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# brain-tumor-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 the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1636
- Accuracy: 0.9373

## 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 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8509        | 0.9877 | 20   | 0.5305          | 0.8467   |
| 0.4478        | 1.9753 | 40   | 0.3092          | 0.9094   |
| 0.3313        | 2.9630 | 60   | 0.2422          | 0.9233   |
| 0.2777        | 4.0    | 81   | 0.1716          | 0.9373   |
| 0.2465        | 4.9383 | 100  | 0.1636          | 0.9373   |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1

glioma_tumor meningioma_tumor no_tumor pituitary_tumor