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Imene/vit-base-patch16-384-wi3
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
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': 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
