./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img

📌 S Retain class distribution for seed 10:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 10:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5679
  Class 1: 4605
Forget set:
  Class 0: 132
  Class 1: 132
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
⚠️ Warning: Retain train loader may not be shuffled.
Training Epoch: 1 [256/10284]	Loss: 0.7294	LR: 0.000000
Training Epoch: 1 [512/10284]	Loss: 0.7284	LR: 0.002439
Training Epoch: 1 [768/10284]	Loss: 0.6883	LR: 0.004878
Training Epoch: 1 [1024/10284]	Loss: 0.7468	LR: 0.007317
Training Epoch: 1 [1280/10284]	Loss: 0.7795	LR: 0.009756
Training Epoch: 1 [1536/10284]	Loss: 0.6934	LR: 0.012195
Training Epoch: 1 [1792/10284]	Loss: 0.8369	LR: 0.014634
Training Epoch: 1 [2048/10284]	Loss: 0.7613	LR: 0.017073
Training Epoch: 1 [2304/10284]	Loss: 0.7376	LR: 0.019512
Training Epoch: 1 [2560/10284]	Loss: 0.8904	LR: 0.021951
Training Epoch: 1 [2816/10284]	Loss: 0.8646	LR: 0.024390
Training Epoch: 1 [3072/10284]	Loss: 1.4993	LR: 0.026829
Training Epoch: 1 [3328/10284]	Loss: 0.9147	LR: 0.029268
Training Epoch: 1 [3584/10284]	Loss: 0.8521	LR: 0.031707
Training Epoch: 1 [3840/10284]	Loss: 1.4081	LR: 0.034146
Training Epoch: 1 [4096/10284]	Loss: 0.8670	LR: 0.036585
Training Epoch: 1 [4352/10284]	Loss: 1.0426	LR: 0.039024
Training Epoch: 1 [4608/10284]	Loss: 0.9298	LR: 0.041463
Training Epoch: 1 [4864/10284]	Loss: 0.6754	LR: 0.043902
Training Epoch: 1 [5120/10284]	Loss: 0.9977	LR: 0.046341
Training Epoch: 1 [5376/10284]	Loss: 0.9131	LR: 0.048780
Training Epoch: 1 [5632/10284]	Loss: 0.6716	LR: 0.051220
Training Epoch: 1 [5888/10284]	Loss: 0.7602	LR: 0.053659
Training Epoch: 1 [6144/10284]	Loss: 0.7064	LR: 0.056098
Training Epoch: 1 [6400/10284]	Loss: 0.6948	LR: 0.058537
Training Epoch: 1 [6656/10284]	Loss: 0.7217	LR: 0.060976
Training Epoch: 1 [6912/10284]	Loss: 0.6709	LR: 0.063415
Training Epoch: 1 [7168/10284]	Loss: 0.7416	LR: 0.065854
Training Epoch: 1 [7424/10284]	Loss: 0.7010	LR: 0.068293
Training Epoch: 1 [7680/10284]	Loss: 0.7191	LR: 0.070732
Training Epoch: 1 [7936/10284]	Loss: 0.6933	LR: 0.073171
Training Epoch: 1 [8192/10284]	Loss: 0.7211	LR: 0.075610
Training Epoch: 1 [8448/10284]	Loss: 0.7211	LR: 0.078049
Training Epoch: 1 [8704/10284]	Loss: 0.8182	LR: 0.080488
Training Epoch: 1 [8960/10284]	Loss: 0.6770	LR: 0.082927
Training Epoch: 1 [9216/10284]	Loss: 0.7478	LR: 0.085366
Training Epoch: 1 [9472/10284]	Loss: 0.6799	LR: 0.087805
Training Epoch: 1 [9728/10284]	Loss: 0.7773	LR: 0.090244
Training Epoch: 1 [9984/10284]	Loss: 0.6509	LR: 0.092683
Training Epoch: 1 [10240/10284]	Loss: 0.6783	LR: 0.095122
Training Epoch: 1 [10284/10284]	Loss: 0.6680	LR: 0.097561
Epoch 1 - Average Train Loss: 0.8021, Train Accuracy: 0.5293
Epoch 1 training time consumed: 391.98s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0035, Accuracy: 0.5613, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-1-best.pth
Training Epoch: 2 [256/10284]	Loss: 0.6683	LR: 0.100000
Training Epoch: 2 [512/10284]	Loss: 0.7113	LR: 0.100000
Training Epoch: 2 [768/10284]	Loss: 0.7132	LR: 0.100000
Training Epoch: 2 [1024/10284]	Loss: 0.6960	LR: 0.100000
Training Epoch: 2 [1280/10284]	Loss: 0.6908	LR: 0.100000
Training Epoch: 2 [1536/10284]	Loss: 0.6593	LR: 0.100000
Training Epoch: 2 [1792/10284]	Loss: 0.6874	LR: 0.100000
Training Epoch: 2 [2048/10284]	Loss: 0.6720	LR: 0.100000
Training Epoch: 2 [2304/10284]	Loss: 0.7037	LR: 0.100000
Training Epoch: 2 [2560/10284]	Loss: 0.6976	LR: 0.100000
Training Epoch: 2 [2816/10284]	Loss: 0.7034	LR: 0.100000
Training Epoch: 2 [3072/10284]	Loss: 0.6934	LR: 0.100000
Training Epoch: 2 [3328/10284]	Loss: 0.7255	LR: 0.100000
Training Epoch: 2 [3584/10284]	Loss: 0.6840	LR: 0.100000
Training Epoch: 2 [3840/10284]	Loss: 0.7093	LR: 0.100000
Training Epoch: 2 [4096/10284]	Loss: 0.6752	LR: 0.100000
Training Epoch: 2 [4352/10284]	Loss: 0.7155	LR: 0.100000
Training Epoch: 2 [4608/10284]	Loss: 0.6893	LR: 0.100000
Training Epoch: 2 [4864/10284]	Loss: 0.6648	LR: 0.100000
Training Epoch: 2 [5120/10284]	Loss: 0.6587	LR: 0.100000
Training Epoch: 2 [5376/10284]	Loss: 0.6500	LR: 0.100000
Training Epoch: 2 [5632/10284]	Loss: 0.6872	LR: 0.100000
Training Epoch: 2 [5888/10284]	Loss: 0.6983	LR: 0.100000
Training Epoch: 2 [6144/10284]	Loss: 0.6854	LR: 0.100000
Training Epoch: 2 [6400/10284]	Loss: 0.6679	LR: 0.100000
Training Epoch: 2 [6656/10284]	Loss: 0.6623	LR: 0.100000
Training Epoch: 2 [6912/10284]	Loss: 0.6650	LR: 0.100000
Training Epoch: 2 [7168/10284]	Loss: 0.6823	LR: 0.100000
Training Epoch: 2 [7424/10284]	Loss: 0.7046	LR: 0.100000
Training Epoch: 2 [7680/10284]	Loss: 0.7105	LR: 0.100000
Training Epoch: 2 [7936/10284]	Loss: 0.6586	LR: 0.100000
Training Epoch: 2 [8192/10284]	Loss: 0.7221	LR: 0.100000
Training Epoch: 2 [8448/10284]	Loss: 0.7050	LR: 0.100000
Training Epoch: 2 [8704/10284]	Loss: 0.6751	LR: 0.100000
Training Epoch: 2 [8960/10284]	Loss: 0.6625	LR: 0.100000
Training Epoch: 2 [9216/10284]	Loss: 0.7252	LR: 0.100000
Training Epoch: 2 [9472/10284]	Loss: 0.6798	LR: 0.100000
Training Epoch: 2 [9728/10284]	Loss: 0.7074	LR: 0.100000
Training Epoch: 2 [9984/10284]	Loss: 0.7506	LR: 0.100000
Training Epoch: 2 [10240/10284]	Loss: 0.6821	LR: 0.100000
Training Epoch: 2 [10284/10284]	Loss: 0.8784	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6908, Train Accuracy: 0.5706
Epoch 2 training time consumed: 154.18s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5680, Time consumed:8.31s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-2-best.pth
Training Epoch: 3 [256/10284]	Loss: 0.6724	LR: 0.100000
Training Epoch: 3 [512/10284]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [768/10284]	Loss: 0.6859	LR: 0.100000
Training Epoch: 3 [1024/10284]	Loss: 0.7030	LR: 0.100000
Training Epoch: 3 [1280/10284]	Loss: 0.6906	LR: 0.100000
Training Epoch: 3 [1536/10284]	Loss: 0.6937	LR: 0.100000
Training Epoch: 3 [1792/10284]	Loss: 0.6732	LR: 0.100000
Training Epoch: 3 [2048/10284]	Loss: 0.7108	LR: 0.100000
Training Epoch: 3 [2304/10284]	Loss: 0.6968	LR: 0.100000
Training Epoch: 3 [2560/10284]	Loss: 0.6809	LR: 0.100000
Training Epoch: 3 [2816/10284]	Loss: 0.7047	LR: 0.100000
Training Epoch: 3 [3072/10284]	Loss: 0.6799	LR: 0.100000
Training Epoch: 3 [3328/10284]	Loss: 0.6714	LR: 0.100000
Training Epoch: 3 [3584/10284]	Loss: 0.6702	LR: 0.100000
Training Epoch: 3 [3840/10284]	Loss: 0.6702	LR: 0.100000
Training Epoch: 3 [4096/10284]	Loss: 0.6762	LR: 0.100000
Training Epoch: 3 [4352/10284]	Loss: 0.6833	LR: 0.100000
Training Epoch: 3 [4608/10284]	Loss: 0.6625	LR: 0.100000
Training Epoch: 3 [4864/10284]	Loss: 0.6601	LR: 0.100000
Training Epoch: 3 [5120/10284]	Loss: 0.6633	LR: 0.100000
Training Epoch: 3 [5376/10284]	Loss: 0.6664	LR: 0.100000
Training Epoch: 3 [5632/10284]	Loss: 0.6854	LR: 0.100000
Training Epoch: 3 [5888/10284]	Loss: 0.6701	LR: 0.100000
Training Epoch: 3 [6144/10284]	Loss: 0.6347	LR: 0.100000
Training Epoch: 3 [6400/10284]	Loss: 0.6279	LR: 0.100000
Training Epoch: 3 [6656/10284]	Loss: 0.6485	LR: 0.100000
Training Epoch: 3 [6912/10284]	Loss: 0.6612	LR: 0.100000
Training Epoch: 3 [7168/10284]	Loss: 0.6805	LR: 0.100000
Training Epoch: 3 [7424/10284]	Loss: 0.7024	LR: 0.100000
Training Epoch: 3 [7680/10284]	Loss: 0.6810	LR: 0.100000
Training Epoch: 3 [7936/10284]	Loss: 0.6829	LR: 0.100000
Training Epoch: 3 [8192/10284]	Loss: 0.6606	LR: 0.100000
Training Epoch: 3 [8448/10284]	Loss: 0.7076	LR: 0.100000
Training Epoch: 3 [8704/10284]	Loss: 0.6758	LR: 0.100000
Training Epoch: 3 [8960/10284]	Loss: 0.6649	LR: 0.100000
Training Epoch: 3 [9216/10284]	Loss: 0.6997	LR: 0.100000
Training Epoch: 3 [9472/10284]	Loss: 0.6711	LR: 0.100000
Training Epoch: 3 [9728/10284]	Loss: 0.6693	LR: 0.100000
Training Epoch: 3 [9984/10284]	Loss: 0.6542	LR: 0.100000
Training Epoch: 3 [10240/10284]	Loss: 0.6751	LR: 0.100000
Training Epoch: 3 [10284/10284]	Loss: 0.6950	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6767, Train Accuracy: 0.5661
Epoch 3 training time consumed: 153.59s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5874, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-3-best.pth
Training Epoch: 4 [256/10284]	Loss: 0.6357	LR: 0.100000
Training Epoch: 4 [512/10284]	Loss: 0.6991	LR: 0.100000
Training Epoch: 4 [768/10284]	Loss: 0.6594	LR: 0.100000
Training Epoch: 4 [1024/10284]	Loss: 0.6729	LR: 0.100000
Training Epoch: 4 [1280/10284]	Loss: 0.7213	LR: 0.100000
Training Epoch: 4 [1536/10284]	Loss: 0.6634	LR: 0.100000
Training Epoch: 4 [1792/10284]	Loss: 0.6653	LR: 0.100000
Training Epoch: 4 [2048/10284]	Loss: 0.6818	LR: 0.100000
Training Epoch: 4 [2304/10284]	Loss: 0.6442	LR: 0.100000
Training Epoch: 4 [2560/10284]	Loss: 0.6566	LR: 0.100000
Training Epoch: 4 [2816/10284]	Loss: 0.6830	LR: 0.100000
Training Epoch: 4 [3072/10284]	Loss: 0.6685	LR: 0.100000
Training Epoch: 4 [3328/10284]	Loss: 0.6928	LR: 0.100000
Training Epoch: 4 [3584/10284]	Loss: 0.6775	LR: 0.100000
Training Epoch: 4 [3840/10284]	Loss: 0.6416	LR: 0.100000
Training Epoch: 4 [4096/10284]	Loss: 0.6661	LR: 0.100000
Training Epoch: 4 [4352/10284]	Loss: 0.6305	LR: 0.100000
Training Epoch: 4 [4608/10284]	Loss: 0.6577	LR: 0.100000
Training Epoch: 4 [4864/10284]	Loss: 0.6871	LR: 0.100000
Training Epoch: 4 [5120/10284]	Loss: 0.6463	LR: 0.100000
Training Epoch: 4 [5376/10284]	Loss: 0.6497	LR: 0.100000
Training Epoch: 4 [5632/10284]	Loss: 0.6461	LR: 0.100000
Training Epoch: 4 [5888/10284]	Loss: 0.6792	LR: 0.100000
Training Epoch: 4 [6144/10284]	Loss: 0.6606	LR: 0.100000
Training Epoch: 4 [6400/10284]	Loss: 0.6415	LR: 0.100000
Training Epoch: 4 [6656/10284]	Loss: 0.6628	LR: 0.100000
Training Epoch: 4 [6912/10284]	Loss: 0.6379	LR: 0.100000
Training Epoch: 4 [7168/10284]	Loss: 0.6785	LR: 0.100000
Training Epoch: 4 [7424/10284]	Loss: 0.6665	LR: 0.100000
Training Epoch: 4 [7680/10284]	Loss: 0.6712	LR: 0.100000
Training Epoch: 4 [7936/10284]	Loss: 0.6468	LR: 0.100000
Training Epoch: 4 [8192/10284]	Loss: 0.6843	LR: 0.100000
Training Epoch: 4 [8448/10284]	Loss: 0.6862	LR: 0.100000
Training Epoch: 4 [8704/10284]	Loss: 0.6581	LR: 0.100000
Training Epoch: 4 [8960/10284]	Loss: 0.6608	LR: 0.100000
Training Epoch: 4 [9216/10284]	Loss: 0.6558	LR: 0.100000
Training Epoch: 4 [9472/10284]	Loss: 0.6541	LR: 0.100000
Training Epoch: 4 [9728/10284]	Loss: 0.6664	LR: 0.100000
Training Epoch: 4 [9984/10284]	Loss: 0.6479	LR: 0.100000
Training Epoch: 4 [10240/10284]	Loss: 0.6920	LR: 0.100000
Training Epoch: 4 [10284/10284]	Loss: 0.6457	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6648, Train Accuracy: 0.6031
Epoch 4 training time consumed: 153.59s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5603, Time consumed:8.34s
Training Epoch: 5 [256/10284]	Loss: 0.6500	LR: 0.100000
Training Epoch: 5 [512/10284]	Loss: 0.6669	LR: 0.100000
Training Epoch: 5 [768/10284]	Loss: 0.6661	LR: 0.100000
Training Epoch: 5 [1024/10284]	Loss: 0.6901	LR: 0.100000
Training Epoch: 5 [1280/10284]	Loss: 0.6589	LR: 0.100000
Training Epoch: 5 [1536/10284]	Loss: 0.6562	LR: 0.100000
Training Epoch: 5 [1792/10284]	Loss: 0.6723	LR: 0.100000
Training Epoch: 5 [2048/10284]	Loss: 0.6340	LR: 0.100000
Training Epoch: 5 [2304/10284]	Loss: 0.6400	LR: 0.100000
Training Epoch: 5 [2560/10284]	Loss: 0.6299	LR: 0.100000
Training Epoch: 5 [2816/10284]	Loss: 0.6302	LR: 0.100000
Training Epoch: 5 [3072/10284]	Loss: 0.6079	LR: 0.100000
Training Epoch: 5 [3328/10284]	Loss: 0.6684	LR: 0.100000
Training Epoch: 5 [3584/10284]	Loss: 0.6538	LR: 0.100000
Training Epoch: 5 [3840/10284]	Loss: 0.6591	LR: 0.100000
Training Epoch: 5 [4096/10284]	Loss: 0.6079	LR: 0.100000
Training Epoch: 5 [4352/10284]	Loss: 0.6424	LR: 0.100000
Training Epoch: 5 [4608/10284]	Loss: 0.6382	LR: 0.100000
Training Epoch: 5 [4864/10284]	Loss: 0.6570	LR: 0.100000
Training Epoch: 5 [5120/10284]	Loss: 0.6825	LR: 0.100000
Training Epoch: 5 [5376/10284]	Loss: 0.6530	LR: 0.100000
Training Epoch: 5 [5632/10284]	Loss: 0.6288	LR: 0.100000
Training Epoch: 5 [5888/10284]	Loss: 0.6713	LR: 0.100000
Training Epoch: 5 [6144/10284]	Loss: 0.6413	LR: 0.100000
Training Epoch: 5 [6400/10284]	Loss: 0.6110	LR: 0.100000
Training Epoch: 5 [6656/10284]	Loss: 0.5993	LR: 0.100000
Training Epoch: 5 [6912/10284]	Loss: 0.5871	LR: 0.100000
Training Epoch: 5 [7168/10284]	Loss: 0.6387	LR: 0.100000
Training Epoch: 5 [7424/10284]	Loss: 0.6113	LR: 0.100000
Training Epoch: 5 [7680/10284]	Loss: 0.5791	LR: 0.100000
Training Epoch: 5 [7936/10284]	Loss: 0.5950	LR: 0.100000
Training Epoch: 5 [8192/10284]	Loss: 0.5770	LR: 0.100000
Training Epoch: 5 [8448/10284]	Loss: 0.6836	LR: 0.100000
Training Epoch: 5 [8704/10284]	Loss: 0.6073	LR: 0.100000
Training Epoch: 5 [8960/10284]	Loss: 0.6301	LR: 0.100000
Training Epoch: 5 [9216/10284]	Loss: 0.6272	LR: 0.100000
Training Epoch: 5 [9472/10284]	Loss: 0.6346	LR: 0.100000
Training Epoch: 5 [9728/10284]	Loss: 0.6221	LR: 0.100000
Training Epoch: 5 [9984/10284]	Loss: 0.6137	LR: 0.100000
Training Epoch: 5 [10240/10284]	Loss: 0.6342	LR: 0.100000
Training Epoch: 5 [10284/10284]	Loss: 0.5875	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6362, Train Accuracy: 0.6393
Epoch 5 training time consumed: 153.09s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0033, Accuracy: 0.5608, Time consumed:8.27s
Training Epoch: 6 [256/10284]	Loss: 0.6312	LR: 0.100000
Training Epoch: 6 [512/10284]	Loss: 0.6362	LR: 0.100000
Training Epoch: 6 [768/10284]	Loss: 0.5972	LR: 0.100000
Training Epoch: 6 [1024/10284]	Loss: 0.6032	LR: 0.100000
Training Epoch: 6 [1280/10284]	Loss: 0.6494	LR: 0.100000
Training Epoch: 6 [1536/10284]	Loss: 0.6205	LR: 0.100000
Training Epoch: 6 [1792/10284]	Loss: 0.6130	LR: 0.100000
Training Epoch: 6 [2048/10284]	Loss: 0.6392	LR: 0.100000
Training Epoch: 6 [2304/10284]	Loss: 0.6693	LR: 0.100000
Training Epoch: 6 [2560/10284]	Loss: 0.6039	LR: 0.100000
Training Epoch: 6 [2816/10284]	Loss: 0.5927	LR: 0.100000
Training Epoch: 6 [3072/10284]	Loss: 0.5963	LR: 0.100000
Training Epoch: 6 [3328/10284]	Loss: 0.5687	LR: 0.100000
Training Epoch: 6 [3584/10284]	Loss: 0.5983	LR: 0.100000
Training Epoch: 6 [3840/10284]	Loss: 0.5586	LR: 0.100000
Training Epoch: 6 [4096/10284]	Loss: 0.5724	LR: 0.100000
Training Epoch: 6 [4352/10284]	Loss: 0.5521	LR: 0.100000
Training Epoch: 6 [4608/10284]	Loss: 0.5309	LR: 0.100000
Training Epoch: 6 [4864/10284]	Loss: 0.5864	LR: 0.100000
Training Epoch: 6 [5120/10284]	Loss: 0.5688	LR: 0.100000
Training Epoch: 6 [5376/10284]	Loss: 0.5309	LR: 0.100000
Training Epoch: 6 [5632/10284]	Loss: 0.6022	LR: 0.100000
Training Epoch: 6 [5888/10284]	Loss: 0.5730	LR: 0.100000
Training Epoch: 6 [6144/10284]	Loss: 0.5119	LR: 0.100000
Training Epoch: 6 [6400/10284]	Loss: 0.5842	LR: 0.100000
Training Epoch: 6 [6656/10284]	Loss: 0.5757	LR: 0.100000
Training Epoch: 6 [6912/10284]	Loss: 0.5253	LR: 0.100000
Training Epoch: 6 [7168/10284]	Loss: 0.5826	LR: 0.100000
Training Epoch: 6 [7424/10284]	Loss: 0.5545	LR: 0.100000
Training Epoch: 6 [7680/10284]	Loss: 0.5699	LR: 0.100000
Training Epoch: 6 [7936/10284]	Loss: 0.5535	LR: 0.100000
Training Epoch: 6 [8192/10284]	Loss: 0.5240	LR: 0.100000
Training Epoch: 6 [8448/10284]	Loss: 0.5166	LR: 0.100000
Training Epoch: 6 [8704/10284]	Loss: 0.6120	LR: 0.100000
Training Epoch: 6 [8960/10284]	Loss: 0.5137	LR: 0.100000
Training Epoch: 6 [9216/10284]	Loss: 0.5818	LR: 0.100000
Training Epoch: 6 [9472/10284]	Loss: 0.5509	LR: 0.100000
Training Epoch: 6 [9728/10284]	Loss: 0.5011	LR: 0.100000
Training Epoch: 6 [9984/10284]	Loss: 0.5653	LR: 0.100000
Training Epoch: 6 [10240/10284]	Loss: 0.4860	LR: 0.100000
Training Epoch: 6 [10284/10284]	Loss: 0.6044	LR: 0.100000
Epoch 6 - Average Train Loss: 0.5752, Train Accuracy: 0.7019
Epoch 6 training time consumed: 153.50s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0035, Accuracy: 0.5874, Time consumed:8.29s
Training Epoch: 7 [256/10284]	Loss: 0.5596	LR: 0.100000
Training Epoch: 7 [512/10284]	Loss: 0.5037	LR: 0.100000
Training Epoch: 7 [768/10284]	Loss: 0.5567	LR: 0.100000
Training Epoch: 7 [1024/10284]	Loss: 0.5461	LR: 0.100000
Training Epoch: 7 [1280/10284]	Loss: 0.5475	LR: 0.100000
Training Epoch: 7 [1536/10284]	Loss: 0.4894	LR: 0.100000
Training Epoch: 7 [1792/10284]	Loss: 0.5306	LR: 0.100000
Training Epoch: 7 [2048/10284]	Loss: 0.4543	LR: 0.100000
Training Epoch: 7 [2304/10284]	Loss: 0.4472	LR: 0.100000
Training Epoch: 7 [2560/10284]	Loss: 0.4818	LR: 0.100000
Training Epoch: 7 [2816/10284]	Loss: 0.4605	LR: 0.100000
Training Epoch: 7 [3072/10284]	Loss: 0.4712	LR: 0.100000
Training Epoch: 7 [3328/10284]	Loss: 0.4116	LR: 0.100000
Training Epoch: 7 [3584/10284]	Loss: 0.4528	LR: 0.100000
Training Epoch: 7 [3840/10284]	Loss: 0.5324	LR: 0.100000
Training Epoch: 7 [4096/10284]	Loss: 0.4286	LR: 0.100000
Training Epoch: 7 [4352/10284]	Loss: 0.5037	LR: 0.100000
Training Epoch: 7 [4608/10284]	Loss: 0.4541	LR: 0.100000
Training Epoch: 7 [4864/10284]	Loss: 0.4476	LR: 0.100000
Training Epoch: 7 [5120/10284]	Loss: 0.4330	LR: 0.100000
Training Epoch: 7 [5376/10284]	Loss: 0.4751	LR: 0.100000
Training Epoch: 7 [5632/10284]	Loss: 0.4796	LR: 0.100000
Training Epoch: 7 [5888/10284]	Loss: 0.4145	LR: 0.100000
Training Epoch: 7 [6144/10284]	Loss: 0.4200	LR: 0.100000
Training Epoch: 7 [6400/10284]	Loss: 0.5097	LR: 0.100000
Training Epoch: 7 [6656/10284]	Loss: 0.4011	LR: 0.100000
Training Epoch: 7 [6912/10284]	Loss: 0.4309	LR: 0.100000
Training Epoch: 7 [7168/10284]	Loss: 0.4542	LR: 0.100000
Training Epoch: 7 [7424/10284]	Loss: 0.4665	LR: 0.100000
Training Epoch: 7 [7680/10284]	Loss: 0.4519	LR: 0.100000
Training Epoch: 7 [7936/10284]	Loss: 0.4625	LR: 0.100000
Training Epoch: 7 [8192/10284]	Loss: 0.4069	LR: 0.100000
Training Epoch: 7 [8448/10284]	Loss: 0.4207	LR: 0.100000
Training Epoch: 7 [8704/10284]	Loss: 0.3766	LR: 0.100000
Training Epoch: 7 [8960/10284]	Loss: 0.3952	LR: 0.100000
Training Epoch: 7 [9216/10284]	Loss: 0.4149	LR: 0.100000
Training Epoch: 7 [9472/10284]	Loss: 0.4441	LR: 0.100000
Training Epoch: 7 [9728/10284]	Loss: 0.3874	LR: 0.100000
Training Epoch: 7 [9984/10284]	Loss: 0.4053	LR: 0.100000
Training Epoch: 7 [10240/10284]	Loss: 0.4237	LR: 0.100000
Training Epoch: 7 [10284/10284]	Loss: 0.5748	LR: 0.100000
Epoch 7 - Average Train Loss: 0.4593, Train Accuracy: 0.7845
Epoch 7 training time consumed: 153.67s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0023, Accuracy: 0.7598, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-7-best.pth
Training Epoch: 8 [256/10284]	Loss: 0.4090	LR: 0.100000
Training Epoch: 8 [512/10284]	Loss: 0.3817	LR: 0.100000
Training Epoch: 8 [768/10284]	Loss: 0.4931	LR: 0.100000
Training Epoch: 8 [1024/10284]	Loss: 0.4070	LR: 0.100000
Training Epoch: 8 [1280/10284]	Loss: 0.4375	LR: 0.100000
Training Epoch: 8 [1536/10284]	Loss: 0.5043	LR: 0.100000
Training Epoch: 8 [1792/10284]	Loss: 0.4685	LR: 0.100000
Training Epoch: 8 [2048/10284]	Loss: 0.4712	LR: 0.100000
Training Epoch: 8 [2304/10284]	Loss: 0.3974	LR: 0.100000
Training Epoch: 8 [2560/10284]	Loss: 0.4763	LR: 0.100000
Training Epoch: 8 [2816/10284]	Loss: 0.4587	LR: 0.100000
Training Epoch: 8 [3072/10284]	Loss: 0.4256	LR: 0.100000
Training Epoch: 8 [3328/10284]	Loss: 0.4016	LR: 0.100000
Training Epoch: 8 [3584/10284]	Loss: 0.4096	LR: 0.100000
Training Epoch: 8 [3840/10284]	Loss: 0.3777	LR: 0.100000
Training Epoch: 8 [4096/10284]	Loss: 0.3675	LR: 0.100000
Training Epoch: 8 [4352/10284]	Loss: 0.4169	LR: 0.100000
Training Epoch: 8 [4608/10284]	Loss: 0.3946	LR: 0.100000
Training Epoch: 8 [4864/10284]	Loss: 0.4179	LR: 0.100000
Training Epoch: 8 [5120/10284]	Loss: 0.3483	LR: 0.100000
Training Epoch: 8 [5376/10284]	Loss: 0.4107	LR: 0.100000
Training Epoch: 8 [5632/10284]	Loss: 0.3853	LR: 0.100000
Training Epoch: 8 [5888/10284]	Loss: 0.3957	LR: 0.100000
Training Epoch: 8 [6144/10284]	Loss: 0.4108	LR: 0.100000
Training Epoch: 8 [6400/10284]	Loss: 0.4292	LR: 0.100000
Training Epoch: 8 [6656/10284]	Loss: 0.3633	LR: 0.100000
Training Epoch: 8 [6912/10284]	Loss: 0.4214	LR: 0.100000
Training Epoch: 8 [7168/10284]	Loss: 0.3391	LR: 0.100000
Training Epoch: 8 [7424/10284]	Loss: 0.3733	LR: 0.100000
Training Epoch: 8 [7680/10284]	Loss: 0.3734	LR: 0.100000
Training Epoch: 8 [7936/10284]	Loss: 0.3547	LR: 0.100000
Training Epoch: 8 [8192/10284]	Loss: 0.3661	LR: 0.100000
Training Epoch: 8 [8448/10284]	Loss: 0.3267	LR: 0.100000
Training Epoch: 8 [8704/10284]	Loss: 0.4243	LR: 0.100000
Training Epoch: 8 [8960/10284]	Loss: 0.4112	LR: 0.100000
Training Epoch: 8 [9216/10284]	Loss: 0.3395	LR: 0.100000
Training Epoch: 8 [9472/10284]	Loss: 0.4141	LR: 0.100000
Training Epoch: 8 [9728/10284]	Loss: 0.4421	LR: 0.100000
Training Epoch: 8 [9984/10284]	Loss: 0.3268	LR: 0.100000
Training Epoch: 8 [10240/10284]	Loss: 0.2866	LR: 0.100000
Training Epoch: 8 [10284/10284]	Loss: 0.2956	LR: 0.100000
Epoch 8 - Average Train Loss: 0.4010, Train Accuracy: 0.8170
Epoch 8 training time consumed: 153.27s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0021, Accuracy: 0.7990, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-8-best.pth
Training Epoch: 9 [256/10284]	Loss: 0.4192	LR: 0.100000
Training Epoch: 9 [512/10284]	Loss: 0.5054	LR: 0.100000
Training Epoch: 9 [768/10284]	Loss: 0.3763	LR: 0.100000
Training Epoch: 9 [1024/10284]	Loss: 0.3485	LR: 0.100000
Training Epoch: 9 [1280/10284]	Loss: 0.3402	LR: 0.100000
Training Epoch: 9 [1536/10284]	Loss: 0.3315	LR: 0.100000
Training Epoch: 9 [1792/10284]	Loss: 0.3690	LR: 0.100000
Training Epoch: 9 [2048/10284]	Loss: 0.3863	LR: 0.100000
Training Epoch: 9 [2304/10284]	Loss: 0.4551	LR: 0.100000
Training Epoch: 9 [2560/10284]	Loss: 0.3728	LR: 0.100000
Training Epoch: 9 [2816/10284]	Loss: 0.3524	LR: 0.100000
Training Epoch: 9 [3072/10284]	Loss: 0.3938	LR: 0.100000
Training Epoch: 9 [3328/10284]	Loss: 0.3359	LR: 0.100000
Training Epoch: 9 [3584/10284]	Loss: 0.3006	LR: 0.100000
Training Epoch: 9 [3840/10284]	Loss: 0.3479	LR: 0.100000
Training Epoch: 9 [4096/10284]	Loss: 0.3187	LR: 0.100000
Training Epoch: 9 [4352/10284]	Loss: 0.4399	LR: 0.100000
Training Epoch: 9 [4608/10284]	Loss: 0.3488	LR: 0.100000
Training Epoch: 9 [4864/10284]	Loss: 0.3133	LR: 0.100000
Training Epoch: 9 [5120/10284]	Loss: 0.3867	LR: 0.100000
Training Epoch: 9 [5376/10284]	Loss: 0.2939	LR: 0.100000
Training Epoch: 9 [5632/10284]	Loss: 0.3089	LR: 0.100000
Training Epoch: 9 [5888/10284]	Loss: 0.3298	LR: 0.100000
Training Epoch: 9 [6144/10284]	Loss: 0.3613	LR: 0.100000
Training Epoch: 9 [6400/10284]	Loss: 0.3228	LR: 0.100000
Training Epoch: 9 [6656/10284]	Loss: 0.3008	LR: 0.100000
Training Epoch: 9 [6912/10284]	Loss: 0.3728	LR: 0.100000
Training Epoch: 9 [7168/10284]	Loss: 0.2877	LR: 0.100000
Training Epoch: 9 [7424/10284]	Loss: 0.3370	LR: 0.100000
Training Epoch: 9 [7680/10284]	Loss: 0.2543	LR: 0.100000
Training Epoch: 9 [7936/10284]	Loss: 0.3293	LR: 0.100000
Training Epoch: 9 [8192/10284]	Loss: 0.2830	LR: 0.100000
Training Epoch: 9 [8448/10284]	Loss: 0.2717	LR: 0.100000
Training Epoch: 9 [8704/10284]	Loss: 0.3374	LR: 0.100000
Training Epoch: 9 [8960/10284]	Loss: 0.2366	LR: 0.100000
Training Epoch: 9 [9216/10284]	Loss: 0.3167	LR: 0.100000
Training Epoch: 9 [9472/10284]	Loss: 0.2975	LR: 0.100000
Training Epoch: 9 [9728/10284]	Loss: 0.3041	LR: 0.100000
Training Epoch: 9 [9984/10284]	Loss: 0.2780	LR: 0.100000
Training Epoch: 9 [10240/10284]	Loss: 0.3731	LR: 0.100000
Training Epoch: 9 [10284/10284]	Loss: 0.2553	LR: 0.100000
Epoch 9 - Average Train Loss: 0.3406, Train Accuracy: 0.8503
Epoch 9 training time consumed: 153.32s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0024, Accuracy: 0.7370, Time consumed:8.31s
Training Epoch: 10 [256/10284]	Loss: 0.3524	LR: 0.020000
Training Epoch: 10 [512/10284]	Loss: 0.3501	LR: 0.020000
Training Epoch: 10 [768/10284]	Loss: 0.3496	LR: 0.020000
Training Epoch: 10 [1024/10284]	Loss: 0.2916	LR: 0.020000
Training Epoch: 10 [1280/10284]	Loss: 0.2817	LR: 0.020000
Training Epoch: 10 [1536/10284]	Loss: 0.3062	LR: 0.020000
Training Epoch: 10 [1792/10284]	Loss: 0.2925	LR: 0.020000
Training Epoch: 10 [2048/10284]	Loss: 0.3142	LR: 0.020000
Training Epoch: 10 [2304/10284]	Loss: 0.2631	LR: 0.020000
Training Epoch: 10 [2560/10284]	Loss: 0.2681	LR: 0.020000
Training Epoch: 10 [2816/10284]	Loss: 0.3123	LR: 0.020000
Training Epoch: 10 [3072/10284]	Loss: 0.2742	LR: 0.020000
Training Epoch: 10 [3328/10284]	Loss: 0.2436	LR: 0.020000
Training Epoch: 10 [3584/10284]	Loss: 0.3277	LR: 0.020000
Training Epoch: 10 [3840/10284]	Loss: 0.2344	LR: 0.020000
Training Epoch: 10 [4096/10284]	Loss: 0.3020	LR: 0.020000
Training Epoch: 10 [4352/10284]	Loss: 0.2700	LR: 0.020000
Training Epoch: 10 [4608/10284]	Loss: 0.2539	LR: 0.020000
Training Epoch: 10 [4864/10284]	Loss: 0.2756	LR: 0.020000
Training Epoch: 10 [5120/10284]	Loss: 0.2464	LR: 0.020000
Training Epoch: 10 [5376/10284]	Loss: 0.3224	LR: 0.020000
Training Epoch: 10 [5632/10284]	Loss: 0.2029	LR: 0.020000
Training Epoch: 10 [5888/10284]	Loss: 0.2961	LR: 0.020000
Training Epoch: 10 [6144/10284]	Loss: 0.2518	LR: 0.020000
Training Epoch: 10 [6400/10284]	Loss: 0.2918	LR: 0.020000
Training Epoch: 10 [6656/10284]	Loss: 0.2352	LR: 0.020000
Training Epoch: 10 [6912/10284]	Loss: 0.2642	LR: 0.020000
Training Epoch: 10 [7168/10284]	Loss: 0.2629	LR: 0.020000
Training Epoch: 10 [7424/10284]	Loss: 0.2338	LR: 0.020000
Training Epoch: 10 [7680/10284]	Loss: 0.2290	LR: 0.020000
Training Epoch: 10 [7936/10284]	Loss: 0.2343	LR: 0.020000
Training Epoch: 10 [8192/10284]	Loss: 0.2234	LR: 0.020000
Training Epoch: 10 [8448/10284]	Loss: 0.2698	LR: 0.020000
Training Epoch: 10 [8704/10284]	Loss: 0.2755	LR: 0.020000
Training Epoch: 10 [8960/10284]	Loss: 0.2535	LR: 0.020000
Training Epoch: 10 [9216/10284]	Loss: 0.2383	LR: 0.020000
Training Epoch: 10 [9472/10284]	Loss: 0.2603	LR: 0.020000
Training Epoch: 10 [9728/10284]	Loss: 0.2318	LR: 0.020000
Training Epoch: 10 [9984/10284]	Loss: 0.2472	LR: 0.020000
Training Epoch: 10 [10240/10284]	Loss: 0.3148	LR: 0.020000
Training Epoch: 10 [10284/10284]	Loss: 0.1605	LR: 0.020000
Epoch 10 - Average Train Loss: 0.2732, Train Accuracy: 0.8837
Epoch 10 training time consumed: 153.20s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0010, Accuracy: 0.9007, Time consumed:8.29s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-10-best.pth
Training Epoch: 11 [256/10284]	Loss: 0.2371	LR: 0.020000
Training Epoch: 11 [512/10284]	Loss: 0.2791	LR: 0.020000
Training Epoch: 11 [768/10284]	Loss: 0.1882	LR: 0.020000
Training Epoch: 11 [1024/10284]	Loss: 0.2183	LR: 0.020000
Training Epoch: 11 [1280/10284]	Loss: 0.2652	LR: 0.020000
Training Epoch: 11 [1536/10284]	Loss: 0.3006	LR: 0.020000
Training Epoch: 11 [1792/10284]	Loss: 0.2580	LR: 0.020000
Training Epoch: 11 [2048/10284]	Loss: 0.2623	LR: 0.020000
Training Epoch: 11 [2304/10284]	Loss: 0.2521	LR: 0.020000
Training Epoch: 11 [2560/10284]	Loss: 0.2499	LR: 0.020000
Training Epoch: 11 [2816/10284]	Loss: 0.1975	LR: 0.020000
Training Epoch: 11 [3072/10284]	Loss: 0.2176	LR: 0.020000
Training Epoch: 11 [3328/10284]	Loss: 0.2662	LR: 0.020000
Training Epoch: 11 [3584/10284]	Loss: 0.2347	LR: 0.020000
Training Epoch: 11 [3840/10284]	Loss: 0.2225	LR: 0.020000
Training Epoch: 11 [4096/10284]	Loss: 0.2423	LR: 0.020000
Training Epoch: 11 [4352/10284]	Loss: 0.2399	LR: 0.020000
Training Epoch: 11 [4608/10284]	Loss: 0.2154	LR: 0.020000
Training Epoch: 11 [4864/10284]	Loss: 0.2483	LR: 0.020000
Training Epoch: 11 [5120/10284]	Loss: 0.2098	LR: 0.020000
Training Epoch: 11 [5376/10284]	Loss: 0.2362	LR: 0.020000
Training Epoch: 11 [5632/10284]	Loss: 0.2361	LR: 0.020000
Training Epoch: 11 [5888/10284]	Loss: 0.2225	LR: 0.020000
Training Epoch: 11 [6144/10284]	Loss: 0.2557	LR: 0.020000
Training Epoch: 11 [6400/10284]	Loss: 0.2772	LR: 0.020000
Training Epoch: 11 [6656/10284]	Loss: 0.1888	LR: 0.020000
Training Epoch: 11 [6912/10284]	Loss: 0.2305	LR: 0.020000
Training Epoch: 11 [7168/10284]	Loss: 0.2146	LR: 0.020000
Training Epoch: 11 [7424/10284]	Loss: 0.2024	LR: 0.020000
Training Epoch: 11 [7680/10284]	Loss: 0.2159	LR: 0.020000
Training Epoch: 11 [7936/10284]	Loss: 0.1993	LR: 0.020000
Training Epoch: 11 [8192/10284]	Loss: 0.2344	LR: 0.020000
Training Epoch: 11 [8448/10284]	Loss: 0.1995	LR: 0.020000
Training Epoch: 11 [8704/10284]	Loss: 0.2974	LR: 0.020000
Training Epoch: 11 [8960/10284]	Loss: 0.2288	LR: 0.020000
Training Epoch: 11 [9216/10284]	Loss: 0.2473	LR: 0.020000
Training Epoch: 11 [9472/10284]	Loss: 0.2588	LR: 0.020000
Training Epoch: 11 [9728/10284]	Loss: 0.2657	LR: 0.020000
Training Epoch: 11 [9984/10284]	Loss: 0.1808	LR: 0.020000
Training Epoch: 11 [10240/10284]	Loss: 0.2166	LR: 0.020000
Training Epoch: 11 [10284/10284]	Loss: 0.3470	LR: 0.020000
Epoch 11 - Average Train Loss: 0.2358, Train Accuracy: 0.9008
Epoch 11 training time consumed: 152.75s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0014, Accuracy: 0.8852, Time consumed:8.09s
Training Epoch: 12 [256/10284]	Loss: 0.2479	LR: 0.020000
Training Epoch: 12 [512/10284]	Loss: 0.2003	LR: 0.020000
Training Epoch: 12 [768/10284]	Loss: 0.2310	LR: 0.020000
Training Epoch: 12 [1024/10284]	Loss: 0.1920	LR: 0.020000
Training Epoch: 12 [1280/10284]	Loss: 0.2403	LR: 0.020000
Training Epoch: 12 [1536/10284]	Loss: 0.1984	LR: 0.020000
Training Epoch: 12 [1792/10284]	Loss: 0.1813	LR: 0.020000
Training Epoch: 12 [2048/10284]	Loss: 0.2682	LR: 0.020000
Training Epoch: 12 [2304/10284]	Loss: 0.2219	LR: 0.020000
Training Epoch: 12 [2560/10284]	Loss: 0.2120	LR: 0.020000
Training Epoch: 12 [2816/10284]	Loss: 0.1998	LR: 0.020000
Training Epoch: 12 [3072/10284]	Loss: 0.2660	LR: 0.020000
Training Epoch: 12 [3328/10284]	Loss: 0.2863	LR: 0.020000
Training Epoch: 12 [3584/10284]	Loss: 0.2507	LR: 0.020000
Training Epoch: 12 [3840/10284]	Loss: 0.1763	LR: 0.020000
Training Epoch: 12 [4096/10284]	Loss: 0.2426	LR: 0.020000
Training Epoch: 12 [4352/10284]	Loss: 0.2188	LR: 0.020000
Training Epoch: 12 [4608/10284]	Loss: 0.2302	LR: 0.020000
Training Epoch: 12 [4864/10284]	Loss: 0.2000	LR: 0.020000
Training Epoch: 12 [5120/10284]	Loss: 0.2591	LR: 0.020000
Training Epoch: 12 [5376/10284]	Loss: 0.2466	LR: 0.020000
Training Epoch: 12 [5632/10284]	Loss: 0.2179	LR: 0.020000
Training Epoch: 12 [5888/10284]	Loss: 0.1989	LR: 0.020000
Training Epoch: 12 [6144/10284]	Loss: 0.2074	LR: 0.020000
Training Epoch: 12 [6400/10284]	Loss: 0.2122	LR: 0.020000
Training Epoch: 12 [6656/10284]	Loss: 0.1841	LR: 0.020000
Training Epoch: 12 [6912/10284]	Loss: 0.2185	LR: 0.020000
Training Epoch: 12 [7168/10284]	Loss: 0.2646	LR: 0.020000
Training Epoch: 12 [7424/10284]	Loss: 0.2183	LR: 0.020000
Training Epoch: 12 [7680/10284]	Loss: 0.2594	LR: 0.020000
Training Epoch: 12 [7936/10284]	Loss: 0.1891	LR: 0.020000
Training Epoch: 12 [8192/10284]	Loss: 0.2532	LR: 0.020000
Training Epoch: 12 [8448/10284]	Loss: 0.2063	LR: 0.020000
Training Epoch: 12 [8704/10284]	Loss: 0.2040	LR: 0.020000
Training Epoch: 12 [8960/10284]	Loss: 0.2460	LR: 0.020000
Training Epoch: 12 [9216/10284]	Loss: 0.2211	LR: 0.020000
Training Epoch: 12 [9472/10284]	Loss: 0.2255	LR: 0.020000
Training Epoch: 12 [9728/10284]	Loss: 0.1439	LR: 0.020000
Training Epoch: 12 [9984/10284]	Loss: 0.2439	LR: 0.020000
Training Epoch: 12 [10240/10284]	Loss: 0.2561	LR: 0.020000
Training Epoch: 12 [10284/10284]	Loss: 0.1728	LR: 0.020000
Epoch 12 - Average Train Loss: 0.2233, Train Accuracy: 0.9030
Epoch 12 training time consumed: 153.16s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0009, Accuracy: 0.9133, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-12-best.pth
Training Epoch: 13 [256/10284]	Loss: 0.2223	LR: 0.020000
Training Epoch: 13 [512/10284]	Loss: 0.2721	LR: 0.020000
Training Epoch: 13 [768/10284]	Loss: 0.2275	LR: 0.020000
Training Epoch: 13 [1024/10284]	Loss: 0.2025	LR: 0.020000
Training Epoch: 13 [1280/10284]	Loss: 0.2016	LR: 0.020000
Training Epoch: 13 [1536/10284]	Loss: 0.2014	LR: 0.020000
Training Epoch: 13 [1792/10284]	Loss: 0.1856	LR: 0.020000
Training Epoch: 13 [2048/10284]	Loss: 0.2005	LR: 0.020000
Training Epoch: 13 [2304/10284]	Loss: 0.2199	LR: 0.020000
Training Epoch: 13 [2560/10284]	Loss: 0.2047	LR: 0.020000
Training Epoch: 13 [2816/10284]	Loss: 0.1902	LR: 0.020000
Training Epoch: 13 [3072/10284]	Loss: 0.2384	LR: 0.020000
Training Epoch: 13 [3328/10284]	Loss: 0.2010	LR: 0.020000
Training Epoch: 13 [3584/10284]	Loss: 0.1673	LR: 0.020000
Training Epoch: 13 [3840/10284]	Loss: 0.1543	LR: 0.020000
Training Epoch: 13 [4096/10284]	Loss: 0.2544	LR: 0.020000
Training Epoch: 13 [4352/10284]	Loss: 0.1816	LR: 0.020000
Training Epoch: 13 [4608/10284]	Loss: 0.2050	LR: 0.020000
Training Epoch: 13 [4864/10284]	Loss: 0.2109	LR: 0.020000
Training Epoch: 13 [5120/10284]	Loss: 0.1534	LR: 0.020000
Training Epoch: 13 [5376/10284]	Loss: 0.1846	LR: 0.020000
Training Epoch: 13 [5632/10284]	Loss: 0.2590	LR: 0.020000
Training Epoch: 13 [5888/10284]	Loss: 0.1516	LR: 0.020000
Training Epoch: 13 [6144/10284]	Loss: 0.2918	LR: 0.020000
Training Epoch: 13 [6400/10284]	Loss: 0.1560	LR: 0.020000
Training Epoch: 13 [6656/10284]	Loss: 0.1644	LR: 0.020000
Training Epoch: 13 [6912/10284]	Loss: 0.1923	LR: 0.020000
Training Epoch: 13 [7168/10284]	Loss: 0.2198	LR: 0.020000
Training Epoch: 13 [7424/10284]	Loss: 0.3052	LR: 0.020000
Training Epoch: 13 [7680/10284]	Loss: 0.2354	LR: 0.020000
Training Epoch: 13 [7936/10284]	Loss: 0.1931	LR: 0.020000
Training Epoch: 13 [8192/10284]	Loss: 0.2884	LR: 0.020000
Training Epoch: 13 [8448/10284]	Loss: 0.1707	LR: 0.020000
Training Epoch: 13 [8704/10284]	Loss: 0.2314	LR: 0.020000
Training Epoch: 13 [8960/10284]	Loss: 0.1607	LR: 0.020000
Training Epoch: 13 [9216/10284]	Loss: 0.2286	LR: 0.020000
Training Epoch: 13 [9472/10284]	Loss: 0.2321	LR: 0.020000
Training Epoch: 13 [9728/10284]	Loss: 0.1473	LR: 0.020000
Training Epoch: 13 [9984/10284]	Loss: 0.1792	LR: 0.020000
Training Epoch: 13 [10240/10284]	Loss: 0.1785	LR: 0.020000
Training Epoch: 13 [10284/10284]	Loss: 0.1204	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2062, Train Accuracy: 0.9183
Epoch 13 training time consumed: 152.07s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0009, Accuracy: 0.9201, Time consumed:8.23s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-13-best.pth
Training Epoch: 14 [256/10284]	Loss: 0.1667	LR: 0.020000
Training Epoch: 14 [512/10284]	Loss: 0.1990	LR: 0.020000
Training Epoch: 14 [768/10284]	Loss: 0.1510	LR: 0.020000
Training Epoch: 14 [1024/10284]	Loss: 0.2045	LR: 0.020000
Training Epoch: 14 [1280/10284]	Loss: 0.1943	LR: 0.020000
Training Epoch: 14 [1536/10284]	Loss: 0.2127	LR: 0.020000
Training Epoch: 14 [1792/10284]	Loss: 0.2103	LR: 0.020000
Training Epoch: 14 [2048/10284]	Loss: 0.2086	LR: 0.020000
Training Epoch: 14 [2304/10284]	Loss: 0.1657	LR: 0.020000
Training Epoch: 14 [2560/10284]	Loss: 0.1568	LR: 0.020000
Training Epoch: 14 [2816/10284]	Loss: 0.1967	LR: 0.020000
Training Epoch: 14 [3072/10284]	Loss: 0.1624	LR: 0.020000
Training Epoch: 14 [3328/10284]	Loss: 0.2282	LR: 0.020000
Training Epoch: 14 [3584/10284]	Loss: 0.2238	LR: 0.020000
Training Epoch: 14 [3840/10284]	Loss: 0.1759	LR: 0.020000
Training Epoch: 14 [4096/10284]	Loss: 0.1929	LR: 0.020000
Training Epoch: 14 [4352/10284]	Loss: 0.1577	LR: 0.020000
Training Epoch: 14 [4608/10284]	Loss: 0.1799	LR: 0.020000
Training Epoch: 14 [4864/10284]	Loss: 0.2229	LR: 0.020000
Training Epoch: 14 [5120/10284]	Loss: 0.2328	LR: 0.020000
Training Epoch: 14 [5376/10284]	Loss: 0.2177	LR: 0.020000
Training Epoch: 14 [5632/10284]	Loss: 0.1984	LR: 0.020000
Training Epoch: 14 [5888/10284]	Loss: 0.1919	LR: 0.020000
Training Epoch: 14 [6144/10284]	Loss: 0.1987	LR: 0.020000
Training Epoch: 14 [6400/10284]	Loss: 0.1961	LR: 0.020000
Training Epoch: 14 [6656/10284]	Loss: 0.1590	LR: 0.020000
Training Epoch: 14 [6912/10284]	Loss: 0.2137	LR: 0.020000
Training Epoch: 14 [7168/10284]	Loss: 0.2356	LR: 0.020000
Training Epoch: 14 [7424/10284]	Loss: 0.1803	LR: 0.020000
Training Epoch: 14 [7680/10284]	Loss: 0.1848	LR: 0.020000
Training Epoch: 14 [7936/10284]	Loss: 0.1671	LR: 0.020000
Training Epoch: 14 [8192/10284]	Loss: 0.2551	LR: 0.020000
Training Epoch: 14 [8448/10284]	Loss: 0.1789	LR: 0.020000
Training Epoch: 14 [8704/10284]	Loss: 0.1995	LR: 0.020000
Training Epoch: 14 [8960/10284]	Loss: 0.2138	LR: 0.020000
Training Epoch: 14 [9216/10284]	Loss: 0.2246	LR: 0.020000
Training Epoch: 14 [9472/10284]	Loss: 0.1980	LR: 0.020000
Training Epoch: 14 [9728/10284]	Loss: 0.2132	LR: 0.020000
Training Epoch: 14 [9984/10284]	Loss: 0.2749	LR: 0.020000
Training Epoch: 14 [10240/10284]	Loss: 0.1794	LR: 0.020000
Training Epoch: 14 [10284/10284]	Loss: 0.1179	LR: 0.020000
Epoch 14 - Average Train Loss: 0.1977, Train Accuracy: 0.9168
Epoch 14 training time consumed: 152.94s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0010, Accuracy: 0.9104, Time consumed:8.43s
Training Epoch: 15 [256/10284]	Loss: 0.2238	LR: 0.020000
Training Epoch: 15 [512/10284]	Loss: 0.1863	LR: 0.020000
Training Epoch: 15 [768/10284]	Loss: 0.2357	LR: 0.020000
Training Epoch: 15 [1024/10284]	Loss: 0.2205	LR: 0.020000
Training Epoch: 15 [1280/10284]	Loss: 0.1777	LR: 0.020000
Training Epoch: 15 [1536/10284]	Loss: 0.1729	LR: 0.020000
Training Epoch: 15 [1792/10284]	Loss: 0.1637	LR: 0.020000
Training Epoch: 15 [2048/10284]	Loss: 0.1644	LR: 0.020000
Training Epoch: 15 [2304/10284]	Loss: 0.1599	LR: 0.020000
Training Epoch: 15 [2560/10284]	Loss: 0.1553	LR: 0.020000
Training Epoch: 15 [2816/10284]	Loss: 0.1813	LR: 0.020000
Training Epoch: 15 [3072/10284]	Loss: 0.1616	LR: 0.020000
Training Epoch: 15 [3328/10284]	Loss: 0.1514	LR: 0.020000
Training Epoch: 15 [3584/10284]	Loss: 0.1987	LR: 0.020000
Training Epoch: 15 [3840/10284]	Loss: 0.1496	LR: 0.020000
Training Epoch: 15 [4096/10284]	Loss: 0.1565	LR: 0.020000
Training Epoch: 15 [4352/10284]	Loss: 0.1954	LR: 0.020000
Training Epoch: 15 [4608/10284]	Loss: 0.1713	LR: 0.020000
Training Epoch: 15 [4864/10284]	Loss: 0.2012	LR: 0.020000
Training Epoch: 15 [5120/10284]	Loss: 0.2428	LR: 0.020000
Training Epoch: 15 [5376/10284]	Loss: 0.2557	LR: 0.020000
Training Epoch: 15 [5632/10284]	Loss: 0.1886	LR: 0.020000
Training Epoch: 15 [5888/10284]	Loss: 0.1496	LR: 0.020000
Training Epoch: 15 [6144/10284]	Loss: 0.1603	LR: 0.020000
Training Epoch: 15 [6400/10284]	Loss: 0.2071	LR: 0.020000
Training Epoch: 15 [6656/10284]	Loss: 0.1778	LR: 0.020000
Training Epoch: 15 [6912/10284]	Loss: 0.1726	LR: 0.020000
Training Epoch: 15 [7168/10284]	Loss: 0.1749	LR: 0.020000
Training Epoch: 15 [7424/10284]	Loss: 0.1700	LR: 0.020000
Training Epoch: 15 [7680/10284]	Loss: 0.1982	LR: 0.020000
Training Epoch: 15 [7936/10284]	Loss: 0.1645	LR: 0.020000
Training Epoch: 15 [8192/10284]	Loss: 0.1796	LR: 0.020000
Training Epoch: 15 [8448/10284]	Loss: 0.1599	LR: 0.020000
Training Epoch: 15 [8704/10284]	Loss: 0.1520	LR: 0.020000
Training Epoch: 15 [8960/10284]	Loss: 0.2527	LR: 0.020000
Training Epoch: 15 [9216/10284]	Loss: 0.1511	LR: 0.020000
Training Epoch: 15 [9472/10284]	Loss: 0.2404	LR: 0.020000
Training Epoch: 15 [9728/10284]	Loss: 0.1955	LR: 0.020000
Training Epoch: 15 [9984/10284]	Loss: 0.1397	LR: 0.020000
Training Epoch: 15 [10240/10284]	Loss: 0.2197	LR: 0.020000
Training Epoch: 15 [10284/10284]	Loss: 0.0788	LR: 0.020000
Epoch 15 - Average Train Loss: 0.1840, Train Accuracy: 0.9247
Epoch 15 training time consumed: 152.93s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0007, Accuracy: 0.9283, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-15-best.pth
Training Epoch: 16 [256/10284]	Loss: 0.1773	LR: 0.020000
Training Epoch: 16 [512/10284]	Loss: 0.1612	LR: 0.020000
Training Epoch: 16 [768/10284]	Loss: 0.1492	LR: 0.020000
Training Epoch: 16 [1024/10284]	Loss: 0.2053	LR: 0.020000
Training Epoch: 16 [1280/10284]	Loss: 0.1936	LR: 0.020000
Training Epoch: 16 [1536/10284]	Loss: 0.1442	LR: 0.020000
Training Epoch: 16 [1792/10284]	Loss: 0.1264	LR: 0.020000
Training Epoch: 16 [2048/10284]	Loss: 0.1979	LR: 0.020000
Training Epoch: 16 [2304/10284]	Loss: 0.1810	LR: 0.020000
Training Epoch: 16 [2560/10284]	Loss: 0.2278	LR: 0.020000
Training Epoch: 16 [2816/10284]	Loss: 0.2598	LR: 0.020000
Training Epoch: 16 [3072/10284]	Loss: 0.1949	LR: 0.020000
Training Epoch: 16 [3328/10284]	Loss: 0.1576	LR: 0.020000
Training Epoch: 16 [3584/10284]	Loss: 0.2365	LR: 0.020000
Training Epoch: 16 [3840/10284]	Loss: 0.1881	LR: 0.020000
Training Epoch: 16 [4096/10284]	Loss: 0.2361	LR: 0.020000
Training Epoch: 16 [4352/10284]	Loss: 0.1757	LR: 0.020000
Training Epoch: 16 [4608/10284]	Loss: 0.1484	LR: 0.020000
Training Epoch: 16 [4864/10284]	Loss: 0.1476	LR: 0.020000
Training Epoch: 16 [5120/10284]	Loss: 0.1202	LR: 0.020000
Training Epoch: 16 [5376/10284]	Loss: 0.2168	LR: 0.020000
Training Epoch: 16 [5632/10284]	Loss: 0.1562	LR: 0.020000
Training Epoch: 16 [5888/10284]	Loss: 0.1552	LR: 0.020000
Training Epoch: 16 [6144/10284]	Loss: 0.1920	LR: 0.020000
Training Epoch: 16 [6400/10284]	Loss: 0.1543	LR: 0.020000
Training Epoch: 16 [6656/10284]	Loss: 0.1943	LR: 0.020000
Training Epoch: 16 [6912/10284]	Loss: 0.1580	LR: 0.020000
Training Epoch: 16 [7168/10284]	Loss: 0.1579	LR: 0.020000
Training Epoch: 16 [7424/10284]	Loss: 0.1977	LR: 0.020000
Training Epoch: 16 [7680/10284]	Loss: 0.3025	LR: 0.020000
Training Epoch: 16 [7936/10284]	Loss: 0.1630	LR: 0.020000
Training Epoch: 16 [8192/10284]	Loss: 0.1850	LR: 0.020000
Training Epoch: 16 [8448/10284]	Loss: 0.2229	LR: 0.020000
Training Epoch: 16 [8704/10284]	Loss: 0.2045	LR: 0.020000
Training Epoch: 16 [8960/10284]	Loss: 0.1587	LR: 0.020000
Training Epoch: 16 [9216/10284]	Loss: 0.2326	LR: 0.020000
Training Epoch: 16 [9472/10284]	Loss: 0.1892	LR: 0.020000
Training Epoch: 16 [9728/10284]	Loss: 0.2329	LR: 0.020000
Training Epoch: 16 [9984/10284]	Loss: 0.1626	LR: 0.020000
Training Epoch: 16 [10240/10284]	Loss: 0.2241	LR: 0.020000
Training Epoch: 16 [10284/10284]	Loss: 0.2424	LR: 0.020000
Epoch 16 - Average Train Loss: 0.1875, Train Accuracy: 0.9227
Epoch 16 training time consumed: 152.89s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0008, Accuracy: 0.9249, Time consumed:8.14s
Training Epoch: 17 [256/10284]	Loss: 0.2335	LR: 0.020000
Training Epoch: 17 [512/10284]	Loss: 0.2103	LR: 0.020000
Training Epoch: 17 [768/10284]	Loss: 0.2069	LR: 0.020000
Training Epoch: 17 [1024/10284]	Loss: 0.1630	LR: 0.020000
Training Epoch: 17 [1280/10284]	Loss: 0.1753	LR: 0.020000
Training Epoch: 17 [1536/10284]	Loss: 0.0906	LR: 0.020000
Training Epoch: 17 [1792/10284]	Loss: 0.1673	LR: 0.020000
Training Epoch: 17 [2048/10284]	Loss: 0.2052	LR: 0.020000
Training Epoch: 17 [2304/10284]	Loss: 0.1486	LR: 0.020000
Training Epoch: 17 [2560/10284]	Loss: 0.1308	LR: 0.020000
Training Epoch: 17 [2816/10284]	Loss: 0.1880	LR: 0.020000
Training Epoch: 17 [3072/10284]	Loss: 0.1353	LR: 0.020000
Training Epoch: 17 [3328/10284]	Loss: 0.1306	LR: 0.020000
Training Epoch: 17 [3584/10284]	Loss: 0.2042	LR: 0.020000
Training Epoch: 17 [3840/10284]	Loss: 0.1822	LR: 0.020000
Training Epoch: 17 [4096/10284]	Loss: 0.1715	LR: 0.020000
Training Epoch: 17 [4352/10284]	Loss: 0.1933	LR: 0.020000
Training Epoch: 17 [4608/10284]	Loss: 0.1811	LR: 0.020000
Training Epoch: 17 [4864/10284]	Loss: 0.1653	LR: 0.020000
Training Epoch: 17 [5120/10284]	Loss: 0.1918	LR: 0.020000
Training Epoch: 17 [5376/10284]	Loss: 0.1409	LR: 0.020000
Training Epoch: 17 [5632/10284]	Loss: 0.2154	LR: 0.020000
Training Epoch: 17 [5888/10284]	Loss: 0.1882	LR: 0.020000
Training Epoch: 17 [6144/10284]	Loss: 0.1913	LR: 0.020000
Training Epoch: 17 [6400/10284]	Loss: 0.2303	LR: 0.020000
Training Epoch: 17 [6656/10284]	Loss: 0.2195	LR: 0.020000
Training Epoch: 17 [6912/10284]	Loss: 0.1980	LR: 0.020000
Training Epoch: 17 [7168/10284]	Loss: 0.1626	LR: 0.020000
Training Epoch: 17 [7424/10284]	Loss: 0.1509	LR: 0.020000
Training Epoch: 17 [7680/10284]	Loss: 0.1590	LR: 0.020000
Training Epoch: 17 [7936/10284]	Loss: 0.1238	LR: 0.020000
Training Epoch: 17 [8192/10284]	Loss: 0.2310	LR: 0.020000
Training Epoch: 17 [8448/10284]	Loss: 0.1063	LR: 0.020000
Training Epoch: 17 [8704/10284]	Loss: 0.1023	LR: 0.020000
Training Epoch: 17 [8960/10284]	Loss: 0.1688	LR: 0.020000
Training Epoch: 17 [9216/10284]	Loss: 0.1785	LR: 0.020000
Training Epoch: 17 [9472/10284]	Loss: 0.1447	LR: 0.020000
Training Epoch: 17 [9728/10284]	Loss: 0.1884	LR: 0.020000
Training Epoch: 17 [9984/10284]	Loss: 0.1742	LR: 0.020000
Training Epoch: 17 [10240/10284]	Loss: 0.1524	LR: 0.020000
Training Epoch: 17 [10284/10284]	Loss: 0.1423	LR: 0.020000
Epoch 17 - Average Train Loss: 0.1724, Train Accuracy: 0.9312
Epoch 17 training time consumed: 153.58s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0008, Accuracy: 0.9254, Time consumed:8.15s
Training Epoch: 18 [256/10284]	Loss: 0.1585	LR: 0.020000
Training Epoch: 18 [512/10284]	Loss: 0.1557	LR: 0.020000
Training Epoch: 18 [768/10284]	Loss: 0.1739	LR: 0.020000
Training Epoch: 18 [1024/10284]	Loss: 0.1406	LR: 0.020000
Training Epoch: 18 [1280/10284]	Loss: 0.2095	LR: 0.020000
Training Epoch: 18 [1536/10284]	Loss: 0.2262	LR: 0.020000
Training Epoch: 18 [1792/10284]	Loss: 0.2179	LR: 0.020000
Training Epoch: 18 [2048/10284]	Loss: 0.1791	LR: 0.020000
Training Epoch: 18 [2304/10284]	Loss: 0.1346	LR: 0.020000
Training Epoch: 18 [2560/10284]	Loss: 0.1871	LR: 0.020000
Training Epoch: 18 [2816/10284]	Loss: 0.1832	LR: 0.020000
Training Epoch: 18 [3072/10284]	Loss: 0.1469	LR: 0.020000
Training Epoch: 18 [3328/10284]	Loss: 0.1405	LR: 0.020000
Training Epoch: 18 [3584/10284]	Loss: 0.1597	LR: 0.020000
Training Epoch: 18 [3840/10284]	Loss: 0.1474	LR: 0.020000
Training Epoch: 18 [4096/10284]	Loss: 0.1639	LR: 0.020000
Training Epoch: 18 [4352/10284]	Loss: 0.2000	LR: 0.020000
Training Epoch: 18 [4608/10284]	Loss: 0.1692	LR: 0.020000
Training Epoch: 18 [4864/10284]	Loss: 0.1632	LR: 0.020000
Training Epoch: 18 [5120/10284]	Loss: 0.1595	LR: 0.020000
Training Epoch: 18 [5376/10284]	Loss: 0.1640	LR: 0.020000
Training Epoch: 18 [5632/10284]	Loss: 0.1823	LR: 0.020000
Training Epoch: 18 [5888/10284]	Loss: 0.1933	LR: 0.020000
Training Epoch: 18 [6144/10284]	Loss: 0.2340	LR: 0.020000
Training Epoch: 18 [6400/10284]	Loss: 0.1909	LR: 0.020000
Training Epoch: 18 [6656/10284]	Loss: 0.1806	LR: 0.020000
Training Epoch: 18 [6912/10284]	Loss: 0.1822	LR: 0.020000
Training Epoch: 18 [7168/10284]	Loss: 0.1641	LR: 0.020000
Training Epoch: 18 [7424/10284]	Loss: 0.1442	LR: 0.020000
Training Epoch: 18 [7680/10284]	Loss: 0.1676	LR: 0.020000
Training Epoch: 18 [7936/10284]	Loss: 0.1278	LR: 0.020000
Training Epoch: 18 [8192/10284]	Loss: 0.1356	LR: 0.020000
Training Epoch: 18 [8448/10284]	Loss: 0.2003	LR: 0.020000
Training Epoch: 18 [8704/10284]	Loss: 0.2066	LR: 0.020000
Training Epoch: 18 [8960/10284]	Loss: 0.1601	LR: 0.020000
Training Epoch: 18 [9216/10284]	Loss: 0.1772	LR: 0.020000
Training Epoch: 18 [9472/10284]	Loss: 0.1724	LR: 0.020000
Training Epoch: 18 [9728/10284]	Loss: 0.1656	LR: 0.020000
Training Epoch: 18 [9984/10284]	Loss: 0.1814	LR: 0.020000
Training Epoch: 18 [10240/10284]	Loss: 0.1759	LR: 0.020000
Training Epoch: 18 [10284/10284]	Loss: 0.1078	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1728, Train Accuracy: 0.9309
Epoch 18 training time consumed: 150.92s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:8.19s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-18-best.pth
Training Epoch: 19 [256/10284]	Loss: 0.1413	LR: 0.020000
Training Epoch: 19 [512/10284]	Loss: 0.1232	LR: 0.020000
Training Epoch: 19 [768/10284]	Loss: 0.1187	LR: 0.020000
Training Epoch: 19 [1024/10284]	Loss: 0.1917	LR: 0.020000
Training Epoch: 19 [1280/10284]	Loss: 0.1246	LR: 0.020000
Training Epoch: 19 [1536/10284]	Loss: 0.2113	LR: 0.020000
Training Epoch: 19 [1792/10284]	Loss: 0.1320	LR: 0.020000
Training Epoch: 19 [2048/10284]	Loss: 0.1582	LR: 0.020000
Training Epoch: 19 [2304/10284]	Loss: 0.2136	LR: 0.020000
Training Epoch: 19 [2560/10284]	Loss: 0.1831	LR: 0.020000
Training Epoch: 19 [2816/10284]	Loss: 0.1458	LR: 0.020000
Training Epoch: 19 [3072/10284]	Loss: 0.1721	LR: 0.020000
Training Epoch: 19 [3328/10284]	Loss: 0.1833	LR: 0.020000
Training Epoch: 19 [3584/10284]	Loss: 0.1718	LR: 0.020000
Training Epoch: 19 [3840/10284]	Loss: 0.1488	LR: 0.020000
Training Epoch: 19 [4096/10284]	Loss: 0.1785	LR: 0.020000
Training Epoch: 19 [4352/10284]	Loss: 0.1396	LR: 0.020000
Training Epoch: 19 [4608/10284]	Loss: 0.1653	LR: 0.020000
Training Epoch: 19 [4864/10284]	Loss: 0.1156	LR: 0.020000
Training Epoch: 19 [5120/10284]	Loss: 0.2298	LR: 0.020000
Training Epoch: 19 [5376/10284]	Loss: 0.1647	LR: 0.020000
Training Epoch: 19 [5632/10284]	Loss: 0.1208	LR: 0.020000
Training Epoch: 19 [5888/10284]	Loss: 0.1632	LR: 0.020000
Training Epoch: 19 [6144/10284]	Loss: 0.1701	LR: 0.020000
Training Epoch: 19 [6400/10284]	Loss: 0.1742	LR: 0.020000
Training Epoch: 19 [6656/10284]	Loss: 0.1445	LR: 0.020000
Training Epoch: 19 [6912/10284]	Loss: 0.1476	LR: 0.020000
Training Epoch: 19 [7168/10284]	Loss: 0.1618	LR: 0.020000
Training Epoch: 19 [7424/10284]	Loss: 0.1498	LR: 0.020000
Training Epoch: 19 [7680/10284]	Loss: 0.1507	LR: 0.020000
Training Epoch: 19 [7936/10284]	Loss: 0.1730	LR: 0.020000
Training Epoch: 19 [8192/10284]	Loss: 0.2089	LR: 0.020000
Training Epoch: 19 [8448/10284]	Loss: 0.1597	LR: 0.020000
Training Epoch: 19 [8704/10284]	Loss: 0.1660	LR: 0.020000
Training Epoch: 19 [8960/10284]	Loss: 0.1668	LR: 0.020000
Training Epoch: 19 [9216/10284]	Loss: 0.1682	LR: 0.020000
Training Epoch: 19 [9472/10284]	Loss: 0.1439	LR: 0.020000
Training Epoch: 19 [9728/10284]	Loss: 0.1657	LR: 0.020000
Training Epoch: 19 [9984/10284]	Loss: 0.1795	LR: 0.020000
Training Epoch: 19 [10240/10284]	Loss: 0.1663	LR: 0.020000
Training Epoch: 19 [10284/10284]	Loss: 0.1239	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1622, Train Accuracy: 0.9341
Epoch 19 training time consumed: 152.35s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0009, Accuracy: 0.9220, Time consumed:8.11s
Training Epoch: 20 [256/10284]	Loss: 0.1243	LR: 0.004000
Training Epoch: 20 [512/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 20 [768/10284]	Loss: 0.2015	LR: 0.004000
Training Epoch: 20 [1024/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 20 [1280/10284]	Loss: 0.1583	LR: 0.004000
Training Epoch: 20 [1536/10284]	Loss: 0.1611	LR: 0.004000
Training Epoch: 20 [1792/10284]	Loss: 0.1558	LR: 0.004000
Training Epoch: 20 [2048/10284]	Loss: 0.1912	LR: 0.004000
Training Epoch: 20 [2304/10284]	Loss: 0.1250	LR: 0.004000
Training Epoch: 20 [2560/10284]	Loss: 0.1438	LR: 0.004000
Training Epoch: 20 [2816/10284]	Loss: 0.1567	LR: 0.004000
Training Epoch: 20 [3072/10284]	Loss: 0.1640	LR: 0.004000
Training Epoch: 20 [3328/10284]	Loss: 0.1419	LR: 0.004000
Training Epoch: 20 [3584/10284]	Loss: 0.1588	LR: 0.004000
Training Epoch: 20 [3840/10284]	Loss: 0.1741	LR: 0.004000
Training Epoch: 20 [4096/10284]	Loss: 0.1623	LR: 0.004000
Training Epoch: 20 [4352/10284]	Loss: 0.1350	LR: 0.004000
Training Epoch: 20 [4608/10284]	Loss: 0.1772	LR: 0.004000
Training Epoch: 20 [4864/10284]	Loss: 0.1538	LR: 0.004000
Training Epoch: 20 [5120/10284]	Loss: 0.1865	LR: 0.004000
Training Epoch: 20 [5376/10284]	Loss: 0.1337	LR: 0.004000
Training Epoch: 20 [5632/10284]	Loss: 0.1681	LR: 0.004000
Training Epoch: 20 [5888/10284]	Loss: 0.1636	LR: 0.004000
Training Epoch: 20 [6144/10284]	Loss: 0.1452	LR: 0.004000
Training Epoch: 20 [6400/10284]	Loss: 0.1408	LR: 0.004000
Training Epoch: 20 [6656/10284]	Loss: 0.1486	LR: 0.004000
Training Epoch: 20 [6912/10284]	Loss: 0.1017	LR: 0.004000
Training Epoch: 20 [7168/10284]	Loss: 0.1362	LR: 0.004000
Training Epoch: 20 [7424/10284]	Loss: 0.1132	LR: 0.004000
Training Epoch: 20 [7680/10284]	Loss: 0.1204	LR: 0.004000
Training Epoch: 20 [7936/10284]	Loss: 0.1770	LR: 0.004000
Training Epoch: 20 [8192/10284]	Loss: 0.1719	LR: 0.004000
Training Epoch: 20 [8448/10284]	Loss: 0.1878	LR: 0.004000
Training Epoch: 20 [8704/10284]	Loss: 0.1534	LR: 0.004000
Training Epoch: 20 [8960/10284]	Loss: 0.1486	LR: 0.004000
Training Epoch: 20 [9216/10284]	Loss: 0.2000	LR: 0.004000
Training Epoch: 20 [9472/10284]	Loss: 0.1394	LR: 0.004000
Training Epoch: 20 [9728/10284]	Loss: 0.1432	LR: 0.004000
Training Epoch: 20 [9984/10284]	Loss: 0.1259	LR: 0.004000
Training Epoch: 20 [10240/10284]	Loss: 0.1676	LR: 0.004000
Training Epoch: 20 [10284/10284]	Loss: 0.0514	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1533, Train Accuracy: 0.9374
Epoch 20 training time consumed: 151.25s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:8.32s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-20-best.pth
Training Epoch: 21 [256/10284]	Loss: 0.1309	LR: 0.004000
Training Epoch: 21 [512/10284]	Loss: 0.1687	LR: 0.004000
Training Epoch: 21 [768/10284]	Loss: 0.1162	LR: 0.004000
Training Epoch: 21 [1024/10284]	Loss: 0.2062	LR: 0.004000
Training Epoch: 21 [1280/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 21 [1536/10284]	Loss: 0.1373	LR: 0.004000
Training Epoch: 21 [1792/10284]	Loss: 0.1362	LR: 0.004000
Training Epoch: 21 [2048/10284]	Loss: 0.1210	LR: 0.004000
Training Epoch: 21 [2304/10284]	Loss: 0.1126	LR: 0.004000
Training Epoch: 21 [2560/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 21 [2816/10284]	Loss: 0.1408	LR: 0.004000
Training Epoch: 21 [3072/10284]	Loss: 0.1239	LR: 0.004000
Training Epoch: 21 [3328/10284]	Loss: 0.1065	LR: 0.004000
Training Epoch: 21 [3584/10284]	Loss: 0.1171	LR: 0.004000
Training Epoch: 21 [3840/10284]	Loss: 0.1501	LR: 0.004000
Training Epoch: 21 [4096/10284]	Loss: 0.1488	LR: 0.004000
Training Epoch: 21 [4352/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 21 [4608/10284]	Loss: 0.1390	LR: 0.004000
Training Epoch: 21 [4864/10284]	Loss: 0.1301	LR: 0.004000
Training Epoch: 21 [5120/10284]	Loss: 0.1668	LR: 0.004000
Training Epoch: 21 [5376/10284]	Loss: 0.1709	LR: 0.004000
Training Epoch: 21 [5632/10284]	Loss: 0.1210	LR: 0.004000
Training Epoch: 21 [5888/10284]	Loss: 0.1401	LR: 0.004000
Training Epoch: 21 [6144/10284]	Loss: 0.1319	LR: 0.004000
Training Epoch: 21 [6400/10284]	Loss: 0.1255	LR: 0.004000
Training Epoch: 21 [6656/10284]	Loss: 0.1132	LR: 0.004000
Training Epoch: 21 [6912/10284]	Loss: 0.1892	LR: 0.004000
Training Epoch: 21 [7168/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 21 [7424/10284]	Loss: 0.1033	LR: 0.004000
Training Epoch: 21 [7680/10284]	Loss: 0.1715	LR: 0.004000
Training Epoch: 21 [7936/10284]	Loss: 0.1766	LR: 0.004000
Training Epoch: 21 [8192/10284]	Loss: 0.1026	LR: 0.004000
Training Epoch: 21 [8448/10284]	Loss: 0.1150	LR: 0.004000
Training Epoch: 21 [8704/10284]	Loss: 0.2087	LR: 0.004000
Training Epoch: 21 [8960/10284]	Loss: 0.1640	LR: 0.004000
Training Epoch: 21 [9216/10284]	Loss: 0.1249	LR: 0.004000
Training Epoch: 21 [9472/10284]	Loss: 0.1569	LR: 0.004000
Training Epoch: 21 [9728/10284]	Loss: 0.1049	LR: 0.004000
Training Epoch: 21 [9984/10284]	Loss: 0.1722	LR: 0.004000
Training Epoch: 21 [10240/10284]	Loss: 0.2180	LR: 0.004000
Training Epoch: 21 [10284/10284]	Loss: 0.1556	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1439, Train Accuracy: 0.9423
Epoch 21 training time consumed: 151.39s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0008, Accuracy: 0.9278, Time consumed:8.21s
Training Epoch: 22 [256/10284]	Loss: 0.1680	LR: 0.004000
Training Epoch: 22 [512/10284]	Loss: 0.1318	LR: 0.004000
Training Epoch: 22 [768/10284]	Loss: 0.1115	LR: 0.004000
Training Epoch: 22 [1024/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 22 [1280/10284]	Loss: 0.1784	LR: 0.004000
Training Epoch: 22 [1536/10284]	Loss: 0.1509	LR: 0.004000
Training Epoch: 22 [1792/10284]	Loss: 0.1504	LR: 0.004000
Training Epoch: 22 [2048/10284]	Loss: 0.1381	LR: 0.004000
Training Epoch: 22 [2304/10284]	Loss: 0.1236	LR: 0.004000
Training Epoch: 22 [2560/10284]	Loss: 0.1077	LR: 0.004000
Training Epoch: 22 [2816/10284]	Loss: 0.1790	LR: 0.004000
Training Epoch: 22 [3072/10284]	Loss: 0.1425	LR: 0.004000
Training Epoch: 22 [3328/10284]	Loss: 0.1528	LR: 0.004000
Training Epoch: 22 [3584/10284]	Loss: 0.1383	LR: 0.004000
Training Epoch: 22 [3840/10284]	Loss: 0.1112	LR: 0.004000
Training Epoch: 22 [4096/10284]	Loss: 0.1536	LR: 0.004000
Training Epoch: 22 [4352/10284]	Loss: 0.1118	LR: 0.004000
Training Epoch: 22 [4608/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 22 [4864/10284]	Loss: 0.1280	LR: 0.004000
Training Epoch: 22 [5120/10284]	Loss: 0.1626	LR: 0.004000
Training Epoch: 22 [5376/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 22 [5632/10284]	Loss: 0.1354	LR: 0.004000
Training Epoch: 22 [5888/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 22 [6144/10284]	Loss: 0.1639	LR: 0.004000
Training Epoch: 22 [6400/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 22 [6656/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 22 [6912/10284]	Loss: 0.1679	LR: 0.004000
Training Epoch: 22 [7168/10284]	Loss: 0.1742	LR: 0.004000
Training Epoch: 22 [7424/10284]	Loss: 0.1857	LR: 0.004000
Training Epoch: 22 [7680/10284]	Loss: 0.1335	LR: 0.004000
Training Epoch: 22 [7936/10284]	Loss: 0.1059	LR: 0.004000
Training Epoch: 22 [8192/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 22 [8448/10284]	Loss: 0.1609	LR: 0.004000
Training Epoch: 22 [8704/10284]	Loss: 0.1526	LR: 0.004000
Training Epoch: 22 [8960/10284]	Loss: 0.1962	LR: 0.004000
Training Epoch: 22 [9216/10284]	Loss: 0.1613	LR: 0.004000
Training Epoch: 22 [9472/10284]	Loss: 0.1813	LR: 0.004000
Training Epoch: 22 [9728/10284]	Loss: 0.1649	LR: 0.004000
Training Epoch: 22 [9984/10284]	Loss: 0.1272	LR: 0.004000
Training Epoch: 22 [10240/10284]	Loss: 0.1184	LR: 0.004000
Training Epoch: 22 [10284/10284]	Loss: 0.2515	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1456, Train Accuracy: 0.9413
Epoch 22 training time consumed: 152.63s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.22s
Training Epoch: 23 [256/10284]	Loss: 0.1100	LR: 0.004000
Training Epoch: 23 [512/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 23 [768/10284]	Loss: 0.1456	LR: 0.004000
Training Epoch: 23 [1024/10284]	Loss: 0.1121	LR: 0.004000
Training Epoch: 23 [1280/10284]	Loss: 0.1558	LR: 0.004000
Training Epoch: 23 [1536/10284]	Loss: 0.1211	LR: 0.004000
Training Epoch: 23 [1792/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 23 [2048/10284]	Loss: 0.1018	LR: 0.004000
Training Epoch: 23 [2304/10284]	Loss: 0.1531	LR: 0.004000
Training Epoch: 23 [2560/10284]	Loss: 0.1521	LR: 0.004000
Training Epoch: 23 [2816/10284]	Loss: 0.1287	LR: 0.004000
Training Epoch: 23 [3072/10284]	Loss: 0.1270	LR: 0.004000
Training Epoch: 23 [3328/10284]	Loss: 0.1243	LR: 0.004000
Training Epoch: 23 [3584/10284]	Loss: 0.1686	LR: 0.004000
Training Epoch: 23 [3840/10284]	Loss: 0.1426	LR: 0.004000
Training Epoch: 23 [4096/10284]	Loss: 0.1616	LR: 0.004000
Training Epoch: 23 [4352/10284]	Loss: 0.1397	LR: 0.004000
Training Epoch: 23 [4608/10284]	Loss: 0.1312	LR: 0.004000
Training Epoch: 23 [4864/10284]	Loss: 0.1514	LR: 0.004000
Training Epoch: 23 [5120/10284]	Loss: 0.1277	LR: 0.004000
Training Epoch: 23 [5376/10284]	Loss: 0.1375	LR: 0.004000
Training Epoch: 23 [5632/10284]	Loss: 0.1461	LR: 0.004000
Training Epoch: 23 [5888/10284]	Loss: 0.1378	LR: 0.004000
Training Epoch: 23 [6144/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 23 [6400/10284]	Loss: 0.1281	LR: 0.004000
Training Epoch: 23 [6656/10284]	Loss: 0.1556	LR: 0.004000
Training Epoch: 23 [6912/10284]	Loss: 0.1340	LR: 0.004000
Training Epoch: 23 [7168/10284]	Loss: 0.1594	LR: 0.004000
Training Epoch: 23 [7424/10284]	Loss: 0.0984	LR: 0.004000
Training Epoch: 23 [7680/10284]	Loss: 0.1619	LR: 0.004000
Training Epoch: 23 [7936/10284]	Loss: 0.1630	LR: 0.004000
Training Epoch: 23 [8192/10284]	Loss: 0.1312	LR: 0.004000
Training Epoch: 23 [8448/10284]	Loss: 0.0983	LR: 0.004000
Training Epoch: 23 [8704/10284]	Loss: 0.1228	LR: 0.004000
Training Epoch: 23 [8960/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 23 [9216/10284]	Loss: 0.1841	LR: 0.004000
Training Epoch: 23 [9472/10284]	Loss: 0.0967	LR: 0.004000
Training Epoch: 23 [9728/10284]	Loss: 0.1181	LR: 0.004000
Training Epoch: 23 [9984/10284]	Loss: 0.1283	LR: 0.004000
Training Epoch: 23 [10240/10284]	Loss: 0.1440	LR: 0.004000
Training Epoch: 23 [10284/10284]	Loss: 0.1851	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1369, Train Accuracy: 0.9433
Epoch 23 training time consumed: 153.27s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.05s
Training Epoch: 24 [256/10284]	Loss: 0.1633	LR: 0.004000
Training Epoch: 24 [512/10284]	Loss: 0.1217	LR: 0.004000
Training Epoch: 24 [768/10284]	Loss: 0.1328	LR: 0.004000
Training Epoch: 24 [1024/10284]	Loss: 0.1381	LR: 0.004000
Training Epoch: 24 [1280/10284]	Loss: 0.1298	LR: 0.004000
Training Epoch: 24 [1536/10284]	Loss: 0.1648	LR: 0.004000
Training Epoch: 24 [1792/10284]	Loss: 0.1360	LR: 0.004000
Training Epoch: 24 [2048/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 24 [2304/10284]	Loss: 0.1685	LR: 0.004000
Training Epoch: 24 [2560/10284]	Loss: 0.1204	LR: 0.004000
Training Epoch: 24 [2816/10284]	Loss: 0.1042	LR: 0.004000
Training Epoch: 24 [3072/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 24 [3328/10284]	Loss: 0.1221	LR: 0.004000
Training Epoch: 24 [3584/10284]	Loss: 0.1169	LR: 0.004000
Training Epoch: 24 [3840/10284]	Loss: 0.0809	LR: 0.004000
Training Epoch: 24 [4096/10284]	Loss: 0.1610	LR: 0.004000
Training Epoch: 24 [4352/10284]	Loss: 0.1547	LR: 0.004000
Training Epoch: 24 [4608/10284]	Loss: 0.1630	LR: 0.004000
Training Epoch: 24 [4864/10284]	Loss: 0.1217	LR: 0.004000
Training Epoch: 24 [5120/10284]	Loss: 0.0967	LR: 0.004000
Training Epoch: 24 [5376/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 24 [5632/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 24 [5888/10284]	Loss: 0.1257	LR: 0.004000
Training Epoch: 24 [6144/10284]	Loss: 0.1605	LR: 0.004000
Training Epoch: 24 [6400/10284]	Loss: 0.1858	LR: 0.004000
Training Epoch: 24 [6656/10284]	Loss: 0.1280	LR: 0.004000
Training Epoch: 24 [6912/10284]	Loss: 0.1273	LR: 0.004000
Training Epoch: 24 [7168/10284]	Loss: 0.2075	LR: 0.004000
Training Epoch: 24 [7424/10284]	Loss: 0.1593	LR: 0.004000
Training Epoch: 24 [7680/10284]	Loss: 0.1253	LR: 0.004000
Training Epoch: 24 [7936/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 24 [8192/10284]	Loss: 0.1348	LR: 0.004000
Training Epoch: 24 [8448/10284]	Loss: 0.1334	LR: 0.004000
Training Epoch: 24 [8704/10284]	Loss: 0.1384	LR: 0.004000
Training Epoch: 24 [8960/10284]	Loss: 0.1517	LR: 0.004000
Training Epoch: 24 [9216/10284]	Loss: 0.1977	LR: 0.004000
Training Epoch: 24 [9472/10284]	Loss: 0.1309	LR: 0.004000
Training Epoch: 24 [9728/10284]	Loss: 0.1144	LR: 0.004000
Training Epoch: 24 [9984/10284]	Loss: 0.1450	LR: 0.004000
Training Epoch: 24 [10240/10284]	Loss: 0.1047	LR: 0.004000
Training Epoch: 24 [10284/10284]	Loss: 0.2133	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1384, Train Accuracy: 0.9451
Epoch 24 training time consumed: 153.44s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9337, Time consumed:8.21s
Training Epoch: 25 [256/10284]	Loss: 0.1128	LR: 0.004000
Training Epoch: 25 [512/10284]	Loss: 0.1525	LR: 0.004000
Training Epoch: 25 [768/10284]	Loss: 0.1645	LR: 0.004000
Training Epoch: 25 [1024/10284]	Loss: 0.1422	LR: 0.004000
Training Epoch: 25 [1280/10284]	Loss: 0.0722	LR: 0.004000
Training Epoch: 25 [1536/10284]	Loss: 0.1062	LR: 0.004000
Training Epoch: 25 [1792/10284]	Loss: 0.1407	LR: 0.004000
Training Epoch: 25 [2048/10284]	Loss: 0.1467	LR: 0.004000
Training Epoch: 25 [2304/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 25 [2560/10284]	Loss: 0.1099	LR: 0.004000
Training Epoch: 25 [2816/10284]	Loss: 0.1046	LR: 0.004000
Training Epoch: 25 [3072/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 25 [3328/10284]	Loss: 0.1455	LR: 0.004000
Training Epoch: 25 [3584/10284]	Loss: 0.1235	LR: 0.004000
Training Epoch: 25 [3840/10284]	Loss: 0.1141	LR: 0.004000
Training Epoch: 25 [4096/10284]	Loss: 0.1817	LR: 0.004000
Training Epoch: 25 [4352/10284]	Loss: 0.1716	LR: 0.004000
Training Epoch: 25 [4608/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 25 [4864/10284]	Loss: 0.1404	LR: 0.004000
Training Epoch: 25 [5120/10284]	Loss: 0.1207	LR: 0.004000
Training Epoch: 25 [5376/10284]	Loss: 0.1062	LR: 0.004000
Training Epoch: 25 [5632/10284]	Loss: 0.1419	LR: 0.004000
Training Epoch: 25 [5888/10284]	Loss: 0.1450	LR: 0.004000
Training Epoch: 25 [6144/10284]	Loss: 0.1297	LR: 0.004000
Training Epoch: 25 [6400/10284]	Loss: 0.1614	LR: 0.004000
Training Epoch: 25 [6656/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 25 [6912/10284]	Loss: 0.1332	LR: 0.004000
Training Epoch: 25 [7168/10284]	Loss: 0.1041	LR: 0.004000
Training Epoch: 25 [7424/10284]	Loss: 0.1359	LR: 0.004000
Training Epoch: 25 [7680/10284]	Loss: 0.1714	LR: 0.004000
Training Epoch: 25 [7936/10284]	Loss: 0.1704	LR: 0.004000
Training Epoch: 25 [8192/10284]	Loss: 0.1160	LR: 0.004000
Training Epoch: 25 [8448/10284]	Loss: 0.1647	LR: 0.004000
Training Epoch: 25 [8704/10284]	Loss: 0.1167	LR: 0.004000
Training Epoch: 25 [8960/10284]	Loss: 0.1017	LR: 0.004000
Training Epoch: 25 [9216/10284]	Loss: 0.1024	LR: 0.004000
Training Epoch: 25 [9472/10284]	Loss: 0.1088	LR: 0.004000
Training Epoch: 25 [9728/10284]	Loss: 0.1412	LR: 0.004000
Training Epoch: 25 [9984/10284]	Loss: 0.1696	LR: 0.004000
Training Epoch: 25 [10240/10284]	Loss: 0.1585	LR: 0.004000
Training Epoch: 25 [10284/10284]	Loss: 0.0706	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1342, Train Accuracy: 0.9450
Epoch 25 training time consumed: 153.36s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9390, Time consumed:8.26s
Training Epoch: 26 [256/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 26 [512/10284]	Loss: 0.0943	LR: 0.004000
Training Epoch: 26 [768/10284]	Loss: 0.1295	LR: 0.004000
Training Epoch: 26 [1024/10284]	Loss: 0.1185	LR: 0.004000
Training Epoch: 26 [1280/10284]	Loss: 0.1490	LR: 0.004000
Training Epoch: 26 [1536/10284]	Loss: 0.1414	LR: 0.004000
Training Epoch: 26 [1792/10284]	Loss: 0.1022	LR: 0.004000
Training Epoch: 26 [2048/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 26 [2304/10284]	Loss: 0.1026	LR: 0.004000
Training Epoch: 26 [2560/10284]	Loss: 0.1279	LR: 0.004000
Training Epoch: 26 [2816/10284]	Loss: 0.2033	LR: 0.004000
Training Epoch: 26 [3072/10284]	Loss: 0.1405	LR: 0.004000
Training Epoch: 26 [3328/10284]	Loss: 0.2129	LR: 0.004000
Training Epoch: 26 [3584/10284]	Loss: 0.1250	LR: 0.004000
Training Epoch: 26 [3840/10284]	Loss: 0.1141	LR: 0.004000
Training Epoch: 26 [4096/10284]	Loss: 0.1112	LR: 0.004000
Training Epoch: 26 [4352/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 26 [4608/10284]	Loss: 0.1565	LR: 0.004000
Training Epoch: 26 [4864/10284]	Loss: 0.1309	LR: 0.004000
Training Epoch: 26 [5120/10284]	Loss: 0.1827	LR: 0.004000
Training Epoch: 26 [5376/10284]	Loss: 0.1652	LR: 0.004000
Training Epoch: 26 [5632/10284]	Loss: 0.1139	LR: 0.004000
Training Epoch: 26 [5888/10284]	Loss: 0.1616	LR: 0.004000
Training Epoch: 26 [6144/10284]	Loss: 0.1377	LR: 0.004000
Training Epoch: 26 [6400/10284]	Loss: 0.1354	LR: 0.004000
Training Epoch: 26 [6656/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 26 [6912/10284]	Loss: 0.1099	LR: 0.004000
Training Epoch: 26 [7168/10284]	Loss: 0.1890	LR: 0.004000
Training Epoch: 26 [7424/10284]	Loss: 0.1285	LR: 0.004000
Training Epoch: 26 [7680/10284]	Loss: 0.0946	LR: 0.004000
Training Epoch: 26 [7936/10284]	Loss: 0.1186	LR: 0.004000
Training Epoch: 26 [8192/10284]	Loss: 0.1283	LR: 0.004000
Training Epoch: 26 [8448/10284]	Loss: 0.1639	LR: 0.004000
Training Epoch: 26 [8704/10284]	Loss: 0.1856	LR: 0.004000
Training Epoch: 26 [8960/10284]	Loss: 0.1218	LR: 0.004000
Training Epoch: 26 [9216/10284]	Loss: 0.0982	LR: 0.004000
Training Epoch: 26 [9472/10284]	Loss: 0.0880	LR: 0.004000
Training Epoch: 26 [9728/10284]	Loss: 0.1389	LR: 0.004000
Training Epoch: 26 [9984/10284]	Loss: 0.1359	LR: 0.004000
Training Epoch: 26 [10240/10284]	Loss: 0.1211	LR: 0.004000
Training Epoch: 26 [10284/10284]	Loss: 0.0903	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1355, Train Accuracy: 0.9448
Epoch 26 training time consumed: 153.02s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.34s
Training Epoch: 27 [256/10284]	Loss: 0.0995	LR: 0.004000
Training Epoch: 27 [512/10284]	Loss: 0.1357	LR: 0.004000
Training Epoch: 27 [768/10284]	Loss: 0.1635	LR: 0.004000
Training Epoch: 27 [1024/10284]	Loss: 0.0986	LR: 0.004000
Training Epoch: 27 [1280/10284]	Loss: 0.1457	LR: 0.004000
Training Epoch: 27 [1536/10284]	Loss: 0.1019	LR: 0.004000
Training Epoch: 27 [1792/10284]	Loss: 0.1355	LR: 0.004000
Training Epoch: 27 [2048/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 27 [2304/10284]	Loss: 0.1530	LR: 0.004000
Training Epoch: 27 [2560/10284]	Loss: 0.1848	LR: 0.004000
Training Epoch: 27 [2816/10284]	Loss: 0.0881	LR: 0.004000
Training Epoch: 27 [3072/10284]	Loss: 0.1900	LR: 0.004000
Training Epoch: 27 [3328/10284]	Loss: 0.1222	LR: 0.004000
Training Epoch: 27 [3584/10284]	Loss: 0.1188	LR: 0.004000
Training Epoch: 27 [3840/10284]	Loss: 0.1173	LR: 0.004000
Training Epoch: 27 [4096/10284]	Loss: 0.1701	LR: 0.004000
Training Epoch: 27 [4352/10284]	Loss: 0.1297	LR: 0.004000
Training Epoch: 27 [4608/10284]	Loss: 0.1703	LR: 0.004000
Training Epoch: 27 [4864/10284]	Loss: 0.1545	LR: 0.004000
Training Epoch: 27 [5120/10284]	Loss: 0.1138	LR: 0.004000
Training Epoch: 27 [5376/10284]	Loss: 0.1147	LR: 0.004000
Training Epoch: 27 [5632/10284]	Loss: 0.1198	LR: 0.004000
Training Epoch: 27 [5888/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 27 [6144/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 27 [6400/10284]	Loss: 0.1317	LR: 0.004000
Training Epoch: 27 [6656/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 27 [6912/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 27 [7168/10284]	Loss: 0.0948	LR: 0.004000
Training Epoch: 27 [7424/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 27 [7680/10284]	Loss: 0.1286	LR: 0.004000
Training Epoch: 27 [7936/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 27 [8192/10284]	Loss: 0.1352	LR: 0.004000
Training Epoch: 27 [8448/10284]	Loss: 0.1605	LR: 0.004000
Training Epoch: 27 [8704/10284]	Loss: 0.1123	LR: 0.004000
Training Epoch: 27 [8960/10284]	Loss: 0.0869	LR: 0.004000
Training Epoch: 27 [9216/10284]	Loss: 0.1527	LR: 0.004000
Training Epoch: 27 [9472/10284]	Loss: 0.1030	LR: 0.004000
Training Epoch: 27 [9728/10284]	Loss: 0.1396	LR: 0.004000
Training Epoch: 27 [9984/10284]	Loss: 0.1091	LR: 0.004000
Training Epoch: 27 [10240/10284]	Loss: 0.1563	LR: 0.004000
Training Epoch: 27 [10284/10284]	Loss: 0.0509	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1315, Train Accuracy: 0.9457
Epoch 27 training time consumed: 153.06s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0008, Accuracy: 0.9288, Time consumed:8.06s
Training Epoch: 28 [256/10284]	Loss: 0.1912	LR: 0.004000
Training Epoch: 28 [512/10284]	Loss: 0.0767	LR: 0.004000
Training Epoch: 28 [768/10284]	Loss: 0.1194	LR: 0.004000
Training Epoch: 28 [1024/10284]	Loss: 0.1421	LR: 0.004000
Training Epoch: 28 [1280/10284]	Loss: 0.0944	LR: 0.004000
Training Epoch: 28 [1536/10284]	Loss: 0.1600	LR: 0.004000
Training Epoch: 28 [1792/10284]	Loss: 0.1482	LR: 0.004000
Training Epoch: 28 [2048/10284]	Loss: 0.1142	LR: 0.004000
Training Epoch: 28 [2304/10284]	Loss: 0.1226	LR: 0.004000
Training Epoch: 28 [2560/10284]	Loss: 0.1657	LR: 0.004000
Training Epoch: 28 [2816/10284]	Loss: 0.1449	LR: 0.004000
Training Epoch: 28 [3072/10284]	Loss: 0.1511	LR: 0.004000
Training Epoch: 28 [3328/10284]	Loss: 0.1458	LR: 0.004000
Training Epoch: 28 [3584/10284]	Loss: 0.1386	LR: 0.004000
Training Epoch: 28 [3840/10284]	Loss: 0.1898	LR: 0.004000
Training Epoch: 28 [4096/10284]	Loss: 0.1322	LR: 0.004000
Training Epoch: 28 [4352/10284]	Loss: 0.1560	LR: 0.004000
Training Epoch: 28 [4608/10284]	Loss: 0.1318	LR: 0.004000
Training Epoch: 28 [4864/10284]	Loss: 0.1009	LR: 0.004000
Training Epoch: 28 [5120/10284]	Loss: 0.1342	LR: 0.004000
Training Epoch: 28 [5376/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 28 [5632/10284]	Loss: 0.0954	LR: 0.004000
Training Epoch: 28 [5888/10284]	Loss: 0.1901	LR: 0.004000
Training Epoch: 28 [6144/10284]	Loss: 0.1349	LR: 0.004000
Training Epoch: 28 [6400/10284]	Loss: 0.1057	LR: 0.004000
Training Epoch: 28 [6656/10284]	Loss: 0.1164	LR: 0.004000
Training Epoch: 28 [6912/10284]	Loss: 0.1137	LR: 0.004000
Training Epoch: 28 [7168/10284]	Loss: 0.1451	LR: 0.004000
Training Epoch: 28 [7424/10284]	Loss: 0.1225	LR: 0.004000
Training Epoch: 28 [7680/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 28 [7936/10284]	Loss: 0.1571	LR: 0.004000
Training Epoch: 28 [8192/10284]	Loss: 0.1010	LR: 0.004000
Training Epoch: 28 [8448/10284]	Loss: 0.1077	LR: 0.004000
Training Epoch: 28 [8704/10284]	Loss: 0.1422	LR: 0.004000
Training Epoch: 28 [8960/10284]	Loss: 0.1142	LR: 0.004000
Training Epoch: 28 [9216/10284]	Loss: 0.1273	LR: 0.004000
Training Epoch: 28 [9472/10284]	Loss: 0.0791	LR: 0.004000
Training Epoch: 28 [9728/10284]	Loss: 0.1099	LR: 0.004000
Training Epoch: 28 [9984/10284]	Loss: 0.1820	LR: 0.004000
Training Epoch: 28 [10240/10284]	Loss: 0.1477	LR: 0.004000
Training Epoch: 28 [10284/10284]	Loss: 0.0784	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1329, Train Accuracy: 0.9468
Epoch 28 training time consumed: 152.70s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_04h_08m_44s/ResNet18-MUCAC-seed10-ret75-28-best.pth
Training Epoch: 29 [256/10284]	Loss: 0.1278	LR: 0.004000
Training Epoch: 29 [512/10284]	Loss: 0.1543	LR: 0.004000
Training Epoch: 29 [768/10284]	Loss: 0.1334	LR: 0.004000
Training Epoch: 29 [1024/10284]	Loss: 0.1283	LR: 0.004000
Training Epoch: 29 [1280/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 29 [1536/10284]	Loss: 0.1504	LR: 0.004000
Training Epoch: 29 [1792/10284]	Loss: 0.1710	LR: 0.004000
Training Epoch: 29 [2048/10284]	Loss: 0.1297	LR: 0.004000
Training Epoch: 29 [2304/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 29 [2560/10284]	Loss: 0.1132	LR: 0.004000
Training Epoch: 29 [2816/10284]	Loss: 0.1320	LR: 0.004000
Training Epoch: 29 [3072/10284]	Loss: 0.1253	LR: 0.004000
Training Epoch: 29 [3328/10284]	Loss: 0.1078	LR: 0.004000
Training Epoch: 29 [3584/10284]	Loss: 0.2058	LR: 0.004000
Training Epoch: 29 [3840/10284]	Loss: 0.1296	LR: 0.004000
Training Epoch: 29 [4096/10284]	Loss: 0.1292	LR: 0.004000
Training Epoch: 29 [4352/10284]	Loss: 0.1139	LR: 0.004000
Training Epoch: 29 [4608/10284]	Loss: 0.1179	LR: 0.004000
Training Epoch: 29 [4864/10284]	Loss: 0.1632	LR: 0.004000
Training Epoch: 29 [5120/10284]	Loss: 0.1663	LR: 0.004000
Training Epoch: 29 [5376/10284]	Loss: 0.1126	LR: 0.004000
Training Epoch: 29 [5632/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 29 [5888/10284]	Loss: 0.1045	LR: 0.004000
Training Epoch: 29 [6144/10284]	Loss: 0.1272	LR: 0.004000
Training Epoch: 29 [6400/10284]	Loss: 0.1376	LR: 0.004000
Training Epoch: 29 [6656/10284]	Loss: 0.1570	LR: 0.004000
Training Epoch: 29 [6912/10284]	Loss: 0.1034	LR: 0.004000
Training Epoch: 29 [7168/10284]	Loss: 0.1217	LR: 0.004000
Training Epoch: 29 [7424/10284]	Loss: 0.1042	LR: 0.004000
Training Epoch: 29 [7680/10284]	Loss: 0.1248	LR: 0.004000
Training Epoch: 29 [7936/10284]	Loss: 0.1311	LR: 0.004000
Training Epoch: 29 [8192/10284]	Loss: 0.1023	LR: 0.004000
Training Epoch: 29 [8448/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 29 [8704/10284]	Loss: 0.1108	LR: 0.004000
Training Epoch: 29 [8960/10284]	Loss: 0.0781	LR: 0.004000
Training Epoch: 29 [9216/10284]	Loss: 0.1195	LR: 0.004000
Training Epoch: 29 [9472/10284]	Loss: 0.1192	LR: 0.004000
Training Epoch: 29 [9728/10284]	Loss: 0.1378	LR: 0.004000
Training Epoch: 29 [9984/10284]	Loss: 0.1180	LR: 0.004000
Training Epoch: 29 [10240/10284]	Loss: 0.1285	LR: 0.004000
Training Epoch: 29 [10284/10284]	Loss: 0.2859	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1306, Train Accuracy: 0.9483
Epoch 29 training time consumed: 153.54s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:8.32s
Training Epoch: 30 [256/10284]	Loss: 0.1615	LR: 0.004000
Training Epoch: 30 [512/10284]	Loss: 0.1406	LR: 0.004000
Training Epoch: 30 [768/10284]	Loss: 0.1019	LR: 0.004000
Training Epoch: 30 [1024/10284]	Loss: 0.1396	LR: 0.004000
Training Epoch: 30 [1280/10284]	Loss: 0.1639	LR: 0.004000
Training Epoch: 30 [1536/10284]	Loss: 0.1294	LR: 0.004000
Training Epoch: 30 [1792/10284]	Loss: 0.0887	LR: 0.004000
Training Epoch: 30 [2048/10284]	Loss: 0.1107	LR: 0.004000
Training Epoch: 30 [2304/10284]	Loss: 0.1246	LR: 0.004000
Training Epoch: 30 [2560/10284]	Loss: 0.1304	LR: 0.004000
Training Epoch: 30 [2816/10284]	Loss: 0.1340	LR: 0.004000
Training Epoch: 30 [3072/10284]	Loss: 0.1121	LR: 0.004000
Training Epoch: 30 [3328/10284]	Loss: 0.1668	LR: 0.004000
Training Epoch: 30 [3584/10284]	Loss: 0.1179	LR: 0.004000
Training Epoch: 30 [3840/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 30 [4096/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 30 [4352/10284]	Loss: 0.1373	LR: 0.004000
Training Epoch: 30 [4608/10284]	Loss: 0.1098	LR: 0.004000
Training Epoch: 30 [4864/10284]	Loss: 0.1418	LR: 0.004000
Training Epoch: 30 [5120/10284]	Loss: 0.1389	LR: 0.004000
Training Epoch: 30 [5376/10284]	Loss: 0.0893	LR: 0.004000
Training Epoch: 30 [5632/10284]	Loss: 0.1069	LR: 0.004000
Training Epoch: 30 [5888/10284]	Loss: 0.1200	LR: 0.004000
Training Epoch: 30 [6144/10284]	Loss: 0.1491	LR: 0.004000
Training Epoch: 30 [6400/10284]	Loss: 0.1065	LR: 0.004000
Training Epoch: 30 [6656/10284]	Loss: 0.1329	LR: 0.004000
Training Epoch: 30 [6912/10284]	Loss: 0.1101	LR: 0.004000
Training Epoch: 30 [7168/10284]	Loss: 0.1336	LR: 0.004000
Training Epoch: 30 [7424/10284]	Loss: 0.1246	LR: 0.004000
Training Epoch: 30 [7680/10284]	Loss: 0.1656	LR: 0.004000
Training Epoch: 30 [7936/10284]	Loss: 0.1550	LR: 0.004000
Training Epoch: 30 [8192/10284]	Loss: 0.1260	LR: 0.004000
Training Epoch: 30 [8448/10284]	Loss: 0.1962	LR: 0.004000
Training Epoch: 30 [8704/10284]	Loss: 0.1101	LR: 0.004000
Training Epoch: 30 [8960/10284]	Loss: 0.1180	LR: 0.004000
Training Epoch: 30 [9216/10284]	Loss: 0.0864	LR: 0.004000
Training Epoch: 30 [9472/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 30 [9728/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 30 [9984/10284]	Loss: 0.1090	LR: 0.004000
Training Epoch: 30 [10240/10284]	Loss: 0.1026	LR: 0.004000
Training Epoch: 30 [10284/10284]	Loss: 0.1701	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1284, Train Accuracy: 0.9481
Epoch 30 training time consumed: 153.64s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9346, Time consumed:8.21s
Training Epoch: 31 [256/10284]	Loss: 0.1271	LR: 0.004000
Training Epoch: 31 [512/10284]	Loss: 0.1993	LR: 0.004000
Training Epoch: 31 [768/10284]	Loss: 0.1302	LR: 0.004000
Training Epoch: 31 [1024/10284]	Loss: 0.1073	LR: 0.004000
Training Epoch: 31 [1280/10284]	Loss: 0.1197	LR: 0.004000
Training Epoch: 31 [1536/10284]	Loss: 0.1411	LR: 0.004000
Training Epoch: 31 [1792/10284]	Loss: 0.1324	LR: 0.004000
Training Epoch: 31 [2048/10284]	Loss: 0.1299	LR: 0.004000
Training Epoch: 31 [2304/10284]	Loss: 0.1085	LR: 0.004000
Training Epoch: 31 [2560/10284]	Loss: 0.1320	LR: 0.004000
Training Epoch: 31 [2816/10284]	Loss: 0.1948	LR: 0.004000
Training Epoch: 31 [3072/10284]	Loss: 0.1072	LR: 0.004000
Training Epoch: 31 [3328/10284]	Loss: 0.1022	LR: 0.004000
Training Epoch: 31 [3584/10284]	Loss: 0.1275	LR: 0.004000
Training Epoch: 31 [3840/10284]	Loss: 0.1536	LR: 0.004000
Training Epoch: 31 [4096/10284]	Loss: 0.1138	LR: 0.004000
Training Epoch: 31 [4352/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 31 [4608/10284]	Loss: 0.1528	LR: 0.004000
Training Epoch: 31 [4864/10284]	Loss: 0.1408	LR: 0.004000
Training Epoch: 31 [5120/10284]	Loss: 0.0953	LR: 0.004000
Training Epoch: 31 [5376/10284]	Loss: 0.1449	LR: 0.004000
Training Epoch: 31 [5632/10284]	Loss: 0.1116	LR: 0.004000
Training Epoch: 31 [5888/10284]	Loss: 0.1255	LR: 0.004000
Training Epoch: 31 [6144/10284]	Loss: 0.1357	LR: 0.004000
Training Epoch: 31 [6400/10284]	Loss: 0.1157	LR: 0.004000
Training Epoch: 31 [6656/10284]	Loss: 0.0776	LR: 0.004000
Training Epoch: 31 [6912/10284]	Loss: 0.1496	LR: 0.004000
Training Epoch: 31 [7168/10284]	Loss: 0.1401	LR: 0.004000
Training Epoch: 31 [7424/10284]	Loss: 0.0976	LR: 0.004000
Training Epoch: 31 [7680/10284]	Loss: 0.1336	LR: 0.004000
Training Epoch: 31 [7936/10284]	Loss: 0.1201	LR: 0.004000
Training Epoch: 31 [8192/10284]	Loss: 0.1192	LR: 0.004000
Training Epoch: 31 [8448/10284]	Loss: 0.1714	LR: 0.004000
Training Epoch: 31 [8704/10284]	Loss: 0.1306	LR: 0.004000
Training Epoch: 31 [8960/10284]	Loss: 0.1143	LR: 0.004000
Training Epoch: 31 [9216/10284]	Loss: 0.1102	LR: 0.004000
Training Epoch: 31 [9472/10284]	Loss: 0.1190	LR: 0.004000
Training Epoch: 31 [9728/10284]	Loss: 0.1499	LR: 0.004000
Training Epoch: 31 [9984/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 31 [10240/10284]	Loss: 0.1234	LR: 0.004000
Training Epoch: 31 [10284/10284]	Loss: 0.1255	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1298, Train Accuracy: 0.9461
Epoch 31 training time consumed: 153.64s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.13s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10284
Forget Train Dl:  264
Retain Valid Dl:  10284
Forget Valid Dl:  264
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 93.87765502929688
Retain Accuracy: 95.17911529541016
Zero-Retain Forget (ZRF): 0.7490251660346985
Membership Inference Attack (MIA): 0.3106060606060606
Forget vs Retain Membership Inference Attack (MIA): 0.5094339622641509
Forget vs Test Membership Inference Attack (MIA): 0.6132075471698113
Test vs Retain Membership Inference Attack (MIA): 0.5399515738498789
Train vs Test Membership Inference Attack (MIA): 0.5435835351089588
Forget Set Accuracy (Df): 97.4609375
Method Execution Time: 6238.52 seconds
