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