---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: alzheimer_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_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: 0.3183
- F1: 0.8946

## 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 128  | 0.8686          | 0.5548 |
| No log        | 2.0   | 256  | 0.8457          | 0.6087 |
| No log        | 3.0   | 384  | 0.7396          | 0.6478 |
| 0.8172        | 4.0   | 512  | 0.6833          | 0.6826 |
| 0.8172        | 5.0   | 640  | 0.6280          | 0.7205 |
| 0.8172        | 6.0   | 768  | 0.5347          | 0.7727 |
| 0.8172        | 7.0   | 896  | 0.5108          | 0.7909 |
| 0.5292        | 8.0   | 1024 | 0.4707          | 0.8078 |
| 0.5292        | 9.0   | 1152 | 0.4477          | 0.8302 |
| 0.5292        | 10.0  | 1280 | 0.4075          | 0.8511 |
| 0.5292        | 11.0  | 1408 | 0.4263          | 0.8380 |
| 0.3498        | 12.0  | 1536 | 0.3558          | 0.8756 |
| 0.3498        | 13.0  | 1664 | 0.3768          | 0.8558 |
| 0.3498        | 14.0  | 1792 | 0.3412          | 0.8701 |
| 0.3498        | 15.0  | 1920 | 0.3028          | 0.8952 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1