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

📌 S Retain class distribution for seed 10:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 10:
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: 0.7345	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7234	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6919	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.6938	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.7829	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.7675	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.7386	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.7348	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.7710	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7677	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.8309	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 1.1390	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 1.5981	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 0.8816	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 0.6996	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 1.1348	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 0.8116	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 0.7169	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.9413	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.6782	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.7265	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.7185	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.8001	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.6894	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.7934	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7098	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.9502	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.7234	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.8812	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7794	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.7402	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.7590	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.6802	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7119	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.8101	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.7244	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.8179	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.7707	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8068, Train Accuracy: 0.5212
Epoch 1 training time consumed: 341.15s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0066, Accuracy: 0.4455, Time consumed:8.09s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.6955	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7263	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.7088	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.7688	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.6772	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.6803	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.7638	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.7252	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.6936	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.6749	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.6894	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.6945	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.6765	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.6847	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6973	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6702	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.6741	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.7068	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.6755	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.6984	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.6878	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6869	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6673	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.7014	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.6965	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6648	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6626	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6919	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.6725	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6973	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.6588	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.7012	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6745	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6413	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6917, Train Accuracy: 0.5503
Epoch 2 training time consumed: 137.63s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0035, Accuracy: 0.4552, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-2-best.pth
Training Epoch: 3 [256/9494]	Loss: 0.7505	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.6953	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6997	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.6697	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.6712	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.6634	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6830	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6821	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.6707	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6675	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6928	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.6666	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6840	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.6721	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6601	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.6684	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6775	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6385	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.6841	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.7662	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.6958	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.7121	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.7808	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.6718	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.7083	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.7053	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6772	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6964	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.7278	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6921	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.6729	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.6703	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6873	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6819	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.7147	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.6902	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6898, Train Accuracy: 0.5627
Epoch 3 training time consumed: 137.61s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5642, Time consumed:7.83s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-3-best.pth
Training Epoch: 4 [256/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.7070	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.6904	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.6626	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.6912	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6526	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.7200	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.6805	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6859	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6745	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6495	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6554	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6637	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6626	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6531	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6469	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.7037	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6477	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.7234	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6802	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6509	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6795	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6827	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6587	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6760	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.6580	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6794	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6664	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.7029	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6999	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.6654	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6622	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6582	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6806	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6497	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.7429	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6750, Train Accuracy: 0.5844
Epoch 4 training time consumed: 137.03s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5613, Time consumed:7.86s
Training Epoch: 5 [256/9494]	Loss: 0.6671	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.6938	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6749	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6759	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6756	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6898	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.6848	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6776	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6784	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6649	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6797	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6733	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6752	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6624	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6707	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6678	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.6798	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6686	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6448	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6928	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6674	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6987	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6634	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6604	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6752	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6812	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6706	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6839	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6431	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6587	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6676	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6661	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.6290	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6733, Train Accuracy: 0.5867
Epoch 5 training time consumed: 137.38s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5564, Time consumed:7.90s
Training Epoch: 6 [256/9494]	Loss: 0.6679	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.6777	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.6642	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.6391	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6558	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6618	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6739	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6287	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6545	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6360	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.5880	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6075	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6657	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6244	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6504	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6830	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6123	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.5982	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6351	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6494	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6080	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6221	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.6747	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.5986	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6051	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6064	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6551	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6092	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6063	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6097	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.5945	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.5734	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6685	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.5881	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.5963	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6047	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.5927	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.5715	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6292, Train Accuracy: 0.6466
Epoch 6 training time consumed: 137.70s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0027, Accuracy: 0.6581, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-6-best.pth
Training Epoch: 7 [256/9494]	Loss: 0.6735	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6619	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6692	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6388	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6229	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.5953	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6182	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.5961	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.5854	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6186	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6036	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6024	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.5715	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6107	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6440	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.5759	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.5818	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.5554	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.5730	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.5916	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.5713	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.5667	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.5568	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6329	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.5888	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.5613	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6559	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.5433	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.5803	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.5950	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.5409	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.5103	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.5115	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.5368	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.5028	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.5130	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.3969	LR: 0.100000
Epoch 7 - Average Train Loss: 0.5892, Train Accuracy: 0.6938
Epoch 7 training time consumed: 137.12s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0028, Accuracy: 0.6896, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-7-best.pth
Training Epoch: 8 [256/9494]	Loss: 0.5857	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.4958	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.6178	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.5860	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6373	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.5545	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.5219	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.5681	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.5330	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.5126	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.5129	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.5079	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.4767	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.4602	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.5118	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.4528	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.4242	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.4635	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.5351	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.3426	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.4244	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.4475	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.5229	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.3906	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.5413	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5590	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.4428	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.4879	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.4558	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.4377	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.4422	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.4283	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.5459	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.4326	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.4243	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.4411	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.5013	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.3850	LR: 0.100000
Epoch 8 - Average Train Loss: 0.4923, Train Accuracy: 0.7683
Epoch 8 training time consumed: 137.43s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0047, Accuracy: 0.5550, Time consumed:7.84s
Training Epoch: 9 [256/9494]	Loss: 0.5172	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.4510	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.4873	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.4320	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.4967	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.4607	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.4300	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.4641	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.4778	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.4619	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.3709	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.3759	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.4113	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.5099	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.3419	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.4261	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.3377	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.3756	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.4362	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.4121	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.3650	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.4472	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.3714	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.3314	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.3738	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.4354	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.4304	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.3671	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.3712	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.3209	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.3761	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.4119	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.3551	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.3779	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.3768	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.3287	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.3583	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.2739	LR: 0.100000
Epoch 9 - Average Train Loss: 0.4071, Train Accuracy: 0.8190
Epoch 9 training time consumed: 137.18s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0014, Accuracy: 0.8625, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-9-best.pth
Training Epoch: 10 [256/9494]	Loss: 0.3409	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.3634	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.3004	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.3226	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.3006	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.3652	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.3008	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.3813	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.2971	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.2875	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.3352	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.3222	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.3499	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.2773	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.3235	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.3322	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.2952	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.3012	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.3081	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.2968	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.3058	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.2870	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.2806	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.2691	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.3689	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.2842	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.3358	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.3121	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.2955	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.3192	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.2538	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.3400	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.2990	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.3423	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.3313	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.2862	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.3586	LR: 0.020000
Epoch 10 - Average Train Loss: 0.3143, Train Accuracy: 0.8668
Epoch 10 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0016, Accuracy: 0.8465, Time consumed:7.89s
Training Epoch: 11 [256/9494]	Loss: 0.3266	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.3217	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.2382	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.2917	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.3617	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.3080	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.2682	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.2983	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.2365	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.3212	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.2936	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.2285	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.2462	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.2838	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.2020	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.2768	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.2793	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.2375	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.2911	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.2579	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.2191	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.2476	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.2694	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.2735	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.2737	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.2759	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.2306	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.2976	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.3594	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.2424	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.1816	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.3060	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.3020	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.2290	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.3023	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.2510	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.1933	LR: 0.020000
Epoch 11 - Average Train Loss: 0.2731, Train Accuracy: 0.8879
Epoch 11 training time consumed: 137.57s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0011, Accuracy: 0.9002, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.3652	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.3393	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.2428	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.2464	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.2505	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.2700	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.2489	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.3510	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.2884	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.2528	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.2503	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.2179	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.2158	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.2344	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.2335	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.2807	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.2451	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.2186	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.2227	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.3375	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.2359	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.2235	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.2486	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.2046	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.2024	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.2686	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3210	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.1968	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.1745	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.2127	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.2281	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.2460	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.2839	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.2548	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.1784	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.2160	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.2239	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.1921	LR: 0.020000
Epoch 12 - Average Train Loss: 0.2494, Train Accuracy: 0.8992
Epoch 12 training time consumed: 137.51s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0011, Accuracy: 0.8954, Time consumed:8.14s
Training Epoch: 13 [256/9494]	Loss: 0.2384	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.2841	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.2264	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.3324	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.2272	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.2548	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.2870	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.2664	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3195	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.2431	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.2422	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.2566	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.2552	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.3372	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.2684	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.2581	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.1915	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.2903	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.2618	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.2029	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.2309	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.2348	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.2000	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.2650	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.2855	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.2491	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.2092	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.2417	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.2216	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.2315	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.2655	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.1909	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.1699	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.2399	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.1876	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.2079	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.2491	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.2532	LR: 0.020000
Epoch 13 - Average Train Loss: 0.2466, Train Accuracy: 0.8977
Epoch 13 training time consumed: 137.02s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0009, Accuracy: 0.9157, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-13-best.pth
Training Epoch: 14 [256/9494]	Loss: 0.1811	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.2688	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.2991	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.2623	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.3146	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.2532	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.2906	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.2473	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.1547	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.1989	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.1769	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.2051	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.1917	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.2353	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.2701	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.3132	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.2695	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.2033	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.1445	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.2825	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.2622	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.2450	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.1998	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.2045	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.2085	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.2235	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.2221	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.1773	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.2163	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.1544	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.2631	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.1873	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.1843	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.2592	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.2084	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.2103	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.1510	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2288, Train Accuracy: 0.9063
Epoch 14 training time consumed: 137.16s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0009, Accuracy: 0.9133, Time consumed:8.15s
Training Epoch: 15 [256/9494]	Loss: 0.1697	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.2032	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.1974	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.1693	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.1800	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.2638	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.2400	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.1920	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.2609	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.2185	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.2312	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.1864	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.2187	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.1868	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.2209	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.1485	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2568	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2101	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.1980	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.1494	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.1541	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2421	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.1727	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.1627	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.1768	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.2342	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.2075	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.2481	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.2386	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.2094	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.1616	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.2299	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.1837	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.2238	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.2553	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.1871	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.1781	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.3200	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2048, Train Accuracy: 0.9196
Epoch 15 training time consumed: 136.75s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0007, Accuracy: 0.9312, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.1672	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.2152	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.2418	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.2080	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.1617	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.2643	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.2037	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.2099	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.2118	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.2103	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2010	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.1753	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.1772	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.1517	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2043	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.2344	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.2136	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.1753	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.2239	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.1526	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.1918	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.2129	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.1645	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.1991	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.1906	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.1666	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.2236	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.1922	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.2022	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2264	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.1821	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.1517	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2355	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2219	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.2159	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.1943	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.2724	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.0725	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2010, Train Accuracy: 0.9178
Epoch 16 training time consumed: 137.04s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0013, Accuracy: 0.8775, Time consumed:8.32s
Training Epoch: 17 [256/9494]	Loss: 0.1766	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.1830	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.1863	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.1647	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.1622	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.1918	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.1910	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2214	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.1696	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.2019	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.1723	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.1575	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.1892	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.1736	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.1784	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.1637	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.1825	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.1674	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.1576	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.1511	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.1696	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.1371	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.1645	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.2057	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.1873	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.1823	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.1792	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.1960	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.1559	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.1795	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2138	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2102	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.1807	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.1769	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.1720	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.4003	LR: 0.020000
Epoch 17 - Average Train Loss: 0.1797, Train Accuracy: 0.9265
Epoch 17 training time consumed: 136.65s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0007, Accuracy: 0.9332, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-17-best.pth
Training Epoch: 18 [256/9494]	Loss: 0.1957	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.2261	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.2123	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.1729	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.2161	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.1552	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2669	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.3086	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.1704	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.1784	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.1844	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2800	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.1247	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.1968	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.1803	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.2025	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.1667	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.1751	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2015	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.1691	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.1674	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.2197	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.1702	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.1388	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.1570	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.1747	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2664	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.1569	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.1719	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.1878	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.1820	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.1540	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2046	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.1731	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.2148	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.2028	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.2024	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2774	LR: 0.020000
Epoch 18 - Average Train Loss: 0.1929, Train Accuracy: 0.9224
Epoch 18 training time consumed: 136.91s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0014, Accuracy: 0.8615, Time consumed:7.92s
Training Epoch: 19 [256/9494]	Loss: 0.2049	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.2063	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.2176	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.2350	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.1843	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.2255	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2403	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.2125	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.2150	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.1989	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.1580	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.1991	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.1900	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2371	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2042	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.1842	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.1947	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.1500	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.1523	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.1295	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.1757	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.1889	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2324	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.1299	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.1349	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.1696	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.1530	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.1102	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.2368	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.1424	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1549	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2009	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.1747	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.1880	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.1332	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1194	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1489	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.4677	LR: 0.020000
Epoch 19 - Average Train Loss: 0.1826, Train Accuracy: 0.9217
Epoch 19 training time consumed: 136.65s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0018, Accuracy: 0.8634, Time consumed:8.05s
Training Epoch: 20 [256/9494]	Loss: 0.1778	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.2307	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.1484	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2284	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.1670	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2159	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.1697	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.2070	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.1378	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.1727	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.1489	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.1808	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.1697	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.1999	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1474	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.1391	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1499	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.1389	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.1714	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.1166	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1474	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.1676	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.1896	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.1474	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1529	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1284	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1638	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1341	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1763	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.4210	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1632, Train Accuracy: 0.9327
Epoch 20 training time consumed: 136.53s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.1260	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.1502	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.1184	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.1551	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.2243	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1485	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.1371	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1776	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1808	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.1685	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1767	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1966	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.1658	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1404	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1131	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.2335	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.0987	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1649	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.1429	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1218	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.1236	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1423	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.1477	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.1635	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1522	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.1472	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.1316	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.1804	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1504, Train Accuracy: 0.9385
Epoch 21 training time consumed: 136.89s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9438, Time consumed:7.87s
Training Epoch: 22 [256/9494]	Loss: 0.1711	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1057	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.1136	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.1834	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1902	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.1554	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1391	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1294	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1320	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1517	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.0877	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1527	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.2299	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.2292	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1219	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.1288	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.1264	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1108	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1256	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.1231	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.1969	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.1213	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.0949	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1695	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1600	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1736	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1296	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.1332	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.1585	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.1503	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1595	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1434	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.1618	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1215	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1295	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.1054	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1457, Train Accuracy: 0.9395
Epoch 22 training time consumed: 137.58s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.90s
Training Epoch: 23 [256/9494]	Loss: 0.1431	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1470	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1294	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1625	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1149	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1541	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.1542	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.1496	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1558	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1320	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.1714	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1216	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1109	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.1565	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.0986	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.1189	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.1055	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1580	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.1128	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.1358	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.1045	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1585	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1863	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.1289	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.1398	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.1756	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1151	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1060	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.2116	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1386, Train Accuracy: 0.9416
Epoch 23 training time consumed: 137.86s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9443, Time consumed:7.83s
Training Epoch: 24 [256/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.0772	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.1134	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1126	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.2047	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.1043	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.2147	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.1581	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1082	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1215	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1729	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1038	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.1827	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.1274	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1208	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.1185	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.0838	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1089	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1776	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.1050	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1893	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.1507	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1502	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1388	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.2186	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.1007	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1464	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1268	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1647	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1300	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1381	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.0688	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1385, Train Accuracy: 0.9418
Epoch 24 training time consumed: 136.63s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9458, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1944	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1375	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.1030	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1353	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.0980	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.1725	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1240	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.1384	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.1687	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1428	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1191	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.1924	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.1559	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1014	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1418	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1254	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1198	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1765	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.1718	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1487	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1693	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1172	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1286	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.1534	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1237	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.0784	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1171	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.1169	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1043	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.0992	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.1814	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1384, Train Accuracy: 0.9420
Epoch 25 training time consumed: 136.78s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9448, Time consumed:8.10s
Training Epoch: 26 [256/9494]	Loss: 0.1428	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.1302	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.0921	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.1154	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.1422	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1257	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1339	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1235	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.0947	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1169	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.2278	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.1066	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1627	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.1458	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.1599	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.0717	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1236	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1496	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1203	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1255	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.1442	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1595	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.1209	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.0951	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.1181	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1175	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1290	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1751	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1224	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1722	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1847	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.4438	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1361, Train Accuracy: 0.9432
Epoch 26 training time consumed: 136.44s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0005, Accuracy: 0.9472, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_11h_38m_17s/ResNet18-MUCAC-seed10-ret100-26-best.pth
Training Epoch: 27 [256/9494]	Loss: 0.1553	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1672	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.0709	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1219	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1643	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1073	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1788	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1814	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1147	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1207	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.1146	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.1336	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.1572	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1556	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1043	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1234	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1131	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.1232	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.1563	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.1310	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1337	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.1067	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1072	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1281	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1719	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1375	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1131	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.0476	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1357, Train Accuracy: 0.9455
Epoch 27 training time consumed: 137.71s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:8.16s
Training Epoch: 28 [256/9494]	Loss: 0.1460	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1078	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1208	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.1260	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1063	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.0992	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1509	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1406	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.1221	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1589	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1536	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.0989	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1397	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1475	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1346	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.0931	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1519	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1005	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.0892	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.0934	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1807	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1078	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1337	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1680	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.1391	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1217	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.0968	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1246	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1590	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1039	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1157	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1691	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.1337	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.2352	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1473	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.0331	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1322, Train Accuracy: 0.9442
Epoch 28 training time consumed: 137.28s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9472, Time consumed:8.19s
Training Epoch: 29 [256/9494]	Loss: 0.1256	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1188	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.0945	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.1180	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.0707	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1241	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.1340	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1268	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1167	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.1065	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1067	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.1129	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.0966	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.0938	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1383	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1347	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1184	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.1388	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1345	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.2129	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.2092	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1207	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1709	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.0977	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1255	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1359	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.1508	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1569	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1226	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1176	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1101	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.0937	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1317	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.0437	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1281, Train Accuracy: 0.9486
Epoch 29 training time consumed: 137.02s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9462, Time consumed:8.08s
Training Epoch: 30 [256/9494]	Loss: 0.1336	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1197	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1091	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1210	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1248	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1288	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1233	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1117	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1119	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1423	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.1434	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.1570	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.1381	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1401	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.1501	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1280	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1160	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1766	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1404	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.1707	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1041	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1259	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.0761	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1183	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.0785	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.0875	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1064	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.0830	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1293	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1584	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.0928	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1218	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1029	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.1482	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1265, Train Accuracy: 0.9493
Epoch 30 training time consumed: 137.19s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:8.16s
Training Epoch: 31 [256/9494]	Loss: 0.1997	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1663	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.0867	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.0991	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.1093	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1126	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1394	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1640	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1216	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1403	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1390	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.1544	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1054	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.1129	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.0718	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1453	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1450	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1573	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.0959	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1489	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1321	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1118	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1351	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.1301	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1606	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1470	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.0925	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.1405	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1058	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1040	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1516	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1231	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1014	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1252	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.1290	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1305, Train Accuracy: 0.9480
Epoch 31 training time consumed: 137.20s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9462, Time consumed:8.29s
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: 94.57210540771484
Retain Accuracy: 95.090087890625
Zero-Retain Forget (ZRF): 0.7353026866912842
Membership Inference Attack (MIA): 0.29316888045540795
Forget vs Retain Membership Inference Attack (MIA): 0.490521327014218
Forget vs Test Membership Inference Attack (MIA): 0.5308056872037915
Test vs Retain Membership Inference Attack (MIA): 0.5169491525423728
Train vs Test Membership Inference Attack (MIA): 0.513317191283293
Forget Set Accuracy (Df): 94.48957824707031
Method Execution Time: 5675.22 seconds
