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# TransferLearning-BrainTumorClassifier

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the BrainTumorMRIForFineTuningViT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7952
- Accuracy: 0.7818

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0462        | 1.0   | 304  | 1.0010          | 0.6418   |
| 0.9093        | 2.0   | 608  | 0.8900          | 0.7433   |
| 0.8251        | 3.0   | 912  | 0.8286          | 0.7678   |
| 0.8113        | 4.0   | 1216 | 0.8048          | 0.7841   |
| 0.8115        | 5.0   | 1520 | 0.7952          | 0.7818   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

glioma meningioma notumor pituitary