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

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

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

📊 Updated class distribution:
Retain set:
  Class 0: 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: 0.7237	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.7306	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.7046	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.7094	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 0.8392	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.7996	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 0.8526	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 0.7913	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 0.7149	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 0.9744	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.7332	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 0.7036	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 0.8022	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 0.9541	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 1.2902	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.9765	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.7587	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.7080	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 0.8134	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.7037	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 0.6909	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.7289	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.8605	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.6610	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.8529	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7096	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.9143	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.7209	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.7921	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.8840	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.9629	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 1.0873	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.7980	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.7233	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.7000	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.7302	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.6840	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.6883	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.6991	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6515	LR: 0.097500
Epoch 1 - Average Train Loss: 0.7988, Train Accuracy: 0.5251
Epoch 1 training time consumed: 336.82s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0399, Accuracy: 0.5550, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 1.1776	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.9126	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.9527	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7825	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.9552	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.8008	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7879	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.7045	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.8559	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.6931	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.7322	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.7264	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.7599	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.7865	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6991	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.7367	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.8156	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.7399	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.7899	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.7461	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.7155	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.7413	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.6948	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.6926	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.7054	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.7251	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.7403	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.6941	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.6922	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.6783	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.6984	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.6988	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.7149	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.6863	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.6834	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.6791	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.7015	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.6748	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.6782	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.6897	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7549, Train Accuracy: 0.5248
Epoch 2 training time consumed: 146.22s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0031, Accuracy: 0.5487, Time consumed:8.17s
Training Epoch: 3 [256/10020]	Loss: 0.7033	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.6736	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.6828	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.6598	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.6943	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.6301	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.6813	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.6592	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.7092	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.6933	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.6731	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.7721	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.6860	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7381	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.6750	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.6906	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.7107	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.7249	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.6636	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.7381	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.6445	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.7913	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.7416	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.6845	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.8643	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.8684	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.7820	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6933	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.7025	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.8617	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6953	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.7436	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6562	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.6890	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.7063	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7084, Train Accuracy: 0.5712
Epoch 3 training time consumed: 145.65s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5714, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-3-best.pth
Training Epoch: 4 [256/10020]	Loss: 0.6561	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.6613	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.7044	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.6905	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.6803	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6971	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6804	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6694	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6877	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.6664	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.6662	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.7131	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6665	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6424	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.7009	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.6731	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6685	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.6696	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6938	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6471	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6739	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6724	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.6773	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6948	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.6626	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6717	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.7215	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.6768	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6872	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.6724	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6830	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6820	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6833	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.6934	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6778, Train Accuracy: 0.5780
Epoch 4 training time consumed: 145.20s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0032, Accuracy: 0.5094, Time consumed:8.04s
Training Epoch: 5 [256/10020]	Loss: 0.6499	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6930	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.7134	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.6594	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6573	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.7194	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6739	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6596	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6831	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6298	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6577	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.7304	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6627	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.7199	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6750	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6777	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.6967	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6575	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6975	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6966	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6468	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6969	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.7074	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6633	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6921	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6526	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.6995	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.7185	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6647	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.7130	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6682	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6798	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6606	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.6970	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6804, Train Accuracy: 0.5881
Epoch 5 training time consumed: 145.50s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0032, Accuracy: 0.5588, Time consumed:8.04s
Training Epoch: 6 [256/10020]	Loss: 0.6902	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6737	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6771	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6937	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6667	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6713	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6897	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6513	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6438	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6930	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6542	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6604	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6753	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6347	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.6599	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6661	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6757	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6707	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6882	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6745	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6647	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6832	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6979	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6499	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6628	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6466	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6392	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6357	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.6312	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6339	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6945	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6456	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.5825	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6842	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6566	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6227	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6470	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6625, Train Accuracy: 0.6104
Epoch 6 training time consumed: 145.48s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.6247, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-6-best.pth
Training Epoch: 7 [256/10020]	Loss: 0.6154	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.6152	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.6464	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6479	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6756	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6283	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6354	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.6443	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6337	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6756	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6457	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.6471	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6382	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6421	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6159	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6344	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6605	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6549	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.5958	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6284	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.5853	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6345	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6038	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.6239	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.5780	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.6456	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.5766	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.5510	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6061	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6196	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6603	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6236	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6116	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6261	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6228	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.5950	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6073	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.6131	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.4644	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6262, Train Accuracy: 0.6544
Epoch 7 training time consumed: 145.32s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.6087, Time consumed:8.01s
Training Epoch: 8 [256/10020]	Loss: 0.6777	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6873	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.5315	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6054	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.5984	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6738	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6247	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6276	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6272	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.6112	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6081	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.5877	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6550	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6187	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.5516	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.6189	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.5710	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.5767	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.5933	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.6503	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.5801	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.5293	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.5496	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.5341	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.5856	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.5391	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.5161	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.5421	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.5847	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.5022	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.5136	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.5489	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.5313	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.5587	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.5347	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.5459	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.4761	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.5328	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.4982	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.3670	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5762, Train Accuracy: 0.7040
Epoch 8 training time consumed: 145.27s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0227, Accuracy: 0.4475, Time consumed:8.27s
Training Epoch: 9 [256/10020]	Loss: 0.5564	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.5400	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.5337	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.5110	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.5237	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.5441	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.5725	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.5289	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.5232	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.4705	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.5190	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.5121	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.5445	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.5878	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.4944	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.4579	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.6442	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.4590	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.5651	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.5427	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.5364	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.5161	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.4768	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.4754	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.4841	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.5189	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.4664	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.4523	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.5292	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.5066	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.4637	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.5076	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.4577	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.5307	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.4974	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.4562	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.5160	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.4750	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.4199	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.4684	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5105, Train Accuracy: 0.7567
Epoch 9 training time consumed: 145.53s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0032, Accuracy: 0.5850, Time consumed:8.00s
Training Epoch: 10 [256/10020]	Loss: 0.4484	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.4165	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.4252	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.4818	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.4686	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.4365	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.4106	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.4598	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.4215	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.4500	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.4482	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.4434	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.4314	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.3576	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.3881	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.3551	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.4307	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.4000	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.3437	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.3927	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.3849	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.3824	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.3905	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.4084	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.3967	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.3449	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.4128	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.4003	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.4130	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.4642	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.4305	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.3542	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.4679	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.3665	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.3976	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.3852	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.3711	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.4107	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.3918	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.4152	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4099, Train Accuracy: 0.8165
Epoch 10 training time consumed: 145.54s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0015, Accuracy: 0.8538, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.3625	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.3364	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.3852	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.3461	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.3604	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.3836	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.3287	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.3652	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.3403	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.3522	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.3916	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.3474	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.3819	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.3255	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.3065	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.3623	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.3490	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.3716	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.3871	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.3478	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.3069	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.3576	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.3188	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.3360	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.3624	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.4349	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.4071	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.3802	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.3119	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.4266	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.3491	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.3916	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.3679	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.3780	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.3341	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.3506	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.3533	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.3399	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.3901	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.4174	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3599, Train Accuracy: 0.8393
Epoch 11 training time consumed: 145.71s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0017, Accuracy: 0.8339, Time consumed:7.97s
Training Epoch: 12 [256/10020]	Loss: 0.3271	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.2874	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.3194	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.3259	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.3280	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.3250	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.3596	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.2841	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.3561	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.3434	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.3538	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.3122	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.3152	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.3584	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.3376	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.3690	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.3126	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.3196	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.3330	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.2126	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.3532	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.3431	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.2714	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.3170	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.2868	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.2732	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.3016	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.3147	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.3341	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.3268	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.3568	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.3275	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.3288	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.2930	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.3031	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.2717	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.3775	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.3464	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.3326	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.4230	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3219, Train Accuracy: 0.8668
Epoch 12 training time consumed: 146.16s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0019, Accuracy: 0.8136, Time consumed:8.10s
Training Epoch: 13 [256/10020]	Loss: 0.2866	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.3376	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.3061	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.2828	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.3857	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.3230	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.3630	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.3499	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.2958	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.3096	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.3006	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.2778	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.3061	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.3241	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.3123	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.3073	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.3985	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.3197	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.3354	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.2841	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.3637	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.2662	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.2712	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.3105	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.3165	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.2973	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.2692	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.3202	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.3458	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.3006	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.2621	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.2582	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.3045	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.2810	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.3041	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.3004	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.3246	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.2764	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.2207	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.3424	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3078, Train Accuracy: 0.8697
Epoch 13 training time consumed: 146.73s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0011, Accuracy: 0.8847, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-13-best.pth
Training Epoch: 14 [256/10020]	Loss: 0.2731	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.2296	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.2986	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.3027	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.3443	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.2936	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.2451	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.2273	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.2904	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.2957	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.3073	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.2686	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.2725	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.2472	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.2805	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.2304	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.2501	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.2411	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.2817	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.2776	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.2341	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.2970	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.2523	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.2908	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.2147	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.2736	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.2314	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.2986	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.3514	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.2186	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.2380	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.2448	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.3115	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.3267	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.2675	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.2617	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.2637	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.2685	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.3012	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.2641	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2719, Train Accuracy: 0.8846
Epoch 14 training time consumed: 145.43s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0010, Accuracy: 0.8964, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-14-best.pth
Training Epoch: 15 [256/10020]	Loss: 0.2805	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.3488	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.2636	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.2973	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.3277	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.3042	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.3066	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.2604	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.2616	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.1877	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.2157	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.2775	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.2410	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.3223	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.2718	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.2384	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.1979	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.2359	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.2803	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.2582	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.2532	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.2110	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.2206	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.3004	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.2406	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.2439	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.1928	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.2185	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.2078	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.2567	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.2422	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.2606	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.2272	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.2018	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.2547	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.1824	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.2388	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.2110	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.2468	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.0957	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2504, Train Accuracy: 0.8958
Epoch 15 training time consumed: 145.77s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0016, Accuracy: 0.8939, Time consumed:8.30s
Training Epoch: 16 [256/10020]	Loss: 0.2552	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.2329	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.2374	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.2550	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.1864	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.2208	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.1965	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.2439	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.1918	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.2667	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.2584	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.2478	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.2155	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.2316	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.1716	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.2501	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.1909	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.2853	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.2303	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.2391	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.1912	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.2408	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.2648	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.2378	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.1686	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.1768	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.1794	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.1968	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.3104	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.2153	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.2392	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.2669	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.2249	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.1895	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.1955	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.2186	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.2409	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.1587	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.2224	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.2644	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2244, Train Accuracy: 0.9088
Epoch 16 training time consumed: 145.24s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0012, Accuracy: 0.8867, Time consumed:8.09s
Training Epoch: 17 [256/10020]	Loss: 0.2659	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.1642	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.2438	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.2582	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.1911	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.2502	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.1986	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.2291	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.1905	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.2166	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.2280	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.2307	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.1915	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.2371	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.1588	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.1796	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.2416	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.2043	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.2136	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.2383	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.2770	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.2342	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.2097	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.2118	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.2265	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.2797	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.1453	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.2638	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.2048	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.2496	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.2213	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.2383	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.2234	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.2475	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.2259	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.2354	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.2243	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.2341	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.2138	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.1751	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2228, Train Accuracy: 0.9089
Epoch 17 training time consumed: 144.89s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0015, Accuracy: 0.8722, Time consumed:7.98s
Training Epoch: 18 [256/10020]	Loss: 0.1520	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.2726	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.2437	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.2787	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.2406	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.2156	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.2086	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.2108	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.2113	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.2284	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.2268	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.2374	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.2572	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.2183	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.1638	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.1915	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.1405	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.1598	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.2189	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.1576	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.2049	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.1767	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2445	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.1870	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.1974	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.1874	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.1822	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.1959	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.1827	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.2243	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.2314	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.1891	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.2316	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.1464	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.2129	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.2328	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.1568	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.1716	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.2053	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.2237	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2051, Train Accuracy: 0.9167
Epoch 18 training time consumed: 145.38s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0009, Accuracy: 0.9206, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-18-best.pth
Training Epoch: 19 [256/10020]	Loss: 0.2890	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.1904	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.2114	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.2385	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.1921	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.1951	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.2014	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.1836	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2228	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.1822	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.2302	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.2147	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.1336	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.1681	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.2326	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.1765	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.1423	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.1964	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2248	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.1842	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.1375	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.1734	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2111	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.1683	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.1966	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.1663	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.2786	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.2056	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.2153	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.1735	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.1807	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.2704	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2195	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2139	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.1339	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.1904	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.1713	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.1496	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.2152	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.1610	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1968, Train Accuracy: 0.9188
Epoch 19 training time consumed: 145.12s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0013, Accuracy: 0.8770, Time consumed:8.06s
Training Epoch: 20 [256/10020]	Loss: 0.2007	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.1986	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.1642	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.2232	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.1527	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.1701	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.0980	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.1846	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.1504	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.1404	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.1900	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.1985	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.1577	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.1773	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.1520	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.2266	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.1617	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.1730	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.1613	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1575	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.1707	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.1408	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.1933	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.2270	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.1594	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1757	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.1771	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.2000	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1467	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1736	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.1241	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.0787	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1706, Train Accuracy: 0.9296
Epoch 20 training time consumed: 145.45s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9370, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1873	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.2075	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.2115	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.1316	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1251	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.1703	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.1126	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.1434	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.1656	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.1747	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1319	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1753	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.1561	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1527	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.1095	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1575	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.1591	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.1436	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.2254	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1570	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1337	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.1710	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1831	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.2274	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1706	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.1516	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1429	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1860	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.1284	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.1195	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.1756	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.1421	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1588, Train Accuracy: 0.9368
Epoch 21 training time consumed: 145.64s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:8.36s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-21-best.pth
Training Epoch: 22 [256/10020]	Loss: 0.1508	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.1853	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1588	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1087	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.1594	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1534	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.1458	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1243	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1425	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.1640	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.1563	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1292	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1562	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.1707	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1097	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.1391	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1545	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1845	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1406	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1339	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1473	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1318	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1644	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1646	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.2124	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1997	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.1360	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.1623	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.2005	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1630	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1190	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1346	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.0833	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1545, Train Accuracy: 0.9363
Epoch 22 training time consumed: 145.84s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9424, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-22-best.pth
Training Epoch: 23 [256/10020]	Loss: 0.1992	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1166	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.2016	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.2176	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.1079	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.1066	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1738	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1666	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.1423	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.2038	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1565	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.1697	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1466	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1701	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1335	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1312	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1628	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.1197	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.0988	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.1729	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.1385	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1458	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1899	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1276	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1651	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1501	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.1890	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1526, Train Accuracy: 0.9382
Epoch 23 training time consumed: 145.67s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9453, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-23-best.pth
Training Epoch: 24 [256/10020]	Loss: 0.1040	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.2087	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1616	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1390	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.1556	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1426	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1451	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1424	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1188	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1378	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1858	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1600	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.2122	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1037	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1147	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1154	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1124	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1356	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1322	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.1306	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1269	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1302	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.1293	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.1833	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1654	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1727	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.1745	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1458, Train Accuracy: 0.9396
Epoch 24 training time consumed: 147.16s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0008, Accuracy: 0.9274, Time consumed:8.15s
Training Epoch: 25 [256/10020]	Loss: 0.1183	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.2305	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1224	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1514	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1253	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1391	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1219	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1339	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1427	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1770	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.1806	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.0894	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.1340	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1388	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.2093	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1622	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1845	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.1478	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.0995	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1164	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1156	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.1202	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1169	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.2346	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1230	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1191	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.1742	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.0473	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1466, Train Accuracy: 0.9400
Epoch 25 training time consumed: 145.64s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:8.00s
Training Epoch: 26 [256/10020]	Loss: 0.1041	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1083	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1302	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.2000	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1121	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.1524	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1069	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1397	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1754	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1934	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1057	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.2143	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1651	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.1618	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1559	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1761	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1744	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.0872	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1238	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1063	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1127	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1618	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1253	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1948	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1825	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1037	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1285	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.1296	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1724	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.1417	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1074	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1285	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.2605	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1430, Train Accuracy: 0.9436
Epoch 26 training time consumed: 145.67s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:8.18s
Training Epoch: 27 [256/10020]	Loss: 0.1541	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.1942	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1535	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1151	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1151	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1480	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1084	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1187	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1885	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1323	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1177	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1337	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1951	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.2092	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1537	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1297	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.1013	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1283	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1368	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1426	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1317	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1712	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1718	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1213	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1084	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1111	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1325	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.1351	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1053	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1288	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1244	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.1400	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1661	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.0999	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.1204	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1401, Train Accuracy: 0.9444
Epoch 27 training time consumed: 145.29s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9370, Time consumed:8.14s
Training Epoch: 28 [256/10020]	Loss: 0.1114	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1358	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1800	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1159	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1704	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1201	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.1350	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1112	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1432	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1221	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1396	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1136	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1278	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1219	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1796	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1372	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.1874	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1848	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1472	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.1735	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1509	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1370	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1499	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1487	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1061	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1358	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1812	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1202	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1109	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.1251	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1423, Train Accuracy: 0.9414
Epoch 28 training time consumed: 145.59s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9143, Time consumed:7.98s
Training Epoch: 29 [256/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1238	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1311	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.1317	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1488	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1173	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1938	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1238	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1543	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1675	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1819	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1666	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1483	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1462	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.1339	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.1112	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1489	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1009	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1220	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.0985	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1229	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.0813	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.1592	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1611	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1312	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1536	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1149	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1521	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1135	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.0820	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1408, Train Accuracy: 0.9444
Epoch 29 training time consumed: 145.18s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0005, Accuracy: 0.9467, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_10h_40m_46s/ResNet18-MUCAC-seed10-ret50-29-best.pth
Training Epoch: 30 [256/10020]	Loss: 0.1808	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.1092	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1250	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1274	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1399	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.1776	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1568	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.0833	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.0870	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1317	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1453	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1013	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1294	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1782	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1043	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1562	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.0886	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1135	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1151	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.0831	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.0750	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1067	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1365	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1292	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1481	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1717	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1523	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1184	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1330	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.0892	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1206	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1606	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1425	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1933	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1749	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.3554	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1331, Train Accuracy: 0.9461
Epoch 30 training time consumed: 145.28s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0008, Accuracy: 0.9269, Time consumed:8.07s
Training Epoch: 31 [256/10020]	Loss: 0.1491	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1628	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1239	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1126	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1064	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1050	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1486	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1584	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1072	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1248	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1370	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.1559	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.1307	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1444	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1264	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1394	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1354	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1113	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1303	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.1776	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.0901	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1422	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1190	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1137	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1848	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1223	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.1402	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.1339	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1322	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1724	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1560	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1221	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.0794	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1356, Train Accuracy: 0.9437
Epoch 31 training time consumed: 145.01s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:8.12s
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: 93.96446228027344
Retain Accuracy: 94.96961975097656
Zero-Retain Forget (ZRF): 0.7369562983512878
Membership Inference Attack (MIA): 0.3125
Forget vs Retain Membership Inference Attack (MIA): 0.5377358490566038
Forget vs Test Membership Inference Attack (MIA): 0.5330188679245284
Test vs Retain Membership Inference Attack (MIA): 0.5314769975786925
Train vs Test Membership Inference Attack (MIA): 0.5363196125907991
Forget Set Accuracy (Df): 93.88021087646484
Method Execution Time: 5924.12 seconds
