vit_4090
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: 0.0003
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
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 |
|---|---|---|---|---|---|---|---|
| 0.1909 | 1.0 | 865 | 0.0626 | 0.9840 | 0.9841 | 0.9840 | 0.9834 |
| 0.0747 | 2.0 | 1730 | 0.0403 | 0.9874 | 0.9876 | 0.9874 | 0.9869 |
| 0.0489 | 3.0 | 2595 | 0.0757 | 0.9788 | 0.9811 | 0.9788 | 0.9790 |
| 0.0352 | 4.0 | 3460 | 0.0187 | 0.9922 | 0.9924 | 0.9922 | 0.9923 |
| 0.0295 | 5.0 | 4325 | 0.0738 | 0.9792 | 0.9808 | 0.9792 | 0.9791 |
| 0.0248 | 6.0 | 5190 | 0.0196 | 0.9939 | 0.9940 | 0.9939 | 0.9939 |
| 0.0172 | 7.0 | 6055 | 0.0281 | 0.9939 | 0.9944 | 0.9939 | 0.9940 |
| 0.0205 | 8.0 | 6920 | 0.0052 | 0.9983 | 0.9983 | 0.9983 | 0.9983 |
| 0.0122 | 9.0 | 7785 | 0.0462 | 0.9883 | 0.9885 | 0.9883 | 0.9881 |
| 0.0106 | 10.0 | 8650 | 0.0258 | 0.9952 | 0.9953 | 0.9952 | 0.9952 |
| 0.0105 | 11.0 | 9515 | 0.0119 | 0.9974 | 0.9974 | 0.9974 | 0.9974 |
| 0.0073 | 12.0 | 10380 | 0.0081 | 0.9970 | 0.9970 | 0.9970 | 0.9970 |
| 0.0052 | 13.0 | 11245 | 0.0034 | 0.9991 | 0.9991 | 0.9991 | 0.9991 |
| 0.0031 | 14.0 | 12110 | 0.0169 | 0.9957 | 0.9957 | 0.9957 | 0.9956 |
| 0.0042 | 15.0 | 12975 | 0.0048 | 0.9991 | 0.9991 | 0.9991 | 0.9991 |
| 0.0014 | 16.0 | 13840 | 0.0015 | 0.9991 | 0.9991 | 0.9991 | 0.9991 |
| 0.0005 | 17.0 | 14705 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 18.0 | 15570 | 0.0026 | 0.9996 | 0.9996 | 0.9996 | 0.9996 |
| 0.0002 | 19.0 | 16435 | 0.0008 | 0.9996 | 0.9996 | 0.9996 | 0.9996 |
| 0.0002 | 20.0 | 17300 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.1