---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: CynthiaCR/food_classifier
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# CynthiaCR/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: 0.5354
- Validation Loss: 1.3575
- Train Accuracy: 0.5062
- Epoch: 9

## 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': 6400, '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': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.0502     | 2.0061          | 0.2375         | 0     |
| 1.8368     | 1.7539          | 0.3187         | 1     |
| 1.6074     | 1.6316          | 0.3875         | 2     |
| 1.4768     | 1.5368          | 0.4437         | 3     |
| 1.3390     | 1.4388          | 0.4813         | 4     |
| 1.1889     | 1.3995          | 0.4562         | 5     |
| 1.0397     | 1.3773          | 0.4688         | 6     |
| 0.8703     | 1.4785          | 0.4625         | 7     |
| 0.6962     | 1.3854          | 0.4938         | 8     |
| 0.5354     | 1.3575          | 0.5062         | 9     |


### Framework versions

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