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

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

📌 S Forget class distribution for seed 3:
Class 0: 527
Class 1: 527

📊 Updated class distribution:
Retain set:
  Class 0: 5415
  Class 1: 4341
Forget set:
  Class 0: 396
  Class 1: 396
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
./data/MUCAC/CelebAMask-HQ/CelebA-HQ-img
⚠️ Warning: Retain train loader may not be shuffled.
Training Epoch: 1 [256/9756]	Loss: 0.7107	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.7157	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6994	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.6970	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.9187	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7332	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.8236	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.7441	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.8320	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 0.8717	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.7411	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 1.1999	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 0.7913	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 0.7817	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 0.6930	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 0.7392	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 1.2150	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 1.7616	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 0.6837	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 0.9993	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 0.8318	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 0.8165	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.7297	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.7530	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 0.7688	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7154	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.7883	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.7605	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.7491	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.7753	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.7292	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.7156	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.8144	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.7994	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 0.7112	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 0.8343	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.7463	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 0.7569	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 0.7738	LR: 0.097436
Epoch 1 - Average Train Loss: 0.8195, Train Accuracy: 0.5141
Epoch 1 training time consumed: 319.25s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.3794, Accuracy: 0.5550, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 1.6233	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 0.7175	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 1.2851	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.8410	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 1.2591	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.8430	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 1.0004	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.8616	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.8753	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.8777	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.6933	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.8762	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.7531	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.8674	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.8372	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.8520	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.7443	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.7801	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.7456	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.7278	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.6895	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.7132	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.7118	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.7032	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.6927	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.7004	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.7169	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.7096	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7171	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.7158	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7072	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.7043	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.6838	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6791	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.7073	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.6825	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.6457	LR: 0.100000
Epoch 2 - Average Train Loss: 0.8061, Train Accuracy: 0.5168
Epoch 2 training time consumed: 141.65s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0038, Accuracy: 0.5550, Time consumed:7.88s
Training Epoch: 3 [256/9756]	Loss: 0.8005	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 0.6911	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.6837	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.7146	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.6980	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.6811	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.7088	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.7554	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.6946	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.7269	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.6865	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.6952	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.7439	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.6998	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.6913	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.7227	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.7024	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.6821	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.7949	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.6719	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.7292	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.6793	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.7417	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6725	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6789	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.6922	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.7088	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.6670	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.7048	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.7095	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6677	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.6895	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.7197	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6825	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.6961	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6710	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.7082	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6715	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.6676	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7035, Train Accuracy: 0.5603
Epoch 3 training time consumed: 140.64s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0033, Accuracy: 0.5550, Time consumed:7.97s
Training Epoch: 4 [256/9756]	Loss: 0.7162	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.7145	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.6728	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.6803	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6933	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.6933	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6472	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.6907	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6698	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6592	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6781	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.6599	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.7070	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.7440	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.6758	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6846	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6896	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6969	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.6955	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.6817	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.7131	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.7133	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6681	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6773	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.7264	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.6792	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.6511	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6894	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6923	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6768	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.6630	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.6547	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6915	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.7151	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.6595	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6411	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6309	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6848, Train Accuracy: 0.5708
Epoch 4 training time consumed: 141.06s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0038, Accuracy: 0.5603, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-4-best.pth
Training Epoch: 5 [256/9756]	Loss: 0.6838	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.7124	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6797	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.7086	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.7252	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.6944	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.6909	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6939	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.7049	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.7149	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6846	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6948	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6860	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6835	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6740	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.7034	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6782	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.6700	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6590	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6688	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6691	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6495	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.6922	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.7035	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6542	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6826	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.6620	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6696	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6582	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6551	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6544	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6627	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6651	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6566	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6607	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6483	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6800, Train Accuracy: 0.5751
Epoch 5 training time consumed: 141.01s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0031, Accuracy: 0.5627, Time consumed:8.07s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-5-best.pth
Training Epoch: 6 [256/9756]	Loss: 0.7216	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.7413	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.6961	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.6942	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6870	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6819	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6877	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6830	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6656	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6934	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6655	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6692	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.6385	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6452	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6380	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6201	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.7107	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.6648	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.7043	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.6947	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.6755	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.6816	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6881	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6717	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6714	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6819	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.6920	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6665	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6638	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6662	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6716	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6706	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6856	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.6716	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6966	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6781, Train Accuracy: 0.5818
Epoch 6 training time consumed: 140.61s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0033, Accuracy: 0.4983, Time consumed:7.93s
Training Epoch: 7 [256/9756]	Loss: 0.6889	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6967	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6819	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6865	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6820	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6951	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6591	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6706	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6799	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.6972	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6491	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6741	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6606	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.6590	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.6473	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6616	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6760	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6469	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6653	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.6584	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6430	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6742	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6532	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6571	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6551	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6403	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6610	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6643	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6729	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6198	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6475	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6365	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6508	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.5973	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6637, Train Accuracy: 0.5999
Epoch 7 training time consumed: 140.89s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0055, Accuracy: 0.4731, Time consumed:7.98s
Training Epoch: 8 [256/9756]	Loss: 0.6795	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.7187	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6687	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.6888	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.6448	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6422	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6928	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6627	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.6810	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.6687	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6755	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6931	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6672	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6532	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6660	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.6727	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6540	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.6556	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.6572	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6416	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6410	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6701	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6593	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6675	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6467	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6481	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.6809	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6567	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6501	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.6431	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6368	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6625	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6218	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.6358	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6344	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6477	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.6461	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.6373	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6603, Train Accuracy: 0.6123
Epoch 8 training time consumed: 140.67s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0028, Accuracy: 0.6291, Time consumed:8.14s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-8-best.pth
Training Epoch: 9 [256/9756]	Loss: 0.6482	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.6536	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.6554	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.6503	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6344	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6496	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6684	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6252	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6518	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.6433	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6498	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6213	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6529	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6024	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.5935	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.6072	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.6379	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.6405	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.5658	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.7108	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.6029	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6890	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.6152	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.6373	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.6271	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.6095	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.6248	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.6481	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.6117	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6189	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.5861	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.6211	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.5853	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.6093	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.5894	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.6024	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.5958	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.5726	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.5154	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6262, Train Accuracy: 0.6576
Epoch 9 training time consumed: 140.93s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0032, Accuracy: 0.5801, Time consumed:8.12s
Training Epoch: 10 [256/9756]	Loss: 0.7137	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.6968	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.6429	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.5792	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.5719	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.5978	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.5383	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.6247	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.5741	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.6228	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.6143	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.6080	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.5742	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.5748	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.5802	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.5698	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.5341	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.5754	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.6255	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.5788	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.5419	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.5771	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.6215	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.6027	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.5872	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.5609	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.5813	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.6116	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.5412	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.5073	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.5335	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.5453	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.5222	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.5809	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.5208	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.5339	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.5495	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.5378	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.4728	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5801, Train Accuracy: 0.7017
Epoch 10 training time consumed: 140.64s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0032, Accuracy: 0.6155, Time consumed:8.01s
Training Epoch: 11 [256/9756]	Loss: 0.5507	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.5927	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.5446	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.5222	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.5730	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.5482	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.5494	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.5911	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.5155	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.5327	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.5541	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.5431	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.5355	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.5224	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.5920	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.5732	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.4928	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.6313	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.5389	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.5273	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.6135	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.5362	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.5512	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.5299	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.5109	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.5428	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.5098	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.5378	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.4793	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.4878	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.5215	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.5178	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.4937	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.4995	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.4627	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.5216	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.4737	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.4920	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.5865	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5347, Train Accuracy: 0.7301
Epoch 11 training time consumed: 140.63s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0049, Accuracy: 0.6867, Time consumed:7.88s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.7336	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.4656	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.4987	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.5446	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.5826	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.5290	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.5842	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.5426	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.5208	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.4955	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.5284	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.5573	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.5398	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.5501	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.5294	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.5169	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.5191	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.5038	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.5313	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.4997	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.5009	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.5229	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.4915	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.5531	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.5027	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.5031	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.4835	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.4789	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.5563	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.5453	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.5223	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.4893	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.5123	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.4820	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.5123	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.5016	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.5124	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.5283	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.4899	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5255, Train Accuracy: 0.7452
Epoch 12 training time consumed: 140.56s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0028, Accuracy: 0.6542, Time consumed:8.09s
Training Epoch: 13 [256/9756]	Loss: 0.4545	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.5050	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.4249	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.4877	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.5306	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.5038	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.5389	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.4556	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.4611	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.4902	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.4780	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.4844	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.4793	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.5192	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.4850	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.5076	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.4216	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.4649	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.4666	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.5392	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.4523	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.4689	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.4137	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.4504	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.4821	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.4625	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.4777	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.4446	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.4528	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.4113	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.4148	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.4396	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.4617	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.4545	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.4196	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.3836	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.4662	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.4180	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.3101	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4646, Train Accuracy: 0.7801
Epoch 13 training time consumed: 140.80s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0029, Accuracy: 0.6349, Time consumed:8.05s
Training Epoch: 14 [256/9756]	Loss: 0.6631	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.4442	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.4495	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.4890	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.4713	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.4978	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.5168	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.5373	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.4751	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.4737	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.4929	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.4667	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.5115	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.4608	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.4388	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.4540	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.4317	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.3941	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.4492	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.4790	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.4400	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.4980	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.4157	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.4888	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.4348	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.4221	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.4276	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.4278	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.3867	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.4949	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.4877	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.4585	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.4470	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.4869	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.5234	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.4025	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.4149	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.4166	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.4119	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4649, Train Accuracy: 0.7851
Epoch 14 training time consumed: 140.77s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0019, Accuracy: 0.8165, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-14-best.pth
Training Epoch: 15 [256/9756]	Loss: 0.4572	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.4221	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.5504	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.4886	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.4463	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.4182	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.4300	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.4259	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.4891	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.4712	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.4406	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.3740	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.4342	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.4411	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.4021	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.3706	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.3896	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.4216	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.4320	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.3768	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.4795	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.4545	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.4552	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.3510	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.3842	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.3952	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.3874	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.3939	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.4178	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.3895	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.3894	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.4055	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.4024	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.3362	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.3945	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.4237	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.4421	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.3764	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.5560	LR: 0.020000
Epoch 15 - Average Train Loss: 0.4204, Train Accuracy: 0.8058
Epoch 15 training time consumed: 140.48s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0019, Accuracy: 0.8155, Time consumed:7.89s
Training Epoch: 16 [256/9756]	Loss: 0.3894	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.4752	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.4225	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.4744	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.3346	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.4196	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.3605	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.4175	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.4032	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.4676	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.3987	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.4920	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.3960	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.3923	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.4217	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.3596	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.3569	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.4200	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.3743	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.3634	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.3688	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.4352	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.3674	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.3538	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.3862	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.4275	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.4705	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.3700	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.4081	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.3952	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.3871	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.3308	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.3586	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.3791	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.3275	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.4425	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.3844	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.3515	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.3336	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3968, Train Accuracy: 0.8226
Epoch 16 training time consumed: 140.38s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0033, Accuracy: 0.6692, Time consumed:8.19s
Training Epoch: 17 [256/9756]	Loss: 0.4479	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.4193	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.3634	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.3999	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.3690	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.4037	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.3774	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.3902	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.4428	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.3921	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.3399	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.3934	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.3838	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.3277	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.4937	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.3458	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.3576	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.4137	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.3940	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.3535	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.3771	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.3225	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.4327	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.4112	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.3496	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.3717	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.3108	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.3059	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.3678	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.4277	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.3581	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.3041	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.3570	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.3508	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.3477	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.3528	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.3718	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.3500	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.2561	LR: 0.020000
Epoch 17 - Average Train Loss: 0.3754, Train Accuracy: 0.8342
Epoch 17 training time consumed: 140.59s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0030, Accuracy: 0.5787, Time consumed:8.07s
Training Epoch: 18 [256/9756]	Loss: 0.3259	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.3223	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.4875	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2637	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.3558	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.3411	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.2856	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.3651	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.3131	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.3704	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.3332	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.3667	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.3305	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.4215	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.3443	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.3723	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.3041	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.3068	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.3752	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.4028	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2681	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.3879	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.3244	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.2974	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.3305	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.3661	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.2962	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.3581	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.3271	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.3470	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.3090	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.3318	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.3100	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.3479	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.2981	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.3578	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.3752	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.3247	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.3331	LR: 0.020000
Epoch 18 - Average Train Loss: 0.3406, Train Accuracy: 0.8518
Epoch 18 training time consumed: 140.11s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0015, Accuracy: 0.8576, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-18-best.pth
Training Epoch: 19 [256/9756]	Loss: 0.3441	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.3704	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.2935	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.3631	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.2998	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.3359	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.3069	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.3176	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.2622	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.2840	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.3101	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.3352	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.3242	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.3472	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.2908	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.3468	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.3005	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.3122	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.3431	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2698	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.2851	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.3657	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.2910	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.3189	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.3240	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.3190	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.2448	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.2428	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.3448	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.3166	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.3102	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.3597	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.3036	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.3266	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.3365	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.2531	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.2452	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.3380	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.3660	LR: 0.020000
Epoch 19 - Average Train Loss: 0.3129, Train Accuracy: 0.8658
Epoch 19 training time consumed: 140.47s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0021, Accuracy: 0.7898, Time consumed:7.76s
Training Epoch: 20 [256/9756]	Loss: 0.3360	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.3226	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.2724	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2962	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.3171	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.2801	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.2283	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.2829	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.2640	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.2814	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.1925	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.3339	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.2843	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.2985	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.3097	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.2830	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.3077	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.2783	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.3052	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.3122	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.3158	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.2559	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.2627	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.2752	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.2764	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.2655	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.2839	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.2489	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.2811	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.3023	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.2677	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.2427	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.2613	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.2066	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.3036	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.2969	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.2280	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.3239	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.2820	LR: 0.004000
Epoch 20 - Average Train Loss: 0.2812, Train Accuracy: 0.8819
Epoch 20 training time consumed: 140.36s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0010, Accuracy: 0.8983, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.2638	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.2680	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.3026	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.2154	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.2844	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.2236	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.2638	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.2182	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.2508	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.2283	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.2057	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.3012	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.2105	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.2686	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.3145	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.2978	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.1955	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.2839	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.3285	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.3067	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.2436	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.2948	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.2548	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.2280	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.2854	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.2704	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.2187	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.1971	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1858	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.2638	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.2411	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.2244	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.2656	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.2604	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.2626	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.2413	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.2507	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.2704	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.1847	LR: 0.004000
Epoch 21 - Average Train Loss: 0.2548, Train Accuracy: 0.8957
Epoch 21 training time consumed: 142.21s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0012, Accuracy: 0.8910, Time consumed:8.12s
Training Epoch: 22 [256/9756]	Loss: 0.2688	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.2482	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.2414	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.3007	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.3022	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.1998	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.2664	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.2356	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.2179	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.2229	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.2015	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.2464	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.2664	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.2311	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.2019	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.2487	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.2387	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.2326	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.2475	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.1911	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.2794	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.2483	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.2967	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.2246	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.2284	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.2355	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.2511	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.2398	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.2415	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.2487	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.3254	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.2168	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.1935	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.2569	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.2218	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.2463	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.2317	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.2325	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.0655	LR: 0.004000
Epoch 22 - Average Train Loss: 0.2424, Train Accuracy: 0.8975
Epoch 22 training time consumed: 140.38s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0011, Accuracy: 0.9007, Time consumed:8.15s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-22-best.pth
Training Epoch: 23 [256/9756]	Loss: 0.2131	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.2491	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.2548	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.2371	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.2910	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.2164	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.1691	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.2204	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.2761	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.2488	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.2699	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.2039	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.2703	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.2555	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.1665	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.2300	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.2081	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.1965	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1887	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.2333	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1828	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.2088	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.2441	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.2135	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.2571	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.2687	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.1960	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.2312	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.2452	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.2249	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.3033	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1839	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.2804	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.2445	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.2972	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.2489	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.3129	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1734	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.2712	LR: 0.004000
Epoch 23 - Average Train Loss: 0.2347, Train Accuracy: 0.9025
Epoch 23 training time consumed: 140.75s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0009, Accuracy: 0.9075, Time consumed:7.80s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-23-best.pth
Training Epoch: 24 [256/9756]	Loss: 0.1877	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.2938	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1883	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.2510	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.2157	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.2154	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.2226	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.2543	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1843	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1975	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.2706	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.2369	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.2168	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.2202	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.2804	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.2357	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.2741	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.2405	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.2419	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.2626	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.1827	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.2103	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.2260	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.2256	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.2527	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.1709	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.2179	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.2259	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.2112	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.2430	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.2822	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.2543	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.2703	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.2068	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.2649	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.1902	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1774	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.2386	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.3071	LR: 0.004000
Epoch 24 - Average Train Loss: 0.2303, Train Accuracy: 0.9054
Epoch 24 training time consumed: 140.40s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0010, Accuracy: 0.9143, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-24-best.pth
Training Epoch: 25 [256/9756]	Loss: 0.2352	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.2573	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.1752	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.2022	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.2953	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1963	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.2310	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.2151	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.2613	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.2498	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1852	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.2203	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.3109	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1879	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.2442	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.1772	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.2487	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.2412	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.2200	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.2198	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.2458	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.2310	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1811	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.2317	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.2435	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.2067	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.2097	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1938	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.2745	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.2038	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1644	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.2263	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1970	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.2463	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1657	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1748	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.2101	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.2497	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.2611	LR: 0.004000
Epoch 25 - Average Train Loss: 0.2220, Train Accuracy: 0.9086
Epoch 25 training time consumed: 140.43s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0010, Accuracy: 0.8959, Time consumed:8.08s
Training Epoch: 26 [256/9756]	Loss: 0.2315	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.2079	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.2237	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.2169	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.1962	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.1999	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.2056	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.2856	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.1795	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.1941	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.2142	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.2323	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.2121	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.2066	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.2232	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.1746	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.2132	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.2044	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1733	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.2217	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.2145	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1905	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1930	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.2347	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.2168	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1862	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1959	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.2246	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.1843	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1956	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1519	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1837	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.2053	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.2694	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1921	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1823	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.2374	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.1083	LR: 0.004000
Epoch 26 - Average Train Loss: 0.2061, Train Accuracy: 0.9153
Epoch 26 training time consumed: 140.35s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0012, Accuracy: 0.8814, Time consumed:7.95s
Training Epoch: 27 [256/9756]	Loss: 0.1932	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.2516	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.2040	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.2326	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.2658	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.2312	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1856	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.2133	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.2454	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.1971	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1963	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.2198	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.2148	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.1947	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.2531	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.2828	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.2760	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.2484	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.2151	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1377	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.2021	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.2969	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.2221	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.2138	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1741	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.2367	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.2030	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.2276	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1818	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1918	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.2535	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1842	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1947	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.1835	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.2307	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.2766	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.2189	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.2838	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.1515	LR: 0.004000
Epoch 27 - Average Train Loss: 0.2218, Train Accuracy: 0.9080
Epoch 27 training time consumed: 140.07s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0010, Accuracy: 0.9090, Time consumed:8.20s
Training Epoch: 28 [256/9756]	Loss: 0.2297	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.1776	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.2912	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.2293	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.2347	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1924	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.2145	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1916	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.1757	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.2812	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.2038	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.2501	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1842	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.2094	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1675	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1975	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.2610	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1752	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.2269	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1158	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.2209	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.2012	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1754	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.2057	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1636	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1661	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1747	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.2534	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.1946	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.2677	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.2124	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.2223	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1634	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1596	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.2026	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1711	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.1396	LR: 0.004000
Epoch 28 - Average Train Loss: 0.2031, Train Accuracy: 0.9162
Epoch 28 training time consumed: 140.34s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9167, Time consumed:7.87s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-28-best.pth
Training Epoch: 29 [256/9756]	Loss: 0.2455	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1896	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1635	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.2271	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1712	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.2269	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.2050	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.1708	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.1974	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1828	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.2063	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.1860	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1919	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1684	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.2395	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1783	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1811	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.2157	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1992	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.1772	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.2207	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.1808	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.2412	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.2115	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.2045	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1803	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.1505	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.2443	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.1860	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.2100	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1738	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.2666	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1944	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.2180	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.2274	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.1904	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1967, Train Accuracy: 0.9196
Epoch 29 training time consumed: 140.28s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0008, Accuracy: 0.9240, Time consumed:7.91s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_00h_18m_20s/ResNet18-MUCAC-seed3-ret25-29-best.pth
Training Epoch: 30 [256/9756]	Loss: 0.1798	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.2306	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.2124	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1936	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1823	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1910	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.1716	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.2006	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1927	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.2262	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.2269	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.2092	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1846	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1995	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.1498	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.2165	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1778	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.1307	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.2104	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.1372	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1737	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.2145	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.2088	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.1988	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.2060	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.2076	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.2484	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1787	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.2230	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.2050	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1721	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1791	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.2279	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.2103	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.1846	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.1717	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1944, Train Accuracy: 0.9197
Epoch 30 training time consumed: 140.36s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0010, Accuracy: 0.9167, Time consumed:7.99s
Training Epoch: 31 [256/9756]	Loss: 0.2229	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1868	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.2158	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.2339	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1880	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.2029	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1741	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.2627	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.2137	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.2515	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.2398	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.2245	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.2893	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.1888	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.2177	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1947	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1664	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1771	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.1866	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.2149	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.1804	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.2276	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.2009	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1575	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.1836	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.1859	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1838	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1669	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1668	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1398	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.2229	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.1663	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.1632	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.1651	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.1416	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.5489	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1959, Train Accuracy: 0.9186
Epoch 31 training time consumed: 140.35s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0010, Accuracy: 0.9061, Time consumed:8.02s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  9756
Forget Train Dl:  792
Retain Valid Dl:  9756
Forget Valid Dl:  792
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 792 samples
Set2 Distribution: 792 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 90.3594741821289
Retain Accuracy: 88.0594711303711
Zero-Retain Forget (ZRF): 0.8712537884712219
Membership Inference Attack (MIA): 0.36742424242424243
Forget vs Retain Membership Inference Attack (MIA): 0.5299684542586751
Forget vs Test Membership Inference Attack (MIA): 0.5488958990536278
Test vs Retain Membership Inference Attack (MIA): 0.5363196125907991
Train vs Test Membership Inference Attack (MIA): 0.5169491525423728
Forget Set Accuracy (Df): 86.84895324707031
Method Execution Time: 5747.99 seconds
