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# vit-base-patch16-224-in21k-finetuned-biopsy

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0838
- Accuracy: 0.9799

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1862        | 1.0   | 42   | 1.1167          | 0.5611   |
| 0.7235        | 2.0   | 84   | 0.6029          | 0.8543   |
| 0.4286        | 3.0   | 126  | 0.3452          | 0.9280   |
| 0.3612        | 4.0   | 168  | 0.3485          | 0.8945   |
| 0.3015        | 5.0   | 210  | 0.2590          | 0.9296   |
| 0.2917        | 6.0   | 252  | 0.2219          | 0.9414   |
| 0.2312        | 7.0   | 294  | 0.2400          | 0.9280   |
| 0.1708        | 8.0   | 336  | 0.2120          | 0.9414   |
| 0.1806        | 9.0   | 378  | 0.1784          | 0.9514   |
| 0.1703        | 10.0  | 420  | 0.1571          | 0.9481   |
| 0.139         | 11.0  | 462  | 0.1544          | 0.9648   |
| 0.1301        | 12.0  | 504  | 0.1431          | 0.9598   |
| 0.122         | 13.0  | 546  | 0.1297          | 0.9631   |
| 0.1104        | 14.0  | 588  | 0.1401          | 0.9598   |
| 0.1075        | 15.0  | 630  | 0.1200          | 0.9665   |
| 0.0986        | 16.0  | 672  | 0.1665          | 0.9581   |
| 0.092         | 17.0  | 714  | 0.1399          | 0.9531   |
| 0.1123        | 18.0  | 756  | 0.1122          | 0.9698   |
| 0.0766        | 19.0  | 798  | 0.1337          | 0.9564   |
| 0.0762        | 20.0  | 840  | 0.0974          | 0.9732   |
| 0.0994        | 21.0  | 882  | 0.1023          | 0.9698   |
| 0.0687        | 22.0  | 924  | 0.0976          | 0.9749   |
| 0.0767        | 23.0  | 966  | 0.0952          | 0.9765   |
| 0.0581        | 24.0  | 1008 | 0.1096          | 0.9665   |
| 0.0544        | 25.0  | 1050 | 0.1123          | 0.9715   |
| 0.079         | 26.0  | 1092 | 0.1040          | 0.9682   |
| 0.0661        | 27.0  | 1134 | 0.0838          | 0.9799   |
| 0.068         | 28.0  | 1176 | 0.1169          | 0.9715   |
| 0.0722        | 29.0  | 1218 | 0.0897          | 0.9732   |
| 0.048         | 30.0  | 1260 | 0.0864          | 0.9732   |
| 0.0509        | 31.0  | 1302 | 0.0858          | 0.9749   |
| 0.047         | 32.0  | 1344 | 0.0801          | 0.9782   |
| 0.0411        | 33.0  | 1386 | 0.1221          | 0.9648   |
| 0.0378        | 34.0  | 1428 | 0.1011          | 0.9648   |
| 0.0358        | 35.0  | 1470 | 0.0834          | 0.9799   |
| 0.0347        | 36.0  | 1512 | 0.0993          | 0.9715   |
| 0.0434        | 37.0  | 1554 | 0.0938          | 0.9732   |
| 0.0507        | 38.0  | 1596 | 0.0874          | 0.9782   |
| 0.0466        | 39.0  | 1638 | 0.0932          | 0.9765   |
| 0.0502        | 40.0  | 1680 | 0.1012          | 0.9698   |
| 0.0289        | 41.0  | 1722 | 0.0841          | 0.9715   |
| 0.0274        | 42.0  | 1764 | 0.0883          | 0.9682   |
| 0.0251        | 43.0  | 1806 | 0.0843          | 0.9782   |
| 0.0343        | 44.0  | 1848 | 0.0812          | 0.9782   |
| 0.0289        | 45.0  | 1890 | 0.0805          | 0.9782   |
| 0.0277        | 46.0  | 1932 | 0.0943          | 0.9698   |
| 0.0332        | 47.0  | 1974 | 0.0807          | 0.9765   |
| 0.0328        | 48.0  | 2016 | 0.0826          | 0.9749   |
| 0.0257        | 49.0  | 2058 | 0.0852          | 0.9749   |
| 0.0287        | 50.0  | 2100 | 0.0848          | 0.9782   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1

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