đ Imene/vit-base-patch16-224-in21k-wwwwii
This model is a fine - tuned version of google/vit-base-patch16-224-in21k on an unknown dataset, achieving specific results on the evaluation set.
đ Quick Start
This model is a fine - tuned version of google/vit-base-patch16-224-in21k on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.8024
- Train Accuracy: 0.9939
- Train Top - 3 - accuracy: 0.9997
- Validation Loss: 1.6739
- Validation Accuracy: 0.6267
- Validation Top - 3 - accuracy: 0.8349
- Epoch: 9
đ Documentation
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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 4e - 05, 'decay_steps': 1620, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e - 08, 'amsgrad': False, 'weight_decay_rate': 0.001}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
Train Loss |
Train Accuracy |
Train Top - 3 - accuracy |
Validation Loss |
Validation Accuracy |
Validation Top - 3 - accuracy |
Epoch |
3.6793 |
0.125 |
0.2805 |
3.4078 |
0.2151 |
0.4756 |
0 |
3.1763 |
0.3448 |
0.6265 |
3.0167 |
0.4209 |
0.6640 |
1 |
2.7546 |
0.5419 |
0.7852 |
2.6634 |
0.5326 |
0.7651 |
2 |
2.3537 |
0.6855 |
0.8843 |
2.3971 |
0.5547 |
0.7860 |
3 |
1.9989 |
0.7814 |
0.9279 |
2.2236 |
0.5837 |
0.7907 |
4 |
1.6670 |
0.875 |
0.9698 |
2.0757 |
0.5977 |
0.7907 |
5 |
1.3815 |
0.9352 |
0.9890 |
1.8921 |
0.6198 |
0.8174 |
6 |
1.1407 |
0.9651 |
0.9956 |
1.7976 |
0.6244 |
0.8174 |
7 |
0.9451 |
0.9866 |
0.9983 |
1.7227 |
0.6349 |
0.8267 |
8 |
0.8024 |
0.9939 |
0.9997 |
1.6739 |
0.6267 |
0.8349 |
9 |
Framework versions
- Transformers 4.21.2
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
đ License
This model is licensed under the Apache 2.0 license.