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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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0984
- Accuracy: 0.9762

## 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: 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
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1192        | 0.1764 | 100  | 0.1158          | 0.9692   |
| 0.0734        | 0.3527 | 200  | 0.1268          | 0.9702   |
| 0.0701        | 0.5291 | 300  | 0.1057          | 0.9673   |
| 0.1107        | 0.7055 | 400  | 0.1081          | 0.9722   |
| 0.0413        | 0.8818 | 500  | 0.0984          | 0.9762   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

negative positive