---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: alzheimer_mri_classification
  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. -->

# alzheimer_mri_classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3404
- Accuracy: 0.8770

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 128  | 0.8345          | 0.5996   |
| No log        | 2.0   | 256  | 0.8245          | 0.6309   |
| No log        | 3.0   | 384  | 0.7492          | 0.6543   |
| 0.8188        | 4.0   | 512  | 0.7173          | 0.6777   |
| 0.8188        | 5.0   | 640  | 0.6625          | 0.7168   |
| 0.8188        | 6.0   | 768  | 0.6182          | 0.7373   |
| 0.8188        | 7.0   | 896  | 0.5058          | 0.8027   |
| 0.5344        | 8.0   | 1024 | 0.5567          | 0.7764   |
| 0.5344        | 9.0   | 1152 | 0.4702          | 0.8193   |
| 0.5344        | 10.0  | 1280 | 0.4502          | 0.8242   |
| 0.5344        | 11.0  | 1408 | 0.4024          | 0.8408   |
| 0.3356        | 12.0  | 1536 | 0.4263          | 0.8516   |
| 0.3356        | 13.0  | 1664 | 0.3782          | 0.8535   |
| 0.3356        | 14.0  | 1792 | 0.3378          | 0.8604   |
| 0.3356        | 15.0  | 1920 | 0.3570          | 0.8701   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2