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# arieg/bw_spec_cls_4_01_noise_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: 0.0370
- Train Categorical Accuracy: 0.2486
- Validation Loss: 0.0349
- Validation Categorical Accuracy: 0.2625
- 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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 7200, '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 Categorical Accuracy | Validation Loss | Validation Categorical Accuracy | Epoch |
|:----------:|:--------------------------:|:---------------:|:-------------------------------:|:-----:|
| 0.6021     | 0.2458                     | 0.2372          | 0.2625                          | 0     |
| 0.1654     | 0.2486                     | 0.1210          | 0.2625                          | 1     |
| 0.1042     | 0.2486                     | 0.0902          | 0.2625                          | 2     |
| 0.0819     | 0.2486                     | 0.0741          | 0.2625                          | 3     |
| 0.0688     | 0.2486                     | 0.0634          | 0.2625                          | 4     |
| 0.0595     | 0.2486                     | 0.0553          | 0.2625                          | 5     |
| 0.0522     | 0.2486                     | 0.0488          | 0.2625                          | 6     |
| 0.0462     | 0.2486                     | 0.0434          | 0.2625                          | 7     |
| 0.0412     | 0.2486                     | 0.0388          | 0.2625                          | 8     |
| 0.0370     | 0.2486                     | 0.0349          | 0.2625                          | 9     |


### Framework versions

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

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