lucataco / watermark_detector

amrul-hzz's fine-tuned version of vit-base-patch16-224-in21k for watermark image detection

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  • 201 runs
  • GitHub
  • Paper
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Input

Output

Run time and cost

This model costs approximately $0.0089 to run on Replicate, or 112 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on CPU hardware. Predictions typically complete within 90 seconds.

Readme

This is a Cog Implementation of amrul-hzz/watermark_detector

watermark_detector

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6014 - Accuracy: 0.6574

Training hyperparameters

The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6492 1.0 1139 0.6375 0.6262
0.6172 2.0 2278 0.6253 0.6438
0.578 3.0 3417 0.6110 0.6508

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3