---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine-tuned-model
  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. -->

# fine-tuned-model

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the Falah/Alzheimer_MRI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8720
- Accuracy: 0.5742

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9696        | 1.0   | 256  | 0.8925          | 0.5781   |
| 0.9141        | 2.0   | 512  | 0.8447          | 0.5938   |
| 0.8669        | 3.0   | 768  | 0.8378          | 0.6035   |
| 0.8356        | 4.0   | 1024 | 0.8236          | 0.5938   |
| 0.8529        | 5.0   | 1280 | 0.8206          | 0.6074   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1