đ Imene/vit-base-patch16-384-wi3
This model is a fine - tuned version of google/vit-base-patch16-384 on an unknown dataset, offering high - performance results on the evaluation set.
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: 0.2020
- Train Accuracy: 0.9984
- Train Top - 3 - accuracy: 0.9997
- Validation Loss: 1.4297
- Validation Accuracy: 0.6195
- Validation Top - 3 - accuracy: 0.8298
- Epoch: 11
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': 1200, '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 |
3.6575 |
0.0902 |
0.1945 |
3.1772 |
0.2028 |
0.3980 |
0 |
2.5870 |
0.3473 |
0.6048 |
2.3845 |
0.3717 |
0.6208 |
1 |
1.8813 |
0.5553 |
0.7895 |
2.0262 |
0.4431 |
0.7196 |
2 |
1.4326 |
0.6815 |
0.8754 |
1.8856 |
0.4793 |
0.7384 |
3 |
1.0572 |
0.7989 |
0.9439 |
1.6570 |
0.5369 |
0.7960 |
4 |
0.7740 |
0.8838 |
0.9749 |
1.6103 |
0.5557 |
0.7960 |
5 |
0.5593 |
0.9417 |
0.9900 |
1.5303 |
0.5695 |
0.8173 |
6 |
0.4151 |
0.9709 |
0.9975 |
1.4939 |
0.5795 |
0.8185 |
7 |
0.3176 |
0.9884 |
0.9978 |
1.4553 |
0.5832 |
0.8248 |
8 |
0.2582 |
0.9950 |
0.9991 |
1.4500 |
0.6020 |
0.8248 |
9 |
0.2222 |
0.9978 |
0.9994 |
1.4315 |
0.6108 |
0.8310 |
10 |
0.2020 |
0.9984 |
0.9997 |
1.4297 |
0.6195 |
0.8298 |
11 |
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.