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# alzheimer_model_aug_deit5

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0472
- Accuracy: 0.9939

## 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: 16
- eval_batch_size: 8
- seed: 1234
- gradient_accumulation_steps: 10
- total_train_batch_size: 160
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.97  | 12   | 0.5252          | 0.8947   |
| No log        | 1.94  | 24   | 0.1506          | 0.9636   |
| No log        | 2.98  | 37   | 0.0787          | 0.9858   |
| No log        | 3.95  | 49   | 0.0587          | 0.9919   |
| No log        | 4.84  | 60   | 0.0472          | 0.9939   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

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