YKXBCi/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: 0.0495
• Train Accuracy: 0.9948
• Train Top-3-accuracy: 0.9999
• Validation Loss: 0.0782
• Validation Accuracy: 0.9839
• Validation Top-3-accuracy: 1.0
• Epoch: 2

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
0.4593	0.9478	0.9912	0.1558	0.9809	0.9995	0
0.1008	0.9876	0.9997	0.0855	0.9856	1.0	1
0.0495	0.9948	0.9999	0.0782	0.9839	1.0	2

Framework versions

• Transformers 4.18.0
• TensorFlow 2.6.0
• Datasets 2.1.0
• Tokenizers 0.12.1