đ Imene/vit-base-patch16-224-in21k-iiii
This model is a fine - tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It offers evaluation results such as train loss, accuracy, and validation metrics, providing insights into its performance.
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: 2.8947
- Train Accuracy: 0.5439
- Train Top - 3 - accuracy: 0.7916
- Validation Loss: 3.0482
- Validation Accuracy: 0.3907
- Validation Top - 3 - accuracy: 0.6302
- Epoch: 4
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': 3e - 05, 'decay_steps': 540, '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': 0.01}}, '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 |
3.8068 |
0.0843 |
0.2108 |
3.6116 |
0.1721 |
0.3593 |
0 |
3.4497 |
0.2735 |
0.4840 |
3.3654 |
0.2779 |
0.4953 |
1 |
3.1913 |
0.3991 |
0.6314 |
3.1839 |
0.3512 |
0.5977 |
2 |
3.0017 |
0.4878 |
0.7311 |
3.0867 |
0.3872 |
0.6233 |
3 |
2.8947 |
0.5439 |
0.7916 |
3.0482 |
0.3907 |
0.6302 |
4 |
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.