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# swin-transformer-results

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8055
- Accuracy: 0.6794
- F1: 0.6810
- Precision: 0.6904

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|
| 1.0686        | 0.1952 | 500  | 1.0585          | 0.5266   | 0.5042 | 0.5355    |
| 1.3283        | 0.3903 | 1000 | 1.0015          | 0.5722   | 0.5794 | 0.6006    |
| 0.991         | 0.5855 | 1500 | 0.9601          | 0.5828   | 0.5865 | 0.6194    |
| 0.7919        | 0.7806 | 2000 | 0.9066          | 0.6135   | 0.6191 | 0.6580    |
| 0.9748        | 0.9758 | 2500 | 0.8327          | 0.6460   | 0.6443 | 0.6458    |
| 0.7183        | 1.1710 | 3000 | 0.8808          | 0.6421   | 0.6419 | 0.6638    |
| 0.769         | 1.3661 | 3500 | 0.8454          | 0.6526   | 0.6483 | 0.6553    |
| 0.8558        | 1.5613 | 4000 | 0.8773          | 0.6482   | 0.6364 | 0.6454    |
| 0.6713        | 1.7564 | 4500 | 0.8338          | 0.6561   | 0.6560 | 0.6711    |
| 0.7476        | 1.9516 | 5000 | 0.8083          | 0.6632   | 0.6636 | 0.6690    |
| 0.6896        | 2.1468 | 5500 | 0.8055          | 0.6794   | 0.6810 | 0.6904    |
| 0.648         | 2.3419 | 6000 | 0.8252          | 0.6697   | 0.6726 | 0.6822    |
| 0.5969        | 2.5371 | 6500 | 0.8179          | 0.6697   | 0.6676 | 0.6661    |
| 0.7098        | 2.7322 | 7000 | 0.8139          | 0.6724   | 0.6705 | 0.6698    |
| 0.5318        | 2.9274 | 7500 | 0.8033          | 0.6790   | 0.6783 | 0.6793    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cpu
- Datasets 3.0.0
- Tokenizers 0.19.1

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