YKXBCi/resnet-50-ucSat

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: 0.9091
• Train Accuracy: 0.7125
• Train Top-3-accuracy: 0.9227
• Validation Loss: 1.0869
• Validation Accuracy: 0.6562
• Validation Top-3-accuracy: 0.8924
• 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': 275, '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
2.6504	0.2057	0.3591	2.2693	0.3299	0.5069	0
1.8871	0.4062	0.6494	1.6561	0.4618	0.7083	1
1.4603	0.5278	0.7790	1.4162	0.5417	0.8021	2
1.1499	0.6199	0.8676	1.2030	0.625	0.8646	3
0.9091	0.7125	0.9227	1.0869	0.6562	0.8924	4

Framework versions

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