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# swin-base-patch4-window7-224_11092024

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5135
- Accuracy: 0.8337

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0366        | 1.0   | 400  | 0.9471          | 0.72     |
| 0.8257        | 2.0   | 800  | 0.7889          | 0.7538   |
| 0.7119        | 3.0   | 1200 | 0.7232          | 0.7775   |
| 0.6969        | 4.0   | 1600 | 0.6739          | 0.7837   |
| 0.6487        | 5.0   | 2000 | 0.6371          | 0.7863   |
| 0.5956        | 6.0   | 2400 | 0.6198          | 0.7887   |
| 0.5604        | 7.0   | 2800 | 0.5941          | 0.8025   |
| 0.5732        | 8.0   | 3200 | 0.5867          | 0.795    |
| 0.5578        | 9.0   | 3600 | 0.5705          | 0.8025   |
| 0.5449        | 10.0  | 4000 | 0.5575          | 0.8113   |
| 0.5419        | 11.0  | 4400 | 0.5505          | 0.8213   |
| 0.5086        | 12.0  | 4800 | 0.5385          | 0.8213   |
| 0.4929        | 13.0  | 5200 | 0.5340          | 0.8213   |
| 0.4701        | 14.0  | 5600 | 0.5297          | 0.8187   |
| 0.4803        | 15.0  | 6000 | 0.5240          | 0.8225   |
| 0.4988        | 16.0  | 6400 | 0.5197          | 0.83     |
| 0.4842        | 17.0  | 6800 | 0.5165          | 0.8313   |
| 0.4917        | 18.0  | 7200 | 0.5148          | 0.8313   |
| 0.4734        | 19.0  | 7600 | 0.5140          | 0.8325   |
| 0.4714        | 20.0  | 8000 | 0.5135          | 0.8337   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cpu
- Datasets 3.0.1
- Tokenizers 0.20.1

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