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# vit-ytr-demo-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: 0.4299
- Accuracy: 0.8497

## 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: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7759        | 0.31  | 100  | 0.7807          | 0.7304   |
| 0.6829        | 0.62  | 200  | 0.6997          | 0.7459   |
| 0.8535        | 0.93  | 300  | 0.6830          | 0.7594   |
| 0.6652        | 1.25  | 400  | 0.6186          | 0.7803   |
| 0.5537        | 1.56  | 500  | 0.5893          | 0.7973   |
| 0.5244        | 1.87  | 600  | 0.5723          | 0.7933   |
| 0.4224        | 2.18  | 700  | 0.5234          | 0.8168   |
| 0.516         | 2.49  | 800  | 0.5281          | 0.8028   |
| 0.4097        | 2.8   | 900  | 0.5010          | 0.8293   |
| 0.2422        | 3.12  | 1000 | 0.4585          | 0.8417   |
| 0.1393        | 3.43  | 1100 | 0.4508          | 0.8502   |
| 0.2486        | 3.74  | 1200 | 0.4299          | 0.8497   |


### 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