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# vit-base-beans-demo-v5

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the PI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0163
- Accuracy: 1.0

## 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: 0.0002
- 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
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1419        | 0.6944 | 100  | 0.1322          | 0.9860   |
| 0.0526        | 1.3889 | 200  | 0.0472          | 0.9965   |
| 0.0287        | 2.0833 | 300  | 0.0333          | 0.9965   |
| 0.0193        | 2.7778 | 400  | 0.0171          | 1.0      |
| 0.0159        | 3.4722 | 500  | 0.0146          | 1.0      |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

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