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YKXBCi/resnet-50-euroSat
This model is a fine-tuned version of microsoft/resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1408
- Train Accuracy: 0.9540
- Train Top-3-accuracy: 0.9973
- Validation Loss: 0.2008
- Validation Accuracy: 0.9335
- Validation Top-3-accuracy: 0.9965
- 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': 3585, '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 |
|---|---|---|---|---|---|---|
| 0.8487 | 0.6969 | 0.9168 | 0.4793 | 0.8274 | 0.9802 | 0 |
| 0.4363 | 0.8428 | 0.9845 | 0.3823 | 0.8641 | 0.9881 | 1 |
| 0.3123 | 0.8863 | 0.9922 | 0.2945 | 0.8988 | 0.9928 | 2 |
| 0.2153 | 0.9259 | 0.9952 | 0.2316 | 0.9187 | 0.9958 | 3 |
| 0.1408 | 0.9540 | 0.9973 | 0.2008 | 0.9335 | 0.9965 | 4 |
Framework versions
- Transformers 4.18.0
- TensorFlow 2.6.0
- Datasets 2.1.0
- Tokenizers 0.12.1
