metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Wound-Image-classification
results: []
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: 0.2278
- Accuracy: 0.9524
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 32
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8831 | 1.0 | 147 | 1.2970 | 0.6531 |
| 0.9115 | 2.0 | 294 | 0.8685 | 0.7143 |
| 0.6506 | 3.0 | 441 | 0.7251 | 0.7653 |
| 0.5561 | 4.0 | 588 | 0.6598 | 0.7959 |
| 0.4606 | 5.0 | 735 | 0.6454 | 0.7806 |
| 0.3946 | 6.0 | 882 | 0.5916 | 0.8282 |
| 0.3433 | 7.0 | 1029 | 0.5672 | 0.8265 |
| 0.281 | 8.0 | 1176 | 0.6194 | 0.8265 |
| 0.2735 | 9.0 | 1323 | 0.4681 | 0.8571 |
| 0.2452 | 10.0 | 1470 | 0.4842 | 0.8673 |
| 0.2358 | 11.0 | 1617 | 0.4283 | 0.8776 |
| 0.1693 | 12.0 | 1764 | 0.4548 | 0.8759 |
| 0.1715 | 13.0 | 1911 | 0.5153 | 0.8724 |
| 0.159 | 14.0 | 2058 | 0.3161 | 0.9184 |
| 0.1557 | 15.0 | 2205 | 0.4901 | 0.8861 |
| 0.1137 | 16.0 | 2352 | 0.4257 | 0.9031 |
| 0.1239 | 17.0 | 2499 | 0.3844 | 0.9031 |
| 0.1426 | 18.0 | 2646 | 0.3769 | 0.8980 |
| 0.128 | 19.0 | 2793 | 0.3641 | 0.9082 |
| 0.1168 | 20.0 | 2940 | 0.3241 | 0.9133 |
| 0.1139 | 21.0 | 3087 | 0.2318 | 0.9320 |
| 0.0975 | 22.0 | 3234 | 0.3019 | 0.9286 |
| 0.0989 | 23.0 | 3381 | 0.2984 | 0.9269 |
| 0.0847 | 24.0 | 3528 | 0.2930 | 0.9201 |
| 0.0659 | 25.0 | 3675 | 0.3112 | 0.9371 |
| 0.0789 | 26.0 | 3822 | 0.2835 | 0.9354 |
| 0.0432 | 27.0 | 3969 | 0.3100 | 0.9303 |
| 0.0438 | 28.0 | 4116 | 0.3168 | 0.9320 |
| 0.0371 | 29.0 | 4263 | 0.2361 | 0.9490 |
| 0.039 | 30.0 | 4410 | 0.2714 | 0.9473 |
| 0.0435 | 31.0 | 4557 | 0.2547 | 0.9524 |
| 0.0512 | 32.0 | 4704 | 0.2278 | 0.9524 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2