---
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: 0.0046
- Train Sparse Categorical Accuracy: 1.0
- Validation Loss: 0.0045
- Validation Sparse Categorical Accuracy: 1.0
- Epoch: 39

## 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': 28800, '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 |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.7335     | 0.9306                            | 0.3009          | 1.0                                    | 0     |
| 0.1862     | 1.0                               | 0.1287          | 1.0                                    | 1     |
| 0.1060     | 1.0                               | 0.0894          | 1.0                                    | 2     |
| 0.0803     | 1.0                               | 0.0719          | 1.0                                    | 3     |
| 0.0664     | 1.0                               | 0.0611          | 1.0                                    | 4     |
| 0.0570     | 1.0                               | 0.0530          | 1.0                                    | 5     |
| 0.0498     | 1.0                               | 0.0468          | 1.0                                    | 6     |
| 0.0440     | 1.0                               | 0.0415          | 1.0                                    | 7     |
| 0.0392     | 1.0                               | 0.0372          | 1.0                                    | 8     |
| 0.0352     | 1.0                               | 0.0334          | 1.0                                    | 9     |
| 0.0317     | 1.0                               | 0.0302          | 1.0                                    | 10    |
| 0.0287     | 1.0                               | 0.0274          | 1.0                                    | 11    |
| 0.0261     | 1.0                               | 0.0250          | 1.0                                    | 12    |
| 0.0238     | 1.0                               | 0.0228          | 1.0                                    | 13    |
| 0.0218     | 1.0                               | 0.0209          | 1.0                                    | 14    |
| 0.0200     | 1.0                               | 0.0193          | 1.0                                    | 15    |
| 0.0184     | 1.0                               | 0.0178          | 1.0                                    | 16    |
| 0.0170     | 1.0                               | 0.0164          | 1.0                                    | 17    |
| 0.0157     | 1.0                               | 0.0152          | 1.0                                    | 18    |
| 0.0146     | 1.0                               | 0.0141          | 1.0                                    | 19    |
| 0.0136     | 1.0                               | 0.0132          | 1.0                                    | 20    |
| 0.0126     | 1.0                               | 0.0123          | 1.0                                    | 21    |
| 0.0118     | 1.0                               | 0.0115          | 1.0                                    | 22    |
| 0.0111     | 1.0                               | 0.0108          | 1.0                                    | 23    |
| 0.0104     | 1.0                               | 0.0101          | 1.0                                    | 24    |
| 0.0097     | 1.0                               | 0.0095          | 1.0                                    | 25    |
| 0.0091     | 1.0                               | 0.0089          | 1.0                                    | 26    |
| 0.0086     | 1.0                               | 0.0084          | 1.0                                    | 27    |
| 0.0081     | 1.0                               | 0.0079          | 1.0                                    | 28    |
| 0.0077     | 1.0                               | 0.0075          | 1.0                                    | 29    |
| 0.0072     | 1.0                               | 0.0071          | 1.0                                    | 30    |
| 0.0069     | 1.0                               | 0.0067          | 1.0                                    | 31    |
| 0.0065     | 1.0                               | 0.0064          | 1.0                                    | 32    |
| 0.0062     | 1.0                               | 0.0060          | 1.0                                    | 33    |
| 0.0058     | 1.0                               | 0.0057          | 1.0                                    | 34    |
| 0.0056     | 1.0                               | 0.0055          | 1.0                                    | 35    |
| 0.0053     | 1.0                               | 0.0052          | 1.0                                    | 36    |
| 0.0050     | 1.0                               | 0.0049          | 1.0                                    | 37    |
| 0.0048     | 1.0                               | 0.0047          | 1.0                                    | 38    |
| 0.0046     | 1.0                               | 0.0045          | 1.0                                    | 39    |


### Framework versions

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