vit_4090_7_3
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: 0.0352
- Accuracy: 0.9942
- Precision: 0.9942
- Recall: 0.9942
- F1: 0.9942
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 |
|---|---|---|---|---|---|---|---|
| 0.2467 | 1.0 | 1238 | 0.1080 | 0.9679 | 0.9677 | 0.9679 | 0.9670 |
| 0.098 | 2.0 | 2476 | 0.0927 | 0.9743 | 0.9754 | 0.9743 | 0.9740 |
| 0.0655 | 3.0 | 3714 | 0.0997 | 0.9749 | 0.9764 | 0.9749 | 0.9752 |
| 0.0494 | 4.0 | 4952 | 0.1050 | 0.9712 | 0.9715 | 0.9712 | 0.9706 |
| 0.0381 | 5.0 | 6190 | 0.1024 | 0.9776 | 0.9776 | 0.9776 | 0.9770 |
| 0.0348 | 6.0 | 7428 | 0.0528 | 0.9861 | 0.9866 | 0.9861 | 0.9861 |
| 0.0253 | 7.0 | 8666 | 0.1030 | 0.9800 | 0.9807 | 0.9800 | 0.9797 |
| 0.0215 | 8.0 | 9904 | 0.0515 | 0.9867 | 0.9870 | 0.9867 | 0.9866 |
| 0.0209 | 9.0 | 11142 | 0.0589 | 0.9870 | 0.9872 | 0.9870 | 0.9868 |
| 0.0123 | 10.0 | 12380 | 0.0783 | 0.9842 | 0.9846 | 0.9842 | 0.9842 |
| 0.0118 | 11.0 | 13618 | 0.0435 | 0.9915 | 0.9915 | 0.9915 | 0.9915 |
| 0.0084 | 12.0 | 14856 | 0.0472 | 0.9927 | 0.9927 | 0.9927 | 0.9927 |
| 0.0081 | 13.0 | 16094 | 0.0394 | 0.9927 | 0.9928 | 0.9927 | 0.9927 |
| 0.0056 | 14.0 | 17332 | 0.0537 | 0.9909 | 0.9909 | 0.9909 | 0.9908 |
| 0.0033 | 15.0 | 18570 | 0.0353 | 0.9933 | 0.9934 | 0.9933 | 0.9933 |
| 0.0022 | 16.0 | 19808 | 0.0386 | 0.9924 | 0.9924 | 0.9924 | 0.9924 |
| 0.0016 | 17.0 | 21046 | 0.0384 | 0.9930 | 0.9930 | 0.9930 | 0.9930 |
| 0.0009 | 18.0 | 22284 | 0.0342 | 0.9945 | 0.9945 | 0.9945 | 0.9945 |
| 0.0009 | 19.0 | 23522 | 0.0363 | 0.9936 | 0.9937 | 0.9936 | 0.9936 |
| 0.0007 | 20.0 | 24760 | 0.0352 | 0.9942 | 0.9942 | 0.9942 | 0.9942 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.1