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# convnext-base-384-finetuned-alzheimer-MRI

This model is a fine-tuned version of [facebook/convnext-base-384](https://huggingface.co/facebook/convnext-base-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8576
- Accuracy: 0.5805

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9877        | 1.0   | 36   | 0.9405          | 0.5625   |
| 0.8723        | 2.0   | 72   | 0.8801          | 0.5957   |
| 0.8327        | 3.0   | 108  | 0.8639          | 0.5977   |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0

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