---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: arieg/bw_spec_cls_4_01_s_200
  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. -->

# arieg/bw_spec_cls_4_01_s_200

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: 0.0157
- Train Sparse Categorical Accuracy: 1.0
- Validation Loss: 0.0151
- Validation Sparse Categorical Accuracy: 1.0
- Epoch: 19

## 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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 14400, '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 | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.7760     | 0.8944                            | 0.3046          | 1.0                                    | 0     |
| 0.2006     | 1.0                               | 0.1346          | 1.0                                    | 1     |
| 0.1136     | 1.0                               | 0.0957          | 1.0                                    | 2     |
| 0.0865     | 1.0                               | 0.0768          | 1.0                                    | 3     |
| 0.0712     | 1.0                               | 0.0652          | 1.0                                    | 4     |
| 0.0611     | 1.0                               | 0.0565          | 1.0                                    | 5     |
| 0.0532     | 1.0                               | 0.0498          | 1.0                                    | 6     |
| 0.0471     | 1.0                               | 0.0441          | 1.0                                    | 7     |
| 0.0420     | 1.0                               | 0.0395          | 1.0                                    | 8     |
| 0.0376     | 1.0                               | 0.0355          | 1.0                                    | 9     |
| 0.0339     | 1.0                               | 0.0321          | 1.0                                    | 10    |
| 0.0307     | 1.0                               | 0.0291          | 1.0                                    | 11    |
| 0.0279     | 1.0                               | 0.0266          | 1.0                                    | 12    |
| 0.0255     | 1.0                               | 0.0243          | 1.0                                    | 13    |
| 0.0233     | 1.0                               | 0.0223          | 1.0                                    | 14    |
| 0.0214     | 1.0                               | 0.0205          | 1.0                                    | 15    |
| 0.0198     | 1.0                               | 0.0190          | 1.0                                    | 16    |
| 0.0183     | 1.0                               | 0.0175          | 1.0                                    | 17    |
| 0.0169     | 1.0                               | 0.0163          | 1.0                                    | 18    |
| 0.0157     | 1.0                               | 0.0151          | 1.0                                    | 19    |


### Framework versions

- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1