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# vit-dropout-v1

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the SkinCancerClassification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4773
- Accuracy: 0.8327

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7239        | 1.0   | 321  | 0.7047          | 0.7659   |
| 0.545         | 2.0   | 642  | 0.5697          | 0.7959   |
| 0.4288        | 3.0   | 963  | 0.5187          | 0.8109   |
| 0.4165        | 4.0   | 1284 | 0.4773          | 0.8327   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2

label_0 label_1 label_2 label_3 label_4 label_5 label_6