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# swin-tiny-patch4-window7-224-finetuned-skin-cancer

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2772
- Accuracy: 0.8984
- Precision Per Class: {0: 0.8644793152639088, 1: 0.8451327433628318, 2: 0.8794117647058823, 3: 0.9717607973421927, 4: 0.8483606557377049, 5: 0.8936507936507937, 6: 1.0}
- Recall Per Class: {0: 0.9237804878048781, 1: 0.8280346820809249, 2: 0.8978978978978979, 3: 0.8369098712446352, 4: 0.9338345864661655, 5: 0.8922345483359746, 6: 0.9795620437956204}
- F1 Per Class: {0: 0.8931466470154754, 1: 0.8364963503649636, 2: 0.8885586924219911, 3: 0.8993082244427363, 4: 0.8890479599141016, 5: 0.8929421094369548, 6: 0.9896755162241887}
- Auc Roc Per Class: {0: 0.9915928254750601, 1: 0.9884721656512784, 2: 0.9917100566306127, 3: 0.9958148687289727, 4: 0.9937121284223217, 5: 0.9929341867176752, 6: 0.9997305333073577}

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Per Class                                                                                                                                | Recall Per Class                                                                                                                                                  | F1 Per Class                                                                                                                                                      | Auc Roc Per Class                                                                                                                                                 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| 0.362         | 1.0   | 330  | 0.2772          | 0.8984   | {0: 0.8644793152639088, 1: 0.8451327433628318, 2: 0.8794117647058823, 3: 0.9717607973421927, 4: 0.8483606557377049, 5: 0.8936507936507937, 6: 1.0} | {0: 0.9237804878048781, 1: 0.8280346820809249, 2: 0.8978978978978979, 3: 0.8369098712446352, 4: 0.9338345864661655, 5: 0.8922345483359746, 6: 0.9795620437956204} | {0: 0.8931466470154754, 1: 0.8364963503649636, 2: 0.8885586924219911, 3: 0.8993082244427363, 4: 0.8890479599141016, 5: 0.8929421094369548, 6: 0.9896755162241887} | {0: 0.9915928254750601, 1: 0.9884721656512784, 2: 0.9917100566306127, 3: 0.9958148687289727, 4: 0.9937121284223217, 5: 0.9929341867176752, 6: 0.9997305333073577} |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2

actinic_keratoses basal_cell_carcinoma benign_keratosis_like dermatofibroma melanocytic_nevi melanoma vascular_lesions