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

📌 S Retain class distribution for seed 5:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 5:
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: 0.7908	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.7788	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.6963	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.9421	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 1.0181	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.7122	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 1.0718	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 1.0330	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 1.2994	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 1.1060	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 1.0866	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 0.8780	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 0.9941	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 0.7758	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.9417	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.6998	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.8786	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.7333	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 0.7975	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.7504	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 1.0862	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.7953	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7899	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.8268	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.7478	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7788	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.7168	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.8252	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.8352	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.7277	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.7384	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.8300	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.7057	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.8517	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.8086	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.8620	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.7074	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.7369	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.7824	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.8004	LR: 0.097500
Epoch 1 - Average Train Loss: 0.8495, Train Accuracy: 0.5079
Epoch 1 training time consumed: 411.82s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0049, Accuracy: 0.5496, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.6983	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.6807	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.7704	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7009	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.7599	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.6981	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7754	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.7131	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.7529	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.7326	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.6785	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.7451	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.7401	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.7256	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6873	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.6757	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.6807	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.7232	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.7555	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.6844	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.7129	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.6883	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.7209	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.7008	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.7231	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.7112	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.6686	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.6743	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.7038	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.7345	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7381	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.6885	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.7052	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.6883	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.6703	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.7113	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.6460	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7085, Train Accuracy: 0.5427
Epoch 2 training time consumed: 145.64s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0036, Accuracy: 0.5366, Time consumed:7.99s
Training Epoch: 3 [256/10020]	Loss: 0.6672	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.7339	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.7086	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.7254	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.6721	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.6754	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.6940	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.7037	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.6882	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.6655	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.6866	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.6711	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.6740	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7313	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.7070	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.7174	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.7239	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.6709	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.6963	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.6934	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.6808	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.6838	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.6989	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.6564	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6825	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.6962	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.7138	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6711	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.6658	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6390	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.6501	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6669	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.6326	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6856, Train Accuracy: 0.5747
Epoch 3 training time consumed: 144.87s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5661, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-3-best.pth
Training Epoch: 4 [256/10020]	Loss: 0.6640	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.7327	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.6728	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.7800	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.7465	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.6864	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6709	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6996	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.7182	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6809	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.6813	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6906	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.7192	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.7290	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6888	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6915	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.7993	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.7463	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.7028	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.7692	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6808	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6696	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6676	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6923	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.6365	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.7031	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.6419	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6954	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.7002	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.6959	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6729	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6536	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.6962	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6820	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6797	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6796	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6680	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.7270	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6968, Train Accuracy: 0.5715
Epoch 4 training time consumed: 145.06s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5651, Time consumed:7.92s
Training Epoch: 5 [256/10020]	Loss: 0.6839	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6765	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.7015	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.7638	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.7735	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.7775	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.7073	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.7223	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6818	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.7005	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.7019	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.7154	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6420	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.6825	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.6853	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6855	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6514	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.7033	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.7191	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6654	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.7019	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6705	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6760	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6716	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6881	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6915	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.7162	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6582	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6536	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6667	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6600	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6429	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6795	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6588	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.7094	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6888, Train Accuracy: 0.5753
Epoch 5 training time consumed: 145.28s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0031, Accuracy: 0.5550, Time consumed:7.95s
Training Epoch: 6 [256/10020]	Loss: 0.6736	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6777	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6574	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6907	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.7190	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6664	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.6708	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6867	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6710	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6695	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6545	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6556	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6632	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.7140	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6659	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6431	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6875	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6591	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6615	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6723	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6765	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6768	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6613	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6923	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6371	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6535	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.6611	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6556	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6878	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6600	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.6162	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6665	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6798	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6498	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6833	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6692, Train Accuracy: 0.5980
Epoch 6 training time consumed: 144.33s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.6082, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-6-best.pth
Training Epoch: 7 [256/10020]	Loss: 0.6425	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.7066	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.6983	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6848	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6788	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6789	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6528	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.6891	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6855	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6767	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.6748	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6735	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6420	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6515	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6592	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6463	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6453	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.6239	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6706	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.6765	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6578	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6459	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.6361	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.7230	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.6542	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.6389	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6659	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6434	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6740	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6595	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6411	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6321	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.6183	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.5916	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6633, Train Accuracy: 0.6119
Epoch 7 training time consumed: 144.61s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0032, Accuracy: 0.5603, Time consumed:7.85s
Training Epoch: 8 [256/10020]	Loss: 0.6449	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6428	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.6418	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6480	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.6488	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6471	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6654	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6533	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6609	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.6124	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6480	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.6429	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6212	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6290	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.6352	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.7004	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.6305	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.6807	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.6608	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.6391	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.6212	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.6447	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.6548	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.5887	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.6541	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.6241	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.5986	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.6361	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.5801	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.6164	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.5743	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.5911	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.6036	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.6239	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.5858	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.6309	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.5605	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.5609	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.6392	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.6356	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6293, Train Accuracy: 0.6570
Epoch 8 training time consumed: 144.04s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0027, Accuracy: 0.6872, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-8-best.pth
Training Epoch: 9 [256/10020]	Loss: 0.6428	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.6626	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.5951	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.6606	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.6024	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.5859	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.6921	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.6069	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.6040	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.6071	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.5796	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.5932	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.5603	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.5554	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.6155	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.6094	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.6063	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.6153	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.5928	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.6254	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.6442	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.5949	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.6290	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.5900	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.5915	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.5750	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.5689	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.5275	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.5885	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.5551	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.4667	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.5244	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.4936	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.5437	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.5630	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.5474	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.4451	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.5181	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.4849	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.5696	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5811, Train Accuracy: 0.6976
Epoch 9 training time consumed: 144.55s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0054, Accuracy: 0.5705, Time consumed:7.96s
Training Epoch: 10 [256/10020]	Loss: 0.7814	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.6410	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.5535	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.5442	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.4902	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.5963	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.5071	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.4642	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.4804	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.4605	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.4031	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.4829	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.4630	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.4834	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.4510	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.4431	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.4483	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.3915	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.4066	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.4506	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.4530	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.4386	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.4052	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.4278	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.3837	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.3586	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.4000	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.3859	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.4583	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.3979	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.4270	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.4067	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.3882	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.3673	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.4002	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.4393	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.3641	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.3646	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.3663	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.3435	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4503, Train Accuracy: 0.7941
Epoch 10 training time consumed: 144.49s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0018, Accuracy: 0.8203, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.3890	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.3928	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.3694	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.4482	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.4169	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.3302	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.3892	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.4293	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.3731	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.2849	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.2964	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.3668	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.3462	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.3152	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.3105	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.3408	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.3145	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.3138	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.3505	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.3161	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.3296	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.2637	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.2887	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.3292	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.4082	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.3026	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.3493	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.2862	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.3407	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.3239	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.3570	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.3661	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.3603	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.3202	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.3186	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.3491	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.3392	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.2316	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.3157	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.1796	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3398, Train Accuracy: 0.8528
Epoch 11 training time consumed: 145.79s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0015, Accuracy: 0.8562, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-11-best.pth
Training Epoch: 12 [256/10020]	Loss: 0.3167	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.3766	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.3430	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.3557	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.3826	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.3014	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.3466	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.3070	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.3467	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.3787	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.3840	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.2623	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.2802	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.3380	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.3373	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.3124	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.3776	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.3000	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.2291	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.3336	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.2649	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.3586	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.2692	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.3135	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.2830	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.2931	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.2584	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.2817	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.2547	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.3573	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.2681	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.3114	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.2446	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.2325	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.2912	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.3043	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.3224	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.2450	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.2176	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.1972	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3068, Train Accuracy: 0.8688
Epoch 12 training time consumed: 144.77s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0011, Accuracy: 0.9075, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-12-best.pth
Training Epoch: 13 [256/10020]	Loss: 0.3063	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.2758	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.3049	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.2478	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.3133	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.2622	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.3131	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.2472	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.2322	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.3488	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.2401	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.2881	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.2875	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.3261	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.2643	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.2455	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.2782	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.2973	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.3486	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.2820	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.2724	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.2705	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.2255	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.2402	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.2416	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.2712	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.2416	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.2889	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.2605	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.2406	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.3060	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.3354	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.2685	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.2366	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.2564	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.2071	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.2694	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.3401	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.2953	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.1971	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2761, Train Accuracy: 0.8862
Epoch 13 training time consumed: 145.52s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0009, Accuracy: 0.9123, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-13-best.pth
Training Epoch: 14 [256/10020]	Loss: 0.2504	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.2045	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.2501	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.2824	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.2597	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.2189	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.2745	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.2129	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.2758	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.2785	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.2658	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.2075	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.2688	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.2628	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.2805	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.2468	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.2231	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.3140	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.2690	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.1750	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.2441	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.2580	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.2353	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.2332	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.2310	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.1755	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.2542	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.2513	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.2188	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.2657	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.2023	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.2348	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.2632	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.2111	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.2681	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.2173	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.2415	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.2481	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.1942	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.2945	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2430, Train Accuracy: 0.9029
Epoch 14 training time consumed: 145.04s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0009, Accuracy: 0.9201, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-14-best.pth
Training Epoch: 15 [256/10020]	Loss: 0.2287	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.1742	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.2463	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.2582	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.2191	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.2473	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.3034	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.2268	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.2253	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.2558	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.2638	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.2472	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.2889	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.1975	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.1802	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.2070	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.2844	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.1631	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.1735	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.1606	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.2175	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.2131	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.2391	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.2088	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.2260	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.2460	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.1993	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.2138	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.2490	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.1745	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.2295	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.2264	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.2738	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.1640	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.2189	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.1998	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.2221	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.2776	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.2191	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.2844	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2251, Train Accuracy: 0.9051
Epoch 15 training time consumed: 145.21s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0017, Accuracy: 0.8232, Time consumed:8.21s
Training Epoch: 16 [256/10020]	Loss: 0.2783	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.2449	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.2837	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.2890	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.2202	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.2340	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.2102	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.2506	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.2114	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.2786	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.2760	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.2258	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.2129	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.1847	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.1695	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.2225	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.2343	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.1943	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.1882	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.2724	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.2542	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.1826	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.2073	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.2250	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.2746	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.2028	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.2285	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.1675	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.2383	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.2165	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.1674	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.1854	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.2024	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.2665	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.2079	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.1530	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.2396	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.1935	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.1837	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.1183	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2221, Train Accuracy: 0.9079
Epoch 16 training time consumed: 144.81s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0015, Accuracy: 0.8494, Time consumed:7.87s
Training Epoch: 17 [256/10020]	Loss: 0.1397	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.2499	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.2060	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.2484	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.1872	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.1686	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.2229	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.2566	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.2481	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.2377	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.2372	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.1922	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.1911	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.2830	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.1715	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.2256	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.1946	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.1857	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.2142	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.2058	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.2071	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.2276	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.2109	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.2168	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.2255	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.2021	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.1682	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.2246	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.2837	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.1405	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.1530	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.1864	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.1847	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.1884	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.2354	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.2098	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.2739	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.1901	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.1477	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.1096	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2084, Train Accuracy: 0.9109
Epoch 17 training time consumed: 144.86s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0008, Accuracy: 0.9259, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-17-best.pth
Training Epoch: 18 [256/10020]	Loss: 0.2237	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.1589	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.2425	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.1423	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.1806	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.1752	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.1533	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.1885	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.2163	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.1613	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.2165	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.1577	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.1766	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.2318	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.1772	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.1925	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.1702	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.1699	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.1811	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.2211	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.2273	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.2102	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2074	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.2163	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.2668	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.1850	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.1731	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.1923	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.1673	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.1886	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.1992	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.1888	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.2136	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.1898	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.2080	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.1617	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.1780	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.1652	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.1334	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.4075	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1908, Train Accuracy: 0.9190
Epoch 18 training time consumed: 145.87s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0009, Accuracy: 0.9153, Time consumed:7.92s
Training Epoch: 19 [256/10020]	Loss: 0.1465	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.2610	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.1844	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.2071	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.2268	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.1902	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.1924	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.1547	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.1573	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.1658	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.1813	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.2291	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.1627	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.2349	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.1957	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.2452	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.1885	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.2030	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2003	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.1883	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.1781	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.1859	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.1715	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.1843	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2222	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.1658	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.1828	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.1681	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.1768	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.1802	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.1670	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.1637	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2119	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.1904	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.2184	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.1343	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.1959	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.1566	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.1791	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.1214	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1882, Train Accuracy: 0.9224
Epoch 19 training time consumed: 148.67s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0010, Accuracy: 0.9153, Time consumed:8.00s
Training Epoch: 20 [256/10020]	Loss: 0.1628	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.1948	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.1103	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.1534	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.1621	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.1591	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.1351	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.1796	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.1812	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.1393	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.1598	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.1112	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.1425	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.2265	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.1749	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.1930	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.0949	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.1526	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.1342	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.1098	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.1315	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1674	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.2000	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.1899	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.1380	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.1683	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.1657	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1624	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.1516	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.1918	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1804	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.1576	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1487	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.1666	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.0722	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1580, Train Accuracy: 0.9342
Epoch 20 training time consumed: 146.58s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1796	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.1236	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.2146	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.1706	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.1436	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.1128	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.1286	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.1396	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1359	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1716	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.1171	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1734	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.1673	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1335	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.1342	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.1826	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.1191	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1585	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.1410	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1163	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.1446	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.2167	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1625	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1246	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.1394	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.1155	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.1009	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1461, Train Accuracy: 0.9387
Epoch 21 training time consumed: 146.41s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:8.04s
Training Epoch: 22 [256/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1297	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.1744	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1250	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.0965	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1230	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.1133	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1296	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.1059	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.1378	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1700	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1920	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.1411	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.1912	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1172	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.1761	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1177	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1571	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1345	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1503	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1813	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1638	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1144	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1606	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.1397	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.1412	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1607	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1104	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.0824	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1445, Train Accuracy: 0.9385
Epoch 22 training time consumed: 146.30s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0005, Accuracy: 0.9404, Time consumed:7.89s
Training Epoch: 23 [256/10020]	Loss: 0.1365	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1136	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1481	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.1546	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.1349	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.1613	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.1081	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1710	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.1518	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.1081	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1316	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1106	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.1824	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1612	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1419	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.2029	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1425	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1833	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1430	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.1420	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1758	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.0933	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.1018	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1424	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1306	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1182	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1143	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1395	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.0450	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1415, Train Accuracy: 0.9405
Epoch 23 training time consumed: 145.51s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0005, Accuracy: 0.9433, Time consumed:8.00s
Training Epoch: 24 [256/10020]	Loss: 0.1874	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.0983	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.2208	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.2021	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1155	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.1750	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1068	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1174	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1107	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1094	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.0957	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1279	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1112	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.2037	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.1121	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1483	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1920	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1218	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1395	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1097	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1412	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1711	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.2056	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1325	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1644	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1113	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.1096	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1032	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.1262	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1570	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1572	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.0468	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1419, Train Accuracy: 0.9401
Epoch 24 training time consumed: 145.30s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0005, Accuracy: 0.9458, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-24-best.pth
Training Epoch: 25 [256/10020]	Loss: 0.1308	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.1432	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1171	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1552	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1266	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1181	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1240	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1297	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1675	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1263	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1108	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.1220	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.0910	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.1463	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.0979	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.1468	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.1294	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1229	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1403	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1236	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1047	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.1281	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1335	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.1249	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1303	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.1036	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1790	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1100	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.1428	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1437	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.3228	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1345, Train Accuracy: 0.9442
Epoch 25 training time consumed: 146.33s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0005, Accuracy: 0.9409, Time consumed:7.96s
Training Epoch: 26 [256/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1376	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.0871	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.0891	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.0921	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1158	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1797	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1239	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1322	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1061	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1243	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.1215	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.1171	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1549	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1782	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1165	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.1982	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1368	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1589	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1234	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1109	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1015	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1480	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1562	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.0939	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1369	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.1273	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1083	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1648	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1506	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1705	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.0234	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1350, Train Accuracy: 0.9440
Epoch 26 training time consumed: 145.77s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0005, Accuracy: 0.9477, Time consumed:8.24s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_02h_25m_17s/ResNet18-MUCAC-seed5-ret50-26-best.pth
Training Epoch: 27 [256/10020]	Loss: 0.1346	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.1390	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1296	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1121	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1601	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1044	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1150	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1304	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1089	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1278	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1273	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1113	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.1503	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1649	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1281	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.1433	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1501	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1154	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.0971	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1329	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1115	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1227	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1272	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1062	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1491	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1155	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.1510	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1557	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1836	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.0903	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1310	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.2348	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1344	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.1617	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1346, Train Accuracy: 0.9443
Epoch 27 training time consumed: 146.52s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9443, Time consumed:8.21s
Training Epoch: 28 [256/10020]	Loss: 0.1838	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1565	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1063	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1868	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1175	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1853	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.1187	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.0826	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1454	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.0753	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1196	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1488	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1045	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1562	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.0872	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1198	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.1030	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1135	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1609	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1721	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1195	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1507	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1034	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1292	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1505	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1486	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1439	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1289	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1097	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1605	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.0875	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1361, Train Accuracy: 0.9431
Epoch 28 training time consumed: 145.76s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0005, Accuracy: 0.9429, Time consumed:7.97s
Training Epoch: 29 [256/10020]	Loss: 0.1007	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1647	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1267	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.1350	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1551	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1143	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1007	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1506	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1258	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.0991	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1040	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1723	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1136	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1785	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.0963	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.0856	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1290	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1114	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.0951	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1199	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.1386	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1321	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.0963	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1690	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1079	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1210	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1149	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1451	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1304	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1784	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1024	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1361	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.0972	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.3438	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1290, Train Accuracy: 0.9470
Epoch 29 training time consumed: 145.87s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0005, Accuracy: 0.9370, Time consumed:8.08s
Training Epoch: 30 [256/10020]	Loss: 0.1175	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.0847	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.1018	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1153	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1703	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1578	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.0857	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1215	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1498	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1312	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1226	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1664	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1360	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1188	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1016	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1463	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.0902	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1185	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1128	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1070	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.0843	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1313	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1120	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1368	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1485	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1505	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1405	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1200	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1889	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1221	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.0996	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.1005	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1544	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1115	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1378	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1753	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.0656	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1290, Train Accuracy: 0.9467
Epoch 30 training time consumed: 145.55s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.05s
Training Epoch: 31 [256/10020]	Loss: 0.0727	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1491	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.0903	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1262	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1182	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1435	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1628	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1161	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1683	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1300	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.0687	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1100	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1339	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.1655	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.0954	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1014	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1376	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1447	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1044	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1137	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1084	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.0877	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1426	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1434	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1139	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1046	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.0982	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1169	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1207	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.1151	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.0860	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1161	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1069	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1425	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.2362	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1228, Train Accuracy: 0.9496
Epoch 31 training time consumed: 145.97s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0005, Accuracy: 0.9433, Time consumed:7.90s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10020
Forget Train Dl:  528
Retain Valid Dl:  10020
Forget Valid Dl:  528
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.921875
Retain Accuracy: 94.97721862792969
Zero-Retain Forget (ZRF): 0.7040852308273315
Membership Inference Attack (MIA): 0.30113636363636365
Forget vs Retain Membership Inference Attack (MIA): 0.5283018867924528
Forget vs Test Membership Inference Attack (MIA): 0.5566037735849056
Test vs Retain Membership Inference Attack (MIA): 0.5145278450363197
Train vs Test Membership Inference Attack (MIA): 0.5230024213075061
Forget Set Accuracy (Df): 94.01041412353516
Method Execution Time: 5994.18 seconds
