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

📌 S Retain class distribution for seed 6:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 6:
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: 0.7081	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7095	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.7137	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.8027	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.7857	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.7037	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.8042	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.7281	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.7905	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.9804	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.7259	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.7021	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 0.8008	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.7671	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.7138	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 1.2999	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 1.6524	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.7948	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 1.2649	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.7131	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.8377	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.6908	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.7289	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.7006	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.6993	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.6939	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.6952	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7159	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.7302	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7085	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.7874	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.6997	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.7283	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7224	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.7476	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.7413	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.7197	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6727	LR: 0.097368
Epoch 1 - Average Train Loss: 0.7972, Train Accuracy: 0.5101
Epoch 1 training time consumed: 343.89s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0126, Accuracy: 0.5530, Time consumed:8.18s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.7896	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7226	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.7299	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.6910	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.8019	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6952	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.7510	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.7359	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.7164	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.7091	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.7125	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6934	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.8071	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6867	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.7218	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.7035	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.7546	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.7521	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.7212	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6741	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6843	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6834	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.7041	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6828	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.6919	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.7092	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.7352	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6783	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.7452	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6862	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6958	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6913	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.7179	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6837	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6846	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6863	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6632	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7134, Train Accuracy: 0.5303
Epoch 2 training time consumed: 137.73s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5177, Time consumed:8.08s
Training Epoch: 3 [256/9494]	Loss: 0.6775	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.7120	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6955	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6858	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.6528	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.7042	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6768	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.6554	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.7002	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6673	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6814	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6836	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6754	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6900	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6807	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6591	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.7128	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6973	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.7128	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.7417	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6647	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.6840	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.7197	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6878	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.6695	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6852	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6800	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6531	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.7166	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6730	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.7043	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6989	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.6443	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.6622	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6853, Train Accuracy: 0.5696
Epoch 3 training time consumed: 137.11s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5467, Time consumed:8.24s
Training Epoch: 4 [256/9494]	Loss: 0.6504	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7149	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.7183	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.7084	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6738	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6889	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6497	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.7034	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6924	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6746	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.7055	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6851	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.7052	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6488	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6638	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6669	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6828	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6915	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6457	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6538	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6750	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6651	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6610	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6870	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6938	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6963	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.7164	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6604	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6681	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6851	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6671	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6638	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6525	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6696	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6467	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.6531	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6780, Train Accuracy: 0.5767
Epoch 4 training time consumed: 137.07s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0043, Accuracy: 0.4547, Time consumed:8.18s
Training Epoch: 5 [256/9494]	Loss: 0.7750	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6376	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6583	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6946	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6621	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.7067	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6815	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6924	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6882	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6795	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6528	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.7004	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.7060	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6610	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6423	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6888	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6249	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6533	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6855	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6820	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6446	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6729	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6701	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6482	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6581	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6534	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6959	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6452	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6574	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6694	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6761	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6509	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6656	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6432	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.5962	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6710, Train Accuracy: 0.6064
Epoch 5 training time consumed: 136.74s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0034, Accuracy: 0.5651, Time consumed:8.24s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-5-best.pth
Training Epoch: 6 [256/9494]	Loss: 0.7188	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6108	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6064	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6333	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6603	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6332	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6375	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6031	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6676	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6922	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6387	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6763	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6459	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6384	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6455	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6460	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6598	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6145	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6321	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6125	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6202	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6378	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6100	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.5970	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6189	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.5916	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6751	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6497	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6432	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6476	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6419	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6637	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6504	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6073	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.6014	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6405, Train Accuracy: 0.6382
Epoch 6 training time consumed: 137.09s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0106, Accuracy: 0.4494, Time consumed:8.23s
Training Epoch: 7 [256/9494]	Loss: 0.6224	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.5920	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6521	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6183	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.5821	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.5838	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6049	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.5991	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.5726	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6202	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6071	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.5918	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.5653	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6028	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.5639	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.5985	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.5187	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.5225	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.5549	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.5288	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.5008	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.5229	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.4541	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.5884	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.5052	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.5342	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.5142	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.5227	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.5084	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.4395	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.5687	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.5168	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.4980	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.4367	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.4636	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.4879	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.3263	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.3513	LR: 0.100000
Epoch 7 - Average Train Loss: 0.5425, Train Accuracy: 0.7337
Epoch 7 training time consumed: 137.18s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0040, Accuracy: 0.5550, Time consumed:8.07s
Training Epoch: 8 [256/9494]	Loss: 0.4537	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.6441	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.4969	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.4673	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.4226	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.4254	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.4420	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.4646	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.5216	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.4716	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.4496	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.3859	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.4369	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.3314	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.3981	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.4175	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.4194	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5680	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.3869	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.5354	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.4834	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.4252	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.3882	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.3942	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.3459	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.3215	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.3984	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.4523	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.4091	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.3294	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.4070	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.3404	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.4346	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.2593	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.4066	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.3038	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.3868	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.2176	LR: 0.100000
Epoch 8 - Average Train Loss: 0.4218, Train Accuracy: 0.8088
Epoch 8 training time consumed: 136.74s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0017, Accuracy: 0.8455, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-8-best.pth
Training Epoch: 9 [256/9494]	Loss: 0.3360	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.5602	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.2987	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.4445	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.3430	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.3602	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.3787	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.2913	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.2928	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.3513	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.3154	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.2930	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.3555	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.3554	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.2767	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.2876	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.2447	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.2832	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.3418	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.3364	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.2859	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.3087	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.3527	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.3753	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.3012	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.3773	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.2736	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.2953	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.3062	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.3420	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.3131	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.2459	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.2766	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.2827	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.2598	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.2302	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.2480	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.2925	LR: 0.100000
Epoch 9 - Average Train Loss: 0.3194, Train Accuracy: 0.8677
Epoch 9 training time consumed: 137.21s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0068, Accuracy: 0.6005, Time consumed:8.22s
Training Epoch: 10 [256/9494]	Loss: 0.2232	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.2633	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.2438	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.2472	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.2898	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.2869	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.2034	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.2581	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.2203	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.2656	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.1928	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.2292	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.2430	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.1979	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.2241	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.2015	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.2284	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.2241	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.2918	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.1964	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.2135	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.2037	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.2236	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.2336	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.2048	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.3171	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.2214	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.1867	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.2635	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.2511	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.2423	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.2956	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.1840	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.1843	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.2031	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.2280	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.1892	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.2512	LR: 0.020000
Epoch 10 - Average Train Loss: 0.2318, Train Accuracy: 0.9044
Epoch 10 training time consumed: 136.66s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0008, Accuracy: 0.9293, Time consumed:7.95s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.2143	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.2269	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.1738	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.2477	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.2330	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.1472	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.2141	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.2213	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.1853	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.2140	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.2231	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.2546	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.2544	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.2406	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.2665	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.1939	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.1741	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.2738	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.2196	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.1894	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.2036	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.2422	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.2079	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.2008	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.1877	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.1707	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.2184	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.2161	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.2101	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.1576	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.1612	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.2162	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.1813	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.2610	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.2204	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.1891	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.2091	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.1587	LR: 0.020000
Epoch 11 - Average Train Loss: 0.2113, Train Accuracy: 0.9124
Epoch 11 training time consumed: 136.80s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0008, Accuracy: 0.9235, Time consumed:7.85s
Training Epoch: 12 [256/9494]	Loss: 0.2251	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.1467	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.2212	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.1703	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.1398	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.1737	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.2177	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.2354	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.1947	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.1752	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.1478	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.1828	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.1659	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.2335	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.1658	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.2509	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.1977	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.1452	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.1591	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.1960	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.2160	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.2201	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.1777	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.2456	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.2367	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.1508	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.1758	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.2502	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.1862	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.1401	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.1940	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.1545	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.1738	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.2842	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.2392	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.1810	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.1726	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.2148	LR: 0.020000
Epoch 12 - Average Train Loss: 0.1931, Train Accuracy: 0.9197
Epoch 12 training time consumed: 136.90s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0008, Accuracy: 0.9264, Time consumed:7.94s
Training Epoch: 13 [256/9494]	Loss: 0.2405	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.1958	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.2159	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.2282	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.1655	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.1671	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.2528	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.1613	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.1773	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.1483	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.1884	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.1477	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.1689	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.1981	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.2005	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.1279	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.1979	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.2403	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.1447	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.2244	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.1952	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.1677	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.2683	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.1228	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.1989	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.2402	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.2264	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.1386	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.2324	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.1764	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.2025	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.1865	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.1780	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.1705	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.1745	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.1451	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.3251	LR: 0.020000
Epoch 13 - Average Train Loss: 0.1904, Train Accuracy: 0.9204
Epoch 13 training time consumed: 137.07s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0016, Accuracy: 0.8663, Time consumed:7.92s
Training Epoch: 14 [256/9494]	Loss: 0.1904	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.1587	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.1306	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.1772	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.3004	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.2147	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.1688	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.2084	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.1726	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.1831	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.1971	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.1810	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.1367	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.2263	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.1727	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.1708	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.1243	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.2188	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.2051	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.2318	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.1650	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.2183	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.2112	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.1462	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.1780	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.1813	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.2107	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.1737	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.1740	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.1772	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.1851	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.2029	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.2174	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.1774	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.1773	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.1530	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.2892	LR: 0.020000
Epoch 14 - Average Train Loss: 0.1869, Train Accuracy: 0.9234
Epoch 14 training time consumed: 137.53s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0008, Accuracy: 0.9366, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-14-best.pth
Training Epoch: 15 [256/9494]	Loss: 0.1146	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.1819	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.2214	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.1510	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.1713	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.1389	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.2334	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.1862	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.2197	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2297	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.1955	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.2106	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.1799	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.1362	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.1899	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.1475	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.1976	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2008	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.1979	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.2982	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.1837	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.1962	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.1725	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.1335	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.1740	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.2256	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.2154	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2051	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.1629	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.1805	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.1659	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2034	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.1848	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.1658	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.1697	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.2001	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.1822	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.2916	LR: 0.020000
Epoch 15 - Average Train Loss: 0.1874, Train Accuracy: 0.9191
Epoch 15 training time consumed: 137.66s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:7.92s
Training Epoch: 16 [256/9494]	Loss: 0.1575	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2015	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.1943	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2363	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.1794	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.1512	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.1721	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.1881	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.1456	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.1818	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.1775	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.1718	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.1860	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.1775	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.1400	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.1767	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.1384	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2231	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2047	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.1320	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.1814	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.1550	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2082	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.1915	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.2154	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.1479	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.1262	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2027	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.1375	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2178	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.1990	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.1466	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.1913	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.1551	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.1698	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.1802	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.1751	LR: 0.020000
Epoch 16 - Average Train Loss: 0.1778, Train Accuracy: 0.9268
Epoch 16 training time consumed: 136.75s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0007, Accuracy: 0.9288, Time consumed:8.12s
Training Epoch: 17 [256/9494]	Loss: 0.2142	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.1752	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.1430	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.1849	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.1764	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.1524	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2108	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.1497	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.1713	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.1950	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.1693	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.1738	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.1421	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.1215	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.1784	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2242	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.1363	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.1902	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2188	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2193	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.1881	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.1562	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.1800	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.1346	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.1391	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.1665	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.1347	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.1902	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.1712	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.1725	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2000	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.1229	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2371	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.1312	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.1523	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.1813	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.1419	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.1138	LR: 0.020000
Epoch 17 - Average Train Loss: 0.1714, Train Accuracy: 0.9267
Epoch 17 training time consumed: 137.39s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0006, Accuracy: 0.9424, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-17-best.pth
Training Epoch: 18 [256/9494]	Loss: 0.1893	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.2027	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.2312	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.1942	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.1541	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.1338	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.1165	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.1820	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.1527	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.2169	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.1484	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.1616	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.1721	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.1499	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.1725	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.1568	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.1673	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2113	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.1520	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.1934	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.1854	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.1518	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.1405	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.1189	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.1293	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.1605	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.1595	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.1264	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.1625	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.1593	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.1504	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.2447	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.1087	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.1926	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.1063	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.1710	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.1559	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2187	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1645, Train Accuracy: 0.9324
Epoch 18 training time consumed: 136.82s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0012, Accuracy: 0.8944, Time consumed:8.31s
Training Epoch: 19 [256/9494]	Loss: 0.2216	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.2269	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.1691	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.1161	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.1223	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.1915	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.1688	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.1738	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.1542	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.1220	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.1457	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1967	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2184	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2004	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.2009	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2040	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1096	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.1578	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.1318	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1723	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.1643	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.1183	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.1592	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.1572	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.1463	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.1333	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2018	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.1821	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1653	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1509	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.1996	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.2388	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.1388	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.1410	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1870	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1676	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.1473	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1687, Train Accuracy: 0.9319
Epoch 19 training time consumed: 137.66s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0007, Accuracy: 0.9375, Time consumed:8.27s
Training Epoch: 20 [256/9494]	Loss: 0.1686	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.1211	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.1192	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.1503	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.1966	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.1116	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1239	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.1862	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.1877	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.1590	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1352	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.1308	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1662	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1086	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1158	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1796	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1387	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1642	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1388	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1021	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1324	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1623	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.1117	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1563	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1892	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1519	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.1856	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1473, Train Accuracy: 0.9373
Epoch 20 training time consumed: 136.98s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:8.22s
Training Epoch: 21 [256/9494]	Loss: 0.1108	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1171	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1655	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1737	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.1417	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1081	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1100	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1586	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1593	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1381	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.2094	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1171	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1187	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1546	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.0952	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1182	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1733	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1334	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.2189	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1942	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1761	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1125	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1560	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1218	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1357	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1358	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1348	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1575	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.1241	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1785	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.0663	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1452, Train Accuracy: 0.9385
Epoch 21 training time consumed: 136.90s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0005, Accuracy: 0.9443, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-21-best.pth
Training Epoch: 22 [256/9494]	Loss: 0.1142	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1205	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1998	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1291	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1846	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.1266	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1859	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.0958	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1254	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1676	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1810	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1298	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1135	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1312	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1543	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1263	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1387	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1751	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.2367	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1560	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1244	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1287	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1117	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1069	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1350	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1433	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.1143	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1083	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1658	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1116	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.2136	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1196	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.1794	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1435, Train Accuracy: 0.9399
Epoch 22 training time consumed: 136.40s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0005, Accuracy: 0.9438, Time consumed:8.20s
Training Epoch: 23 [256/9494]	Loss: 0.1085	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1187	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1791	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1014	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1322	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1095	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1466	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1472	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1514	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1526	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1172	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1274	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1194	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1454	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.1066	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1491	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1441	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1890	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1113	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1763	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1005	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1195	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1212	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1146	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.0953	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1024	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1086	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1227	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.1367	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1339, Train Accuracy: 0.9439
Epoch 23 training time consumed: 136.87s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0005, Accuracy: 0.9390, Time consumed:8.18s
Training Epoch: 24 [256/9494]	Loss: 0.1232	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1532	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1366	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1477	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1457	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1723	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.0961	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1304	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1694	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1240	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1084	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1449	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1394	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1052	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1234	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1100	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1511	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1624	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1157	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1278	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.0921	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1473	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.0879	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1246	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1262	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1329	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1465	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.2406	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1343, Train Accuracy: 0.9436
Epoch 24 training time consumed: 136.65s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0005, Accuracy: 0.9424, Time consumed:8.00s
Training Epoch: 25 [256/9494]	Loss: 0.1496	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1531	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1281	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.0920	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1427	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.0995	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1126	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1757	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1462	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1163	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1724	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1025	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1325	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1511	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1682	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1678	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1327	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1754	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1543	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1440	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1247	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.0979	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1956	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1234	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.0946	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1872	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1123	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1299	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.1280	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.1419	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1374, Train Accuracy: 0.9435
Epoch 25 training time consumed: 136.71s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9414, Time consumed:7.84s
Training Epoch: 26 [256/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1304	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1341	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1324	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1057	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1482	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1587	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1575	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.0931	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1099	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1391	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1642	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.1261	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1121	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1295	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1161	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1230	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.0946	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1693	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1174	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1837	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1340	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1435	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1136	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1302	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.0925	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1836	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1160	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.0562	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1355, Train Accuracy: 0.9426
Epoch 26 training time consumed: 137.25s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0005, Accuracy: 0.9414, Time consumed:7.83s
Training Epoch: 27 [256/9494]	Loss: 0.1561	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1516	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.0843	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.0989	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1236	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1455	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1351	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1483	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1052	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1801	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1188	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1094	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1080	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1358	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1143	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1145	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1087	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.0965	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1291	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1395	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1233	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1222	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1447	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1514	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1552	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1557	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1232	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1712	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1130	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1111	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.1367	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1315, Train Accuracy: 0.9426
Epoch 27 training time consumed: 137.47s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0005, Accuracy: 0.9458, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_05h_17m_55s/ResNet18-MUCAC-seed6-ret100-27-best.pth
Training Epoch: 28 [256/9494]	Loss: 0.1395	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1132	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1244	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1414	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1130	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1156	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1299	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1018	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.0719	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1352	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1053	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.0891	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1163	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1275	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1749	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1623	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.0936	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1287	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1114	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1537	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1098	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1278	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1060	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1211	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1466	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1621	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1670	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1201	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1179	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1137	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1385	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1678	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.0972	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1293, Train Accuracy: 0.9432
Epoch 28 training time consumed: 136.99s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:7.90s
Training Epoch: 29 [256/9494]	Loss: 0.1258	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1036	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1318	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.0893	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1823	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.0996	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1238	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.0998	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1451	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1337	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.0940	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1516	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1106	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1151	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1241	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1165	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1097	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1222	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1814	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1277	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1267	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1139	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1246	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1088	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1195	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1277	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1237	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1518	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1837	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1499	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1435	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1121	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.0448	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1301, Train Accuracy: 0.9434
Epoch 29 training time consumed: 137.25s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0005, Accuracy: 0.9443, Time consumed:7.92s
Training Epoch: 30 [256/9494]	Loss: 0.1093	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1069	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1018	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1202	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.0935	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1659	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1163	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.0853	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1465	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.0744	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1088	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1083	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1777	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1032	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1081	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1861	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1222	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1009	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1834	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1373	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1205	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1435	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1500	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1227	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1190	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1157	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1784	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1184	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1099	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1075	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1223	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.3823	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1270, Train Accuracy: 0.9477
Epoch 30 training time consumed: 137.35s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0005, Accuracy: 0.9424, Time consumed:7.96s
Training Epoch: 31 [256/9494]	Loss: 0.1549	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1632	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1639	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1483	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1678	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1402	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1343	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1366	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.0979	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1355	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.0974	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1358	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1377	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1454	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1327	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1311	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1665	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1752	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1410	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.0801	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1351	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1014	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1196	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1402	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1587	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.1981	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1350	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1032	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1244	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1206	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1148	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1461	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.1033	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1377, Train Accuracy: 0.9428
Epoch 31 training time consumed: 137.22s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0005, Accuracy: 0.9404, Time consumed:8.14s
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: 94.66146087646484
Retain Accuracy: 94.65180206298828
Zero-Retain Forget (ZRF): 0.7254909873008728
Membership Inference Attack (MIA): 0.27419354838709675
Forget vs Retain Membership Inference Attack (MIA): 0.5023696682464455
Forget vs Test Membership Inference Attack (MIA): 0.4928909952606635
Test vs Retain Membership Inference Attack (MIA): 0.5326876513317191
Train vs Test Membership Inference Attack (MIA): 0.5387409200968523
Forget Set Accuracy (Df): 94.05729675292969
Method Execution Time: 5678.88 seconds
