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

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

📌 S Forget class distribution for seed 1:
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: 0.6971	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.6886	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.6918	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.6925	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 0.6796	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.6895	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 0.7219	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 0.7443	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 1.0306	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 0.7438	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.8777	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 1.3114	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 0.8803	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 0.7350	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.8822	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 1.3209	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.8797	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.9761	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 1.2726	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.7087	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 1.1205	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.7000	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7461	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.8494	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.7512	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7549	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.7359	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 1.0231	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.7194	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.7000	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.7842	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.7728	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.7101	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.6899	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.7187	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.6983	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.6984	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.6910	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.7045	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6831	LR: 0.097500
Epoch 1 - Average Train Loss: 0.8147, Train Accuracy: 0.5175
Epoch 1 training time consumed: 332.87s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.2223, Accuracy: 0.5550, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.7762	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.7315	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.7029	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7143	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.7266	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.7126	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7428	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.6915	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.7795	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.7877	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.6917	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.7016	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.7309	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.6797	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.7350	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.7627	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.7147	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.7741	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.7188	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.7637	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.7108	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.7052	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.6903	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.7027	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.6924	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.7105	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.7127	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.7032	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.6910	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.7183	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.7022	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7001	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.7056	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.6864	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.7195	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.6847	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.6980	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.7071	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.6430	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7168, Train Accuracy: 0.5196
Epoch 2 training time consumed: 145.73s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5283, Time consumed:8.15s
Training Epoch: 3 [256/10020]	Loss: 0.6740	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.6680	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.6791	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.7277	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.6863	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.6908	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.6847	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.7095	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.6692	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.6892	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.7330	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.7129	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.6640	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.7679	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7770	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.7224	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.6813	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.6875	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.7720	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.7345	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.7486	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.7053	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.6911	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.6946	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.7019	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.7178	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6898	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.6844	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.7205	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.6898	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.6750	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6522	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.7177	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6913	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.6472	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6994, Train Accuracy: 0.5579
Epoch 3 training time consumed: 145.42s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5947, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-3-best.pth
Training Epoch: 4 [256/10020]	Loss: 0.6854	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.6834	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.6809	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.6753	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.6718	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6852	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6844	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6876	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.7034	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.7186	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6588	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.6991	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.6782	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6862	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6784	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.6753	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6772	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6566	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6763	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6798	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.6589	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6876	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.6843	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6904	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.6858	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.7423	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6500	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6800	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.7059	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6984	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6926	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6705	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6782	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.6390	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6827, Train Accuracy: 0.5769
Epoch 4 training time consumed: 144.95s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0031, Accuracy: 0.5041, Time consumed:7.93s
Training Epoch: 5 [256/10020]	Loss: 0.6830	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.7629	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.7355	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.6893	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6769	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.7154	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6994	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6892	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6726	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.6779	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.6969	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6970	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.6823	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6468	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6634	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6969	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6578	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6717	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.7080	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6668	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6524	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6882	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.7102	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6750	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6885	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6765	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6566	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6878	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6967	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6678	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6818	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.7121	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6854, Train Accuracy: 0.5735
Epoch 5 training time consumed: 145.13s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0032, Accuracy: 0.5559, Time consumed:8.09s
Training Epoch: 6 [256/10020]	Loss: 0.6767	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6841	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.7097	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6923	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6837	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6898	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6729	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6715	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6793	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6629	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6697	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.7032	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6546	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6520	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6559	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6758	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6445	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6916	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.7340	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6601	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6594	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6768	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6838	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6669	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6456	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6766	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.6780	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6775	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6741	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.6500	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6737	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6542	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6052	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6742, Train Accuracy: 0.5852
Epoch 6 training time consumed: 145.31s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0032, Accuracy: 0.5099, Time consumed:7.93s
Training Epoch: 7 [256/10020]	Loss: 0.6714	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.6795	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.7019	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.7054	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6684	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6614	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.6482	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6712	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6697	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6660	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6728	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6582	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.6729	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6809	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.6729	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6598	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6932	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.6904	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.6553	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.7060	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.6629	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6470	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6540	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6733	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6562	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6749	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6748	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6496	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.7055	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6480	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.7286	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.5638	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6734, Train Accuracy: 0.5874
Epoch 7 training time consumed: 145.24s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.5748, Time consumed:8.09s
Training Epoch: 8 [256/10020]	Loss: 0.6532	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6999	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.6960	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6732	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.6535	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6475	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6804	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6902	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.6890	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.6694	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6636	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6651	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.6594	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.7029	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.6826	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.6458	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.6702	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.6820	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.7041	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.6588	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.6591	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.6740	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.6576	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.6591	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.6630	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.6511	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.6516	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.6616	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.6445	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.6349	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.6097	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.6479	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.6294	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.6243	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.6028	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.6520	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.5528	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6623, Train Accuracy: 0.6075
Epoch 8 training time consumed: 145.22s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0028, Accuracy: 0.6475, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-8-best.pth
Training Epoch: 9 [256/10020]	Loss: 0.5885	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.6229	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.6035	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.5839	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.6576	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.6523	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.6369	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.6389	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.5888	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.6086	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.6259	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.6368	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.6260	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.6288	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.6307	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.6199	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.6573	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.6282	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.6181	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.6129	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.6040	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.5843	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.6340	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.6154	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.5658	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.6081	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.6200	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.6377	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.5980	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.5712	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.5542	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.6353	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.6228	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.5670	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.5888	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.6408	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.6270	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.5931	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.5658	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6151, Train Accuracy: 0.6682
Epoch 9 training time consumed: 145.43s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0030, Accuracy: 0.6179, Time consumed:8.16s
Training Epoch: 10 [256/10020]	Loss: 0.5987	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.6329	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.5940	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.5973	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.6254	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.5956	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.5760	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.5478	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.5761	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.5623	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.5450	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.5866	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.5956	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.5881	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.5770	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.6546	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.5328	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.5716	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.5683	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.5145	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.5874	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.5523	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.5723	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.4960	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.5822	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.5842	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.5663	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.5555	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.5276	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.5181	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.5542	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.5278	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.5160	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.5929	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.5753	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.5293	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.5526	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.5013	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.5351	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.4815	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5655, Train Accuracy: 0.7048
Epoch 10 training time consumed: 145.34s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0025, Accuracy: 0.7143, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.4898	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.6421	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.6475	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.6102	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.5755	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.5726	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.5690	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.5781	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.6379	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.5790	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.5328	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.5843	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.5586	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.4912	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.5064	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.5202	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.5519	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.5172	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.5149	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.5255	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.5109	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.4853	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.5080	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.5088	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.5366	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.4919	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.5235	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.4804	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.4661	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.4992	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.4941	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.5084	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.5339	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.4557	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.4650	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.4835	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.5436	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.4767	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.4754	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.5813	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5297, Train Accuracy: 0.7430
Epoch 11 training time consumed: 144.70s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0023, Accuracy: 0.7419, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-11-best.pth
Training Epoch: 12 [256/10020]	Loss: 0.4805	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.5384	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.5056	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.5182	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.4583	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.5209	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.5113	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.4914	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.4248	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.5051	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.5031	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.4578	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.4667	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.4211	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.4564	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.4403	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.3708	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.4820	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.4227	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.4894	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.5296	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.4747	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.4404	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.5340	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.4666	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.4573	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.3924	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.4251	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.4446	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.4497	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.4244	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.4768	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.4157	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.4465	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.4988	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.4044	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.4043	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.3873	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.4235	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.3255	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4601, Train Accuracy: 0.7879
Epoch 12 training time consumed: 145.06s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0020, Accuracy: 0.7879, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-12-best.pth
Training Epoch: 13 [256/10020]	Loss: 0.3600	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.4497	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.4664	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.3910	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.4320	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.4173	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.3978	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.3609	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.4610	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.3840	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.3504	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.4544	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.4133	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.4286	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.4574	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.4171	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.3308	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.3618	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.4023	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.4227	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.3838	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.4135	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.3823	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.3760	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.3873	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.3644	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.3654	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.4059	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.3636	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.3225	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.4292	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.4176	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.3703	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.3909	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.3978	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.3656	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.4439	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.3515	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.3963	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.3349	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3969, Train Accuracy: 0.8236
Epoch 13 training time consumed: 144.93s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0019, Accuracy: 0.8044, Time consumed:7.83s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-13-best.pth
Training Epoch: 14 [256/10020]	Loss: 0.4345	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.3802	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.3732	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.4938	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.4528	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.4257	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.3632	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.3672	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.4301	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.3660	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.3967	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.3714	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.3484	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.3880	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.4017	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.3821	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.3746	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.4061	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.3662	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.3791	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.3970	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.4044	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.3477	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.3538	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.3866	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.3981	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.4381	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.3759	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.3119	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.4126	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.3480	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.4518	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.3366	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.3665	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.3324	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.3758	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.3785	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.4230	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.3146	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.3126	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3857, Train Accuracy: 0.8311
Epoch 14 training time consumed: 145.31s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0028, Accuracy: 0.6939, Time consumed:8.02s
Training Epoch: 15 [256/10020]	Loss: 0.4209	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.4402	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.3447	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.2881	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.3178	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.3448	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.3327	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.3561	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.3316	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.3592	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.3710	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.3495	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.2950	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.3162	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.3327	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.2962	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.3169	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.3171	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.3324	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.3054	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.2803	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.3185	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.3582	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.3021	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.3499	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.3625	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.3848	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.3096	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.3146	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.3145	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.3014	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.2755	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.3426	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.3508	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.2770	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.3209	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.3212	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.3317	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.2731	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.3659	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3298, Train Accuracy: 0.8598
Epoch 15 training time consumed: 144.93s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0019, Accuracy: 0.8194, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-15-best.pth
Training Epoch: 16 [256/10020]	Loss: 0.3075	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.3539	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.3528	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.2642	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.2682	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.3098	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.3592	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.3355	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.2912	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.3194	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.2675	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.3168	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.2651	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.2712	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.2827	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.3370	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.2662	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.2652	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.2462	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.2418	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.2814	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.2433	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.3319	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.2144	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.2697	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.2571	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.2850	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.3019	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.2803	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.2797	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.3008	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.2508	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.2773	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.2711	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.2247	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.2536	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.2991	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.2537	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.2065	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.1419	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2816, Train Accuracy: 0.8840
Epoch 16 training time consumed: 145.79s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0014, Accuracy: 0.8726, Time consumed:8.19s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-16-best.pth
Training Epoch: 17 [256/10020]	Loss: 0.2163	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.1762	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.1420	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.2445	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.2455	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.2353	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.3076	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.3056	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.2778	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.2319	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.2893	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.1620	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.2564	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.2741	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.2528	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.2435	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.2198	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.2963	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.2511	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.3050	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.4095	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.2999	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.3754	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.2646	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.2873	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.2414	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.2160	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.3050	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.2564	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.2672	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.2530	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.2701	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.3253	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.2583	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.3293	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.2939	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.2201	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.3699	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.2637	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.3348	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2679, Train Accuracy: 0.8869
Epoch 17 training time consumed: 144.97s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0019, Accuracy: 0.8426, Time consumed:8.04s
Training Epoch: 18 [256/10020]	Loss: 0.3141	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.3381	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.2296	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.2292	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.2489	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.3054	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.2913	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.2482	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.1933	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.3368	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.2656	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.2270	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.2373	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.2649	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.2292	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.1918	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.2622	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.2446	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.1987	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.2575	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.1742	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.2060	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2330	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.2085	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.2331	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.2255	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.1880	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.2120	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.1812	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.1929	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.2382	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.2187	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.2470	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.1738	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.2240	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.2084	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.2421	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.1884	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.2227	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.1943	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2340, Train Accuracy: 0.9037
Epoch 18 training time consumed: 144.89s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0010, Accuracy: 0.9056, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-18-best.pth
Training Epoch: 19 [256/10020]	Loss: 0.2498	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.1937	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.2482	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.2401	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.1885	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.1944	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.2296	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.2099	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2138	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.1791	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.2215	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.2283	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.1657	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.1946	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.2660	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.1751	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.1515	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.2643	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.1675	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.2528	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.1882	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.1975	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2295	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.1771	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2354	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.1694	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.2040	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.2165	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.1797	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.1875	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.2134	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.1785	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2491	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2045	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.2288	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.2236	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.1932	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.1707	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.1945	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.3590	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2076, Train Accuracy: 0.9142
Epoch 19 training time consumed: 144.79s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0016, Accuracy: 0.8450, Time consumed:8.06s
Training Epoch: 20 [256/10020]	Loss: 0.1698	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.1726	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.2490	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.1542	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.1512	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.2315	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.1985	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.1781	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.1849	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.2201	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.2025	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.2360	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.1316	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.1924	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.1963	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.2420	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.2321	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.2100	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.1846	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.1572	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.1563	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.1715	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.1939	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.1713	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.1892	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.1784	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.1675	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1349	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.1827	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.1566	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1714	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.1742	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.1383	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1800, Train Accuracy: 0.9248
Epoch 20 training time consumed: 144.96s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1247	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.1693	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.2114	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1454	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1510	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.1323	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.1831	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.1864	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1352	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1444	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.1827	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.1901	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.2089	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.1627	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.1504	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1670	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.1198	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1487	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.1571	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1397	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.1191	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1486	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.1893	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1543	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1649	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.1796	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.1706	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.2223	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.2039	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.1737	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1628, Train Accuracy: 0.9322
Epoch 21 training time consumed: 145.08s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9414, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-21-best.pth
Training Epoch: 22 [256/10020]	Loss: 0.1056	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1260	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.1057	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.1717	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1082	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1661	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1804	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.1563	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.1417	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.1561	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1644	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.1725	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1936	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1635	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1552	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1299	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1837	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1711	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1611	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.2105	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.1776	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1704	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1699	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.1498	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.1931	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.1283	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1888	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.2384	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1585, Train Accuracy: 0.9355
Epoch 22 training time consumed: 145.27s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_14h_49m_04s/ResNet18-MUCAC-seed1-ret50-22-best.pth
Training Epoch: 23 [256/10020]	Loss: 0.1685	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1262	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.1942	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1702	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.1715	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.1155	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.1448	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.1334	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1306	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1832	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.1856	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.1325	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1516	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.2372	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1885	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1552	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1538	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1469	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1211	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1916	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.1140	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.1867	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.1523	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.1373	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1257	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1765	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1429	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1318	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1650	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1794	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.0649	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1549, Train Accuracy: 0.9356
Epoch 23 training time consumed: 145.17s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0008, Accuracy: 0.9191, Time consumed:7.99s
Training Epoch: 24 [256/10020]	Loss: 0.1596	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.1535	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.1981	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1234	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1566	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.1549	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1241	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1192	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1464	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1553	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.0976	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1584	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1087	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1649	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1765	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.1811	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.1911	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.2194	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1823	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1582	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1232	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.0962	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1303	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.0892	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1952	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1106	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1526	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.1126	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1469	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.2231	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.1519	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1232	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1031	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.0787	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1480, Train Accuracy: 0.9394
Epoch 24 training time consumed: 145.10s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:7.90s
Training Epoch: 25 [256/10020]	Loss: 0.1467	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1593	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1187	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1871	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1243	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1011	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1970	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1349	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1622	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1611	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.2001	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.1678	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.1577	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1232	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.1072	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.0900	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1774	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1354	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1374	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1638	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.1402	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1311	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1033	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1148	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.1304	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1183	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.1581	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1141	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1559	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1735	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.1696	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1560	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.0482	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1442, Train Accuracy: 0.9412
Epoch 25 training time consumed: 144.54s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:8.17s
Training Epoch: 26 [256/10020]	Loss: 0.1107	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1485	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.0849	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1469	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.1685	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1337	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.1319	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1649	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1582	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1993	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1554	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1723	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1082	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1454	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1101	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.0957	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1227	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1897	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1295	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.1078	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1739	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1337	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1700	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1060	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1541	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1643	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1445	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1330	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1398	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.0907	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.2068	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1282	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.2280	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1186	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1555	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.1064	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1443, Train Accuracy: 0.9415
Epoch 26 training time consumed: 144.97s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:7.86s
Training Epoch: 27 [256/10020]	Loss: 0.1378	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.2060	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1492	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1295	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1103	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1122	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1839	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1600	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1461	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.0968	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1824	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1614	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.0894	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1592	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1429	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1264	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1523	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1447	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1382	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1125	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1231	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1232	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.0960	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.2120	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1021	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1058	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1519	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.1613	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1323	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1178	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.0724	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1394, Train Accuracy: 0.9436
Epoch 27 training time consumed: 144.84s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.18s
Training Epoch: 28 [256/10020]	Loss: 0.0929	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1234	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1002	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1134	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1019	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1344	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.0983	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.2193	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1483	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1104	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1302	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1145	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1741	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1727	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.0853	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1670	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.1001	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.0985	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.2042	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1462	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.2478	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1644	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1077	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.2123	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1366	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1213	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1160	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1267	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1226	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1722	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1534	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1270	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.2037	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1389, Train Accuracy: 0.9434
Epoch 28 training time consumed: 144.70s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0009, Accuracy: 0.9196, Time consumed:7.85s
Training Epoch: 29 [256/10020]	Loss: 0.1216	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.1747	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1761	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1576	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1270	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1514	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1256	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1602	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1693	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1187	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1008	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1078	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1479	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.1311	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.1741	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.1286	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1313	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1226	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.0988	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1480	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1297	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1701	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1764	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1134	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1612	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1315	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.1187	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1432, Train Accuracy: 0.9410
Epoch 29 training time consumed: 144.67s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0005, Accuracy: 0.9414, Time consumed:8.17s
Training Epoch: 30 [256/10020]	Loss: 0.1538	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1429	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.0948	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1003	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1529	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1257	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.1317	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1328	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1153	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1876	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1832	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1485	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1750	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1273	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1167	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1282	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1361	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1395	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.1367	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1099	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1366	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1205	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1070	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1588	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1184	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.0998	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1208	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1344	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.1859	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1109	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1600	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.0955	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1194	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.2134	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1354, Train Accuracy: 0.9439
Epoch 30 training time consumed: 144.52s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:7.82s
Training Epoch: 31 [256/10020]	Loss: 0.1018	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1876	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1487	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1117	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1773	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1323	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1076	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1269	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1678	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1229	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1402	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1649	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.0969	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.1790	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1173	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1396	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1261	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1198	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1858	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1109	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1444	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1067	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1305	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.0985	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1084	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.1061	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1220	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1676	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1328	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1149	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.0981	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1345, Train Accuracy: 0.9440
Epoch 31 training time consumed: 144.55s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:8.16s
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: 94.79166412353516
Retain Accuracy: 94.072265625
Zero-Retain Forget (ZRF): 0.7942689657211304
Membership Inference Attack (MIA): 0.3162878787878788
Forget vs Retain Membership Inference Attack (MIA): 0.45754716981132076
Forget vs Test Membership Inference Attack (MIA): 0.5094339622641509
Test vs Retain Membership Inference Attack (MIA): 0.513317191283293
Train vs Test Membership Inference Attack (MIA): 0.5314769975786925
Forget Set Accuracy (Df): 93.359375
Method Execution Time: 5896.02 seconds
