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

📌 S Retain class distribution for seed 4:
Class 0: 5284
Class 1: 4210

📌 S Forget class distribution for seed 4:
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: 0.7768	LR: 0.000000
Training Epoch: 1 [512/10020]	Loss: 0.7976	LR: 0.002500
Training Epoch: 1 [768/10020]	Loss: 0.7378	LR: 0.005000
Training Epoch: 1 [1024/10020]	Loss: 0.8064	LR: 0.007500
Training Epoch: 1 [1280/10020]	Loss: 1.1284	LR: 0.010000
Training Epoch: 1 [1536/10020]	Loss: 0.9044	LR: 0.012500
Training Epoch: 1 [1792/10020]	Loss: 1.2627	LR: 0.015000
Training Epoch: 1 [2048/10020]	Loss: 1.1697	LR: 0.017500
Training Epoch: 1 [2304/10020]	Loss: 1.1642	LR: 0.020000
Training Epoch: 1 [2560/10020]	Loss: 1.2813	LR: 0.022500
Training Epoch: 1 [2816/10020]	Loss: 0.6559	LR: 0.025000
Training Epoch: 1 [3072/10020]	Loss: 1.3336	LR: 0.027500
Training Epoch: 1 [3328/10020]	Loss: 0.8038	LR: 0.030000
Training Epoch: 1 [3584/10020]	Loss: 1.3066	LR: 0.032500
Training Epoch: 1 [3840/10020]	Loss: 0.7995	LR: 0.035000
Training Epoch: 1 [4096/10020]	Loss: 0.8878	LR: 0.037500
Training Epoch: 1 [4352/10020]	Loss: 0.8575	LR: 0.040000
Training Epoch: 1 [4608/10020]	Loss: 0.7038	LR: 0.042500
Training Epoch: 1 [4864/10020]	Loss: 0.7173	LR: 0.045000
Training Epoch: 1 [5120/10020]	Loss: 0.8490	LR: 0.047500
Training Epoch: 1 [5376/10020]	Loss: 0.7700	LR: 0.050000
Training Epoch: 1 [5632/10020]	Loss: 0.7432	LR: 0.052500
Training Epoch: 1 [5888/10020]	Loss: 0.7425	LR: 0.055000
Training Epoch: 1 [6144/10020]	Loss: 0.8150	LR: 0.057500
Training Epoch: 1 [6400/10020]	Loss: 0.6918	LR: 0.060000
Training Epoch: 1 [6656/10020]	Loss: 0.7227	LR: 0.062500
Training Epoch: 1 [6912/10020]	Loss: 0.7184	LR: 0.065000
Training Epoch: 1 [7168/10020]	Loss: 0.8386	LR: 0.067500
Training Epoch: 1 [7424/10020]	Loss: 0.6962	LR: 0.070000
Training Epoch: 1 [7680/10020]	Loss: 0.7351	LR: 0.072500
Training Epoch: 1 [7936/10020]	Loss: 0.7534	LR: 0.075000
Training Epoch: 1 [8192/10020]	Loss: 0.7499	LR: 0.077500
Training Epoch: 1 [8448/10020]	Loss: 0.6936	LR: 0.080000
Training Epoch: 1 [8704/10020]	Loss: 0.7184	LR: 0.082500
Training Epoch: 1 [8960/10020]	Loss: 0.8571	LR: 0.085000
Training Epoch: 1 [9216/10020]	Loss: 0.7425	LR: 0.087500
Training Epoch: 1 [9472/10020]	Loss: 0.7033	LR: 0.090000
Training Epoch: 1 [9728/10020]	Loss: 0.6994	LR: 0.092500
Training Epoch: 1 [9984/10020]	Loss: 0.7211	LR: 0.095000
Training Epoch: 1 [10020/10020]	Loss: 0.6964	LR: 0.097500
Epoch 1 - Average Train Loss: 0.8471, Train Accuracy: 0.5119
Epoch 1 training time consumed: 7985.01s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0037, Accuracy: 0.5346, Time consumed:423.87s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-1-best.pth
Training Epoch: 2 [256/10020]	Loss: 0.7345	LR: 0.100000
Training Epoch: 2 [512/10020]	Loss: 0.7541	LR: 0.100000
Training Epoch: 2 [768/10020]	Loss: 0.6884	LR: 0.100000
Training Epoch: 2 [1024/10020]	Loss: 0.7214	LR: 0.100000
Training Epoch: 2 [1280/10020]	Loss: 0.6841	LR: 0.100000
Training Epoch: 2 [1536/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 2 [1792/10020]	Loss: 0.6831	LR: 0.100000
Training Epoch: 2 [2048/10020]	Loss: 0.6792	LR: 0.100000
Training Epoch: 2 [2304/10020]	Loss: 0.6896	LR: 0.100000
Training Epoch: 2 [2560/10020]	Loss: 0.6856	LR: 0.100000
Training Epoch: 2 [2816/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 2 [3072/10020]	Loss: 0.6735	LR: 0.100000
Training Epoch: 2 [3328/10020]	Loss: 0.6829	LR: 0.100000
Training Epoch: 2 [3584/10020]	Loss: 0.6975	LR: 0.100000
Training Epoch: 2 [3840/10020]	Loss: 0.6835	LR: 0.100000
Training Epoch: 2 [4096/10020]	Loss: 0.7084	LR: 0.100000
Training Epoch: 2 [4352/10020]	Loss: 0.6957	LR: 0.100000
Training Epoch: 2 [4608/10020]	Loss: 0.6537	LR: 0.100000
Training Epoch: 2 [4864/10020]	Loss: 0.6745	LR: 0.100000
Training Epoch: 2 [5120/10020]	Loss: 0.7230	LR: 0.100000
Training Epoch: 2 [5376/10020]	Loss: 0.7004	LR: 0.100000
Training Epoch: 2 [5632/10020]	Loss: 0.6905	LR: 0.100000
Training Epoch: 2 [5888/10020]	Loss: 0.7193	LR: 0.100000
Training Epoch: 2 [6144/10020]	Loss: 0.8021	LR: 0.100000
Training Epoch: 2 [6400/10020]	Loss: 0.6932	LR: 0.100000
Training Epoch: 2 [6656/10020]	Loss: 0.7143	LR: 0.100000
Training Epoch: 2 [6912/10020]	Loss: 0.8865	LR: 0.100000
Training Epoch: 2 [7168/10020]	Loss: 0.7765	LR: 0.100000
Training Epoch: 2 [7424/10020]	Loss: 0.9435	LR: 0.100000
Training Epoch: 2 [7680/10020]	Loss: 0.8346	LR: 0.100000
Training Epoch: 2 [7936/10020]	Loss: 0.7582	LR: 0.100000
Training Epoch: 2 [8192/10020]	Loss: 0.7780	LR: 0.100000
Training Epoch: 2 [8448/10020]	Loss: 0.7502	LR: 0.100000
Training Epoch: 2 [8704/10020]	Loss: 0.7599	LR: 0.100000
Training Epoch: 2 [8960/10020]	Loss: 0.7634	LR: 0.100000
Training Epoch: 2 [9216/10020]	Loss: 0.7264	LR: 0.100000
Training Epoch: 2 [9472/10020]	Loss: 0.7633	LR: 0.100000
Training Epoch: 2 [9728/10020]	Loss: 0.7008	LR: 0.100000
Training Epoch: 2 [9984/10020]	Loss: 0.7358	LR: 0.100000
Training Epoch: 2 [10020/10020]	Loss: 0.7248	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7277, Train Accuracy: 0.5303
Epoch 2 training time consumed: 144.73s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0032, Accuracy: 0.5433, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-2-best.pth
Training Epoch: 3 [256/10020]	Loss: 0.6994	LR: 0.100000
Training Epoch: 3 [512/10020]	Loss: 0.7160	LR: 0.100000
Training Epoch: 3 [768/10020]	Loss: 0.6800	LR: 0.100000
Training Epoch: 3 [1024/10020]	Loss: 0.7170	LR: 0.100000
Training Epoch: 3 [1280/10020]	Loss: 0.6893	LR: 0.100000
Training Epoch: 3 [1536/10020]	Loss: 0.7740	LR: 0.100000
Training Epoch: 3 [1792/10020]	Loss: 0.6892	LR: 0.100000
Training Epoch: 3 [2048/10020]	Loss: 0.6726	LR: 0.100000
Training Epoch: 3 [2304/10020]	Loss: 0.6979	LR: 0.100000
Training Epoch: 3 [2560/10020]	Loss: 0.7185	LR: 0.100000
Training Epoch: 3 [2816/10020]	Loss: 0.7613	LR: 0.100000
Training Epoch: 3 [3072/10020]	Loss: 0.7451	LR: 0.100000
Training Epoch: 3 [3328/10020]	Loss: 0.6843	LR: 0.100000
Training Epoch: 3 [3584/10020]	Loss: 0.7052	LR: 0.100000
Training Epoch: 3 [3840/10020]	Loss: 0.6627	LR: 0.100000
Training Epoch: 3 [4096/10020]	Loss: 0.6640	LR: 0.100000
Training Epoch: 3 [4352/10020]	Loss: 0.7333	LR: 0.100000
Training Epoch: 3 [4608/10020]	Loss: 0.7064	LR: 0.100000
Training Epoch: 3 [4864/10020]	Loss: 0.8144	LR: 0.100000
Training Epoch: 3 [5120/10020]	Loss: 0.7156	LR: 0.100000
Training Epoch: 3 [5376/10020]	Loss: 0.7135	LR: 0.100000
Training Epoch: 3 [5632/10020]	Loss: 0.7125	LR: 0.100000
Training Epoch: 3 [5888/10020]	Loss: 0.6778	LR: 0.100000
Training Epoch: 3 [6144/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 3 [6400/10020]	Loss: 0.7282	LR: 0.100000
Training Epoch: 3 [6656/10020]	Loss: 0.7119	LR: 0.100000
Training Epoch: 3 [6912/10020]	Loss: 0.6769	LR: 0.100000
Training Epoch: 3 [7168/10020]	Loss: 0.6586	LR: 0.100000
Training Epoch: 3 [7424/10020]	Loss: 0.6976	LR: 0.100000
Training Epoch: 3 [7680/10020]	Loss: 0.6835	LR: 0.100000
Training Epoch: 3 [7936/10020]	Loss: 0.6584	LR: 0.100000
Training Epoch: 3 [8192/10020]	Loss: 0.6789	LR: 0.100000
Training Epoch: 3 [8448/10020]	Loss: 0.6848	LR: 0.100000
Training Epoch: 3 [8704/10020]	Loss: 0.6881	LR: 0.100000
Training Epoch: 3 [8960/10020]	Loss: 0.6687	LR: 0.100000
Training Epoch: 3 [9216/10020]	Loss: 0.6582	LR: 0.100000
Training Epoch: 3 [9472/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 3 [9728/10020]	Loss: 0.6453	LR: 0.100000
Training Epoch: 3 [9984/10020]	Loss: 0.6862	LR: 0.100000
Training Epoch: 3 [10020/10020]	Loss: 0.5793	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6979, Train Accuracy: 0.5653
Epoch 3 training time consumed: 144.71s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5806, Time consumed:7.98s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-3-best.pth
Training Epoch: 4 [256/10020]	Loss: 0.6841	LR: 0.100000
Training Epoch: 4 [512/10020]	Loss: 0.6986	LR: 0.100000
Training Epoch: 4 [768/10020]	Loss: 0.6453	LR: 0.100000
Training Epoch: 4 [1024/10020]	Loss: 0.6769	LR: 0.100000
Training Epoch: 4 [1280/10020]	Loss: 0.7202	LR: 0.100000
Training Epoch: 4 [1536/10020]	Loss: 0.6537	LR: 0.100000
Training Epoch: 4 [1792/10020]	Loss: 0.6880	LR: 0.100000
Training Epoch: 4 [2048/10020]	Loss: 0.6649	LR: 0.100000
Training Epoch: 4 [2304/10020]	Loss: 0.6793	LR: 0.100000
Training Epoch: 4 [2560/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 4 [2816/10020]	Loss: 0.6705	LR: 0.100000
Training Epoch: 4 [3072/10020]	Loss: 0.6821	LR: 0.100000
Training Epoch: 4 [3328/10020]	Loss: 0.6645	LR: 0.100000
Training Epoch: 4 [3584/10020]	Loss: 0.7035	LR: 0.100000
Training Epoch: 4 [3840/10020]	Loss: 0.6952	LR: 0.100000
Training Epoch: 4 [4096/10020]	Loss: 0.6387	LR: 0.100000
Training Epoch: 4 [4352/10020]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [4608/10020]	Loss: 0.6427	LR: 0.100000
Training Epoch: 4 [4864/10020]	Loss: 0.6762	LR: 0.100000
Training Epoch: 4 [5120/10020]	Loss: 0.6922	LR: 0.100000
Training Epoch: 4 [5376/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 4 [5632/10020]	Loss: 0.6684	LR: 0.100000
Training Epoch: 4 [5888/10020]	Loss: 0.6675	LR: 0.100000
Training Epoch: 4 [6144/10020]	Loss: 0.6600	LR: 0.100000
Training Epoch: 4 [6400/10020]	Loss: 0.6846	LR: 0.100000
Training Epoch: 4 [6656/10020]	Loss: 0.6720	LR: 0.100000
Training Epoch: 4 [6912/10020]	Loss: 0.6665	LR: 0.100000
Training Epoch: 4 [7168/10020]	Loss: 0.6652	LR: 0.100000
Training Epoch: 4 [7424/10020]	Loss: 0.7142	LR: 0.100000
Training Epoch: 4 [7680/10020]	Loss: 0.6597	LR: 0.100000
Training Epoch: 4 [7936/10020]	Loss: 0.6843	LR: 0.100000
Training Epoch: 4 [8192/10020]	Loss: 0.6671	LR: 0.100000
Training Epoch: 4 [8448/10020]	Loss: 0.6920	LR: 0.100000
Training Epoch: 4 [8704/10020]	Loss: 0.6579	LR: 0.100000
Training Epoch: 4 [8960/10020]	Loss: 0.6790	LR: 0.100000
Training Epoch: 4 [9216/10020]	Loss: 0.6622	LR: 0.100000
Training Epoch: 4 [9472/10020]	Loss: 0.6607	LR: 0.100000
Training Epoch: 4 [9728/10020]	Loss: 0.6799	LR: 0.100000
Training Epoch: 4 [9984/10020]	Loss: 0.6734	LR: 0.100000
Training Epoch: 4 [10020/10020]	Loss: 0.6696	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6753, Train Accuracy: 0.5833
Epoch 4 training time consumed: 144.51s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0030, Accuracy: 0.5709, Time consumed:7.68s
Training Epoch: 5 [256/10020]	Loss: 0.6867	LR: 0.100000
Training Epoch: 5 [512/10020]	Loss: 0.6765	LR: 0.100000
Training Epoch: 5 [768/10020]	Loss: 0.6581	LR: 0.100000
Training Epoch: 5 [1024/10020]	Loss: 0.6759	LR: 0.100000
Training Epoch: 5 [1280/10020]	Loss: 0.6733	LR: 0.100000
Training Epoch: 5 [1536/10020]	Loss: 0.6708	LR: 0.100000
Training Epoch: 5 [1792/10020]	Loss: 0.6805	LR: 0.100000
Training Epoch: 5 [2048/10020]	Loss: 0.6741	LR: 0.100000
Training Epoch: 5 [2304/10020]	Loss: 0.6546	LR: 0.100000
Training Epoch: 5 [2560/10020]	Loss: 0.6904	LR: 0.100000
Training Epoch: 5 [2816/10020]	Loss: 0.6668	LR: 0.100000
Training Epoch: 5 [3072/10020]	Loss: 0.6819	LR: 0.100000
Training Epoch: 5 [3328/10020]	Loss: 0.6738	LR: 0.100000
Training Epoch: 5 [3584/10020]	Loss: 0.6650	LR: 0.100000
Training Epoch: 5 [3840/10020]	Loss: 0.6695	LR: 0.100000
Training Epoch: 5 [4096/10020]	Loss: 0.6575	LR: 0.100000
Training Epoch: 5 [4352/10020]	Loss: 0.6793	LR: 0.100000
Training Epoch: 5 [4608/10020]	Loss: 0.6386	LR: 0.100000
Training Epoch: 5 [4864/10020]	Loss: 0.6656	LR: 0.100000
Training Epoch: 5 [5120/10020]	Loss: 0.6665	LR: 0.100000
Training Epoch: 5 [5376/10020]	Loss: 0.6499	LR: 0.100000
Training Epoch: 5 [5632/10020]	Loss: 0.6716	LR: 0.100000
Training Epoch: 5 [5888/10020]	Loss: 0.6601	LR: 0.100000
Training Epoch: 5 [6144/10020]	Loss: 0.6674	LR: 0.100000
Training Epoch: 5 [6400/10020]	Loss: 0.6859	LR: 0.100000
Training Epoch: 5 [6656/10020]	Loss: 0.6584	LR: 0.100000
Training Epoch: 5 [6912/10020]	Loss: 0.6806	LR: 0.100000
Training Epoch: 5 [7168/10020]	Loss: 0.6911	LR: 0.100000
Training Epoch: 5 [7424/10020]	Loss: 0.6633	LR: 0.100000
Training Epoch: 5 [7680/10020]	Loss: 0.6683	LR: 0.100000
Training Epoch: 5 [7936/10020]	Loss: 0.6840	LR: 0.100000
Training Epoch: 5 [8192/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 5 [8448/10020]	Loss: 0.6982	LR: 0.100000
Training Epoch: 5 [8704/10020]	Loss: 0.6469	LR: 0.100000
Training Epoch: 5 [8960/10020]	Loss: 0.6469	LR: 0.100000
Training Epoch: 5 [9216/10020]	Loss: 0.6857	LR: 0.100000
Training Epoch: 5 [9472/10020]	Loss: 0.6963	LR: 0.100000
Training Epoch: 5 [9728/10020]	Loss: 0.6681	LR: 0.100000
Training Epoch: 5 [9984/10020]	Loss: 0.6919	LR: 0.100000
Training Epoch: 5 [10020/10020]	Loss: 0.6854	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6717, Train Accuracy: 0.5903
Epoch 5 training time consumed: 144.52s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5404, Time consumed:7.96s
Training Epoch: 6 [256/10020]	Loss: 0.6949	LR: 0.100000
Training Epoch: 6 [512/10020]	Loss: 0.7291	LR: 0.100000
Training Epoch: 6 [768/10020]	Loss: 0.6952	LR: 0.100000
Training Epoch: 6 [1024/10020]	Loss: 0.6916	LR: 0.100000
Training Epoch: 6 [1280/10020]	Loss: 0.6710	LR: 0.100000
Training Epoch: 6 [1536/10020]	Loss: 0.6754	LR: 0.100000
Training Epoch: 6 [1792/10020]	Loss: 0.7340	LR: 0.100000
Training Epoch: 6 [2048/10020]	Loss: 0.7181	LR: 0.100000
Training Epoch: 6 [2304/10020]	Loss: 0.6671	LR: 0.100000
Training Epoch: 6 [2560/10020]	Loss: 0.6866	LR: 0.100000
Training Epoch: 6 [2816/10020]	Loss: 0.6712	LR: 0.100000
Training Epoch: 6 [3072/10020]	Loss: 0.6927	LR: 0.100000
Training Epoch: 6 [3328/10020]	Loss: 0.6804	LR: 0.100000
Training Epoch: 6 [3584/10020]	Loss: 0.6648	LR: 0.100000
Training Epoch: 6 [3840/10020]	Loss: 0.6840	LR: 0.100000
Training Epoch: 6 [4096/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 6 [4352/10020]	Loss: 0.6830	LR: 0.100000
Training Epoch: 6 [4608/10020]	Loss: 0.6708	LR: 0.100000
Training Epoch: 6 [4864/10020]	Loss: 0.6521	LR: 0.100000
Training Epoch: 6 [5120/10020]	Loss: 0.6637	LR: 0.100000
Training Epoch: 6 [5376/10020]	Loss: 0.6587	LR: 0.100000
Training Epoch: 6 [5632/10020]	Loss: 0.6835	LR: 0.100000
Training Epoch: 6 [5888/10020]	Loss: 0.6821	LR: 0.100000
Training Epoch: 6 [6144/10020]	Loss: 0.6633	LR: 0.100000
Training Epoch: 6 [6400/10020]	Loss: 0.6499	LR: 0.100000
Training Epoch: 6 [6656/10020]	Loss: 0.6860	LR: 0.100000
Training Epoch: 6 [6912/10020]	Loss: 0.6325	LR: 0.100000
Training Epoch: 6 [7168/10020]	Loss: 0.6679	LR: 0.100000
Training Epoch: 6 [7424/10020]	Loss: 0.6620	LR: 0.100000
Training Epoch: 6 [7680/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 6 [7936/10020]	Loss: 0.6817	LR: 0.100000
Training Epoch: 6 [8192/10020]	Loss: 0.7066	LR: 0.100000
Training Epoch: 6 [8448/10020]	Loss: 0.6581	LR: 0.100000
Training Epoch: 6 [8704/10020]	Loss: 0.6775	LR: 0.100000
Training Epoch: 6 [8960/10020]	Loss: 0.6693	LR: 0.100000
Training Epoch: 6 [9216/10020]	Loss: 0.6787	LR: 0.100000
Training Epoch: 6 [9472/10020]	Loss: 0.6891	LR: 0.100000
Training Epoch: 6 [9728/10020]	Loss: 0.6830	LR: 0.100000
Training Epoch: 6 [9984/10020]	Loss: 0.6973	LR: 0.100000
Training Epoch: 6 [10020/10020]	Loss: 0.6451	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6792, Train Accuracy: 0.5728
Epoch 6 training time consumed: 144.48s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0030, Accuracy: 0.5797, Time consumed:7.78s
Training Epoch: 7 [256/10020]	Loss: 0.6889	LR: 0.100000
Training Epoch: 7 [512/10020]	Loss: 0.7163	LR: 0.100000
Training Epoch: 7 [768/10020]	Loss: 0.6957	LR: 0.100000
Training Epoch: 7 [1024/10020]	Loss: 0.6832	LR: 0.100000
Training Epoch: 7 [1280/10020]	Loss: 0.6722	LR: 0.100000
Training Epoch: 7 [1536/10020]	Loss: 0.6747	LR: 0.100000
Training Epoch: 7 [1792/10020]	Loss: 0.6768	LR: 0.100000
Training Epoch: 7 [2048/10020]	Loss: 0.6936	LR: 0.100000
Training Epoch: 7 [2304/10020]	Loss: 0.6746	LR: 0.100000
Training Epoch: 7 [2560/10020]	Loss: 0.6698	LR: 0.100000
Training Epoch: 7 [2816/10020]	Loss: 0.6719	LR: 0.100000
Training Epoch: 7 [3072/10020]	Loss: 0.6751	LR: 0.100000
Training Epoch: 7 [3328/10020]	Loss: 0.6480	LR: 0.100000
Training Epoch: 7 [3584/10020]	Loss: 0.6755	LR: 0.100000
Training Epoch: 7 [3840/10020]	Loss: 0.6694	LR: 0.100000
Training Epoch: 7 [4096/10020]	Loss: 0.6617	LR: 0.100000
Training Epoch: 7 [4352/10020]	Loss: 0.6763	LR: 0.100000
Training Epoch: 7 [4608/10020]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [4864/10020]	Loss: 0.7011	LR: 0.100000
Training Epoch: 7 [5120/10020]	Loss: 0.6712	LR: 0.100000
Training Epoch: 7 [5376/10020]	Loss: 0.6626	LR: 0.100000
Training Epoch: 7 [5632/10020]	Loss: 0.6703	LR: 0.100000
Training Epoch: 7 [5888/10020]	Loss: 0.6917	LR: 0.100000
Training Epoch: 7 [6144/10020]	Loss: 0.6680	LR: 0.100000
Training Epoch: 7 [6400/10020]	Loss: 0.6651	LR: 0.100000
Training Epoch: 7 [6656/10020]	Loss: 0.6821	LR: 0.100000
Training Epoch: 7 [6912/10020]	Loss: 0.6592	LR: 0.100000
Training Epoch: 7 [7168/10020]	Loss: 0.6687	LR: 0.100000
Training Epoch: 7 [7424/10020]	Loss: 0.6643	LR: 0.100000
Training Epoch: 7 [7680/10020]	Loss: 0.6482	LR: 0.100000
Training Epoch: 7 [7936/10020]	Loss: 0.6487	LR: 0.100000
Training Epoch: 7 [8192/10020]	Loss: 0.6301	LR: 0.100000
Training Epoch: 7 [8448/10020]	Loss: 0.6508	LR: 0.100000
Training Epoch: 7 [8704/10020]	Loss: 0.6243	LR: 0.100000
Training Epoch: 7 [8960/10020]	Loss: 0.6619	LR: 0.100000
Training Epoch: 7 [9216/10020]	Loss: 0.6533	LR: 0.100000
Training Epoch: 7 [9472/10020]	Loss: 0.6235	LR: 0.100000
Training Epoch: 7 [9728/10020]	Loss: 0.6685	LR: 0.100000
Training Epoch: 7 [9984/10020]	Loss: 0.6915	LR: 0.100000
Training Epoch: 7 [10020/10020]	Loss: 0.5879	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6686, Train Accuracy: 0.5945
Epoch 7 training time consumed: 144.67s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0029, Accuracy: 0.5903, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-7-best.pth
Training Epoch: 8 [256/10020]	Loss: 0.6953	LR: 0.100000
Training Epoch: 8 [512/10020]	Loss: 0.6582	LR: 0.100000
Training Epoch: 8 [768/10020]	Loss: 0.6435	LR: 0.100000
Training Epoch: 8 [1024/10020]	Loss: 0.6972	LR: 0.100000
Training Epoch: 8 [1280/10020]	Loss: 0.6700	LR: 0.100000
Training Epoch: 8 [1536/10020]	Loss: 0.6660	LR: 0.100000
Training Epoch: 8 [1792/10020]	Loss: 0.6647	LR: 0.100000
Training Epoch: 8 [2048/10020]	Loss: 0.6838	LR: 0.100000
Training Epoch: 8 [2304/10020]	Loss: 0.6439	LR: 0.100000
Training Epoch: 8 [2560/10020]	Loss: 0.6555	LR: 0.100000
Training Epoch: 8 [2816/10020]	Loss: 0.6544	LR: 0.100000
Training Epoch: 8 [3072/10020]	Loss: 0.6403	LR: 0.100000
Training Epoch: 8 [3328/10020]	Loss: 0.6336	LR: 0.100000
Training Epoch: 8 [3584/10020]	Loss: 0.6592	LR: 0.100000
Training Epoch: 8 [3840/10020]	Loss: 0.6383	LR: 0.100000
Training Epoch: 8 [4096/10020]	Loss: 0.6456	LR: 0.100000
Training Epoch: 8 [4352/10020]	Loss: 0.6517	LR: 0.100000
Training Epoch: 8 [4608/10020]	Loss: 0.6548	LR: 0.100000
Training Epoch: 8 [4864/10020]	Loss: 0.6482	LR: 0.100000
Training Epoch: 8 [5120/10020]	Loss: 0.6316	LR: 0.100000
Training Epoch: 8 [5376/10020]	Loss: 0.6080	LR: 0.100000
Training Epoch: 8 [5632/10020]	Loss: 0.6552	LR: 0.100000
Training Epoch: 8 [5888/10020]	Loss: 0.6490	LR: 0.100000
Training Epoch: 8 [6144/10020]	Loss: 0.6627	LR: 0.100000
Training Epoch: 8 [6400/10020]	Loss: 0.6595	LR: 0.100000
Training Epoch: 8 [6656/10020]	Loss: 0.6459	LR: 0.100000
Training Epoch: 8 [6912/10020]	Loss: 0.6196	LR: 0.100000
Training Epoch: 8 [7168/10020]	Loss: 0.6798	LR: 0.100000
Training Epoch: 8 [7424/10020]	Loss: 0.6533	LR: 0.100000
Training Epoch: 8 [7680/10020]	Loss: 0.6390	LR: 0.100000
Training Epoch: 8 [7936/10020]	Loss: 0.6098	LR: 0.100000
Training Epoch: 8 [8192/10020]	Loss: 0.6677	LR: 0.100000
Training Epoch: 8 [8448/10020]	Loss: 0.6321	LR: 0.100000
Training Epoch: 8 [8704/10020]	Loss: 0.6132	LR: 0.100000
Training Epoch: 8 [8960/10020]	Loss: 0.6141	LR: 0.100000
Training Epoch: 8 [9216/10020]	Loss: 0.6507	LR: 0.100000
Training Epoch: 8 [9472/10020]	Loss: 0.6204	LR: 0.100000
Training Epoch: 8 [9728/10020]	Loss: 0.6489	LR: 0.100000
Training Epoch: 8 [9984/10020]	Loss: 0.6022	LR: 0.100000
Training Epoch: 8 [10020/10020]	Loss: 0.7448	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6482, Train Accuracy: 0.6242
Epoch 8 training time consumed: 144.36s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0031, Accuracy: 0.6179, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-8-best.pth
Training Epoch: 9 [256/10020]	Loss: 0.6633	LR: 0.100000
Training Epoch: 9 [512/10020]	Loss: 0.6059	LR: 0.100000
Training Epoch: 9 [768/10020]	Loss: 0.6426	LR: 0.100000
Training Epoch: 9 [1024/10020]	Loss: 0.6215	LR: 0.100000
Training Epoch: 9 [1280/10020]	Loss: 0.6444	LR: 0.100000
Training Epoch: 9 [1536/10020]	Loss: 0.6189	LR: 0.100000
Training Epoch: 9 [1792/10020]	Loss: 0.6229	LR: 0.100000
Training Epoch: 9 [2048/10020]	Loss: 0.6504	LR: 0.100000
Training Epoch: 9 [2304/10020]	Loss: 0.6276	LR: 0.100000
Training Epoch: 9 [2560/10020]	Loss: 0.6521	LR: 0.100000
Training Epoch: 9 [2816/10020]	Loss: 0.6272	LR: 0.100000
Training Epoch: 9 [3072/10020]	Loss: 0.6597	LR: 0.100000
Training Epoch: 9 [3328/10020]	Loss: 0.5931	LR: 0.100000
Training Epoch: 9 [3584/10020]	Loss: 0.6764	LR: 0.100000
Training Epoch: 9 [3840/10020]	Loss: 0.6150	LR: 0.100000
Training Epoch: 9 [4096/10020]	Loss: 0.6059	LR: 0.100000
Training Epoch: 9 [4352/10020]	Loss: 0.5943	LR: 0.100000
Training Epoch: 9 [4608/10020]	Loss: 0.6347	LR: 0.100000
Training Epoch: 9 [4864/10020]	Loss: 0.6377	LR: 0.100000
Training Epoch: 9 [5120/10020]	Loss: 0.5899	LR: 0.100000
Training Epoch: 9 [5376/10020]	Loss: 0.5914	LR: 0.100000
Training Epoch: 9 [5632/10020]	Loss: 0.5933	LR: 0.100000
Training Epoch: 9 [5888/10020]	Loss: 0.6332	LR: 0.100000
Training Epoch: 9 [6144/10020]	Loss: 0.6056	LR: 0.100000
Training Epoch: 9 [6400/10020]	Loss: 0.6035	LR: 0.100000
Training Epoch: 9 [6656/10020]	Loss: 0.6232	LR: 0.100000
Training Epoch: 9 [6912/10020]	Loss: 0.6199	LR: 0.100000
Training Epoch: 9 [7168/10020]	Loss: 0.5600	LR: 0.100000
Training Epoch: 9 [7424/10020]	Loss: 0.5940	LR: 0.100000
Training Epoch: 9 [7680/10020]	Loss: 0.6154	LR: 0.100000
Training Epoch: 9 [7936/10020]	Loss: 0.5884	LR: 0.100000
Training Epoch: 9 [8192/10020]	Loss: 0.6083	LR: 0.100000
Training Epoch: 9 [8448/10020]	Loss: 0.5627	LR: 0.100000
Training Epoch: 9 [8704/10020]	Loss: 0.5583	LR: 0.100000
Training Epoch: 9 [8960/10020]	Loss: 0.6634	LR: 0.100000
Training Epoch: 9 [9216/10020]	Loss: 0.5671	LR: 0.100000
Training Epoch: 9 [9472/10020]	Loss: 0.6097	LR: 0.100000
Training Epoch: 9 [9728/10020]	Loss: 0.6465	LR: 0.100000
Training Epoch: 9 [9984/10020]	Loss: 0.5972	LR: 0.100000
Training Epoch: 9 [10020/10020]	Loss: 0.6118	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6160, Train Accuracy: 0.6636
Epoch 9 training time consumed: 144.50s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0027, Accuracy: 0.6857, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-9-best.pth
Training Epoch: 10 [256/10020]	Loss: 0.7023	LR: 0.020000
Training Epoch: 10 [512/10020]	Loss: 0.6352	LR: 0.020000
Training Epoch: 10 [768/10020]	Loss: 0.6396	LR: 0.020000
Training Epoch: 10 [1024/10020]	Loss: 0.6478	LR: 0.020000
Training Epoch: 10 [1280/10020]	Loss: 0.6094	LR: 0.020000
Training Epoch: 10 [1536/10020]	Loss: 0.5970	LR: 0.020000
Training Epoch: 10 [1792/10020]	Loss: 0.6194	LR: 0.020000
Training Epoch: 10 [2048/10020]	Loss: 0.6245	LR: 0.020000
Training Epoch: 10 [2304/10020]	Loss: 0.6545	LR: 0.020000
Training Epoch: 10 [2560/10020]	Loss: 0.5798	LR: 0.020000
Training Epoch: 10 [2816/10020]	Loss: 0.5532	LR: 0.020000
Training Epoch: 10 [3072/10020]	Loss: 0.5650	LR: 0.020000
Training Epoch: 10 [3328/10020]	Loss: 0.5848	LR: 0.020000
Training Epoch: 10 [3584/10020]	Loss: 0.5443	LR: 0.020000
Training Epoch: 10 [3840/10020]	Loss: 0.5659	LR: 0.020000
Training Epoch: 10 [4096/10020]	Loss: 0.6060	LR: 0.020000
Training Epoch: 10 [4352/10020]	Loss: 0.5210	LR: 0.020000
Training Epoch: 10 [4608/10020]	Loss: 0.5763	LR: 0.020000
Training Epoch: 10 [4864/10020]	Loss: 0.5379	LR: 0.020000
Training Epoch: 10 [5120/10020]	Loss: 0.6116	LR: 0.020000
Training Epoch: 10 [5376/10020]	Loss: 0.5561	LR: 0.020000
Training Epoch: 10 [5632/10020]	Loss: 0.5588	LR: 0.020000
Training Epoch: 10 [5888/10020]	Loss: 0.5285	LR: 0.020000
Training Epoch: 10 [6144/10020]	Loss: 0.5947	LR: 0.020000
Training Epoch: 10 [6400/10020]	Loss: 0.5866	LR: 0.020000
Training Epoch: 10 [6656/10020]	Loss: 0.5420	LR: 0.020000
Training Epoch: 10 [6912/10020]	Loss: 0.5549	LR: 0.020000
Training Epoch: 10 [7168/10020]	Loss: 0.5520	LR: 0.020000
Training Epoch: 10 [7424/10020]	Loss: 0.5520	LR: 0.020000
Training Epoch: 10 [7680/10020]	Loss: 0.5783	LR: 0.020000
Training Epoch: 10 [7936/10020]	Loss: 0.5670	LR: 0.020000
Training Epoch: 10 [8192/10020]	Loss: 0.6060	LR: 0.020000
Training Epoch: 10 [8448/10020]	Loss: 0.5593	LR: 0.020000
Training Epoch: 10 [8704/10020]	Loss: 0.5519	LR: 0.020000
Training Epoch: 10 [8960/10020]	Loss: 0.5628	LR: 0.020000
Training Epoch: 10 [9216/10020]	Loss: 0.5505	LR: 0.020000
Training Epoch: 10 [9472/10020]	Loss: 0.5339	LR: 0.020000
Training Epoch: 10 [9728/10020]	Loss: 0.5447	LR: 0.020000
Training Epoch: 10 [9984/10020]	Loss: 0.5279	LR: 0.020000
Training Epoch: 10 [10020/10020]	Loss: 0.5774	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5790, Train Accuracy: 0.6976
Epoch 10 training time consumed: 144.39s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0025, Accuracy: 0.7225, Time consumed:7.85s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-10-best.pth
Training Epoch: 11 [256/10020]	Loss: 0.5922	LR: 0.020000
Training Epoch: 11 [512/10020]	Loss: 0.5146	LR: 0.020000
Training Epoch: 11 [768/10020]	Loss: 0.5344	LR: 0.020000
Training Epoch: 11 [1024/10020]	Loss: 0.6015	LR: 0.020000
Training Epoch: 11 [1280/10020]	Loss: 0.4755	LR: 0.020000
Training Epoch: 11 [1536/10020]	Loss: 0.5511	LR: 0.020000
Training Epoch: 11 [1792/10020]	Loss: 0.5153	LR: 0.020000
Training Epoch: 11 [2048/10020]	Loss: 0.5225	LR: 0.020000
Training Epoch: 11 [2304/10020]	Loss: 0.4904	LR: 0.020000
Training Epoch: 11 [2560/10020]	Loss: 0.4777	LR: 0.020000
Training Epoch: 11 [2816/10020]	Loss: 0.5042	LR: 0.020000
Training Epoch: 11 [3072/10020]	Loss: 0.5289	LR: 0.020000
Training Epoch: 11 [3328/10020]	Loss: 0.4812	LR: 0.020000
Training Epoch: 11 [3584/10020]	Loss: 0.5251	LR: 0.020000
Training Epoch: 11 [3840/10020]	Loss: 0.5395	LR: 0.020000
Training Epoch: 11 [4096/10020]	Loss: 0.5211	LR: 0.020000
Training Epoch: 11 [4352/10020]	Loss: 0.4812	LR: 0.020000
Training Epoch: 11 [4608/10020]	Loss: 0.5611	LR: 0.020000
Training Epoch: 11 [4864/10020]	Loss: 0.5317	LR: 0.020000
Training Epoch: 11 [5120/10020]	Loss: 0.5179	LR: 0.020000
Training Epoch: 11 [5376/10020]	Loss: 0.4495	LR: 0.020000
Training Epoch: 11 [5632/10020]	Loss: 0.4923	LR: 0.020000
Training Epoch: 11 [5888/10020]	Loss: 0.5303	LR: 0.020000
Training Epoch: 11 [6144/10020]	Loss: 0.5119	LR: 0.020000
Training Epoch: 11 [6400/10020]	Loss: 0.4840	LR: 0.020000
Training Epoch: 11 [6656/10020]	Loss: 0.5064	LR: 0.020000
Training Epoch: 11 [6912/10020]	Loss: 0.4878	LR: 0.020000
Training Epoch: 11 [7168/10020]	Loss: 0.5050	LR: 0.020000
Training Epoch: 11 [7424/10020]	Loss: 0.4709	LR: 0.020000
Training Epoch: 11 [7680/10020]	Loss: 0.4687	LR: 0.020000
Training Epoch: 11 [7936/10020]	Loss: 0.4356	LR: 0.020000
Training Epoch: 11 [8192/10020]	Loss: 0.4520	LR: 0.020000
Training Epoch: 11 [8448/10020]	Loss: 0.4778	LR: 0.020000
Training Epoch: 11 [8704/10020]	Loss: 0.4150	LR: 0.020000
Training Epoch: 11 [8960/10020]	Loss: 0.4650	LR: 0.020000
Training Epoch: 11 [9216/10020]	Loss: 0.5364	LR: 0.020000
Training Epoch: 11 [9472/10020]	Loss: 0.4575	LR: 0.020000
Training Epoch: 11 [9728/10020]	Loss: 0.5010	LR: 0.020000
Training Epoch: 11 [9984/10020]	Loss: 0.4872	LR: 0.020000
Training Epoch: 11 [10020/10020]	Loss: 0.4884	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5025, Train Accuracy: 0.7594
Epoch 11 training time consumed: 144.53s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0027, Accuracy: 0.6823, Time consumed:7.77s
Training Epoch: 12 [256/10020]	Loss: 0.3850	LR: 0.020000
Training Epoch: 12 [512/10020]	Loss: 0.4098	LR: 0.020000
Training Epoch: 12 [768/10020]	Loss: 0.5268	LR: 0.020000
Training Epoch: 12 [1024/10020]	Loss: 0.4866	LR: 0.020000
Training Epoch: 12 [1280/10020]	Loss: 0.4612	LR: 0.020000
Training Epoch: 12 [1536/10020]	Loss: 0.4668	LR: 0.020000
Training Epoch: 12 [1792/10020]	Loss: 0.5166	LR: 0.020000
Training Epoch: 12 [2048/10020]	Loss: 0.4803	LR: 0.020000
Training Epoch: 12 [2304/10020]	Loss: 0.4637	LR: 0.020000
Training Epoch: 12 [2560/10020]	Loss: 0.4371	LR: 0.020000
Training Epoch: 12 [2816/10020]	Loss: 0.4512	LR: 0.020000
Training Epoch: 12 [3072/10020]	Loss: 0.4511	LR: 0.020000
Training Epoch: 12 [3328/10020]	Loss: 0.4627	LR: 0.020000
Training Epoch: 12 [3584/10020]	Loss: 0.4642	LR: 0.020000
Training Epoch: 12 [3840/10020]	Loss: 0.4856	LR: 0.020000
Training Epoch: 12 [4096/10020]	Loss: 0.4717	LR: 0.020000
Training Epoch: 12 [4352/10020]	Loss: 0.4721	LR: 0.020000
Training Epoch: 12 [4608/10020]	Loss: 0.3790	LR: 0.020000
Training Epoch: 12 [4864/10020]	Loss: 0.4910	LR: 0.020000
Training Epoch: 12 [5120/10020]	Loss: 0.5036	LR: 0.020000
Training Epoch: 12 [5376/10020]	Loss: 0.4858	LR: 0.020000
Training Epoch: 12 [5632/10020]	Loss: 0.4602	LR: 0.020000
Training Epoch: 12 [5888/10020]	Loss: 0.4059	LR: 0.020000
Training Epoch: 12 [6144/10020]	Loss: 0.4690	LR: 0.020000
Training Epoch: 12 [6400/10020]	Loss: 0.4043	LR: 0.020000
Training Epoch: 12 [6656/10020]	Loss: 0.5205	LR: 0.020000
Training Epoch: 12 [6912/10020]	Loss: 0.4283	LR: 0.020000
Training Epoch: 12 [7168/10020]	Loss: 0.3878	LR: 0.020000
Training Epoch: 12 [7424/10020]	Loss: 0.3810	LR: 0.020000
Training Epoch: 12 [7680/10020]	Loss: 0.4589	LR: 0.020000
Training Epoch: 12 [7936/10020]	Loss: 0.4305	LR: 0.020000
Training Epoch: 12 [8192/10020]	Loss: 0.4534	LR: 0.020000
Training Epoch: 12 [8448/10020]	Loss: 0.4987	LR: 0.020000
Training Epoch: 12 [8704/10020]	Loss: 0.4979	LR: 0.020000
Training Epoch: 12 [8960/10020]	Loss: 0.4947	LR: 0.020000
Training Epoch: 12 [9216/10020]	Loss: 0.4727	LR: 0.020000
Training Epoch: 12 [9472/10020]	Loss: 0.3937	LR: 0.020000
Training Epoch: 12 [9728/10020]	Loss: 0.4216	LR: 0.020000
Training Epoch: 12 [9984/10020]	Loss: 0.4687	LR: 0.020000
Training Epoch: 12 [10020/10020]	Loss: 0.4668	LR: 0.020000
Epoch 12 - Average Train Loss: 0.4564, Train Accuracy: 0.7860
Epoch 12 training time consumed: 144.02s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0018, Accuracy: 0.8232, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-12-best.pth
Training Epoch: 13 [256/10020]	Loss: 0.4609	LR: 0.020000
Training Epoch: 13 [512/10020]	Loss: 0.5264	LR: 0.020000
Training Epoch: 13 [768/10020]	Loss: 0.3948	LR: 0.020000
Training Epoch: 13 [1024/10020]	Loss: 0.3597	LR: 0.020000
Training Epoch: 13 [1280/10020]	Loss: 0.4474	LR: 0.020000
Training Epoch: 13 [1536/10020]	Loss: 0.5288	LR: 0.020000
Training Epoch: 13 [1792/10020]	Loss: 0.3715	LR: 0.020000
Training Epoch: 13 [2048/10020]	Loss: 0.3909	LR: 0.020000
Training Epoch: 13 [2304/10020]	Loss: 0.4121	LR: 0.020000
Training Epoch: 13 [2560/10020]	Loss: 0.4580	LR: 0.020000
Training Epoch: 13 [2816/10020]	Loss: 0.4688	LR: 0.020000
Training Epoch: 13 [3072/10020]	Loss: 0.5049	LR: 0.020000
Training Epoch: 13 [3328/10020]	Loss: 0.4173	LR: 0.020000
Training Epoch: 13 [3584/10020]	Loss: 0.4164	LR: 0.020000
Training Epoch: 13 [3840/10020]	Loss: 0.4352	LR: 0.020000
Training Epoch: 13 [4096/10020]	Loss: 0.4478	LR: 0.020000
Training Epoch: 13 [4352/10020]	Loss: 0.4096	LR: 0.020000
Training Epoch: 13 [4608/10020]	Loss: 0.4409	LR: 0.020000
Training Epoch: 13 [4864/10020]	Loss: 0.4607	LR: 0.020000
Training Epoch: 13 [5120/10020]	Loss: 0.4513	LR: 0.020000
Training Epoch: 13 [5376/10020]	Loss: 0.4558	LR: 0.020000
Training Epoch: 13 [5632/10020]	Loss: 0.4040	LR: 0.020000
Training Epoch: 13 [5888/10020]	Loss: 0.4222	LR: 0.020000
Training Epoch: 13 [6144/10020]	Loss: 0.4365	LR: 0.020000
Training Epoch: 13 [6400/10020]	Loss: 0.4275	LR: 0.020000
Training Epoch: 13 [6656/10020]	Loss: 0.4153	LR: 0.020000
Training Epoch: 13 [6912/10020]	Loss: 0.4560	LR: 0.020000
Training Epoch: 13 [7168/10020]	Loss: 0.3808	LR: 0.020000
Training Epoch: 13 [7424/10020]	Loss: 0.3945	LR: 0.020000
Training Epoch: 13 [7680/10020]	Loss: 0.4506	LR: 0.020000
Training Epoch: 13 [7936/10020]	Loss: 0.5251	LR: 0.020000
Training Epoch: 13 [8192/10020]	Loss: 0.3516	LR: 0.020000
Training Epoch: 13 [8448/10020]	Loss: 0.4214	LR: 0.020000
Training Epoch: 13 [8704/10020]	Loss: 0.4650	LR: 0.020000
Training Epoch: 13 [8960/10020]	Loss: 0.3608	LR: 0.020000
Training Epoch: 13 [9216/10020]	Loss: 0.4173	LR: 0.020000
Training Epoch: 13 [9472/10020]	Loss: 0.4513	LR: 0.020000
Training Epoch: 13 [9728/10020]	Loss: 0.3804	LR: 0.020000
Training Epoch: 13 [9984/10020]	Loss: 0.3902	LR: 0.020000
Training Epoch: 13 [10020/10020]	Loss: 0.3214	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4306, Train Accuracy: 0.8036
Epoch 13 training time consumed: 144.12s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0020, Accuracy: 0.8068, Time consumed:8.09s
Training Epoch: 14 [256/10020]	Loss: 0.4707	LR: 0.020000
Training Epoch: 14 [512/10020]	Loss: 0.3921	LR: 0.020000
Training Epoch: 14 [768/10020]	Loss: 0.4058	LR: 0.020000
Training Epoch: 14 [1024/10020]	Loss: 0.3808	LR: 0.020000
Training Epoch: 14 [1280/10020]	Loss: 0.3897	LR: 0.020000
Training Epoch: 14 [1536/10020]	Loss: 0.3745	LR: 0.020000
Training Epoch: 14 [1792/10020]	Loss: 0.4483	LR: 0.020000
Training Epoch: 14 [2048/10020]	Loss: 0.4222	LR: 0.020000
Training Epoch: 14 [2304/10020]	Loss: 0.3823	LR: 0.020000
Training Epoch: 14 [2560/10020]	Loss: 0.3631	LR: 0.020000
Training Epoch: 14 [2816/10020]	Loss: 0.4590	LR: 0.020000
Training Epoch: 14 [3072/10020]	Loss: 0.4674	LR: 0.020000
Training Epoch: 14 [3328/10020]	Loss: 0.3384	LR: 0.020000
Training Epoch: 14 [3584/10020]	Loss: 0.4134	LR: 0.020000
Training Epoch: 14 [3840/10020]	Loss: 0.4849	LR: 0.020000
Training Epoch: 14 [4096/10020]	Loss: 0.3798	LR: 0.020000
Training Epoch: 14 [4352/10020]	Loss: 0.4050	LR: 0.020000
Training Epoch: 14 [4608/10020]	Loss: 0.3359	LR: 0.020000
Training Epoch: 14 [4864/10020]	Loss: 0.4326	LR: 0.020000
Training Epoch: 14 [5120/10020]	Loss: 0.3680	LR: 0.020000
Training Epoch: 14 [5376/10020]	Loss: 0.3915	LR: 0.020000
Training Epoch: 14 [5632/10020]	Loss: 0.3728	LR: 0.020000
Training Epoch: 14 [5888/10020]	Loss: 0.4556	LR: 0.020000
Training Epoch: 14 [6144/10020]	Loss: 0.4069	LR: 0.020000
Training Epoch: 14 [6400/10020]	Loss: 0.4949	LR: 0.020000
Training Epoch: 14 [6656/10020]	Loss: 0.3519	LR: 0.020000
Training Epoch: 14 [6912/10020]	Loss: 0.3778	LR: 0.020000
Training Epoch: 14 [7168/10020]	Loss: 0.3997	LR: 0.020000
Training Epoch: 14 [7424/10020]	Loss: 0.4157	LR: 0.020000
Training Epoch: 14 [7680/10020]	Loss: 0.3772	LR: 0.020000
Training Epoch: 14 [7936/10020]	Loss: 0.3324	LR: 0.020000
Training Epoch: 14 [8192/10020]	Loss: 0.3766	LR: 0.020000
Training Epoch: 14 [8448/10020]	Loss: 0.4754	LR: 0.020000
Training Epoch: 14 [8704/10020]	Loss: 0.4047	LR: 0.020000
Training Epoch: 14 [8960/10020]	Loss: 0.3545	LR: 0.020000
Training Epoch: 14 [9216/10020]	Loss: 0.3549	LR: 0.020000
Training Epoch: 14 [9472/10020]	Loss: 0.3296	LR: 0.020000
Training Epoch: 14 [9728/10020]	Loss: 0.3874	LR: 0.020000
Training Epoch: 14 [9984/10020]	Loss: 0.3785	LR: 0.020000
Training Epoch: 14 [10020/10020]	Loss: 0.5008	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3991, Train Accuracy: 0.8231
Epoch 14 training time consumed: 143.81s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0022, Accuracy: 0.7588, Time consumed:7.76s
Training Epoch: 15 [256/10020]	Loss: 0.3782	LR: 0.020000
Training Epoch: 15 [512/10020]	Loss: 0.3808	LR: 0.020000
Training Epoch: 15 [768/10020]	Loss: 0.3522	LR: 0.020000
Training Epoch: 15 [1024/10020]	Loss: 0.3769	LR: 0.020000
Training Epoch: 15 [1280/10020]	Loss: 0.3779	LR: 0.020000
Training Epoch: 15 [1536/10020]	Loss: 0.4252	LR: 0.020000
Training Epoch: 15 [1792/10020]	Loss: 0.3602	LR: 0.020000
Training Epoch: 15 [2048/10020]	Loss: 0.3409	LR: 0.020000
Training Epoch: 15 [2304/10020]	Loss: 0.3813	LR: 0.020000
Training Epoch: 15 [2560/10020]	Loss: 0.4152	LR: 0.020000
Training Epoch: 15 [2816/10020]	Loss: 0.3444	LR: 0.020000
Training Epoch: 15 [3072/10020]	Loss: 0.3259	LR: 0.020000
Training Epoch: 15 [3328/10020]	Loss: 0.3691	LR: 0.020000
Training Epoch: 15 [3584/10020]	Loss: 0.3840	LR: 0.020000
Training Epoch: 15 [3840/10020]	Loss: 0.3629	LR: 0.020000
Training Epoch: 15 [4096/10020]	Loss: 0.3539	LR: 0.020000
Training Epoch: 15 [4352/10020]	Loss: 0.3901	LR: 0.020000
Training Epoch: 15 [4608/10020]	Loss: 0.3629	LR: 0.020000
Training Epoch: 15 [4864/10020]	Loss: 0.3114	LR: 0.020000
Training Epoch: 15 [5120/10020]	Loss: 0.3858	LR: 0.020000
Training Epoch: 15 [5376/10020]	Loss: 0.4072	LR: 0.020000
Training Epoch: 15 [5632/10020]	Loss: 0.3573	LR: 0.020000
Training Epoch: 15 [5888/10020]	Loss: 0.3151	LR: 0.020000
Training Epoch: 15 [6144/10020]	Loss: 0.3052	LR: 0.020000
Training Epoch: 15 [6400/10020]	Loss: 0.3686	LR: 0.020000
Training Epoch: 15 [6656/10020]	Loss: 0.3000	LR: 0.020000
Training Epoch: 15 [6912/10020]	Loss: 0.3616	LR: 0.020000
Training Epoch: 15 [7168/10020]	Loss: 0.3634	LR: 0.020000
Training Epoch: 15 [7424/10020]	Loss: 0.2705	LR: 0.020000
Training Epoch: 15 [7680/10020]	Loss: 0.3512	LR: 0.020000
Training Epoch: 15 [7936/10020]	Loss: 0.3362	LR: 0.020000
Training Epoch: 15 [8192/10020]	Loss: 0.3180	LR: 0.020000
Training Epoch: 15 [8448/10020]	Loss: 0.3748	LR: 0.020000
Training Epoch: 15 [8704/10020]	Loss: 0.3512	LR: 0.020000
Training Epoch: 15 [8960/10020]	Loss: 0.3465	LR: 0.020000
Training Epoch: 15 [9216/10020]	Loss: 0.3137	LR: 0.020000
Training Epoch: 15 [9472/10020]	Loss: 0.3351	LR: 0.020000
Training Epoch: 15 [9728/10020]	Loss: 0.4303	LR: 0.020000
Training Epoch: 15 [9984/10020]	Loss: 0.3627	LR: 0.020000
Training Epoch: 15 [10020/10020]	Loss: 0.3158	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3575, Train Accuracy: 0.8436
Epoch 15 training time consumed: 145.78s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0013, Accuracy: 0.8702, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-15-best.pth
Training Epoch: 16 [256/10020]	Loss: 0.3460	LR: 0.020000
Training Epoch: 16 [512/10020]	Loss: 0.2886	LR: 0.020000
Training Epoch: 16 [768/10020]	Loss: 0.3273	LR: 0.020000
Training Epoch: 16 [1024/10020]	Loss: 0.2591	LR: 0.020000
Training Epoch: 16 [1280/10020]	Loss: 0.3718	LR: 0.020000
Training Epoch: 16 [1536/10020]	Loss: 0.3213	LR: 0.020000
Training Epoch: 16 [1792/10020]	Loss: 0.3321	LR: 0.020000
Training Epoch: 16 [2048/10020]	Loss: 0.3272	LR: 0.020000
Training Epoch: 16 [2304/10020]	Loss: 0.3345	LR: 0.020000
Training Epoch: 16 [2560/10020]	Loss: 0.3289	LR: 0.020000
Training Epoch: 16 [2816/10020]	Loss: 0.3592	LR: 0.020000
Training Epoch: 16 [3072/10020]	Loss: 0.4216	LR: 0.020000
Training Epoch: 16 [3328/10020]	Loss: 0.2883	LR: 0.020000
Training Epoch: 16 [3584/10020]	Loss: 0.3475	LR: 0.020000
Training Epoch: 16 [3840/10020]	Loss: 0.3701	LR: 0.020000
Training Epoch: 16 [4096/10020]	Loss: 0.3880	LR: 0.020000
Training Epoch: 16 [4352/10020]	Loss: 0.3387	LR: 0.020000
Training Epoch: 16 [4608/10020]	Loss: 0.3260	LR: 0.020000
Training Epoch: 16 [4864/10020]	Loss: 0.3608	LR: 0.020000
Training Epoch: 16 [5120/10020]	Loss: 0.3036	LR: 0.020000
Training Epoch: 16 [5376/10020]	Loss: 0.3168	LR: 0.020000
Training Epoch: 16 [5632/10020]	Loss: 0.2847	LR: 0.020000
Training Epoch: 16 [5888/10020]	Loss: 0.3202	LR: 0.020000
Training Epoch: 16 [6144/10020]	Loss: 0.2909	LR: 0.020000
Training Epoch: 16 [6400/10020]	Loss: 0.3109	LR: 0.020000
Training Epoch: 16 [6656/10020]	Loss: 0.2833	LR: 0.020000
Training Epoch: 16 [6912/10020]	Loss: 0.3488	LR: 0.020000
Training Epoch: 16 [7168/10020]	Loss: 0.3715	LR: 0.020000
Training Epoch: 16 [7424/10020]	Loss: 0.3746	LR: 0.020000
Training Epoch: 16 [7680/10020]	Loss: 0.3265	LR: 0.020000
Training Epoch: 16 [7936/10020]	Loss: 0.2485	LR: 0.020000
Training Epoch: 16 [8192/10020]	Loss: 0.3905	LR: 0.020000
Training Epoch: 16 [8448/10020]	Loss: 0.3052	LR: 0.020000
Training Epoch: 16 [8704/10020]	Loss: 0.3312	LR: 0.020000
Training Epoch: 16 [8960/10020]	Loss: 0.3307	LR: 0.020000
Training Epoch: 16 [9216/10020]	Loss: 0.2606	LR: 0.020000
Training Epoch: 16 [9472/10020]	Loss: 0.3742	LR: 0.020000
Training Epoch: 16 [9728/10020]	Loss: 0.3200	LR: 0.020000
Training Epoch: 16 [9984/10020]	Loss: 0.3654	LR: 0.020000
Training Epoch: 16 [10020/10020]	Loss: 0.3076	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3306, Train Accuracy: 0.8605
Epoch 16 training time consumed: 146.81s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0018, Accuracy: 0.8160, Time consumed:8.02s
Training Epoch: 17 [256/10020]	Loss: 0.3177	LR: 0.020000
Training Epoch: 17 [512/10020]	Loss: 0.3489	LR: 0.020000
Training Epoch: 17 [768/10020]	Loss: 0.3405	LR: 0.020000
Training Epoch: 17 [1024/10020]	Loss: 0.3401	LR: 0.020000
Training Epoch: 17 [1280/10020]	Loss: 0.3280	LR: 0.020000
Training Epoch: 17 [1536/10020]	Loss: 0.3851	LR: 0.020000
Training Epoch: 17 [1792/10020]	Loss: 0.3224	LR: 0.020000
Training Epoch: 17 [2048/10020]	Loss: 0.3012	LR: 0.020000
Training Epoch: 17 [2304/10020]	Loss: 0.2979	LR: 0.020000
Training Epoch: 17 [2560/10020]	Loss: 0.2900	LR: 0.020000
Training Epoch: 17 [2816/10020]	Loss: 0.3201	LR: 0.020000
Training Epoch: 17 [3072/10020]	Loss: 0.3326	LR: 0.020000
Training Epoch: 17 [3328/10020]	Loss: 0.2590	LR: 0.020000
Training Epoch: 17 [3584/10020]	Loss: 0.3173	LR: 0.020000
Training Epoch: 17 [3840/10020]	Loss: 0.2875	LR: 0.020000
Training Epoch: 17 [4096/10020]	Loss: 0.3028	LR: 0.020000
Training Epoch: 17 [4352/10020]	Loss: 0.3048	LR: 0.020000
Training Epoch: 17 [4608/10020]	Loss: 0.3069	LR: 0.020000
Training Epoch: 17 [4864/10020]	Loss: 0.2744	LR: 0.020000
Training Epoch: 17 [5120/10020]	Loss: 0.2321	LR: 0.020000
Training Epoch: 17 [5376/10020]	Loss: 0.2627	LR: 0.020000
Training Epoch: 17 [5632/10020]	Loss: 0.2789	LR: 0.020000
Training Epoch: 17 [5888/10020]	Loss: 0.2600	LR: 0.020000
Training Epoch: 17 [6144/10020]	Loss: 0.2399	LR: 0.020000
Training Epoch: 17 [6400/10020]	Loss: 0.2515	LR: 0.020000
Training Epoch: 17 [6656/10020]	Loss: 0.2722	LR: 0.020000
Training Epoch: 17 [6912/10020]	Loss: 0.2959	LR: 0.020000
Training Epoch: 17 [7168/10020]	Loss: 0.2689	LR: 0.020000
Training Epoch: 17 [7424/10020]	Loss: 0.3263	LR: 0.020000
Training Epoch: 17 [7680/10020]	Loss: 0.3097	LR: 0.020000
Training Epoch: 17 [7936/10020]	Loss: 0.2913	LR: 0.020000
Training Epoch: 17 [8192/10020]	Loss: 0.2892	LR: 0.020000
Training Epoch: 17 [8448/10020]	Loss: 0.2840	LR: 0.020000
Training Epoch: 17 [8704/10020]	Loss: 0.2751	LR: 0.020000
Training Epoch: 17 [8960/10020]	Loss: 0.2588	LR: 0.020000
Training Epoch: 17 [9216/10020]	Loss: 0.3173	LR: 0.020000
Training Epoch: 17 [9472/10020]	Loss: 0.3021	LR: 0.020000
Training Epoch: 17 [9728/10020]	Loss: 0.2206	LR: 0.020000
Training Epoch: 17 [9984/10020]	Loss: 0.2597	LR: 0.020000
Training Epoch: 17 [10020/10020]	Loss: 0.1718	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2938, Train Accuracy: 0.8791
Epoch 17 training time consumed: 147.17s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0014, Accuracy: 0.8712, Time consumed:7.92s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-17-best.pth
Training Epoch: 18 [256/10020]	Loss: 0.2915	LR: 0.020000
Training Epoch: 18 [512/10020]	Loss: 0.2516	LR: 0.020000
Training Epoch: 18 [768/10020]	Loss: 0.3000	LR: 0.020000
Training Epoch: 18 [1024/10020]	Loss: 0.3058	LR: 0.020000
Training Epoch: 18 [1280/10020]	Loss: 0.2270	LR: 0.020000
Training Epoch: 18 [1536/10020]	Loss: 0.2940	LR: 0.020000
Training Epoch: 18 [1792/10020]	Loss: 0.2481	LR: 0.020000
Training Epoch: 18 [2048/10020]	Loss: 0.2648	LR: 0.020000
Training Epoch: 18 [2304/10020]	Loss: 0.2964	LR: 0.020000
Training Epoch: 18 [2560/10020]	Loss: 0.2538	LR: 0.020000
Training Epoch: 18 [2816/10020]	Loss: 0.2730	LR: 0.020000
Training Epoch: 18 [3072/10020]	Loss: 0.1901	LR: 0.020000
Training Epoch: 18 [3328/10020]	Loss: 0.2894	LR: 0.020000
Training Epoch: 18 [3584/10020]	Loss: 0.3521	LR: 0.020000
Training Epoch: 18 [3840/10020]	Loss: 0.2237	LR: 0.020000
Training Epoch: 18 [4096/10020]	Loss: 0.2959	LR: 0.020000
Training Epoch: 18 [4352/10020]	Loss: 0.2055	LR: 0.020000
Training Epoch: 18 [4608/10020]	Loss: 0.1990	LR: 0.020000
Training Epoch: 18 [4864/10020]	Loss: 0.2591	LR: 0.020000
Training Epoch: 18 [5120/10020]	Loss: 0.2560	LR: 0.020000
Training Epoch: 18 [5376/10020]	Loss: 0.2569	LR: 0.020000
Training Epoch: 18 [5632/10020]	Loss: 0.2753	LR: 0.020000
Training Epoch: 18 [5888/10020]	Loss: 0.2331	LR: 0.020000
Training Epoch: 18 [6144/10020]	Loss: 0.1834	LR: 0.020000
Training Epoch: 18 [6400/10020]	Loss: 0.2139	LR: 0.020000
Training Epoch: 18 [6656/10020]	Loss: 0.2351	LR: 0.020000
Training Epoch: 18 [6912/10020]	Loss: 0.2282	LR: 0.020000
Training Epoch: 18 [7168/10020]	Loss: 0.3328	LR: 0.020000
Training Epoch: 18 [7424/10020]	Loss: 0.2763	LR: 0.020000
Training Epoch: 18 [7680/10020]	Loss: 0.3185	LR: 0.020000
Training Epoch: 18 [7936/10020]	Loss: 0.2457	LR: 0.020000
Training Epoch: 18 [8192/10020]	Loss: 0.2478	LR: 0.020000
Training Epoch: 18 [8448/10020]	Loss: 0.2753	LR: 0.020000
Training Epoch: 18 [8704/10020]	Loss: 0.3059	LR: 0.020000
Training Epoch: 18 [8960/10020]	Loss: 0.2836	LR: 0.020000
Training Epoch: 18 [9216/10020]	Loss: 0.2771	LR: 0.020000
Training Epoch: 18 [9472/10020]	Loss: 0.2280	LR: 0.020000
Training Epoch: 18 [9728/10020]	Loss: 0.2214	LR: 0.020000
Training Epoch: 18 [9984/10020]	Loss: 0.2353	LR: 0.020000
Training Epoch: 18 [10020/10020]	Loss: 0.4157	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2608, Train Accuracy: 0.8874
Epoch 18 training time consumed: 145.40s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0012, Accuracy: 0.8862, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-18-best.pth
Training Epoch: 19 [256/10020]	Loss: 0.3382	LR: 0.020000
Training Epoch: 19 [512/10020]	Loss: 0.2759	LR: 0.020000
Training Epoch: 19 [768/10020]	Loss: 0.3270	LR: 0.020000
Training Epoch: 19 [1024/10020]	Loss: 0.3600	LR: 0.020000
Training Epoch: 19 [1280/10020]	Loss: 0.2494	LR: 0.020000
Training Epoch: 19 [1536/10020]	Loss: 0.2319	LR: 0.020000
Training Epoch: 19 [1792/10020]	Loss: 0.3473	LR: 0.020000
Training Epoch: 19 [2048/10020]	Loss: 0.2460	LR: 0.020000
Training Epoch: 19 [2304/10020]	Loss: 0.2812	LR: 0.020000
Training Epoch: 19 [2560/10020]	Loss: 0.2358	LR: 0.020000
Training Epoch: 19 [2816/10020]	Loss: 0.3030	LR: 0.020000
Training Epoch: 19 [3072/10020]	Loss: 0.3344	LR: 0.020000
Training Epoch: 19 [3328/10020]	Loss: 0.2550	LR: 0.020000
Training Epoch: 19 [3584/10020]	Loss: 0.2290	LR: 0.020000
Training Epoch: 19 [3840/10020]	Loss: 0.2552	LR: 0.020000
Training Epoch: 19 [4096/10020]	Loss: 0.2166	LR: 0.020000
Training Epoch: 19 [4352/10020]	Loss: 0.2169	LR: 0.020000
Training Epoch: 19 [4608/10020]	Loss: 0.2634	LR: 0.020000
Training Epoch: 19 [4864/10020]	Loss: 0.2280	LR: 0.020000
Training Epoch: 19 [5120/10020]	Loss: 0.2676	LR: 0.020000
Training Epoch: 19 [5376/10020]	Loss: 0.2089	LR: 0.020000
Training Epoch: 19 [5632/10020]	Loss: 0.2220	LR: 0.020000
Training Epoch: 19 [5888/10020]	Loss: 0.2421	LR: 0.020000
Training Epoch: 19 [6144/10020]	Loss: 0.3159	LR: 0.020000
Training Epoch: 19 [6400/10020]	Loss: 0.2043	LR: 0.020000
Training Epoch: 19 [6656/10020]	Loss: 0.1961	LR: 0.020000
Training Epoch: 19 [6912/10020]	Loss: 0.2269	LR: 0.020000
Training Epoch: 19 [7168/10020]	Loss: 0.2563	LR: 0.020000
Training Epoch: 19 [7424/10020]	Loss: 0.2427	LR: 0.020000
Training Epoch: 19 [7680/10020]	Loss: 0.2865	LR: 0.020000
Training Epoch: 19 [7936/10020]	Loss: 0.2096	LR: 0.020000
Training Epoch: 19 [8192/10020]	Loss: 0.2149	LR: 0.020000
Training Epoch: 19 [8448/10020]	Loss: 0.2388	LR: 0.020000
Training Epoch: 19 [8704/10020]	Loss: 0.2235	LR: 0.020000
Training Epoch: 19 [8960/10020]	Loss: 0.3106	LR: 0.020000
Training Epoch: 19 [9216/10020]	Loss: 0.2137	LR: 0.020000
Training Epoch: 19 [9472/10020]	Loss: 0.2435	LR: 0.020000
Training Epoch: 19 [9728/10020]	Loss: 0.2695	LR: 0.020000
Training Epoch: 19 [9984/10020]	Loss: 0.2457	LR: 0.020000
Training Epoch: 19 [10020/10020]	Loss: 0.5408	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2583, Train Accuracy: 0.8952
Epoch 19 training time consumed: 145.54s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0015, Accuracy: 0.8446, Time consumed:8.02s
Training Epoch: 20 [256/10020]	Loss: 0.2360	LR: 0.004000
Training Epoch: 20 [512/10020]	Loss: 0.3067	LR: 0.004000
Training Epoch: 20 [768/10020]	Loss: 0.2524	LR: 0.004000
Training Epoch: 20 [1024/10020]	Loss: 0.2304	LR: 0.004000
Training Epoch: 20 [1280/10020]	Loss: 0.2577	LR: 0.004000
Training Epoch: 20 [1536/10020]	Loss: 0.2052	LR: 0.004000
Training Epoch: 20 [1792/10020]	Loss: 0.2542	LR: 0.004000
Training Epoch: 20 [2048/10020]	Loss: 0.2004	LR: 0.004000
Training Epoch: 20 [2304/10020]	Loss: 0.2289	LR: 0.004000
Training Epoch: 20 [2560/10020]	Loss: 0.2141	LR: 0.004000
Training Epoch: 20 [2816/10020]	Loss: 0.2212	LR: 0.004000
Training Epoch: 20 [3072/10020]	Loss: 0.2242	LR: 0.004000
Training Epoch: 20 [3328/10020]	Loss: 0.2501	LR: 0.004000
Training Epoch: 20 [3584/10020]	Loss: 0.2444	LR: 0.004000
Training Epoch: 20 [3840/10020]	Loss: 0.2742	LR: 0.004000
Training Epoch: 20 [4096/10020]	Loss: 0.2296	LR: 0.004000
Training Epoch: 20 [4352/10020]	Loss: 0.2027	LR: 0.004000
Training Epoch: 20 [4608/10020]	Loss: 0.2207	LR: 0.004000
Training Epoch: 20 [4864/10020]	Loss: 0.2002	LR: 0.004000
Training Epoch: 20 [5120/10020]	Loss: 0.1872	LR: 0.004000
Training Epoch: 20 [5376/10020]	Loss: 0.1774	LR: 0.004000
Training Epoch: 20 [5632/10020]	Loss: 0.1489	LR: 0.004000
Training Epoch: 20 [5888/10020]	Loss: 0.1519	LR: 0.004000
Training Epoch: 20 [6144/10020]	Loss: 0.2137	LR: 0.004000
Training Epoch: 20 [6400/10020]	Loss: 0.1836	LR: 0.004000
Training Epoch: 20 [6656/10020]	Loss: 0.1589	LR: 0.004000
Training Epoch: 20 [6912/10020]	Loss: 0.2124	LR: 0.004000
Training Epoch: 20 [7168/10020]	Loss: 0.1772	LR: 0.004000
Training Epoch: 20 [7424/10020]	Loss: 0.1718	LR: 0.004000
Training Epoch: 20 [7680/10020]	Loss: 0.1934	LR: 0.004000
Training Epoch: 20 [7936/10020]	Loss: 0.2563	LR: 0.004000
Training Epoch: 20 [8192/10020]	Loss: 0.2190	LR: 0.004000
Training Epoch: 20 [8448/10020]	Loss: 0.2300	LR: 0.004000
Training Epoch: 20 [8704/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 20 [8960/10020]	Loss: 0.2220	LR: 0.004000
Training Epoch: 20 [9216/10020]	Loss: 0.1772	LR: 0.004000
Training Epoch: 20 [9472/10020]	Loss: 0.2441	LR: 0.004000
Training Epoch: 20 [9728/10020]	Loss: 0.1865	LR: 0.004000
Training Epoch: 20 [9984/10020]	Loss: 0.1490	LR: 0.004000
Training Epoch: 20 [10020/10020]	Loss: 0.3903	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2129, Train Accuracy: 0.9148
Epoch 20 training time consumed: 145.27s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0008, Accuracy: 0.9278, Time consumed:7.75s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-20-best.pth
Training Epoch: 21 [256/10020]	Loss: 0.1907	LR: 0.004000
Training Epoch: 21 [512/10020]	Loss: 0.1966	LR: 0.004000
Training Epoch: 21 [768/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 21 [1024/10020]	Loss: 0.1655	LR: 0.004000
Training Epoch: 21 [1280/10020]	Loss: 0.2464	LR: 0.004000
Training Epoch: 21 [1536/10020]	Loss: 0.2307	LR: 0.004000
Training Epoch: 21 [1792/10020]	Loss: 0.2620	LR: 0.004000
Training Epoch: 21 [2048/10020]	Loss: 0.1701	LR: 0.004000
Training Epoch: 21 [2304/10020]	Loss: 0.2567	LR: 0.004000
Training Epoch: 21 [2560/10020]	Loss: 0.2023	LR: 0.004000
Training Epoch: 21 [2816/10020]	Loss: 0.1770	LR: 0.004000
Training Epoch: 21 [3072/10020]	Loss: 0.2279	LR: 0.004000
Training Epoch: 21 [3328/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 21 [3584/10020]	Loss: 0.1713	LR: 0.004000
Training Epoch: 21 [3840/10020]	Loss: 0.1544	LR: 0.004000
Training Epoch: 21 [4096/10020]	Loss: 0.1786	LR: 0.004000
Training Epoch: 21 [4352/10020]	Loss: 0.1992	LR: 0.004000
Training Epoch: 21 [4608/10020]	Loss: 0.2686	LR: 0.004000
Training Epoch: 21 [4864/10020]	Loss: 0.1572	LR: 0.004000
Training Epoch: 21 [5120/10020]	Loss: 0.2281	LR: 0.004000
Training Epoch: 21 [5376/10020]	Loss: 0.1608	LR: 0.004000
Training Epoch: 21 [5632/10020]	Loss: 0.2136	LR: 0.004000
Training Epoch: 21 [5888/10020]	Loss: 0.2093	LR: 0.004000
Training Epoch: 21 [6144/10020]	Loss: 0.1654	LR: 0.004000
Training Epoch: 21 [6400/10020]	Loss: 0.1784	LR: 0.004000
Training Epoch: 21 [6656/10020]	Loss: 0.2060	LR: 0.004000
Training Epoch: 21 [6912/10020]	Loss: 0.1719	LR: 0.004000
Training Epoch: 21 [7168/10020]	Loss: 0.2152	LR: 0.004000
Training Epoch: 21 [7424/10020]	Loss: 0.1915	LR: 0.004000
Training Epoch: 21 [7680/10020]	Loss: 0.2245	LR: 0.004000
Training Epoch: 21 [7936/10020]	Loss: 0.1787	LR: 0.004000
Training Epoch: 21 [8192/10020]	Loss: 0.1907	LR: 0.004000
Training Epoch: 21 [8448/10020]	Loss: 0.1542	LR: 0.004000
Training Epoch: 21 [8704/10020]	Loss: 0.1664	LR: 0.004000
Training Epoch: 21 [8960/10020]	Loss: 0.2240	LR: 0.004000
Training Epoch: 21 [9216/10020]	Loss: 0.1896	LR: 0.004000
Training Epoch: 21 [9472/10020]	Loss: 0.1216	LR: 0.004000
Training Epoch: 21 [9728/10020]	Loss: 0.1820	LR: 0.004000
Training Epoch: 21 [9984/10020]	Loss: 0.2610	LR: 0.004000
Training Epoch: 21 [10020/10020]	Loss: 0.1054	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1959, Train Accuracy: 0.9209
Epoch 21 training time consumed: 144.37s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9298, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-21-best.pth
Training Epoch: 22 [256/10020]	Loss: 0.1933	LR: 0.004000
Training Epoch: 22 [512/10020]	Loss: 0.1345	LR: 0.004000
Training Epoch: 22 [768/10020]	Loss: 0.2006	LR: 0.004000
Training Epoch: 22 [1024/10020]	Loss: 0.1401	LR: 0.004000
Training Epoch: 22 [1280/10020]	Loss: 0.1712	LR: 0.004000
Training Epoch: 22 [1536/10020]	Loss: 0.1975	LR: 0.004000
Training Epoch: 22 [1792/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 22 [2048/10020]	Loss: 0.1421	LR: 0.004000
Training Epoch: 22 [2304/10020]	Loss: 0.2095	LR: 0.004000
Training Epoch: 22 [2560/10020]	Loss: 0.1939	LR: 0.004000
Training Epoch: 22 [2816/10020]	Loss: 0.1711	LR: 0.004000
Training Epoch: 22 [3072/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 22 [3328/10020]	Loss: 0.2318	LR: 0.004000
Training Epoch: 22 [3584/10020]	Loss: 0.2538	LR: 0.004000
Training Epoch: 22 [3840/10020]	Loss: 0.1774	LR: 0.004000
Training Epoch: 22 [4096/10020]	Loss: 0.1623	LR: 0.004000
Training Epoch: 22 [4352/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 22 [4608/10020]	Loss: 0.2012	LR: 0.004000
Training Epoch: 22 [4864/10020]	Loss: 0.1648	LR: 0.004000
Training Epoch: 22 [5120/10020]	Loss: 0.1607	LR: 0.004000
Training Epoch: 22 [5376/10020]	Loss: 0.1469	LR: 0.004000
Training Epoch: 22 [5632/10020]	Loss: 0.1580	LR: 0.004000
Training Epoch: 22 [5888/10020]	Loss: 0.1500	LR: 0.004000
Training Epoch: 22 [6144/10020]	Loss: 0.1760	LR: 0.004000
Training Epoch: 22 [6400/10020]	Loss: 0.1817	LR: 0.004000
Training Epoch: 22 [6656/10020]	Loss: 0.1876	LR: 0.004000
Training Epoch: 22 [6912/10020]	Loss: 0.1760	LR: 0.004000
Training Epoch: 22 [7168/10020]	Loss: 0.1987	LR: 0.004000
Training Epoch: 22 [7424/10020]	Loss: 0.1436	LR: 0.004000
Training Epoch: 22 [7680/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 22 [7936/10020]	Loss: 0.2416	LR: 0.004000
Training Epoch: 22 [8192/10020]	Loss: 0.1778	LR: 0.004000
Training Epoch: 22 [8448/10020]	Loss: 0.1581	LR: 0.004000
Training Epoch: 22 [8704/10020]	Loss: 0.2597	LR: 0.004000
Training Epoch: 22 [8960/10020]	Loss: 0.1415	LR: 0.004000
Training Epoch: 22 [9216/10020]	Loss: 0.2320	LR: 0.004000
Training Epoch: 22 [9472/10020]	Loss: 0.1569	LR: 0.004000
Training Epoch: 22 [9728/10020]	Loss: 0.1659	LR: 0.004000
Training Epoch: 22 [9984/10020]	Loss: 0.2481	LR: 0.004000
Training Epoch: 22 [10020/10020]	Loss: 0.0661	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1805, Train Accuracy: 0.9251
Epoch 22 training time consumed: 144.39s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0008, Accuracy: 0.9245, Time consumed:7.64s
Training Epoch: 23 [256/10020]	Loss: 0.1497	LR: 0.004000
Training Epoch: 23 [512/10020]	Loss: 0.1392	LR: 0.004000
Training Epoch: 23 [768/10020]	Loss: 0.1920	LR: 0.004000
Training Epoch: 23 [1024/10020]	Loss: 0.1697	LR: 0.004000
Training Epoch: 23 [1280/10020]	Loss: 0.2464	LR: 0.004000
Training Epoch: 23 [1536/10020]	Loss: 0.1669	LR: 0.004000
Training Epoch: 23 [1792/10020]	Loss: 0.1946	LR: 0.004000
Training Epoch: 23 [2048/10020]	Loss: 0.2296	LR: 0.004000
Training Epoch: 23 [2304/10020]	Loss: 0.1863	LR: 0.004000
Training Epoch: 23 [2560/10020]	Loss: 0.2155	LR: 0.004000
Training Epoch: 23 [2816/10020]	Loss: 0.1907	LR: 0.004000
Training Epoch: 23 [3072/10020]	Loss: 0.1693	LR: 0.004000
Training Epoch: 23 [3328/10020]	Loss: 0.2103	LR: 0.004000
Training Epoch: 23 [3584/10020]	Loss: 0.2320	LR: 0.004000
Training Epoch: 23 [3840/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 23 [4096/10020]	Loss: 0.1519	LR: 0.004000
Training Epoch: 23 [4352/10020]	Loss: 0.1719	LR: 0.004000
Training Epoch: 23 [4608/10020]	Loss: 0.1948	LR: 0.004000
Training Epoch: 23 [4864/10020]	Loss: 0.2133	LR: 0.004000
Training Epoch: 23 [5120/10020]	Loss: 0.1928	LR: 0.004000
Training Epoch: 23 [5376/10020]	Loss: 0.1846	LR: 0.004000
Training Epoch: 23 [5632/10020]	Loss: 0.1914	LR: 0.004000
Training Epoch: 23 [5888/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 23 [6144/10020]	Loss: 0.2134	LR: 0.004000
Training Epoch: 23 [6400/10020]	Loss: 0.1912	LR: 0.004000
Training Epoch: 23 [6656/10020]	Loss: 0.1817	LR: 0.004000
Training Epoch: 23 [6912/10020]	Loss: 0.1404	LR: 0.004000
Training Epoch: 23 [7168/10020]	Loss: 0.0982	LR: 0.004000
Training Epoch: 23 [7424/10020]	Loss: 0.1809	LR: 0.004000
Training Epoch: 23 [7680/10020]	Loss: 0.2270	LR: 0.004000
Training Epoch: 23 [7936/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 23 [8192/10020]	Loss: 0.1985	LR: 0.004000
Training Epoch: 23 [8448/10020]	Loss: 0.1633	LR: 0.004000
Training Epoch: 23 [8704/10020]	Loss: 0.1354	LR: 0.004000
Training Epoch: 23 [8960/10020]	Loss: 0.2410	LR: 0.004000
Training Epoch: 23 [9216/10020]	Loss: 0.1612	LR: 0.004000
Training Epoch: 23 [9472/10020]	Loss: 0.1718	LR: 0.004000
Training Epoch: 23 [9728/10020]	Loss: 0.1529	LR: 0.004000
Training Epoch: 23 [9984/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 23 [10020/10020]	Loss: 0.2221	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1833, Train Accuracy: 0.9252
Epoch 23 training time consumed: 144.15s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9370, Time consumed:7.97s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-23-best.pth
Training Epoch: 24 [256/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 24 [512/10020]	Loss: 0.1534	LR: 0.004000
Training Epoch: 24 [768/10020]	Loss: 0.1294	LR: 0.004000
Training Epoch: 24 [1024/10020]	Loss: 0.1588	LR: 0.004000
Training Epoch: 24 [1280/10020]	Loss: 0.1456	LR: 0.004000
Training Epoch: 24 [1536/10020]	Loss: 0.2057	LR: 0.004000
Training Epoch: 24 [1792/10020]	Loss: 0.2197	LR: 0.004000
Training Epoch: 24 [2048/10020]	Loss: 0.1908	LR: 0.004000
Training Epoch: 24 [2304/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 24 [2560/10020]	Loss: 0.1650	LR: 0.004000
Training Epoch: 24 [2816/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 24 [3072/10020]	Loss: 0.1645	LR: 0.004000
Training Epoch: 24 [3328/10020]	Loss: 0.1566	LR: 0.004000
Training Epoch: 24 [3584/10020]	Loss: 0.1676	LR: 0.004000
Training Epoch: 24 [3840/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 24 [4096/10020]	Loss: 0.1333	LR: 0.004000
Training Epoch: 24 [4352/10020]	Loss: 0.1570	LR: 0.004000
Training Epoch: 24 [4608/10020]	Loss: 0.1830	LR: 0.004000
Training Epoch: 24 [4864/10020]	Loss: 0.2058	LR: 0.004000
Training Epoch: 24 [5120/10020]	Loss: 0.1488	LR: 0.004000
Training Epoch: 24 [5376/10020]	Loss: 0.1686	LR: 0.004000
Training Epoch: 24 [5632/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 24 [5888/10020]	Loss: 0.1674	LR: 0.004000
Training Epoch: 24 [6144/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 24 [6400/10020]	Loss: 0.1478	LR: 0.004000
Training Epoch: 24 [6656/10020]	Loss: 0.1534	LR: 0.004000
Training Epoch: 24 [6912/10020]	Loss: 0.1987	LR: 0.004000
Training Epoch: 24 [7168/10020]	Loss: 0.1429	LR: 0.004000
Training Epoch: 24 [7424/10020]	Loss: 0.2372	LR: 0.004000
Training Epoch: 24 [7680/10020]	Loss: 0.1844	LR: 0.004000
Training Epoch: 24 [7936/10020]	Loss: 0.1640	LR: 0.004000
Training Epoch: 24 [8192/10020]	Loss: 0.1507	LR: 0.004000
Training Epoch: 24 [8448/10020]	Loss: 0.2471	LR: 0.004000
Training Epoch: 24 [8704/10020]	Loss: 0.1863	LR: 0.004000
Training Epoch: 24 [8960/10020]	Loss: 0.1424	LR: 0.004000
Training Epoch: 24 [9216/10020]	Loss: 0.2221	LR: 0.004000
Training Epoch: 24 [9472/10020]	Loss: 0.2053	LR: 0.004000
Training Epoch: 24 [9728/10020]	Loss: 0.2320	LR: 0.004000
Training Epoch: 24 [9984/10020]	Loss: 0.1714	LR: 0.004000
Training Epoch: 24 [10020/10020]	Loss: 0.2750	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1728, Train Accuracy: 0.9308
Epoch 24 training time consumed: 144.26s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0007, Accuracy: 0.9278, Time consumed:7.74s
Training Epoch: 25 [256/10020]	Loss: 0.1531	LR: 0.004000
Training Epoch: 25 [512/10020]	Loss: 0.1522	LR: 0.004000
Training Epoch: 25 [768/10020]	Loss: 0.1433	LR: 0.004000
Training Epoch: 25 [1024/10020]	Loss: 0.1895	LR: 0.004000
Training Epoch: 25 [1280/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 25 [1536/10020]	Loss: 0.1880	LR: 0.004000
Training Epoch: 25 [1792/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 25 [2048/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 25 [2304/10020]	Loss: 0.1717	LR: 0.004000
Training Epoch: 25 [2560/10020]	Loss: 0.2085	LR: 0.004000
Training Epoch: 25 [2816/10020]	Loss: 0.1767	LR: 0.004000
Training Epoch: 25 [3072/10020]	Loss: 0.1626	LR: 0.004000
Training Epoch: 25 [3328/10020]	Loss: 0.1931	LR: 0.004000
Training Epoch: 25 [3584/10020]	Loss: 0.1507	LR: 0.004000
Training Epoch: 25 [3840/10020]	Loss: 0.1921	LR: 0.004000
Training Epoch: 25 [4096/10020]	Loss: 0.2331	LR: 0.004000
Training Epoch: 25 [4352/10020]	Loss: 0.1743	LR: 0.004000
Training Epoch: 25 [4608/10020]	Loss: 0.1837	LR: 0.004000
Training Epoch: 25 [4864/10020]	Loss: 0.1866	LR: 0.004000
Training Epoch: 25 [5120/10020]	Loss: 0.2007	LR: 0.004000
Training Epoch: 25 [5376/10020]	Loss: 0.1493	LR: 0.004000
Training Epoch: 25 [5632/10020]	Loss: 0.1749	LR: 0.004000
Training Epoch: 25 [5888/10020]	Loss: 0.1398	LR: 0.004000
Training Epoch: 25 [6144/10020]	Loss: 0.1565	LR: 0.004000
Training Epoch: 25 [6400/10020]	Loss: 0.1450	LR: 0.004000
Training Epoch: 25 [6656/10020]	Loss: 0.1486	LR: 0.004000
Training Epoch: 25 [6912/10020]	Loss: 0.2170	LR: 0.004000
Training Epoch: 25 [7168/10020]	Loss: 0.1844	LR: 0.004000
Training Epoch: 25 [7424/10020]	Loss: 0.1707	LR: 0.004000
Training Epoch: 25 [7680/10020]	Loss: 0.1810	LR: 0.004000
Training Epoch: 25 [7936/10020]	Loss: 0.1674	LR: 0.004000
Training Epoch: 25 [8192/10020]	Loss: 0.2320	LR: 0.004000
Training Epoch: 25 [8448/10020]	Loss: 0.1410	LR: 0.004000
Training Epoch: 25 [8704/10020]	Loss: 0.0946	LR: 0.004000
Training Epoch: 25 [8960/10020]	Loss: 0.1783	LR: 0.004000
Training Epoch: 25 [9216/10020]	Loss: 0.1833	LR: 0.004000
Training Epoch: 25 [9472/10020]	Loss: 0.1864	LR: 0.004000
Training Epoch: 25 [9728/10020]	Loss: 0.1921	LR: 0.004000
Training Epoch: 25 [9984/10020]	Loss: 0.1833	LR: 0.004000
Training Epoch: 25 [10020/10020]	Loss: 0.1324	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1736, Train Accuracy: 0.9303
Epoch 25 training time consumed: 143.99s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9375, Time consumed:8.00s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-25-best.pth
Training Epoch: 26 [256/10020]	Loss: 0.1434	LR: 0.004000
Training Epoch: 26 [512/10020]	Loss: 0.1290	LR: 0.004000
Training Epoch: 26 [768/10020]	Loss: 0.1861	LR: 0.004000
Training Epoch: 26 [1024/10020]	Loss: 0.1757	LR: 0.004000
Training Epoch: 26 [1280/10020]	Loss: 0.1656	LR: 0.004000
Training Epoch: 26 [1536/10020]	Loss: 0.1935	LR: 0.004000
Training Epoch: 26 [1792/10020]	Loss: 0.1530	LR: 0.004000
Training Epoch: 26 [2048/10020]	Loss: 0.1574	LR: 0.004000
Training Epoch: 26 [2304/10020]	Loss: 0.1388	LR: 0.004000
Training Epoch: 26 [2560/10020]	Loss: 0.1545	LR: 0.004000
Training Epoch: 26 [2816/10020]	Loss: 0.1168	LR: 0.004000
Training Epoch: 26 [3072/10020]	Loss: 0.1818	LR: 0.004000
Training Epoch: 26 [3328/10020]	Loss: 0.1922	LR: 0.004000
Training Epoch: 26 [3584/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 26 [3840/10020]	Loss: 0.1260	LR: 0.004000
Training Epoch: 26 [4096/10020]	Loss: 0.1976	LR: 0.004000
Training Epoch: 26 [4352/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 26 [4608/10020]	Loss: 0.1791	LR: 0.004000
Training Epoch: 26 [4864/10020]	Loss: 0.1445	LR: 0.004000
Training Epoch: 26 [5120/10020]	Loss: 0.1336	LR: 0.004000
Training Epoch: 26 [5376/10020]	Loss: 0.1375	LR: 0.004000
Training Epoch: 26 [5632/10020]	Loss: 0.0887	LR: 0.004000
Training Epoch: 26 [5888/10020]	Loss: 0.1721	LR: 0.004000
Training Epoch: 26 [6144/10020]	Loss: 0.1881	LR: 0.004000
Training Epoch: 26 [6400/10020]	Loss: 0.2136	LR: 0.004000
Training Epoch: 26 [6656/10020]	Loss: 0.1848	LR: 0.004000
Training Epoch: 26 [6912/10020]	Loss: 0.1571	LR: 0.004000
Training Epoch: 26 [7168/10020]	Loss: 0.1813	LR: 0.004000
Training Epoch: 26 [7424/10020]	Loss: 0.1791	LR: 0.004000
Training Epoch: 26 [7680/10020]	Loss: 0.1834	LR: 0.004000
Training Epoch: 26 [7936/10020]	Loss: 0.1731	LR: 0.004000
Training Epoch: 26 [8192/10020]	Loss: 0.1619	LR: 0.004000
Training Epoch: 26 [8448/10020]	Loss: 0.1435	LR: 0.004000
Training Epoch: 26 [8704/10020]	Loss: 0.1353	LR: 0.004000
Training Epoch: 26 [8960/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 26 [9216/10020]	Loss: 0.1797	LR: 0.004000
Training Epoch: 26 [9472/10020]	Loss: 0.1299	LR: 0.004000
Training Epoch: 26 [9728/10020]	Loss: 0.1713	LR: 0.004000
Training Epoch: 26 [9984/10020]	Loss: 0.1442	LR: 0.004000
Training Epoch: 26 [10020/10020]	Loss: 0.1020	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1599, Train Accuracy: 0.9328
Epoch 26 training time consumed: 144.44s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9375, Time consumed:7.57s
Training Epoch: 27 [256/10020]	Loss: 0.1465	LR: 0.004000
Training Epoch: 27 [512/10020]	Loss: 0.2350	LR: 0.004000
Training Epoch: 27 [768/10020]	Loss: 0.1246	LR: 0.004000
Training Epoch: 27 [1024/10020]	Loss: 0.1488	LR: 0.004000
Training Epoch: 27 [1280/10020]	Loss: 0.1650	LR: 0.004000
Training Epoch: 27 [1536/10020]	Loss: 0.1578	LR: 0.004000
Training Epoch: 27 [1792/10020]	Loss: 0.1769	LR: 0.004000
Training Epoch: 27 [2048/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 27 [2304/10020]	Loss: 0.1040	LR: 0.004000
Training Epoch: 27 [2560/10020]	Loss: 0.1384	LR: 0.004000
Training Epoch: 27 [2816/10020]	Loss: 0.2302	LR: 0.004000
Training Epoch: 27 [3072/10020]	Loss: 0.1453	LR: 0.004000
Training Epoch: 27 [3328/10020]	Loss: 0.1099	LR: 0.004000
Training Epoch: 27 [3584/10020]	Loss: 0.1150	LR: 0.004000
Training Epoch: 27 [3840/10020]	Loss: 0.1906	LR: 0.004000
Training Epoch: 27 [4096/10020]	Loss: 0.1797	LR: 0.004000
Training Epoch: 27 [4352/10020]	Loss: 0.1004	LR: 0.004000
Training Epoch: 27 [4608/10020]	Loss: 0.1829	LR: 0.004000
Training Epoch: 27 [4864/10020]	Loss: 0.1124	LR: 0.004000
Training Epoch: 27 [5120/10020]	Loss: 0.1482	LR: 0.004000
Training Epoch: 27 [5376/10020]	Loss: 0.1379	LR: 0.004000
Training Epoch: 27 [5632/10020]	Loss: 0.1396	LR: 0.004000
Training Epoch: 27 [5888/10020]	Loss: 0.1284	LR: 0.004000
Training Epoch: 27 [6144/10020]	Loss: 0.2043	LR: 0.004000
Training Epoch: 27 [6400/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 27 [6656/10020]	Loss: 0.1663	LR: 0.004000
Training Epoch: 27 [6912/10020]	Loss: 0.1689	LR: 0.004000
Training Epoch: 27 [7168/10020]	Loss: 0.1585	LR: 0.004000
Training Epoch: 27 [7424/10020]	Loss: 0.1475	LR: 0.004000
Training Epoch: 27 [7680/10020]	Loss: 0.1527	LR: 0.004000
Training Epoch: 27 [7936/10020]	Loss: 0.1644	LR: 0.004000
Training Epoch: 27 [8192/10020]	Loss: 0.1698	LR: 0.004000
Training Epoch: 27 [8448/10020]	Loss: 0.1678	LR: 0.004000
Training Epoch: 27 [8704/10020]	Loss: 0.1709	LR: 0.004000
Training Epoch: 27 [8960/10020]	Loss: 0.1287	LR: 0.004000
Training Epoch: 27 [9216/10020]	Loss: 0.1614	LR: 0.004000
Training Epoch: 27 [9472/10020]	Loss: 0.1851	LR: 0.004000
Training Epoch: 27 [9728/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 27 [9984/10020]	Loss: 0.1434	LR: 0.004000
Training Epoch: 27 [10020/10020]	Loss: 0.3205	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1559, Train Accuracy: 0.9373
Epoch 27 training time consumed: 143.85s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0008, Accuracy: 0.9254, Time consumed:7.96s
Training Epoch: 28 [256/10020]	Loss: 0.1576	LR: 0.004000
Training Epoch: 28 [512/10020]	Loss: 0.1899	LR: 0.004000
Training Epoch: 28 [768/10020]	Loss: 0.1840	LR: 0.004000
Training Epoch: 28 [1024/10020]	Loss: 0.1492	LR: 0.004000
Training Epoch: 28 [1280/10020]	Loss: 0.2520	LR: 0.004000
Training Epoch: 28 [1536/10020]	Loss: 0.1455	LR: 0.004000
Training Epoch: 28 [1792/10020]	Loss: 0.1513	LR: 0.004000
Training Epoch: 28 [2048/10020]	Loss: 0.2329	LR: 0.004000
Training Epoch: 28 [2304/10020]	Loss: 0.1643	LR: 0.004000
Training Epoch: 28 [2560/10020]	Loss: 0.1607	LR: 0.004000
Training Epoch: 28 [2816/10020]	Loss: 0.1473	LR: 0.004000
Training Epoch: 28 [3072/10020]	Loss: 0.1588	LR: 0.004000
Training Epoch: 28 [3328/10020]	Loss: 0.1470	LR: 0.004000
Training Epoch: 28 [3584/10020]	Loss: 0.1767	LR: 0.004000
Training Epoch: 28 [3840/10020]	Loss: 0.1615	LR: 0.004000
Training Epoch: 28 [4096/10020]	Loss: 0.1572	LR: 0.004000
Training Epoch: 28 [4352/10020]	Loss: 0.1362	LR: 0.004000
Training Epoch: 28 [4608/10020]	Loss: 0.1394	LR: 0.004000
Training Epoch: 28 [4864/10020]	Loss: 0.1498	LR: 0.004000
Training Epoch: 28 [5120/10020]	Loss: 0.1850	LR: 0.004000
Training Epoch: 28 [5376/10020]	Loss: 0.1824	LR: 0.004000
Training Epoch: 28 [5632/10020]	Loss: 0.1667	LR: 0.004000
Training Epoch: 28 [5888/10020]	Loss: 0.1299	LR: 0.004000
Training Epoch: 28 [6144/10020]	Loss: 0.1477	LR: 0.004000
Training Epoch: 28 [6400/10020]	Loss: 0.0775	LR: 0.004000
Training Epoch: 28 [6656/10020]	Loss: 0.1327	LR: 0.004000
Training Epoch: 28 [6912/10020]	Loss: 0.1813	LR: 0.004000
Training Epoch: 28 [7168/10020]	Loss: 0.1443	LR: 0.004000
Training Epoch: 28 [7424/10020]	Loss: 0.1587	LR: 0.004000
Training Epoch: 28 [7680/10020]	Loss: 0.1501	LR: 0.004000
Training Epoch: 28 [7936/10020]	Loss: 0.1422	LR: 0.004000
Training Epoch: 28 [8192/10020]	Loss: 0.1696	LR: 0.004000
Training Epoch: 28 [8448/10020]	Loss: 0.1491	LR: 0.004000
Training Epoch: 28 [8704/10020]	Loss: 0.1456	LR: 0.004000
Training Epoch: 28 [8960/10020]	Loss: 0.1555	LR: 0.004000
Training Epoch: 28 [9216/10020]	Loss: 0.1436	LR: 0.004000
Training Epoch: 28 [9472/10020]	Loss: 0.1718	LR: 0.004000
Training Epoch: 28 [9728/10020]	Loss: 0.1229	LR: 0.004000
Training Epoch: 28 [9984/10020]	Loss: 0.1446	LR: 0.004000
Training Epoch: 28 [10020/10020]	Loss: 0.7221	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1600, Train Accuracy: 0.9351
Epoch 28 training time consumed: 143.64s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9240, Time consumed:7.64s
Training Epoch: 29 [256/10020]	Loss: 0.1998	LR: 0.004000
Training Epoch: 29 [512/10020]	Loss: 0.1540	LR: 0.004000
Training Epoch: 29 [768/10020]	Loss: 0.2144	LR: 0.004000
Training Epoch: 29 [1024/10020]	Loss: 0.1985	LR: 0.004000
Training Epoch: 29 [1280/10020]	Loss: 0.1775	LR: 0.004000
Training Epoch: 29 [1536/10020]	Loss: 0.1533	LR: 0.004000
Training Epoch: 29 [1792/10020]	Loss: 0.1643	LR: 0.004000
Training Epoch: 29 [2048/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 29 [2304/10020]	Loss: 0.2278	LR: 0.004000
Training Epoch: 29 [2560/10020]	Loss: 0.1235	LR: 0.004000
Training Epoch: 29 [2816/10020]	Loss: 0.1862	LR: 0.004000
Training Epoch: 29 [3072/10020]	Loss: 0.1898	LR: 0.004000
Training Epoch: 29 [3328/10020]	Loss: 0.1846	LR: 0.004000
Training Epoch: 29 [3584/10020]	Loss: 0.1732	LR: 0.004000
Training Epoch: 29 [3840/10020]	Loss: 0.1599	LR: 0.004000
Training Epoch: 29 [4096/10020]	Loss: 0.1795	LR: 0.004000
Training Epoch: 29 [4352/10020]	Loss: 0.1403	LR: 0.004000
Training Epoch: 29 [4608/10020]	Loss: 0.1870	LR: 0.004000
Training Epoch: 29 [4864/10020]	Loss: 0.2140	LR: 0.004000
Training Epoch: 29 [5120/10020]	Loss: 0.1612	LR: 0.004000
Training Epoch: 29 [5376/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 29 [5632/10020]	Loss: 0.1589	LR: 0.004000
Training Epoch: 29 [5888/10020]	Loss: 0.1286	LR: 0.004000
Training Epoch: 29 [6144/10020]	Loss: 0.1687	LR: 0.004000
Training Epoch: 29 [6400/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 29 [6656/10020]	Loss: 0.2103	LR: 0.004000
Training Epoch: 29 [6912/10020]	Loss: 0.2008	LR: 0.004000
Training Epoch: 29 [7168/10020]	Loss: 0.2067	LR: 0.004000
Training Epoch: 29 [7424/10020]	Loss: 0.2174	LR: 0.004000
Training Epoch: 29 [7680/10020]	Loss: 0.1508	LR: 0.004000
Training Epoch: 29 [7936/10020]	Loss: 0.1338	LR: 0.004000
Training Epoch: 29 [8192/10020]	Loss: 0.1728	LR: 0.004000
Training Epoch: 29 [8448/10020]	Loss: 0.1331	LR: 0.004000
Training Epoch: 29 [8704/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 29 [8960/10020]	Loss: 0.1722	LR: 0.004000
Training Epoch: 29 [9216/10020]	Loss: 0.1815	LR: 0.004000
Training Epoch: 29 [9472/10020]	Loss: 0.1276	LR: 0.004000
Training Epoch: 29 [9728/10020]	Loss: 0.1595	LR: 0.004000
Training Epoch: 29 [9984/10020]	Loss: 0.1949	LR: 0.004000
Training Epoch: 29 [10020/10020]	Loss: 0.0713	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1704, Train Accuracy: 0.9319
Epoch 29 training time consumed: 143.89s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0007, Accuracy: 0.9346, Time consumed:8.03s
Training Epoch: 30 [256/10020]	Loss: 0.1840	LR: 0.004000
Training Epoch: 30 [512/10020]	Loss: 0.1511	LR: 0.004000
Training Epoch: 30 [768/10020]	Loss: 0.1629	LR: 0.004000
Training Epoch: 30 [1024/10020]	Loss: 0.1680	LR: 0.004000
Training Epoch: 30 [1280/10020]	Loss: 0.1160	LR: 0.004000
Training Epoch: 30 [1536/10020]	Loss: 0.2015	LR: 0.004000
Training Epoch: 30 [1792/10020]	Loss: 0.1732	LR: 0.004000
Training Epoch: 30 [2048/10020]	Loss: 0.1869	LR: 0.004000
Training Epoch: 30 [2304/10020]	Loss: 0.1698	LR: 0.004000
Training Epoch: 30 [2560/10020]	Loss: 0.1725	LR: 0.004000
Training Epoch: 30 [2816/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 30 [3072/10020]	Loss: 0.1496	LR: 0.004000
Training Epoch: 30 [3328/10020]	Loss: 0.1309	LR: 0.004000
Training Epoch: 30 [3584/10020]	Loss: 0.1841	LR: 0.004000
Training Epoch: 30 [3840/10020]	Loss: 0.1593	LR: 0.004000
Training Epoch: 30 [4096/10020]	Loss: 0.1695	LR: 0.004000
Training Epoch: 30 [4352/10020]	Loss: 0.1121	LR: 0.004000
Training Epoch: 30 [4608/10020]	Loss: 0.1802	LR: 0.004000
Training Epoch: 30 [4864/10020]	Loss: 0.1413	LR: 0.004000
Training Epoch: 30 [5120/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 30 [5376/10020]	Loss: 0.1526	LR: 0.004000
Training Epoch: 30 [5632/10020]	Loss: 0.2100	LR: 0.004000
Training Epoch: 30 [5888/10020]	Loss: 0.1616	LR: 0.004000
Training Epoch: 30 [6144/10020]	Loss: 0.1323	LR: 0.004000
Training Epoch: 30 [6400/10020]	Loss: 0.1280	LR: 0.004000
Training Epoch: 30 [6656/10020]	Loss: 0.1579	LR: 0.004000
Training Epoch: 30 [6912/10020]	Loss: 0.1181	LR: 0.004000
Training Epoch: 30 [7168/10020]	Loss: 0.1746	LR: 0.004000
Training Epoch: 30 [7424/10020]	Loss: 0.1002	LR: 0.004000
Training Epoch: 30 [7680/10020]	Loss: 0.1539	LR: 0.004000
Training Epoch: 30 [7936/10020]	Loss: 0.1356	LR: 0.004000
Training Epoch: 30 [8192/10020]	Loss: 0.1450	LR: 0.004000
Training Epoch: 30 [8448/10020]	Loss: 0.1441	LR: 0.004000
Training Epoch: 30 [8704/10020]	Loss: 0.2189	LR: 0.004000
Training Epoch: 30 [8960/10020]	Loss: 0.1306	LR: 0.004000
Training Epoch: 30 [9216/10020]	Loss: 0.1512	LR: 0.004000
Training Epoch: 30 [9472/10020]	Loss: 0.1633	LR: 0.004000
Training Epoch: 30 [9728/10020]	Loss: 0.1112	LR: 0.004000
Training Epoch: 30 [9984/10020]	Loss: 0.1812	LR: 0.004000
Training Epoch: 30 [10020/10020]	Loss: 0.1395	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1562, Train Accuracy: 0.9354
Epoch 30 training time consumed: 144.15s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9429, Time consumed:7.55s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_20h_07m_31s/ResNet18-MUCAC-seed4-ret50-30-best.pth
Training Epoch: 31 [256/10020]	Loss: 0.1395	LR: 0.004000
Training Epoch: 31 [512/10020]	Loss: 0.1298	LR: 0.004000
Training Epoch: 31 [768/10020]	Loss: 0.1205	LR: 0.004000
Training Epoch: 31 [1024/10020]	Loss: 0.0916	LR: 0.004000
Training Epoch: 31 [1280/10020]	Loss: 0.1741	LR: 0.004000
Training Epoch: 31 [1536/10020]	Loss: 0.1969	LR: 0.004000
Training Epoch: 31 [1792/10020]	Loss: 0.1599	LR: 0.004000
Training Epoch: 31 [2048/10020]	Loss: 0.1662	LR: 0.004000
Training Epoch: 31 [2304/10020]	Loss: 0.1514	LR: 0.004000
Training Epoch: 31 [2560/10020]	Loss: 0.1346	LR: 0.004000
Training Epoch: 31 [2816/10020]	Loss: 0.1431	LR: 0.004000
Training Epoch: 31 [3072/10020]	Loss: 0.1964	LR: 0.004000
Training Epoch: 31 [3328/10020]	Loss: 0.1515	LR: 0.004000
Training Epoch: 31 [3584/10020]	Loss: 0.0988	LR: 0.004000
Training Epoch: 31 [3840/10020]	Loss: 0.1418	LR: 0.004000
Training Epoch: 31 [4096/10020]	Loss: 0.2021	LR: 0.004000
Training Epoch: 31 [4352/10020]	Loss: 0.1682	LR: 0.004000
Training Epoch: 31 [4608/10020]	Loss: 0.1584	LR: 0.004000
Training Epoch: 31 [4864/10020]	Loss: 0.1650	LR: 0.004000
Training Epoch: 31 [5120/10020]	Loss: 0.1174	LR: 0.004000
Training Epoch: 31 [5376/10020]	Loss: 0.1634	LR: 0.004000
Training Epoch: 31 [5632/10020]	Loss: 0.1000	LR: 0.004000
Training Epoch: 31 [5888/10020]	Loss: 0.1601	LR: 0.004000
Training Epoch: 31 [6144/10020]	Loss: 0.1621	LR: 0.004000
Training Epoch: 31 [6400/10020]	Loss: 0.1167	LR: 0.004000
Training Epoch: 31 [6656/10020]	Loss: 0.1204	LR: 0.004000
Training Epoch: 31 [6912/10020]	Loss: 0.2430	LR: 0.004000
Training Epoch: 31 [7168/10020]	Loss: 0.1117	LR: 0.004000
Training Epoch: 31 [7424/10020]	Loss: 0.1965	LR: 0.004000
Training Epoch: 31 [7680/10020]	Loss: 0.1636	LR: 0.004000
Training Epoch: 31 [7936/10020]	Loss: 0.1675	LR: 0.004000
Training Epoch: 31 [8192/10020]	Loss: 0.1609	LR: 0.004000
Training Epoch: 31 [8448/10020]	Loss: 0.1373	LR: 0.004000
Training Epoch: 31 [8704/10020]	Loss: 0.1285	LR: 0.004000
Training Epoch: 31 [8960/10020]	Loss: 0.1452	LR: 0.004000
Training Epoch: 31 [9216/10020]	Loss: 0.1751	LR: 0.004000
Training Epoch: 31 [9472/10020]	Loss: 0.1340	LR: 0.004000
Training Epoch: 31 [9728/10020]	Loss: 0.1381	LR: 0.004000
Training Epoch: 31 [9984/10020]	Loss: 0.2113	LR: 0.004000
Training Epoch: 31 [10020/10020]	Loss: 0.1699	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1524, Train Accuracy: 0.9360
Epoch 31 training time consumed: 144.30s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0006, Accuracy: 0.9332, Time consumed:7.92s
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: 94.01041412353516
Retain Accuracy: 93.1716537475586
Zero-Retain Forget (ZRF): 0.7444837093353271
Membership Inference Attack (MIA): 0.35984848484848486
Forget vs Retain Membership Inference Attack (MIA): 0.47641509433962265
Forget vs Test Membership Inference Attack (MIA): 0.5424528301886793
Test vs Retain Membership Inference Attack (MIA): 0.5060532687651331
Train vs Test Membership Inference Attack (MIA): 0.5314769975786925
Forget Set Accuracy (Df): 92.83853912353516
Method Execution Time: 22650.26 seconds
