vit_itri_46
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: 0.0480
- Accuracy: 0.9910
- Precision: 0.9911
- Recall: 0.9910
- F1: 0.9907
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 |
|---|---|---|---|---|---|---|---|
| 0.3639 | 1.0 | 708 | 0.2151 | 0.9401 | 0.9413 | 0.9401 | 0.9345 |
| 0.1373 | 2.0 | 1416 | 0.1163 | 0.9602 | 0.9612 | 0.9602 | 0.9590 |
| 0.0879 | 3.0 | 2124 | 0.0978 | 0.9735 | 0.9731 | 0.9735 | 0.9728 |
| 0.0639 | 4.0 | 2832 | 0.1333 | 0.9650 | 0.9657 | 0.9650 | 0.9637 |
| 0.053 | 5.0 | 3540 | 0.0817 | 0.9777 | 0.9771 | 0.9777 | 0.9766 |
| 0.0391 | 6.0 | 4248 | 0.0876 | 0.9756 | 0.9775 | 0.9756 | 0.9758 |
| 0.0284 | 7.0 | 4956 | 0.0579 | 0.9857 | 0.9858 | 0.9857 | 0.9852 |
| 0.0198 | 8.0 | 5664 | 0.0821 | 0.9820 | 0.9827 | 0.9820 | 0.9818 |
| 0.0176 | 9.0 | 6372 | 0.0717 | 0.9862 | 0.9862 | 0.9862 | 0.9859 |
| 0.0143 | 10.0 | 7080 | 0.1047 | 0.9820 | 0.9816 | 0.9820 | 0.9810 |
| 0.0135 | 11.0 | 7788 | 0.0724 | 0.9862 | 0.9864 | 0.9862 | 0.9860 |
| 0.0093 | 12.0 | 8496 | 0.0869 | 0.9857 | 0.9858 | 0.9857 | 0.9852 |
| 0.0067 | 13.0 | 9204 | 0.0863 | 0.9846 | 0.9858 | 0.9846 | 0.9840 |
| 0.0059 | 14.0 | 9912 | 0.0603 | 0.9867 | 0.9869 | 0.9867 | 0.9865 |
| 0.0038 | 15.0 | 10620 | 0.0591 | 0.9889 | 0.9891 | 0.9889 | 0.9886 |
| 0.003 | 16.0 | 11328 | 0.0568 | 0.9894 | 0.9895 | 0.9894 | 0.9891 |
| 0.0029 | 17.0 | 12036 | 0.0589 | 0.9873 | 0.9873 | 0.9873 | 0.9869 |
| 0.0005 | 18.0 | 12744 | 0.0530 | 0.9910 | 0.9911 | 0.9910 | 0.9907 |
| 0.0003 | 19.0 | 13452 | 0.0453 | 0.9920 | 0.9921 | 0.9920 | 0.9918 |
| 0.0002 | 20.0 | 14160 | 0.0480 | 0.9910 | 0.9911 | 0.9910 | 0.9907 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1