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Imene/vit-base-patch16-224-in21k-wi2
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: 2.9892
- Train Accuracy: 0.5568
- Train Top-3-accuracy: 0.8130
- Validation Loss: 3.0923
- Validation Accuracy: 0.4280
- Validation Top-3-accuracy: 0.7034
- Epoch: 4
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': 500, '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 |
|---|---|---|---|---|---|---|
| 3.8488 | 0.0720 | 0.1713 | 3.7116 | 0.1564 | 0.3617 | 0 |
| 3.5246 | 0.2703 | 0.4898 | 3.4122 | 0.3217 | 0.5732 | 1 |
| 3.2493 | 0.4150 | 0.6827 | 3.2232 | 0.3880 | 0.6633 | 2 |
| 3.0840 | 0.5002 | 0.7670 | 3.1275 | 0.4255 | 0.6921 | 3 |
| 2.9892 | 0.5568 | 0.8130 | 3.0923 | 0.4280 | 0.7034 | 4 |
Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
