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