YKXBCi/vit-base-patch16-224-in21k-aidSat
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: 0.4026
- Train Accuracy: 0.9981
- Train Top-3-accuracy: 0.9998
- Validation Loss: 0.4715
- Validation Accuracy: 0.9796
- Validation Top-3-accuracy: 0.9980
- 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': 1325, '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 |
---|---|---|---|---|---|---|
2.3544 | 0.7383 | 0.8687 | 1.5415 | 0.9266 | 0.9857 | 0 |
1.1313 | 0.9522 | 0.9942 | 0.8788 | 0.9613 | 0.9966 | 1 |
0.6741 | 0.9841 | 0.9985 | 0.6268 | 0.9640 | 0.9986 | 2 |
0.4785 | 0.9953 | 0.9995 | 0.5058 | 0.9755 | 0.9980 | 3 |
0.4026 | 0.9981 | 0.9998 | 0.4715 | 0.9796 | 0.9980 | 4 |
Framework versions
- Transformers 4.18.0
- TensorFlow 2.6.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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