158 lines
6.3 KiB
Plaintext
158 lines
6.3 KiB
Plaintext
🚀 BẮT ĐẦU TÌM KIẾM SIÊU THAM SỐ CHO SWIN-UNET
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Loading data from dataset_cache/training_data_507bd2ba4ec0d3fe107839cbf73a7a7d.joblib...
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Using device: cuda
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[1/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.5984
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🌟 NEW BEST ACCURACY: 0.5984
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[2/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6063
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🌟 NEW BEST ACCURACY: 0.6063
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[3/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6142
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🌟 NEW BEST ACCURACY: 0.6142
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[4/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6772
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🌟 NEW BEST ACCURACY: 0.6772
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[5/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.5827
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[6/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.5984
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[7/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.5669
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[8/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6142
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[9/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6142
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[10/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.5118
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[11/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.5591
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[12/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6063
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[13/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.7008
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🌟 NEW BEST ACCURACY: 0.7008
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[14/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6142
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[15/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6772
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[16/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6063
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[17/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.5906
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[18/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6457
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[19/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.5906
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[20/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.5906
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[21/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6220
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[22/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6457
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[23/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.5984
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[24/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6063
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[25/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.7087
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🌟 NEW BEST ACCURACY: 0.7087
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[26/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.7323
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🌟 NEW BEST ACCURACY: 0.7323
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[27/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6457
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[28/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6142
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[29/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.5984
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[30/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.5906
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[31/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6142
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[32/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.7008
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[33/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6299
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[34/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6299
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[35/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6378
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[36/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6457
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[37/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6142
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[38/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6457
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[39/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6378
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[40/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6299
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[41/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6378
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[42/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.6220
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[43/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6142
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[44/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.7008
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[45/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
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Test Accuracy: 0.6457
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[46/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
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Test Accuracy: 0.7323
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[47/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
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Test Accuracy: 0.6693
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[48/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
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Test Accuracy: 0.6457
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✅ Đã lưu mô hình tốt nhất (Acc: 0.7323) vào land_classification_model/model_swin-unet_optimized_95.joblib
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Cấu hình tốt nhất: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
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