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

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

📌 S Forget class distribution for seed 7:
Class 0: 527
Class 1: 527
./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 [256/9494]	Loss: 0.9134	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.9110	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6991	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.9803	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 1.4208	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.9992	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 1.2714	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 1.1920	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 1.0035	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 1.2042	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.8819	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.9013	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 0.6973	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.8697	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.6848	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 0.7819	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.6932	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.7908	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.7399	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.7594	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.7223	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.8001	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.8178	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.7136	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.8265	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7488	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.8044	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.6947	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.7458	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7735	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.6945	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.7676	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.7274	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7359	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.6913	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.6992	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.7076	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6438	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8392, Train Accuracy: 0.5105
Epoch 1 training time consumed: 355.04s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0030, Accuracy: 0.5617, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.6715	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7275	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.6929	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.7200	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.7127	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.6706	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.6997	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.7083	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.6991	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.6921	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6998	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6813	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.6873	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.6876	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6723	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.6702	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6858	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6514	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6869	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6729	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.7193	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.6823	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.7171	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6849	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.7077	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.7045	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6678	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.7384	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.7173	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6705	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.7059	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6954	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.7323	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6915, Train Accuracy: 0.5557
Epoch 2 training time consumed: 137.76s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5763, Time consumed:8.21s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-2-best.pth
Training Epoch: 3 [256/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6939	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6857	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6875	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.6673	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.7100	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6720	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6589	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6974	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.7492	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.7540	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6515	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.7086	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.7196	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6649	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.7497	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.6566	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.8196	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.7055	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.7745	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.7492	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.7410	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.6856	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6680	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.7245	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6977	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6681	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6840	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6810	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6734	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.7002	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6662	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.6770	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.7007	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6983, Train Accuracy: 0.5559
Epoch 3 training time consumed: 137.49s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5588, Time consumed:8.31s
Training Epoch: 4 [256/9494]	Loss: 0.6953	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7098	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.7065	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6858	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6955	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.7134	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.6937	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6906	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6667	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6812	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6915	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.7065	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6858	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6947	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6543	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6770	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.7671	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.7169	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6894	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6869	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6846	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.7060	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6549	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6785	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6865	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6743	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6887	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6824	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6470	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6843	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6776	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6737	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.7207	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6880, Train Accuracy: 0.5615
Epoch 4 training time consumed: 137.68s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0031, Accuracy: 0.5545, Time consumed:8.04s
Training Epoch: 5 [256/9494]	Loss: 0.6478	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6746	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6733	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6738	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6677	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6588	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6758	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6673	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6991	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6836	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6517	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6831	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6815	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6806	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6624	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6591	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6664	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6581	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6603	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6543	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6435	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6359	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6833	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6797	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6517	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6865	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6852	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6589	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6678	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6717	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6600	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6677	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6723	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.7194	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6695, Train Accuracy: 0.5905
Epoch 5 training time consumed: 137.27s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5971, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-5-best.pth
Training Epoch: 6 [256/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6386	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6710	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6682	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6655	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6624	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6716	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6573	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6781	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6992	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6628	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6771	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6648	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6691	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6885	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6717	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6576	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6601	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6801	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6264	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6500	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6094	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6914	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6599	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6711	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6498	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6574	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6446	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6414	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6349	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6564	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6460	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6580	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6603	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.5951	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6625, Train Accuracy: 0.6034
Epoch 6 training time consumed: 137.55s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.6266, Time consumed:8.31s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-6-best.pth
Training Epoch: 7 [256/9494]	Loss: 0.6684	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6864	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6741	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6575	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6473	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6604	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6576	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6607	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6511	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6647	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6323	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6571	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6511	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6701	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6724	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6716	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6421	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6349	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6491	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6475	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6586	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6432	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6646	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6204	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6191	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6145	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6009	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6238	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6283	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6244	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.6074	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6270	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.5761	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.5990	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.6027	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.6431	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6427, Train Accuracy: 0.6305
Epoch 7 training time consumed: 137.47s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0028, Accuracy: 0.6499, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-7-best.pth
Training Epoch: 8 [256/9494]	Loss: 0.6258	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.6694	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.6045	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6302	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6214	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6303	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6369	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6362	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6068	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.6008	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.6158	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.6140	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.6244	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.6127	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.6577	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.6373	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.6158	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5703	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.5596	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.6127	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.5942	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.5515	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5479	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.6024	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5511	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5942	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5856	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.5740	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.5934	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.6072	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.5570	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.5698	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5652	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5985	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.5578	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5852	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5328	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.5903	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5986, Train Accuracy: 0.6872
Epoch 8 training time consumed: 137.53s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0033, Accuracy: 0.5869, Time consumed:8.21s
Training Epoch: 9 [256/9494]	Loss: 0.5868	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.5949	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.5889	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.6308	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.5806	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.6303	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.5724	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.5706	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.5813	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.5942	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.6142	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.5758	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5345	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.5612	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.5510	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.5264	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.5549	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.5697	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.5350	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.5193	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.5137	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.6242	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.5291	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5601	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.5693	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.5200	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.5517	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.5257	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.5752	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.4682	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.5784	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4995	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.5355	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.5024	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.5607	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.5000	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.5079	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.6472	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5568, Train Accuracy: 0.7143
Epoch 9 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0037, Accuracy: 0.5758, Time consumed:8.13s
Training Epoch: 10 [256/9494]	Loss: 0.5751	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.6947	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.5825	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.5148	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.5007	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.5390	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.5016	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.4581	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.5947	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.5344	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.5583	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.4864	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.4798	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.5211	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.4614	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.4611	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.4855	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.4828	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.4765	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.4365	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.4322	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.4757	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.4563	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.4410	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.4558	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.4269	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.4546	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.4277	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.4032	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.4382	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.4146	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.4089	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.4222	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.3942	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.4367	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.4121	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.4365	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.4446	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4778, Train Accuracy: 0.7726
Epoch 10 training time consumed: 137.31s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0020, Accuracy: 0.8068, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.3594	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.3755	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.4416	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.4505	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.4545	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.3838	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.4053	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.4360	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.3406	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.4568	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.3881	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.4919	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.4843	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.3440	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.5236	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.4263	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.4158	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.4774	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.3914	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.4013	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.4526	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.4350	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.3778	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.4014	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.4216	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.3716	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.4159	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.3980	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.3851	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.4341	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.4319	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.3804	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.3643	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.3679	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.3955	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.4073	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.4072	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.1256	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4127, Train Accuracy: 0.8151
Epoch 11 training time consumed: 137.41s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0017, Accuracy: 0.8475, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.4041	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.3578	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.3917	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.3781	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.4004	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.4333	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.3987	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.3828	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.3851	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.3706	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.4345	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.3772	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.3514	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.3982	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.3979	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.4018	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.3433	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.3738	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.3147	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.3369	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.3731	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.4113	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.3738	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.3765	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.4249	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.3448	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3521	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.3531	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.3426	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.3601	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.3734	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.3362	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3478	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.4132	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.2987	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.3059	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.3669	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.5068	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3729, Train Accuracy: 0.8328
Epoch 12 training time consumed: 137.23s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0022, Accuracy: 0.7685, Time consumed:8.06s
Training Epoch: 13 [256/9494]	Loss: 0.3416	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.3765	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.3901	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.4257	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.3773	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.4276	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.3467	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.4263	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3529	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.3760	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.3741	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.3562	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.3703	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.2993	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.2940	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.3285	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.3828	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.4058	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.3478	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.3399	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.2996	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.3494	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.2893	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.3007	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.4078	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.3416	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.3175	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.3040	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.2993	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.3570	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.2982	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.3085	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.2817	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3903	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.3105	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.3524	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.2954	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.2879	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3470, Train Accuracy: 0.8502
Epoch 13 training time consumed: 137.48s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0023, Accuracy: 0.7496, Time consumed:7.93s
Training Epoch: 14 [256/9494]	Loss: 0.2616	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.3330	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.3225	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.2656	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.2893	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.2973	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.2960	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.3060	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.3109	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.3225	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.3101	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.3590	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.3685	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.3247	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.3151	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.3218	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.3032	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.3011	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.2580	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.2608	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.3108	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.2932	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.2879	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.3338	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.2902	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.2737	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.2939	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.3262	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.2889	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.2066	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.2781	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.3825	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.3005	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.3178	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.2873	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.3166	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.4238	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3038, Train Accuracy: 0.8730
Epoch 14 training time consumed: 137.01s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0017, Accuracy: 0.8339, Time consumed:7.90s
Training Epoch: 15 [256/9494]	Loss: 0.2655	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.3126	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.3099	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3338	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.2898	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.3317	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.2818	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.2981	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.3119	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.3317	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.2774	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.2432	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.2825	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.3132	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.3053	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.3074	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.3624	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2985	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.2687	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.2166	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.3347	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2441	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.3390	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.2449	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.3179	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.2313	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.2456	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2211	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.2878	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.2822	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.3219	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2205	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.3378	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.3262	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.2634	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.3071	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.2640	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.2212	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2899, Train Accuracy: 0.8776
Epoch 15 training time consumed: 137.15s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0021, Accuracy: 0.7937, Time consumed:8.15s
Training Epoch: 16 [256/9494]	Loss: 0.2575	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2711	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.2240	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2638	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.2680	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.3468	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.2797	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.3025	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.2294	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.2977	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2721	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.2811	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.2432	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.2934	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2597	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2257	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.2503	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2889	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2121	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2801	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2761	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2551	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.1822	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2571	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.2947	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.2088	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.2307	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.1949	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2780	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2417	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2059	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.2116	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.3502	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2641	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2487	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.2122	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.1897	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.4321	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2558, Train Accuracy: 0.8925
Epoch 16 training time consumed: 137.79s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0012, Accuracy: 0.8872, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-16-best.pth
Training Epoch: 17 [256/9494]	Loss: 0.2805	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.3149	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.3491	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.3521	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.3034	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.3278	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2988	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.3072	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.3364	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2714	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2482	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2644	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.2574	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.2424	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2267	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.1663	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.2739	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2446	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2274	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2992	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.2435	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.2566	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.2772	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.1742	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.3072	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.2160	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2227	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.1857	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2290	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.1978	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2358	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2432	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.2034	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.1761	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.2236	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.3095	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2552, Train Accuracy: 0.8930
Epoch 17 training time consumed: 137.42s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0020, Accuracy: 0.8131, Time consumed:7.88s
Training Epoch: 18 [256/9494]	Loss: 0.2679	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.2522	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.1937	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.1813	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.2978	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.2469	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2451	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2682	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2679	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.2773	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.2751	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2430	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2298	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2515	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2161	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.1819	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.2039	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2611	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.1800	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.2030	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.2416	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.1731	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.1744	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.2357	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.1590	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.1985	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.1683	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.2413	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.2037	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.1757	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2164	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.1716	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2428	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.1731	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2519	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.1555	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.1751	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2156	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2189, Train Accuracy: 0.9133
Epoch 18 training time consumed: 136.98s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0014, Accuracy: 0.8833, Time consumed:7.95s
Training Epoch: 19 [256/9494]	Loss: 0.2272	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.1869	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.1628	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.2054	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.2439	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.2037	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2097	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.1932	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.1920	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.1971	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.2330	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.1988	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1734	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.1657	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.1657	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.1592	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2369	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1674	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.2269	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.1873	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1754	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.2268	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2223	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.1835	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.1586	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.2182	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.2237	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2309	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.2307	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1592	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1792	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2285	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.2506	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.1740	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.1818	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.2837	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1569	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.2448	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2006, Train Accuracy: 0.9181
Epoch 19 training time consumed: 137.15s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0013, Accuracy: 0.8702, Time consumed:7.92s
Training Epoch: 20 [256/9494]	Loss: 0.1956	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.2321	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1915	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2296	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.2305	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.1846	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.1804	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1871	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.1941	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.2011	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.1382	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.2506	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.2183	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1637	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.1660	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.1894	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.2138	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1958	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1902	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1754	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1746	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1727	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.1541	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1071	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1433	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1559	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.2465	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1771, Train Accuracy: 0.9271
Epoch 20 training time consumed: 137.37s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9380, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1145	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1596	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.2082	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1873	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1810	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.2138	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.2002	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1667	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1853	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1988	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1167	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1844	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1503	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1845	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1382	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1539	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1989	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1580	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1857	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1815	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1400	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1511	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.2062	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1289	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.1525	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1857	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.2138	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1664, Train Accuracy: 0.9320
Epoch 21 training time consumed: 137.57s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9390, Time consumed:8.02s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-21-best.pth
Training Epoch: 22 [256/9494]	Loss: 0.1820	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1561	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1480	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1718	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.1798	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1212	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1430	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1783	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1716	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1763	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1524	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1339	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1566	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1913	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.1639	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1426	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1684	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1986	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.2016	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1980	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1664	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.1445	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.1766	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1664	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1585	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1285	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1290	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1025	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.0967	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1603, Train Accuracy: 0.9334
Epoch 22 training time consumed: 137.26s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9414, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-22-best.pth
Training Epoch: 23 [256/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.2241	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1946	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1741	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1867	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1803	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1152	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1614	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1055	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1831	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1655	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.0969	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.0948	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1764	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1361	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1229	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1438	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1406	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1825	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.2093	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1621	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1996	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1503	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1205	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1505	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.2020	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.2194	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1342	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1173	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.3429	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1558, Train Accuracy: 0.9350
Epoch 23 training time consumed: 136.91s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.96s
Training Epoch: 24 [256/9494]	Loss: 0.1488	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1993	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1421	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1426	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1295	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1911	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.2022	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1994	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1399	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1162	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1529	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1469	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1531	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1363	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1459	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1589	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.2104	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1280	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1637	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.2577	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.2028	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1733	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1188	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1096	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.2327	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1571, Train Accuracy: 0.9356
Epoch 24 training time consumed: 136.67s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9351, Time consumed:8.28s
Training Epoch: 25 [256/9494]	Loss: 0.1519	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1221	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1361	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1821	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1977	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1623	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1758	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1532	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1131	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.2392	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1222	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1466	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1375	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1439	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1865	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1541	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1607	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1457	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1438	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1773	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1190	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1391	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1183	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1428	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1457	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1406	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.2151	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.2069	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1539, Train Accuracy: 0.9380
Epoch 25 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:8.31s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-25-best.pth
Training Epoch: 26 [256/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1742	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1750	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1287	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1411	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1165	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.1454	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1438	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1480	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1765	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.1595	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1153	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1232	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1236	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1729	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1557	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1466	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1706	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1115	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1019	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1679	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1451	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1439	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1553	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.7335	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1488, Train Accuracy: 0.9373
Epoch 26 training time consumed: 137.90s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9472, Time consumed:8.23s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_06h_52m_55s/ResNet18-MUCAC-seed7-ret100-26-best.pth
Training Epoch: 27 [256/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.0977	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1591	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.0935	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1246	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1623	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1916	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1266	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.2742	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1323	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1878	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1473	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1661	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1905	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1667	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1906	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1551	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1070	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1675	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1146	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1455	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1586	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1090	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1513	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1478	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1442	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1409	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.0978	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1572	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1308	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1636	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.3538	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1504, Train Accuracy: 0.9379
Epoch 27 training time consumed: 137.60s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:8.25s
Training Epoch: 28 [256/9494]	Loss: 0.2307	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1377	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1408	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1256	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1410	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1516	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1571	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1295	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1247	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1360	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1366	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1243	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1190	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1435	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.0959	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1888	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.2098	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1266	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1197	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1518	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1410	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1203	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1257	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1651	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1033	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1022	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1442	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1436	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1316	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1768	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.2190	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1439, Train Accuracy: 0.9418
Epoch 28 training time consumed: 137.31s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:8.06s
Training Epoch: 29 [256/9494]	Loss: 0.1572	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1402	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1172	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1204	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1146	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1137	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1233	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1502	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1363	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1235	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.2005	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1528	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1845	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1187	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1039	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1180	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1318	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1594	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1470	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1316	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1140	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1353	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1281	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1404	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.2056	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1391, Train Accuracy: 0.9405
Epoch 29 training time consumed: 137.45s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:8.20s
Training Epoch: 30 [256/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1485	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1036	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1595	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1426	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1780	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1845	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1737	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1247	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.0809	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.2282	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1608	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.0877	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1150	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1174	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1029	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.0945	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1472	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1866	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1314	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1806	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1561	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.0904	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1022	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1293	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1175	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1142	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1447	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.0244	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1392, Train Accuracy: 0.9429
Epoch 30 training time consumed: 137.22s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9361, Time consumed:8.15s
Training Epoch: 31 [256/9494]	Loss: 0.1240	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1707	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1751	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1006	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1217	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1201	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1721	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1198	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1000	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1495	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1491	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1619	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.2023	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1732	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1688	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.0970	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.0891	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1535	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1177	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1152	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1561	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1349	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.1850	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1237	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1629	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1684	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.0983	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1016	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1384	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.2264	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1403, Train Accuracy: 0.9416
Epoch 31 training time consumed: 137.38s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:8.05s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9494
Forget Train Dl:  1054
Retain Valid Dl:  9494
Forget Valid Dl:  1054
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.61805725097656
Retain Accuracy: 94.15557861328125
Zero-Retain Forget (ZRF): 0.7495840787887573
Membership Inference Attack (MIA): 0.2998102466793169
Forget vs Retain Membership Inference Attack (MIA): 0.5023696682464455
Forget vs Test Membership Inference Attack (MIA): 0.5260663507109005
Test vs Retain Membership Inference Attack (MIA): 0.5048426150121066
Train vs Test Membership Inference Attack (MIA): 0.5145278450363197
Forget Set Accuracy (Df): 92.609375
Method Execution Time: 5696.87 seconds
