---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: leopuv/dog_chicken_muffin_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. -->

# leopuv/dog_chicken_muffin_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: 0.0326
- Train Accuracy: 0.9947
- Validation Loss: 0.0191
- Validation Accuracy: 0.9947
- 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': 22500, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.4271     | 0.996          | 0.1010          | 0.9960              | 0     |
| 0.1111     | 0.9933         | 0.0613          | 0.9933              | 1     |
| 0.0774     | 0.9947         | 0.0451          | 0.9947              | 2     |
| 0.0592     | 0.9947         | 0.0354          | 0.9947              | 3     |
| 0.0457     | 0.9987         | 0.0252          | 0.9987              | 4     |
| 0.0434     | 0.992          | 0.0346          | 0.9920              | 5     |
| 0.0429     | 0.996          | 0.0270          | 0.9960              | 6     |
| 0.0397     | 0.9973         | 0.0177          | 0.9973              | 7     |
| 0.0326     | 0.9973         | 0.0161          | 0.9973              | 8     |
| 0.0326     | 0.9947         | 0.0191          | 0.9947              | 9     |


### Framework versions

- Transformers 4.30.2
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3