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philschmid/vit-base-patch16-224-in21k-euroSat
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: 0.0218
- Train Accuracy: 0.9990
- Train Top-3-accuracy: 1.0000
- Validation Loss: 0.0440
- Validation Accuracy: 0.9906
- Validation Top-3-accuracy: 1.0
- Epoch: 5
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 |
|---|---|---|---|---|---|---|
| 0.4692 | 0.9471 | 0.9878 | 0.1455 | 0.9861 | 0.9998 | 1 |
| 0.0998 | 0.9888 | 0.9996 | 0.0821 | 0.9864 | 0.9995 | 2 |
| 0.0517 | 0.9939 | 0.9999 | 0.0617 | 0.9871 | 1.0 | 3 |
| 0.0309 | 0.9971 | 0.9999 | 0.0524 | 0.9878 | 0.9998 | 4 |
| 0.0218 | 0.9990 | 1.0000 | 0.0440 | 0.9906 | 1.0 | 5 |
Framework versions
- Transformers 4.15.0
- TensorFlow 2.7.0
- Datasets 1.17.0
- Tokenizers 0.10.3
