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# vit-beta1-0.85

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: 0.5102
- Accuracy: 0.8558
- Precision: 0.8568
- Recall: 0.8558
- F1: 0.8553

## 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=(0.85,0.999) 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.763         | 1.0   | 321  | 0.9505          | 0.6952   | 0.6346    | 0.6952 | 0.6202 |
| 1.149         | 2.0   | 642  | 0.7147          | 0.7445   | 0.7457    | 0.7445 | 0.7230 |
| 1.0452        | 3.0   | 963  | 0.6250          | 0.7573   | 0.7591    | 0.7573 | 0.7321 |
| 1.0048        | 4.0   | 1284 | 0.5614          | 0.7784   | 0.7792    | 0.7784 | 0.7737 |
| 0.931         | 5.0   | 1605 | 0.6082          | 0.7739   | 0.8020    | 0.7739 | 0.7823 |
| 0.9808        | 6.0   | 1926 | 0.5542          | 0.7982   | 0.7984    | 0.7982 | 0.7951 |
| 0.8908        | 7.0   | 2247 | 0.5957          | 0.7545   | 0.8202    | 0.7545 | 0.7709 |
| 0.7747        | 8.0   | 2568 | 0.5766          | 0.7694   | 0.8155    | 0.7694 | 0.7836 |
| 0.741         | 9.0   | 2889 | 0.5431          | 0.7996   | 0.8190    | 0.7996 | 0.8047 |
| 0.7179        | 10.0  | 3210 | 0.5865          | 0.7774   | 0.8313    | 0.7774 | 0.7904 |
| 0.6102        | 11.0  | 3531 | 0.5288          | 0.8096   | 0.8361    | 0.8096 | 0.8180 |
| 0.574         | 12.0  | 3852 | 0.5991          | 0.7996   | 0.8332    | 0.7996 | 0.8096 |
| 0.4515        | 13.0  | 4173 | 0.5890          | 0.8370   | 0.8334    | 0.8370 | 0.8293 |
| 0.4629        | 14.0  | 4494 | 0.5573          | 0.8121   | 0.8463    | 0.8121 | 0.8205 |
| 0.3927        | 15.0  | 4815 | 0.5279          | 0.8332   | 0.8506    | 0.8332 | 0.8357 |
| 0.3535        | 16.0  | 5136 | 0.5364          | 0.8356   | 0.8494    | 0.8356 | 0.8405 |
| 0.2635        | 17.0  | 5457 | 0.5475          | 0.8547   | 0.8626    | 0.8547 | 0.8532 |
| 0.2493        | 18.0  | 5778 | 0.5102          | 0.8558   | 0.8568    | 0.8558 | 0.8553 |
| 0.2125        | 19.0  | 6099 | 0.6120          | 0.8329   | 0.8623    | 0.8329 | 0.8418 |
| 0.2179        | 20.0  | 6420 | 0.5721          | 0.8568   | 0.8563    | 0.8568 | 0.8563 |
| 0.1598        | 21.0  | 6741 | 0.5503          | 0.8651   | 0.8623    | 0.8651 | 0.8633 |
| 0.1194        | 22.0  | 7062 | 0.5829          | 0.8679   | 0.8672    | 0.8679 | 0.8669 |
| 0.1245        | 23.0  | 7383 | 0.6138          | 0.8682   | 0.8632    | 0.8682 | 0.8629 |
| 0.1239        | 24.0  | 7704 | 0.6136          | 0.8731   | 0.8703    | 0.8731 | 0.8695 |
| 0.1159        | 25.0  | 8025 | 0.5931          | 0.8752   | 0.8724    | 0.8752 | 0.8726 |
| 0.089         | 26.0  | 8346 | 0.5847          | 0.8776   | 0.8743    | 0.8776 | 0.8750 |
| 0.1123        | 27.0  | 8667 | 0.5941          | 0.8752   | 0.8710    | 0.8752 | 0.8719 |
| 0.0779        | 28.0  | 8988 | 0.6038          | 0.8766   | 0.8722    | 0.8766 | 0.8729 |


### Framework versions

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

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