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Imene/vit-base-patch16-224-in21k-iiii
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: 2.8947
- Train Accuracy: 0.5439
- Train Top-3-accuracy: 0.7916
- Validation Loss: 3.0482
- Validation Accuracy: 0.3907
- Validation Top-3-accuracy: 0.6302
- 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': 540, '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 |
---|---|---|---|---|---|---|
3.8068 | 0.0843 | 0.2108 | 3.6116 | 0.1721 | 0.3593 | 0 |
3.4497 | 0.2735 | 0.4840 | 3.3654 | 0.2779 | 0.4953 | 1 |
3.1913 | 0.3991 | 0.6314 | 3.1839 | 0.3512 | 0.5977 | 2 |
3.0017 | 0.4878 | 0.7311 | 3.0867 | 0.3872 | 0.6233 | 3 |
2.8947 | 0.5439 | 0.7916 | 3.0482 | 0.3907 | 0.6302 | 4 |
Framework versions
- Transformers 4.21.2
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1