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# swin-small-patch4-window7-224-finetuned-isic217

This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9417
- Accuracy: 0.5455

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.1844        | 0.9796  | 24   | 2.1103          | 0.1364   |
| 2.0018        | 2.0     | 49   | 1.8737          | 0.2727   |
| 1.6474        | 2.9796  | 73   | 1.9019          | 0.2727   |
| 1.3757        | 4.0     | 98   | 1.7487          | 0.3636   |
| 1.1526        | 4.9796  | 122  | 1.7576          | 0.4091   |
| 0.9161        | 6.0     | 147  | 1.5886          | 0.5      |
| 0.7568        | 6.9796  | 171  | 1.8935          | 0.4545   |
| 0.4024        | 8.0     | 196  | 1.6767          | 0.4545   |
| 0.814         | 8.9796  | 220  | 1.7112          | 0.3636   |
| 0.4346        | 10.0    | 245  | 1.9364          | 0.4091   |
| 0.3456        | 10.9796 | 269  | 1.9417          | 0.5455   |
| 0.228         | 12.0    | 294  | 2.1569          | 0.4091   |
| 0.1681        | 12.9796 | 318  | 2.0565          | 0.4545   |
| 0.1498        | 14.0    | 343  | 2.0701          | 0.3636   |
| 0.1599        | 14.9796 | 367  | 2.4973          | 0.5      |
| 0.3856        | 16.0    | 392  | 2.2473          | 0.4545   |
| 0.2529        | 16.9796 | 416  | 2.0918          | 0.4545   |
| 0.0557        | 18.0    | 441  | 1.9596          | 0.5455   |
| 0.0895        | 18.9796 | 465  | 2.5522          | 0.4545   |
| 0.0719        | 20.0    | 490  | 2.2938          | 0.5      |
| 0.0764        | 20.9796 | 514  | 2.6754          | 0.4545   |
| 0.1301        | 22.0    | 539  | 2.5287          | 0.4545   |
| 0.1205        | 22.9796 | 563  | 2.7532          | 0.4091   |
| 0.1013        | 24.0    | 588  | 2.6988          | 0.4545   |
| 0.0777        | 24.9796 | 612  | 2.9345          | 0.4091   |
| 0.1807        | 26.0    | 637  | 2.9981          | 0.4545   |
| 0.0298        | 26.9796 | 661  | 2.8549          | 0.4545   |
| 0.0589        | 28.0    | 686  | 2.6967          | 0.4545   |
| 0.0896        | 28.9796 | 710  | 2.6903          | 0.4545   |
| 0.0218        | 29.3878 | 720  | 2.6902          | 0.4545   |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

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