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# vit-beta2-0.9995

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: 0.5000
- Accuracy: 0.8519
- Precision: 0.8575
- Recall: 0.8519
- F1: 0.8527

## 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=(0.9,0.9995) 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7395        | 1.0   | 321  | 0.9629          | 0.6845   | 0.6040    | 0.6845 | 0.5948 |
| 1.1477        | 2.0   | 642  | 0.7630          | 0.7174   | 0.7438    | 0.7174 | 0.7138 |
| 1.0466        | 3.0   | 963  | 0.6211          | 0.7660   | 0.7543    | 0.7660 | 0.7373 |
| 0.9366        | 4.0   | 1284 | 0.6310          | 0.7354   | 0.7934    | 0.7354 | 0.7518 |
| 0.9629        | 5.0   | 1605 | 0.5584          | 0.7982   | 0.7934    | 0.7982 | 0.7865 |
| 0.9753        | 6.0   | 1926 | 0.5606          | 0.7920   | 0.7922    | 0.7920 | 0.7916 |
| 0.8629        | 7.0   | 2247 | 0.7154          | 0.6969   | 0.8040    | 0.6969 | 0.7238 |
| 0.7817        | 8.0   | 2568 | 0.6276          | 0.7597   | 0.8105    | 0.7597 | 0.7743 |
| 0.7355        | 9.0   | 2889 | 0.5259          | 0.8110   | 0.8215    | 0.8110 | 0.8133 |
| 0.6878        | 10.0  | 3210 | 0.5347          | 0.7885   | 0.8388    | 0.7885 | 0.8022 |
| 0.6206        | 11.0  | 3531 | 0.5543          | 0.7958   | 0.8375    | 0.7958 | 0.8079 |
| 0.5628        | 12.0  | 3852 | 0.6465          | 0.7819   | 0.8285    | 0.7819 | 0.7960 |
| 0.4607        | 13.0  | 4173 | 0.6070          | 0.8190   | 0.8411    | 0.8190 | 0.8195 |
| 0.4558        | 14.0  | 4494 | 0.6088          | 0.8138   | 0.8424    | 0.8138 | 0.8215 |
| 0.3984        | 15.0  | 4815 | 0.5507          | 0.8308   | 0.8486    | 0.8308 | 0.8343 |
| 0.3541        | 16.0  | 5136 | 0.5112          | 0.8412   | 0.8528    | 0.8412 | 0.8448 |
| 0.3203        | 17.0  | 5457 | 0.5000          | 0.8519   | 0.8575    | 0.8519 | 0.8527 |
| 0.2685        | 18.0  | 5778 | 0.5630          | 0.8429   | 0.8574    | 0.8429 | 0.8472 |
| 0.214         | 19.0  | 6099 | 0.5670          | 0.8405   | 0.8607    | 0.8405 | 0.8464 |
| 0.2195        | 20.0  | 6420 | 0.6209          | 0.8478   | 0.8557    | 0.8478 | 0.8500 |
| 0.1598        | 21.0  | 6741 | 0.5597          | 0.8630   | 0.8585    | 0.8630 | 0.8590 |
| 0.1174        | 22.0  | 7062 | 0.5682          | 0.8637   | 0.8617    | 0.8637 | 0.8624 |
| 0.1341        | 23.0  | 7383 | 0.6186          | 0.8662   | 0.8638    | 0.8662 | 0.8622 |
| 0.1307        | 24.0  | 7704 | 0.5961          | 0.8727   | 0.8710    | 0.8727 | 0.8701 |
| 0.1075        | 25.0  | 8025 | 0.5912          | 0.8738   | 0.8715    | 0.8738 | 0.8717 |
| 0.0741        | 26.0  | 8346 | 0.5991          | 0.8755   | 0.8711    | 0.8755 | 0.8713 |
| 0.1476        | 27.0  | 8667 | 0.5900          | 0.8745   | 0.8705    | 0.8745 | 0.8714 |


### Framework versions

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

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