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# vit-food-classification-gutkia01

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the food-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- 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: 5e-05
- 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0           | 1.0   | 2171  | 0.0000          | 1.0      |
| 0.0           | 2.0   | 4342  | 0.0000          | 1.0      |
| 0.0           | 3.0   | 6513  | 0.0000          | 1.0      |
| 0.0           | 4.0   | 8684  | 0.0000          | 1.0      |
| 0.0           | 5.0   | 10855 | 0.0000          | 1.0      |
| 0.0           | 6.0   | 13026 | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

fruits junkfood