vit-base-patch16-224-for-pre_evaluation
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6048
- Accuracy: 0.3929
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5774 | 0.98 | 16 | 1.5109 | 0.3022 |
| 1.4794 | 1.97 | 32 | 1.4942 | 0.3242 |
| 1.4536 | 2.95 | 48 | 1.4943 | 0.3187 |
| 1.421 | 4.0 | 65 | 1.4247 | 0.3407 |
| 1.3882 | 4.98 | 81 | 1.4944 | 0.3462 |
| 1.3579 | 5.97 | 97 | 1.4180 | 0.3571 |
| 1.2838 | 6.95 | 113 | 1.4693 | 0.3681 |
| 1.2695 | 8.0 | 130 | 1.4359 | 0.3434 |
| 1.2016 | 8.98 | 146 | 1.4656 | 0.3599 |
| 1.2087 | 9.97 | 162 | 1.4550 | 0.3379 |
| 1.206 | 10.95 | 178 | 1.5056 | 0.3516 |
| 1.1236 | 12.0 | 195 | 1.5003 | 0.3434 |
| 1.0534 | 12.98 | 211 | 1.5193 | 0.3269 |
| 1.0024 | 13.97 | 227 | 1.4890 | 0.3681 |
| 0.9767 | 14.95 | 243 | 1.5628 | 0.3434 |
| 0.9201 | 16.0 | 260 | 1.6306 | 0.3516 |
| 0.9136 | 16.98 | 276 | 1.5715 | 0.3626 |
| 0.8566 | 17.97 | 292 | 1.5966 | 0.3654 |
| 0.8273 | 18.95 | 308 | 1.6048 | 0.3929 |
| 0.7825 | 20.0 | 325 | 1.6175 | 0.3846 |
| 0.736 | 20.98 | 341 | 1.6526 | 0.3929 |
| 0.7008 | 21.97 | 357 | 1.6563 | 0.3736 |
| 0.6714 | 22.95 | 373 | 1.7319 | 0.3901 |
| 0.7039 | 24.0 | 390 | 1.6866 | 0.3929 |
| 0.628 | 24.98 | 406 | 1.7023 | 0.3791 |
| 0.6182 | 25.97 | 422 | 1.7301 | 0.3901 |
| 0.5957 | 26.95 | 438 | 1.7157 | 0.3846 |
| 0.5973 | 28.0 | 455 | 1.7478 | 0.3709 |
| 0.5655 | 28.98 | 471 | 1.7377 | 0.3736 |
| 0.5631 | 29.54 | 480 | 1.7374 | 0.3736 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3