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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
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Evaluation results