đ Imene/vit-base-patch16-224-wi2
This model is a fine - tuned version of google/vit-base-patch16-224, aiming to provide better performance on specific tasks.
đ Quick Start
This model is a fine - tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.3098
- Train Accuracy: 0.9821
- Train Top - 5 - accuracy: 0.9971
- Validation Loss: 3.0737
- Validation Accuracy: 0.2491
- Validation Top - 5 - accuracy: 0.4476
- 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': 0.0003, 'decay_steps': 1750, '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 - 5 - accuracy |
Validation Loss |
Validation Accuracy |
Validation Top - 5 - accuracy |
Epoch |
4.4859 |
0.0195 |
0.0579 |
4.2995 |
0.0368 |
0.0865 |
0 |
4.1729 |
0.0355 |
0.0987 |
4.0916 |
0.0472 |
0.1266 |
1 |
3.9541 |
0.0666 |
0.1641 |
3.8050 |
0.0781 |
0.2035 |
2 |
3.5823 |
0.1247 |
0.2615 |
3.4015 |
0.1429 |
0.2950 |
3 |
3.0156 |
0.1913 |
0.3987 |
3.0598 |
0.1880 |
0.3916 |
4 |
2.4618 |
0.3077 |
0.5572 |
2.9869 |
0.2056 |
0.4129 |
5 |
1.8979 |
0.4541 |
0.7165 |
2.9507 |
0.2298 |
0.4425 |
6 |
1.2075 |
0.6914 |
0.8886 |
3.0106 |
0.2394 |
0.4425 |
7 |
0.6026 |
0.9097 |
0.9810 |
3.0739 |
0.2428 |
0.4413 |
8 |
0.3098 |
0.9821 |
0.9971 |
3.0737 |
0.2491 |
0.4476 |
9 |
Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
đ License
This project is licensed under the Apache - 2.0 license.