---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: fanaf91318/image-classifier-78-10-epoch-clean
  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. -->

# fanaf91318/image-classifier-78-10-epoch-clean

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: 0.7377
- Validation Loss: 1.1864
- Train Accuracy: 0.7046
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 59000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 3.7894     | 3.2415          | 0.3476         | 0     |
| 2.9188     | 2.5308          | 0.4824         | 1     |
| 2.2939     | 2.0642          | 0.5501         | 2     |
| 1.8570     | 1.7353          | 0.5962         | 3     |
| 1.5300     | 1.5211          | 0.6369         | 4     |
| 1.2610     | 1.4143          | 0.6612         | 5     |
| 1.0738     | 1.2610          | 0.6965         | 6     |
| 0.9197     | 1.2404          | 0.6897         | 7     |
| 0.8280     | 1.2069          | 0.6985         | 8     |
| 0.7377     | 1.1864          | 0.7046         | 9     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1