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

📌 S Retain class distribution for seed 7:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 7:
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: 0.8858	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.9341	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.7152	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.9571	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 1.4090	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 1.1365	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 1.0452	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 1.0447	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 0.8687	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 1.1196	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.6717	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 1.2564	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 0.6730	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 1.0690	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.8539	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.7744	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.8260	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.7777	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 0.7498	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.7544	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 0.7663	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.7093	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7526	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.7719	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.7399	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7054	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.8688	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.7869	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.7428	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.8266	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.7912	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.6984	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.6971	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 1.0708	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.7257	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.7017	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 1.0401	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.8458	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.7312	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6791	LR: 0.097500
Epoch 1 - Average Train Loss: 0.8582, Train Accuracy: 0.5072
Epoch 1 training time consumed: 333.24s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0756, Accuracy: 0.5550, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.8784	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.7565	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.8583	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7808	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.7897	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.7750	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7593	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.7069	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.7085	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.7599	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.7013	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.7337	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.8123	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6761	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.7285	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.7131	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.7475	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.7014	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.7040	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.7087	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.7206	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.6820	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.6903	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.6974	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.6816	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.7201	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.6513	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.7420	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.6933	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.7426	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7035	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.7180	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.8111	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.7373	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.7274	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.8255	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.6730	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.8260	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 1.0040	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7377, Train Accuracy: 0.5250
Epoch 2 training time consumed: 145.04s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0031, Accuracy: 0.5584, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-2-best.pth
Training Epoch: 3 [256/10020]	Loss: 0.8323	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 1.0480	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 1.0307	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.7426	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.6989	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.8320	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.8798	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.7751	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.7063	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.8397	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.7815	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.6904	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.7021	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.7243	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.6774	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.7005	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7071	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.6931	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.7024	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.6942	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.6900	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.6844	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.6941	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.6695	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.6787	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.7012	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6651	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.6756	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6875	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.7211	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6935	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.7196	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6905	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.6814	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.6442	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7310, Train Accuracy: 0.5409
Epoch 3 training time consumed: 144.69s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0040, Accuracy: 0.5467, Time consumed:8.20s
Training Epoch: 4 [256/10020]	Loss: 0.7105	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.7279	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.6694	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.6908	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6951	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.7110	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.7064	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6848	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6688	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6519	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.6992	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.7444	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6764	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.6837	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.6850	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6532	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6876	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.7061	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.7346	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6979	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.7112	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6667	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6865	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6658	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.7154	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6571	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.7314	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6960	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.7049	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.6716	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6902	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6898	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.7057	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.7059	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.7036	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6621	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6885	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.7111	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6922, Train Accuracy: 0.5611
Epoch 4 training time consumed: 144.55s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5942, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-4-best.pth
Training Epoch: 5 [256/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6838	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.6916	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.6845	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6778	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6951	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.6993	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.6739	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6828	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6724	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6777	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6977	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6650	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.6763	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6704	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.6536	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6661	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6788	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.7023	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6928	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6792	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6450	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6687	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.7170	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6811	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6895	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.6881	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6750	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6840	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.6795	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6669	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6847	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6686	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6983	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6906	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6596	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.7659	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6810, Train Accuracy: 0.5714
Epoch 5 training time consumed: 144.78s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5981, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-5-best.pth
Training Epoch: 6 [256/10020]	Loss: 0.6836	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6851	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6845	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6766	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6969	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6874	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.6718	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6551	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6667	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6674	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6781	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6677	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6691	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6902	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6972	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6565	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6876	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6712	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6836	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6869	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6762	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6803	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6727	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6865	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.6696	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6554	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6561	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6771	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.7006	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6574	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6648	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6671	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6078	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6759, Train Accuracy: 0.5789
Epoch 6 training time consumed: 145.70s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0031, Accuracy: 0.5603, Time consumed:8.00s
Training Epoch: 7 [256/10020]	Loss: 0.6931	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.6954	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.7016	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6911	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6525	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.7054	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6564	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6692	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6708	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.6891	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6672	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6537	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6511	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6867	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6619	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.6670	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6672	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.7184	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6593	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6836	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.7100	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.6600	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.6686	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.6623	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.6724	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6756	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6875	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6793	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6497	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6503	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6763	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.6869	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6603	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.6642	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.6530	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6743, Train Accuracy: 0.5900
Epoch 7 training time consumed: 146.18s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.6199, Time consumed:8.36s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-7-best.pth
Training Epoch: 8 [256/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6819	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.6816	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6575	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.6766	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6343	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6637	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6776	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6559	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.7045	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6641	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6552	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.6550	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.6515	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.6370	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.6033	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.6460	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.6047	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.6508	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.6438	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.6268	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.6539	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.6355	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.6501	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.6354	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.6524	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.6562	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.6458	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.5999	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.6306	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.6279	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.6160	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.6151	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.6007	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.6154	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.5785	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6480, Train Accuracy: 0.6305
Epoch 8 training time consumed: 145.64s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0046, Accuracy: 0.5855, Time consumed:8.21s
Training Epoch: 9 [256/10020]	Loss: 0.6846	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.6829	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.6629	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.6388	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.6647	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.6326	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.6388	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.6495	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.6059	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.6123	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.6819	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.6408	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.6229	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.6393	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.5968	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.6067	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.6372	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.6402	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.6021	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.6167	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.5899	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.6093	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.5645	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.6047	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.5869	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.6015	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.5818	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.5793	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.6502	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.6091	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.6136	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.6300	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.6297	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.5984	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.5929	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.6055	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.5686	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.6360	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6241, Train Accuracy: 0.6552
Epoch 9 training time consumed: 145.17s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0034, Accuracy: 0.5588, Time consumed:7.99s
Training Epoch: 10 [256/10020]	Loss: 0.6352	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.6327	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.5675	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.5682	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.5343	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.5430	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.5782	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.5401	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.5725	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.5942	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.5703	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.5946	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.5755	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.5967	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.6305	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.5493	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.5625	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.5671	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.5608	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.5335	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.5403	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.5357	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.5193	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.5879	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.5380	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.5684	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.5674	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.5497	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.5497	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.5378	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.5559	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.5229	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.4998	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.5514	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.5259	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.5251	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.5274	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.5072	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.5953	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.4439	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5589, Train Accuracy: 0.7151
Epoch 10 training time consumed: 145.31s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0027, Accuracy: 0.7027, Time consumed:8.21s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.5234	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.5046	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.6043	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.5472	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.4785	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.4790	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.5951	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.5168	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.5156	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.5138	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.5122	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.4895	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.4698	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.5345	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.4726	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.5003	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.4578	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.5300	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.4941	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.4543	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.4690	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.5323	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.4875	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.5132	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.5213	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.4733	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.4499	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.4996	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.5205	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.4200	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.4944	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.5037	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.4584	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.4518	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.5021	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.5067	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.4708	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.4588	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.4430	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.4092	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4963, Train Accuracy: 0.7636
Epoch 11 training time consumed: 146.39s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0039, Accuracy: 0.5540, Time consumed:8.11s
Training Epoch: 12 [256/10020]	Loss: 0.4854	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.4230	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.4645	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.4187	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.4832	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.4489	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.5001	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.5020	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.3979	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.4422	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.5147	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.4953	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.4342	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.4573	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.4374	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.4765	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.4465	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.4655	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.4720	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.4752	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.4114	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.4690	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.4934	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.4311	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.3931	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.4054	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.4293	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.4835	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.4470	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.4346	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.4357	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.4715	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.3722	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.3844	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.4059	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.4350	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.3913	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.4247	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.4317	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.4234	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4458, Train Accuracy: 0.7949
Epoch 12 training time consumed: 145.93s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0021, Accuracy: 0.7801, Time consumed:8.02s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-12-best.pth
Training Epoch: 13 [256/10020]	Loss: 0.4155	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.5085	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.3838	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.4737	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.4160	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.4550	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.4803	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.4663	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.4953	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.4217	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.4587	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.4623	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.4293	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.4336	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.4462	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.3990	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.4205	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.5176	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.4126	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.3878	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.4197	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.4429	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.4289	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.4325	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.4125	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.4806	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.4481	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.4455	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.4013	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.3933	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.4724	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.3843	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.3878	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.3289	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.3777	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.4441	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.3643	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.3370	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.4459	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.4384	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4290, Train Accuracy: 0.8045
Epoch 13 training time consumed: 146.96s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0026, Accuracy: 0.7215, Time consumed:8.08s
Training Epoch: 14 [256/10020]	Loss: 0.3863	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.3427	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.4013	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.4310	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.4505	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.4324	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.3848	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.4392	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.4058	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.4024	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.4537	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.3699	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.3734	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.3883	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.4068	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.4166	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.4188	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.3745	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.4126	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.4529	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.4209	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.4080	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.3780	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.4477	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.3710	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.3867	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.3411	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.3938	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.4673	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.3150	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.3466	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.3309	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.3630	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.3774	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.3683	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.5023	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.4724	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.3851	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.3916	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.4295	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4004, Train Accuracy: 0.8225
Epoch 14 training time consumed: 145.79s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0015, Accuracy: 0.8649, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-14-best.pth
Training Epoch: 15 [256/10020]	Loss: 0.3892	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.4028	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.4297	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.4100	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.3703	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.4397	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.4238	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.4460	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.3310	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.4106	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.3645	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.4094	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.3869	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.3680	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.3929	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.3400	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.3861	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.3800	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.3906	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.3725	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.3512	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.3595	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.3822	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.3364	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.4075	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.4051	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.3849	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.3982	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.3770	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.4212	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.3978	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.4062	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.3325	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.3469	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.3719	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.4351	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.3603	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.4172	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.3591	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.5418	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3876, Train Accuracy: 0.8247
Epoch 15 training time consumed: 146.42s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0018, Accuracy: 0.8208, Time consumed:8.12s
Training Epoch: 16 [256/10020]	Loss: 0.3494	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.3845	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.3977	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.4317	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.3772	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.3496	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.3660	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.4017	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.3819	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.3513	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.4044	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.3950	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.3977	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.3259	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.3123	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.3977	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.3385	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.3577	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.3495	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.3611	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.3777	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.2996	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.3636	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.3278	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.2684	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.2705	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.3439	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.4047	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.2781	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.3996	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.3672	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.3456	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.3353	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.3763	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.3524	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.2856	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.3496	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.3413	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.3286	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.1904	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3544, Train Accuracy: 0.8456
Epoch 16 training time consumed: 145.67s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0018, Accuracy: 0.8189, Time consumed:8.35s
Training Epoch: 17 [256/10020]	Loss: 0.3788	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.3708	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.4272	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.3135	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.3522	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.3194	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.3599	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.3605	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.3111	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.3180	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.3035	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.3613	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.3336	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.2435	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.3041	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.3586	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.3948	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.2856	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.3184	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.3214	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.3730	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.3302	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.3261	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.3029	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.3345	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.3468	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.3093	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.3493	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.3209	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.2967	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.3282	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.2656	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.3023	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.3016	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.3282	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.2718	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.2733	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.3436	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.2691	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.1871	LR: 0.020000
Epoch 17 - Average Train Loss: 0.3254, Train Accuracy: 0.8603
Epoch 17 training time consumed: 146.15s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0012, Accuracy: 0.8765, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-17-best.pth
Training Epoch: 18 [256/10020]	Loss: 0.3124	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.3481	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.3149	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.3395	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.2496	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.3432	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.3428	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.3059	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.2796	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.3415	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.3206	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.4176	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.3017	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.3617	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.3442	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.3186	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.3197	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.2778	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.2569	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.2992	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.2801	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.2862	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2548	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.2490	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.3222	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.3262	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.2582	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.2999	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.2958	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.2752	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.3011	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.2914	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.3105	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.2543	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.3131	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.2520	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.3099	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.2794	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.2944	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.2925	LR: 0.020000
Epoch 18 - Average Train Loss: 0.3038, Train Accuracy: 0.8715
Epoch 18 training time consumed: 146.01s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0013, Accuracy: 0.8722, Time consumed:8.00s
Training Epoch: 19 [256/10020]	Loss: 0.3064	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.3265	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.2875	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.3013	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.3372	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.2543	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.2341	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.3168	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2125	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.2133	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.1895	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.2771	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.3081	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.2711	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.2513	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.2534	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.3078	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.2892	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2566	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.2930	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.3169	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.2134	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2327	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.3318	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2251	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.2834	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.2867	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.3357	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.2595	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.2537	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.2384	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.2776	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2935	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2328	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.3199	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.2637	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.2814	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.2415	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.2957	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.4397	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2742, Train Accuracy: 0.8861
Epoch 19 training time consumed: 146.35s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0020, Accuracy: 0.8107, Time consumed:8.05s
Training Epoch: 20 [256/10020]	Loss: 0.2965	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.2882	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.3111	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.3366	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.2952	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.3130	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.2519	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.2249	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.3073	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.2407	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.2399	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.2332	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.2837	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.2491	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.2456	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.2385	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.2228	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.3199	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.2546	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.2079	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.2095	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.2114	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.2298	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.2173	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.2783	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.2250	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.2161	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.2492	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.2791	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.2289	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.2329	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1867	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.2232	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.2672	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.2096	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.2739	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.2125	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.2000	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.1932	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.4226	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2495, Train Accuracy: 0.8972
Epoch 20 training time consumed: 146.23s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0009, Accuracy: 0.9094, Time consumed:8.19s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.2270	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.2033	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.2322	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1694	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1911	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.2115	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.2526	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.2013	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.2457	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.2006	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1911	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.2116	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.2229	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1935	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.1898	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.2107	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.2018	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1600	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.2325	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.3014	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.2025	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.2439	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.2533	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.2192	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.2537	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.2356	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1891	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.2091	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.1856	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.2293	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.2274	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1793	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1761	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.2326	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.2295	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.2355	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.2726	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.2435	LR: 0.004000
Epoch 21 - Average Train Loss: 0.2153, Train Accuracy: 0.9128
Epoch 21 training time consumed: 145.34s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0008, Accuracy: 0.9196, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-21-best.pth
Training Epoch: 22 [256/10020]	Loss: 0.2529	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.2191	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.2100	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.2161	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.3047	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.2419	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.2124	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.1503	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.2993	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.2149	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.2006	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.2230	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.2135	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.2208	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.2088	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.1556	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.2606	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.2047	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1996	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1772	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1716	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1937	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1715	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1750	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1953	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.2542	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1518	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1951	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.2661	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.2242	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.2099	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1478	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1969	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1940	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.3469	LR: 0.004000
Epoch 22 - Average Train Loss: 0.2048, Train Accuracy: 0.9174
Epoch 22 training time consumed: 145.64s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0010, Accuracy: 0.9070, Time consumed:8.13s
Training Epoch: 23 [256/10020]	Loss: 0.1874	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1755	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1949	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.2025	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.2062	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.2206	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.2361	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.2196	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.2401	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.2306	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1931	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.2161	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.2530	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1919	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1877	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.2459	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.2181	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1810	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1713	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.2933	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1548	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.2079	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1720	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.1646	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.2053	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.2205	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1954	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.2458	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1725	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1892	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1868	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1862	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1913	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.2806	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.2188	LR: 0.004000
Epoch 23 - Average Train Loss: 0.2020, Train Accuracy: 0.9182
Epoch 23 training time consumed: 146.59s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9254, Time consumed:8.32s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-23-best.pth
Training Epoch: 24 [256/10020]	Loss: 0.1736	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.2191	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.1864	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1923	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1692	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1787	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.2287	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.2027	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.2123	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.2199	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.2198	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1447	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.2428	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1913	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1902	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.2001	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.2217	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1905	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1702	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1786	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1638	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.2072	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1667	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1473	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.2745	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.1613	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1996	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1891	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.1606	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1977	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.2414	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.2178	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1677	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1617	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.1704	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1906, Train Accuracy: 0.9247
Epoch 24 training time consumed: 145.78s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:8.08s
Training Epoch: 25 [256/10020]	Loss: 0.1799	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.1964	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1374	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1855	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1816	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.2089	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.2016	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1992	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1755	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1903	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1412	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.2250	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.1550	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.2095	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1178	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.2080	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.2327	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.1981	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1717	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1819	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1910	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1878	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1889	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.2213	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1510	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.2199	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1633	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.2417	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.2310	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1549	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.1403	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.2058	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1777	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.2570	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.2336	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.1090	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1885, Train Accuracy: 0.9237
Epoch 25 training time consumed: 145.28s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9264, Time consumed:8.27s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-25-best.pth
Training Epoch: 26 [256/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.1631	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1873	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.1498	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1235	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.2012	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.2054	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1715	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1903	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.2036	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1490	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1581	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.2138	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.2369	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1708	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1880	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.1752	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1611	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1910	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1738	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.2045	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1803	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1577	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1795	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1511	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.2064	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1954	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.1963	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.2384	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.2245	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1922	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1470	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1590	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.1848	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1792, Train Accuracy: 0.9254
Epoch 26 training time consumed: 146.32s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-26-best.pth
Training Epoch: 27 [256/10020]	Loss: 0.1902	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1351	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1666	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1712	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.2032	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1652	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1936	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1786	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1740	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1911	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.2153	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.2073	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.2829	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.2094	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.2034	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1989	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1868	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1953	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1697	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1969	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1383	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1091	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.2481	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1495	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.2227	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.2005	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1909	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1804	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1883	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1419	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.2488	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.2084	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1853	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1714	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.1264	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1850, Train Accuracy: 0.9242
Epoch 27 training time consumed: 146.03s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:7.93s
Training Epoch: 28 [256/10020]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.2002	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1110	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1606	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1315	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1872	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1797	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.2362	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1808	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1419	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.2073	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1524	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1354	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.1999	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1369	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.1848	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1646	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.2334	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1808	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1355	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1656	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1845	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1684	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1850	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1624	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1884	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1896	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1695	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1822	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1841	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.2819	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1721, Train Accuracy: 0.9312
Epoch 28 training time consumed: 146.21s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-28-best.pth
Training Epoch: 29 [256/10020]	Loss: 0.1315	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1714	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1611	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.2138	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1643	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1661	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1862	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1542	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1861	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1599	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1856	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1724	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.1849	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.1979	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1810	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1014	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.1824	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1360	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.2171	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1356	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.1618	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1520	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1766	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1895	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1702	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1559	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1602	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1784	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1382	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1862	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1880	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.0999	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1684, Train Accuracy: 0.9314
Epoch 29 training time consumed: 145.63s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9298, Time consumed:8.06s
Training Epoch: 30 [256/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1180	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.1556	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1871	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.2208	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1602	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.2320	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1303	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1543	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.0958	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1403	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1594	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1930	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1657	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1286	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.1417	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1767	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1603	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1584	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.2032	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.2035	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1277	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1719	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1904	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1382	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.1799	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1709	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1458	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.2103	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1733	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.2150	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1640, Train Accuracy: 0.9352
Epoch 30 training time consumed: 146.29s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_05h_43m_43s/ResNet18-MUCAC-seed7-ret50-30-best.pth
Training Epoch: 31 [256/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1797	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1937	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1640	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1206	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1624	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1946	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1252	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1823	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1863	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1730	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1389	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.2176	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1863	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1621	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.2050	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.2134	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1852	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1536	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1627	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1483	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1917	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1488	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1667	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.2200	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1567	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1376	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.2013	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.1892	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1852	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1492	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1585	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1577	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1032	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.2941	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1693, Train Accuracy: 0.9319
Epoch 31 training time consumed: 146.95s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0007, Accuracy: 0.9332, Time consumed:8.27s
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: 93.40023040771484
Retain Accuracy: 92.73003387451172
Zero-Retain Forget (ZRF): 0.7897065877914429
Membership Inference Attack (MIA): 0.3314393939393939
Forget vs Retain Membership Inference Attack (MIA): 0.5
Forget vs Test Membership Inference Attack (MIA): 0.5235849056603774
Test vs Retain Membership Inference Attack (MIA): 0.5254237288135594
Train vs Test Membership Inference Attack (MIA): 0.5423728813559322
Forget Set Accuracy (Df): 91.40625
Method Execution Time: 5927.88 seconds
