vit_itri_ipcl
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: 0.0379
- Accuracy: 0.9963
- Precision: 0.9964
- Recall: 0.9963
- F1: 0.9963
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0373 | 1.0 | 2335 | 0.0582 | 0.9817 | 0.9824 | 0.9817 | 0.9817 |
| 0.0159 | 2.0 | 4670 | 0.1773 | 0.9584 | 0.9617 | 0.9584 | 0.9583 |
| 0.0106 | 3.0 | 7005 | 0.0308 | 0.9954 | 0.9954 | 0.9954 | 0.9954 |
| 0.0072 | 4.0 | 9340 | 0.0895 | 0.9803 | 0.9811 | 0.9803 | 0.9803 |
| 0.0052 | 5.0 | 11675 | 0.0921 | 0.9726 | 0.9736 | 0.9726 | 0.9726 |
| 0.0034 | 6.0 | 14010 | 0.0304 | 0.9948 | 0.9948 | 0.9948 | 0.9948 |
| 0.0015 | 7.0 | 16345 | 0.0551 | 0.9917 | 0.9919 | 0.9917 | 0.9917 |
| 0.0014 | 8.0 | 18680 | 0.0290 | 0.9971 | 0.9971 | 0.9971 | 0.9971 |
| 0.0005 | 9.0 | 21015 | 0.0321 | 0.9969 | 0.9969 | 0.9969 | 0.9969 |
| 0.0001 | 10.0 | 23350 | 0.0379 | 0.9963 | 0.9964 | 0.9963 | 0.9963 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1