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# swin-brain-plane-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: 0.0556
- Accuracy: 0.9778

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0606        | 1.0   | 5    | 0.7887          | 0.8741   |
| 0.7256        | 2.0   | 10   | 0.3949          | 0.9111   |
| 0.4331        | 3.0   | 15   | 0.1731          | 0.9704   |
| 0.3165        | 4.0   | 20   | 0.1250          | 0.9630   |
| 0.1827        | 5.0   | 25   | 0.0847          | 0.9704   |
| 0.1488        | 6.0   | 30   | 0.0919          | 0.9630   |
| 0.1425        | 7.0   | 35   | 0.0604          | 0.9778   |
| 0.1487        | 8.0   | 40   | 0.0718          | 0.9778   |
| 0.118         | 9.0   | 45   | 0.0578          | 0.9778   |
| 0.1278        | 10.0  | 50   | 0.0556          | 0.9778   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

axial coronal sagittal