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

📌 S Retain class distribution for seed 8:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 8:
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: 0.7227	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7274	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6943	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.6690	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.8100	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.7001	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.7387	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.7350	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.7084	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7673	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.7180	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.6978	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 0.6900	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.7681	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 1.0067	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 2.6394	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.7110	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 1.3335	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.9837	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.8870	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 1.3749	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.9460	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.9247	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.9484	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.7391	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7862	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.7405	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7292	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.8363	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.6912	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.7672	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.6890	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.6994	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7107	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.7221	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.6861	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.6828	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6721	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8478, Train Accuracy: 0.5195
Epoch 1 training time consumed: 333.02s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0033, Accuracy: 0.5564, Time consumed:8.19s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.7233	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.6766	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.6992	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.7057	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.6583	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.7762	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.6925	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.7087	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.6609	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.6914	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.6794	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.6721	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6665	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6693	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6793	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.6468	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.6576	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6899	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.7015	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6831	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6879	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6835	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6674	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.7141	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.7014	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6824	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6783	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.7139	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6901	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6887	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6870	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6738	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6773	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6765	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6610	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6215	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6861, Train Accuracy: 0.5750
Epoch 2 training time consumed: 137.64s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0032, Accuracy: 0.5056, Time consumed:8.26s
Training Epoch: 3 [256/9494]	Loss: 0.6932	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6746	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6622	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6690	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.6624	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.7021	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6539	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6756	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.6700	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.7192	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6949	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.7031	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6770	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6886	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.7033	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.7059	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.6811	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6946	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6769	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.6583	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.6697	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.6878	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.7061	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6658	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.6895	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6388	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6781	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6719	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6421	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6946	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6537	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6984	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.6696	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.7284	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6793, Train Accuracy: 0.5764
Epoch 3 training time consumed: 137.86s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0031, Accuracy: 0.5046, Time consumed:8.16s
Training Epoch: 4 [256/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.6848	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6978	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6792	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.6761	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.6746	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6799	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6595	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6764	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6947	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6534	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.7012	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6716	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6818	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6756	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6704	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6722	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6750	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6633	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.7073	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6928	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6449	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6897	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6747	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6484	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6481	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6278	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.6352	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6679	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6818	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6471	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6590	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6696	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.7076	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6634	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.6618	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6721, Train Accuracy: 0.5908
Epoch 4 training time consumed: 137.66s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.6087, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-4-best.pth
Training Epoch: 5 [256/9494]	Loss: 0.6541	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6737	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6652	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6873	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6727	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6849	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6759	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6638	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6658	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6475	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6732	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6344	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6973	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6721	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6517	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6660	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6607	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6939	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6538	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6552	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6865	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6743	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6819	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6801	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6671	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6626	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6882	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6548	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6795	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6692	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6566	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.7264	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6698, Train Accuracy: 0.5921
Epoch 5 training time consumed: 137.79s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0031, Accuracy: 0.5278, Time consumed:8.13s
Training Epoch: 6 [256/9494]	Loss: 0.6839	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6541	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.7083	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6567	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6744	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6959	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6510	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6895	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6537	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6632	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.7043	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6898	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6456	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6849	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6839	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6241	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6788	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6369	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.7011	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6321	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6486	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6811	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6689	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6372	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6677	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6731	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6484	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6396	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6501	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6424	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6294	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6883	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.6477	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6231	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.5686	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6634, Train Accuracy: 0.6009
Epoch 6 training time consumed: 137.62s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0033, Accuracy: 0.5245, Time consumed:8.05s
Training Epoch: 7 [256/9494]	Loss: 0.6775	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6983	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.7465	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6630	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6791	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6729	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6504	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6606	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6549	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6651	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6601	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6691	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6365	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6948	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6375	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6727	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6416	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6271	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6939	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6182	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6410	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6648	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6847	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6370	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6258	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6295	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6432	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6473	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.6393	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6041	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6136	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.6244	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.5566	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6562, Train Accuracy: 0.6203
Epoch 7 training time consumed: 138.10s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.5918, Time consumed:8.10s
Training Epoch: 8 [256/9494]	Loss: 0.6336	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.6601	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.6277	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6230	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6447	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6479	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6490	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6133	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6066	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.5919	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.6193	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.6373	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.6372	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.5955	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.5762	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.6042	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.6070	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5922	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.6536	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.5906	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.5595	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.5987	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5907	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.5916	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5779	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5872	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.5511	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.5907	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.6825	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.5718	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.5719	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.6011	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5432	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5601	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.6341	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5590	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5872	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.5091	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6044, Train Accuracy: 0.6788
Epoch 8 training time consumed: 137.00s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0027, Accuracy: 0.6712, Time consumed:8.33s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-8-best.pth
Training Epoch: 9 [256/9494]	Loss: 0.5688	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.6294	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.6411	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.5665	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.5733	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.5510	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.5557	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.5920	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.5960	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.5669	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.5832	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.5488	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.5089	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.4826	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.5373	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.4940	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.5536	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.5739	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.5319	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.5709	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.5006	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.4590	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.4667	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.4788	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.4846	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.4549	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.4918	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.4572	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.4483	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.5236	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.4758	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4873	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.4244	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.4323	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.4860	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.4387	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.4818	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.2747	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5188, Train Accuracy: 0.7463
Epoch 9 training time consumed: 137.59s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0045, Accuracy: 0.5637, Time consumed:8.20s
Training Epoch: 10 [256/9494]	Loss: 0.4984	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.4457	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.4967	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.3992	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.4473	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.3879	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.4977	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.4367	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.3896	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.4476	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.4641	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.4699	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.4296	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.4881	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.4150	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.4692	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.4449	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.4369	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.4437	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.4412	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.4199	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.3621	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.4368	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.3965	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.3874	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.3994	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.4331	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.3894	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.3560	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.3778	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.3801	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.3357	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.3827	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.3882	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.4745	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.3597	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.3517	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.5416	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4214, Train Accuracy: 0.8125
Epoch 10 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0019, Accuracy: 0.8305, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-10-best.pth
Training Epoch: 11 [256/9494]	Loss: 0.3937	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.3544	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.4341	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.3995	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.4425	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.3853	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.5021	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.3227	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.4405	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.3427	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.4156	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.3661	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.4172	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.4060	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.4065	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.3957	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.3973	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.3545	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.3745	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.3666	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.3775	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.3512	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.3327	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.3847	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.3763	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.3888	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.3619	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.4042	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.3746	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.3454	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.3703	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.4186	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.3003	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.4003	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.3830	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.3119	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.3343	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.4414	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3821, Train Accuracy: 0.8285
Epoch 11 training time consumed: 137.75s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0022, Accuracy: 0.7855, Time consumed:8.20s
Training Epoch: 12 [256/9494]	Loss: 0.2746	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.4406	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.3603	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.5062	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.3599	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.4211	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.3505	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.3524	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.3207	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.3584	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.4366	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.3516	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.3350	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.3829	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.3570	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.3471	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.3437	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.3481	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.3534	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.3226	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.3727	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.3168	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.3670	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.3438	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.3069	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.3317	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3421	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.3172	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.3513	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.3529	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.3502	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.3053	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3069	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.3059	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.3487	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.2668	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.4131	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.2519	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3517, Train Accuracy: 0.8452
Epoch 12 training time consumed: 137.37s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0014, Accuracy: 0.8600, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-12-best.pth
Training Epoch: 13 [256/9494]	Loss: 0.3424	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.4030	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.3719	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.3230	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.3473	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.3530	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.3958	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.3369	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3728	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.2992	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.2713	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.2825	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.4171	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.2740	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.2889	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.3095	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.3762	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.3489	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.2946	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.3259	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.3303	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.2885	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.3205	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.2852	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.2899	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.2985	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.2532	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.2917	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.2500	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.2378	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.2870	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.3173	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3129	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.3665	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.3301	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.2926	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.4165	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3191, Train Accuracy: 0.8633
Epoch 13 training time consumed: 137.17s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0023, Accuracy: 0.7593, Time consumed:8.34s
Training Epoch: 14 [256/9494]	Loss: 0.3156	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.3191	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.3730	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.2985	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.2720	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.3347	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.2879	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.3236	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.2633	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.3281	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.3055	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.3305	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.3465	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.3415	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.2753	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.2713	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.2942	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.3301	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.3219	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.2848	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.4026	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.2989	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.2633	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.2828	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.2411	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.2423	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.2729	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.2517	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.2944	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.2817	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.2521	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.2863	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.2913	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.1893	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.3081	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.3055	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.2416	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.2850	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2952, Train Accuracy: 0.8723
Epoch 14 training time consumed: 137.44s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0015, Accuracy: 0.8683, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-14-best.pth
Training Epoch: 15 [256/9494]	Loss: 0.2204	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.2992	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.3039	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3391	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.2808	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.3157	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.3049	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.2565	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.2170	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2736	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.2437	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.3027	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.2589	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.2387	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.2595	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.1960	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2604	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.1776	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.3071	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.1784	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.1972	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2529	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.3798	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.2793	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.2841	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.3321	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.3710	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2133	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.2671	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.2165	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.2562	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2606	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.1969	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.1975	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.2344	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.2520	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.2661	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.1498	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2617, Train Accuracy: 0.8889
Epoch 15 training time consumed: 137.61s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0010, Accuracy: 0.9041, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.1968	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.3193	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.2133	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2368	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.2198	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.2395	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.2457	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.2618	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.1765	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2861	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.2673	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.1770	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.2028	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2826	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.2986	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.2217	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2124	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2339	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.2501	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2468	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.1996	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.2374	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.1579	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.3223	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.2594	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2246	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2143	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2698	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.2524	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2360	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2047	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2375	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.2626	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.3144	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.5015	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2416, Train Accuracy: 0.8968
Epoch 16 training time consumed: 137.44s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0010, Accuracy: 0.8993, Time consumed:7.99s
Training Epoch: 17 [256/9494]	Loss: 0.1996	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.3137	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2382	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.2684	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2244	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.3156	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.3228	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.2303	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.2538	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2473	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.2421	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2896	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.3114	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.2469	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.2268	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.2294	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.2212	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.2289	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2337	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2155	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2893	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.2690	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.1998	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.2143	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.2371	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.1816	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.1857	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.2478	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2369	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.2180	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2317	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.1966	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2154	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2839	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.1581	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2563	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.2280	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.6123	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2417, Train Accuracy: 0.8984
Epoch 17 training time consumed: 137.31s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0011, Accuracy: 0.8920, Time consumed:7.96s
Training Epoch: 18 [256/9494]	Loss: 0.2779	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.4196	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.3114	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.3553	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.3124	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.3174	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.3001	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.2949	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.2445	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.2582	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.2918	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2406	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2430	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2724	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.2768	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2330	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.2521	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2584	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.1570	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.2422	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.2513	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2530	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2396	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.2121	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.2200	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.1617	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.1975	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.1944	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.2616	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.1942	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2783	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.1655	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2558	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.2340	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2831	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.1984	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.2287	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2926	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2538, Train Accuracy: 0.8936
Epoch 18 training time consumed: 137.04s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0028, Accuracy: 0.7433, Time consumed:7.88s
Training Epoch: 19 [256/9494]	Loss: 0.2002	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.2122	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.2125	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.2466	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.2188	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.2542	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2843	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.1968	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.2196	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.2022	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.1989	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.2340	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1733	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2358	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2410	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.2305	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2427	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1915	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.1872	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2116	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1910	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.1938	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2173	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.2260	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.2268	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.2013	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.1889	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2284	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.2728	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1875	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1468	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2183	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.1778	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.1831	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.1997	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1705	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.2060	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.1822	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2116, Train Accuracy: 0.9114
Epoch 19 training time consumed: 137.11s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0021, Accuracy: 0.8082, Time consumed:8.01s
Training Epoch: 20 [256/9494]	Loss: 0.1768	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.1931	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.2001	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2410	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.2444	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2354	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.2046	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.2036	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1550	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.2085	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.1440	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.2019	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.1604	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.2094	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1461	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.2017	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1294	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.2012	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1257	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.2003	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1382	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1812	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1362	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1726	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.2050	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.2146	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1392	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.2262	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1607	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1376	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1697	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1810	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.2094	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.2612	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1814, Train Accuracy: 0.9256
Epoch 20 training time consumed: 137.06s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9351, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.1716	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1617	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1274	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1815	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.1974	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1825	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1911	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1736	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.2001	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1834	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1935	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1778	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1687	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1549	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1875	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1589	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.0984	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1948	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.2452	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1794	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1785	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1609	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1657	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1641	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1326	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.0991	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1470	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.0866	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1664, Train Accuracy: 0.9306
Epoch 21 training time consumed: 137.37s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:7.80s
Training Epoch: 22 [256/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1513	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1456	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1560	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.1927	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1801	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1657	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1721	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1532	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.2040	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.1755	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1890	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1505	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1722	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1227	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1537	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1413	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.2072	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1586	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1331	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1110	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1520	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1608	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1073	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.2224	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.2366	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1332	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1633	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1967	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.1379	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1620, Train Accuracy: 0.9327
Epoch 22 training time consumed: 137.27s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9298, Time consumed:7.91s
Training Epoch: 23 [256/9494]	Loss: 0.1616	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1603	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1577	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1661	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1456	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1980	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1721	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.2056	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1669	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1400	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1081	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1270	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1955	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1347	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1209	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1747	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1389	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1705	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1831	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1666	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1067	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1626	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1762	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1417	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1864	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1881	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1998	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1839	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1614	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1125	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1277	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.0797	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1592, Train Accuracy: 0.9353
Epoch 23 training time consumed: 137.58s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9370, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-23-best.pth
Training Epoch: 24 [256/9494]	Loss: 0.1289	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1225	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1650	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1958	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1943	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1408	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1667	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1003	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1641	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1174	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1141	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1900	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1059	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.1549	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1557	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1638	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1599	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1651	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1537	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1633	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1247	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.2099	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1563	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1933	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1076	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1155	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1308	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1435	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.1721	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1514, Train Accuracy: 0.9398
Epoch 24 training time consumed: 136.93s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9327, Time consumed:8.25s
Training Epoch: 25 [256/9494]	Loss: 0.1468	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1864	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1289	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1488	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1218	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.1846	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1458	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1956	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1411	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1990	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1998	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1614	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1615	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.2300	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1122	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1330	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1969	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1321	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.2206	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.2057	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1626	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1570	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1719	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.2002	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1748	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1291	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1447	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1253	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.2669	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1618, Train Accuracy: 0.9326
Epoch 25 training time consumed: 136.95s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.20s
Training Epoch: 26 [256/9494]	Loss: 0.1354	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1500	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1864	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1493	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1602	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1836	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1533	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1306	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.1278	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.0893	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1444	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1361	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1858	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1628	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1060	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.2061	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1342	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1113	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1434	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1882	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1939	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.2177	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1639	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1076	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1174	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1315	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1191	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.2172	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.0314	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1528, Train Accuracy: 0.9392
Epoch 26 training time consumed: 137.12s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-26-best.pth
Training Epoch: 27 [256/9494]	Loss: 0.1615	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1087	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1760	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1180	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1594	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1148	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1207	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1260	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1526	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1895	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1753	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1908	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1318	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1430	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1964	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1387	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1214	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1784	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1329	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1126	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1289	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1119	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1449	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1809	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1499	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1489	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1506	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1326	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1220	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1256	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1574	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1894	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1596	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.3849	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1468, Train Accuracy: 0.9414
Epoch 27 training time consumed: 137.19s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9390, Time consumed:8.15s
Training Epoch: 28 [256/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1200	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.2339	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1362	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1606	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1867	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1365	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1730	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1642	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1809	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1683	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1442	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1397	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1377	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1094	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1217	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1463	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1591	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.0987	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1533	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1553	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1313	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1256	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1319	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.0851	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1442, Train Accuracy: 0.9412
Epoch 28 training time consumed: 137.25s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0007, Accuracy: 0.9380, Time consumed:8.14s
Training Epoch: 29 [256/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1994	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1188	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.0920	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.0750	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1580	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1590	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1322	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1364	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1666	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1525	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1116	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1105	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1486	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1756	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1417	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1098	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1633	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1891	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1031	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1722	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1312	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1560	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1038	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1351	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1025	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1865	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1692	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1093	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1400	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.0515	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1396, Train Accuracy: 0.9410
Epoch 29 training time consumed: 136.67s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9453, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_08h_28m_13s/ResNet18-MUCAC-seed8-ret100-29-best.pth
Training Epoch: 30 [256/9494]	Loss: 0.2179	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1555	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1209	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1325	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1119	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1820	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1582	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1101	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1297	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1190	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1092	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.2422	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1859	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1383	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1192	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1520	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1185	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1609	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1284	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.1134	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1577	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1072	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1163	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1649	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.0833	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1610	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1830	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.1635	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1428, Train Accuracy: 0.9431
Epoch 30 training time consumed: 137.14s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:8.15s
Training Epoch: 31 [256/9494]	Loss: 0.1054	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1108	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1922	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1711	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1671	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1728	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1469	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1140	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1624	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1421	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1107	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.0906	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1168	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.2000	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1112	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1347	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1441	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1360	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1135	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1458	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1510	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1845	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1362	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1515	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1582	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1036	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.1206	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1840	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1356	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.0982	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1103	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1594	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.5224	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1428, Train Accuracy: 0.9430
Epoch 31 training time consumed: 137.38s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9356, Time consumed:8.24s
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: 94.22743225097656
Retain Accuracy: 93.96307373046875
Zero-Retain Forget (ZRF): 0.7551162242889404
Membership Inference Attack (MIA): 0.33586337760910817
Forget vs Retain Membership Inference Attack (MIA): 0.5023696682464455
Forget vs Test Membership Inference Attack (MIA): 0.5379146919431279
Test vs Retain Membership Inference Attack (MIA): 0.5193704600484261
Train vs Test Membership Inference Attack (MIA): 0.5423728813559322
Forget Set Accuracy (Df): 92.33854675292969
Method Execution Time: 5676.38 seconds
