
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-skin-demo-v2

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: 0.5206
- Accuracy: 0.8027

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.749         | 0.31  | 100  | 0.8017          | 0.7322   |
| 0.7376        | 0.62  | 200  | 0.7833          | 0.7210   |
| 0.6393        | 0.93  | 300  | 0.7435          | 0.7453   |
| 0.6058        | 1.25  | 400  | 0.8366          | 0.7391   |
| 0.5794        | 1.56  | 500  | 0.7278          | 0.7597   |
| 0.6625        | 1.87  | 600  | 0.6116          | 0.7846   |
| 0.5256        | 2.18  | 700  | 0.6108          | 0.7759   |
| 0.6053        | 2.49  | 800  | 0.5631          | 0.7965   |
| 0.601         | 2.8   | 900  | 0.5206          | 0.8027   |
| 0.4709        | 3.12  | 1000 | 0.5477          | 0.8177   |
| 0.5498        | 3.43  | 1100 | 0.5426          | 0.8121   |
| 0.4196        | 3.74  | 1200 | 0.5652          | 0.8065   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2

akiec bcc bkl df mel nv vasc