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

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

📌 S Forget class distribution for seed 1:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5415
  Class 1: 4341
Forget set:
  Class 0: 396
  Class 1: 396
./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 [256/9756]	Loss: 0.6843	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.6755	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6860	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.7129	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.7032	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7043	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.6865	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.6936	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.6951	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 0.6997	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.6717	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 0.7974	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 1.2412	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 1.1465	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 0.8482	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 0.9131	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 1.2771	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 1.3686	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.6896	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 1.1093	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 1.0729	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.7013	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 1.0347	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.8190	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 1.0584	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7010	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 1.1937	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.8326	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.9645	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.9453	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.7235	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.7575	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.9394	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.6929	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 0.8407	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 0.7327	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.7390	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 0.8139	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 0.7263	LR: 0.097436
Epoch 1 - Average Train Loss: 0.8566, Train Accuracy: 0.5243
Epoch 1 training time consumed: 366.66s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0087, Accuracy: 0.5375, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.7325	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 0.7626	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.7245	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.7275	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 0.6967	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7117	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7112	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.7140	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.7153	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.6831	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.6950	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.7248	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.7137	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.7052	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.6822	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.7056	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.7023	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7017	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.6964	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.7027	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.6777	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.6961	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.6966	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.6955	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.6901	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.6747	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.6841	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.6853	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.6826	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.6887	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.6758	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.6720	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.6493	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6790	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.7037	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.6574	LR: 0.100000
Epoch 2 - Average Train Loss: 0.6973, Train Accuracy: 0.5375
Epoch 2 training time consumed: 141.41s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0031, Accuracy: 0.5390, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-2-best.pth
Training Epoch: 3 [256/9756]	Loss: 0.6777	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 0.6587	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7169	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.6923	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.6929	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.6701	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.6692	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.6742	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.6878	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.6896	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.6935	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.6633	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.6944	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.6747	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.6697	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.6833	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.6817	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6798	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6683	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.6912	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.6661	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.6756	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.6960	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.6880	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6940	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.7033	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6834	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6731	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6804	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.7186	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6796	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.6562	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6820, Train Accuracy: 0.5707
Epoch 3 training time consumed: 141.09s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.6034, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-3-best.pth
Training Epoch: 4 [256/9756]	Loss: 0.6825	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.6740	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.6916	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.6937	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6872	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.6619	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6646	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.6743	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6755	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6771	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.6591	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.6856	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6883	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6931	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.6766	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.6505	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6637	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6765	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.6811	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6670	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6831	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6621	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6567	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.6908	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6847	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6674	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6708	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6519	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6579	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6741, Train Accuracy: 0.5856
Epoch 4 training time consumed: 141.08s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.5826, Time consumed:8.08s
Training Epoch: 5 [256/9756]	Loss: 0.6668	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.6535	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6746	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.6741	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.6820	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.6761	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6963	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.6602	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.6906	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.6814	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.6818	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6710	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6725	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6817	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6952	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6829	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6910	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.6713	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6696	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6598	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6540	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6531	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6460	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.6628	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.6521	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6536	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6463	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.7331	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6662	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6636	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.7000	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6542	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6803	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6525	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6729, Train Accuracy: 0.5908
Epoch 5 training time consumed: 141.49s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0029, Accuracy: 0.5918, Time consumed:7.84s
Training Epoch: 6 [256/9756]	Loss: 0.6710	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6596	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.7081	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.7323	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6544	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6875	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6983	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6646	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6584	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6869	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6915	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6727	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6826	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6931	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6830	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6574	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6809	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6750	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.6824	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6810	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6626	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6618	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.6698	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6637	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6482	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6549	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6518	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.7199	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6642	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6420	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6652	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6859	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6483	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6746	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6742, Train Accuracy: 0.5861
Epoch 6 training time consumed: 141.67s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5627, Time consumed:8.13s
Training Epoch: 7 [256/9756]	Loss: 0.6553	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6636	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6742	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6562	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6692	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6221	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6478	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6406	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6375	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6409	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6689	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6165	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.6197	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.6558	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6016	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6479	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6477	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.5852	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6472	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6231	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.5981	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6379	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6222	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6447	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.5874	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6114	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.5897	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6172	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6231	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6230	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6243	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6213	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.5802	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.5568	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.5855	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6038	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.7364	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6289, Train Accuracy: 0.6526
Epoch 7 training time consumed: 141.11s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0031, Accuracy: 0.5584, Time consumed:8.06s
Training Epoch: 8 [256/9756]	Loss: 0.6638	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6400	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.5826	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.6186	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6348	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.5927	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6035	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6240	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.5995	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.5766	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.5788	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.5866	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.5379	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6490	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6318	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6064	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6121	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.5846	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.5804	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.5560	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.5930	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.5937	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6162	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.5945	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6728	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.5988	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.5845	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.5980	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6016	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.5967	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.5992	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6320	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.5393	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.5982	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.5646	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.5419	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6021	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.5344	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.6256	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5980, Train Accuracy: 0.6836
Epoch 8 training time consumed: 141.44s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0032, Accuracy: 0.5864, Time consumed:8.11s
Training Epoch: 9 [256/9756]	Loss: 0.5990	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.5781	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.5978	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.5246	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6198	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.5458	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.5388	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.5315	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.5986	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.5725	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.5234	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.5407	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.5574	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.4979	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.5188	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.4963	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.5006	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.5508	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.5118	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.4995	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.4604	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.4937	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.5454	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.5345	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.4782	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.5372	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.5042	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.5244	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.4936	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.5178	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.4929	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.4914	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.5403	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.5056	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.5329	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.4820	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.4982	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.5561	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.4087	LR: 0.100000
Epoch 9 - Average Train Loss: 0.5284, Train Accuracy: 0.7407
Epoch 9 training time consumed: 141.32s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0025, Accuracy: 0.7056, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-9-best.pth
Training Epoch: 10 [256/9756]	Loss: 0.4760	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.5633	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.4569	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.5137	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.4267	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.4466	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.4506	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.4705	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.4039	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.4752	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.4406	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.4164	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.4448	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.3660	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.4563	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.4015	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.3838	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.4687	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.4071	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.3884	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.4092	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.4506	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.4866	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.4549	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.4566	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.4242	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.3911	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.3923	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.4098	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.3947	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.4404	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.4364	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.4702	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.4644	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.4543	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.4171	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.4318	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.4046	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.5328	LR: 0.020000
Epoch 10 - Average Train Loss: 0.4383, Train Accuracy: 0.7952
Epoch 10 training time consumed: 141.34s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0017, Accuracy: 0.8363, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-10-best.pth
Training Epoch: 11 [256/9756]	Loss: 0.3911	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.3980	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.4403	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.4156	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.4264	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.4065	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.4079	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.3836	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.4204	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.4450	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.4252	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.4075	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.3984	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.4025	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.3939	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.3673	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.4122	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.3750	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.3866	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.3849	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.3582	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.3994	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.4127	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.3610	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.3876	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.4179	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.3499	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.3621	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.3897	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.3318	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.3758	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.3709	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.3246	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.3253	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.3586	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.3604	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.3096	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.3478	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.2806	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3847, Train Accuracy: 0.8279
Epoch 11 training time consumed: 141.26s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0017, Accuracy: 0.8450, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.3424	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.3493	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.3760	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.3937	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.3603	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.3690	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.3847	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.3831	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.4161	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.3771	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.3959	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.4603	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.3397	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.3826	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.3432	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.3614	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.3449	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.3021	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.3279	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.3365	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.3412	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.4053	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.3327	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.3294	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.3855	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.3966	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.3834	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.3064	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.2920	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.3169	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.3525	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.3827	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.3043	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.3603	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.3025	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.3540	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.3862	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.3094	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.3907	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3577, Train Accuracy: 0.8390
Epoch 12 training time consumed: 141.14s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0027, Accuracy: 0.7002, Time consumed:7.99s
Training Epoch: 13 [256/9756]	Loss: 0.4473	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.3776	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.4023	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.3276	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.3227	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.3472	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.3658	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.3225	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.3267	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.3497	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.3139	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.3052	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.3409	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.2829	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.3100	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.3244	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.3328	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.2761	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.3206	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.2426	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.3013	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.3004	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.2628	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.2856	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.2833	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.3242	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.3717	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.2521	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.2375	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.2333	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.2522	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.2993	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.3796	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.3025	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.3100	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.3288	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.3269	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.3053	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.2063	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3154, Train Accuracy: 0.8663
Epoch 13 training time consumed: 141.24s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0028, Accuracy: 0.7002, Time consumed:7.84s
Training Epoch: 14 [256/9756]	Loss: 0.2202	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.1912	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.2945	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.3743	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.3062	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.3089	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.2826	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.2569	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.3011	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.3356	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.2483	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.2876	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.2945	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.2964	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.2508	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.2624	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.3131	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.1979	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.2963	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.2103	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.3169	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.2676	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.2770	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.2257	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.2554	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.2999	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.2499	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.2105	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.2466	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.2851	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.3466	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.2793	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.2102	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.2681	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.2939	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.2760	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.3259	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.2106	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.3183	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2731, Train Accuracy: 0.8886
Epoch 14 training time consumed: 141.02s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0014, Accuracy: 0.8678, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-14-best.pth
Training Epoch: 15 [256/9756]	Loss: 0.2554	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.2519	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.3061	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.2629	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.2265	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.2598	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.2505	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.2527	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.2343	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.2305	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.2722	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.2320	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.2243	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.2372	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.2261	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.3776	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.3196	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.2943	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.2640	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.2329	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.1643	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.2648	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.2470	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.2554	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.1983	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.2175	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.1943	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.2453	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.2410	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.2430	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.3251	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.3086	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.1824	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.2435	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.2753	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.2111	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.2072	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.2849	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.1142	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2501, Train Accuracy: 0.8964
Epoch 15 training time consumed: 142.16s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0011, Accuracy: 0.9041, Time consumed:8.16s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-15-best.pth
Training Epoch: 16 [256/9756]	Loss: 0.2138	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.2252	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.2019	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.2182	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.2296	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.2267	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.2200	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.2079	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.2717	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.2032	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.2746	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.2070	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.2367	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.3096	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.2545	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.2152	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.2431	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.2273	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.2355	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.2970	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.2594	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.2732	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.2139	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.1920	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.2228	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.2782	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.2391	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.2207	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.2098	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.1788	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.2040	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.1982	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.1726	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.2110	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.1626	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.2014	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.2050	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.2607	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.3759	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2273, Train Accuracy: 0.9020
Epoch 16 training time consumed: 141.55s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0008, Accuracy: 0.9225, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-16-best.pth
Training Epoch: 17 [256/9756]	Loss: 0.2202	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.3056	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.3184	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.2305	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.2164	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.2091	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.2435	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.2762	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.2515	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.2416	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.2608	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.2793	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.1926	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.1742	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.2020	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.2766	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.2333	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.2630	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.2745	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.2098	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.1773	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.2196	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.3037	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.2272	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.2540	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.2224	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.1676	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.1740	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.2291	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.2124	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.2749	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.2375	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.2045	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.2105	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.2074	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.2651	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.1773	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.2038	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.1499	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2326, Train Accuracy: 0.9055
Epoch 17 training time consumed: 141.56s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0010, Accuracy: 0.9070, Time consumed:7.97s
Training Epoch: 18 [256/9756]	Loss: 0.2503	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.2153	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.2071	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2033	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.2448	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.2833	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.2180	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.1999	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.1882	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.2002	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.3012	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.1801	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.2372	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.2383	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.2345	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.1674	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.1778	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.2134	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.1557	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.2321	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2119	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.1711	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.1723	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.2433	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.1927	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.2106	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.2420	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.1981	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.1661	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.2126	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.1675	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.1474	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.1885	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.2110	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.2449	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.2096	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.1940	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.1739	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.4477	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2087, Train Accuracy: 0.9121
Epoch 18 training time consumed: 140.95s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0018, Accuracy: 0.8538, Time consumed:8.15s
Training Epoch: 19 [256/9756]	Loss: 0.2301	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.2928	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.2987	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.2414	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.2443	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.2467	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.2179	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.2500	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.2125	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.2224	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.2360	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.1868	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.2042	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.2672	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.2195	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.1937	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.1801	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.2128	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.2137	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2251	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.2166	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.1747	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.1858	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.1806	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.2218	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.2007	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.1842	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.1924	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.1899	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.1744	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.1504	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.2066	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.2117	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.1597	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.1881	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.2324	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.1891	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.2070	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.2035	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2121, Train Accuracy: 0.9113
Epoch 19 training time consumed: 141.23s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0018, Accuracy: 0.8465, Time consumed:8.23s
Training Epoch: 20 [256/9756]	Loss: 0.1857	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.2346	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.2204	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2055	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.2043	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.2054	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.1306	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.1898	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.1705	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.1976	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.2332	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.1598	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.1598	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.1714	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.1831	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.1828	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.1757	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.1949	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.1746	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.1269	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.1422	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.1851	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.2238	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.1708	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.1424	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.1402	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.1905	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.1487	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.1317	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.1652	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.1341	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.1518	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.0958	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1730, Train Accuracy: 0.9271
Epoch 20 training time consumed: 141.51s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9346, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.1295	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.1728	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.1200	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.1800	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.1410	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.1623	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.1405	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.2077	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.1486	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.1238	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.1358	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.1502	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.2174	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.1107	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.1461	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.1701	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.1781	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.1761	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.1268	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.1730	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.1724	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.1683	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.1869	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.1521	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1160	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.1796	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.1509	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.1760	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.1640	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.1340	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.1196	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.1887	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.1630	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.1814	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.2160	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1569, Train Accuracy: 0.9343
Epoch 21 training time consumed: 141.35s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9361, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-21-best.pth
Training Epoch: 22 [256/9756]	Loss: 0.1327	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.1798	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.1542	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.1846	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.1525	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.1191	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.1722	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.1687	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.1824	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.1377	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.1637	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.1813	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.2273	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.1721	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.1284	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.1509	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.1509	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.1562	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.1578	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.1699	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.1707	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.1260	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.1645	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.1050	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.1621	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.1332	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.1500	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.1065	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.1859	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.1448	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.1207	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.1059	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.1884	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.2334	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.1438	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.2108	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.0789	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1579, Train Accuracy: 0.9330
Epoch 22 training time consumed: 141.22s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0005, Accuracy: 0.9438, Time consumed:8.08s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-22-best.pth
Training Epoch: 23 [256/9756]	Loss: 0.1398	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.1407	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.1828	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.2251	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.1297	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.1466	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.1680	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.1657	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.1283	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.1275	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.1419	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.1337	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.1336	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.2247	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1987	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.1597	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1211	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.1274	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.1189	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.1686	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.1258	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.2035	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.1616	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.1341	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.1548	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1307	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.1373	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.1309	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.1421	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.1446	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.1525	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1807	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.1125	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1525, Train Accuracy: 0.9360
Epoch 23 training time consumed: 141.30s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.97s
Training Epoch: 24 [256/9756]	Loss: 0.1237	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.1176	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1725	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.1269	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.1308	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.1498	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.1515	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.1226	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1611	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1597	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.1125	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.1293	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.1924	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.1814	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.1501	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.1134	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.1238	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.1698	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.1322	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.1645	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.1460	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.1585	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.1388	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.1540	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.2115	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.1670	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.1469	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.1153	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.1113	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.1633	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.1555	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.1929	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.1138	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1544	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.1702	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.2902	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1488, Train Accuracy: 0.9395
Epoch 24 training time consumed: 141.18s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0005, Accuracy: 0.9472, Time consumed:7.86s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-24-best.pth
Training Epoch: 25 [256/9756]	Loss: 0.1359	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.1567	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.1436	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1931	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.1472	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.1582	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.2191	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.1279	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.1675	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.1483	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1837	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.1861	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.1170	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.1149	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.1448	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.1054	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.1294	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.1395	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.1430	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1212	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.1221	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.1293	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.1781	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.1642	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.1954	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.1401	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1411	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.1216	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1334	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.1131	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1253	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1408	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.1826	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.1463	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.0562	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1471, Train Accuracy: 0.9372
Epoch 25 training time consumed: 141.23s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9477, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-25-best.pth
Training Epoch: 26 [256/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.1518	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.1516	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.1300	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.1195	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.1227	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.1266	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.1815	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.1973	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.1759	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.1515	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.1679	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.1128	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.0959	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.1782	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.1082	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.1465	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1406	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.1137	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1778	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1436	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.1153	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.1232	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1540	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1723	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.1074	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.2053	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1475	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1455	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1560	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.1155	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.1747	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.0893	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1278	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1848	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.1638	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.1358	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1463, Train Accuracy: 0.9379
Epoch 26 training time consumed: 141.40s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0005, Accuracy: 0.9453, Time consumed:8.16s
Training Epoch: 27 [256/9756]	Loss: 0.1276	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.1350	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.1168	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.1329	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.1575	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.1999	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1643	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.1236	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.1226	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.1072	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.1188	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.0974	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.1590	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.1003	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.1864	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.1398	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.1435	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1801	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.1355	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.1330	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.1818	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.1267	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.1563	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.1232	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.1683	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1347	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.1383	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1335	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1470	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.0944	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.2113	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.1786	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.1006	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.1743	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.1814	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1427, Train Accuracy: 0.9415
Epoch 27 training time consumed: 141.37s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0005, Accuracy: 0.9496, Time consumed:7.81s
Saving weights file to checkpoint/retrain/ResNet18/Friday_25_July_2025_21h_04m_38s/ResNet18-MUCAC-seed1-ret25-27-best.pth
Training Epoch: 28 [256/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.0966	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.1690	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.1526	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.1265	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1498	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.1887	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.1020	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.1158	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1021	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1163	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.1684	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1495	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1788	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.1673	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1569	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.1480	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1530	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.1172	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.1122	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1985	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.1726	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1812	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1731	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1216	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.1281	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.1484	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.1310	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.1320	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1054	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1076	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.0957	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1449	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.2102	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1420, Train Accuracy: 0.9417
Epoch 28 training time consumed: 141.26s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0005, Accuracy: 0.9482, Time consumed:7.99s
Training Epoch: 29 [256/9756]	Loss: 0.1447	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1506	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1176	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1548	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.1742	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.1389	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.1212	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.0874	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.1337	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.1236	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.1326	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1042	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1331	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.1863	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1044	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1043	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.1626	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1975	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.1319	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1922	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.1330	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.1806	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.1194	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.1505	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1559	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.1288	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.1420	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.1083	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.1240	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.2837	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1519	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.1870	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1815	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.1269	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.1440	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.2739	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1463, Train Accuracy: 0.9386
Epoch 29 training time consumed: 141.36s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:8.02s
Training Epoch: 30 [256/9756]	Loss: 0.1612	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.1558	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.1647	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1544	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1433	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.1677	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.1341	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1604	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1449	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.0917	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.1326	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1708	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1213	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.2221	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.1001	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.1522	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1096	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.1440	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.1854	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.1138	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1388	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1301	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.1153	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.1355	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.1782	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.0952	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.1374	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1117	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.1046	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.1823	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1669	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.1619	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.1088	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.2097	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.1490	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1443, Train Accuracy: 0.9382
Epoch 30 training time consumed: 141.71s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0005, Accuracy: 0.9462, Time consumed:8.03s
Training Epoch: 31 [256/9756]	Loss: 0.0984	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.1473	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1344	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.1466	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1213	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.1574	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1064	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.1448	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.0996	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.1697	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.1068	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.1690	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.1349	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.2006	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.1446	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1954	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1202	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1793	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1410	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.0954	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.1104	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.1048	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.1210	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.1425	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1471	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.1257	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.0999	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1056	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1464	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1194	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1400	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1360	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.1292	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.1307	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1368, Train Accuracy: 0.9424
Epoch 31 training time consumed: 141.39s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0005, Accuracy: 0.9487, Time consumed:7.82s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9756
Forget Train Dl:  792
Retain Valid Dl:  9756
Forget Valid Dl:  792
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.78911590576172
Retain Accuracy: 94.66861724853516
Zero-Retain Forget (ZRF): 0.7642453908920288
Membership Inference Attack (MIA): 0.32575757575757575
Forget vs Retain Membership Inference Attack (MIA): 0.5457413249211357
Forget vs Test Membership Inference Attack (MIA): 0.5709779179810726
Test vs Retain Membership Inference Attack (MIA): 0.5157384987893463
Train vs Test Membership Inference Attack (MIA): 0.5351089588377724
Forget Set Accuracy (Df): 92.64323425292969
Method Execution Time: 5821.52 seconds
