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# shbA/food_classifier

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6730
- Train Accuracy: 0.675
- Validation Loss: 0.6380
- Validation Accuracy: 0.8000
- Epoch: 5

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1600, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.05}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.8438     | 0.625          | 0.6171          | 0.8000              | 0     |
| 0.9123     | 0.625          | 0.8710          | 0.6000              | 1     |
| 0.7847     | 0.7            | 0.5295          | 1.0                 | 2     |
| 0.8369     | 0.625          | 0.5829          | 1.0                 | 3     |
| 0.7734     | 0.675          | 1.0318          | 0.4000              | 4     |
| 0.6730     | 0.675          | 0.6380          | 0.8000              | 5     |


### Framework versions

- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

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