vit-base-patch16-224_rice-leaf-disease-augmented-v4_v5_pft
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4332
- Accuracy: 0.8456
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 256
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1701 | 0.5 | 64 | 1.9984 | 0.2349 |
| 1.878 | 1.0 | 128 | 1.6113 | 0.4698 |
| 1.4921 | 1.5 | 192 | 1.2635 | 0.6174 |
| 1.2126 | 2.0 | 256 | 1.0178 | 0.6812 |
| 0.9922 | 2.5 | 320 | 0.8928 | 0.7148 |
| 0.8858 | 3.0 | 384 | 0.7883 | 0.7483 |
| 0.7966 | 3.5 | 448 | 0.7408 | 0.7517 |
| 0.7427 | 4.0 | 512 | 0.6912 | 0.7651 |
| 0.7077 | 4.5 | 576 | 0.6795 | 0.7718 |
| 0.6796 | 5.0 | 640 | 0.6647 | 0.7785 |
| 0.6597 | 5.5 | 704 | 0.6684 | 0.7752 |
| 0.6652 | 6.0 | 768 | 0.6535 | 0.7752 |
| 0.6762 | 6.5 | 832 | 0.6533 | 0.7752 |
| 0.6277 | 7.0 | 896 | 0.6356 | 0.7886 |
| 0.6264 | 7.5 | 960 | 0.6008 | 0.7987 |
| 0.5906 | 8.0 | 1024 | 0.5791 | 0.8154 |
| 0.5596 | 8.5 | 1088 | 0.5789 | 0.8054 |
| 0.5619 | 9.0 | 1152 | 0.5785 | 0.7987 |
| 0.5381 | 9.5 | 1216 | 0.5532 | 0.8121 |
| 0.5275 | 10.0 | 1280 | 0.5591 | 0.8087 |
| 0.5183 | 10.5 | 1344 | 0.5555 | 0.8054 |
| 0.5236 | 11.0 | 1408 | 0.5551 | 0.8087 |
| 0.5198 | 11.5 | 1472 | 0.5649 | 0.8020 |
| 0.5128 | 12.0 | 1536 | 0.5312 | 0.8356 |
| 0.4932 | 12.5 | 1600 | 0.5238 | 0.8054 |
| 0.4854 | 13.0 | 1664 | 0.5234 | 0.8121 |
| 0.4674 | 13.5 | 1728 | 0.5142 | 0.8221 |
| 0.4614 | 14.0 | 1792 | 0.5109 | 0.8154 |
| 0.4558 | 14.5 | 1856 | 0.5095 | 0.8289 |
| 0.4419 | 15.0 | 1920 | 0.5043 | 0.8188 |
| 0.4362 | 15.5 | 1984 | 0.5034 | 0.8221 |
| 0.4496 | 16.0 | 2048 | 0.5032 | 0.8221 |
| 0.4484 | 16.5 | 2112 | 0.5017 | 0.8221 |
| 0.4325 | 17.0 | 2176 | 0.5015 | 0.8289 |
| 0.428 | 17.5 | 2240 | 0.4967 | 0.8221 |
| 0.4091 | 18.0 | 2304 | 0.4704 | 0.8356 |
| 0.405 | 18.5 | 2368 | 0.4792 | 0.8289 |
| 0.4012 | 19.0 | 2432 | 0.4750 | 0.8322 |
| 0.3887 | 19.5 | 2496 | 0.4750 | 0.8289 |
| 0.3986 | 20.0 | 2560 | 0.4711 | 0.8255 |
| 0.3983 | 20.5 | 2624 | 0.4713 | 0.8255 |
| 0.3857 | 21.0 | 2688 | 0.4750 | 0.8289 |
| 0.3925 | 21.5 | 2752 | 0.4506 | 0.8456 |
| 0.3787 | 22.0 | 2816 | 0.4622 | 0.8255 |
| 0.368 | 22.5 | 2880 | 0.4583 | 0.8389 |
| 0.3702 | 23.0 | 2944 | 0.4479 | 0.8423 |
| 0.3591 | 23.5 | 3008 | 0.4485 | 0.8389 |
| 0.3588 | 24.0 | 3072 | 0.4534 | 0.8356 |
| 0.3517 | 24.5 | 3136 | 0.4496 | 0.8356 |
| 0.3546 | 25.0 | 3200 | 0.4482 | 0.8389 |
| 0.3636 | 25.5 | 3264 | 0.4518 | 0.8356 |
| 0.3435 | 26.0 | 3328 | 0.4495 | 0.8322 |
| 0.3423 | 26.5 | 3392 | 0.4427 | 0.8322 |
| 0.3477 | 27.0 | 3456 | 0.4365 | 0.8423 |
| 0.3405 | 27.5 | 3520 | 0.4380 | 0.8389 |
| 0.3254 | 28.0 | 3584 | 0.4366 | 0.8389 |
| 0.3245 | 28.5 | 3648 | 0.4316 | 0.8423 |
| 0.3265 | 29.0 | 3712 | 0.4305 | 0.8423 |
| 0.3193 | 29.5 | 3776 | 0.4339 | 0.8456 |
| 0.3244 | 30.0 | 3840 | 0.4332 | 0.8456 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1