vit_4090_3_7
This model is a fine-tuned version of google/vit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0353
- Accuracy: 0.9908
- Precision: 0.9907
- Recall: 0.9908
- F1: 0.9906
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: 0.0001
- train_batch_size: 24
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3443 | 1.0 | 531 | 0.2528 | 0.9216 | 0.9410 | 0.9216 | 0.9264 |
| 0.1457 | 2.0 | 1062 | 0.1413 | 0.9590 | 0.9589 | 0.9590 | 0.9584 |
| 0.0938 | 3.0 | 1593 | 0.1220 | 0.9611 | 0.9599 | 0.9611 | 0.9597 |
| 0.0737 | 4.0 | 2124 | 0.0718 | 0.9781 | 0.9760 | 0.9781 | 0.9764 |
| 0.0513 | 5.0 | 2655 | 0.1124 | 0.9731 | 0.9734 | 0.9731 | 0.9721 |
| 0.0389 | 6.0 | 3186 | 0.1038 | 0.9760 | 0.9766 | 0.9760 | 0.9754 |
| 0.0314 | 7.0 | 3717 | 0.0736 | 0.9837 | 0.9847 | 0.9837 | 0.9835 |
| 0.0291 | 8.0 | 4248 | 0.0958 | 0.9802 | 0.9805 | 0.9802 | 0.9800 |
| 0.0183 | 9.0 | 4779 | 0.0914 | 0.9823 | 0.9828 | 0.9823 | 0.9823 |
| 0.014 | 10.0 | 5310 | 0.0916 | 0.9781 | 0.9783 | 0.9781 | 0.9776 |
| 0.0171 | 11.0 | 5841 | 0.0554 | 0.9866 | 0.9869 | 0.9866 | 0.9863 |
| 0.009 | 12.0 | 6372 | 0.0778 | 0.9830 | 0.9835 | 0.9830 | 0.9827 |
| 0.0049 | 13.0 | 6903 | 0.0761 | 0.9873 | 0.9873 | 0.9873 | 0.9871 |
| 0.0057 | 14.0 | 7434 | 0.0628 | 0.9880 | 0.9879 | 0.9880 | 0.9877 |
| 0.0032 | 15.0 | 7965 | 0.0563 | 0.9887 | 0.9887 | 0.9887 | 0.9885 |
| 0.0028 | 16.0 | 8496 | 0.0695 | 0.9852 | 0.9854 | 0.9852 | 0.9850 |
| 0.0021 | 17.0 | 9027 | 0.0470 | 0.9887 | 0.9887 | 0.9887 | 0.9886 |
| 0.0006 | 18.0 | 9558 | 0.0403 | 0.9908 | 0.9908 | 0.9908 | 0.9907 |
| 0.0001 | 19.0 | 10089 | 0.0354 | 0.9922 | 0.9922 | 0.9922 | 0.9920 |
| 0.0001 | 20.0 | 10620 | 0.0353 | 0.9908 | 0.9907 | 0.9908 | 0.9906 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.1