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# swin-tiny-patch4-window7-224-finetuned-ViT

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: 0.2048
- Accuracy: 0.9371

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1549        | 1.0   | 41   | 0.8420          | 0.7654   |
| 0.5664        | 2.0   | 82   | 0.4272          | 0.8525   |
| 0.4053        | 3.0   | 123  | 0.3613          | 0.8767   |
| 0.3093        | 4.0   | 164  | 0.3808          | 0.8658   |
| 0.3           | 5.0   | 205  | 0.2971          | 0.8863   |
| 0.2445        | 6.0   | 246  | 0.3009          | 0.8851   |
| 0.2508        | 7.0   | 287  | 0.2582          | 0.9105   |
| 0.1998        | 8.0   | 328  | 0.2356          | 0.9202   |
| 0.1722        | 9.0   | 369  | 0.2187          | 0.9287   |
| 0.1176        | 10.0  | 410  | 0.2048          | 0.9371   |
| 0.1073        | 11.0  | 451  | 0.2066          | 0.9274   |
| 0.1075        | 12.0  | 492  | 0.2239          | 0.9262   |
| 0.1109        | 13.0  | 533  | 0.2336          | 0.9202   |
| 0.095         | 14.0  | 574  | 0.2187          | 0.9347   |
| 0.0824        | 15.0  | 615  | 0.2178          | 0.9287   |
| 0.0757        | 16.0  | 656  | 0.1958          | 0.9359   |
| 0.0643        | 17.0  | 697  | 0.2183          | 0.9335   |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0

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