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# swin-tiny-patch4-window7-224-finetunedo

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: 0.3710
- Roc Auc: 0.8606

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 3    | 0.5066          | 0.7647  |
| No log        | 2.0   | 6    | 0.4204          | 0.7941  |
| No log        | 3.0   | 9    | 0.4298          | 0.7353  |
| 0.4868        | 4.0   | 12   | 0.4040          | 0.8018  |
| 0.4868        | 5.0   | 15   | 0.3925          | 0.7724  |
| 0.4868        | 6.0   | 18   | 0.3674          | 0.8235  |
| 0.4096        | 7.0   | 21   | 0.3673          | 0.8606  |
| 0.4096        | 8.0   | 24   | 0.3710          | 0.8606  |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

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