🚀 BẮT ĐẦU TÌM KIẾM SIÊU THAM SỐ CHO SWIN-UNET
Loading data from dataset_cache/training_data_507bd2ba4ec0d3fe107839cbf73a7a7d.joblib...
Using device: cuda

[1/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.5984
🌟 NEW BEST ACCURACY: 0.5984

[2/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6063
🌟 NEW BEST ACCURACY: 0.6063

[3/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6142
🌟 NEW BEST ACCURACY: 0.6142

[4/48] Training with params: {'embed_dim': 64, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6772
🌟 NEW BEST ACCURACY: 0.6772

[5/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.5827

[6/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.5984

[7/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.5669

[8/48] Training with params: {'embed_dim': 64, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6142

[9/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6142

[10/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.5118

[11/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.5591

[12/48] Training with params: {'embed_dim': 64, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6063

[13/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.7008
🌟 NEW BEST ACCURACY: 0.7008

[14/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6142

[15/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6772

[16/48] Training with params: {'embed_dim': 128, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6063

[17/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.5906

[18/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6457

[19/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.5906

[20/48] Training with params: {'embed_dim': 128, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.5906

[21/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6220

[22/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6457

[23/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.5984

[24/48] Training with params: {'embed_dim': 128, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6063

[25/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.7087
🌟 NEW BEST ACCURACY: 0.7087

[26/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.7323
🌟 NEW BEST ACCURACY: 0.7323

[27/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6457

[28/48] Training with params: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6142

[29/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.5984

[30/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.5906

[31/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6142

[32/48] Training with params: {'embed_dim': 256, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.7008

[33/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6299

[34/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6299

[35/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6378

[36/48] Training with params: {'embed_dim': 256, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6457

[37/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6142

[38/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6457

[39/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6378

[40/48] Training with params: {'embed_dim': 512, 'lr': 0.001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6299

[41/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6378

[42/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.6220

[43/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6142

[44/48] Training with params: {'embed_dim': 512, 'lr': 0.0005, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.7008

[45/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 200}
Test Accuracy: 0.6457

[46/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.01, 'epochs': 500}
Test Accuracy: 0.7323

[47/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 200}
Test Accuracy: 0.6693

[48/48] Training with params: {'embed_dim': 512, 'lr': 0.0001, 'weight_decay': 0.001, 'epochs': 500}
Test Accuracy: 0.6457

✅ Đã lưu mô hình tốt nhất (Acc: 0.7323) vào land_classification_model/model_swin-unet_optimized_95.joblib
Cấu hình tốt nhất: {'embed_dim': 256, 'lr': 0.001, 'weight_decay': 0.01, 'epochs': 500}