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

📌 S Retain class distribution for seed 3:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 3:
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: 0.7083	LR: 0.000000
Training Epoch: 1 [512/9494]	Loss: 0.7389	LR: 0.002632
Training Epoch: 1 [768/9494]	Loss: 0.6871	LR: 0.005263
Training Epoch: 1 [1024/9494]	Loss: 0.7456	LR: 0.007895
Training Epoch: 1 [1280/9494]	Loss: 0.7261	LR: 0.010526
Training Epoch: 1 [1536/9494]	Loss: 0.7279	LR: 0.013158
Training Epoch: 1 [1792/9494]	Loss: 0.7549	LR: 0.015789
Training Epoch: 1 [2048/9494]	Loss: 0.8826	LR: 0.018421
Training Epoch: 1 [2304/9494]	Loss: 0.7111	LR: 0.021053
Training Epoch: 1 [2560/9494]	Loss: 0.7587	LR: 0.023684
Training Epoch: 1 [2816/9494]	Loss: 0.7027	LR: 0.026316
Training Epoch: 1 [3072/9494]	Loss: 0.8200	LR: 0.028947
Training Epoch: 1 [3328/9494]	Loss: 1.2216	LR: 0.031579
Training Epoch: 1 [3584/9494]	Loss: 1.3729	LR: 0.034211
Training Epoch: 1 [3840/9494]	Loss: 1.0031	LR: 0.036842
Training Epoch: 1 [4096/9494]	Loss: 0.9831	LR: 0.039474
Training Epoch: 1 [4352/9494]	Loss: 1.1203	LR: 0.042105
Training Epoch: 1 [4608/9494]	Loss: 1.1161	LR: 0.044737
Training Epoch: 1 [4864/9494]	Loss: 0.8599	LR: 0.047368
Training Epoch: 1 [5120/9494]	Loss: 0.7170	LR: 0.050000
Training Epoch: 1 [5376/9494]	Loss: 0.8947	LR: 0.052632
Training Epoch: 1 [5632/9494]	Loss: 0.9161	LR: 0.055263
Training Epoch: 1 [5888/9494]	Loss: 0.7797	LR: 0.057895
Training Epoch: 1 [6144/9494]	Loss: 0.7085	LR: 0.060526
Training Epoch: 1 [6400/9494]	Loss: 0.6943	LR: 0.063158
Training Epoch: 1 [6656/9494]	Loss: 0.7411	LR: 0.065789
Training Epoch: 1 [6912/9494]	Loss: 0.6869	LR: 0.068421
Training Epoch: 1 [7168/9494]	Loss: 0.6925	LR: 0.071053
Training Epoch: 1 [7424/9494]	Loss: 0.7556	LR: 0.073684
Training Epoch: 1 [7680/9494]	Loss: 0.7481	LR: 0.076316
Training Epoch: 1 [7936/9494]	Loss: 0.6879	LR: 0.078947
Training Epoch: 1 [8192/9494]	Loss: 0.7084	LR: 0.081579
Training Epoch: 1 [8448/9494]	Loss: 0.8229	LR: 0.084211
Training Epoch: 1 [8704/9494]	Loss: 0.7214	LR: 0.086842
Training Epoch: 1 [8960/9494]	Loss: 0.7231	LR: 0.089474
Training Epoch: 1 [9216/9494]	Loss: 0.6844	LR: 0.092105
Training Epoch: 1 [9472/9494]	Loss: 0.6898	LR: 0.094737
Training Epoch: 1 [9494/9494]	Loss: 0.6679	LR: 0.097368
Epoch 1 - Average Train Loss: 0.8108, Train Accuracy: 0.5119
Epoch 1 training time consumed: 407.31s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0031, Accuracy: 0.5462, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-1-best.pth
Training Epoch: 2 [256/9494]	Loss: 0.6860	LR: 0.100000
Training Epoch: 2 [512/9494]	Loss: 0.7013	LR: 0.100000
Training Epoch: 2 [768/9494]	Loss: 0.6510	LR: 0.100000
Training Epoch: 2 [1024/9494]	Loss: 0.6839	LR: 0.100000
Training Epoch: 2 [1280/9494]	Loss: 0.7093	LR: 0.100000
Training Epoch: 2 [1536/9494]	Loss: 0.7642	LR: 0.100000
Training Epoch: 2 [1792/9494]	Loss: 0.6935	LR: 0.100000
Training Epoch: 2 [2048/9494]	Loss: 0.7063	LR: 0.100000
Training Epoch: 2 [2304/9494]	Loss: 0.7262	LR: 0.100000
Training Epoch: 2 [2560/9494]	Loss: 0.7320	LR: 0.100000
Training Epoch: 2 [2816/9494]	Loss: 0.7277	LR: 0.100000
Training Epoch: 2 [3072/9494]	Loss: 0.7142	LR: 0.100000
Training Epoch: 2 [3328/9494]	Loss: 0.7006	LR: 0.100000
Training Epoch: 2 [3584/9494]	Loss: 0.7183	LR: 0.100000
Training Epoch: 2 [3840/9494]	Loss: 0.6634	LR: 0.100000
Training Epoch: 2 [4096/9494]	Loss: 0.6916	LR: 0.100000
Training Epoch: 2 [4352/9494]	Loss: 0.6956	LR: 0.100000
Training Epoch: 2 [4608/9494]	Loss: 0.6856	LR: 0.100000
Training Epoch: 2 [4864/9494]	Loss: 0.7252	LR: 0.100000
Training Epoch: 2 [5120/9494]	Loss: 0.7010	LR: 0.100000
Training Epoch: 2 [5376/9494]	Loss: 0.6735	LR: 0.100000
Training Epoch: 2 [5632/9494]	Loss: 0.7028	LR: 0.100000
Training Epoch: 2 [5888/9494]	Loss: 0.6551	LR: 0.100000
Training Epoch: 2 [6144/9494]	Loss: 0.7100	LR: 0.100000
Training Epoch: 2 [6400/9494]	Loss: 0.6792	LR: 0.100000
Training Epoch: 2 [6656/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 2 [6912/9494]	Loss: 0.6881	LR: 0.100000
Training Epoch: 2 [7168/9494]	Loss: 0.6674	LR: 0.100000
Training Epoch: 2 [7424/9494]	Loss: 0.6869	LR: 0.100000
Training Epoch: 2 [7680/9494]	Loss: 0.6696	LR: 0.100000
Training Epoch: 2 [7936/9494]	Loss: 0.6521	LR: 0.100000
Training Epoch: 2 [8192/9494]	Loss: 0.7054	LR: 0.100000
Training Epoch: 2 [8448/9494]	Loss: 0.6598	LR: 0.100000
Training Epoch: 2 [8704/9494]	Loss: 0.7053	LR: 0.100000
Training Epoch: 2 [8960/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 2 [9216/9494]	Loss: 0.7331	LR: 0.100000
Training Epoch: 2 [9472/9494]	Loss: 0.6925	LR: 0.100000
Training Epoch: 2 [9494/9494]	Loss: 0.6535	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6952, Train Accuracy: 0.5610
Epoch 2 training time consumed: 136.66s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0033, Accuracy: 0.5123, Time consumed:7.94s
Training Epoch: 3 [256/9494]	Loss: 0.7345	LR: 0.100000
Training Epoch: 3 [512/9494]	Loss: 0.7665	LR: 0.100000
Training Epoch: 3 [768/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 3 [1024/9494]	Loss: 0.7163	LR: 0.100000
Training Epoch: 3 [1280/9494]	Loss: 0.6887	LR: 0.100000
Training Epoch: 3 [1536/9494]	Loss: 0.7121	LR: 0.100000
Training Epoch: 3 [1792/9494]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [2048/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 3 [2304/9494]	Loss: 0.7001	LR: 0.100000
Training Epoch: 3 [2560/9494]	Loss: 0.6959	LR: 0.100000
Training Epoch: 3 [2816/9494]	Loss: 0.6791	LR: 0.100000
Training Epoch: 3 [3072/9494]	Loss: 0.6728	LR: 0.100000
Training Epoch: 3 [3328/9494]	Loss: 0.6811	LR: 0.100000
Training Epoch: 3 [3584/9494]	Loss: 0.7162	LR: 0.100000
Training Epoch: 3 [3840/9494]	Loss: 0.6662	LR: 0.100000
Training Epoch: 3 [4096/9494]	Loss: 0.7242	LR: 0.100000
Training Epoch: 3 [4352/9494]	Loss: 0.6933	LR: 0.100000
Training Epoch: 3 [4608/9494]	Loss: 0.6690	LR: 0.100000
Training Epoch: 3 [4864/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 3 [5120/9494]	Loss: 0.6640	LR: 0.100000
Training Epoch: 3 [5376/9494]	Loss: 0.7124	LR: 0.100000
Training Epoch: 3 [5632/9494]	Loss: 0.6883	LR: 0.100000
Training Epoch: 3 [5888/9494]	Loss: 0.6627	LR: 0.100000
Training Epoch: 3 [6144/9494]	Loss: 0.7060	LR: 0.100000
Training Epoch: 3 [6400/9494]	Loss: 0.7172	LR: 0.100000
Training Epoch: 3 [6656/9494]	Loss: 0.6782	LR: 0.100000
Training Epoch: 3 [6912/9494]	Loss: 0.6676	LR: 0.100000
Training Epoch: 3 [7168/9494]	Loss: 0.7372	LR: 0.100000
Training Epoch: 3 [7424/9494]	Loss: 0.6872	LR: 0.100000
Training Epoch: 3 [7680/9494]	Loss: 0.6719	LR: 0.100000
Training Epoch: 3 [7936/9494]	Loss: 0.6743	LR: 0.100000
Training Epoch: 3 [8192/9494]	Loss: 0.6680	LR: 0.100000
Training Epoch: 3 [8448/9494]	Loss: 0.7121	LR: 0.100000
Training Epoch: 3 [8704/9494]	Loss: 0.7459	LR: 0.100000
Training Epoch: 3 [8960/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 3 [9216/9494]	Loss: 0.6714	LR: 0.100000
Training Epoch: 3 [9472/9494]	Loss: 0.7113	LR: 0.100000
Training Epoch: 3 [9494/9494]	Loss: 0.8150	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6949, Train Accuracy: 0.5652
Epoch 3 training time consumed: 136.21s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0029, Accuracy: 0.6034, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-3-best.pth
Training Epoch: 4 [256/9494]	Loss: 0.7037	LR: 0.100000
Training Epoch: 4 [512/9494]	Loss: 0.6667	LR: 0.100000
Training Epoch: 4 [768/9494]	Loss: 0.7580	LR: 0.100000
Training Epoch: 4 [1024/9494]	Loss: 0.7721	LR: 0.100000
Training Epoch: 4 [1280/9494]	Loss: 0.7043	LR: 0.100000
Training Epoch: 4 [1536/9494]	Loss: 0.6896	LR: 0.100000
Training Epoch: 4 [1792/9494]	Loss: 0.7254	LR: 0.100000
Training Epoch: 4 [2048/9494]	Loss: 0.7323	LR: 0.100000
Training Epoch: 4 [2304/9494]	Loss: 0.6888	LR: 0.100000
Training Epoch: 4 [2560/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 4 [2816/9494]	Loss: 0.6605	LR: 0.100000
Training Epoch: 4 [3072/9494]	Loss: 0.6702	LR: 0.100000
Training Epoch: 4 [3328/9494]	Loss: 0.6941	LR: 0.100000
Training Epoch: 4 [3584/9494]	Loss: 0.6708	LR: 0.100000
Training Epoch: 4 [3840/9494]	Loss: 0.6853	LR: 0.100000
Training Epoch: 4 [4096/9494]	Loss: 0.6882	LR: 0.100000
Training Epoch: 4 [4352/9494]	Loss: 0.6790	LR: 0.100000
Training Epoch: 4 [4608/9494]	Loss: 0.6726	LR: 0.100000
Training Epoch: 4 [4864/9494]	Loss: 0.6847	LR: 0.100000
Training Epoch: 4 [5120/9494]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [5376/9494]	Loss: 0.6943	LR: 0.100000
Training Epoch: 4 [5632/9494]	Loss: 0.6580	LR: 0.100000
Training Epoch: 4 [5888/9494]	Loss: 0.6916	LR: 0.100000
Training Epoch: 4 [6144/9494]	Loss: 0.6902	LR: 0.100000
Training Epoch: 4 [6400/9494]	Loss: 0.6577	LR: 0.100000
Training Epoch: 4 [6656/9494]	Loss: 0.7127	LR: 0.100000
Training Epoch: 4 [6912/9494]	Loss: 0.6475	LR: 0.100000
Training Epoch: 4 [7168/9494]	Loss: 0.6861	LR: 0.100000
Training Epoch: 4 [7424/9494]	Loss: 0.6570	LR: 0.100000
Training Epoch: 4 [7680/9494]	Loss: 0.7086	LR: 0.100000
Training Epoch: 4 [7936/9494]	Loss: 0.6706	LR: 0.100000
Training Epoch: 4 [8192/9494]	Loss: 0.7014	LR: 0.100000
Training Epoch: 4 [8448/9494]	Loss: 0.6983	LR: 0.100000
Training Epoch: 4 [8704/9494]	Loss: 0.6645	LR: 0.100000
Training Epoch: 4 [8960/9494]	Loss: 0.6647	LR: 0.100000
Training Epoch: 4 [9216/9494]	Loss: 0.6596	LR: 0.100000
Training Epoch: 4 [9472/9494]	Loss: 0.7009	LR: 0.100000
Training Epoch: 4 [9494/9494]	Loss: 0.7057	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6879, Train Accuracy: 0.5742
Epoch 4 training time consumed: 136.14s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0033, Accuracy: 0.5550, Time consumed:7.95s
Training Epoch: 5 [256/9494]	Loss: 0.6602	LR: 0.100000
Training Epoch: 5 [512/9494]	Loss: 0.7198	LR: 0.100000
Training Epoch: 5 [768/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 5 [1024/9494]	Loss: 0.6888	LR: 0.100000
Training Epoch: 5 [1280/9494]	Loss: 0.6536	LR: 0.100000
Training Epoch: 5 [1536/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 5 [1792/9494]	Loss: 0.7028	LR: 0.100000
Training Epoch: 5 [2048/9494]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [2304/9494]	Loss: 0.6672	LR: 0.100000
Training Epoch: 5 [2560/9494]	Loss: 0.6867	LR: 0.100000
Training Epoch: 5 [2816/9494]	Loss: 0.6632	LR: 0.100000
Training Epoch: 5 [3072/9494]	Loss: 0.6717	LR: 0.100000
Training Epoch: 5 [3328/9494]	Loss: 0.6590	LR: 0.100000
Training Epoch: 5 [3584/9494]	Loss: 0.6455	LR: 0.100000
Training Epoch: 5 [3840/9494]	Loss: 0.6466	LR: 0.100000
Training Epoch: 5 [4096/9494]	Loss: 0.6560	LR: 0.100000
Training Epoch: 5 [4352/9494]	Loss: 0.6656	LR: 0.100000
Training Epoch: 5 [4608/9494]	Loss: 0.7207	LR: 0.100000
Training Epoch: 5 [4864/9494]	Loss: 0.6672	LR: 0.100000
Training Epoch: 5 [5120/9494]	Loss: 0.6650	LR: 0.100000
Training Epoch: 5 [5376/9494]	Loss: 0.6791	LR: 0.100000
Training Epoch: 5 [5632/9494]	Loss: 0.6767	LR: 0.100000
Training Epoch: 5 [5888/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 5 [6144/9494]	Loss: 0.6689	LR: 0.100000
Training Epoch: 5 [6400/9494]	Loss: 0.6817	LR: 0.100000
Training Epoch: 5 [6656/9494]	Loss: 0.6520	LR: 0.100000
Training Epoch: 5 [6912/9494]	Loss: 0.6662	LR: 0.100000
Training Epoch: 5 [7168/9494]	Loss: 0.6753	LR: 0.100000
Training Epoch: 5 [7424/9494]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [7680/9494]	Loss: 0.6783	LR: 0.100000
Training Epoch: 5 [7936/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 5 [8192/9494]	Loss: 0.6883	LR: 0.100000
Training Epoch: 5 [8448/9494]	Loss: 0.6722	LR: 0.100000
Training Epoch: 5 [8704/9494]	Loss: 0.6578	LR: 0.100000
Training Epoch: 5 [8960/9494]	Loss: 0.6685	LR: 0.100000
Training Epoch: 5 [9216/9494]	Loss: 0.6703	LR: 0.100000
Training Epoch: 5 [9472/9494]	Loss: 0.6466	LR: 0.100000
Training Epoch: 5 [9494/9494]	Loss: 0.6342	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6723, Train Accuracy: 0.5949
Epoch 5 training time consumed: 136.06s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0032, Accuracy: 0.5303, Time consumed:7.97s
Training Epoch: 6 [256/9494]	Loss: 0.6501	LR: 0.100000
Training Epoch: 6 [512/9494]	Loss: 0.7094	LR: 0.100000
Training Epoch: 6 [768/9494]	Loss: 0.7312	LR: 0.100000
Training Epoch: 6 [1024/9494]	Loss: 0.7556	LR: 0.100000
Training Epoch: 6 [1280/9494]	Loss: 0.6986	LR: 0.100000
Training Epoch: 6 [1536/9494]	Loss: 0.6835	LR: 0.100000
Training Epoch: 6 [1792/9494]	Loss: 0.6725	LR: 0.100000
Training Epoch: 6 [2048/9494]	Loss: 0.6678	LR: 0.100000
Training Epoch: 6 [2304/9494]	Loss: 0.6950	LR: 0.100000
Training Epoch: 6 [2560/9494]	Loss: 0.6918	LR: 0.100000
Training Epoch: 6 [2816/9494]	Loss: 0.6812	LR: 0.100000
Training Epoch: 6 [3072/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 6 [3328/9494]	Loss: 0.6908	LR: 0.100000
Training Epoch: 6 [3584/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 6 [3840/9494]	Loss: 0.6656	LR: 0.100000
Training Epoch: 6 [4096/9494]	Loss: 0.6736	LR: 0.100000
Training Epoch: 6 [4352/9494]	Loss: 0.6585	LR: 0.100000
Training Epoch: 6 [4608/9494]	Loss: 0.6655	LR: 0.100000
Training Epoch: 6 [4864/9494]	Loss: 0.6688	LR: 0.100000
Training Epoch: 6 [5120/9494]	Loss: 0.6774	LR: 0.100000
Training Epoch: 6 [5376/9494]	Loss: 0.6765	LR: 0.100000
Training Epoch: 6 [5632/9494]	Loss: 0.6596	LR: 0.100000
Training Epoch: 6 [5888/9494]	Loss: 0.7124	LR: 0.100000
Training Epoch: 6 [6144/9494]	Loss: 0.6603	LR: 0.100000
Training Epoch: 6 [6400/9494]	Loss: 0.6535	LR: 0.100000
Training Epoch: 6 [6656/9494]	Loss: 0.6662	LR: 0.100000
Training Epoch: 6 [6912/9494]	Loss: 0.6694	LR: 0.100000
Training Epoch: 6 [7168/9494]	Loss: 0.6359	LR: 0.100000
Training Epoch: 6 [7424/9494]	Loss: 0.6516	LR: 0.100000
Training Epoch: 6 [7680/9494]	Loss: 0.6690	LR: 0.100000
Training Epoch: 6 [7936/9494]	Loss: 0.6489	LR: 0.100000
Training Epoch: 6 [8192/9494]	Loss: 0.6665	LR: 0.100000
Training Epoch: 6 [8448/9494]	Loss: 0.6850	LR: 0.100000
Training Epoch: 6 [8704/9494]	Loss: 0.6331	LR: 0.100000
Training Epoch: 6 [8960/9494]	Loss: 0.7209	LR: 0.100000
Training Epoch: 6 [9216/9494]	Loss: 0.6576	LR: 0.100000
Training Epoch: 6 [9472/9494]	Loss: 0.6634	LR: 0.100000
Training Epoch: 6 [9494/9494]	Loss: 0.7833	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6767, Train Accuracy: 0.5886
Epoch 6 training time consumed: 137.56s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5535, Time consumed:7.89s
Training Epoch: 7 [256/9494]	Loss: 0.6515	LR: 0.100000
Training Epoch: 7 [512/9494]	Loss: 0.6601	LR: 0.100000
Training Epoch: 7 [768/9494]	Loss: 0.6885	LR: 0.100000
Training Epoch: 7 [1024/9494]	Loss: 0.6743	LR: 0.100000
Training Epoch: 7 [1280/9494]	Loss: 0.6845	LR: 0.100000
Training Epoch: 7 [1536/9494]	Loss: 0.6927	LR: 0.100000
Training Epoch: 7 [1792/9494]	Loss: 0.6880	LR: 0.100000
Training Epoch: 7 [2048/9494]	Loss: 0.6811	LR: 0.100000
Training Epoch: 7 [2304/9494]	Loss: 0.6826	LR: 0.100000
Training Epoch: 7 [2560/9494]	Loss: 0.6779	LR: 0.100000
Training Epoch: 7 [2816/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 7 [3072/9494]	Loss: 0.6906	LR: 0.100000
Training Epoch: 7 [3328/9494]	Loss: 0.6797	LR: 0.100000
Training Epoch: 7 [3584/9494]	Loss: 0.6655	LR: 0.100000
Training Epoch: 7 [3840/9494]	Loss: 0.6745	LR: 0.100000
Training Epoch: 7 [4096/9494]	Loss: 0.6892	LR: 0.100000
Training Epoch: 7 [4352/9494]	Loss: 0.6929	LR: 0.100000
Training Epoch: 7 [4608/9494]	Loss: 0.6819	LR: 0.100000
Training Epoch: 7 [4864/9494]	Loss: 0.6789	LR: 0.100000
Training Epoch: 7 [5120/9494]	Loss: 0.6816	LR: 0.100000
Training Epoch: 7 [5376/9494]	Loss: 0.6988	LR: 0.100000
Training Epoch: 7 [5632/9494]	Loss: 0.6838	LR: 0.100000
Training Epoch: 7 [5888/9494]	Loss: 0.6883	LR: 0.100000
Training Epoch: 7 [6144/9494]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [6400/9494]	Loss: 0.6711	LR: 0.100000
Training Epoch: 7 [6656/9494]	Loss: 0.6570	LR: 0.100000
Training Epoch: 7 [6912/9494]	Loss: 0.6736	LR: 0.100000
Training Epoch: 7 [7168/9494]	Loss: 0.6718	LR: 0.100000
Training Epoch: 7 [7424/9494]	Loss: 0.6638	LR: 0.100000
Training Epoch: 7 [7680/9494]	Loss: 0.6547	LR: 0.100000
Training Epoch: 7 [7936/9494]	Loss: 0.6441	LR: 0.100000
Training Epoch: 7 [8192/9494]	Loss: 0.6371	LR: 0.100000
Training Epoch: 7 [8448/9494]	Loss: 0.6530	LR: 0.100000
Training Epoch: 7 [8704/9494]	Loss: 0.6518	LR: 0.100000
Training Epoch: 7 [8960/9494]	Loss: 0.6620	LR: 0.100000
Training Epoch: 7 [9216/9494]	Loss: 0.6261	LR: 0.100000
Training Epoch: 7 [9472/9494]	Loss: 0.6741	LR: 0.100000
Training Epoch: 7 [9494/9494]	Loss: 0.6607	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6721, Train Accuracy: 0.5822
Epoch 7 training time consumed: 136.87s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.5758, Time consumed:7.95s
Training Epoch: 8 [256/9494]	Loss: 0.6475	LR: 0.100000
Training Epoch: 8 [512/9494]	Loss: 0.6680	LR: 0.100000
Training Epoch: 8 [768/9494]	Loss: 0.6563	LR: 0.100000
Training Epoch: 8 [1024/9494]	Loss: 0.6564	LR: 0.100000
Training Epoch: 8 [1280/9494]	Loss: 0.6736	LR: 0.100000
Training Epoch: 8 [1536/9494]	Loss: 0.6699	LR: 0.100000
Training Epoch: 8 [1792/9494]	Loss: 0.6488	LR: 0.100000
Training Epoch: 8 [2048/9494]	Loss: 0.6469	LR: 0.100000
Training Epoch: 8 [2304/9494]	Loss: 0.6442	LR: 0.100000
Training Epoch: 8 [2560/9494]	Loss: 0.6259	LR: 0.100000
Training Epoch: 8 [2816/9494]	Loss: 0.6420	LR: 0.100000
Training Epoch: 8 [3072/9494]	Loss: 0.6335	LR: 0.100000
Training Epoch: 8 [3328/9494]	Loss: 0.6369	LR: 0.100000
Training Epoch: 8 [3584/9494]	Loss: 0.6421	LR: 0.100000
Training Epoch: 8 [3840/9494]	Loss: 0.6210	LR: 0.100000
Training Epoch: 8 [4096/9494]	Loss: 0.6478	LR: 0.100000
Training Epoch: 8 [4352/9494]	Loss: 0.5999	LR: 0.100000
Training Epoch: 8 [4608/9494]	Loss: 0.5915	LR: 0.100000
Training Epoch: 8 [4864/9494]	Loss: 0.6202	LR: 0.100000
Training Epoch: 8 [5120/9494]	Loss: 0.5953	LR: 0.100000
Training Epoch: 8 [5376/9494]	Loss: 0.6426	LR: 0.100000
Training Epoch: 8 [5632/9494]	Loss: 0.6377	LR: 0.100000
Training Epoch: 8 [5888/9494]	Loss: 0.6207	LR: 0.100000
Training Epoch: 8 [6144/9494]	Loss: 0.6275	LR: 0.100000
Training Epoch: 8 [6400/9494]	Loss: 0.6023	LR: 0.100000
Training Epoch: 8 [6656/9494]	Loss: 0.5772	LR: 0.100000
Training Epoch: 8 [6912/9494]	Loss: 0.6143	LR: 0.100000
Training Epoch: 8 [7168/9494]	Loss: 0.6080	LR: 0.100000
Training Epoch: 8 [7424/9494]	Loss: 0.6238	LR: 0.100000
Training Epoch: 8 [7680/9494]	Loss: 0.5680	LR: 0.100000
Training Epoch: 8 [7936/9494]	Loss: 0.6058	LR: 0.100000
Training Epoch: 8 [8192/9494]	Loss: 0.5806	LR: 0.100000
Training Epoch: 8 [8448/9494]	Loss: 0.6219	LR: 0.100000
Training Epoch: 8 [8704/9494]	Loss: 0.5784	LR: 0.100000
Training Epoch: 8 [8960/9494]	Loss: 0.7183	LR: 0.100000
Training Epoch: 8 [9216/9494]	Loss: 0.5986	LR: 0.100000
Training Epoch: 8 [9472/9494]	Loss: 0.6259	LR: 0.100000
Training Epoch: 8 [9494/9494]	Loss: 0.8114	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6280, Train Accuracy: 0.6529
Epoch 8 training time consumed: 137.63s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0029, Accuracy: 0.6557, Time consumed:7.87s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-8-best.pth
Training Epoch: 9 [256/9494]	Loss: 0.6777	LR: 0.100000
Training Epoch: 9 [512/9494]	Loss: 0.7035	LR: 0.100000
Training Epoch: 9 [768/9494]	Loss: 0.6302	LR: 0.100000
Training Epoch: 9 [1024/9494]	Loss: 0.6386	LR: 0.100000
Training Epoch: 9 [1280/9494]	Loss: 0.6338	LR: 0.100000
Training Epoch: 9 [1536/9494]	Loss: 0.6596	LR: 0.100000
Training Epoch: 9 [1792/9494]	Loss: 0.6778	LR: 0.100000
Training Epoch: 9 [2048/9494]	Loss: 0.5854	LR: 0.100000
Training Epoch: 9 [2304/9494]	Loss: 0.6706	LR: 0.100000
Training Epoch: 9 [2560/9494]	Loss: 0.6359	LR: 0.100000
Training Epoch: 9 [2816/9494]	Loss: 0.5930	LR: 0.100000
Training Epoch: 9 [3072/9494]	Loss: 0.6010	LR: 0.100000
Training Epoch: 9 [3328/9494]	Loss: 0.6102	LR: 0.100000
Training Epoch: 9 [3584/9494]	Loss: 0.6084	LR: 0.100000
Training Epoch: 9 [3840/9494]	Loss: 0.6249	LR: 0.100000
Training Epoch: 9 [4096/9494]	Loss: 0.6106	LR: 0.100000
Training Epoch: 9 [4352/9494]	Loss: 0.6043	LR: 0.100000
Training Epoch: 9 [4608/9494]	Loss: 0.6269	LR: 0.100000
Training Epoch: 9 [4864/9494]	Loss: 0.5700	LR: 0.100000
Training Epoch: 9 [5120/9494]	Loss: 0.5829	LR: 0.100000
Training Epoch: 9 [5376/9494]	Loss: 0.5622	LR: 0.100000
Training Epoch: 9 [5632/9494]	Loss: 0.5570	LR: 0.100000
Training Epoch: 9 [5888/9494]	Loss: 0.5596	LR: 0.100000
Training Epoch: 9 [6144/9494]	Loss: 0.5947	LR: 0.100000
Training Epoch: 9 [6400/9494]	Loss: 0.5463	LR: 0.100000
Training Epoch: 9 [6656/9494]	Loss: 0.6133	LR: 0.100000
Training Epoch: 9 [6912/9494]	Loss: 0.6145	LR: 0.100000
Training Epoch: 9 [7168/9494]	Loss: 0.6401	LR: 0.100000
Training Epoch: 9 [7424/9494]	Loss: 0.5500	LR: 0.100000
Training Epoch: 9 [7680/9494]	Loss: 0.5787	LR: 0.100000
Training Epoch: 9 [7936/9494]	Loss: 0.5791	LR: 0.100000
Training Epoch: 9 [8192/9494]	Loss: 0.5805	LR: 0.100000
Training Epoch: 9 [8448/9494]	Loss: 0.6234	LR: 0.100000
Training Epoch: 9 [8704/9494]	Loss: 0.5760	LR: 0.100000
Training Epoch: 9 [8960/9494]	Loss: 0.5975	LR: 0.100000
Training Epoch: 9 [9216/9494]	Loss: 0.5730	LR: 0.100000
Training Epoch: 9 [9472/9494]	Loss: 0.5719	LR: 0.100000
Training Epoch: 9 [9494/9494]	Loss: 0.9331	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6079, Train Accuracy: 0.6742
Epoch 9 training time consumed: 137.71s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0032, Accuracy: 0.6155, Time consumed:7.93s
Training Epoch: 10 [256/9494]	Loss: 0.6419	LR: 0.020000
Training Epoch: 10 [512/9494]	Loss: 0.6793	LR: 0.020000
Training Epoch: 10 [768/9494]	Loss: 0.6452	LR: 0.020000
Training Epoch: 10 [1024/9494]	Loss: 0.6518	LR: 0.020000
Training Epoch: 10 [1280/9494]	Loss: 0.5688	LR: 0.020000
Training Epoch: 10 [1536/9494]	Loss: 0.5812	LR: 0.020000
Training Epoch: 10 [1792/9494]	Loss: 0.5972	LR: 0.020000
Training Epoch: 10 [2048/9494]	Loss: 0.5081	LR: 0.020000
Training Epoch: 10 [2304/9494]	Loss: 0.5286	LR: 0.020000
Training Epoch: 10 [2560/9494]	Loss: 0.5609	LR: 0.020000
Training Epoch: 10 [2816/9494]	Loss: 0.6077	LR: 0.020000
Training Epoch: 10 [3072/9494]	Loss: 0.5892	LR: 0.020000
Training Epoch: 10 [3328/9494]	Loss: 0.5651	LR: 0.020000
Training Epoch: 10 [3584/9494]	Loss: 0.5637	LR: 0.020000
Training Epoch: 10 [3840/9494]	Loss: 0.5764	LR: 0.020000
Training Epoch: 10 [4096/9494]	Loss: 0.6183	LR: 0.020000
Training Epoch: 10 [4352/9494]	Loss: 0.5595	LR: 0.020000
Training Epoch: 10 [4608/9494]	Loss: 0.6027	LR: 0.020000
Training Epoch: 10 [4864/9494]	Loss: 0.5378	LR: 0.020000
Training Epoch: 10 [5120/9494]	Loss: 0.5533	LR: 0.020000
Training Epoch: 10 [5376/9494]	Loss: 0.5530	LR: 0.020000
Training Epoch: 10 [5632/9494]	Loss: 0.5518	LR: 0.020000
Training Epoch: 10 [5888/9494]	Loss: 0.6211	LR: 0.020000
Training Epoch: 10 [6144/9494]	Loss: 0.5518	LR: 0.020000
Training Epoch: 10 [6400/9494]	Loss: 0.5817	LR: 0.020000
Training Epoch: 10 [6656/9494]	Loss: 0.6010	LR: 0.020000
Training Epoch: 10 [6912/9494]	Loss: 0.5748	LR: 0.020000
Training Epoch: 10 [7168/9494]	Loss: 0.5675	LR: 0.020000
Training Epoch: 10 [7424/9494]	Loss: 0.5453	LR: 0.020000
Training Epoch: 10 [7680/9494]	Loss: 0.5100	LR: 0.020000
Training Epoch: 10 [7936/9494]	Loss: 0.5357	LR: 0.020000
Training Epoch: 10 [8192/9494]	Loss: 0.5545	LR: 0.020000
Training Epoch: 10 [8448/9494]	Loss: 0.5024	LR: 0.020000
Training Epoch: 10 [8704/9494]	Loss: 0.5579	LR: 0.020000
Training Epoch: 10 [8960/9494]	Loss: 0.5442	LR: 0.020000
Training Epoch: 10 [9216/9494]	Loss: 0.5738	LR: 0.020000
Training Epoch: 10 [9472/9494]	Loss: 0.5417	LR: 0.020000
Training Epoch: 10 [9494/9494]	Loss: 0.6074	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5732, Train Accuracy: 0.7046
Epoch 10 training time consumed: 141.79s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0032, Accuracy: 0.5952, Time consumed:8.44s
Training Epoch: 11 [256/9494]	Loss: 0.5886	LR: 0.020000
Training Epoch: 11 [512/9494]	Loss: 0.5462	LR: 0.020000
Training Epoch: 11 [768/9494]	Loss: 0.5424	LR: 0.020000
Training Epoch: 11 [1024/9494]	Loss: 0.5570	LR: 0.020000
Training Epoch: 11 [1280/9494]	Loss: 0.5144	LR: 0.020000
Training Epoch: 11 [1536/9494]	Loss: 0.5163	LR: 0.020000
Training Epoch: 11 [1792/9494]	Loss: 0.4898	LR: 0.020000
Training Epoch: 11 [2048/9494]	Loss: 0.5102	LR: 0.020000
Training Epoch: 11 [2304/9494]	Loss: 0.5128	LR: 0.020000
Training Epoch: 11 [2560/9494]	Loss: 0.4944	LR: 0.020000
Training Epoch: 11 [2816/9494]	Loss: 0.5289	LR: 0.020000
Training Epoch: 11 [3072/9494]	Loss: 0.5819	LR: 0.020000
Training Epoch: 11 [3328/9494]	Loss: 0.4339	LR: 0.020000
Training Epoch: 11 [3584/9494]	Loss: 0.4963	LR: 0.020000
Training Epoch: 11 [3840/9494]	Loss: 0.4710	LR: 0.020000
Training Epoch: 11 [4096/9494]	Loss: 0.4988	LR: 0.020000
Training Epoch: 11 [4352/9494]	Loss: 0.5420	LR: 0.020000
Training Epoch: 11 [4608/9494]	Loss: 0.4905	LR: 0.020000
Training Epoch: 11 [4864/9494]	Loss: 0.4646	LR: 0.020000
Training Epoch: 11 [5120/9494]	Loss: 0.4371	LR: 0.020000
Training Epoch: 11 [5376/9494]	Loss: 0.4475	LR: 0.020000
Training Epoch: 11 [5632/9494]	Loss: 0.4553	LR: 0.020000
Training Epoch: 11 [5888/9494]	Loss: 0.5130	LR: 0.020000
Training Epoch: 11 [6144/9494]	Loss: 0.4553	LR: 0.020000
Training Epoch: 11 [6400/9494]	Loss: 0.4552	LR: 0.020000
Training Epoch: 11 [6656/9494]	Loss: 0.4810	LR: 0.020000
Training Epoch: 11 [6912/9494]	Loss: 0.4474	LR: 0.020000
Training Epoch: 11 [7168/9494]	Loss: 0.4754	LR: 0.020000
Training Epoch: 11 [7424/9494]	Loss: 0.4544	LR: 0.020000
Training Epoch: 11 [7680/9494]	Loss: 0.4576	LR: 0.020000
Training Epoch: 11 [7936/9494]	Loss: 0.4543	LR: 0.020000
Training Epoch: 11 [8192/9494]	Loss: 0.5181	LR: 0.020000
Training Epoch: 11 [8448/9494]	Loss: 0.4162	LR: 0.020000
Training Epoch: 11 [8704/9494]	Loss: 0.5143	LR: 0.020000
Training Epoch: 11 [8960/9494]	Loss: 0.5157	LR: 0.020000
Training Epoch: 11 [9216/9494]	Loss: 0.4654	LR: 0.020000
Training Epoch: 11 [9472/9494]	Loss: 0.4671	LR: 0.020000
Training Epoch: 11 [9494/9494]	Loss: 0.5733	LR: 0.020000
Epoch 11 - Average Train Loss: 0.4924, Train Accuracy: 0.7672
Epoch 11 training time consumed: 141.99s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0027, Accuracy: 0.7036, Time consumed:8.03s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-11-best.pth
Training Epoch: 12 [256/9494]	Loss: 0.4526	LR: 0.020000
Training Epoch: 12 [512/9494]	Loss: 0.5073	LR: 0.020000
Training Epoch: 12 [768/9494]	Loss: 0.4698	LR: 0.020000
Training Epoch: 12 [1024/9494]	Loss: 0.5918	LR: 0.020000
Training Epoch: 12 [1280/9494]	Loss: 0.5060	LR: 0.020000
Training Epoch: 12 [1536/9494]	Loss: 0.4642	LR: 0.020000
Training Epoch: 12 [1792/9494]	Loss: 0.4700	LR: 0.020000
Training Epoch: 12 [2048/9494]	Loss: 0.4659	LR: 0.020000
Training Epoch: 12 [2304/9494]	Loss: 0.4020	LR: 0.020000
Training Epoch: 12 [2560/9494]	Loss: 0.4810	LR: 0.020000
Training Epoch: 12 [2816/9494]	Loss: 0.4824	LR: 0.020000
Training Epoch: 12 [3072/9494]	Loss: 0.5424	LR: 0.020000
Training Epoch: 12 [3328/9494]	Loss: 0.3935	LR: 0.020000
Training Epoch: 12 [3584/9494]	Loss: 0.4659	LR: 0.020000
Training Epoch: 12 [3840/9494]	Loss: 0.4736	LR: 0.020000
Training Epoch: 12 [4096/9494]	Loss: 0.4133	LR: 0.020000
Training Epoch: 12 [4352/9494]	Loss: 0.4543	LR: 0.020000
Training Epoch: 12 [4608/9494]	Loss: 0.4383	LR: 0.020000
Training Epoch: 12 [4864/9494]	Loss: 0.4258	LR: 0.020000
Training Epoch: 12 [5120/9494]	Loss: 0.4104	LR: 0.020000
Training Epoch: 12 [5376/9494]	Loss: 0.4228	LR: 0.020000
Training Epoch: 12 [5632/9494]	Loss: 0.4712	LR: 0.020000
Training Epoch: 12 [5888/9494]	Loss: 0.3913	LR: 0.020000
Training Epoch: 12 [6144/9494]	Loss: 0.3891	LR: 0.020000
Training Epoch: 12 [6400/9494]	Loss: 0.3857	LR: 0.020000
Training Epoch: 12 [6656/9494]	Loss: 0.4695	LR: 0.020000
Training Epoch: 12 [6912/9494]	Loss: 0.3940	LR: 0.020000
Training Epoch: 12 [7168/9494]	Loss: 0.3819	LR: 0.020000
Training Epoch: 12 [7424/9494]	Loss: 0.4214	LR: 0.020000
Training Epoch: 12 [7680/9494]	Loss: 0.4665	LR: 0.020000
Training Epoch: 12 [7936/9494]	Loss: 0.4251	LR: 0.020000
Training Epoch: 12 [8192/9494]	Loss: 0.4123	LR: 0.020000
Training Epoch: 12 [8448/9494]	Loss: 0.3755	LR: 0.020000
Training Epoch: 12 [8704/9494]	Loss: 0.3534	LR: 0.020000
Training Epoch: 12 [8960/9494]	Loss: 0.4709	LR: 0.020000
Training Epoch: 12 [9216/9494]	Loss: 0.5003	LR: 0.020000
Training Epoch: 12 [9472/9494]	Loss: 0.4350	LR: 0.020000
Training Epoch: 12 [9494/9494]	Loss: 0.4199	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4453, Train Accuracy: 0.7947
Epoch 12 training time consumed: 138.57s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0031, Accuracy: 0.6373, Time consumed:8.04s
Training Epoch: 13 [256/9494]	Loss: 0.4363	LR: 0.020000
Training Epoch: 13 [512/9494]	Loss: 0.3873	LR: 0.020000
Training Epoch: 13 [768/9494]	Loss: 0.4320	LR: 0.020000
Training Epoch: 13 [1024/9494]	Loss: 0.4500	LR: 0.020000
Training Epoch: 13 [1280/9494]	Loss: 0.3943	LR: 0.020000
Training Epoch: 13 [1536/9494]	Loss: 0.4437	LR: 0.020000
Training Epoch: 13 [1792/9494]	Loss: 0.3826	LR: 0.020000
Training Epoch: 13 [2048/9494]	Loss: 0.4822	LR: 0.020000
Training Epoch: 13 [2304/9494]	Loss: 0.3867	LR: 0.020000
Training Epoch: 13 [2560/9494]	Loss: 0.4214	LR: 0.020000
Training Epoch: 13 [2816/9494]	Loss: 0.3508	LR: 0.020000
Training Epoch: 13 [3072/9494]	Loss: 0.4067	LR: 0.020000
Training Epoch: 13 [3328/9494]	Loss: 0.4107	LR: 0.020000
Training Epoch: 13 [3584/9494]	Loss: 0.4030	LR: 0.020000
Training Epoch: 13 [3840/9494]	Loss: 0.4481	LR: 0.020000
Training Epoch: 13 [4096/9494]	Loss: 0.3934	LR: 0.020000
Training Epoch: 13 [4352/9494]	Loss: 0.4116	LR: 0.020000
Training Epoch: 13 [4608/9494]	Loss: 0.4104	LR: 0.020000
Training Epoch: 13 [4864/9494]	Loss: 0.3970	LR: 0.020000
Training Epoch: 13 [5120/9494]	Loss: 0.4244	LR: 0.020000
Training Epoch: 13 [5376/9494]	Loss: 0.4411	LR: 0.020000
Training Epoch: 13 [5632/9494]	Loss: 0.4191	LR: 0.020000
Training Epoch: 13 [5888/9494]	Loss: 0.4315	LR: 0.020000
Training Epoch: 13 [6144/9494]	Loss: 0.5143	LR: 0.020000
Training Epoch: 13 [6400/9494]	Loss: 0.4272	LR: 0.020000
Training Epoch: 13 [6656/9494]	Loss: 0.4036	LR: 0.020000
Training Epoch: 13 [6912/9494]	Loss: 0.4295	LR: 0.020000
Training Epoch: 13 [7168/9494]	Loss: 0.3794	LR: 0.020000
Training Epoch: 13 [7424/9494]	Loss: 0.4299	LR: 0.020000
Training Epoch: 13 [7680/9494]	Loss: 0.3998	LR: 0.020000
Training Epoch: 13 [7936/9494]	Loss: 0.4228	LR: 0.020000
Training Epoch: 13 [8192/9494]	Loss: 0.3473	LR: 0.020000
Training Epoch: 13 [8448/9494]	Loss: 0.4024	LR: 0.020000
Training Epoch: 13 [8704/9494]	Loss: 0.3874	LR: 0.020000
Training Epoch: 13 [8960/9494]	Loss: 0.3768	LR: 0.020000
Training Epoch: 13 [9216/9494]	Loss: 0.4067	LR: 0.020000
Training Epoch: 13 [9472/9494]	Loss: 0.4383	LR: 0.020000
Training Epoch: 13 [9494/9494]	Loss: 0.2703	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4140, Train Accuracy: 0.8124
Epoch 13 training time consumed: 138.85s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0028, Accuracy: 0.6692, Time consumed:7.95s
Training Epoch: 14 [256/9494]	Loss: 0.4120	LR: 0.020000
Training Epoch: 14 [512/9494]	Loss: 0.4221	LR: 0.020000
Training Epoch: 14 [768/9494]	Loss: 0.3569	LR: 0.020000
Training Epoch: 14 [1024/9494]	Loss: 0.3699	LR: 0.020000
Training Epoch: 14 [1280/9494]	Loss: 0.3939	LR: 0.020000
Training Epoch: 14 [1536/9494]	Loss: 0.4087	LR: 0.020000
Training Epoch: 14 [1792/9494]	Loss: 0.4112	LR: 0.020000
Training Epoch: 14 [2048/9494]	Loss: 0.3521	LR: 0.020000
Training Epoch: 14 [2304/9494]	Loss: 0.3497	LR: 0.020000
Training Epoch: 14 [2560/9494]	Loss: 0.4071	LR: 0.020000
Training Epoch: 14 [2816/9494]	Loss: 0.4061	LR: 0.020000
Training Epoch: 14 [3072/9494]	Loss: 0.3348	LR: 0.020000
Training Epoch: 14 [3328/9494]	Loss: 0.3583	LR: 0.020000
Training Epoch: 14 [3584/9494]	Loss: 0.3683	LR: 0.020000
Training Epoch: 14 [3840/9494]	Loss: 0.2873	LR: 0.020000
Training Epoch: 14 [4096/9494]	Loss: 0.3701	LR: 0.020000
Training Epoch: 14 [4352/9494]	Loss: 0.3478	LR: 0.020000
Training Epoch: 14 [4608/9494]	Loss: 0.3196	LR: 0.020000
Training Epoch: 14 [4864/9494]	Loss: 0.3518	LR: 0.020000
Training Epoch: 14 [5120/9494]	Loss: 0.3572	LR: 0.020000
Training Epoch: 14 [5376/9494]	Loss: 0.3536	LR: 0.020000
Training Epoch: 14 [5632/9494]	Loss: 0.4227	LR: 0.020000
Training Epoch: 14 [5888/9494]	Loss: 0.3884	LR: 0.020000
Training Epoch: 14 [6144/9494]	Loss: 0.3428	LR: 0.020000
Training Epoch: 14 [6400/9494]	Loss: 0.2947	LR: 0.020000
Training Epoch: 14 [6656/9494]	Loss: 0.3281	LR: 0.020000
Training Epoch: 14 [6912/9494]	Loss: 0.2723	LR: 0.020000
Training Epoch: 14 [7168/9494]	Loss: 0.3869	LR: 0.020000
Training Epoch: 14 [7424/9494]	Loss: 0.3129	LR: 0.020000
Training Epoch: 14 [7680/9494]	Loss: 0.3230	LR: 0.020000
Training Epoch: 14 [7936/9494]	Loss: 0.3621	LR: 0.020000
Training Epoch: 14 [8192/9494]	Loss: 0.3198	LR: 0.020000
Training Epoch: 14 [8448/9494]	Loss: 0.3383	LR: 0.020000
Training Epoch: 14 [8704/9494]	Loss: 0.3935	LR: 0.020000
Training Epoch: 14 [8960/9494]	Loss: 0.2857	LR: 0.020000
Training Epoch: 14 [9216/9494]	Loss: 0.3364	LR: 0.020000
Training Epoch: 14 [9472/9494]	Loss: 0.3485	LR: 0.020000
Training Epoch: 14 [9494/9494]	Loss: 0.2352	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3563, Train Accuracy: 0.8418
Epoch 14 training time consumed: 138.60s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0017, Accuracy: 0.8223, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-14-best.pth
Training Epoch: 15 [256/9494]	Loss: 0.3439	LR: 0.020000
Training Epoch: 15 [512/9494]	Loss: 0.4503	LR: 0.020000
Training Epoch: 15 [768/9494]	Loss: 0.4007	LR: 0.020000
Training Epoch: 15 [1024/9494]	Loss: 0.3937	LR: 0.020000
Training Epoch: 15 [1280/9494]	Loss: 0.3314	LR: 0.020000
Training Epoch: 15 [1536/9494]	Loss: 0.3436	LR: 0.020000
Training Epoch: 15 [1792/9494]	Loss: 0.3676	LR: 0.020000
Training Epoch: 15 [2048/9494]	Loss: 0.3840	LR: 0.020000
Training Epoch: 15 [2304/9494]	Loss: 0.4368	LR: 0.020000
Training Epoch: 15 [2560/9494]	Loss: 0.3111	LR: 0.020000
Training Epoch: 15 [2816/9494]	Loss: 0.3459	LR: 0.020000
Training Epoch: 15 [3072/9494]	Loss: 0.3011	LR: 0.020000
Training Epoch: 15 [3328/9494]	Loss: 0.3659	LR: 0.020000
Training Epoch: 15 [3584/9494]	Loss: 0.3794	LR: 0.020000
Training Epoch: 15 [3840/9494]	Loss: 0.2789	LR: 0.020000
Training Epoch: 15 [4096/9494]	Loss: 0.3152	LR: 0.020000
Training Epoch: 15 [4352/9494]	Loss: 0.2909	LR: 0.020000
Training Epoch: 15 [4608/9494]	Loss: 0.2970	LR: 0.020000
Training Epoch: 15 [4864/9494]	Loss: 0.3679	LR: 0.020000
Training Epoch: 15 [5120/9494]	Loss: 0.3251	LR: 0.020000
Training Epoch: 15 [5376/9494]	Loss: 0.3330	LR: 0.020000
Training Epoch: 15 [5632/9494]	Loss: 0.2945	LR: 0.020000
Training Epoch: 15 [5888/9494]	Loss: 0.3408	LR: 0.020000
Training Epoch: 15 [6144/9494]	Loss: 0.3595	LR: 0.020000
Training Epoch: 15 [6400/9494]	Loss: 0.3749	LR: 0.020000
Training Epoch: 15 [6656/9494]	Loss: 0.4122	LR: 0.020000
Training Epoch: 15 [6912/9494]	Loss: 0.3424	LR: 0.020000
Training Epoch: 15 [7168/9494]	Loss: 0.3395	LR: 0.020000
Training Epoch: 15 [7424/9494]	Loss: 0.3648	LR: 0.020000
Training Epoch: 15 [7680/9494]	Loss: 0.3635	LR: 0.020000
Training Epoch: 15 [7936/9494]	Loss: 0.3187	LR: 0.020000
Training Epoch: 15 [8192/9494]	Loss: 0.3053	LR: 0.020000
Training Epoch: 15 [8448/9494]	Loss: 0.3366	LR: 0.020000
Training Epoch: 15 [8704/9494]	Loss: 0.3136	LR: 0.020000
Training Epoch: 15 [8960/9494]	Loss: 0.3294	LR: 0.020000
Training Epoch: 15 [9216/9494]	Loss: 0.4429	LR: 0.020000
Training Epoch: 15 [9472/9494]	Loss: 0.3660	LR: 0.020000
Training Epoch: 15 [9494/9494]	Loss: 0.2786	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3503, Train Accuracy: 0.8480
Epoch 15 training time consumed: 139.10s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0014, Accuracy: 0.8731, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-15-best.pth
Training Epoch: 16 [256/9494]	Loss: 0.2968	LR: 0.020000
Training Epoch: 16 [512/9494]	Loss: 0.3126	LR: 0.020000
Training Epoch: 16 [768/9494]	Loss: 0.3328	LR: 0.020000
Training Epoch: 16 [1024/9494]	Loss: 0.3697	LR: 0.020000
Training Epoch: 16 [1280/9494]	Loss: 0.3817	LR: 0.020000
Training Epoch: 16 [1536/9494]	Loss: 0.3337	LR: 0.020000
Training Epoch: 16 [1792/9494]	Loss: 0.2867	LR: 0.020000
Training Epoch: 16 [2048/9494]	Loss: 0.3202	LR: 0.020000
Training Epoch: 16 [2304/9494]	Loss: 0.4236	LR: 0.020000
Training Epoch: 16 [2560/9494]	Loss: 0.3775	LR: 0.020000
Training Epoch: 16 [2816/9494]	Loss: 0.2849	LR: 0.020000
Training Epoch: 16 [3072/9494]	Loss: 0.3341	LR: 0.020000
Training Epoch: 16 [3328/9494]	Loss: 0.2654	LR: 0.020000
Training Epoch: 16 [3584/9494]	Loss: 0.3697	LR: 0.020000
Training Epoch: 16 [3840/9494]	Loss: 0.2901	LR: 0.020000
Training Epoch: 16 [4096/9494]	Loss: 0.3236	LR: 0.020000
Training Epoch: 16 [4352/9494]	Loss: 0.3077	LR: 0.020000
Training Epoch: 16 [4608/9494]	Loss: 0.3378	LR: 0.020000
Training Epoch: 16 [4864/9494]	Loss: 0.3535	LR: 0.020000
Training Epoch: 16 [5120/9494]	Loss: 0.2753	LR: 0.020000
Training Epoch: 16 [5376/9494]	Loss: 0.3250	LR: 0.020000
Training Epoch: 16 [5632/9494]	Loss: 0.3572	LR: 0.020000
Training Epoch: 16 [5888/9494]	Loss: 0.2721	LR: 0.020000
Training Epoch: 16 [6144/9494]	Loss: 0.2777	LR: 0.020000
Training Epoch: 16 [6400/9494]	Loss: 0.3000	LR: 0.020000
Training Epoch: 16 [6656/9494]	Loss: 0.3291	LR: 0.020000
Training Epoch: 16 [6912/9494]	Loss: 0.3628	LR: 0.020000
Training Epoch: 16 [7168/9494]	Loss: 0.3483	LR: 0.020000
Training Epoch: 16 [7424/9494]	Loss: 0.3132	LR: 0.020000
Training Epoch: 16 [7680/9494]	Loss: 0.2434	LR: 0.020000
Training Epoch: 16 [7936/9494]	Loss: 0.2689	LR: 0.020000
Training Epoch: 16 [8192/9494]	Loss: 0.2482	LR: 0.020000
Training Epoch: 16 [8448/9494]	Loss: 0.2754	LR: 0.020000
Training Epoch: 16 [8704/9494]	Loss: 0.2973	LR: 0.020000
Training Epoch: 16 [8960/9494]	Loss: 0.3135	LR: 0.020000
Training Epoch: 16 [9216/9494]	Loss: 0.3279	LR: 0.020000
Training Epoch: 16 [9472/9494]	Loss: 0.3835	LR: 0.020000
Training Epoch: 16 [9494/9494]	Loss: 0.3174	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3195, Train Accuracy: 0.8611
Epoch 16 training time consumed: 138.63s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0014, Accuracy: 0.8581, Time consumed:7.86s
Training Epoch: 17 [256/9494]	Loss: 0.3021	LR: 0.020000
Training Epoch: 17 [512/9494]	Loss: 0.3038	LR: 0.020000
Training Epoch: 17 [768/9494]	Loss: 0.2792	LR: 0.020000
Training Epoch: 17 [1024/9494]	Loss: 0.3156	LR: 0.020000
Training Epoch: 17 [1280/9494]	Loss: 0.2617	LR: 0.020000
Training Epoch: 17 [1536/9494]	Loss: 0.3727	LR: 0.020000
Training Epoch: 17 [1792/9494]	Loss: 0.2922	LR: 0.020000
Training Epoch: 17 [2048/9494]	Loss: 0.2942	LR: 0.020000
Training Epoch: 17 [2304/9494]	Loss: 0.2402	LR: 0.020000
Training Epoch: 17 [2560/9494]	Loss: 0.2698	LR: 0.020000
Training Epoch: 17 [2816/9494]	Loss: 0.3068	LR: 0.020000
Training Epoch: 17 [3072/9494]	Loss: 0.3329	LR: 0.020000
Training Epoch: 17 [3328/9494]	Loss: 0.3012	LR: 0.020000
Training Epoch: 17 [3584/9494]	Loss: 0.3286	LR: 0.020000
Training Epoch: 17 [3840/9494]	Loss: 0.2908	LR: 0.020000
Training Epoch: 17 [4096/9494]	Loss: 0.3527	LR: 0.020000
Training Epoch: 17 [4352/9494]	Loss: 0.2944	LR: 0.020000
Training Epoch: 17 [4608/9494]	Loss: 0.2740	LR: 0.020000
Training Epoch: 17 [4864/9494]	Loss: 0.2970	LR: 0.020000
Training Epoch: 17 [5120/9494]	Loss: 0.2966	LR: 0.020000
Training Epoch: 17 [5376/9494]	Loss: 0.2496	LR: 0.020000
Training Epoch: 17 [5632/9494]	Loss: 0.3224	LR: 0.020000
Training Epoch: 17 [5888/9494]	Loss: 0.2663	LR: 0.020000
Training Epoch: 17 [6144/9494]	Loss: 0.3065	LR: 0.020000
Training Epoch: 17 [6400/9494]	Loss: 0.2768	LR: 0.020000
Training Epoch: 17 [6656/9494]	Loss: 0.3304	LR: 0.020000
Training Epoch: 17 [6912/9494]	Loss: 0.2511	LR: 0.020000
Training Epoch: 17 [7168/9494]	Loss: 0.2501	LR: 0.020000
Training Epoch: 17 [7424/9494]	Loss: 0.2688	LR: 0.020000
Training Epoch: 17 [7680/9494]	Loss: 0.2601	LR: 0.020000
Training Epoch: 17 [7936/9494]	Loss: 0.2600	LR: 0.020000
Training Epoch: 17 [8192/9494]	Loss: 0.2858	LR: 0.020000
Training Epoch: 17 [8448/9494]	Loss: 0.2413	LR: 0.020000
Training Epoch: 17 [8704/9494]	Loss: 0.2819	LR: 0.020000
Training Epoch: 17 [8960/9494]	Loss: 0.2837	LR: 0.020000
Training Epoch: 17 [9216/9494]	Loss: 0.2891	LR: 0.020000
Training Epoch: 17 [9472/9494]	Loss: 0.2773	LR: 0.020000
Training Epoch: 17 [9494/9494]	Loss: 0.2341	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2893, Train Accuracy: 0.8774
Epoch 17 training time consumed: 137.37s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0037, Accuracy: 0.6455, Time consumed:7.72s
Training Epoch: 18 [256/9494]	Loss: 0.3006	LR: 0.020000
Training Epoch: 18 [512/9494]	Loss: 0.3288	LR: 0.020000
Training Epoch: 18 [768/9494]	Loss: 0.2932	LR: 0.020000
Training Epoch: 18 [1024/9494]	Loss: 0.4494	LR: 0.020000
Training Epoch: 18 [1280/9494]	Loss: 0.2347	LR: 0.020000
Training Epoch: 18 [1536/9494]	Loss: 0.2093	LR: 0.020000
Training Epoch: 18 [1792/9494]	Loss: 0.2959	LR: 0.020000
Training Epoch: 18 [2048/9494]	Loss: 0.3329	LR: 0.020000
Training Epoch: 18 [2304/9494]	Loss: 0.3150	LR: 0.020000
Training Epoch: 18 [2560/9494]	Loss: 0.3033	LR: 0.020000
Training Epoch: 18 [2816/9494]	Loss: 0.2909	LR: 0.020000
Training Epoch: 18 [3072/9494]	Loss: 0.2873	LR: 0.020000
Training Epoch: 18 [3328/9494]	Loss: 0.2921	LR: 0.020000
Training Epoch: 18 [3584/9494]	Loss: 0.2649	LR: 0.020000
Training Epoch: 18 [3840/9494]	Loss: 0.3030	LR: 0.020000
Training Epoch: 18 [4096/9494]	Loss: 0.3140	LR: 0.020000
Training Epoch: 18 [4352/9494]	Loss: 0.2124	LR: 0.020000
Training Epoch: 18 [4608/9494]	Loss: 0.2592	LR: 0.020000
Training Epoch: 18 [4864/9494]	Loss: 0.2914	LR: 0.020000
Training Epoch: 18 [5120/9494]	Loss: 0.2766	LR: 0.020000
Training Epoch: 18 [5376/9494]	Loss: 0.2336	LR: 0.020000
Training Epoch: 18 [5632/9494]	Loss: 0.3392	LR: 0.020000
Training Epoch: 18 [5888/9494]	Loss: 0.2782	LR: 0.020000
Training Epoch: 18 [6144/9494]	Loss: 0.2732	LR: 0.020000
Training Epoch: 18 [6400/9494]	Loss: 0.3295	LR: 0.020000
Training Epoch: 18 [6656/9494]	Loss: 0.2436	LR: 0.020000
Training Epoch: 18 [6912/9494]	Loss: 0.2826	LR: 0.020000
Training Epoch: 18 [7168/9494]	Loss: 0.2765	LR: 0.020000
Training Epoch: 18 [7424/9494]	Loss: 0.2556	LR: 0.020000
Training Epoch: 18 [7680/9494]	Loss: 0.2916	LR: 0.020000
Training Epoch: 18 [7936/9494]	Loss: 0.2607	LR: 0.020000
Training Epoch: 18 [8192/9494]	Loss: 0.2777	LR: 0.020000
Training Epoch: 18 [8448/9494]	Loss: 0.2654	LR: 0.020000
Training Epoch: 18 [8704/9494]	Loss: 0.2220	LR: 0.020000
Training Epoch: 18 [8960/9494]	Loss: 0.3296	LR: 0.020000
Training Epoch: 18 [9216/9494]	Loss: 0.3461	LR: 0.020000
Training Epoch: 18 [9472/9494]	Loss: 0.2529	LR: 0.020000
Training Epoch: 18 [9494/9494]	Loss: 0.2053	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2867, Train Accuracy: 0.8818
Epoch 18 training time consumed: 137.16s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0025, Accuracy: 0.7676, Time consumed:7.75s
Training Epoch: 19 [256/9494]	Loss: 0.2802	LR: 0.020000
Training Epoch: 19 [512/9494]	Loss: 0.2760	LR: 0.020000
Training Epoch: 19 [768/9494]	Loss: 0.2734	LR: 0.020000
Training Epoch: 19 [1024/9494]	Loss: 0.3569	LR: 0.020000
Training Epoch: 19 [1280/9494]	Loss: 0.2907	LR: 0.020000
Training Epoch: 19 [1536/9494]	Loss: 0.3086	LR: 0.020000
Training Epoch: 19 [1792/9494]	Loss: 0.2495	LR: 0.020000
Training Epoch: 19 [2048/9494]	Loss: 0.2410	LR: 0.020000
Training Epoch: 19 [2304/9494]	Loss: 0.3006	LR: 0.020000
Training Epoch: 19 [2560/9494]	Loss: 0.2912	LR: 0.020000
Training Epoch: 19 [2816/9494]	Loss: 0.2061	LR: 0.020000
Training Epoch: 19 [3072/9494]	Loss: 0.2461	LR: 0.020000
Training Epoch: 19 [3328/9494]	Loss: 0.2564	LR: 0.020000
Training Epoch: 19 [3584/9494]	Loss: 0.2876	LR: 0.020000
Training Epoch: 19 [3840/9494]	Loss: 0.2864	LR: 0.020000
Training Epoch: 19 [4096/9494]	Loss: 0.1857	LR: 0.020000
Training Epoch: 19 [4352/9494]	Loss: 0.2041	LR: 0.020000
Training Epoch: 19 [4608/9494]	Loss: 0.2671	LR: 0.020000
Training Epoch: 19 [4864/9494]	Loss: 0.2327	LR: 0.020000
Training Epoch: 19 [5120/9494]	Loss: 0.2416	LR: 0.020000
Training Epoch: 19 [5376/9494]	Loss: 0.2262	LR: 0.020000
Training Epoch: 19 [5632/9494]	Loss: 0.2158	LR: 0.020000
Training Epoch: 19 [5888/9494]	Loss: 0.2572	LR: 0.020000
Training Epoch: 19 [6144/9494]	Loss: 0.3470	LR: 0.020000
Training Epoch: 19 [6400/9494]	Loss: 0.2181	LR: 0.020000
Training Epoch: 19 [6656/9494]	Loss: 0.1819	LR: 0.020000
Training Epoch: 19 [6912/9494]	Loss: 0.2488	LR: 0.020000
Training Epoch: 19 [7168/9494]	Loss: 0.2030	LR: 0.020000
Training Epoch: 19 [7424/9494]	Loss: 0.2442	LR: 0.020000
Training Epoch: 19 [7680/9494]	Loss: 0.2206	LR: 0.020000
Training Epoch: 19 [7936/9494]	Loss: 0.1971	LR: 0.020000
Training Epoch: 19 [8192/9494]	Loss: 0.2310	LR: 0.020000
Training Epoch: 19 [8448/9494]	Loss: 0.1712	LR: 0.020000
Training Epoch: 19 [8704/9494]	Loss: 0.2589	LR: 0.020000
Training Epoch: 19 [8960/9494]	Loss: 0.2494	LR: 0.020000
Training Epoch: 19 [9216/9494]	Loss: 0.1636	LR: 0.020000
Training Epoch: 19 [9472/9494]	Loss: 0.1891	LR: 0.020000
Training Epoch: 19 [9494/9494]	Loss: 0.5161	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2467, Train Accuracy: 0.8998
Epoch 19 training time consumed: 137.09s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0015, Accuracy: 0.8659, Time consumed:7.81s
Training Epoch: 20 [256/9494]	Loss: 0.3628	LR: 0.004000
Training Epoch: 20 [512/9494]	Loss: 0.2420	LR: 0.004000
Training Epoch: 20 [768/9494]	Loss: 0.2590	LR: 0.004000
Training Epoch: 20 [1024/9494]	Loss: 0.2685	LR: 0.004000
Training Epoch: 20 [1280/9494]	Loss: 0.3008	LR: 0.004000
Training Epoch: 20 [1536/9494]	Loss: 0.2170	LR: 0.004000
Training Epoch: 20 [1792/9494]	Loss: 0.2783	LR: 0.004000
Training Epoch: 20 [2048/9494]	Loss: 0.2762	LR: 0.004000
Training Epoch: 20 [2304/9494]	Loss: 0.2141	LR: 0.004000
Training Epoch: 20 [2560/9494]	Loss: 0.2881	LR: 0.004000
Training Epoch: 20 [2816/9494]	Loss: 0.2356	LR: 0.004000
Training Epoch: 20 [3072/9494]	Loss: 0.2129	LR: 0.004000
Training Epoch: 20 [3328/9494]	Loss: 0.2593	LR: 0.004000
Training Epoch: 20 [3584/9494]	Loss: 0.2489	LR: 0.004000
Training Epoch: 20 [3840/9494]	Loss: 0.1898	LR: 0.004000
Training Epoch: 20 [4096/9494]	Loss: 0.2228	LR: 0.004000
Training Epoch: 20 [4352/9494]	Loss: 0.2438	LR: 0.004000
Training Epoch: 20 [4608/9494]	Loss: 0.2256	LR: 0.004000
Training Epoch: 20 [4864/9494]	Loss: 0.1828	LR: 0.004000
Training Epoch: 20 [5120/9494]	Loss: 0.2354	LR: 0.004000
Training Epoch: 20 [5376/9494]	Loss: 0.2071	LR: 0.004000
Training Epoch: 20 [5632/9494]	Loss: 0.1861	LR: 0.004000
Training Epoch: 20 [5888/9494]	Loss: 0.2194	LR: 0.004000
Training Epoch: 20 [6144/9494]	Loss: 0.2252	LR: 0.004000
Training Epoch: 20 [6400/9494]	Loss: 0.2333	LR: 0.004000
Training Epoch: 20 [6656/9494]	Loss: 0.2718	LR: 0.004000
Training Epoch: 20 [6912/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 20 [7168/9494]	Loss: 0.2252	LR: 0.004000
Training Epoch: 20 [7424/9494]	Loss: 0.2107	LR: 0.004000
Training Epoch: 20 [7680/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 20 [7936/9494]	Loss: 0.2399	LR: 0.004000
Training Epoch: 20 [8192/9494]	Loss: 0.2193	LR: 0.004000
Training Epoch: 20 [8448/9494]	Loss: 0.1928	LR: 0.004000
Training Epoch: 20 [8704/9494]	Loss: 0.1583	LR: 0.004000
Training Epoch: 20 [8960/9494]	Loss: 0.1679	LR: 0.004000
Training Epoch: 20 [9216/9494]	Loss: 0.1967	LR: 0.004000
Training Epoch: 20 [9472/9494]	Loss: 0.1788	LR: 0.004000
Training Epoch: 20 [9494/9494]	Loss: 0.1494	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2271, Train Accuracy: 0.9070
Epoch 20 training time consumed: 137.09s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0010, Accuracy: 0.9080, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-20-best.pth
Training Epoch: 21 [256/9494]	Loss: 0.1796	LR: 0.004000
Training Epoch: 21 [512/9494]	Loss: 0.2021	LR: 0.004000
Training Epoch: 21 [768/9494]	Loss: 0.2104	LR: 0.004000
Training Epoch: 21 [1024/9494]	Loss: 0.2338	LR: 0.004000
Training Epoch: 21 [1280/9494]	Loss: 0.2571	LR: 0.004000
Training Epoch: 21 [1536/9494]	Loss: 0.2245	LR: 0.004000
Training Epoch: 21 [1792/9494]	Loss: 0.1720	LR: 0.004000
Training Epoch: 21 [2048/9494]	Loss: 0.1971	LR: 0.004000
Training Epoch: 21 [2304/9494]	Loss: 0.2220	LR: 0.004000
Training Epoch: 21 [2560/9494]	Loss: 0.2072	LR: 0.004000
Training Epoch: 21 [2816/9494]	Loss: 0.2030	LR: 0.004000
Training Epoch: 21 [3072/9494]	Loss: 0.1782	LR: 0.004000
Training Epoch: 21 [3328/9494]	Loss: 0.1877	LR: 0.004000
Training Epoch: 21 [3584/9494]	Loss: 0.2068	LR: 0.004000
Training Epoch: 21 [3840/9494]	Loss: 0.1945	LR: 0.004000
Training Epoch: 21 [4096/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 21 [4352/9494]	Loss: 0.1817	LR: 0.004000
Training Epoch: 21 [4608/9494]	Loss: 0.2360	LR: 0.004000
Training Epoch: 21 [4864/9494]	Loss: 0.2171	LR: 0.004000
Training Epoch: 21 [5120/9494]	Loss: 0.2161	LR: 0.004000
Training Epoch: 21 [5376/9494]	Loss: 0.1305	LR: 0.004000
Training Epoch: 21 [5632/9494]	Loss: 0.1432	LR: 0.004000
Training Epoch: 21 [5888/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 21 [6144/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 21 [6400/9494]	Loss: 0.1716	LR: 0.004000
Training Epoch: 21 [6656/9494]	Loss: 0.1687	LR: 0.004000
Training Epoch: 21 [6912/9494]	Loss: 0.2018	LR: 0.004000
Training Epoch: 21 [7168/9494]	Loss: 0.1489	LR: 0.004000
Training Epoch: 21 [7424/9494]	Loss: 0.2134	LR: 0.004000
Training Epoch: 21 [7680/9494]	Loss: 0.2149	LR: 0.004000
Training Epoch: 21 [7936/9494]	Loss: 0.1691	LR: 0.004000
Training Epoch: 21 [8192/9494]	Loss: 0.1997	LR: 0.004000
Training Epoch: 21 [8448/9494]	Loss: 0.2193	LR: 0.004000
Training Epoch: 21 [8704/9494]	Loss: 0.2253	LR: 0.004000
Training Epoch: 21 [8960/9494]	Loss: 0.1681	LR: 0.004000
Training Epoch: 21 [9216/9494]	Loss: 0.2802	LR: 0.004000
Training Epoch: 21 [9472/9494]	Loss: 0.2300	LR: 0.004000
Training Epoch: 21 [9494/9494]	Loss: 0.2145	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1969, Train Accuracy: 0.9187
Epoch 21 training time consumed: 137.22s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0008, Accuracy: 0.9225, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-21-best.pth
Training Epoch: 22 [256/9494]	Loss: 0.2150	LR: 0.004000
Training Epoch: 22 [512/9494]	Loss: 0.1968	LR: 0.004000
Training Epoch: 22 [768/9494]	Loss: 0.2202	LR: 0.004000
Training Epoch: 22 [1024/9494]	Loss: 0.2169	LR: 0.004000
Training Epoch: 22 [1280/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 22 [1536/9494]	Loss: 0.2852	LR: 0.004000
Training Epoch: 22 [1792/9494]	Loss: 0.1863	LR: 0.004000
Training Epoch: 22 [2048/9494]	Loss: 0.1193	LR: 0.004000
Training Epoch: 22 [2304/9494]	Loss: 0.1483	LR: 0.004000
Training Epoch: 22 [2560/9494]	Loss: 0.1746	LR: 0.004000
Training Epoch: 22 [2816/9494]	Loss: 0.1842	LR: 0.004000
Training Epoch: 22 [3072/9494]	Loss: 0.1830	LR: 0.004000
Training Epoch: 22 [3328/9494]	Loss: 0.2088	LR: 0.004000
Training Epoch: 22 [3584/9494]	Loss: 0.1904	LR: 0.004000
Training Epoch: 22 [3840/9494]	Loss: 0.1856	LR: 0.004000
Training Epoch: 22 [4096/9494]	Loss: 0.2322	LR: 0.004000
Training Epoch: 22 [4352/9494]	Loss: 0.2012	LR: 0.004000
Training Epoch: 22 [4608/9494]	Loss: 0.1996	LR: 0.004000
Training Epoch: 22 [4864/9494]	Loss: 0.1799	LR: 0.004000
Training Epoch: 22 [5120/9494]	Loss: 0.2013	LR: 0.004000
Training Epoch: 22 [5376/9494]	Loss: 0.2108	LR: 0.004000
Training Epoch: 22 [5632/9494]	Loss: 0.2137	LR: 0.004000
Training Epoch: 22 [5888/9494]	Loss: 0.2329	LR: 0.004000
Training Epoch: 22 [6144/9494]	Loss: 0.2105	LR: 0.004000
Training Epoch: 22 [6400/9494]	Loss: 0.1576	LR: 0.004000
Training Epoch: 22 [6656/9494]	Loss: 0.1929	LR: 0.004000
Training Epoch: 22 [6912/9494]	Loss: 0.1944	LR: 0.004000
Training Epoch: 22 [7168/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 22 [7424/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 22 [7680/9494]	Loss: 0.2240	LR: 0.004000
Training Epoch: 22 [7936/9494]	Loss: 0.2359	LR: 0.004000
Training Epoch: 22 [8192/9494]	Loss: 0.2377	LR: 0.004000
Training Epoch: 22 [8448/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 22 [8704/9494]	Loss: 0.1883	LR: 0.004000
Training Epoch: 22 [8960/9494]	Loss: 0.2077	LR: 0.004000
Training Epoch: 22 [9216/9494]	Loss: 0.1855	LR: 0.004000
Training Epoch: 22 [9472/9494]	Loss: 0.1890	LR: 0.004000
Training Epoch: 22 [9494/9494]	Loss: 0.6496	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1981, Train Accuracy: 0.9241
Epoch 22 training time consumed: 137.24s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0008, Accuracy: 0.9235, Time consumed:7.72s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-22-best.pth
Training Epoch: 23 [256/9494]	Loss: 0.1580	LR: 0.004000
Training Epoch: 23 [512/9494]	Loss: 0.1580	LR: 0.004000
Training Epoch: 23 [768/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 23 [1024/9494]	Loss: 0.1828	LR: 0.004000
Training Epoch: 23 [1280/9494]	Loss: 0.1784	LR: 0.004000
Training Epoch: 23 [1536/9494]	Loss: 0.2168	LR: 0.004000
Training Epoch: 23 [1792/9494]	Loss: 0.1995	LR: 0.004000
Training Epoch: 23 [2048/9494]	Loss: 0.1664	LR: 0.004000
Training Epoch: 23 [2304/9494]	Loss: 0.2132	LR: 0.004000
Training Epoch: 23 [2560/9494]	Loss: 0.2222	LR: 0.004000
Training Epoch: 23 [2816/9494]	Loss: 0.2601	LR: 0.004000
Training Epoch: 23 [3072/9494]	Loss: 0.2298	LR: 0.004000
Training Epoch: 23 [3328/9494]	Loss: 0.1725	LR: 0.004000
Training Epoch: 23 [3584/9494]	Loss: 0.2144	LR: 0.004000
Training Epoch: 23 [3840/9494]	Loss: 0.1995	LR: 0.004000
Training Epoch: 23 [4096/9494]	Loss: 0.2504	LR: 0.004000
Training Epoch: 23 [4352/9494]	Loss: 0.1968	LR: 0.004000
Training Epoch: 23 [4608/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 23 [4864/9494]	Loss: 0.2183	LR: 0.004000
Training Epoch: 23 [5120/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 23 [5376/9494]	Loss: 0.2266	LR: 0.004000
Training Epoch: 23 [5632/9494]	Loss: 0.2513	LR: 0.004000
Training Epoch: 23 [5888/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 23 [6144/9494]	Loss: 0.2245	LR: 0.004000
Training Epoch: 23 [6400/9494]	Loss: 0.2126	LR: 0.004000
Training Epoch: 23 [6656/9494]	Loss: 0.2028	LR: 0.004000
Training Epoch: 23 [6912/9494]	Loss: 0.1309	LR: 0.004000
Training Epoch: 23 [7168/9494]	Loss: 0.1726	LR: 0.004000
Training Epoch: 23 [7424/9494]	Loss: 0.1932	LR: 0.004000
Training Epoch: 23 [7680/9494]	Loss: 0.1899	LR: 0.004000
Training Epoch: 23 [7936/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 23 [8192/9494]	Loss: 0.2203	LR: 0.004000
Training Epoch: 23 [8448/9494]	Loss: 0.2215	LR: 0.004000
Training Epoch: 23 [8704/9494]	Loss: 0.2597	LR: 0.004000
Training Epoch: 23 [8960/9494]	Loss: 0.2117	LR: 0.004000
Training Epoch: 23 [9216/9494]	Loss: 0.1322	LR: 0.004000
Training Epoch: 23 [9472/9494]	Loss: 0.1909	LR: 0.004000
Training Epoch: 23 [9494/9494]	Loss: 0.1539	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1969, Train Accuracy: 0.9208
Epoch 23 training time consumed: 136.99s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0008, Accuracy: 0.9235, Time consumed:7.91s
Training Epoch: 24 [256/9494]	Loss: 0.1849	LR: 0.004000
Training Epoch: 24 [512/9494]	Loss: 0.1902	LR: 0.004000
Training Epoch: 24 [768/9494]	Loss: 0.2560	LR: 0.004000
Training Epoch: 24 [1024/9494]	Loss: 0.1752	LR: 0.004000
Training Epoch: 24 [1280/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 24 [1536/9494]	Loss: 0.2476	LR: 0.004000
Training Epoch: 24 [1792/9494]	Loss: 0.1637	LR: 0.004000
Training Epoch: 24 [2048/9494]	Loss: 0.2179	LR: 0.004000
Training Epoch: 24 [2304/9494]	Loss: 0.1586	LR: 0.004000
Training Epoch: 24 [2560/9494]	Loss: 0.1777	LR: 0.004000
Training Epoch: 24 [2816/9494]	Loss: 0.1958	LR: 0.004000
Training Epoch: 24 [3072/9494]	Loss: 0.1335	LR: 0.004000
Training Epoch: 24 [3328/9494]	Loss: 0.1886	LR: 0.004000
Training Epoch: 24 [3584/9494]	Loss: 0.2382	LR: 0.004000
Training Epoch: 24 [3840/9494]	Loss: 0.2170	LR: 0.004000
Training Epoch: 24 [4096/9494]	Loss: 0.1530	LR: 0.004000
Training Epoch: 24 [4352/9494]	Loss: 0.2149	LR: 0.004000
Training Epoch: 24 [4608/9494]	Loss: 0.2002	LR: 0.004000
Training Epoch: 24 [4864/9494]	Loss: 0.2355	LR: 0.004000
Training Epoch: 24 [5120/9494]	Loss: 0.1590	LR: 0.004000
Training Epoch: 24 [5376/9494]	Loss: 0.1705	LR: 0.004000
Training Epoch: 24 [5632/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 24 [5888/9494]	Loss: 0.2210	LR: 0.004000
Training Epoch: 24 [6144/9494]	Loss: 0.1814	LR: 0.004000
Training Epoch: 24 [6400/9494]	Loss: 0.1909	LR: 0.004000
Training Epoch: 24 [6656/9494]	Loss: 0.2148	LR: 0.004000
Training Epoch: 24 [6912/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 24 [7168/9494]	Loss: 0.1387	LR: 0.004000
Training Epoch: 24 [7424/9494]	Loss: 0.1592	LR: 0.004000
Training Epoch: 24 [7680/9494]	Loss: 0.2098	LR: 0.004000
Training Epoch: 24 [7936/9494]	Loss: 0.1964	LR: 0.004000
Training Epoch: 24 [8192/9494]	Loss: 0.1913	LR: 0.004000
Training Epoch: 24 [8448/9494]	Loss: 0.1832	LR: 0.004000
Training Epoch: 24 [8704/9494]	Loss: 0.1608	LR: 0.004000
Training Epoch: 24 [8960/9494]	Loss: 0.1588	LR: 0.004000
Training Epoch: 24 [9216/9494]	Loss: 0.1668	LR: 0.004000
Training Epoch: 24 [9472/9494]	Loss: 0.1693	LR: 0.004000
Training Epoch: 24 [9494/9494]	Loss: 0.1819	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1862, Train Accuracy: 0.9211
Epoch 24 training time consumed: 137.13s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0008, Accuracy: 0.9254, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-24-best.pth
Training Epoch: 25 [256/9494]	Loss: 0.1419	LR: 0.004000
Training Epoch: 25 [512/9494]	Loss: 0.1665	LR: 0.004000
Training Epoch: 25 [768/9494]	Loss: 0.1841	LR: 0.004000
Training Epoch: 25 [1024/9494]	Loss: 0.2099	LR: 0.004000
Training Epoch: 25 [1280/9494]	Loss: 0.1853	LR: 0.004000
Training Epoch: 25 [1536/9494]	Loss: 0.2663	LR: 0.004000
Training Epoch: 25 [1792/9494]	Loss: 0.2159	LR: 0.004000
Training Epoch: 25 [2048/9494]	Loss: 0.1693	LR: 0.004000
Training Epoch: 25 [2304/9494]	Loss: 0.2095	LR: 0.004000
Training Epoch: 25 [2560/9494]	Loss: 0.1344	LR: 0.004000
Training Epoch: 25 [2816/9494]	Loss: 0.2036	LR: 0.004000
Training Epoch: 25 [3072/9494]	Loss: 0.2075	LR: 0.004000
Training Epoch: 25 [3328/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 25 [3584/9494]	Loss: 0.1376	LR: 0.004000
Training Epoch: 25 [3840/9494]	Loss: 0.2333	LR: 0.004000
Training Epoch: 25 [4096/9494]	Loss: 0.2069	LR: 0.004000
Training Epoch: 25 [4352/9494]	Loss: 0.1416	LR: 0.004000
Training Epoch: 25 [4608/9494]	Loss: 0.1785	LR: 0.004000
Training Epoch: 25 [4864/9494]	Loss: 0.1380	LR: 0.004000
Training Epoch: 25 [5120/9494]	Loss: 0.1980	LR: 0.004000
Training Epoch: 25 [5376/9494]	Loss: 0.1613	LR: 0.004000
Training Epoch: 25 [5632/9494]	Loss: 0.2329	LR: 0.004000
Training Epoch: 25 [5888/9494]	Loss: 0.1604	LR: 0.004000
Training Epoch: 25 [6144/9494]	Loss: 0.2264	LR: 0.004000
Training Epoch: 25 [6400/9494]	Loss: 0.1434	LR: 0.004000
Training Epoch: 25 [6656/9494]	Loss: 0.1350	LR: 0.004000
Training Epoch: 25 [6912/9494]	Loss: 0.1991	LR: 0.004000
Training Epoch: 25 [7168/9494]	Loss: 0.1745	LR: 0.004000
Training Epoch: 25 [7424/9494]	Loss: 0.2073	LR: 0.004000
Training Epoch: 25 [7680/9494]	Loss: 0.1113	LR: 0.004000
Training Epoch: 25 [7936/9494]	Loss: 0.1321	LR: 0.004000
Training Epoch: 25 [8192/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 25 [8448/9494]	Loss: 0.1985	LR: 0.004000
Training Epoch: 25 [8704/9494]	Loss: 0.2230	LR: 0.004000
Training Epoch: 25 [8960/9494]	Loss: 0.1630	LR: 0.004000
Training Epoch: 25 [9216/9494]	Loss: 0.1666	LR: 0.004000
Training Epoch: 25 [9472/9494]	Loss: 0.2084	LR: 0.004000
Training Epoch: 25 [9494/9494]	Loss: 0.7143	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1824, Train Accuracy: 0.9273
Epoch 25 training time consumed: 137.26s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0009, Accuracy: 0.9090, Time consumed:8.04s
Training Epoch: 26 [256/9494]	Loss: 0.2141	LR: 0.004000
Training Epoch: 26 [512/9494]	Loss: 0.2173	LR: 0.004000
Training Epoch: 26 [768/9494]	Loss: 0.1809	LR: 0.004000
Training Epoch: 26 [1024/9494]	Loss: 0.2588	LR: 0.004000
Training Epoch: 26 [1280/9494]	Loss: 0.2352	LR: 0.004000
Training Epoch: 26 [1536/9494]	Loss: 0.1905	LR: 0.004000
Training Epoch: 26 [1792/9494]	Loss: 0.1901	LR: 0.004000
Training Epoch: 26 [2048/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 26 [2304/9494]	Loss: 0.1994	LR: 0.004000
Training Epoch: 26 [2560/9494]	Loss: 0.1437	LR: 0.004000
Training Epoch: 26 [2816/9494]	Loss: 0.1759	LR: 0.004000
Training Epoch: 26 [3072/9494]	Loss: 0.2620	LR: 0.004000
Training Epoch: 26 [3328/9494]	Loss: 0.2539	LR: 0.004000
Training Epoch: 26 [3584/9494]	Loss: 0.1718	LR: 0.004000
Training Epoch: 26 [3840/9494]	Loss: 0.2290	LR: 0.004000
Training Epoch: 26 [4096/9494]	Loss: 0.2163	LR: 0.004000
Training Epoch: 26 [4352/9494]	Loss: 0.2428	LR: 0.004000
Training Epoch: 26 [4608/9494]	Loss: 0.1498	LR: 0.004000
Training Epoch: 26 [4864/9494]	Loss: 0.1710	LR: 0.004000
Training Epoch: 26 [5120/9494]	Loss: 0.1540	LR: 0.004000
Training Epoch: 26 [5376/9494]	Loss: 0.1886	LR: 0.004000
Training Epoch: 26 [5632/9494]	Loss: 0.1917	LR: 0.004000
Training Epoch: 26 [5888/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 26 [6144/9494]	Loss: 0.1431	LR: 0.004000
Training Epoch: 26 [6400/9494]	Loss: 0.1785	LR: 0.004000
Training Epoch: 26 [6656/9494]	Loss: 0.2630	LR: 0.004000
Training Epoch: 26 [6912/9494]	Loss: 0.1715	LR: 0.004000
Training Epoch: 26 [7168/9494]	Loss: 0.2582	LR: 0.004000
Training Epoch: 26 [7424/9494]	Loss: 0.1986	LR: 0.004000
Training Epoch: 26 [7680/9494]	Loss: 0.2175	LR: 0.004000
Training Epoch: 26 [7936/9494]	Loss: 0.1452	LR: 0.004000
Training Epoch: 26 [8192/9494]	Loss: 0.1699	LR: 0.004000
Training Epoch: 26 [8448/9494]	Loss: 0.1327	LR: 0.004000
Training Epoch: 26 [8704/9494]	Loss: 0.1879	LR: 0.004000
Training Epoch: 26 [8960/9494]	Loss: 0.1802	LR: 0.004000
Training Epoch: 26 [9216/9494]	Loss: 0.1538	LR: 0.004000
Training Epoch: 26 [9472/9494]	Loss: 0.1897	LR: 0.004000
Training Epoch: 26 [9494/9494]	Loss: 0.3287	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1941, Train Accuracy: 0.9206
Epoch 26 training time consumed: 137.49s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0010, Accuracy: 0.9065, Time consumed:7.99s
Training Epoch: 27 [256/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 27 [512/9494]	Loss: 0.1696	LR: 0.004000
Training Epoch: 27 [768/9494]	Loss: 0.1848	LR: 0.004000
Training Epoch: 27 [1024/9494]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [1280/9494]	Loss: 0.1857	LR: 0.004000
Training Epoch: 27 [1536/9494]	Loss: 0.1555	LR: 0.004000
Training Epoch: 27 [1792/9494]	Loss: 0.1862	LR: 0.004000
Training Epoch: 27 [2048/9494]	Loss: 0.1611	LR: 0.004000
Training Epoch: 27 [2304/9494]	Loss: 0.1556	LR: 0.004000
Training Epoch: 27 [2560/9494]	Loss: 0.2331	LR: 0.004000
Training Epoch: 27 [2816/9494]	Loss: 0.1701	LR: 0.004000
Training Epoch: 27 [3072/9494]	Loss: 0.1679	LR: 0.004000
Training Epoch: 27 [3328/9494]	Loss: 0.1938	LR: 0.004000
Training Epoch: 27 [3584/9494]	Loss: 0.2059	LR: 0.004000
Training Epoch: 27 [3840/9494]	Loss: 0.2056	LR: 0.004000
Training Epoch: 27 [4096/9494]	Loss: 0.2098	LR: 0.004000
Training Epoch: 27 [4352/9494]	Loss: 0.1386	LR: 0.004000
Training Epoch: 27 [4608/9494]	Loss: 0.1854	LR: 0.004000
Training Epoch: 27 [4864/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 27 [5120/9494]	Loss: 0.1743	LR: 0.004000
Training Epoch: 27 [5376/9494]	Loss: 0.2185	LR: 0.004000
Training Epoch: 27 [5632/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 27 [5888/9494]	Loss: 0.2114	LR: 0.004000
Training Epoch: 27 [6144/9494]	Loss: 0.2109	LR: 0.004000
Training Epoch: 27 [6400/9494]	Loss: 0.2363	LR: 0.004000
Training Epoch: 27 [6656/9494]	Loss: 0.2136	LR: 0.004000
Training Epoch: 27 [6912/9494]	Loss: 0.1863	LR: 0.004000
Training Epoch: 27 [7168/9494]	Loss: 0.2104	LR: 0.004000
Training Epoch: 27 [7424/9494]	Loss: 0.1801	LR: 0.004000
Training Epoch: 27 [7680/9494]	Loss: 0.2115	LR: 0.004000
Training Epoch: 27 [7936/9494]	Loss: 0.1334	LR: 0.004000
Training Epoch: 27 [8192/9494]	Loss: 0.1624	LR: 0.004000
Training Epoch: 27 [8448/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 27 [8704/9494]	Loss: 0.2032	LR: 0.004000
Training Epoch: 27 [8960/9494]	Loss: 0.1747	LR: 0.004000
Training Epoch: 27 [9216/9494]	Loss: 0.1633	LR: 0.004000
Training Epoch: 27 [9472/9494]	Loss: 0.1931	LR: 0.004000
Training Epoch: 27 [9494/9494]	Loss: 0.1573	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1830, Train Accuracy: 0.9286
Epoch 27 training time consumed: 137.20s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0007, Accuracy: 0.9288, Time consumed:8.04s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_00h_30m_32s/ResNet18-MUCAC-seed3-ret100-27-best.pth
Training Epoch: 28 [256/9494]	Loss: 0.1239	LR: 0.004000
Training Epoch: 28 [512/9494]	Loss: 0.1761	LR: 0.004000
Training Epoch: 28 [768/9494]	Loss: 0.1910	LR: 0.004000
Training Epoch: 28 [1024/9494]	Loss: 0.1712	LR: 0.004000
Training Epoch: 28 [1280/9494]	Loss: 0.2266	LR: 0.004000
Training Epoch: 28 [1536/9494]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [1792/9494]	Loss: 0.1523	LR: 0.004000
Training Epoch: 28 [2048/9494]	Loss: 0.1564	LR: 0.004000
Training Epoch: 28 [2304/9494]	Loss: 0.1597	LR: 0.004000
Training Epoch: 28 [2560/9494]	Loss: 0.1609	LR: 0.004000
Training Epoch: 28 [2816/9494]	Loss: 0.2381	LR: 0.004000
Training Epoch: 28 [3072/9494]	Loss: 0.1824	LR: 0.004000
Training Epoch: 28 [3328/9494]	Loss: 0.1372	LR: 0.004000
Training Epoch: 28 [3584/9494]	Loss: 0.1438	LR: 0.004000
Training Epoch: 28 [3840/9494]	Loss: 0.1970	LR: 0.004000
Training Epoch: 28 [4096/9494]	Loss: 0.1576	LR: 0.004000
Training Epoch: 28 [4352/9494]	Loss: 0.1804	LR: 0.004000
Training Epoch: 28 [4608/9494]	Loss: 0.1940	LR: 0.004000
Training Epoch: 28 [4864/9494]	Loss: 0.1746	LR: 0.004000
Training Epoch: 28 [5120/9494]	Loss: 0.1396	LR: 0.004000
Training Epoch: 28 [5376/9494]	Loss: 0.1370	LR: 0.004000
Training Epoch: 28 [5632/9494]	Loss: 0.1750	LR: 0.004000
Training Epoch: 28 [5888/9494]	Loss: 0.1794	LR: 0.004000
Training Epoch: 28 [6144/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 28 [6400/9494]	Loss: 0.1504	LR: 0.004000
Training Epoch: 28 [6656/9494]	Loss: 0.1606	LR: 0.004000
Training Epoch: 28 [6912/9494]	Loss: 0.2076	LR: 0.004000
Training Epoch: 28 [7168/9494]	Loss: 0.1814	LR: 0.004000
Training Epoch: 28 [7424/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 28 [7680/9494]	Loss: 0.1338	LR: 0.004000
Training Epoch: 28 [7936/9494]	Loss: 0.1861	LR: 0.004000
Training Epoch: 28 [8192/9494]	Loss: 0.1873	LR: 0.004000
Training Epoch: 28 [8448/9494]	Loss: 0.1795	LR: 0.004000
Training Epoch: 28 [8704/9494]	Loss: 0.1196	LR: 0.004000
Training Epoch: 28 [8960/9494]	Loss: 0.2024	LR: 0.004000
Training Epoch: 28 [9216/9494]	Loss: 0.1948	LR: 0.004000
Training Epoch: 28 [9472/9494]	Loss: 0.1700	LR: 0.004000
Training Epoch: 28 [9494/9494]	Loss: 0.2118	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1705, Train Accuracy: 0.9296
Epoch 28 training time consumed: 137.38s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0007, Accuracy: 0.9225, Time consumed:8.23s
Training Epoch: 29 [256/9494]	Loss: 0.2007	LR: 0.004000
Training Epoch: 29 [512/9494]	Loss: 0.1648	LR: 0.004000
Training Epoch: 29 [768/9494]	Loss: 0.1708	LR: 0.004000
Training Epoch: 29 [1024/9494]	Loss: 0.2143	LR: 0.004000
Training Epoch: 29 [1280/9494]	Loss: 0.1612	LR: 0.004000
Training Epoch: 29 [1536/9494]	Loss: 0.2000	LR: 0.004000
Training Epoch: 29 [1792/9494]	Loss: 0.1448	LR: 0.004000
Training Epoch: 29 [2048/9494]	Loss: 0.2091	LR: 0.004000
Training Epoch: 29 [2304/9494]	Loss: 0.1896	LR: 0.004000
Training Epoch: 29 [2560/9494]	Loss: 0.1860	LR: 0.004000
Training Epoch: 29 [2816/9494]	Loss: 0.2245	LR: 0.004000
Training Epoch: 29 [3072/9494]	Loss: 0.1774	LR: 0.004000
Training Epoch: 29 [3328/9494]	Loss: 0.2091	LR: 0.004000
Training Epoch: 29 [3584/9494]	Loss: 0.1591	LR: 0.004000
Training Epoch: 29 [3840/9494]	Loss: 0.1887	LR: 0.004000
Training Epoch: 29 [4096/9494]	Loss: 0.1512	LR: 0.004000
Training Epoch: 29 [4352/9494]	Loss: 0.1674	LR: 0.004000
Training Epoch: 29 [4608/9494]	Loss: 0.1717	LR: 0.004000
Training Epoch: 29 [4864/9494]	Loss: 0.2298	LR: 0.004000
Training Epoch: 29 [5120/9494]	Loss: 0.1622	LR: 0.004000
Training Epoch: 29 [5376/9494]	Loss: 0.1550	LR: 0.004000
Training Epoch: 29 [5632/9494]	Loss: 0.2223	LR: 0.004000
Training Epoch: 29 [5888/9494]	Loss: 0.1947	LR: 0.004000
Training Epoch: 29 [6144/9494]	Loss: 0.1361	LR: 0.004000
Training Epoch: 29 [6400/9494]	Loss: 0.1789	LR: 0.004000
Training Epoch: 29 [6656/9494]	Loss: 0.2181	LR: 0.004000
Training Epoch: 29 [6912/9494]	Loss: 0.1783	LR: 0.004000
Training Epoch: 29 [7168/9494]	Loss: 0.1601	LR: 0.004000
Training Epoch: 29 [7424/9494]	Loss: 0.1568	LR: 0.004000
Training Epoch: 29 [7680/9494]	Loss: 0.2260	LR: 0.004000
Training Epoch: 29 [7936/9494]	Loss: 0.1758	LR: 0.004000
Training Epoch: 29 [8192/9494]	Loss: 0.1790	LR: 0.004000
Training Epoch: 29 [8448/9494]	Loss: 0.1461	LR: 0.004000
Training Epoch: 29 [8704/9494]	Loss: 0.1872	LR: 0.004000
Training Epoch: 29 [8960/9494]	Loss: 0.1376	LR: 0.004000
Training Epoch: 29 [9216/9494]	Loss: 0.1490	LR: 0.004000
Training Epoch: 29 [9472/9494]	Loss: 0.1433	LR: 0.004000
Training Epoch: 29 [9494/9494]	Loss: 0.0504	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1788, Train Accuracy: 0.9252
Epoch 29 training time consumed: 137.51s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9264, Time consumed:8.13s
Training Epoch: 30 [256/9494]	Loss: 0.1332	LR: 0.004000
Training Epoch: 30 [512/9494]	Loss: 0.1832	LR: 0.004000
Training Epoch: 30 [768/9494]	Loss: 0.1598	LR: 0.004000
Training Epoch: 30 [1024/9494]	Loss: 0.1924	LR: 0.004000
Training Epoch: 30 [1280/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 30 [1536/9494]	Loss: 0.1627	LR: 0.004000
Training Epoch: 30 [1792/9494]	Loss: 0.1734	LR: 0.004000
Training Epoch: 30 [2048/9494]	Loss: 0.1273	LR: 0.004000
Training Epoch: 30 [2304/9494]	Loss: 0.1274	LR: 0.004000
Training Epoch: 30 [2560/9494]	Loss: 0.1237	LR: 0.004000
Training Epoch: 30 [2816/9494]	Loss: 0.1605	LR: 0.004000
Training Epoch: 30 [3072/9494]	Loss: 0.2413	LR: 0.004000
Training Epoch: 30 [3328/9494]	Loss: 0.2057	LR: 0.004000
Training Epoch: 30 [3584/9494]	Loss: 0.2207	LR: 0.004000
Training Epoch: 30 [3840/9494]	Loss: 0.1650	LR: 0.004000
Training Epoch: 30 [4096/9494]	Loss: 0.1514	LR: 0.004000
Training Epoch: 30 [4352/9494]	Loss: 0.2100	LR: 0.004000
Training Epoch: 30 [4608/9494]	Loss: 0.1467	LR: 0.004000
Training Epoch: 30 [4864/9494]	Loss: 0.1348	LR: 0.004000
Training Epoch: 30 [5120/9494]	Loss: 0.1840	LR: 0.004000
Training Epoch: 30 [5376/9494]	Loss: 0.1907	LR: 0.004000
Training Epoch: 30 [5632/9494]	Loss: 0.2503	LR: 0.004000
Training Epoch: 30 [5888/9494]	Loss: 0.1279	LR: 0.004000
Training Epoch: 30 [6144/9494]	Loss: 0.1223	LR: 0.004000
Training Epoch: 30 [6400/9494]	Loss: 0.1703	LR: 0.004000
Training Epoch: 30 [6656/9494]	Loss: 0.1976	LR: 0.004000
Training Epoch: 30 [6912/9494]	Loss: 0.1179	LR: 0.004000
Training Epoch: 30 [7168/9494]	Loss: 0.2154	LR: 0.004000
Training Epoch: 30 [7424/9494]	Loss: 0.1383	LR: 0.004000
Training Epoch: 30 [7680/9494]	Loss: 0.1664	LR: 0.004000
Training Epoch: 30 [7936/9494]	Loss: 0.1471	LR: 0.004000
Training Epoch: 30 [8192/9494]	Loss: 0.1356	LR: 0.004000
Training Epoch: 30 [8448/9494]	Loss: 0.1631	LR: 0.004000
Training Epoch: 30 [8704/9494]	Loss: 0.1767	LR: 0.004000
Training Epoch: 30 [8960/9494]	Loss: 0.1955	LR: 0.004000
Training Epoch: 30 [9216/9494]	Loss: 0.1810	LR: 0.004000
Training Epoch: 30 [9472/9494]	Loss: 0.1639	LR: 0.004000
Training Epoch: 30 [9494/9494]	Loss: 0.0736	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1690, Train Accuracy: 0.9327
Epoch 30 training time consumed: 137.03s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0008, Accuracy: 0.9235, Time consumed:8.04s
Training Epoch: 31 [256/9494]	Loss: 0.1373	LR: 0.004000
Training Epoch: 31 [512/9494]	Loss: 0.1149	LR: 0.004000
Training Epoch: 31 [768/9494]	Loss: 0.1547	LR: 0.004000
Training Epoch: 31 [1024/9494]	Loss: 0.1891	LR: 0.004000
Training Epoch: 31 [1280/9494]	Loss: 0.2155	LR: 0.004000
Training Epoch: 31 [1536/9494]	Loss: 0.1744	LR: 0.004000
Training Epoch: 31 [1792/9494]	Loss: 0.1360	LR: 0.004000
Training Epoch: 31 [2048/9494]	Loss: 0.1480	LR: 0.004000
Training Epoch: 31 [2304/9494]	Loss: 0.1481	LR: 0.004000
Training Epoch: 31 [2560/9494]	Loss: 0.1726	LR: 0.004000
Training Epoch: 31 [2816/9494]	Loss: 0.1655	LR: 0.004000
Training Epoch: 31 [3072/9494]	Loss: 0.2043	LR: 0.004000
Training Epoch: 31 [3328/9494]	Loss: 0.1771	LR: 0.004000
Training Epoch: 31 [3584/9494]	Loss: 0.2148	LR: 0.004000
Training Epoch: 31 [3840/9494]	Loss: 0.1786	LR: 0.004000
Training Epoch: 31 [4096/9494]	Loss: 0.1303	LR: 0.004000
Training Epoch: 31 [4352/9494]	Loss: 0.1729	LR: 0.004000
Training Epoch: 31 [4608/9494]	Loss: 0.1545	LR: 0.004000
Training Epoch: 31 [4864/9494]	Loss: 0.1739	LR: 0.004000
Training Epoch: 31 [5120/9494]	Loss: 0.1479	LR: 0.004000
Training Epoch: 31 [5376/9494]	Loss: 0.1514	LR: 0.004000
Training Epoch: 31 [5632/9494]	Loss: 0.1310	LR: 0.004000
Training Epoch: 31 [5888/9494]	Loss: 0.1407	LR: 0.004000
Training Epoch: 31 [6144/9494]	Loss: 0.2095	LR: 0.004000
Training Epoch: 31 [6400/9494]	Loss: 0.1768	LR: 0.004000
Training Epoch: 31 [6656/9494]	Loss: 0.1669	LR: 0.004000
Training Epoch: 31 [6912/9494]	Loss: 0.1446	LR: 0.004000
Training Epoch: 31 [7168/9494]	Loss: 0.1288	LR: 0.004000
Training Epoch: 31 [7424/9494]	Loss: 0.1524	LR: 0.004000
Training Epoch: 31 [7680/9494]	Loss: 0.1576	LR: 0.004000
Training Epoch: 31 [7936/9494]	Loss: 0.1933	LR: 0.004000
Training Epoch: 31 [8192/9494]	Loss: 0.1478	LR: 0.004000
Training Epoch: 31 [8448/9494]	Loss: 0.1282	LR: 0.004000
Training Epoch: 31 [8704/9494]	Loss: 0.1329	LR: 0.004000
Training Epoch: 31 [8960/9494]	Loss: 0.1368	LR: 0.004000
Training Epoch: 31 [9216/9494]	Loss: 0.1772	LR: 0.004000
Training Epoch: 31 [9472/9494]	Loss: 0.1272	LR: 0.004000
Training Epoch: 31 [9494/9494]	Loss: 0.3785	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1603, Train Accuracy: 0.9333
Epoch 31 training time consumed: 137.72s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0009, Accuracy: 0.9220, Time consumed:8.10s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9494
Forget Train Dl:  1054
Retain Valid Dl:  9494
Forget Valid Dl:  1054
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 1054 samples
Set2 Distribution: 1054 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 92.40196228027344
Retain Accuracy: 92.1230239868164
Zero-Retain Forget (ZRF): 0.8098870515823364
Membership Inference Attack (MIA): 0.3301707779886148
Forget vs Retain Membership Inference Attack (MIA): 0.5545023696682464
Forget vs Test Membership Inference Attack (MIA): 0.5308056872037915
Test vs Retain Membership Inference Attack (MIA): 0.5242130750605327
Train vs Test Membership Inference Attack (MIA): 0.5326876513317191
Forget Set Accuracy (Df): 91.515625
Method Execution Time: 5773.17 seconds
