đ Imene/vit-base-patch16-384-wi4
This model is a fine - tuned version of google/vit-base-patch16-384 on an unknown dataset. It offers evaluation results that provide insights into its performance, such as train loss, accuracy, and validation metrics.
đ Quick Start
This model is a fine - tuned version of google/vit-base-patch16-384 on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1742
- Train Accuracy: 0.9982
- Train Top - 3 - accuracy: 0.9997
- Validation Loss: 1.5010
- Validation Accuracy: 0.5746
- Validation Top - 3 - accuracy: 0.8040
- Epoch: 10
đ Documentation
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
đ§ Technical Details
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': 1800, '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 |
3.7777 |
0.0845 |
0.1855 |
3.3754 |
0.1543 |
0.3014 |
0 |
2.7253 |
0.3277 |
0.5560 |
2.4975 |
0.3452 |
0.5892 |
1 |
2.0079 |
0.5236 |
0.7589 |
2.1228 |
0.4234 |
0.6882 |
2 |
1.5256 |
0.6663 |
0.8549 |
1.9117 |
0.4734 |
0.7445 |
3 |
1.1602 |
0.7712 |
0.9270 |
1.8059 |
0.5162 |
0.7560 |
4 |
0.8509 |
0.8659 |
0.9614 |
1.6534 |
0.5516 |
0.7758 |
5 |
0.5955 |
0.9353 |
0.9836 |
1.6139 |
0.5610 |
0.7935 |
6 |
0.4229 |
0.9687 |
0.9940 |
1.5655 |
0.5631 |
0.7925 |
7 |
0.3045 |
0.9859 |
0.9979 |
1.5290 |
0.5714 |
0.7987 |
8 |
0.2221 |
0.9958 |
0.9990 |
1.5061 |
0.5954 |
0.8008 |
9 |
0.1742 |
0.9982 |
0.9997 |
1.5010 |
0.5746 |
0.8040 |
10 |
Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
đ License
This model is licensed under the Apache 2.0 license.