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# vit-beta1-0.95

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: 0.5187
- Accuracy: 0.8384
- Precision: 0.8496
- Recall: 0.8384
- F1: 0.8421

## 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=(0.95,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1733
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7463        | 1.0   | 321  | 1.0838          | 0.6810   | 0.6594    | 0.6810 | 0.6416 |
| 1.2057        | 2.0   | 642  | 0.7826          | 0.7025   | 0.7172    | 0.7025 | 0.6909 |
| 1.0261        | 3.0   | 963  | 0.7040          | 0.7406   | 0.7119    | 0.7406 | 0.6962 |
| 1.0269        | 4.0   | 1284 | 0.6113          | 0.7573   | 0.7934    | 0.7573 | 0.7620 |
| 0.943         | 5.0   | 1605 | 0.7935          | 0.6848   | 0.7925    | 0.6848 | 0.7063 |
| 0.9677        | 6.0   | 1926 | 0.6434          | 0.7555   | 0.7996    | 0.7555 | 0.7690 |
| 0.875         | 7.0   | 2247 | 0.6981          | 0.7157   | 0.7962    | 0.7157 | 0.7344 |
| 0.7796        | 8.0   | 2568 | 0.7443          | 0.7115   | 0.8097    | 0.7115 | 0.7352 |
| 0.7308        | 9.0   | 2889 | 0.5311          | 0.8103   | 0.8217    | 0.8103 | 0.8125 |
| 0.7036        | 10.0  | 3210 | 0.5371          | 0.7892   | 0.8341    | 0.7892 | 0.8006 |
| 0.637         | 11.0  | 3531 | 0.6372          | 0.7850   | 0.8268    | 0.7850 | 0.7963 |
| 0.5668        | 12.0  | 3852 | 0.5850          | 0.8024   | 0.8279    | 0.8024 | 0.8109 |
| 0.4823        | 13.0  | 4173 | 0.6345          | 0.8284   | 0.8341    | 0.8284 | 0.8115 |
| 0.4808        | 14.0  | 4494 | 0.6609          | 0.7992   | 0.8328    | 0.7992 | 0.8038 |
| 0.4087        | 15.0  | 4815 | 0.6568          | 0.7791   | 0.8373    | 0.7791 | 0.7952 |
| 0.3579        | 16.0  | 5136 | 0.5462          | 0.8294   | 0.8510    | 0.8294 | 0.8364 |
| 0.3015        | 17.0  | 5457 | 0.5187          | 0.8384   | 0.8496    | 0.8384 | 0.8421 |
| 0.2794        | 18.0  | 5778 | 0.6125          | 0.8204   | 0.8538    | 0.8204 | 0.8300 |
| 0.2297        | 19.0  | 6099 | 0.5672          | 0.8391   | 0.8500    | 0.8391 | 0.8429 |
| 0.229         | 20.0  | 6420 | 0.6051          | 0.8526   | 0.8543    | 0.8526 | 0.8524 |
| 0.1743        | 21.0  | 6741 | 0.5990          | 0.8606   | 0.8598    | 0.8606 | 0.8577 |
| 0.1327        | 22.0  | 7062 | 0.6290          | 0.8568   | 0.8636    | 0.8568 | 0.8590 |
| 0.1321        | 23.0  | 7383 | 0.6259          | 0.8655   | 0.8613    | 0.8655 | 0.8625 |
| 0.1236        | 24.0  | 7704 | 0.6135          | 0.8703   | 0.8699    | 0.8703 | 0.8697 |
| 0.126         | 25.0  | 8025 | 0.6107          | 0.8655   | 0.8658    | 0.8655 | 0.8645 |
| 0.0919        | 26.0  | 8346 | 0.6001          | 0.8700   | 0.8657    | 0.8700 | 0.8665 |
| 0.1421        | 27.0  | 8667 | 0.5894          | 0.8745   | 0.8721    | 0.8745 | 0.8727 |


### Framework versions

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

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