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# vit-dropout-v2

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: 0.4413
- Accuracy: 0.8602

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure
- dropout: 0.2
### 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: 10
- mixed_precision_training: Native AMP

### Training results
   
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6816        | 1.56  | 500  | 0.8345          | 0.7347   |
| 0.4391        | 3.12  | 1000 | 0.5814          | 0.7778   |
| 0.4074        | 4.67  | 1500 | 0.5231          | 0.8027   |
| 0.3939        | 6.23  | 2000 | 0.4802          | 0.8308   |
| 0.3035        | 7.79  | 2500 | 0.4515          | 0.8471   |
| 0.1723        | 9.35  | 3000 | 0.4413          | 0.8602   |


### Framework versions

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

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