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# vit-ds-processed

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the skin-cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5326
- Accuracy: 0.8235
- Precision: 0.8344
- Recall: 0.8235
- F1: 0.8208

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 770
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8606        | 1.0   | 321  | 0.5784          | 0.7930   | 0.7895    | 0.7930 | 0.7809 |
| 0.5095        | 2.0   | 642  | 0.5439          | 0.8048   | 0.8197    | 0.8048 | 0.7949 |
| 0.4085        | 3.0   | 963  | 0.5629          | 0.8228   | 0.8183    | 0.8228 | 0.8064 |
| 0.2672        | 4.0   | 1284 | 0.5326          | 0.8235   | 0.8344    | 0.8235 | 0.8208 |
| 0.1578        | 5.0   | 1605 | 0.6352          | 0.8422   | 0.8433    | 0.8422 | 0.8379 |
| 0.0921        | 6.0   | 1926 | 0.7425          | 0.8232   | 0.8397    | 0.8232 | 0.8261 |
| 0.0537        | 7.0   | 2247 | 0.8936          | 0.8336   | 0.8288    | 0.8336 | 0.8188 |
| 0.0481        | 8.0   | 2568 | 0.9522          | 0.8509   | 0.8451    | 0.8509 | 0.8409 |
| 0.0291        | 9.0   | 2889 | 0.9770          | 0.8450   | 0.8454    | 0.8450 | 0.8429 |
| 0.04          | 10.0  | 3210 | 0.9303          | 0.8471   | 0.8478    | 0.8471 | 0.8445 |
| 0.0235        | 11.0  | 3531 | 0.9866          | 0.8454   | 0.8439    | 0.8454 | 0.8395 |
| 0.0164        | 12.0  | 3852 | 1.0983          | 0.8408   | 0.8473    | 0.8408 | 0.8346 |
| 0.005         | 13.0  | 4173 | 1.1124          | 0.8429   | 0.8433    | 0.8429 | 0.8376 |
| 0.0064        | 14.0  | 4494 | 1.0629          | 0.8575   | 0.8519    | 0.8575 | 0.8534 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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