<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
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. 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
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
