/loss=1.710]
Epoch 0: |          | 281/? [01:45<00:00,  2.67it/s, train/loss=1.710]
Epoch 0: |          | 281/? [01:45<00:00,  2.67it/s, train/loss=2.830]
Epoch 0: |          | 282/? [01:45<00:00,  2.67it/s, train/loss=2.830]
Epoch 0: |          | 282/? [01:45<00:00,  2.67it/s, train/loss=4.200]
Epoch 0: |          | 283/? [01:45<00:00,  2.67it/s, train/loss=4.200]
Epoch 0: |          | 283/? [01:45<00:00,  2.67it/s, train/loss=5.560]
Epoch 0: |          | 284/? [01:46<00:00,  2.67it/s, train/loss=5.560]
Epoch 0: |          | 284/? [01:46<00:00,  2.67it/s, train/loss=2.860]
Epoch 0: |          | 285/? [01:46<00:00,  2.68it/s, train/loss=2.860]
Epoch 0: |          | 285/? [01:46<00:00,  2.68it/s, train/loss=5.520]
Epoch 0: |          | 286/? [01:46<00:00,  2.68it/s, train/loss=5.520]
Epoch 0: |          | 286/? [01:46<00:00,  2.68it/s, train/loss=3.260]
Epoch 0: |          | 287/? [01:46<00:00,  2.69it/s, train/loss=3.260]
Epoch 0: |          | 287/? [01:46<00:00,  2.69it/s, train/loss=5.480]
Epoch 0: |          | 288/? [01:47<00:00,  2.69it/s, train/loss=5.480]
Epoch 0: |          | 288/? [01:47<00:00,  2.69it/s, train/loss=2.080]
Epoch 0: |          | 289/? [01:47<00:00,  2.70it/s, train/loss=2.080]
Epoch 0: |          | 289/? [01:47<00:00,  2.70it/s, train/loss=5.440]
Epoch 0: |          | 290/? [01:47<00:00,  2.70it/s, train/loss=5.440]
Epoch 0: |          | 290/? [01:47<00:00,  2.70it/s, train/loss=2.980]
Epoch 0: |          | 291/? [01:48<00:00,  2.68it/s, train/loss=2.980]
Epoch 0: |          | 291/? [01:48<00:00,  2.68it/s, train/loss=1.650]
Epoch 0: |          | 292/? [01:48<00:00,  2.69it/s, train/loss=1.650]
Epoch 0: |          | 292/? [01:48<00:00,  2.68it/s, train/loss=1.700]
Epoch 0: |          | 293/? [01:48<00:00,  2.69it/s, train/loss=1.700]
Epoch 0: |          | 293/? [01:48<00:00,  2.69it/s, train/loss=5.400]
Epoch 0: |          | 294/? [01:49<00:00,  2.69it/s, train/loss=5.400]
Epoch 0: |          | 294/? [01:49<00:00,  2.69it/s, train/loss=3.030]
Epoch 0: |          | 295/? [01:49<00:00,  2.70it/s, train/loss=3.030]
Epoch 0: |          | 295/? [01:49<00:00,  2.70it/s, train/loss=5.380]
Epoch 0: |          | 296/? [01:49<00:00,  2.70it/s, train/loss=5.380]
Epoch 0: |          | 296/? [01:49<00:00,  2.70it/s, train/loss=2.820]
Epoch 0: |          | 297/? [01:49<00:00,  2.71it/s, train/loss=2.820]
Epoch 0: |          | 297/? [01:49<00:00,  2.71it/s, train/loss=5.350]
Epoch 0: |          | 298/? [01:50<00:00,  2.71it/s, train/loss=5.350]
Epoch 0: |          | 298/? [01:50<00:00,  2.71it/s, train/loss=1.420]
Epoch 0: |          | 299/? [01:50<00:00,  2.71it/s, train/loss=1.420]
Epoch 0: |          | 299/? [01:50<00:00,  2.71it/s, train/loss=5.320]
Epoch 0: |          | 300/? [01:50<00:00,  2.71it/s, train/loss=5.320]
Epoch 0: |          | 300/? [01:50<00:00,  2.71it/s, train/loss=1.020]
Epoch 0: |          | 301/? [01:51<00:00,  2.70it/s, train/loss=1.020]
Epoch 0: |          | 301/? [01:51<00:00,  2.70it/s, train/loss=0.883]
Epoch 0: |          | 302/? [01:51<00:00,  2.70it/s, train/loss=0.883]
Epoch 0: |          | 302/? [01:51<00:00,  2.70it/s, train/loss=3.050]
Epoch 0: |          | 303/? [01:51<00:00,  2.71it/s, train/loss=3.050]
Epoch 0: |          | 303/? [01:51<00:00,  2.71it/s, train/loss=5.280]
Epoch 0: |          | 304/? [01:52<00:00,  2.71it/s, train/loss=5.280]
Epoch 0: |          | 304/? [01:52<00:00,  2.71it/s, train/loss=2.640]
Epoch 0: |          | 305/? [01:52<00:00,  2.72it/s, train/loss=2.640]
Epoch 0: |          | 305/? [01:52<00:00,  2.72it/s, train/loss=5.260]
Epoch 0: |          | 306/? [01:52<00:00,  2.71it/s, train/loss=5.260]
Epoch 0: |          | 306/? [01:52<00:00,  2.71it/s, train/loss=1.430]
Epoch 0: |          | 307/? [01:52<00:00,  2.72it/s, train/loss=1.430]
Epoch 0: |          | 307/? [01:52<00:00,  2.72it/s, train/loss=5.230]
Epoch 0: |          | 308/? [01:53<00:00,  2.72it/s, train/loss=5.230]
Epoch 0: |          | 308/? [01:53<00:00,  2.72it/s, train/loss=2.380]
Epoch 0: |          | 309/? [01:53<00:00,  2.73it/s, train/loss=2.380]
Epoch 0: |          | 309/? [01:53<00:00,  2.73it/s, train/loss=5.200]
Epoch 0: |          | 310/? [01:53<00:00,  2.73it/s, train/loss=5.200]
Epoch 0: |          | 310/? [01:53<00:00,  2.73it/s, train/loss=1.700]
Epoch 0: |          | 311/? [01:54<00:00,  2.72it/s, train/loss=1.700]
Epoch 0: |          | 311/? [01:54<00:00,  2.71it/s, train/loss=2.040]
Epoch 0: |          | 312/? [01:54<00:00,  2.72it/s, train/loss=2.040]
Epoch 0: |          | 312/? [01:54<00:00,  2.71it/s, train/loss=0.999]
Epoch 0: |          | 313/? [01:54<00:00,  2.72it/s, train/loss=0.999]
Epoch 0: |          | 313/? [01:54<00:00,  2.72it/s, train/loss=5.190]
Epoch 0: |          | 314/? [01:55<00:00,  2.72it/s, train/loss=5.190]
Epoch 0: |          | 314/? [01:55<00:00,  2.72it/s, train/loss=1.130]
Epoch 0: |          | 315/? [01:55<00:00,  2.73it/s, train/loss=1.130]
Epoch 0: |          | 315/? [01:55<00:00,  2.73it/s, train/loss=5.190]
Epoch 0: |          | 316/? [01:55<00:00,  2.73it/s, train/loss=5.190]
Epoch 0: |          | 316/? [01:55<00:00,  2.73it/s, train/loss=3.310]
Epoch 0: |          | 317/? [01:55<00:00,  2.74it/s, train/loss=3.310]
Epoch 0: |          | 317/? [01:55<00:00,  2.74it/s, train/loss=5.170]
Epoch 0: |          | 318/? [01:56<00:00,  2.73it/s, train/loss=5.170]
Epoch 0: |          | 318/? [01:56<00:00,  2.73it/s, train/loss=1.810]
Epoch 0: |          | 319/? [01:56<00:00,  2.74it/s, train/loss=1.810]
Epoch 0: |          | 319/? [01:56<00:00,  2.74it/s, train/loss=5.160]
Epoch 0: |          | 320/? [01:56<00:00,  2.74it/s, train/loss=5.160]
Epoch 0: |          | 320/? [01:56<00:00,  2.74it/s, train/loss=2.270]
Epoch 0: |          | 321/? [01:57<00:00,  2.73it/s, train/loss=2.270]
Epoch 0: |          | 321/? [01:57<00:00,  2.73it/s, train/loss=1.920]
Epoch 0: |          | 322/? [01:57<00:00,  2.73it/s, train/loss=1.920]
Epoch 0: |          | 322/? [01:58<00:00,  2.73it/s, train/loss=1.600]
Epoch 0: |          | 323/? [01:58<00:00,  2.73it/s, train/loss=1.600]
Epoch 0: |          | 323/? [01:58<00:00,  2.73it/s, train/loss=5.150]
Epoch 0: |          | 324/? [01:58<00:00,  2.73it/s, train/loss=5.150]
Epoch 0: |          | 324/? [01:58<00:00,  2.73it/s, train/loss=3.730]
Epoch 0: |          | 325/? [01:58<00:00,  2.74it/s, train/loss=3.730]
Epoch 0: |          | 325/? [01:58<00:00,  2.74it/s, train/loss=5.150]
Epoch 0: |          | 326/? [01:58<00:00,  2.74it/s, train/loss=5.150]
Epoch 0: |          | 326/? [01:58<00:00,  2.74it/s, train/loss=2.220]
Epoch 0: |          | 327/? [01:59<00:00,  2.75it/s, train/loss=2.220]
Epoch 0: |          | 327/? [01:59<00:00,  2.75it/s, train/loss=5.130]
Epoch 0: |          | 328/? [01:59<00:00,  2.75it/s, train/loss=5.130]
Epoch 0: |          | 328/? [01:59<00:00,  2.75it/s, train/loss=1.950]
Epoch 0: |          | 329/? [01:59<00:00,  2.75it/s, train/loss=1.950]
Epoch 0: |          | 329/? [01:59<00:00,  2.75it/s, train/loss=5.100]
Epoch 0: |          | 330/? [01:59<00:00,  2.75it/s, train/loss=5.100]
Epoch 0: |          | 330/? [01:59<00:00,  2.75it/s, train/loss=5.410]
Epoch 0: |          | 331/? [02:00<00:00,  2.74it/s, train/loss=5.410]
Epoch 0: |          | 331/? [02:00<00:00,  2.74it/s, train/loss=2.210]
Epoch 0: |          | 332/? [02:01<00:00,  2.74it/s, train/loss=2.210]
Epoch 0: |          | 332/? [02:01<00:00,  2.74it/s, train/loss=1.130]
Epoch 0: |          | 333/? [02:01<00:00,  2.75it/s, train/loss=1.130]
Epoch 0: |          | 333/? [02:01<00:00,  2.75it/s, train/loss=5.080]
Epoch 0: |          | 334/? [02:01<00:00,  2.75it/s, train/loss=5.080]
Epoch 0: |          | 334/? [02:01<00:00,  2.75it/s, train/loss=2.390]
Epoch 0: |          | 335/? [02:01<00:00,  2.75it/s, train/loss=2.390]
Epoch 0: |          | 335/? [02:01<00:00,  2.75it/s, train/loss=5.060]
Epoch 0: |          | 336/? [02:02<00:00,  2.75it/s, train/loss=5.060]
Epoch 0: |          | 336/? [02:02<00:00,  2.75it/s, train/loss=3.190]
Epoch 0: |          | 337/? [02:02<00:00,  2.76it/s, train/loss=3.190]
Epoch 0: |          | 337/? [02:02<00:00,  2.76it/s, train/loss=5.040]
Epoch 0: |          | 338/? [02:02<00:00,  2.76it/s, train/loss=5.040]
Epoch 0: |          | 338/? [02:02<00:00,  2.76it/s, train/loss=0.746]
Epoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=0.746]
Epoch 0: |          | 339/? [02:02<00:00,  2.77it/s, train/loss=5.020]
Epoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=5.020]
Epoch 0: |          | 340/? [02:02<00:00,  2.77it/s, train/loss=1.340]
Epoch 0: |          | 341/? [02:03<00:00,  2.75it/s, train/loss=1.340]
Epoch 0: |          | 341/? [02:03<00:00,  2.75it/s, train/loss=1.570]
Epoch 0: |          | 342/? [02:04<00:00,  2.75it/s, train/loss=1.570]
Epoch 0: |          | 342/? [02:04<00:00,  2.75it/s, train/loss=2.380]
Epoch 0: |          | 343/? [02:04<00:00,  2.76it/s, train/loss=2.380]
Epoch 0: |          | 343/? [02:04<00:00,  2.76it/s, train/loss=5.000]
Epoch 0: |          | 344/? [02:04<00:00,  2.76it/s, train/loss=5.000]
Epoch 0: |          | 344/? [02:04<00:00,  2.76it/s, train/loss=4.760]
Epoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=4.760]
Epoch 0: |          | 345/? [02:04<00:00,  2.77it/s, train/loss=4.980]
Epoch 0: |          | 346/? [02:05<00:00,  2.77it/s, train/loss=4.980]
Epoch 0: |          | 346/? [02:05<00:00,  2.77it/s, train/loss=3.570]
Epoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=3.570]
Epoch 0: |          | 347/? [02:05<00:00,  2.77it/s, train/loss=4.940]
Epoch 0: |          | 348/? [02:05<00:00,  2.77it/s, train/loss=4.940]
Epoch 0: |          | 348/? [02:05<00:00,  2.77it/s, train/loss=2.680]
Epoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=2.680]
Epoch 0: |          | 349/? [02:05<00:00,  2.78it/s, train/loss=4.940]
Epoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=4.940]
Epoch 0: |          | 350/? [02:06<00:00,  2.78it/s, train/loss=1.490]
Epoch 0: |          | 351/? [02:06<00:00,  2.77it/s, train/loss=1.490]
Epoch 0: |          | 351/? [02:06<00:00,  2.76it/s, train/loss=2.270]
Epoch 0: |          | 352/? [02:07<00:00,  2.77it/s, train/loss=2.270]
Epoch 0: |          | 352/? [02:07<00:00,  2.77it/s, train/loss=1.580]
Epoch 0: |          | 353/? [02:07<00:00,  2.77it/s, train/loss=1.580]
Epoch 0: |          | 353/? [02:07<00:00,  2.77it/s, train/loss=4.990]
Epoch 0: |          | 354/? [02:07<00:00,  2.77it/s, train/loss=4.990]
Epoch 0: |          | 354/? [02:07<00:00,  2.77it/s, train/loss=0.693]
Epoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=0.693]
Epoch 0: |          | 355/? [02:07<00:00,  2.78it/s, train/loss=4.980]
Epoch 0: |          | 356/? [02:08<00:00,  2.77it/s, train/loss=4.980]
Epoch 0: |          | 356/? [02:08<00:00,  2.77it/s, train/loss=2.220]
Epoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=2.220]
Epoch 0: |          | 357/? [02:08<00:00,  2.78it/s, train/loss=4.950]
Epoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=4.950]
Epoch 0: |          | 358/? [02:08<00:00,  2.78it/s, train/loss=0.770]
Epoch 0: |          | 359/? [02:08<00:00,  2.79it/s, train/loss=0.770]
Epoch 0: |          | 359/? [02:08<00:00,  2.79it/s, train/loss=4.930]
Epoch 0: |          | 360/? [02:09<00:00,  2.79it/s, train/loss=4.930]
Epoch 0: |          | 360/? [02:09<00:00,  2.79it/s, train/loss=3.010]
Epoch 0: |          | 361/? [02:10<00:00,  2.77it/s, train/loss=3.010]
Epoch 0: |          | 361/? [02:10<00:00,  2.77it/s, train/loss=0.704]
Epoch 0: |          | 362/? [02:10<00:00,  2.78it/s, train/loss=0.704]
Epoch 0: |          | 362/? [02:10<00:00,  2.77it/s, train/loss=2.000]
Epoch 0: |          | 363/? [02:10<00:00,  2.78it/s, train/loss=2.000]
Epoch 0: |          | 363/? [02:10<00:00,  2.78it/s, train/loss=4.930]
Epoch 0: |          | 364/? [02:10<00:00,  2.78it/s, train/loss=4.930]
Epoch 0: |          | 364/? [02:10<00:00,  2.78it/s, train/loss=2.770]
Epoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=2.770]
Epoch 0: |          | 365/? [02:10<00:00,  2.79it/s, train/loss=4.920]
Epoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=4.920]
Epoch 0: |          | 366/? [02:11<00:00,  2.79it/s, train/loss=1.270]
Epoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=1.270]
Epoch 0: |          | 367/? [02:11<00:00,  2.79it/s, train/loss=4.900]
Epoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=4.900]
Epoch 0: |          | 368/? [02:11<00:00,  2.79it/s, train/loss=2.370]
Epoch 0: |          | 369/? [02:11<00:00,  2.80it/s, train/loss=2.370]
Epoch 0: |          | 369/? [02:11<00:00,  2.80it/s, train/loss=4.890]
Epoch 0: |          | 370/? [02:12<00:00,  2.80it/s, train/loss=4.890]
Epoch 0: |          | 370/? [02:12<00:00,  2.80it/s, train/loss=1.150]
Epoch 0: |          | 371/? [02:13<00:00,  2.79it/s, train/loss=1.150]
Epoch 0: |          | 371/? [02:13<00:00,  2.78it/s, train/loss=2.940]
Epoch 0: |          | 372/? [02:13<00:00,  2.79it/s, train/loss=2.940]
Epoch 0: |          | 372/? [02:13<00:00,  2.78it/s, train/loss=1.090]
Epoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=1.090]
Epoch 0: |          | 373/? [02:13<00:00,  2.79it/s, train/loss=4.880]
Epoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=4.880]
Epoch 0: |          | 374/? [02:14<00:00,  2.79it/s, train/loss=3.940]
Epoch 0: |          | 375/? [02:14<00:00,  2.80it/s, train/loss=3.940]
Epoch 0: |          | 375/? [02:14<00:00,  2.80it/s, train/loss=4.870]
Epoch 0: |          | 376/? [02:14<00:00,  2.80it/s, train/loss=4.870]
Epoch 0: |          | 376/? [02:14<00:00,  2.80it/s, train/loss=2.950]
Epoch 0: |          | 377/? [02:14<00:00,  2.80it/s, train/loss=2.950]
Epoch 0: |          | 377/? [02:14<00:00,  2.80it/s, train/loss=4.840]
Epoch 0: |          | 378/? [02:14<00:00,  2.80it/s, train/loss=4.840]
Epoch 0: |          | 378/? [02:14<00:00,  2.80it/s, train/loss=2.900]
Epoch 0: |          | 379/? [02:14<00:00,  2.81it/s, train/loss=2.900]
Epoch 0: |          | 379/? [02:14<00:00,  2.81it/s, train/loss=4.820]
Epoch 0: |          | 380/? [02:15<00:00,  2.81it/s, train/loss=4.820]
Epoch 0: |          | 380/? [02:15<00:00,  2.81it/s, train/loss=2.240]
Epoch 0: |          | 381/? [02:16<00:00,  2.80it/s, train/loss=2.240]
Epoch 0: |          | 381/? [02:16<00:00,  2.79it/s, train/loss=0.726]
Epoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=0.726]
Epoch 0: |          | 382/? [02:16<00:00,  2.79it/s, train/loss=1.090]
Epoch 0: |          | 383/? [02:16<00:00,  2.80it/s, train/loss=1.090]
Epoch 0: |          | 383/? [02:16<00:00,  2.80it/s, train/loss=4.800]
Epoch 0: |          | 384/? [02:17<00:00,  2.80it/s, train/loss=4.800]
Epoch 0: |          | 384/? [02:17<00:00,  2.80it/s, train/loss=3.060]
Epoch 0: |          | 385/? [02:17<00:00,  2.81it/s, train/loss=3.060]
Epoch 0: |          | 385/? [02:17<00:00,  2.81it/s, train/loss=4.780]
Epoch 0: |          | 386/? [02:17<00:00,  2.80it/s, train/loss=4.780]
Epoch 0: |          | 386/? [02:17<00:00,  2.80it/s, train/loss=2.630]
Epoch 0: |          | 387/? [02:17<00:00,  2.81it/s, train/loss=2.630]
Epoch 0: |          | 387/? [02:17<00:00,  2.81it/s, train/loss=4.750]
Epoch 0: |          | 388/? [02:18<00:00,  2.81it/s, train/loss=4.750]
Epoch 0: |          | 388/? [02:18<00:00,  2.81it/s, train/loss=0.970]
Epoch 0: |          | 389/? [02:18<00:00,  2.82it/s, train/loss=0.970]
Epoch 0: |          | 389/? [02:18<00:00,  2.82it/s, train/loss=4.730]
Epoch 0: |          | 390/? [02:18<00:00,  2.81it/s, train/loss=4.730]
Epoch 0: |          | 390/? [02:18<00:00,  2.81it/s, train/loss=3.590]
Epoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=3.590]
Epoch 0: |          | 391/? [02:19<00:00,  2.80it/s, train/loss=1.050]
Epoch 0: |          | 392/? [02:19<00:00,  2.80it/s, train/loss=1.050]
Epoch 0: |          | 392/? [02:19<00:00,  2.80it/s, train/loss=0.961]
Epoch 0: |          | 393/? [02:19<00:00,  2.81it/s, train/loss=0.961]
Epoch 0: |          | 393/? [02:19<00:00,  2.81it/s, train/loss=4.700]
Epoch 0: |          | 394/? [02:20<00:00,  2.81it/s, train/loss=4.700]
Epoch 0: |          | 394/? [02:20<00:00,  2.81it/s, train/loss=2.750]
Epoch 0: |          | 395/? [02:20<00:00,  2.81it/s, train/loss=2.750]
Epoch 0: |          | 395/? [02:20<00:00,  2.81it/s, train/loss=4.690]
Epoch 0: |          | 396/? [02:20<00:00,  2.81it/s, train/loss=4.690]
Epoch 0: |          | 396/? [02:20<00:00,  2.81it/s, train/loss=4.030]
Epoch 0: |          | 397/? [02:20<00:00,  2.82it/s, train/loss=4.030]
Epoch 0: |          | 397/? [02:20<00:00,  2.82it/s, train/loss=4.670]
Epoch 0: |          | 398/? [02:21<00:00,  2.82it/s, train/loss=4.670]
Epoch 0: |          | 398/? [02:21<00:00,  2.82it/s, train/loss=2.210]
Epoch 0: |          | 399/? [02:21<00:00,  2.82it/s, train/loss=2.210]
Epoch 0: |          | 399/? [02:21<00:00,  2.82it/s, train/loss=4.660]
Epoch 0: |          | 400/? [02:21<00:00,  2.82it/s, train/loss=4.660]
Epoch 0: |          | 400/? [02:21<00:00,  2.82it/s, train/loss=2.450]
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Epoch 0: |          | 400/? [02:30<00:00,  2.65it/s, train/loss=2.450]
Epoch 0: |          | 401/? [02:50<00:00,  2.35it/s, train/loss=2.450]
Epoch 0: |          | 401/? [02:51<00:00,  2.34it/s, train/loss=0.663]
Epoch 0: |          | 402/? [02:51<00:00,  2.35it/s, train/loss=0.663]
Epoch 0: |          | 402/? [02:51<00:00,  2.35it/s, train/loss=1.990]
Epoch 0: |          | 403/? [02:51<00:00,  2.35it/s, train/loss=1.990]
Epoch 0: |          | 403/? [02:51<00:00,  2.35it/s, train/loss=4.650]
Epoch 0: |          | 404/? [02:51<00:00,  2.35it/s, train/loss=4.650]
Epoch 0: |          | 404/? [02:51<00:00,  2.35it/s, train/loss=1.070]
Epoch 0: |          | 405/? [02:51<00:00,  2.36it/s, train/loss=1.070]
Epoch 0: |          | 405/? [02:51<00:00,  2.36it/s, train/loss=4.640]
Epoch 0: |          | 406/? [02:52<00:00,  2.36it/s, train/loss=4.640]
Epoch 0: |          | 406/? [02:52<00:00,  2.36it/s, train/loss=2.970]
Epoch 0: |          | 407/? [02:52<00:00,  2.36it/s, train/loss=2.970]
Epoch 0: |          | 407/? [02:52<00:00,  2.36it/s, train/loss=4.610]
Epoch 0: |          | 408/? [02:52<00:00,  2.36it/s, train/loss=4.610]
Epoch 0: |          | 408/? [02:52<00:00,  2.36it/s, train/loss=2.380]
Epoch 0: |          | 409/? [02:52<00:00,  2.37it/s, train/loss=2.380]
Epoch 0: |          | 409/? [02:52<00:00,  2.37it/s, train/loss=4.590]
Epoch 0: |          | 410/? [02:53<00:00,  2.36it/s, train/loss=4.590]
Epoch 0: |          | 410/? [02:53<00:00,  2.36it/s, train/loss=1.430]
Epoch 0: |          | 411/? [02:54<00:00,  2.36it/s, train/loss=1.430]
Epoch 0: |          | 411/? [02:54<00:00,  2.35it/s, train/loss=1.160]
Epoch 0: |          | 412/? [02:54<00:00,  2.36it/s, train/loss=1.160]
Epoch 0: |          | 412/? [02:54<00:00,  2.36it/s, train/loss=1.590]
Epoch 0: |          | 413/? [02:54<00:00,  2.36it/s, train/loss=1.590]
Epoch 0: |          | 413/? [02:54<00:00,  2.36it/s, train/loss=4.570]
Epoch 0: |          | 414/? [02:55<00:00,  2.36it/s, train/loss=4.570]
Epoch 0: |          | 414/? [02:55<00:00,  2.36it/s, train/loss=1.560]
Epoch 0: |          | 415/? [02:55<00:00,  2.37it/s, train/loss=1.560]
Epoch 0: |          | 415/? [02:55<00:00,  2.37it/s, train/loss=4.550]
Epoch 0: |          | 416/? [02:55<00:00,  2.37it/s, train/loss=4.550]
Epoch 0: |          | 416/? [02:55<00:00,  2.37it/s, train/loss=3.270]
Epoch 0: |          | 417/? [02:55<00:00,  2.37it/s, train/loss=3.270]
Epoch 0: |          | 417/? [02:55<00:00,  2.37it/s, train/loss=4.530]
Epoch 0: |          | 418/? [02:56<00:00,  2.37it/s, train/loss=4.530]
Epoch 0: |          | 418/? [02:56<00:00,  2.37it/s, train/loss=3.370]
Epoch 0: |          | 419/? [02:56<00:00,  2.38it/s, train/loss=3.370]
Epoch 0: |          | 419/? [02:56<00:00,  2.38it/s, train/loss=4.520]
Epoch 0: |          | 420/? [02:56<00:00,  2.38it/s, train/loss=4.520]
Epoch 0: |          | 420/? [02:56<00:00,  2.38it/s, train/loss=2.730]
Epoch 0: |          | 421/? [02:57<00:00,  2.37it/s, train/loss=2.730]
Epoch 0: |          | 421/? [02:57<00:00,  2.37it/s, train/loss=0.665]
Epoch 0: |          | 422/? [02:58<00:00,  2.37it/s, train/loss=0.665]
Epoch 0: |          | 422/? [02:58<00:00,  2.37it/s, train/loss=2.290]
Epoch 0: |          | 423/? [02:58<00:00,  2.37it/s, train/loss=2.290]
Epoch 0: |          | 423/? [02:58<00:00,  2.37it/s, train/loss=4.540]
Epoch 0: |          | 424/? [02:58<00:00,  2.38it/s, train/loss=4.540]
Epoch 0: |          | 424/? [02:58<00:00,  2.38it/s, train/loss=2.300]
Epoch 0: |          | 425/? [02:58<00:00,  2.38it/s, train/loss=2.300]
Epoch 0: |          | 425/? [02:58<00:00,  2.38it/s, train/loss=4.540]
Epoch 0: |          | 426/? [02:58<00:00,  2.38it/s, train/loss=4.540]
Epoch 0: |          | 426/? [02:58<00:00,  2.38it/s, train/loss=1.450]
Epoch 0: |          | 427/? [02:59<00:00,  2.39it/s, train/loss=1.450]
Epoch 0: |          | 427/? [02:59<00:00,  2.38it/s, train/loss=4.500]
Epoch 0: |          | 428/? [02:59<00:00,  2.39it/s, train/loss=4.500]
Epoch 0: |          | 428/? [02:59<00:00,  2.39it/s, train/loss=0.830]
Epoch 0: |          | 429/? [02:59<00:00,  2.39it/s, train/loss=0.830]
Epoch 0: |          | 429/? [02:59<00:00,  2.39it/s, train/loss=4.490]
Epoch 0: |          | 430/? [02:59<00:00,  2.39it/s, train/loss=4.490]
Epoch 0: |          | 430/? [02:59<00:00,  2.39it/s, train/loss=0.742]
Epoch 0: |          | 431/? [03:00<00:00,  2.38it/s, train/loss=0.742]
Epoch 0: |          | 431/? [03:00<00:00,  2.38it/s, train/loss=1.350]
Epoch 0: |          | 432/? [03:01<00:00,  2.38it/s, train/loss=1.350]
Epoch 0: |          | 432/? [03:01<00:00,  2.38it/s, train/loss=2.160]
Epoch 0: |          | 433/? [03:01<00:00,  2.39it/s, train/loss=2.160]
Epoch 0: |          | 433/? [03:01<00:00,  2.39it/s, train/loss=4.540]
Epoch 0: |          | 434/? [03:01<00:00,  2.39it/s, train/loss=4.540]
Epoch 0: |          | 434/? [03:01<00:00,  2.39it/s, train/loss=2.430]
Epoch 0: |          | 435/? [03:01<00:00,  2.39it/s, train/loss=2.430]
Epoch 0: |          | 435/? [03:01<00:00,  2.39it/s, train/loss=4.530]
Epoch 0: |          | 436/? [03:02<00:00,  2.39it/s, train/loss=4.530]
Epoch 0: |          | 436/? [03:02<00:00,  2.39it/s, train/loss=3.150]
Epoch 0: |          | 437/? [03:02<00:00,  2.40it/s, train/loss=3.150]
Epoch 0: |          | 437/? [03:02<00:00,  2.40it/s, train/loss=4.510]
Epoch 0: |          | 438/? [03:02<00:00,  2.40it/s, train/loss=4.510]
Epoch 0: |          | 438/? [03:02<00:00,  2.40it/s, train/loss=2.300]
Epoch 0: |          | 439/? [03:02<00:00,  2.40it/s, train/loss=2.300]
Epoch 0: |          | 439/? [03:02<00:00,  2.40it/s, train/loss=4.510]
Epoch 0: |          | 440/? [03:03<00:00,  2.40it/s, train/loss=4.510]
Epoch 0: |          | 440/? [03:03<00:00,  2.40it/s, train/loss=3.060]
Epoch 0: |          | 441/? [03:03<00:00,  2.40it/s, train/loss=3.060]
Epoch 0: |          | 441/? [03:03<00:00,  2.40it/s, train/loss=1.380]
Epoch 0: |          | 442/? [03:04<00:00,  2.40it/s, train/loss=1.380]
Epoch 0: |          | 442/? [03:04<00:00,  2.40it/s, train/loss=2.210]
Epoch 0: |          | 443/? [03:04<00:00,  2.40it/s, train/loss=2.210]
Epoch 0: |          | 443/? [03:04<00:00,  2.40it/s, train/loss=4.530]
Epoch 0: |          | 444/? [03:04<00:00,  2.40it/s, train/loss=4.530]
Epoch 0: |          | 444/? [03:04<00:00,  2.40it/s, train/loss=1.410]
Epoch 0: |          | 445/? [03:04<00:00,  2.41it/s, train/loss=1.410]
Epoch 0: |          | 445/? [03:04<00:00,  2.41it/s, train/loss=4.520]
Epoch 0: |          | 446/? [03:05<00:00,  2.41it/s, train/loss=4.520]
Epoch 0: |          | 446/? [03:05<00:00,  2.41it/s, train/loss=0.731]
Epoch 0: |          | 447/? [03:05<00:00,  2.41it/s, train/loss=0.731]
Epoch 0: |          | 447/? [03:05<00:00,  2.41it/s, train/loss=4.500]
Epoch 0: |          | 448/? [03:05<00:00,  2.41it/s, train/loss=4.500]
Epoch 0: |          | 448/? [03:05<00:00,  2.41it/s, train/loss=1.490]
Epoch 0: |          | 449/? [03:05<00:00,  2.42it/s, train/loss=1.490]
Epoch 0: |          | 449/? [03:05<00:00,  2.42it/s, train/loss=4.470]
Epoch 0: |          | 450/? [03:06<00:00,  2.42it/s, train/loss=4.470]
Epoch 0: |          | 450/? [03:06<00:00,  2.42it/s, train/loss=3.620]
Epoch 0: |          | 451/? [03:07<00:00,  2.41it/s, train/loss=3.620]
Epoch 0: |          | 451/? [03:07<00:00,  2.41it/s, train/loss=3.350]
Epoch 0: |          | 452/? [03:07<00:00,  2.41it/s, train/loss=3.350]
Epoch 0: |          | 452/? [03:07<00:00,  2.41it/s, train/loss=1.390]
Epoch 0: |          | 453/? [03:07<00:00,  2.42it/s, train/loss=1.390]
Epoch 0: |          | 453/? [03:07<00:00,  2.42it/s, train/loss=4.420]
Epoch 0: |          | 454/? [03:07<00:00,  2.42it/s, train/loss=4.420]
Epoch 0: |          | 454/? [03:07<00:00,  2.42it/s, train/loss=2.750]
Epoch 0: |          | 455/? [03:07<00:00,  2.42it/s, train/loss=2.750]
Epoch 0: |          | 455/? [03:07<00:00,  2.42it/s, train/loss=4.400]
Epoch 0: |          | 456/? [03:08<00:00,  2.42it/s, train/loss=4.400]
Epoch 0: |          | 456/? [03:08<00:00,  2.42it/s, train/loss=1.430]
Epoch 0: |          | 457/? [03:08<00:00,  2.43it/s, train/loss=1.430]
Epoch 0: |          | 457/? [03:08<00:00,  2.43it/s, train/loss=4.380]
Epoch 0: |          | 458/? [03:08<00:00,  2.43it/s, train/loss=4.380]
Epoch 0: |          | 458/? [03:08<00:00,  2.43it/s, train/loss=1.900]
Epoch 0: |          | 459/? [03:08<00:00,  2.43it/s, train/loss=1.900]
Epoch 0: |          | 459/? [03:08<00:00,  2.43it/s, train/loss=4.350]
Epoch 0: |          | 460/? [03:09<00:00,  2.43it/s, train/loss=4.350]
Epoch 0: |          | 460/? [03:09<00:00,  2.43it/s, train/loss=3.030]
Epoch 0: |          | 461/? [03:10<00:00,  2.42it/s, train/loss=3.030]
Epoch 0: |          | 461/? [03:10<00:00,  2.42it/s, train/loss=2.120]
Epoch 0: |          | 462/? [03:10<00:00,  2.43it/s, train/loss=2.120]
Epoch 0: |          | 462/? [03:10<00:00,  2.42it/s, train/loss=1.960]
Epoch 0: |          | 463/? [03:10<00:00,  2.43it/s, train/loss=1.960]
Epoch 0: |          | 463/? [03:10<00:00,  2.43it/s, train/loss=4.340]
Epoch 0: |          | 464/? [03:10<00:00,  2.43it/s, train/loss=4.340]
Epoch 0: |          | 464/? [03:10<00:00,  2.43it/s, train/loss=1.650]
Epoch 0: |          | 465/? [03:11<00:00,  2.43it/s, train/loss=1.650]
Epoch 0: |          | 465/? [03:11<00:00,  2.43it/s, train/loss=4.340]
Epoch 0: |          | 466/? [03:11<00:00,  2.43it/s, train/loss=4.340]
Epoch 0: |          | 466/? [03:11<00:00,  2.43it/s, train/loss=0.967]
Epoch 0: |          | 467/? [03:11<00:00,  2.44it/s, train/loss=0.967]
Epoch 0: |          | 467/? [03:11<00:00,  2.44it/s, train/loss=4.320]
Epoch 0: |          | 468/? [03:11<00:00,  2.44it/s, train/loss=4.320]
Epoch 0: |          | 468/? [03:11<00:00,  2.44it/s, train/loss=3.190]
Epoch 0: |          | 469/? [03:11<00:00,  2.44it/s, train/loss=3.190]
Epoch 0: |          | 469/? [03:11<00:00,  2.44it/s, train/loss=4.310]
Epoch 0: |          | 470/? [03:12<00:00,  2.44it/s, train/loss=4.310]
Epoch 0: |          | 470/? [03:12<00:00,  2.44it/s, train/loss=2.530]
Epoch 0: |          | 471/? [03:13<00:00,  2.44it/s, train/loss=2.530]
Epoch 0: |          | 471/? [03:13<00:00,  2.44it/s, train/loss=2.540]
Epoch 0: |          | 472/? [03:13<00:00,  2.44it/s, train/loss=2.540]
Epoch 0: |          | 472/? [03:13<00:00,  2.44it/s, train/loss=1.790]
Epoch 0: |          | 473/? [03:13<00:00,  2.44it/s, train/loss=1.790]
Epoch 0: |          | 473/? [03:13<00:00,  2.44it/s, train/loss=4.330]
Epoch 0: |          | 474/? [03:14<00:00,  2.44it/s, train/loss=4.330]
Epoch 0: |          | 474/? [03:14<00:00,  2.44it/s, train/loss=3.140]
Epoch 0: |          | 475/? [03:14<00:00,  2.45it/s, train/loss=3.140]
Epoch 0: |          | 475/? [03:14<00:00,  2.45it/s, train/loss=4.320]
Epoch 0: |          | 476/? [03:14<00:00,  2.45it/s, train/loss=4.320]
Epoch 0: |          | 476/? [03:14<00:00,  2.45it/s, train/loss=2.120]
Epoch 0: |          | 477/? [03:14<00:00,  2.45it/s, train/loss=2.120]
Epoch 0: |          | 477/? [03:14<00:00,  2.45it/s, train/loss=4.300]
Epoch 0: |          | 478/? [03:15<00:00,  2.45it/s, train/loss=4.300]
Epoch 0: |          | 478/? [03:15<00:00,  2.45it/s, train/loss=1.920]
Epoch 0: |          | 479/? [03:15<00:00,  2.46it/s, train/loss=1.920]
Epoch 0: |          | 479/? [03:15<00:00,  2.46it/s, train/loss=4.280]
Epoch 0: |          | 480/? [03:15<00:00,  2.46it/s, train/loss=4.280]
Epoch 0: |          | 480/? [03:15<00:00,  2.46it/s, train/loss=2.280]
Epoch 0: |          | 481/? [03:16<00:00,  2.45it/s, train/loss=2.280]
Epoch 0: |          | 481/? [03:16<00:00,  2.45it/s, train/loss=0.513]
Epoch 0: |          | 482/? [03:16<00:00,  2.45it/s, train/loss=0.513]
Epoch 0: |          | 482/? [03:16<00:00,  2.45it/s, train/loss=0.849]
Epoch 0: |          | 483/? [03:16<00:00,  2.45it/s, train/loss=0.849]
Epoch 0: |          | 483/? [03:16<00:00,  2.45it/s, train/loss=4.270]
Epoch 0: |          | 484/? [03:17<00:00,  2.45it/s, train/loss=4.270]
Epoch 0: |          | 484/? [03:17<00:00,  2.45it/s, train/loss=1.970]
Epoch 0: |          | 485/? [03:17<00:00,  2.46it/s, train/loss=1.970]
Epoch 0: |          | 485/? [03:17<00:00,  2.46it/s, train/loss=4.250]
Epoch 0: |          | 486/? [03:17<00:00,  2.46it/s, train/loss=4.250]
Epoch 0: |          | 486/? [03:17<00:00,  2.46it/s, train/loss=1.330]
Epoch 0: |          | 487/? [03:17<00:00,  2.46it/s, train/loss=1.330]
Epoch 0: |          | 487/? [03:17<00:00,  2.46it/s, train/loss=4.240]
Epoch 0: |          | 488/? [03:18<00:00,  2.46it/s, train/loss=4.240]
Epoch 0: |          | 488/? [03:18<00:00,  2.46it/s, train/loss=3.980]
Epoch 0: |          | 489/? [03:18<00:00,  2.47it/s, train/loss=3.980]
Epoch 0: |          | 489/? [03:18<00:00,  2.47it/s, train/loss=4.250]
Epoch 0: |          | 490/? [03:18<00:00,  2.47it/s, train/loss=4.250]
Epoch 0: |          | 490/? [03:18<00:00,  2.47it/s, train/loss=3.170]
Epoch 0: |          | 491/? [03:19<00:00,  2.46it/s, train/loss=3.170]
Epoch 0: |          | 491/? [03:19<00:00,  2.46it/s, train/loss=3.520]
Epoch 0: |          | 492/? [03:19<00:00,  2.46it/s, train/loss=3.520]
Epoch 0: |          | 492/? [03:19<00:00,  2.46it/s, train/loss=1.780]
Epoch 0: |          | 493/? [03:19<00:00,  2.47it/s, train/loss=1.780]
Epoch 0: |          | 493/? [03:19<00:00,  2.47it/s, train/loss=4.330]
Epoch 0: |          | 494/? [03:20<00:00,  2.47it/s, train/loss=4.330]
Epoch 0: |          | 494/? [03:20<00:00,  2.46it/s, train/loss=2.840]
Epoch 0: |          | 495/? [03:20<00:00,  2.47it/s, train/loss=2.840]
Epoch 0: |          | 495/? [03:20<00:00,  2.47it/s, train/loss=4.350]
Epoch 0: |          | 496/? [03:20<00:00,  2.47it/s, train/loss=4.350]
Epoch 0: |          | 496/? [03:20<00:00,  2.47it/s, train/loss=2.180]
Epoch 0: |          | 497/? [03:21<00:00,  2.47it/s, train/loss=2.180]
Epoch 0: |          | 497/? [03:21<00:00,  2.47it/s, train/loss=4.350]
Epoch 0: |          | 498/? [03:21<00:00,  2.47it/s, train/loss=4.350]
Epoch 0: |          | 498/? [03:21<00:00,  2.47it/s, train/loss=0.676]
Epoch 0: |          | 499/? [03:21<00:00,  2.48it/s, train/loss=0.676]
Epoch 0: |          | 499/? [03:21<00:00,  2.48it/s, train/loss=4.340]
Epoch 0: |          | 500/? [03:21<00:00,  2.48it/s, train/loss=4.340]
Epoch 0: |          | 500/? [03:21<00:00,  2.48it/s, train/loss=1.350]
Epoch 0: |          | 501/? [03:22<00:00,  2.47it/s, train/loss=1.350]
Epoch 0: |          | 501/? [03:22<00:00,  2.47it/s, train/loss=1.280]
Epoch 0: |          | 502/? [03:23<00:00,  2.47it/s, train/loss=1.280]
Epoch 0: |          | 502/? [03:23<00:00,  2.47it/s, train/loss=1.450]
Epoch 0: |          | 503/? [03:23<00:00,  2.47it/s, train/loss=1.450]
Epoch 0: |          | 503/? [03:23<00:00,  2.47it/s, train/loss=4.360]
Epoch 0: |          | 504/? [03:23<00:00,  2.47it/s, train/loss=4.360]
Epoch 0: |          | 504/? [03:23<00:00,  2.47it/s, train/loss=2.170]
Epoch 0: |          | 505/? [03:23<00:00,  2.48it/s, train/loss=2.170]
Epoch 0: |          | 505/? [03:23<00:00,  2.48it/s, train/loss=4.350]
Epoch 0: |          | 506/? [03:24<00:00,  2.48it/s, train/loss=4.350]
Epoch 0: |          | 506/? [03:24<00:00,  2.48it/s, train/loss=1.810]
Epoch 0: |          | 507/? [03:24<00:00,  2.48it/s, train/loss=1.810]
Epoch 0: |          | 507/? [03:24<00:00,  2.48it/s, train/loss=4.340]
Epoch 0: |          | 508/? [03:24<00:00,  2.48it/s, train/loss=4.340]
Epoch 0: |          | 508/? [03:24<00:00,  2.48it/s, train/loss=2.820]
Epoch 0: |          | 509/? [03:24<00:00,  2.49it/s, train/loss=2.820]
Epoch 0: |          | 509/? [03:24<00:00,  2.49it/s, train/loss=4.320]
Epoch 0: |          | 510/? [03:25<00:00,  2.49it/s, train/loss=4.320]
Epoch 0: |          | 510/? [03:25<00:00,  2.49it/s, train/loss=1.890]
Epoch 0: |          | 511/? [03:25<00:00,  2.48it/s, train/loss=1.890]
Epoch 0: |          | 511/? [03:26<00:00,  2.48it/s, train/loss=1.120]
Epoch 0: |          | 512/? [03:26<00:00,  2.48it/s, train/loss=1.120]
Epoch 0: |          | 512/? [03:26<00:00,  2.48it/s, train/loss=2.630]
Epoch 0: |          | 513/? [03:26<00:00,  2.49it/s, train/loss=2.630]
Epoch 0: |          | 513/? [03:26<00:00,  2.49it/s, train/loss=4.340]
Epoch 0: |          | 514/? [03:26<00:00,  2.49it/s, train/loss=4.340]
Epoch 0: |          | 514/? [03:26<00:00,  2.49it/s, train/loss=0.942]
Epoch 0: |          | 515/? [03:26<00:00,  2.49it/s, train/loss=0.942]
Epoch 0: |          | 515/? [03:26<00:00,  2.49it/s, train/loss=4.340]
Epoch 0: |          | 516/? [03:27<00:00,  2.49it/s, train/loss=4.340]
Epoch 0: |          | 516/? [03:27<00:00,  2.49it/s, train/loss=1.110]
Epoch 0: |          | 517/? [03:27<00:00,  2.49it/s, train/loss=1.110]
Epoch 0: |          | 517/? [03:27<00:00,  2.49it/s, train/loss=4.320]
Epoch 0: |          | 518/? [03:27<00:00,  2.49it/s, train/loss=4.320]
Epoch 0: |          | 518/? [03:27<00:00,  2.49it/s, train/loss=4.760]
Epoch 0: |          | 519/? [03:27<00:00,  2.50it/s, train/loss=4.760]
Epoch 0: |          | 519/? [03:27<00:00,  2.50it/s, train/loss=4.300]
Epoch 0: |          | 520/? [03:28<00:00,  2.50it/s, train/loss=4.300]
Epoch 0: |          | 520/? [03:28<00:00,  2.50it/s, train/loss=1.390]
Epoch 0: |          | 521/? [03:29<00:00,  2.49it/s, train/loss=1.390]
Epoch 0: |          | 521/? [03:29<00:00,  2.49it/s, train/loss=1.430]
Epoch 0: |          | 522/? [03:29<00:00,  2.49it/s, train/loss=1.430]
Epoch 0: |          | 522/? [03:29<00:00,  2.49it/s, train/loss=1.370]
Epoch 0: |          | 523/? [03:29<00:00,  2.50it/s, train/loss=1.370]
Epoch 0: |          | 523/? [03:29<00:00,  2.50it/s, train/loss=4.260]
Epoch 0: |          | 524/? [03:29<00:00,  2.50it/s, train/loss=4.260]
Epoch 0: |          | 524/? [03:29<00:00,  2.50it/s, train/loss=1.990]
Epoch 0: |          | 525/? [03:29<00:00,  2.50it/s, train/loss=1.990]
Epoch 0: |          | 525/? [03:29<00:00,  2.50it/s, train/loss=4.240]
Epoch 0: |          | 526/? [03:30<00:00,  2.50it/s, train/loss=4.240]
Epoch 0: |          | 526/? [03:30<00:00,  2.50it/s, train/loss=1.040]
Epoch 0: |          | 527/? [03:30<00:00,  2.50it/s, train/loss=1.040]
Epoch 0: |          | 527/? [03:30<00:00,  2.50it/s, train/loss=4.210]
Epoch 0: |          | 528/? [03:30<00:00,  2.50it/s, train/loss=4.210]
Epoch 0: |          | 528/? [03:30<00:00,  2.50it/s, train/loss=1.550]
Epoch 0: |          | 529/? [03:30<00:00,  2.51it/s, train/loss=1.550]
Epoch 0: |          | 529/? [03:30<00:00,  2.51it/s, train/loss=4.190]
Epoch 0: |          | 530/? [03:31<00:00,  2.51it/s, train/loss=4.190]
Epoch 0: |          | 530/? [03:31<00:00,  2.51it/s, train/loss=2.190]
Epoch 0: |          | 531/? [03:32<00:00,  2.50it/s, train/loss=2.190]
Epoch 0: |          | 531/? [03:32<00:00,  2.50it/s, train/loss=2.480]
Epoch 0: |          | 532/? [03:32<00:00,  2.50it/s, train/loss=2.480]
Epoch 0: |          | 532/? [03:32<00:00,  2.50it/s, train/loss=3.060]
Epoch 0: |          | 533/? [03:32<00:00,  2.51it/s, train/loss=3.060]
Epoch 0: |          | 533/? [03:32<00:00,  2.51it/s, train/loss=4.170]
Epoch 0: |          | 534/? [03:33<00:00,  2.51it/s, train/loss=4.170]
Epoch 0: |          | 534/? [03:33<00:00,  2.51it/s, train/loss=1.580]
Epoch 0: |          | 535/? [03:33<00:00,  2.51it/s, train/loss=1.580]
Epoch 0: |          | 535/? [03:33<00:00,  2.51it/s, train/loss=4.150]
Epoch 0: |          | 536/? [03:33<00:00,  2.51it/s, train/loss=4.150]
Epoch 0: |          | 536/? [03:33<00:00,  2.51it/s, train/loss=2.330]
Epoch 0: |          | 537/? [03:33<00:00,  2.51it/s, train/loss=2.330]
Epoch 0: |          | 537/? [03:33<00:00,  2.51it/s, train/loss=4.130]
Epoch 0: |          | 538/? [03:33<00:00,  2.51it/s, train/loss=4.130]
Epoch 0: |          | 538/? [03:33<00:00,  2.51it/s, train/loss=1.740]
Epoch 0: |          | 539/? [03:34<00:00,  2.52it/s, train/loss=1.740]
Epoch 0: |          | 539/? [03:34<00:00,  2.52it/s, train/loss=4.120]
Epoch 0: |          | 540/? [03:34<00:00,  2.52it/s, train/loss=4.120]
Epoch 0: |          | 540/? [03:34<00:00,  2.52it/s, train/loss=2.130]
Epoch 0: |          | 541/? [03:35<00:00,  2.51it/s, train/loss=2.130]
Epoch 0: |          | 541/? [03:35<00:00,  2.51it/s, train/loss=2.980]
Epoch 0: |          | 542/? [03:35<00:00,  2.51it/s, train/loss=2.980]
Epoch 0: |          | 542/? [03:35<00:00,  2.51it/s, train/loss=1.930]
Epoch 0: |          | 543/? [03:35<00:00,  2.52it/s, train/loss=1.930]
Epoch 0: |          | 543/? [03:35<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 544/? [03:36<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 544/? [03:36<00:00,  2.52it/s, train/loss=2.970]
Epoch 0: |          | 545/? [03:36<00:00,  2.52it/s, train/loss=2.970]
Epoch 0: |          | 545/? [03:36<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 546/? [03:36<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 546/? [03:36<00:00,  2.52it/s, train/loss=1.780]
Epoch 0: |          | 547/? [03:36<00:00,  2.52it/s, train/loss=1.780]
Epoch 0: |          | 547/? [03:36<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 548/? [03:37<00:00,  2.52it/s, train/loss=4.130]
Epoch 0: |          | 548/? [03:37<00:00,  2.52it/s, train/loss=2.270]
Epoch 0: |          | 549/? [03:37<00:00,  2.53it/s, train/loss=2.270]
Epoch 0: |          | 549/? [03:37<00:00,  2.53it/s, train/loss=4.110]
Epoch 0: |          | 550/? [03:37<00:00,  2.53it/s, train/loss=4.110]
Epoch 0: |          | 550/? [03:37<00:00,  2.53it/s, train/loss=2.440]
Epoch 0: |          | 551/? [03:38<00:00,  2.52it/s, train/loss=2.440]
Epoch 0: |          | 551/? [03:38<00:00,  2.52it/s, train/loss=2.390]
Epoch 0: |          | 552/? [03:38<00:00,  2.52it/s, train/loss=2.390]
Epoch 0: |          | 552/? [03:38<00:00,  2.52it/s, train/loss=1.130]
Epoch 0: |          | 553/? [03:38<00:00,  2.53it/s, train/loss=1.130]
Epoch 0: |          | 553/? [03:38<00:00,  2.53it/s, train/loss=4.110]
Epoch 0: |          | 554/? [03:39<00:00,  2.53it/s, train/loss=4.110]
Epoch 0: |          | 554/? [03:39<00:00,  2.53it/s, train/loss=0.801]
Epoch 0: |          | 555/? [03:39<00:00,  2.53it/s, train/loss=0.801]
Epoch 0: |          | 555/? [03:39<00:00,  2.53it/s, train/loss=4.090]
Epoch 0: |          | 556/? [03:39<00:00,  2.53it/s, train/loss=4.090]
Epoch 0: |          | 556/? [03:39<00:00,  2.53it/s, train/loss=3.380]
Epoch 0: |          | 557/? [03:39<00:00,  2.53it/s, train/loss=3.380]
Epoch 0: |          | 557/? [03:39<00:00,  2.53it/s, train/loss=4.070]
Epoch 0: |          | 558/? [03:40<00:00,  2.53it/s, train/loss=4.070]
Epoch 0: |          | 558/? [03:40<00:00,  2.53it/s, train/loss=2.010]
Epoch 0: |          | 559/? [03:40<00:00,  2.54it/s, train/loss=2.010]
Epoch 0: |          | 559/? [03:40<00:00,  2.54it/s, train/loss=4.050]
Epoch 0: |          | 560/? [03:40<00:00,  2.54it/s, train/loss=4.050]
Epoch 0: |          | 560/? [03:40<00:00,  2.54it/s, train/loss=1.340]
Epoch 0: |          | 561/? [03:41<00:00,  2.53it/s, train/loss=1.340]
Epoch 0: |          | 561/? [03:41<00:00,  2.53it/s, train/loss=2.310]
Epoch 0: |          | 562/? [03:42<00:00,  2.53it/s, train/loss=2.310]
Epoch 0: |          | 562/? [03:42<00:00,  2.53it/s, train/loss=0.956]
Epoch 0: |          | 563/? [03:42<00:00,  2.53it/s, train/loss=0.956]
Epoch 0: |          | 563/? [03:42<00:00,  2.53it/s, train/loss=4.030]
Epoch 0: |          | 564/? [03:42<00:00,  2.53it/s, train/loss=4.030]
Epoch 0: |          | 564/? [03:42<00:00,  2.53it/s, train/loss=3.390]
Epoch 0: |          | 565/? [03:42<00:00,  2.54it/s, train/loss=3.390]
Epoch 0: |          | 565/? [03:42<00:00,  2.54it/s, train/loss=4.010]
Epoch 0: |          | 566/? [03:43<00:00,  2.54it/s, train/loss=4.010]
Epoch 0: |          | 566/? [03:43<00:00,  2.54it/s, train/loss=2.930]
Epoch 0: |          | 567/? [03:43<00:00,  2.54it/s, train/loss=2.930]
Epoch 0: |          | 567/? [03:43<00:00,  2.54it/s, train/loss=4.000]
Epoch 0: |          | 568/? [03:43<00:00,  2.54it/s, train/loss=4.000]
Epoch 0: |          | 568/? [03:43<00:00,  2.54it/s, train/loss=2.650]
Epoch 0: |          | 569/? [03:43<00:00,  2.55it/s, train/loss=2.650]
Epoch 0: |          | 569/? [03:43<00:00,  2.55it/s, train/loss=3.990]
Epoch 0: |          | 570/? [03:43<00:00,  2.55it/s, train/loss=3.990]
Epoch 0: |          | 570/? [03:43<00:00,  2.55it/s, train/loss=0.636]
Epoch 0: |          | 571/? [03:44<00:00,  2.54it/s, train/loss=0.636]
Epoch 0: |          | 571/? [03:44<00:00,  2.54it/s, train/loss=1.320]
Epoch 0: |          | 572/? [03:45<00:00,  2.54it/s, train/loss=1.320]
Epoch 0: |          | 572/? [03:45<00:00,  2.54it/s, train/loss=0.937]
Epoch 0: |          | 573/? [03:45<00:00,  2.54it/s, train/loss=0.937]
Epoch 0: |          | 573/? [03:45<00:00,  2.54it/s, train/loss=4.000]
Epoch 0: |          | 574/? [03:45<00:00,  2.54it/s, train/loss=4.000]
Epoch 0: |          | 574/? [03:45<00:00,  2.54it/s, train/loss=0.672]
Epoch 0: |          | 575/? [03:45<00:00,  2.55it/s, train/loss=0.672]
Epoch 0: |          | 575/? [03:45<00:00,  2.55it/s, train/loss=3.980]
Epoch 0: |          | 576/? [03:46<00:00,  2.55it/s, train/loss=3.980]
Epoch 0: |          | 576/? [03:46<00:00,  2.55it/s, train/loss=2.170]
Epoch 0: |          | 577/? [03:46<00:00,  2.55it/s, train/loss=2.170]
Epoch 0: |          | 577/? [03:46<00:00,  2.55it/s, train/loss=3.970]
Epoch 0: |          | 578/? [03:46<00:00,  2.55it/s, train/loss=3.970]
Epoch 0: |          | 578/? [03:46<00:00,  2.55it/s, train/loss=1.480]
Epoch 0: |          | 579/? [03:46<00:00,  2.55it/s, train/loss=1.480]
Epoch 0: |          | 579/? [03:46<00:00,  2.55it/s, train/loss=3.960]
Epoch 0: |          | 580/? [03:47<00:00,  2.55it/s, train/loss=3.960]
Epoch 0: |          | 580/? [03:47<00:00,  2.55it/s, train/loss=3.060]
Epoch 0: |          | 581/? [03:47<00:00,  2.55it/s, train/loss=3.060]
Epoch 0: |          | 581/? [03:48<00:00,  2.55it/s, train/loss=2.920]
Epoch 0: |          | 582/? [03:48<00:00,  2.55it/s, train/loss=2.920]
Epoch 0: |          | 582/? [03:48<00:00,  2.55it/s, train/loss=0.917]
Epoch 0: |          | 583/? [03:48<00:00,  2.55it/s, train/loss=0.917]
Epoch 0: |          | 583/? [03:48<00:00,  2.55it/s, train/loss=3.960]
Epoch 0: |          | 584/? [03:48<00:00,  2.55it/s, train/loss=3.960]
Epoch 0: |          | 584/? [03:48<00:00,  2.55it/s, train/loss=2.450]
Epoch 0: |          | 585/? [03:49<00:00,  2.55it/s, train/loss=2.450]
Epoch 0: |          | 585/? [03:49<00:00,  2.55it/s, train/loss=3.950]
Epoch 0: |          | 586/? [03:49<00:00,  2.55it/s, train/loss=3.950]
Epoch 0: |          | 586/? [03:49<00:00,  2.55it/s, train/loss=2.180]
Epoch 0: |          | 587/? [03:49<00:00,  2.56it/s, train/loss=2.180]
Epoch 0: |          | 587/? [03:49<00:00,  2.56it/s, train/loss=3.920]
Epoch 0: |          | 588/? [03:49<00:00,  2.56it/s, train/loss=3.920]
Epoch 0: |          | 588/? [03:49<00:00,  2.56it/s, train/loss=2.390]
Epoch 0: |          | 589/? [03:49<00:00,  2.56it/s, train/loss=2.390]
Epoch 0: |          | 589/? [03:49<00:00,  2.56it/s, train/loss=3.920]
Epoch 0: |          | 590/? [03:50<00:00,  2.56it/s, train/loss=3.920]
Epoch 0: |          | 590/? [03:50<00:00,  2.56it/s, train/loss=3.030]
Epoch 0: |          | 591/? [03:51<00:00,  2.56it/s, train/loss=3.030]
Epoch 0: |          | 591/? [03:51<00:00,  2.56it/s, train/loss=1.200]
Epoch 0: |          | 592/? [03:51<00:00,  2.56it/s, train/loss=1.200]
Epoch 0: |          | 592/? [03:51<00:00,  2.56it/s, train/loss=0.798]
Epoch 0: |          | 593/? [03:51<00:00,  2.56it/s, train/loss=0.798]
Epoch 0: |          | 593/? [03:51<00:00,  2.56it/s, train/loss=3.990]
Epoch 0: |          | 594/? [03:52<00:00,  2.56it/s, train/loss=3.990]
Epoch 0: |          | 594/? [03:52<00:00,  2.56it/s, train/loss=1.160]
Epoch 0: |          | 595/? [03:52<00:00,  2.56it/s, train/loss=1.160]
Epoch 0: |          | 595/? [03:52<00:00,  2.56it/s, train/loss=4.010]
Epoch 0: |          | 596/? [03:52<00:00,  2.56it/s, train/loss=4.010]
Epoch 0: |          | 596/? [03:52<00:00,  2.56it/s, train/loss=3.640]
Epoch 0: |          | 597/? [03:52<00:00,  2.57it/s, train/loss=3.640]
Epoch 0: |          | 597/? [03:52<00:00,  2.57it/s, train/loss=4.010]
Epoch 0: |          | 598/? [03:53<00:00,  2.57it/s, train/loss=4.010]
Epoch 0: |          | 598/? [03:53<00:00,  2.57it/s, train/loss=2.290]
Epoch 0: |          | 599/? [03:53<00:00,  2.57it/s, train/loss=2.290]
Epoch 0: |          | 599/? [03:53<00:00,  2.57it/s, train/loss=4.020]
Epoch 0: |          | 600/? [03:53<00:00,  2.57it/s, train/loss=4.020]
Epoch 0: |          | 600/? [03:53<00:00,  2.57it/s, train/loss=2.900]
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Epoch 0: |          | 600/? [04:04<00:00,  2.46it/s, train/loss=2.900]
Epoch 0: |          | 601/? [04:19<00:00,  2.31it/s, train/loss=2.900]
Epoch 0: |          | 601/? [04:19<00:00,  2.31it/s, train/loss=1.340]
Epoch 0: |          | 602/? [04:19<00:00,  2.32it/s, train/loss=1.340]
Epoch 0: |          | 602/? [04:20<00:00,  2.32it/s, train/loss=1.860]
Epoch 0: |          | 603/? [04:20<00:00,  2.32it/s, train/loss=1.860]
Epoch 0: |          | 603/? [04:20<00:00,  2.32it/s, train/loss=4.060]
Epoch 0: |          | 604/? [04:20<00:00,  2.32it/s, train/loss=4.060]
Epoch 0: |          | 604/? [04:20<00:00,  2.32it/s, train/loss=2.570]
Epoch 0: |          | 605/? [04:20<00:00,  2.32it/s, train/loss=2.570]
Epoch 0: |          | 605/? [04:20<00:00,  2.32it/s, train/loss=4.070]
Epoch 0: |          | 606/? [04:20<00:00,  2.32it/s, train/loss=4.070]
Epoch 0: |          | 606/? [04:20<00:00,  2.32it/s, train/loss=3.590]
Epoch 0: |          | 607/? [04:20<00:00,  2.33it/s, train/loss=3.590]
Epoch 0: |          | 607/? [04:20<00:00,  2.33it/s, train/loss=4.070]
Epoch 0: |          | 608/? [04:21<00:00,  2.33it/s, train/loss=4.070]
Epoch 0: |          | 608/? [04:21<00:00,  2.33it/s, train/loss=3.050]
Epoch 0: |          | 609/? [04:21<00:00,  2.33it/s, train/loss=3.050]
Epoch 0: |          | 609/? [04:21<00:00,  2.33it/s, train/loss=4.060]
Epoch 0: |          | 610/? [04:21<00:00,  2.33it/s, train/loss=4.060]
Epoch 0: |          | 610/? [04:21<00:00,  2.33it/s, train/loss=1.530]
Epoch 0: |          | 611/? [04:22<00:00,  2.33it/s, train/loss=1.530]
Epoch 0: |          | 611/? [04:22<00:00,  2.32it/s, train/loss=1.450]
Epoch 0: |          | 612/? [04:23<00:00,  2.33it/s, train/loss=1.450]
Epoch 0: |          | 612/? [04:23<00:00,  2.33it/s, train/loss=1.410]
Epoch 0: |          | 613/? [04:23<00:00,  2.33it/s, train/loss=1.410]
Epoch 0: |          | 613/? [04:23<00:00,  2.33it/s, train/loss=4.070]
Epoch 0: |          | 614/? [04:23<00:00,  2.33it/s, train/loss=4.070]
Epoch 0: |          | 614/? [04:23<00:00,  2.33it/s, train/loss=2.290]
Epoch 0: |          | 615/? [04:23<00:00,  2.33it/s, train/loss=2.290]
Epoch 0: |          | 615/? [04:23<00:00,  2.33it/s, train/loss=4.050]
Epoch 0: |          | 616/? [04:24<00:00,  2.33it/s, train/loss=4.050]
Epoch 0: |          | 616/? [04:24<00:00,  2.33it/s, train/loss=2.550]
Epoch 0: |          | 617/? [04:24<00:00,  2.34it/s, train/loss=2.550]
Epoch 0: |          | 617/? [04:24<00:00,  2.34it/s, train/loss=4.010]
Epoch 0: |          | 618/? [04:24<00:00,  2.34it/s, train/loss=4.010]
Epoch 0: |          | 618/? [04:24<00:00,  2.34it/s, train/loss=2.220]
Epoch 0: |          | 619/? [04:24<00:00,  2.34it/s, train/loss=2.220]
Epoch 0: |          | 619/? [04:24<00:00,  2.34it/s, train/loss=3.990]
Epoch 0: |          | 620/? [04:25<00:00,  2.34it/s, train/loss=3.990]
Epoch 0: |          | 620/? [04:25<00:00,  2.34it/s, train/loss=0.898]
Epoch 0: |          | 621/? [04:25<00:00,  2.33it/s, train/loss=0.898]
Epoch 0: |          | 621/? [04:26<00:00,  2.33it/s, train/loss=1.590]
Epoch 0: |          | 622/? [04:26<00:00,  2.34it/s, train/loss=1.590]
Epoch 0: |          | 622/? [04:26<00:00,  2.34it/s, train/loss=0.873]
Epoch 0: |          | 623/? [04:26<00:00,  2.34it/s, train/loss=0.873]
Epoch 0: |          | 623/? [04:26<00:00,  2.34it/s, train/loss=3.970]
Epoch 0: |          | 624/? [04:26<00:00,  2.34it/s, train/loss=3.970]
Epoch 0: |          | 624/? [04:26<00:00,  2.34it/s, train/loss=2.080]
Epoch 0: |          | 625/? [04:26<00:00,  2.34it/s, train/loss=2.080]
Epoch 0: |          | 625/? [04:26<00:00,  2.34it/s, train/loss=3.940]
Epoch 0: |          | 626/? [04:27<00:00,  2.34it/s, train/loss=3.940]
Epoch 0: |          | 626/? [04:27<00:00,  2.34it/s, train/loss=2.700]
Epoch 0: |          | 627/? [04:27<00:00,  2.35it/s, train/loss=2.700]
Epoch 0: |          | 627/? [04:27<00:00,  2.35it/s, train/loss=3.920]
Epoch 0: |          | 628/? [04:27<00:00,  2.35it/s, train/loss=3.920]
Epoch 0: |          | 628/? [04:27<00:00,  2.35it/s, train/loss=1.280]
Epoch 0: |          | 629/? [04:27<00:00,  2.35it/s, train/loss=1.280]
Epoch 0: |          | 629/? [04:27<00:00,  2.35it/s, train/loss=3.910]
Epoch 0: |          | 630/? [04:28<00:00,  2.35it/s, train/loss=3.910]
Epoch 0: |          | 630/? [04:28<00:00,  2.35it/s, train/loss=1.190]
Epoch 0: |          | 631/? [04:29<00:00,  2.35it/s, train/loss=1.190]
Epoch 0: |          | 631/? [04:29<00:00,  2.34it/s, train/loss=0.802]
Epoch 0: |          | 632/? [04:29<00:00,  2.35it/s, train/loss=0.802]
Epoch 0: |          | 632/? [04:29<00:00,  2.35it/s, train/loss=1.520]
Epoch 0: |          | 633/? [04:29<00:00,  2.35it/s, train/loss=1.520]
Epoch 0: |          | 633/? [04:29<00:00,  2.35it/s, train/loss=3.940]
Epoch 0: |          | 634/? [04:29<00:00,  2.35it/s, train/loss=3.940]
Epoch 0: |          | 634/? [04:29<00:00,  2.35it/s, train/loss=3.810]
Epoch 0: |          | 635/? [04:29<00:00,  2.35it/s, train/loss=3.810]
Epoch 0: |          | 635/? [04:29<00:00,  2.35it/s, train/loss=3.930]
Epoch 0: |          | 636/? [04:30<00:00,  2.35it/s, train/loss=3.930]
Epoch 0: |          | 636/? [04:30<00:00,  2.35it/s, train/loss=2.680]
Epoch 0: |          | 637/? [04:30<00:00,  2.36it/s, train/loss=2.680]
Epoch 0: |          | 637/? [04:30<00:00,  2.36it/s, train/loss=3.910]
Epoch 0: |          | 638/? [04:30<00:00,  2.36it/s, train/loss=3.910]
Epoch 0: |          | 638/? [04:30<00:00,  2.36it/s, train/loss=2.430]
Epoch 0: |          | 639/? [04:30<00:00,  2.36it/s, train/loss=2.430]
Epoch 0: |          | 639/? [04:30<00:00,  2.36it/s, train/loss=3.890]
Epoch 0: |          | 640/? [04:31<00:00,  2.36it/s, train/loss=3.890]
Epoch 0: |          | 640/? [04:31<00:00,  2.36it/s, train/loss=3.000]
Epoch 0: |          | 641/? [04:32<00:00,  2.36it/s, train/loss=3.000]
Epoch 0: |          | 641/? [04:32<00:00,  2.35it/s, train/loss=0.737]
Epoch 0: |          | 642/? [04:32<00:00,  2.36it/s, train/loss=0.737]
Epoch 0: |          | 642/? [04:32<00:00,  2.36it/s, train/loss=1.870]
Epoch 0: |          | 643/? [04:32<00:00,  2.36it/s, train/loss=1.870]
Epoch 0: |          | 643/? [04:32<00:00,  2.36it/s, train/loss=3.870]
Epoch 0: |          | 644/? [04:33<00:00,  2.36it/s, train/loss=3.870]
Epoch 0: |          | 644/? [04:33<00:00,  2.36it/s, train/loss=2.900]
Epoch 0: |          | 645/? [04:33<00:00,  2.36it/s, train/loss=2.900]
Epoch 0: |          | 645/? [04:33<00:00,  2.36it/s, train/loss=3.850]
Epoch 0: |          | 646/? [04:33<00:00,  2.36it/s, train/loss=3.850]
Epoch 0: |          | 646/? [04:33<00:00,  2.36it/s, train/loss=2.790]
Epoch 0: |          | 647/? [04:33<00:00,  2.37it/s, train/loss=2.790]
Epoch 0: |          | 647/? [04:33<00:00,  2.37it/s, train/loss=3.830]
Epoch 0: |          | 648/? [04:33<00:00,  2.37it/s, train/loss=3.830]
Epoch 0: |          | 648/? [04:33<00:00,  2.37it/s, train/loss=3.090]
Epoch 0: |          | 649/? [04:33<00:00,  2.37it/s, train/loss=3.090]
Epoch 0: |          | 649/? [04:34<00:00,  2.37it/s, train/loss=3.810]
Epoch 0: |          | 650/? [04:34<00:00,  2.37it/s, train/loss=3.810]
Epoch 0: |          | 650/? [04:34<00:00,  2.37it/s, train/loss=5.800]
Epoch 0: |          | 651/? [04:35<00:00,  2.36it/s, train/loss=5.800]
Epoch 0: |          | 651/? [04:35<00:00,  2.36it/s, train/loss=1.430]
Epoch 0: |          | 652/? [04:35<00:00,  2.36it/s, train/loss=1.430]
Epoch 0: |          | 652/? [04:35<00:00,  2.36it/s, train/loss=0.542]
Epoch 0: |          | 653/? [04:35<00:00,  2.37it/s, train/loss=0.542]
Epoch 0: |          | 653/? [04:35<00:00,  2.37it/s, train/loss=3.840]
Epoch 0: |          | 654/? [04:36<00:00,  2.37it/s, train/loss=3.840]
Epoch 0: |          | 654/? [04:36<00:00,  2.37it/s, train/loss=1.890]
Epoch 0: |          | 655/? [04:36<00:00,  2.37it/s, train/loss=1.890]
Epoch 0: |          | 655/? [04:36<00:00,  2.37it/s, train/loss=3.850]
Epoch 0: |          | 656/? [04:36<00:00,  2.37it/s, train/loss=3.850]
Epoch 0: |          | 656/? [04:36<00:00,  2.37it/s, train/loss=1.940]
Epoch 0: |          | 657/? [04:36<00:00,  2.37it/s, train/loss=1.940]
Epoch 0: |          | 657/? [04:36<00:00,  2.37it/s, train/loss=3.850]
Epoch 0: |          | 658/? [04:37<00:00,  2.37it/s, train/loss=3.850]
Epoch 0: |          | 658/? [04:37<00:00,  2.37it/s, train/loss=2.310]
Epoch 0: |          | 659/? [04:37<00:00,  2.38it/s, train/loss=2.310]
Epoch 0: |          | 659/? [04:37<00:00,  2.38it/s, train/loss=3.850]
Epoch 0: |          | 660/? [04:37<00:00,  2.38it/s, train/loss=3.850]
Epoch 0: |          | 660/? [04:37<00:00,  2.38it/s, train/loss=3.240]
Epoch 0: |          | 661/? [04:38<00:00,  2.37it/s, train/loss=3.240]
Epoch 0: |          | 661/? [04:38<00:00,  2.37it/s, train/loss=1.370]
Epoch 0: |          | 662/? [04:38<00:00,  2.37it/s, train/loss=1.370]
Epoch 0: |          | 662/? [04:38<00:00,  2.37it/s, train/loss=0.638]
Epoch 0: |          | 663/? [04:38<00:00,  2.38it/s, train/loss=0.638]
Epoch 0: |          | 663/? [04:38<00:00,  2.38it/s, train/loss=3.890]
Epoch 0: |          | 664/? [04:39<00:00,  2.38it/s, train/loss=3.890]
Epoch 0: |          | 664/? [04:39<00:00,  2.38it/s, train/loss=2.390]
Epoch 0: |          | 665/? [04:39<00:00,  2.38it/s, train/loss=2.390]
Epoch 0: |          | 665/? [04:39<00:00,  2.38it/s, train/loss=3.900]
Epoch 0: |          | 666/? [04:39<00:00,  2.38it/s, train/loss=3.900]
Epoch 0: |          | 666/? [04:39<00:00,  2.38it/s, train/loss=1.330]
Epoch 0: |          | 667/? [04:39<00:00,  2.38it/s, train/loss=1.330]
Epoch 0: |          | 667/? [04:39<00:00,  2.38it/s, train/loss=3.870]
Epoch 0: |          | 668/? [04:40<00:00,  2.38it/s, train/loss=3.870]
Epoch 0: |          | 668/? [04:40<00:00,  2.38it/s, train/loss=2.550]
Epoch 0: |          | 669/? [04:40<00:00,  2.39it/s, train/loss=2.550]
Epoch 0: |          | 669/? [04:40<00:00,  2.39it/s, train/loss=3.870]
Epoch 0: |          | 670/? [04:40<00:00,  2.39it/s, train/loss=3.870]
Epoch 0: |          | 670/? [04:40<00:00,  2.39it/s, train/loss=1.670]
Epoch 0: |          | 671/? [04:41<00:00,  2.38it/s, train/loss=1.670]
Epoch 0: |          | 671/? [04:41<00:00,  2.38it/s, train/loss=0.788]
Epoch 0: |          | 672/? [04:41<00:00,  2.38it/s, train/loss=0.788]
Epoch 0: |          | 672/? [04:42<00:00,  2.38it/s, train/loss=1.160]
Epoch 0: |          | 673/? [04:42<00:00,  2.39it/s, train/loss=1.160]
Epoch 0: |          | 673/? [04:42<00:00,  2.39it/s, train/loss=3.890]
Epoch 0: |          | 674/? [04:42<00:00,  2.39it/s, train/loss=3.890]
Epoch 0: |          | 674/? [04:42<00:00,  2.39it/s, train/loss=1.260]
Epoch 0: |          | 675/? [04:42<00:00,  2.39it/s, train/loss=1.260]
Epoch 0: |          | 675/? [04:42<00:00,  2.39it/s, train/loss=3.880]
Epoch 0: |          | 676/? [04:42<00:00,  2.39it/s, train/loss=3.880]
Epoch 0: |          | 676/? [04:42<00:00,  2.39it/s, train/loss=3.090]
Epoch 0: |          | 677/? [04:43<00:00,  2.39it/s, train/loss=3.090]
Epoch 0: |          | 677/? [04:43<00:00,  2.39it/s, train/loss=3.870]
Epoch 0: |          | 678/? [04:43<00:00,  2.39it/s, train/loss=3.870]
Epoch 0: |          | 678/? [04:43<00:00,  2.39it/s, train/loss=3.090]
Epoch 0: |          | 679/? [04:43<00:00,  2.40it/s, train/loss=3.090]
Epoch 0: |          | 679/? [04:43<00:00,  2.40it/s, train/loss=3.850]
Epoch 0: |          | 680/? [04:43<00:00,  2.40it/s, train/loss=3.850]
Epoch 0: |          | 680/? [04:43<00:00,  2.40it/s, train/loss=2.110]
Epoch 0: |          | 681/? [04:44<00:00,  2.39it/s, train/loss=2.110]
Epoch 0: |          | 681/? [04:44<00:00,  2.39it/s, train/loss=0.638]
Epoch 0: |          | 682/? [04:45<00:00,  2.39it/s, train/loss=0.638]
Epoch 0: |          | 682/? [04:45<00:00,  2.39it/s, train/loss=1.190]
Epoch 0: |          | 683/? [04:45<00:00,  2.39it/s, train/loss=1.190]
Epoch 0: |          | 683/? [04:45<00:00,  2.39it/s, train/loss=3.870]
Epoch 0: |          | 684/? [04:45<00:00,  2.40it/s, train/loss=3.870]
Epoch 0: |          | 684/? [04:45<00:00,  2.40it/s, train/loss=2.190]
Epoch 0: |          | 685/? [04:45<00:00,  2.40it/s, train/loss=2.190]
Epoch 0: |          | 685/? [04:45<00:00,  2.40it/s, train/loss=3.850]
Epoch 0: |          | 686/? [04:46<00:00,  2.40it/s, train/loss=3.850]
Epoch 0: |          | 686/? [04:46<00:00,  2.40it/s, train/loss=2.970]
Epoch 0: |          | 687/? [04:46<00:00,  2.40it/s, train/loss=2.970]
Epoch 0: |          | 687/? [04:46<00:00,  2.40it/s, train/loss=3.830]
Epoch 0: |          | 688/? [04:46<00:00,  2.40it/s, train/loss=3.830]
Epoch 0: |          | 688/? [04:46<00:00,  2.40it/s, train/loss=3.460]
Epoch 0: |          | 689/? [04:46<00:00,  2.40it/s, train/loss=3.460]
Epoch 0: |          | 689/? [04:46<00:00,  2.40it/s, train/loss=3.830]
Epoch 0: |          | 690/? [04:46<00:00,  2.40it/s, train/loss=3.830]
Epoch 0: |          | 690/? [04:46<00:00,  2.40it/s, train/loss=3.190]
Epoch 0: |          | 691/? [04:47<00:00,  2.40it/s, train/loss=3.190]
Epoch 0: |          | 691/? [04:47<00:00,  2.40it/s, train/loss=5.260]
Epoch 0: |          | 692/? [04:48<00:00,  2.40it/s, train/loss=5.260]
Epoch 0: |          | 692/? [04:48<00:00,  2.40it/s, train/loss=1.940]
Epoch 0: |          | 693/? [04:48<00:00,  2.40it/s, train/loss=1.940]
Epoch 0: |          | 693/? [04:48<00:00,  2.40it/s, train/loss=3.870]
Epoch 0: |          | 694/? [04:48<00:00,  2.40it/s, train/loss=3.870]
Epoch 0: |          | 694/? [04:48<00:00,  2.40it/s, train/loss=1.400]
Epoch 0: |          | 695/? [04:48<00:00,  2.41it/s, train/loss=1.400]
Epoch 0: |          | 695/? [04:48<00:00,  2.41it/s, train/loss=3.880]
Epoch 0: |          | 696/? [04:49<00:00,  2.41it/s, train/loss=3.880]
Epoch 0: |          | 696/? [04:49<00:00,  2.41it/s, train/loss=3.600]
Epoch 0: |          | 697/? [04:49<00:00,  2.41it/s, train/loss=3.600]
Epoch 0: |          | 697/? [04:49<00:00,  2.41it/s, train/loss=3.870]
Epoch 0: |          | 698/? [04:49<00:00,  2.41it/s, train/loss=3.870]
Epoch 0: |          | 698/? [04:49<00:00,  2.41it/s, train/loss=0.728]
Epoch 0: |          | 699/? [04:49<00:00,  2.41it/s, train/loss=0.728]
Epoch 0: |          | 699/? [04:49<00:00,  2.41it/s, train/loss=3.880]
Epoch 0: |          | 700/? [04:50<00:00,  2.41it/s, train/loss=3.880]
Epoch 0: |          | 700/? [04:50<00:00,  2.41it/s, train/loss=4.150]
Epoch 0: |          | 701/? [04:50<00:00,  2.41it/s, train/loss=4.150]
Epoch 0: |          | 701/? [04:51<00:00,  2.41it/s, train/loss=3.100]
Epoch 0: |          | 702/? [04:51<00:00,  2.41it/s, train/loss=3.100]
Epoch 0: |          | 702/? [04:51<00:00,  2.41it/s, train/loss=1.620]
Epoch 0: |          | 703/? [04:51<00:00,  2.41it/s, train/loss=1.620]
Epoch 0: |          | 703/? [04:51<00:00,  2.41it/s, train/loss=3.910]
Epoch 0: |          | 704/? [04:51<00:00,  2.41it/s, train/loss=3.910]
Epoch 0: |          | 704/? [04:51<00:00,  2.41it/s, train/loss=2.630]
Epoch 0: |          | 705/? [04:51<00:00,  2.42it/s, train/loss=2.630]
Epoch 0: |          | 705/? [04:51<00:00,  2.42it/s, train/loss=3.910]
Epoch 0: |          | 706/? [04:52<00:00,  2.42it/s, train/loss=3.910]
Epoch 0: |          | 706/? [04:52<00:00,  2.42it/s, train/loss=2.230]
Epoch 0: |          | 707/? [04:52<00:00,  2.42it/s, train/loss=2.230]
Epoch 0: |          | 707/? [04:52<00:00,  2.42it/s, train/loss=3.910]
Epoch 0: |          | 708/? [04:52<00:00,  2.42it/s, train/loss=3.910]
Epoch 0: |          | 708/? [04:52<00:00,  2.42it/s, train/loss=1.250]
Epoch 0: |          | 709/? [04:52<00:00,  2.42it/s, train/loss=1.250]
Epoch 0: |          | 709/? [04:52<00:00,  2.42it/s, train/loss=3.920]
Epoch 0: |          | 710/? [04:53<00:00,  2.42it/s, train/loss=3.920]
Epoch 0: |          | 710/? [04:53<00:00,  2.42it/s, train/loss=4.350]
Epoch 0: |          | 711/? [04:54<00:00,  2.42it/s, train/loss=4.350]
Epoch 0: |          | 711/? [04:54<00:00,  2.42it/s, train/loss=1.360]
Epoch 0: |          | 712/? [04:54<00:00,  2.42it/s, train/loss=1.360]
Epoch 0: |          | 712/? [04:54<00:00,  2.42it/s, train/loss=0.907]
Epoch 0: |          | 713/? [04:54<00:00,  2.42it/s, train/loss=0.907]
Epoch 0: |          | 713/? [04:54<00:00,  2.42it/s, train/loss=3.970]
Epoch 0: |          | 714/? [04:54<00:00,  2.42it/s, train/loss=3.970]
Epoch 0: |          | 714/? [04:54<00:00,  2.42it/s, train/loss=1.470]
Epoch 0: |          | 715/? [04:54<00:00,  2.42it/s, train/loss=1.470]
Epoch 0: |          | 715/? [04:54<00:00,  2.42it/s, train/loss=3.970]
Epoch 0: |          | 716/? [04:55<00:00,  2.42it/s, train/loss=3.970]
Epoch 0: |          | 716/? [04:55<00:00,  2.42it/s, train/loss=3.030]
Epoch 0: |          | 717/? [04:55<00:00,  2.43it/s, train/loss=3.030]
Epoch 0: |          | 717/? [04:55<00:00,  2.43it/s, train/loss=3.970]
Epoch 0: |          | 718/? [04:55<00:00,  2.43it/s, train/loss=3.970]
Epoch 0: |          | 718/? [04:55<00:00,  2.43it/s, train/loss=3.100]
Epoch 0: |          | 719/? [04:55<00:00,  2.43it/s, train/loss=3.100]
Epoch 0: |          | 719/? [04:55<00:00,  2.43it/s, train/loss=3.960]
Epoch 0: |          | 720/? [04:56<00:00,  2.43it/s, train/loss=3.960]
Epoch 0: |          | 720/? [04:56<00:00,  2.43it/s, train/loss=0.764]
Epoch 0: |          | 721/? [04:57<00:00,  2.43it/s, train/loss=0.764]
Epoch 0: |          | 721/? [04:57<00:00,  2.43it/s, train/loss=1.450]
Epoch 0: |          | 722/? [04:57<00:00,  2.43it/s, train/loss=1.450]
Epoch 0: |          | 722/? [04:57<00:00,  2.43it/s, train/loss=0.801]
Epoch 0: |          | 723/? [04:57<00:00,  2.43it/s, train/loss=0.801]
Epoch 0: |          | 723/? [04:57<00:00,  2.43it/s, train/loss=3.990]
Epoch 0: |          | 724/? [04:58<00:00,  2.43it/s, train/loss=3.990]
Epoch 0: |          | 724/? [04:58<00:00,  2.43it/s, train/loss=4.620]
Epoch 0: |          | 725/? [04:58<00:00,  2.43it/s, train/loss=4.620]
Epoch 0: |          | 725/? [04:58<00:00,  2.43it/s, train/loss=3.990]
Epoch 0: |          | 726/? [04:58<00:00,  2.43it/s, train/loss=3.990]
Epoch 0: |          | 726/? [04:58<00:00,  2.43it/s, train/loss=2.560]
Epoch 0: |          | 727/? [04:58<00:00,  2.43it/s, train/loss=2.560]
Epoch 0: |          | 727/? [04:58<00:00,  2.43it/s, train/loss=3.970]
Epoch 0: |          | 728/? [04:58<00:00,  2.44it/s, train/loss=3.970]
Epoch 0: |          | 728/? [04:58<00:00,  2.44it/s, train/loss=2.670]
Epoch 0: |          | 729/? [04:59<00:00,  2.44it/s, train/loss=2.670]
Epoch 0: |          | 729/? [04:59<00:00,  2.44it/s, train/loss=3.950]
Epoch 0: |          | 730/? [04:59<00:00,  2.44it/s, train/loss=3.950]
Epoch 0: |          | 730/? [04:59<00:00,  2.44it/s, train/loss=1.660]
Epoch 0: |          | 731/? [05:00<00:00,  2.43it/s, train/loss=1.660]
Epoch 0: |          | 731/? [05:00<00:00,  2.43it/s, train/loss=0.466]
Epoch 0: |          | 732/? [05:00<00:00,  2.43it/s, train/loss=0.466]
Epoch 0: |          | 732/? [05:00<00:00,  2.43it/s, train/loss=1.160]
Epoch 0: |          | 733/? [05:00<00:00,  2.44it/s, train/loss=1.160]
Epoch 0: |          | 733/? [05:00<00:00,  2.44it/s, train/loss=3.940]
Epoch 0: |          | 734/? [05:01<00:00,  2.44it/s, train/loss=3.940]
Epoch 0: |          | 734/? [05:01<00:00,  2.44it/s, train/loss=1.240]
Epoch 0: |          | 735/? [05:01<00:00,  2.44it/s, train/loss=1.240]
Epoch 0: |          | 735/? [05:01<00:00,  2.44it/s, train/loss=3.910]
Epoch 0: |          | 736/? [05:01<00:00,  2.44it/s, train/loss=3.910]
Epoch 0: |          | 736/? [05:01<00:00,  2.44it/s, train/loss=1.670]
Epoch 0: |          | 737/? [05:01<00:00,  2.44it/s, train/loss=1.670]
Epoch 0: |          | 737/? [05:01<00:00,  2.44it/s, train/loss=3.890]
Epoch 0: |          | 738/? [05:02<00:00,  2.44it/s, train/loss=3.890]
Epoch 0: |          | 738/? [05:02<00:00,  2.44it/s, train/loss=3.870]
Epoch 0: |          | 739/? [05:02<00:00,  2.44it/s, train/loss=3.870]
Epoch 0: |          | 739/? [05:02<00:00,  2.44it/s, train/loss=3.870]
Epoch 0: |          | 740/? [05:02<00:00,  2.44it/s, train/loss=3.870]
Epoch 0: |          | 740/? [05:02<00:00,  2.44it/s, train/loss=2.820]
Epoch 0: |          | 741/? [05:03<00:00,  2.44it/s, train/loss=2.820]
Epoch 0: |          | 741/? [05:03<00:00,  2.44it/s, train/loss=1.030]
Epoch 0: |          | 742/? [05:03<00:00,  2.44it/s, train/loss=1.030]
Epoch 0: |          | 742/? [05:03<00:00,  2.44it/s, train/loss=4.110]
Epoch 0: |          | 743/? [05:04<00:00,  2.44it/s, train/loss=4.110]
Epoch 0: |          | 743/? [05:04<00:00,  2.44it/s, train/loss=3.850]
Epoch 0: |          | 744/? [05:04<00:00,  2.44it/s, train/loss=3.850]
Epoch 0: |          | 744/? [05:04<00:00,  2.44it/s, train/loss=3.620]
Epoch 0: |          | 745/? [05:04<00:00,  2.45it/s, train/loss=3.620]
Epoch 0: |          | 745/? [05:04<00:00,  2.45it/s, train/loss=3.840]
Epoch 0: |          | 746/? [05:04<00:00,  2.45it/s, train/loss=3.840]
Epoch 0: |          | 746/? [05:04<00:00,  2.45it/s, train/loss=4.150]
Epoch 0: |          | 747/? [05:04<00:00,  2.45it/s, train/loss=4.150]
Epoch 0: |          | 747/? [05:04<00:00,  2.45it/s, train/loss=3.830]
Epoch 0: |          | 748/? [05:05<00:00,  2.45it/s, train/loss=3.830]
Epoch 0: |          | 748/? [05:05<00:00,  2.45it/s, train/loss=2.550]
Epoch 0: |          | 749/? [05:05<00:00,  2.45it/s, train/loss=2.550]
Epoch 0: |          | 749/? [05:05<00:00,  2.45it/s, train/loss=3.820]
Epoch 0: |          | 750/? [05:05<00:00,  2.45it/s, train/loss=3.820]
Epoch 0: |          | 750/? [05:05<00:00,  2.45it/s, train/loss=3.150]
Epoch 0: |          | 751/? [05:06<00:00,  2.45it/s, train/loss=3.150]
Epoch 0: |          | 751/? [05:06<00:00,  2.45it/s, train/loss=1.720]
Epoch 0: |          | 752/? [05:07<00:00,  2.45it/s, train/loss=1.720]
Epoch 0: |          | 752/? [05:07<00:00,  2.45it/s, train/loss=1.990]
Epoch 0: |          | 753/? [05:07<00:00,  2.45it/s, train/loss=1.990]
Epoch 0: |          | 753/? [05:07<00:00,  2.45it/s, train/loss=3.870]
Epoch 0: |          | 754/? [05:07<00:00,  2.45it/s, train/loss=3.870]
Epoch 0: |          | 754/? [05:07<00:00,  2.45it/s, train/loss=1.640]
Epoch 0: |          | 755/? [05:07<00:00,  2.45it/s, train/loss=1.640]
Epoch 0: |          | 755/? [05:07<00:00,  2.45it/s, train/loss=3.870]
Epoch 0: |          | 756/? [05:07<00:00,  2.45it/s, train/loss=3.870]
Epoch 0: |          | 756/? [05:07<00:00,  2.45it/s, train/loss=1.770]
Epoch 0: |          | 757/? [05:08<00:00,  2.46it/s, train/loss=1.770]
Epoch 0: |          | 757/? [05:08<00:00,  2.46it/s, train/loss=3.860]
Epoch 0: |          | 758/? [05:08<00:00,  2.46it/s, train/loss=3.860]
Epoch 0: |          | 758/? [05:08<00:00,  2.46it/s, train/loss=0.981]
Epoch 0: |          | 759/? [05:08<00:00,  2.46it/s, train/loss=0.981]
Epoch 0: |          | 759/? [05:08<00:00,  2.46it/s, train/loss=3.860]
Epoch 0: |          | 760/? [05:08<00:00,  2.46it/s, train/loss=3.860]
Epoch 0: |          | 760/? [05:08<00:00,  2.46it/s, train/loss=0.939]
Epoch 0: |          | 761/? [05:09<00:00,  2.46it/s, train/loss=0.939]
Epoch 0: |          | 761/? [05:09<00:00,  2.46it/s, train/loss=0.714]
Epoch 0: |          | 762/? [05:10<00:00,  2.46it/s, train/loss=0.714]
Epoch 0: |          | 762/? [05:10<00:00,  2.46it/s, train/loss=1.130]
Epoch 0: |          | 763/? [05:10<00:00,  2.46it/s, train/loss=1.130]
Epoch 0: |          | 763/? [05:10<00:00,  2.46it/s, train/loss=3.880]
Epoch 0: |          | 764/? [05:10<00:00,  2.46it/s, train/loss=3.880]
Epoch 0: |          | 764/? [05:10<00:00,  2.46it/s, train/loss=0.977]
Epoch 0: |          | 765/? [05:10<00:00,  2.46it/s, train/loss=0.977]
Epoch 0: |          | 765/? [05:10<00:00,  2.46it/s, train/loss=3.870]
Epoch 0: |          | 766/? [05:11<00:00,  2.46it/s, train/loss=3.870]
Epoch 0: |          | 766/? [05:11<00:00,  2.46it/s, train/loss=0.962]
Epoch 0: |          | 767/? [05:11<00:00,  2.47it/s, train/loss=0.962]
Epoch 0: |          | 767/? [05:11<00:00,  2.47it/s, train/loss=3.830]
Epoch 0: |          | 768/? [05:11<00:00,  2.47it/s, train/loss=3.830]
Epoch 0: |          | 768/? [05:11<00:00,  2.47it/s, train/loss=1.210]
Epoch 0: |          | 769/? [05:11<00:00,  2.47it/s, train/loss=1.210]
Epoch 0: |          | 769/? [05:11<00:00,  2.47it/s, train/loss=3.820]
Epoch 0: |          | 770/? [05:11<00:00,  2.47it/s, train/loss=3.820]
Epoch 0: |          | 770/? [05:11<00:00,  2.47it/s, train/loss=3.870]
Epoch 0: |          | 771/? [05:12<00:00,  2.46it/s, train/loss=3.870]
Epoch 0: |          | 771/? [05:12<00:00,  2.46it/s, train/loss=1.360]
Epoch 0: |          | 772/? [05:13<00:00,  2.47it/s, train/loss=1.360]
Epoch 0: |          | 772/? [05:13<00:00,  2.46it/s, train/loss=3.670]
Epoch 0: |          | 773/? [05:13<00:00,  2.47it/s, train/loss=3.670]
Epoch 0: |          | 773/? [05:13<00:00,  2.47it/s, train/loss=3.870]
Epoch 0: |          | 774/? [05:13<00:00,  2.47it/s, train/loss=3.870]
Epoch 0: |          | 774/? [05:13<00:00,  2.47it/s, train/loss=3.310]
Epoch 0: |          | 775/? [05:13<00:00,  2.47it/s, train/loss=3.310]
Epoch 0: |          | 775/? [05:13<00:00,  2.47it/s, train/loss=3.890]
Epoch 0: |          | 776/? [05:14<00:00,  2.47it/s, train/loss=3.890]
Epoch 0: |          | 776/? [05:14<00:00,  2.47it/s, train/loss=2.750]
Epoch 0: |          | 777/? [05:14<00:00,  2.47it/s, train/loss=2.750]
Epoch 0: |          | 777/? [05:14<00:00,  2.47it/s, train/loss=3.880]
Epoch 0: |          | 778/? [05:14<00:00,  2.47it/s, train/loss=3.880]
Epoch 0: |          | 778/? [05:14<00:00,  2.47it/s, train/loss=2.020]
Epoch 0: |          | 779/? [05:14<00:00,  2.48it/s, train/loss=2.020]
Epoch 0: |          | 779/? [05:14<00:00,  2.48it/s, train/loss=3.880]
Epoch 0: |          | 780/? [05:15<00:00,  2.48it/s, train/loss=3.880]
Epoch 0: |          | 780/? [05:15<00:00,  2.48it/s, train/loss=2.680]
Epoch 0: |          | 781/? [05:15<00:00,  2.47it/s, train/loss=2.680]
Epoch 0: |          | 781/? [05:15<00:00,  2.47it/s, train/loss=0.906]
Epoch 0: |          | 782/? [05:16<00:00,  2.47it/s, train/loss=0.906]
Epoch 0: |          | 782/? [05:16<00:00,  2.47it/s, train/loss=0.567]
Epoch 0: |          | 783/? [05:16<00:00,  2.48it/s, train/loss=0.567]
Epoch 0: |          | 783/? [05:16<00:00,  2.48it/s, train/loss=3.910]
Epoch 0: |          | 784/? [05:16<00:00,  2.48it/s, train/loss=3.910]
Epoch 0: |          | 784/? [05:16<00:00,  2.48it/s, train/loss=1.590]
Epoch 0: |          | 785/? [05:16<00:00,  2.48it/s, train/loss=1.590]
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Epoch 0: |          | 800/? [05:57<00:00,  2.24it/s, train/loss=1.040]
`Trainer.fit` stopped: `max_steps=800` reached.
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Epoch 0: |          | 800/? [05:57<00:00,  2.24it/s, train/loss=1.040]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
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Test results saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save
Running step 5: Exporting meshes
{'name': 'dreamcraft3d-texture', 'description': '', 'tag': 'replicate_user', 'seed': 0, 'use_timestamp': True, 'timestamp': '@20240222-135357', 'exp_root_dir': 'outputs', 'exp_dir': 'outputs/dreamcraft3d-texture', 'trial_name': 'replicate_user@20240222-135357', 'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357', 'n_gpus': 1, 'resume': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt', 'data_type': 'dreamcraft3d-single-image-datamodule', 'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}}, 'system_type': 'dreamcraft3d-system', 'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt', 'exporter_type': 'mesh-exporter', 'exporter': {'context_type': 'cuda'}}, 'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0}, 'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800}}
Loading Stable Diffusion ...
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Loaded Stable Diffusion!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
Missing logger folder: /src/lightning_logs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
Restoring states from the checkpoint path at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loaded model weights from the checkpoint at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'predict_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
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/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/loops/prediction_loop.py:255: predict returned None if it was on purpose, ignore this warning...
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Using xatlas to perform UV unwrapping, may take a while ...
Exporting textures ...
Perform UV padding on texture maps to avoid seams, may take a while ...
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Export assets saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save

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