---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-brain-alzheimer-detection
  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-alzheimer-detection

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: 0.2428
- Accuracy: 0.9508

## 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: 2e-05
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9772        | 0.7812  | 200  | 0.9400          | 0.5801   |
| 0.7451        | 1.5625  | 400  | 0.7947          | 0.6553   |
| 0.5701        | 2.3438  | 600  | 0.7642          | 0.7236   |
| 0.3704        | 3.125   | 800  | 0.5532          | 0.7744   |
| 0.2906        | 3.9062  | 1000 | 0.4423          | 0.8555   |
| 0.1636        | 4.6875  | 1200 | 0.3226          | 0.9004   |
| 0.0837        | 5.4688  | 1400 | 0.3483          | 0.9023   |
| 0.0368        | 6.25    | 1600 | 0.2423          | 0.9395   |
| 0.063         | 7.0312  | 1800 | 0.3091          | 0.9277   |
| 0.047         | 7.8125  | 2000 | 0.3907          | 0.9023   |
| 0.0127        | 8.5938  | 2200 | 0.2002          | 0.9561   |
| 0.0102        | 9.375   | 2400 | 0.3001          | 0.9307   |
| 0.0086        | 10.1562 | 2600 | 0.1998          | 0.9512   |
| 0.0073        | 10.9375 | 2800 | 0.1932          | 0.9590   |
| 0.0064        | 11.7188 | 3000 | 0.1988          | 0.9561   |
| 0.0056        | 12.5    | 3200 | 0.1993          | 0.9580   |
| 0.0049        | 13.2812 | 3400 | 0.2047          | 0.9590   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1