---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-brain-mri
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-brain-mri

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the BrainMRI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1297
- Accuracy: 0.5685

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 72   | 0.6289   | 0.9818          |
| 1.0744        | 2.0   | 144  | 0.6864   | 0.8287          |
| 0.7716        | 3.0   | 216  | 0.7160   | 0.7535          |
| 0.7716        | 4.0   | 288  | 0.7404   | 0.7140          |
| 0.6975        | 5.0   | 360  | 0.7491   | 0.7015          |
| 0.6651        | 6.0   | 432  | 0.7631   | 0.6839          |
| 0.6307        | 7.0   | 504  | 0.7700   | 0.6624          |
| 0.6307        | 8.0   | 576  | 0.7822   | 0.6363          |
| 0.5857        | 9.0   | 648  | 0.7822   | 0.6089          |
| 0.576         | 10.0  | 720  | 0.7770   | 0.6249          |
| 0.576         | 11.0  | 792  | 0.6184   | 0.7840          |
| 0.5733        | 12.0  | 864  | 0.6006   | 0.7944          |
| 0.5555        | 13.0  | 936  | 0.5898   | 0.8014          |
| 0.5481        | 14.0  | 1008 | 0.5857   | 0.8223          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1