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---
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
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