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# beit-base-patch16-224-pt22k-ft22k-finetuned-Brain_Cancer

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4982
- Accuracy: 0.8540
- Precision: 0.8565
- F1 Score: 0.8532

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | F1 Score |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:--------:|
| 1.1401        | 1.0    | 5    | 0.9244          | 0.5885   | 0.7026    | 0.5746   |
| 0.6598        | 2.0    | 10   | 0.5261          | 0.8496   | 0.8513    | 0.8481   |
| 0.5349        | 2.4706 | 12   | 0.4982          | 0.8540   | 0.8565    | 0.8532   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

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