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# swin-tiny-patch4-window7-224-med-device-classification

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2927
- Accuracy: 0.75

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 1.6093          | 0.5      |
| No log        | 2.0   | 2    | 1.6063          | 0.5      |
| No log        | 3.0   | 3    | 1.6063          | 0.5      |
| No log        | 4.0   | 4    | 1.6100          | 0.25     |
| No log        | 5.0   | 5    | 1.6100          | 0.25     |
| No log        | 6.0   | 6    | 1.6170          | 0.25     |
| No log        | 7.0   | 7    | 1.6170          | 0.25     |
| No log        | 8.0   | 8    | 1.5910          | 0.25     |
| No log        | 9.0   | 9    | 1.5910          | 0.25     |
| 0.7949        | 10.0  | 10   | 1.5705          | 0.25     |
| 0.7949        | 11.0  | 11   | 1.5705          | 0.25     |
| 0.7949        | 12.0  | 12   | 1.5368          | 0.25     |
| 0.7949        | 13.0  | 13   | 1.5368          | 0.25     |
| 0.7949        | 14.0  | 14   | 1.4843          | 0.25     |
| 0.7949        | 15.0  | 15   | 1.4843          | 0.25     |
| 0.7949        | 16.0  | 16   | 1.4413          | 0.25     |
| 0.7949        | 17.0  | 17   | 1.4413          | 0.25     |
| 0.7949        | 18.0  | 18   | 1.4050          | 0.5      |
| 0.7949        | 19.0  | 19   | 1.4050          | 0.5      |
| 0.6509        | 20.0  | 20   | 1.3670          | 0.5      |
| 0.6509        | 21.0  | 21   | 1.3670          | 0.5      |
| 0.6509        | 22.0  | 22   | 1.3404          | 0.5      |
| 0.6509        | 23.0  | 23   | 1.3404          | 0.5      |
| 0.6509        | 24.0  | 24   | 1.3212          | 0.5      |
| 0.6509        | 25.0  | 25   | 1.3212          | 0.5      |
| 0.6509        | 26.0  | 26   | 1.3087          | 0.5      |
| 0.6509        | 27.0  | 27   | 1.3087          | 0.5      |
| 0.6509        | 28.0  | 28   | 1.2969          | 0.75     |
| 0.6509        | 29.0  | 29   | 1.2969          | 0.75     |
| 0.5774        | 30.0  | 30   | 1.2927          | 0.75     |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3

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