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

📌 S Retain class distribution for seed 8:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 8:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5547
  Class 1: 4473
Forget set:
  Class 0: 264
  Class 1: 264
./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 [256/10020]	Loss: 0.7518	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.7361	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.7056	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.7415	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 0.8989	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.7830	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 0.8227	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 0.8760	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 0.7571	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 0.7970	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.7331	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 0.7637	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 1.1252	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 1.0624	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.8520	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.7249	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.8353	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 2.6818	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 2.2865	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.8021	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 0.9341	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 1.2550	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7596	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.8426	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.8414	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.6973	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.7740	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.7624	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.7077	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.6990	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.7410	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.7189	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.7104	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.7674	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.7145	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.7178	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.7095	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.8657	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.7453	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6845	LR: 0.097500
Epoch 1 - Average Train Loss: 0.8890, Train Accuracy: 0.5063
Epoch 1 training time consumed: 327.09s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0107, Accuracy: 0.5579, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.7047	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.6945	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.6899	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.7399	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.6859	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7851	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.7018	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.7031	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.6945	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.6893	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.6927	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.6822	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.7224	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6780	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.7333	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.6964	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.6668	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.6731	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.6754	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.7698	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.6987	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.7043	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.6903	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.7803	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.8474	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.7796	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.7222	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.7573	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.8166	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.6978	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7342	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.6937	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.7404	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.7047	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.7291	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.7937	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.7135	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.7271	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.6920	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7203, Train Accuracy: 0.5419
Epoch 2 training time consumed: 146.96s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5341, Time consumed:8.07s
Training Epoch: 3 [256/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.7251	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.6705	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.7589	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.7405	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.7186	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.7747	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.6878	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.7235	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.6797	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.7094	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.6826	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.7164	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.6941	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.6782	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.7202	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7004	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.6671	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.7067	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.6990	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.7262	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.7218	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.6877	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.6875	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.7179	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.6825	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.6807	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.6788	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.7300	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6624	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.6674	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.7066	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6806	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.6728	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6864	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.6625	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6756	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.6469	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6976, Train Accuracy: 0.5508
Epoch 3 training time consumed: 146.56s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0032, Accuracy: 0.5530, Time consumed:8.25s
Training Epoch: 4 [256/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.7013	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.6532	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.6662	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6692	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6894	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6840	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6676	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6934	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.7290	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.6911	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6926	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.6967	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.6981	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6907	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6981	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.7053	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.6863	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6691	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.7218	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.7012	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6957	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.7172	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6820	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.6601	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6565	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.6775	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.7133	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6715	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6594	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.6879	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6813	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6854	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6382	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6602	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.6455	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6834, Train Accuracy: 0.5595
Epoch 4 training time consumed: 146.27s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5487, Time consumed:7.88s
Training Epoch: 5 [256/10020]	Loss: 0.7376	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6837	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.6444	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.7089	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6813	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.6571	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6667	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6980	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6583	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6501	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6474	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.6579	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.7016	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6657	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.6691	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6576	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6879	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6678	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6812	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6608	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6740	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.6824	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6364	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.6608	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6764	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6830	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6495	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6517	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6514	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6527	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.7071	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.8427	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6730, Train Accuracy: 0.5946
Epoch 5 training time consumed: 146.53s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.5971, Time consumed:8.26s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-5-best.pth
Training Epoch: 6 [256/10020]	Loss: 0.6628	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6985	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.7100	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6789	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6866	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.6951	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6912	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.7085	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6914	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6852	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6894	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6881	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6989	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.6963	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6834	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6992	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6851	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6915	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6927	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6907	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6879	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6689	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6952	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6581	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6773	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6995	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6955	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.6670	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6695	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6938	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6975	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.6678	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6823	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6833	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6927	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6871, Train Accuracy: 0.5462
Epoch 6 training time consumed: 146.66s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5642, Time consumed:8.24s
Training Epoch: 7 [256/10020]	Loss: 0.6888	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.6683	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6994	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6865	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6749	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6436	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.6845	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6532	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6778	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.7017	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6892	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6768	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6938	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6826	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6654	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.6723	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6531	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.6906	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6798	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6734	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.6668	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.6788	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.6569	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.7076	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6734	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6493	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6626	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6589	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6629	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6664	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6738	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6459	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.6696	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6663	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.6241	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6737, Train Accuracy: 0.5862
Epoch 7 training time consumed: 146.89s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0034, Accuracy: 0.5148, Time consumed:8.11s
Training Epoch: 8 [256/10020]	Loss: 0.7127	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6906	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.6822	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6648	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.6628	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6939	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6767	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.6583	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6560	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.6802	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.6660	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.6705	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.6570	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.6589	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.7000	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.7069	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.6615	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.6577	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.6598	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.6563	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.6861	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.6726	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.6567	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.7010	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.6596	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.6458	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.6343	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.6597	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.6685	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.6404	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.6528	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.6776	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.6990	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.6550	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6694, Train Accuracy: 0.5973
Epoch 8 training time consumed: 146.52s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0032, Accuracy: 0.5574, Time consumed:8.03s
Training Epoch: 9 [256/10020]	Loss: 0.6616	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.7029	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.7316	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.6632	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.6546	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.6661	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.6612	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.6470	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.6784	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.6593	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.6847	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.6791	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.6929	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.6891	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.7026	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.6641	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.6564	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.6704	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.6547	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.6617	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.6602	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.6738	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.6517	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.6501	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.6518	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.6564	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.6656	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.6423	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.6611	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.6516	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.6621	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.6625	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.6304	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.6473	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.6394	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.6923	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6663, Train Accuracy: 0.5962
Epoch 9 training time consumed: 146.24s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0032, Accuracy: 0.5559, Time consumed:8.30s
Training Epoch: 10 [256/10020]	Loss: 0.6412	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.6617	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.6898	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.6606	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.6521	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.6878	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.6507	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.6604	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.6701	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.6347	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.6341	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.6674	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.6355	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.7054	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.6391	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.6135	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.6435	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.6327	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.6745	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.6678	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.6490	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.6426	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.6573	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.6184	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.6444	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.6241	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.6565	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.6454	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.6408	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.6097	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.6633	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.6466	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.6657	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.6678	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.6160	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.6191	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.6532	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.6436	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.6275	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.7379	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6494, Train Accuracy: 0.6255
Epoch 10 training time consumed: 146.42s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0028, Accuracy: 0.6596, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.6236	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.6410	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.6190	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.6304	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.6222	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.6574	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.6064	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.6427	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.6264	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.6481	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.6438	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.6160	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.6282	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.6051	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.5885	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.6570	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.6123	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.6629	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.6073	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.6202	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.6125	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.6317	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.5746	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.6135	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.6133	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.5946	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.5825	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.6129	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.6097	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.6191	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.6417	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.6174	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.6192	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.6152	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.6675	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.5946	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.5860	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.5932	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.6285	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.5962	LR: 0.020000
Epoch 11 - Average Train Loss: 0.6201, Train Accuracy: 0.6604
Epoch 11 training time consumed: 146.97s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0026, Accuracy: 0.6939, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-11-best.pth
Training Epoch: 12 [256/10020]	Loss: 0.6001	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.5994	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.5912	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.5882	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.6354	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.6156	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.5870	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.6375	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.5939	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.6269	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.5584	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.6145	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.6261	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.6298	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.5973	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.6417	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.6099	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.6348	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.6120	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.6125	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.6168	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.5972	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.5851	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.6252	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.5689	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.5714	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.6362	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.6422	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.5761	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.6132	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.5893	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.5946	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.6194	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.6248	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.5489	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.5906	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.6112	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.5657	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.5704	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.5670	LR: 0.020000
Epoch 12 - Average Train Loss: 0.6040, Train Accuracy: 0.6747
Epoch 12 training time consumed: 146.35s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0026, Accuracy: 0.6920, Time consumed:8.21s
Training Epoch: 13 [256/10020]	Loss: 0.6148	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.6227	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.5576	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.6074	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.5982	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.5898	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.6112	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.6071	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.6301	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.5866	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.6076	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.6097	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.6200	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.5680	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.6230	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.5935	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.5498	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.5990	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.5479	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.5806	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.5724	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.5952	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.5873	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.5635	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.5955	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.5502	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.5562	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.5539	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.6128	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.5589	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.5118	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.5701	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.5539	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.6062	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.5399	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.5887	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.5893	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.5805	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.5455	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.5562	LR: 0.020000
Epoch 13 - Average Train Loss: 0.5834, Train Accuracy: 0.6939
Epoch 13 training time consumed: 145.34s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0073, Accuracy: 0.4886, Time consumed:8.16s
Training Epoch: 14 [256/10020]	Loss: 0.5635	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.5886	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.5622	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.5907	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.5355	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.6266	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.6071	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.6719	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.5779	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.6169	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.5802	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.5826	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.5635	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.5914	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.5903	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.5485	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.5318	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.5835	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.6298	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.5579	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.5057	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.5816	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.5452	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.5884	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.5176	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.5361	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.5689	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.5176	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.5369	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.4698	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.5091	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.5351	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.5141	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.5527	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.5338	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.5695	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.5322	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.5358	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.5266	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.5271	LR: 0.020000
Epoch 14 - Average Train Loss: 0.5608, Train Accuracy: 0.7114
Epoch 14 training time consumed: 146.59s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0026, Accuracy: 0.6877, Time consumed:8.02s
Training Epoch: 15 [256/10020]	Loss: 0.5380	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.5499	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.6122	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.5654	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.5839	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.5280	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.5889	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.5194	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.5459	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.4792	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.5372	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.5131	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.5424	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.5546	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.5409	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.5200	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.5208	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.5295	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.4943	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.5250	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.5165	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.5223	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.5090	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.5238	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.4784	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.4790	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.4714	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.4518	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.4600	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.4801	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.4984	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.4776	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.5131	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.4340	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.5083	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.5104	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.5042	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.4542	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.4778	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.3828	LR: 0.020000
Epoch 15 - Average Train Loss: 0.5139, Train Accuracy: 0.7517
Epoch 15 training time consumed: 146.14s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0028, Accuracy: 0.6600, Time consumed:8.13s
Training Epoch: 16 [256/10020]	Loss: 0.4955	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.5118	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.4798	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.4811	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.4716	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.4967	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.5189	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.5053	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.4588	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.5208	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.5589	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.4783	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.4723	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.4779	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.4255	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.4132	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.4229	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.4847	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.4221	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.4223	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.5030	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.4095	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.4305	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.4208	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.4639	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.4594	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.4185	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.4037	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.4563	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.3506	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.4015	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.4039	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.4464	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.4481	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.4510	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.4655	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.3660	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.4283	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.4299	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.4016	LR: 0.020000
Epoch 16 - Average Train Loss: 0.4530, Train Accuracy: 0.7895
Epoch 16 training time consumed: 145.98s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0019, Accuracy: 0.8131, Time consumed:8.17s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-16-best.pth
Training Epoch: 17 [256/10020]	Loss: 0.4144	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.4882	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.4033	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.4313	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.4447	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.4638	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.4197	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.4796	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.4344	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.4934	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.3915	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.3944	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.4494	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.4920	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.4406	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.4408	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.3702	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.3781	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.4153	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.3975	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.3725	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.4130	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.3897	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.4366	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.5302	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.3906	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.3747	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.3740	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.3824	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.4011	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.3867	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.3623	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.3285	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.3645	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.3491	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.3613	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.3815	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.3678	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.3450	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.3355	LR: 0.020000
Epoch 17 - Average Train Loss: 0.4088, Train Accuracy: 0.8180
Epoch 17 training time consumed: 145.25s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0036, Accuracy: 0.6116, Time consumed:7.99s
Training Epoch: 18 [256/10020]	Loss: 0.4289	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.3816	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.4449	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.3788	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.2864	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.3185	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.3805	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.3617	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.3916	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.3523	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.3854	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.3629	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.3349	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.3615	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.3667	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.3245	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.3767	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.3619	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.3516	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.4094	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.3098	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.3540	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.3269	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.2842	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.3975	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.3855	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.2878	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.3342	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.3539	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.3189	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.3028	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.2308	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.3178	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.4248	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.3224	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.2558	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.3187	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.2459	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.2811	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.1516	LR: 0.020000
Epoch 18 - Average Train Loss: 0.3432, Train Accuracy: 0.8541
Epoch 18 training time consumed: 146.35s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0026, Accuracy: 0.7540, Time consumed:8.31s
Training Epoch: 19 [256/10020]	Loss: 0.2984	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.2425	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.3454	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.2596	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.3004	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.2778	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.3048	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.3636	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2759	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.3047	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.2765	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.3444	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.3494	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.3359	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.3205	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.3058	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.3053	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.3012	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2257	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.2542	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.2675	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.2584	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2490	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.2434	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2729	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.2121	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.2423	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.2172	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.2665	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.2788	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.2391	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.2459	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2831	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2236	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.2270	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.2210	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.2334	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.2579	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.2219	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.1700	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2728, Train Accuracy: 0.8871
Epoch 19 training time consumed: 146.83s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0012, Accuracy: 0.8881, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-19-best.pth
Training Epoch: 20 [256/10020]	Loss: 0.2261	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.2019	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.2218	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.2592	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.1862	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.2505	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.2461	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.1936	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.2466	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.1949	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.2161	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.2129	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.2632	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.1873	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.1854	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.2604	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.1780	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.2114	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.1978	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.1883	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.2384	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.1960	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.2448	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.2129	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.2106	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1987	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.1980	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.2165	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.2100	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.1791	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.2381	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1850	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.1973	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.1883	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.2292	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1539	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.1986	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1667	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.2284	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.1329	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2104, Train Accuracy: 0.9138
Epoch 20 training time consumed: 146.49s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0008, Accuracy: 0.9283, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1822	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.2137	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.1586	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.2493	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1833	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1708	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.2263	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.2225	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.2385	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.2374	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1940	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.2080	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1719	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.2048	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1617	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.2341	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1640	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.1277	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.1887	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.1788	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.2073	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1867	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.1199	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1840	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.1546	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1892	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.1861	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.2323	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1473	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.1276	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.2039	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1573	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.2035	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.2068	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.2116	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.1784	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1869, Train Accuracy: 0.9250
Epoch 21 training time consumed: 145.40s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0010, Accuracy: 0.8959, Time consumed:8.01s
Training Epoch: 22 [256/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1887	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.1921	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1713	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.2065	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.1625	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1694	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1472	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1719	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.2405	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1868	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1772	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1945	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.2020	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.2053	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1786	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.2114	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1866	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1884	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1978	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1919	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.2220	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.2188	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.2263	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1742	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.1842	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.2011	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1971	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.1772	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.2061	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.1654	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1990	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.2115	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1924	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.2138	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1889, Train Accuracy: 0.9212
Epoch 22 training time consumed: 146.00s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0010, Accuracy: 0.9119, Time consumed:8.26s
Training Epoch: 23 [256/10020]	Loss: 0.1465	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1443	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.2230	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.1766	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1472	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.2071	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.2317	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.2123	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.1777	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1545	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.2259	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.1821	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1798	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1997	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.1578	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1690	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1665	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1541	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1764	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.2075	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.2485	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1976	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.2296	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.1426	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.2144	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1557	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1480	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1914	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.2337	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1893	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1945	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1752	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1291	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1882	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.1027	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1820, Train Accuracy: 0.9219
Epoch 23 training time consumed: 145.26s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0008, Accuracy: 0.9206, Time consumed:7.99s
Training Epoch: 24 [256/10020]	Loss: 0.2029	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.1973	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.2025	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1540	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1174	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1942	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.2111	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1557	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1464	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1749	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1689	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1724	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1872	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.2074	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.1903	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.1575	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1566	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1825	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1948	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1656	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1884	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1971	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1811	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1783	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1812	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.2016	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.1632	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.1897	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1704	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1366	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1699	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.2026	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1739, Train Accuracy: 0.9298
Epoch 24 training time consumed: 144.99s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9337, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-24-best.pth
Training Epoch: 25 [256/10020]	Loss: 0.1089	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.1774	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1748	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1652	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1521	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1946	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.2310	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.2165	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1692	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1179	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.2162	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.1916	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.1882	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.1352	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1964	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.2419	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1416	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.1768	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1651	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1577	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1742	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1476	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1554	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.1563	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1944	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.2081	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1619	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.1603	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.1346	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1894	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1601	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.1830	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1280	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.1540	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1682, Train Accuracy: 0.9322
Epoch 25 training time consumed: 146.01s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0010, Accuracy: 0.9133, Time consumed:8.17s
Training Epoch: 26 [256/10020]	Loss: 0.1624	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1763	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.1589	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1243	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.1914	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1247	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.2116	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1740	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1422	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1706	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.2228	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1664	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1657	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1467	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.1914	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1445	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1365	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1539	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1953	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.2024	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1138	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1658	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1950	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1856	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1835	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1521	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.2032	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1191	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1512	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1358	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.2382	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1746	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.1082	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1501	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1594	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.2060	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.1737	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1657, Train Accuracy: 0.9309
Epoch 26 training time consumed: 145.42s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:8.16s
Training Epoch: 27 [256/10020]	Loss: 0.1205	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.1541	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1153	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1398	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1837	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.2097	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1624	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1597	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1527	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1764	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1760	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.1602	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1095	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1965	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1738	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.1495	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1946	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1839	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1996	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1633	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1237	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1197	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1389	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1942	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1832	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1582	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1866	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.1823	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1506	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1231	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.1921	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1579, Train Accuracy: 0.9353
Epoch 27 training time consumed: 145.70s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-27-best.pth
Training Epoch: 28 [256/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1518	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1363	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1180	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1526	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1263	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1359	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.1864	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1509	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.0910	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1609	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1782	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1215	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1861	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1733	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.1278	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1601	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.2116	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1361	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1758	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1372	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1465	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1821	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1921	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1949	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1437	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1351	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1243	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1392	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1367	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.0881	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.0766	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1493, Train Accuracy: 0.9384
Epoch 28 training time consumed: 145.68s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-28-best.pth
Training Epoch: 29 [256/10020]	Loss: 0.1110	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1792	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1284	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1231	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.2030	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1563	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1684	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1140	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1372	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1544	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1175	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1570	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1335	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.2186	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.1264	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1631	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1466	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1570	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.1757	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1782	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.1455	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1214	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1135	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1278	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1197	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1552	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1268	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1411	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.2267	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1479	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.1186	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1484, Train Accuracy: 0.9403
Epoch 29 training time consumed: 146.23s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9303, Time consumed:8.22s
Training Epoch: 30 [256/10020]	Loss: 0.1670	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1451	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.2044	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1622	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.1203	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1258	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1388	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1978	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1364	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1813	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1299	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1451	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1226	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1845	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1561	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1469	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1450	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1562	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1282	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1320	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1158	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1769	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.1773	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1506	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1399	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1780	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.1704	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1505, Train Accuracy: 0.9349
Epoch 30 training time consumed: 146.03s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9414, Time consumed:8.26s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_07h_22m_45s/ResNet18-MUCAC-seed8-ret50-30-best.pth
Training Epoch: 31 [256/10020]	Loss: 0.0959	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1430	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.2118	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1235	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.0826	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1265	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1133	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1959	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1083	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1781	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.1464	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.1595	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1330	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1620	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1460	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1852	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1600	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1901	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1279	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1081	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1437	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1278	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1302	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1746	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1126	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.2064	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.1208	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1712	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1582	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.0863	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1621	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.2526	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1455, Train Accuracy: 0.9412
Epoch 31 training time consumed: 146.54s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.10s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10020
Forget Train Dl:  528
Retain Valid Dl:  10020
Forget Valid Dl:  528
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 93.79085540771484
Retain Accuracy: 93.7673568725586
Zero-Retain Forget (ZRF): 0.8088387846946716
Membership Inference Attack (MIA): 0.32954545454545453
Forget vs Retain Membership Inference Attack (MIA): 0.4811320754716981
Forget vs Test Membership Inference Attack (MIA): 0.5566037735849056
Test vs Retain Membership Inference Attack (MIA): 0.5084745762711864
Train vs Test Membership Inference Attack (MIA): 0.5266343825665859
Forget Set Accuracy (Df): 92.83853912353516
Method Execution Time: 5939.80 seconds
