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

📌 S Retain class distribution for seed 9:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 9:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5547
  Class 1: 4473
Forget set:
  Class 0: 264
  Class 1: 264
./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 [256/10020]	Loss: 0.7069	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.6942	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.6897	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.7090	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 0.7168	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.7191	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 0.7090	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 0.7283	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 0.6903	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 0.6574	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.7493	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 0.8461	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 1.0789	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 1.0923	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.8769	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.7719	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.7510	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.7717	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 1.4590	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 1.5010	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 0.6855	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.8537	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7471	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.8094	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.6746	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7129	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.7595	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.7481	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.7970	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.6977	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.8844	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.6811	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.7101	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.7137	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.7062	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.6821	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.7503	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.7181	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.6719	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6637	LR: 0.097500
Epoch 1 - Average Train Loss: 0.7924, Train Accuracy: 0.5313
Epoch 1 training time consumed: 329.27s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0164, Accuracy: 0.5671, Time consumed:8.29s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.8273	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.6651	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.6955	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7132	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.7582	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.6925	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.7424	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.6815	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.7809	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.6769	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.7275	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.6877	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.7280	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.7141	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.6970	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.6660	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.6940	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.6593	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.6823	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.6880	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.7027	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.6508	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.6465	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.6576	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.6650	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.6644	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.7661	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.7100	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.7177	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.6620	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7109	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.7477	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.6618	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.6858	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.7265	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.6697	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.7291	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.7165	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.6642	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7013, Train Accuracy: 0.5614
Epoch 2 training time consumed: 147.15s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0030, Accuracy: 0.5719, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-2-best.pth
Training Epoch: 3 [256/10020]	Loss: 0.7097	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.6871	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.7178	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.6938	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.6603	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.6845	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.7599	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.7146	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.6273	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.6608	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.6763	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.7115	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.6859	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.6551	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.7101	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.6791	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.6718	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.6849	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.6717	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.6744	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.7091	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.6843	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.7497	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.6847	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.6918	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.6916	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.6653	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.6704	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6479	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.7129	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.6979	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6802	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.6752	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.7009	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.7141	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.6446	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6870, Train Accuracy: 0.5723
Epoch 3 training time consumed: 145.95s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0035, Accuracy: 0.5516, Time consumed:8.25s
Training Epoch: 4 [256/10020]	Loss: 0.7099	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.6637	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.7149	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.7150	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.7095	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6770	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.7052	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6893	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6900	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6960	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.7136	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.7134	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.7267	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.6772	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.7334	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.7556	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.7293	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.7017	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.6684	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.6904	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6950	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.6674	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6609	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6446	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6754	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6439	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.7040	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6430	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.6620	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6632	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.6782	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.6546	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6417	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6823	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6575	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6672	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.7542	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6859, Train Accuracy: 0.5771
Epoch 4 training time consumed: 146.22s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5956, Time consumed:8.21s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-4-best.pth
Training Epoch: 5 [256/10020]	Loss: 0.6245	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6827	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.6936	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.6751	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6859	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.6812	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.6747	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6704	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6627	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6687	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6701	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.7002	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6881	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.6494	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6788	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.6716	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6516	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6559	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6574	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6488	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6490	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6728	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.6635	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6998	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6472	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6897	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.6848	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6608	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6867	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6534	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6645	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6664	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6471	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.6987	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6691, Train Accuracy: 0.5918
Epoch 5 training time consumed: 146.47s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5724, Time consumed:8.07s
Training Epoch: 6 [256/10020]	Loss: 0.6708	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.6599	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.5981	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6291	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6583	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6488	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.6645	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.6426	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6558	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6311	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6440	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6475	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6345	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.6085	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6609	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6589	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6037	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6563	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6724	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6236	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6358	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6201	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6535	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6333	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6665	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6069	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6083	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6119	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6085	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.5917	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.5940	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6384	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6372	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.5824	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6403	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6225	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6574	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6033	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6359, Train Accuracy: 0.6426
Epoch 6 training time consumed: 146.11s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0029, Accuracy: 0.5893, Time consumed:8.25s
Training Epoch: 7 [256/10020]	Loss: 0.6125	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.5931	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.6775	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6356	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.5918	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.5923	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6488	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.5935	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6061	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.5457	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6917	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.5479	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6148	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6299	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6013	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6023	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.5695	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.5568	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.5599	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.4662	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.5975	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6037	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.5442	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.5513	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.5697	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.5422	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.5185	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.5717	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.5881	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.5594	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.5994	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.5981	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.5684	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.5309	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.5865	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.5238	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.5454	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.5334	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.4962	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.4439	LR: 0.100000
Epoch 7 - Average Train Loss: 0.5781, Train Accuracy: 0.7012
Epoch 7 training time consumed: 145.55s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0036, Accuracy: 0.6073, Time consumed:8.24s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-7-best.pth
Training Epoch: 8 [256/10020]	Loss: 0.5471	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6230	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.5291	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.5632	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.5307	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6134	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.5607	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.5575	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.5283	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.5867	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.5870	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.5720	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.5622	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.5797	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.5165	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.6063	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.5263	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.5572	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.5130	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.4832	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.5286	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.5630	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.4968	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.5125	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.4702	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.4906	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.5094	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.4314	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.4834	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.4611	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.5082	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.4532	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.5159	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.4961	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.5271	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.4260	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.4828	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.4721	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.4796	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.5486	LR: 0.100000
Epoch 8 - Average Train Loss: 0.5245, Train Accuracy: 0.7486
Epoch 8 training time consumed: 145.43s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0041, Accuracy: 0.5550, Time consumed:7.93s
Training Epoch: 9 [256/10020]	Loss: 0.5500	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.5609	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.5315	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.5313	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.5053	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.4783	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.5244	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.4940	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.4725	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.4789	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.4370	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.4796	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.5171	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.4823	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.5112	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.5854	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.5084	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.4314	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.5018	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.4535	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.4922	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.4468	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.4141	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.4559	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.4476	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.3864	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.4383	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.4355	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.4484	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.4217	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.4576	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.4058	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.3995	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.4435	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.3839	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.4063	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.4103	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.4192	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.4431	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.3142	LR: 0.100000
Epoch 9 - Average Train Loss: 0.4659, Train Accuracy: 0.7805
Epoch 9 training time consumed: 145.36s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0026, Accuracy: 0.7278, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-9-best.pth
Training Epoch: 10 [256/10020]	Loss: 0.4459	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.4054	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.4490	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.4189	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.4289	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.3545	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.3885	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.3614	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.3952	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.3841	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.3606	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.3511	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.4409	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.4002	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.3686	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.3523	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.4220	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.3753	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.4142	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.4154	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.3549	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.3482	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.3890	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.3840	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.3470	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.3705	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.3451	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.3330	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.4421	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.4086	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.3565	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.3775	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.4042	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.3951	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.3667	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.4496	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.3686	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.3883	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.3419	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.3769	LR: 0.020000
Epoch 10 - Average Train Loss: 0.3872, Train Accuracy: 0.8306
Epoch 10 training time consumed: 145.42s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0016, Accuracy: 0.8557, Time consumed:8.21s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.3055	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.4054	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.3638	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.3547	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.3398	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.4040	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.3549	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.3118	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.3191	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.3787	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.3524	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.3491	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.3411	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.3358	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.4060	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.3817	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.2678	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.3383	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.4320	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.3718	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.3863	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.3340	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.4201	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.3389	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.3513	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.3084	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.4250	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.2802	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.3196	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.3050	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.3349	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.3387	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.3399	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.3006	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.3381	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.3506	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.4134	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.3391	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.3164	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.3084	LR: 0.020000
Epoch 11 - Average Train Loss: 0.3500, Train Accuracy: 0.8490
Epoch 11 training time consumed: 145.31s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0017, Accuracy: 0.8295, Time consumed:7.84s
Training Epoch: 12 [256/10020]	Loss: 0.2998	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.3577	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.3544	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.3423	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.3021	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.3716	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.3580	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.3725	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.3377	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.3436	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.3535	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.3381	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.3939	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.3386	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.3623	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.2921	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.4200	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.3346	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.3390	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.3408	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.3163	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.3213	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.3074	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.3142	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.3042	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.4257	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.3834	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.3088	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.3638	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.3679	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.3100	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.3202	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.2715	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.3700	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.3537	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.2444	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.4038	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.3005	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.3076	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.2415	LR: 0.020000
Epoch 12 - Average Train Loss: 0.3393, Train Accuracy: 0.8568
Epoch 12 training time consumed: 145.44s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0016, Accuracy: 0.8484, Time consumed:8.16s
Training Epoch: 13 [256/10020]	Loss: 0.2988	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.3988	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.3086	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.2873	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.2857	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.2955	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.2680	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.3008	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.3268	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.3417	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.2971	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.3156	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.2867	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.3237	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.3734	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.2702	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.2749	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.3357	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.3368	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.3532	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.2625	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.3468	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.2891	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.2627	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.3032	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.2439	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.2956	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.2638	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.2869	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.3105	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.2727	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.2737	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.2786	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.2911	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.3234	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.3598	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.3202	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.2488	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.2615	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.1507	LR: 0.020000
Epoch 13 - Average Train Loss: 0.3014, Train Accuracy: 0.8715
Epoch 13 training time consumed: 145.15s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0016, Accuracy: 0.8354, Time consumed:8.01s
Training Epoch: 14 [256/10020]	Loss: 0.3157	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.3083	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.3086	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.3675	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.3730	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.2760	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.2667	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.3269	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.2962	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.2927	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.2661	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.3167	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.2947	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.3880	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.2440	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.2849	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.2764	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.2255	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.2775	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.2792	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.3200	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.2769	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.2890	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.3260	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.2383	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.2422	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.2861	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.2425	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.2968	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.3100	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.2395	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.2865	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.2910	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.2750	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.2285	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.2453	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.2975	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.2761	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.2439	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.3215	LR: 0.020000
Epoch 14 - Average Train Loss: 0.2872, Train Accuracy: 0.8785
Epoch 14 training time consumed: 147.77s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0020, Accuracy: 0.8344, Time consumed:7.91s
Training Epoch: 15 [256/10020]	Loss: 0.2198	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.2558	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.2815	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.2531	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.2669	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.2155	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.3421	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.2488	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.3688	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.3147	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.2704	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.3801	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.2572	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.2941	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.2156	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.2073	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.1917	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.2965	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.3018	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.3064	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.3100	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.2303	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.2848	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.2571	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.2660	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.2796	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.2130	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.2743	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.2376	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.2745	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.2764	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.2487	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.2444	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.2816	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.2397	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.2847	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.2774	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.2527	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.2306	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.3326	LR: 0.020000
Epoch 15 - Average Train Loss: 0.2682, Train Accuracy: 0.8859
Epoch 15 training time consumed: 145.41s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0017, Accuracy: 0.8416, Time consumed:8.11s
Training Epoch: 16 [256/10020]	Loss: 0.2356	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.3011	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.3116	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.3467	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.3533	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.2852	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.2494	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.2780	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.2743	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.3207	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.2649	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.2791	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.2542	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.2525	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.2909	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.2857	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.2692	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.2367	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.2399	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.2091	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.2890	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.2876	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.2105	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.2666	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.2306	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.2590	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.2413	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.2942	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.2213	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.2830	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.2328	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.2097	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.1960	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.2854	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.1772	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.1665	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.2442	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.2233	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.2259	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.1451	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2581, Train Accuracy: 0.8912
Epoch 16 training time consumed: 145.26s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0013, Accuracy: 0.8828, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-16-best.pth
Training Epoch: 17 [256/10020]	Loss: 0.2619	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.1981	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.2443	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.2435	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.2534	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.2445	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.2120	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.1913	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.2057	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.2580	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.2388	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.2923	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.2854	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.2297	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.2088	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.2540	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.2624	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.2125	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.2422	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.2709	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.2098	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.2337	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.3100	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.2059	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.2718	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.2246	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.2309	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.2646	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.1959	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.2956	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.2680	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.2935	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.2877	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.2439	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.2704	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.2556	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.2467	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.2551	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.2528	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.0857	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2462, Train Accuracy: 0.8991
Epoch 17 training time consumed: 145.60s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0014, Accuracy: 0.8843, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-17-best.pth
Training Epoch: 18 [256/10020]	Loss: 0.2429	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.2853	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.2494	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.2466	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.1870	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.2153	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.2113	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.2642	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.2275	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.2189	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.2045	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.2111	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.2414	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.2391	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.2101	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.2458	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.2248	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.2254	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.2025	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.1915	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.1835	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.2143	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2199	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.2092	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.2157	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.2782	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.1854	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.1764	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.1755	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.1647	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.2109	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.2142	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.1801	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.2151	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.2637	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.1999	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.1817	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.2265	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.1840	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.1752	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2163, Train Accuracy: 0.9131
Epoch 18 training time consumed: 145.68s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0019, Accuracy: 0.8368, Time consumed:8.18s
Training Epoch: 19 [256/10020]	Loss: 0.1839	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.1979	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.2133	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.1931	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.2421	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.1287	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.2041	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.1380	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2264	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.1557	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.1942	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.1900	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.2805	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.2913	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.2083	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.2073	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.2817	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.1878	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2496	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.2721	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.2302	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.2415	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2384	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.2441	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2031	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.2083	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.1601	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.2243	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.2627	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.1740	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.2289	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.2384	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.1709	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2094	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.2358	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.1854	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.1436	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.2562	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.2318	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.3204	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2141, Train Accuracy: 0.9117
Epoch 19 training time consumed: 145.30s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0011, Accuracy: 0.8944, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-19-best.pth
Training Epoch: 20 [256/10020]	Loss: 0.2672	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.2377	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.2223	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.2009	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.3208	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.1653	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.1594	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.2090	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.1676	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.1885	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.1834	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.2459	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.1623	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.2514	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.1723	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.1507	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.1971	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.1807	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.1518	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.1842	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.2001	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.1371	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.2312	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1538	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.1770	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.1966	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.1711	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.2162	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.1492	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.2098	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.2073	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.1609	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1841	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.1190	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1560	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.2061	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.2010	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1886, Train Accuracy: 0.9222
Epoch 20 training time consumed: 145.09s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1527	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.1963	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.1717	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.2062	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.1916	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.1898	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.1926	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.1808	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.1992	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.1799	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1700	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.2009	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.2246	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1494	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.2158	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.2004	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.1960	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.1481	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1409	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.2017	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1705	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.2041	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1517	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.1632	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.1616	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.1589	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.1552	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.1211	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.2049	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.1583	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.1899	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.2952	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1707, Train Accuracy: 0.9328
Epoch 21 training time consumed: 145.09s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9341, Time consumed:7.93s
Training Epoch: 22 [256/10020]	Loss: 0.1267	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.2276	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1601	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.1295	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.1343	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1849	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.2094	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1590	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1979	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.1691	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.2038	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1732	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1559	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1459	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.1301	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.2004	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1584	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.1821	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1793	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1708	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.2114	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1746	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1558	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1471	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1367	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1240	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1424	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.1704	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.1926	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.1794	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.1239	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1861	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1637	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.1721	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.0995	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1660, Train Accuracy: 0.9341
Epoch 22 training time consumed: 145.23s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0007, Accuracy: 0.9259, Time consumed:8.21s
Training Epoch: 23 [256/10020]	Loss: 0.1030	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1631	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.2024	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.2034	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1830	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.1424	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.1281	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.1848	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.2049	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1304	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.1866	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.1729	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1380	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1905	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1585	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1105	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1419	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1769	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1844	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1923	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.2003	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1658	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.1016	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.0945	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.1484	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1625	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1909	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1765	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.1602	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1727	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1502	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.0605	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1597, Train Accuracy: 0.9351
Epoch 23 training time consumed: 145.23s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:8.06s
Training Epoch: 24 [256/10020]	Loss: 0.1657	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.1880	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1975	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1226	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.1272	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1483	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1965	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1307	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1164	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1089	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.1056	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.1720	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1286	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1652	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1745	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1845	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1695	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1568	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1521	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1332	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1807	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.2149	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1556	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.1912	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.1886	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.1609	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.0983	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1558, Train Accuracy: 0.9356
Epoch 24 training time consumed: 145.20s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-24-best.pth
Training Epoch: 25 [256/10020]	Loss: 0.1588	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.2217	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1276	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1963	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1100	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1408	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.1539	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1730	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1197	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.2333	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.0970	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.1211	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1806	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.1678	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1106	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.1262	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1468	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1364	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1377	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1328	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1604	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1753	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.1780	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1985	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.1669	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.2135	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1295	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.1924	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.1922	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1351	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1326	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1783	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.2062	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1816	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.1362	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1581, Train Accuracy: 0.9350
Epoch 25 training time consumed: 145.28s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:8.21s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-25-best.pth
Training Epoch: 26 [256/10020]	Loss: 0.1726	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1207	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1929	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1342	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1461	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1462	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1222	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1639	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.2072	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1360	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1688	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1814	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1699	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.1796	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1319	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.1256	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1208	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1972	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1764	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1800	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1411	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1535	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1547	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.2145	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1364	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.1229	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1578	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1638	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.1830	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1539, Train Accuracy: 0.9371
Epoch 26 training time consumed: 145.13s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0007, Accuracy: 0.9308, Time consumed:7.88s
Training Epoch: 27 [256/10020]	Loss: 0.2116	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.0991	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1372	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1777	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1020	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1451	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1341	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1272	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1436	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.1457	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1684	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.1715	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1373	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1148	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1275	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.1412	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1812	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1195	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1190	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1468	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.1886	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1783	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1628	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1271	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1395	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1703	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1205	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1157	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1150	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1285	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.1825	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1876	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1449	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.1525	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1471, Train Accuracy: 0.9406
Epoch 27 training time consumed: 145.30s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:8.12s
Training Epoch: 28 [256/10020]	Loss: 0.1388	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1683	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1091	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.1417	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1474	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1684	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.1193	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1328	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1572	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1068	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1726	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1605	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1548	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1764	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1477	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1503	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.1080	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1738	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.2102	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1221	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1635	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.1053	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1411	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1102	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1458	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.0997	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1181	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1700	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1357	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1167	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1359	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1820	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1348	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1153	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1710	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.2330	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1439, Train Accuracy: 0.9419
Epoch 28 training time consumed: 145.16s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:8.12s
Training Epoch: 29 [256/10020]	Loss: 0.1245	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1499	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.1117	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1350	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.1121	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1619	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1641	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1437	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.1936	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.2278	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1179	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1867	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1521	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1698	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1693	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1567	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.1697	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.1462	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1133	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1118	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.1537	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1161	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.1443	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.1280	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.1924	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.1440	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1382	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1565	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1482	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1460	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1189	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.2313	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1350	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1063	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1372	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.1764	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1487, Train Accuracy: 0.9405
Epoch 29 training time consumed: 145.23s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:7.94s
Saving weights file to checkpoint/retrain/ResNet18/Sunday_27_July_2025_09h_02m_00s/ResNet18-MUCAC-seed9-ret50-29-best.pth
Training Epoch: 30 [256/10020]	Loss: 0.1434	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1361	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1212	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1188	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.1806	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.1356	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.0870	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1301	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1400	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1422	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1157	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1067	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1262	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1672	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1038	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1347	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1532	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1066	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.1290	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1622	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1332	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1291	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1089	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1100	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1037	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.2143	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1238	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1543	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1495	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1525	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.2056	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.2080	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1308	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1495	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.1241	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1397, Train Accuracy: 0.9433
Epoch 30 training time consumed: 145.40s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:8.28s
Training Epoch: 31 [256/10020]	Loss: 0.2094	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1307	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1767	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.0998	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1255	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1787	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.0981	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1273	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1174	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.1018	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1591	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.1369	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.1199	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1240	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1387	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1586	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1437	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1359	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1091	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1726	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.1459	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1512	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1291	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1780	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1619	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1029	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.2270	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.1878	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.0668	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1279	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1057	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1564	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.1342	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.0995	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1437, Train Accuracy: 0.9402
Epoch 31 training time consumed: 145.31s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:7.88s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10020
Forget Train Dl:  528
Retain Valid Dl:  10020
Forget Valid Dl:  528
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 528 samples
Set2 Distribution: 528 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 94.79166412353516
Retain Accuracy: 94.4607162475586
Zero-Retain Forget (ZRF): 0.7850565314292908
Membership Inference Attack (MIA): 0.30303030303030304
Forget vs Retain Membership Inference Attack (MIA): 0.5424528301886793
Forget vs Test Membership Inference Attack (MIA): 0.5377358490566038
Test vs Retain Membership Inference Attack (MIA): 0.5084745762711864
Train vs Test Membership Inference Attack (MIA): 0.5096852300242131
Forget Set Accuracy (Df): 91.796875
Method Execution Time: 5911.55 seconds
