Wound-Image-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1209
- Accuracy: 0.965
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0919 | 1.0 | 200 | 0.7780 | 0.76 |
| 0.6157 | 2.0 | 400 | 0.5695 | 0.7925 |
| 0.4894 | 3.0 | 600 | 0.3667 | 0.8775 |
| 0.3786 | 4.0 | 800 | 0.4436 | 0.8625 |
| 0.3142 | 5.0 | 1000 | 0.4412 | 0.8625 |
| 0.2636 | 6.0 | 1200 | 0.4430 | 0.86 |
| 0.198 | 7.0 | 1400 | 0.2760 | 0.9175 |
| 0.1456 | 8.0 | 1600 | 0.2211 | 0.93 |
| 0.1586 | 9.0 | 1800 | 0.3520 | 0.905 |
| 0.1307 | 10.0 | 2000 | 0.3188 | 0.9175 |
| 0.106 | 11.0 | 2200 | 0.3167 | 0.925 |
| 0.0975 | 12.0 | 2400 | 0.2633 | 0.92 |
| 0.0734 | 13.0 | 2600 | 0.1813 | 0.9525 |
| 0.0994 | 14.0 | 2800 | 0.2150 | 0.945 |
| 0.0622 | 15.0 | 3000 | 0.1757 | 0.955 |
| 0.0609 | 16.0 | 3200 | 0.1209 | 0.965 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2