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

📌 S Retain class distribution for seed 4:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 4:
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: 0.8193	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.8586	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6964	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.8740	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 1.1592	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.8606	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 1.2424	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 1.0351	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 1.2546	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 1.0173	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.8535	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.9568	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 1.0232	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.7889	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.8096	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 0.7505	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.6690	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.8228	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.6616	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.7177	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.7500	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.6763	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.7101	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.6947	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.6909	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.6869	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.7238	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7138	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.7070	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.6726	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.7002	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.6838	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.6733	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.6766	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.6622	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.6879	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.6822	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6812	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8014, Train Accuracy: 0.5395
Epoch 1 training time consumed: 347.31s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0031, Accuracy: 0.5714, Time consumed:8.17s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.6717	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7378	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.6912	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.7394	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.7819	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6934	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.7021	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.6679	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.7228	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.8016	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.7214	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6997	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.7660	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.7887	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.7809	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.7207	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6868	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.7506	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.7021	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6979	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.7052	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.7035	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.7070	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.6657	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6490	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.7136	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6593	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6579	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6877	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6774	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6776	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6591	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6615	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.7331	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7050, Train Accuracy: 0.5488
Epoch 2 training time consumed: 139.39s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.6087, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-2-best.pth
Training Epoch: 3 [256/9494]	Loss: 0.6714	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.7251	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.7035	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.7057	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.6733	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6700	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6722	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.7250	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.7154	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6783	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6857	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6994	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6519	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6663	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6810	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6692	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.6971	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6520	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6786	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.6985	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.6921	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.7282	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6508	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.6709	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.7248	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6704	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.6586	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6610	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6622	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.7061	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6830	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6459	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6636	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6926	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6794	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.6735	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.6848	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6825, Train Accuracy: 0.5772
Epoch 3 training time consumed: 139.41s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0034, Accuracy: 0.5031, Time consumed:8.16s
Training Epoch: 4 [256/9494]	Loss: 0.7097	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7299	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.6885	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.6847	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.7259	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.7380	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6989	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.6876	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6983	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6818	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.7124	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6985	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6687	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6663	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.7016	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6694	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6955	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.7448	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6565	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.7214	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6886	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.7029	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.7044	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.7076	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6831	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6954	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6911	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6949	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6637	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6969	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6877	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6996	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6950	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.7046	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.6937	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6956, Train Accuracy: 0.5494
Epoch 4 training time consumed: 138.98s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0032, Accuracy: 0.4964, Time consumed:8.03s
Training Epoch: 5 [256/9494]	Loss: 0.7182	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.7196	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6909	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6656	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6975	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6834	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6808	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6884	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6792	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6853	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6952	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6633	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6819	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6896	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6734	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6635	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6705	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6740	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6552	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6394	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6544	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6864	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6905	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6762	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6905	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6677	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6554	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6793	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6786	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6636	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6503	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6470	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6885	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.7383	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6775, Train Accuracy: 0.5787
Epoch 5 training time consumed: 138.91s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5777, Time consumed:8.01s
Training Epoch: 6 [256/9494]	Loss: 0.6629	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.7067	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6462	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6999	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6923	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6736	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6970	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6887	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6889	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6796	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6709	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6963	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6787	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6661	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6741	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6832	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6803	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6503	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6562	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6700	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6868	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6402	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6632	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6493	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6565	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6563	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6566	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6598	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6519	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6404	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6361	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6403	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6336	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.6547	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6675, Train Accuracy: 0.5938
Epoch 6 training time consumed: 137.53s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0032, Accuracy: 0.5511, Time consumed:7.93s
Training Epoch: 7 [256/9494]	Loss: 0.6857	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6707	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6468	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.7160	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6627	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6186	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6772	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6251	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6555	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6467	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6268	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6629	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6457	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6219	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6355	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6218	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6229	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6637	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6008	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6319	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6417	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6179	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6156	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6379	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6686	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6486	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6332	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6622	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6201	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6652	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.5817	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6114	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.5914	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6285	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.6083	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.6456	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6408, Train Accuracy: 0.6420
Epoch 7 training time consumed: 137.72s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0033, Accuracy: 0.5714, Time consumed:8.19s
Training Epoch: 8 [256/9494]	Loss: 0.6236	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.6535	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.5912	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6185	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6482	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6376	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6356	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6360	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.5795	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.5942	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.5663	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.5629	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.5931	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.5916	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.5773	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.5407	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5806	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.6107	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.5854	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.6220	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.6103	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5715	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.5761	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5755	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5529	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5411	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.5308	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.6268	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.6293	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.5711	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.5542	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5881	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5639	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.5406	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5867	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5454	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.6722	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5920, Train Accuracy: 0.6889
Epoch 8 training time consumed: 137.71s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0033, Accuracy: 0.5516, Time consumed:7.99s
Training Epoch: 9 [256/9494]	Loss: 0.5551	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.5775	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.5978	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.4974	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.5969	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.5220	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.5117	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.6215	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.6048	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.5642	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.5243	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.5105	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5299	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.5328	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.5161	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.4961	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.4780	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.5512	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.5446	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.5090	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.5323	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.5392	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.5532	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5164	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.4974	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.5167	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.5569	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.5026	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.5458	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.4984	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.4759	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4515	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.5489	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.5119	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.4688	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.4299	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.4485	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.2506	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5246, Train Accuracy: 0.7474
Epoch 9 training time consumed: 137.55s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0058, Accuracy: 0.5550, Time consumed:8.41s
Training Epoch: 10 [256/9494]	Loss: 0.6481	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.6014	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.5155	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.5060	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.4957	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.5449	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.4621	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.5136	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.5029	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.4462	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.4474	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.4721	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.4609	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.4107	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.4228	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.3982	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.4976	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.4000	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.4578	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.4590	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.4596	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.4044	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.4112	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.4663	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.4380	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.4261	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.3830	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.4534	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.3676	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.3909	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.4484	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.4014	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.3957	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.3879	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.4853	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.4045	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.3956	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.4706	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4536, Train Accuracy: 0.7930
Epoch 10 training time consumed: 142.26s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0019, Accuracy: 0.8116, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.4049	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.4444	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.4194	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.4214	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.4503	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.3907	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.3471	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.3670	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.4851	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.3559	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.3660	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.4076	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.3888	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.4277	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.3617	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.4776	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.4512	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.3782	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.4565	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.4062	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.3779	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.4564	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.4242	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.4019	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.3895	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.3792	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.3562	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.3860	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.3609	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.4409	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.3621	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.4528	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.3430	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.3816	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.4339	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.5234	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.3551	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.4332	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4064, Train Accuracy: 0.8165
Epoch 11 training time consumed: 138.29s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0015, Accuracy: 0.8513, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.3385	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.3410	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.3938	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.3902	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.4306	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.3322	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.3999	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.4296	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.3671	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.3895	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.4428	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.4029	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.4420	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.3547	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.4398	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.3449	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.3811	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.3923	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.3426	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.3050	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.3991	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.4020	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.4022	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.3799	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.3503	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.3467	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3883	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.3224	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.2996	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.3971	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.3676	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.3977	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3333	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.3585	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.3218	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.3112	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.3687	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.4195	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3733, Train Accuracy: 0.8363
Epoch 12 training time consumed: 137.14s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0015, Accuracy: 0.8542, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-12-best.pth
Training Epoch: 13 [256/9494]	Loss: 0.3150	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.3748	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.3899	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.3301	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.2757	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.3399	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.3554	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.3557	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3427	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.3544	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.3575	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.3024	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.3295	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.3697	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.4076	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.3111	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.3995	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.3483	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.2987	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.3313	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.3416	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.3395	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.3652	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.2958	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.3586	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.2934	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.3734	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.3233	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.3899	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.3594	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.3394	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.3619	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.4144	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3055	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.3192	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.3701	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.3405	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.4130	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3456, Train Accuracy: 0.8495
Epoch 13 training time consumed: 138.73s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0016, Accuracy: 0.8489, Time consumed:8.03s
Training Epoch: 14 [256/9494]	Loss: 0.2744	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.3194	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.3496	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.3440	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.3444	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.3469	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.3188	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.3587	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.3694	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.2890	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.4097	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.3528	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.2953	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.3314	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.3432	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.3104	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.3078	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.3214	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.2635	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.3707	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.3182	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.3035	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.2770	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.2970	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.3033	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.2617	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.3038	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.3305	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.3428	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.3217	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.3034	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.2794	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.3010	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.3607	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.2999	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.3179	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.3539	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3205, Train Accuracy: 0.8624
Epoch 14 training time consumed: 138.75s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0015, Accuracy: 0.8446, Time consumed:8.33s
Training Epoch: 15 [256/9494]	Loss: 0.3692	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.4045	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.3298	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3553	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.2603	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.3153	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.3379	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.3127	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.3421	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2924	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.3740	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.2546	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.2842	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.2566	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.3078	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.3177	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2833	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2636	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.3140	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.3153	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.2818	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2696	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.3587	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.2736	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.2594	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.2354	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.2737	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2532	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.2724	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.3563	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.3503	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2835	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.2590	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.3039	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.2881	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.2533	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.2766	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.3090	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3011, Train Accuracy: 0.8698
Epoch 15 training time consumed: 139.06s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0012, Accuracy: 0.8872, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.2185	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2431	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.2837	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.3418	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.3269	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.3047	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.3386	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.3185	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.3500	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.3050	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2966	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.2555	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.3150	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.2888	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2946	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2828	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.3043	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2698	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2560	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2599	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2122	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2951	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2643	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2574	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.3010	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.2479	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.1758	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.2397	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.3335	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2277	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2185	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.2061	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2742	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2527	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2437	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.3125	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.2771	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.1513	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2752, Train Accuracy: 0.8801
Epoch 16 training time consumed: 138.83s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0011, Accuracy: 0.8939, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-16-best.pth
Training Epoch: 17 [256/9494]	Loss: 0.2363	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.2408	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2742	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.2942	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2550	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.2784	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2461	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.2717	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.1875	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2028	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2330	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2216	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.3185	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.2799	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.2202	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2522	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.2721	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.2288	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2702	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.1488	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2828	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.3058	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.1976	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.2289	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.3078	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.2509	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.2479	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.2516	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2128	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.2582	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2791	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.2401	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2122	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2589	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.2839	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2366	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.2228	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.5644	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2497, Train Accuracy: 0.8980
Epoch 17 training time consumed: 138.63s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0047, Accuracy: 0.5709, Time consumed:8.41s
Training Epoch: 18 [256/9494]	Loss: 0.2666	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.3144	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.3408	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.3166	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.3077	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.2710	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2587	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2832	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2574	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.1973	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.2266	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2947	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2420	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2935	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2162	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2428	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.3019	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2655	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2494	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.2221	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.2188	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2751	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2430	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.2228	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.2577	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.2751	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2597	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.2181	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.1887	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.2290	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2303	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.2839	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2242	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.2170	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2831	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.2477	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.2707	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2368	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2571, Train Accuracy: 0.8932
Epoch 18 training time consumed: 138.79s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0014, Accuracy: 0.8678, Time consumed:8.24s
Training Epoch: 19 [256/9494]	Loss: 0.2369	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.2342	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.2860	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.2920	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.2731	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.2208	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2390	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.2065	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.2572	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.2607	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.2133	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.2383	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.2575	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2478	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2398	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.2433	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2221	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1967	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.2111	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2113	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1400	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.2380	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2336	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.2777	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.2228	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.2057	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.2238	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2398	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.1957	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.2195	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.2695	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2694	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.2546	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.2508	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.2155	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1896	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.2617	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.4206	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2354, Train Accuracy: 0.9004
Epoch 19 training time consumed: 139.23s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0014, Accuracy: 0.8620, Time consumed:8.05s
Training Epoch: 20 [256/9494]	Loss: 0.2181	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.2265	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1742	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2329	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.1807	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2495	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.2248	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.2056	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.2339	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.2265	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.2370	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.1890	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1964	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1938	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.2000	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.2331	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1961	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.1966	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1669	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1861	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1748	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.2268	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1908	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.2643	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1707	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1969	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1860	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.2110	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.2189	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1915	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1652	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.2773	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1986, Train Accuracy: 0.9192
Epoch 20 training time consumed: 138.68s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0008, Accuracy: 0.9240, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.2521	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.2164	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.2128	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.2663	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1868	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1937	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.2374	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.1616	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1707	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.2330	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1654	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1979	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1671	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.2229	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.2049	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1906	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1722	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1836	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1677	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1645	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1587	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1888	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1649	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1678	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1208	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1973	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1945	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.2111	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.0518	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1833, Train Accuracy: 0.9274
Epoch 21 training time consumed: 138.93s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9317, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-21-best.pth
Training Epoch: 22 [256/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1541	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1200	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1482	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1342	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.2113	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1288	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1862	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.2255	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1884	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.2093	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1888	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1807	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1980	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1617	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.2155	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1766	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1862	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1321	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.1478	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.2082	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1677	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1660	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1802	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1901	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1688	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1303	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.2299	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.2240	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1655	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.2042	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1519	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.5321	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1766, Train Accuracy: 0.9282
Epoch 22 training time consumed: 139.04s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9337, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-22-best.pth
Training Epoch: 23 [256/9494]	Loss: 0.1526	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1184	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.2083	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.2359	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.2041	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1814	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.2118	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.2296	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1837	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1937	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1343	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.2725	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.2533	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1464	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1973	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.2402	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1971	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1282	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1628	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.2142	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1664	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1341	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1977	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1807	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1977	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1589	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1476	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1089	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.2472	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1797, Train Accuracy: 0.9291
Epoch 23 training time consumed: 139.43s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9332, Time consumed:8.04s
Training Epoch: 24 [256/9494]	Loss: 0.2036	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1979	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1845	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.2323	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1410	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.2316	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1472	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1730	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1903	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1731	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.2155	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1567	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1282	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1992	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1314	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1570	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1801	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1770	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.2062	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1691	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1757	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1285	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1621	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1910	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1885	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1878	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1089	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1855	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1652	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.0525	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1705, Train Accuracy: 0.9305
Epoch 24 training time consumed: 138.09s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9341, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1579	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1064	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1794	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1591	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.2145	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1100	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1719	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1370	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1593	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1617	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1770	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1236	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1689	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.2201	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1304	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.2190	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1445	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1979	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1876	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1661	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1518	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1343	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1881	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.2181	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1038	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1559	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1421	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1578	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.1596	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.1528	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1594, Train Accuracy: 0.9342
Epoch 25 training time consumed: 138.59s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9332, Time consumed:8.09s
Training Epoch: 26 [256/9494]	Loss: 0.1496	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.2263	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1937	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1276	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1177	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.0927	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.1446	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.2072	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1851	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1737	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.2143	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1780	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1227	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1619	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1161	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1201	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1640	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1279	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1578	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.2065	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1161	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1843	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1869	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.1960	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1573, Train Accuracy: 0.9371
Epoch 26 training time consumed: 138.42s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0007, Accuracy: 0.9303, Time consumed:8.16s
Training Epoch: 27 [256/9494]	Loss: 0.2422	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.2088	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1111	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1607	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1319	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1526	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1756	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.2254	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1229	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1493	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1939	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1828	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1627	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1155	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1424	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1682	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1730	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1653	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1637	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1457	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1800	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1520	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1765	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1280	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1918	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1420	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1606	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1198	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.3791	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1609, Train Accuracy: 0.9339
Epoch 27 training time consumed: 139.01s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_02h_07m_02s/ResNet18-MUCAC-seed4-ret100-27-best.pth
Training Epoch: 28 [256/9494]	Loss: 0.1842	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1505	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1369	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1570	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1903	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.2275	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1370	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1646	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1388	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1946	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1552	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1873	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1449	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1633	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1615	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.2115	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1779	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1723	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1901	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1115	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1881	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1689	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1511	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1336	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.2262	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1740	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1402	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1186	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1543	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.0712	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1643, Train Accuracy: 0.9310
Epoch 28 training time consumed: 137.66s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0007, Accuracy: 0.9356, Time consumed:8.13s
Training Epoch: 29 [256/9494]	Loss: 0.2073	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1251	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1228	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1806	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1228	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1590	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1718	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1670	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1721	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1836	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1370	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1038	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1724	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1986	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1678	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1125	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1285	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1326	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1829	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1161	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1352	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1411	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.0957	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1276	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1705	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.1338	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1490, Train Accuracy: 0.9401
Epoch 29 training time consumed: 137.01s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9356, Time consumed:8.11s
Training Epoch: 30 [256/9494]	Loss: 0.1720	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.2093	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1455	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1660	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1100	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.2268	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1194	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1737	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1406	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1339	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1331	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1382	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1914	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1331	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.0802	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1873	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1293	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1791	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1230	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1117	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1798	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.2010	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.1044	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1516, Train Accuracy: 0.9398
Epoch 30 training time consumed: 136.48s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0007, Accuracy: 0.9303, Time consumed:7.84s
Training Epoch: 31 [256/9494]	Loss: 0.1520	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1578	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1427	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1238	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1414	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1537	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1139	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1360	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1770	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1325	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1093	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1009	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1770	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1731	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1862	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1766	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1591	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1722	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1150	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1666	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1636	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1577	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.2309	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.0841	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1677	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1209	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1820	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1587	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1516	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.3584	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1490, Train Accuracy: 0.9369
Epoch 31 training time consumed: 137.78s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0009, Accuracy: 0.9206, Time consumed:7.85s
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: 92.27175903320312
Retain Accuracy: 92.3145980834961
Zero-Retain Forget (ZRF): 0.7972162961959839
Membership Inference Attack (MIA): 0.34629981024667933
Forget vs Retain Membership Inference Attack (MIA): 0.5023696682464455
Forget vs Test Membership Inference Attack (MIA): 0.5545023696682464
Test vs Retain Membership Inference Attack (MIA): 0.5217917675544794
Train vs Test Membership Inference Attack (MIA): 0.5278450363196125
Forget Set Accuracy (Df): 90.06770324707031
Method Execution Time: 5738.32 seconds
