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

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

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

📊 Updated class distribution:
Retain set:
  Class 0: 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: 0.7013	LR: 0.000000
Training Epoch: 1 [512/9756]	Loss: 0.6676	LR: 0.002564
Training Epoch: 1 [768/9756]	Loss: 0.6905	LR: 0.005128
Training Epoch: 1 [1024/9756]	Loss: 0.6951	LR: 0.007692
Training Epoch: 1 [1280/9756]	Loss: 0.7046	LR: 0.010256
Training Epoch: 1 [1536/9756]	Loss: 0.7134	LR: 0.012821
Training Epoch: 1 [1792/9756]	Loss: 0.6858	LR: 0.015385
Training Epoch: 1 [2048/9756]	Loss: 0.6929	LR: 0.017949
Training Epoch: 1 [2304/9756]	Loss: 0.6886	LR: 0.020513
Training Epoch: 1 [2560/9756]	Loss: 0.6692	LR: 0.023077
Training Epoch: 1 [2816/9756]	Loss: 0.6946	LR: 0.025641
Training Epoch: 1 [3072/9756]	Loss: 0.7449	LR: 0.028205
Training Epoch: 1 [3328/9756]	Loss: 0.8497	LR: 0.030769
Training Epoch: 1 [3584/9756]	Loss: 0.7827	LR: 0.033333
Training Epoch: 1 [3840/9756]	Loss: 0.9051	LR: 0.035897
Training Epoch: 1 [4096/9756]	Loss: 1.4404	LR: 0.038462
Training Epoch: 1 [4352/9756]	Loss: 1.9052	LR: 0.041026
Training Epoch: 1 [4608/9756]	Loss: 0.8232	LR: 0.043590
Training Epoch: 1 [4864/9756]	Loss: 2.7539	LR: 0.046154
Training Epoch: 1 [5120/9756]	Loss: 1.0722	LR: 0.048718
Training Epoch: 1 [5376/9756]	Loss: 1.7085	LR: 0.051282
Training Epoch: 1 [5632/9756]	Loss: 1.0978	LR: 0.053846
Training Epoch: 1 [5888/9756]	Loss: 0.8289	LR: 0.056410
Training Epoch: 1 [6144/9756]	Loss: 0.9045	LR: 0.058974
Training Epoch: 1 [6400/9756]	Loss: 0.9731	LR: 0.061538
Training Epoch: 1 [6656/9756]	Loss: 0.7296	LR: 0.064103
Training Epoch: 1 [6912/9756]	Loss: 0.8006	LR: 0.066667
Training Epoch: 1 [7168/9756]	Loss: 0.7342	LR: 0.069231
Training Epoch: 1 [7424/9756]	Loss: 0.8278	LR: 0.071795
Training Epoch: 1 [7680/9756]	Loss: 0.7563	LR: 0.074359
Training Epoch: 1 [7936/9756]	Loss: 0.7034	LR: 0.076923
Training Epoch: 1 [8192/9756]	Loss: 0.8460	LR: 0.079487
Training Epoch: 1 [8448/9756]	Loss: 0.7713	LR: 0.082051
Training Epoch: 1 [8704/9756]	Loss: 0.7485	LR: 0.084615
Training Epoch: 1 [8960/9756]	Loss: 0.8288	LR: 0.087179
Training Epoch: 1 [9216/9756]	Loss: 0.6958	LR: 0.089744
Training Epoch: 1 [9472/9756]	Loss: 0.8386	LR: 0.092308
Training Epoch: 1 [9728/9756]	Loss: 0.7169	LR: 0.094872
Training Epoch: 1 [9756/9756]	Loss: 0.8210	LR: 0.097436
Epoch 1 - Average Train Loss: 0.9048, Train Accuracy: 0.5232
Epoch 1 training time consumed: 326.51s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.0068, Accuracy: 0.5550, Time consumed:8.26s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-1-best.pth
Training Epoch: 2 [256/9756]	Loss: 0.6721	LR: 0.100000
Training Epoch: 2 [512/9756]	Loss: 0.6884	LR: 0.100000
Training Epoch: 2 [768/9756]	Loss: 0.7564	LR: 0.100000
Training Epoch: 2 [1024/9756]	Loss: 0.7002	LR: 0.100000
Training Epoch: 2 [1280/9756]	Loss: 0.8126	LR: 0.100000
Training Epoch: 2 [1536/9756]	Loss: 0.7544	LR: 0.100000
Training Epoch: 2 [1792/9756]	Loss: 0.7861	LR: 0.100000
Training Epoch: 2 [2048/9756]	Loss: 0.8280	LR: 0.100000
Training Epoch: 2 [2304/9756]	Loss: 0.8481	LR: 0.100000
Training Epoch: 2 [2560/9756]	Loss: 0.7178	LR: 0.100000
Training Epoch: 2 [2816/9756]	Loss: 0.7477	LR: 0.100000
Training Epoch: 2 [3072/9756]	Loss: 0.7588	LR: 0.100000
Training Epoch: 2 [3328/9756]	Loss: 0.9042	LR: 0.100000
Training Epoch: 2 [3584/9756]	Loss: 0.8423	LR: 0.100000
Training Epoch: 2 [3840/9756]	Loss: 0.8217	LR: 0.100000
Training Epoch: 2 [4096/9756]	Loss: 0.7307	LR: 0.100000
Training Epoch: 2 [4352/9756]	Loss: 0.7279	LR: 0.100000
Training Epoch: 2 [4608/9756]	Loss: 0.9602	LR: 0.100000
Training Epoch: 2 [4864/9756]	Loss: 0.7604	LR: 0.100000
Training Epoch: 2 [5120/9756]	Loss: 0.8458	LR: 0.100000
Training Epoch: 2 [5376/9756]	Loss: 0.7414	LR: 0.100000
Training Epoch: 2 [5632/9756]	Loss: 0.8163	LR: 0.100000
Training Epoch: 2 [5888/9756]	Loss: 0.7791	LR: 0.100000
Training Epoch: 2 [6144/9756]	Loss: 0.7065	LR: 0.100000
Training Epoch: 2 [6400/9756]	Loss: 0.8172	LR: 0.100000
Training Epoch: 2 [6656/9756]	Loss: 0.9442	LR: 0.100000
Training Epoch: 2 [6912/9756]	Loss: 0.7195	LR: 0.100000
Training Epoch: 2 [7168/9756]	Loss: 0.7586	LR: 0.100000
Training Epoch: 2 [7424/9756]	Loss: 0.8856	LR: 0.100000
Training Epoch: 2 [7680/9756]	Loss: 0.7570	LR: 0.100000
Training Epoch: 2 [7936/9756]	Loss: 0.6866	LR: 0.100000
Training Epoch: 2 [8192/9756]	Loss: 0.7618	LR: 0.100000
Training Epoch: 2 [8448/9756]	Loss: 0.7622	LR: 0.100000
Training Epoch: 2 [8704/9756]	Loss: 0.6951	LR: 0.100000
Training Epoch: 2 [8960/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 2 [9216/9756]	Loss: 0.7218	LR: 0.100000
Training Epoch: 2 [9472/9756]	Loss: 0.6987	LR: 0.100000
Training Epoch: 2 [9728/9756]	Loss: 0.6995	LR: 0.100000
Training Epoch: 2 [9756/9756]	Loss: 0.9878	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7714, Train Accuracy: 0.5244
Epoch 2 training time consumed: 141.01s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0038, Accuracy: 0.5550, Time consumed:7.87s
Training Epoch: 3 [256/9756]	Loss: 0.8097	LR: 0.100000
Training Epoch: 3 [512/9756]	Loss: 1.0294	LR: 0.100000
Training Epoch: 3 [768/9756]	Loss: 0.9107	LR: 0.100000
Training Epoch: 3 [1024/9756]	Loss: 0.8905	LR: 0.100000
Training Epoch: 3 [1280/9756]	Loss: 0.7022	LR: 0.100000
Training Epoch: 3 [1536/9756]	Loss: 0.9436	LR: 0.100000
Training Epoch: 3 [1792/9756]	Loss: 0.8905	LR: 0.100000
Training Epoch: 3 [2048/9756]	Loss: 0.7716	LR: 0.100000
Training Epoch: 3 [2304/9756]	Loss: 0.6630	LR: 0.100000
Training Epoch: 3 [2560/9756]	Loss: 0.7031	LR: 0.100000
Training Epoch: 3 [2816/9756]	Loss: 0.7187	LR: 0.100000
Training Epoch: 3 [3072/9756]	Loss: 0.6844	LR: 0.100000
Training Epoch: 3 [3328/9756]	Loss: 0.6900	LR: 0.100000
Training Epoch: 3 [3584/9756]	Loss: 0.6962	LR: 0.100000
Training Epoch: 3 [3840/9756]	Loss: 0.7400	LR: 0.100000
Training Epoch: 3 [4096/9756]	Loss: 0.7053	LR: 0.100000
Training Epoch: 3 [4352/9756]	Loss: 0.7008	LR: 0.100000
Training Epoch: 3 [4608/9756]	Loss: 0.6836	LR: 0.100000
Training Epoch: 3 [4864/9756]	Loss: 0.7038	LR: 0.100000
Training Epoch: 3 [5120/9756]	Loss: 0.6803	LR: 0.100000
Training Epoch: 3 [5376/9756]	Loss: 0.6916	LR: 0.100000
Training Epoch: 3 [5632/9756]	Loss: 0.6868	LR: 0.100000
Training Epoch: 3 [5888/9756]	Loss: 0.6810	LR: 0.100000
Training Epoch: 3 [6144/9756]	Loss: 0.6877	LR: 0.100000
Training Epoch: 3 [6400/9756]	Loss: 0.6706	LR: 0.100000
Training Epoch: 3 [6656/9756]	Loss: 0.6645	LR: 0.100000
Training Epoch: 3 [6912/9756]	Loss: 0.6906	LR: 0.100000
Training Epoch: 3 [7168/9756]	Loss: 0.6648	LR: 0.100000
Training Epoch: 3 [7424/9756]	Loss: 0.6659	LR: 0.100000
Training Epoch: 3 [7680/9756]	Loss: 0.6871	LR: 0.100000
Training Epoch: 3 [7936/9756]	Loss: 0.6808	LR: 0.100000
Training Epoch: 3 [8192/9756]	Loss: 0.6979	LR: 0.100000
Training Epoch: 3 [8448/9756]	Loss: 0.6841	LR: 0.100000
Training Epoch: 3 [8704/9756]	Loss: 0.6875	LR: 0.100000
Training Epoch: 3 [8960/9756]	Loss: 0.7017	LR: 0.100000
Training Epoch: 3 [9216/9756]	Loss: 0.6849	LR: 0.100000
Training Epoch: 3 [9472/9756]	Loss: 0.6869	LR: 0.100000
Training Epoch: 3 [9728/9756]	Loss: 0.6692	LR: 0.100000
Training Epoch: 3 [9756/9756]	Loss: 0.6835	LR: 0.100000
Epoch 3 - Average Train Loss: 0.7262, Train Accuracy: 0.5441
Epoch 3 training time consumed: 141.04s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5366, Time consumed:7.84s
Training Epoch: 4 [256/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [512/9756]	Loss: 0.6656	LR: 0.100000
Training Epoch: 4 [768/9756]	Loss: 0.6932	LR: 0.100000
Training Epoch: 4 [1024/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [1280/9756]	Loss: 0.6683	LR: 0.100000
Training Epoch: 4 [1536/9756]	Loss: 0.6708	LR: 0.100000
Training Epoch: 4 [1792/9756]	Loss: 0.6739	LR: 0.100000
Training Epoch: 4 [2048/9756]	Loss: 0.6713	LR: 0.100000
Training Epoch: 4 [2304/9756]	Loss: 0.6679	LR: 0.100000
Training Epoch: 4 [2560/9756]	Loss: 0.6655	LR: 0.100000
Training Epoch: 4 [2816/9756]	Loss: 0.6740	LR: 0.100000
Training Epoch: 4 [3072/9756]	Loss: 0.6674	LR: 0.100000
Training Epoch: 4 [3328/9756]	Loss: 0.7192	LR: 0.100000
Training Epoch: 4 [3584/9756]	Loss: 0.6880	LR: 0.100000
Training Epoch: 4 [3840/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 4 [4096/9756]	Loss: 0.7005	LR: 0.100000
Training Epoch: 4 [4352/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 4 [4608/9756]	Loss: 0.6773	LR: 0.100000
Training Epoch: 4 [4864/9756]	Loss: 0.6798	LR: 0.100000
Training Epoch: 4 [5120/9756]	Loss: 0.6715	LR: 0.100000
Training Epoch: 4 [5376/9756]	Loss: 0.7091	LR: 0.100000
Training Epoch: 4 [5632/9756]	Loss: 0.6976	LR: 0.100000
Training Epoch: 4 [5888/9756]	Loss: 0.7027	LR: 0.100000
Training Epoch: 4 [6144/9756]	Loss: 0.6638	LR: 0.100000
Training Epoch: 4 [6400/9756]	Loss: 0.6969	LR: 0.100000
Training Epoch: 4 [6656/9756]	Loss: 0.6859	LR: 0.100000
Training Epoch: 4 [6912/9756]	Loss: 0.6998	LR: 0.100000
Training Epoch: 4 [7168/9756]	Loss: 0.7497	LR: 0.100000
Training Epoch: 4 [7424/9756]	Loss: 0.6704	LR: 0.100000
Training Epoch: 4 [7680/9756]	Loss: 0.6838	LR: 0.100000
Training Epoch: 4 [7936/9756]	Loss: 0.6823	LR: 0.100000
Training Epoch: 4 [8192/9756]	Loss: 0.7419	LR: 0.100000
Training Epoch: 4 [8448/9756]	Loss: 0.7517	LR: 0.100000
Training Epoch: 4 [8704/9756]	Loss: 0.6744	LR: 0.100000
Training Epoch: 4 [8960/9756]	Loss: 0.7242	LR: 0.100000
Training Epoch: 4 [9216/9756]	Loss: 0.7699	LR: 0.100000
Training Epoch: 4 [9472/9756]	Loss: 0.7422	LR: 0.100000
Training Epoch: 4 [9728/9756]	Loss: 0.6801	LR: 0.100000
Training Epoch: 4 [9756/9756]	Loss: 0.6422	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6922, Train Accuracy: 0.5767
Epoch 4 training time consumed: 140.94s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0029, Accuracy: 0.5768, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-4-best.pth
Training Epoch: 5 [256/9756]	Loss: 0.7367	LR: 0.100000
Training Epoch: 5 [512/9756]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [768/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [1024/9756]	Loss: 0.6748	LR: 0.100000
Training Epoch: 5 [1280/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 5 [1536/9756]	Loss: 0.6722	LR: 0.100000
Training Epoch: 5 [1792/9756]	Loss: 0.6616	LR: 0.100000
Training Epoch: 5 [2048/9756]	Loss: 0.6993	LR: 0.100000
Training Epoch: 5 [2304/9756]	Loss: 0.6714	LR: 0.100000
Training Epoch: 5 [2560/9756]	Loss: 0.7197	LR: 0.100000
Training Epoch: 5 [2816/9756]	Loss: 0.6775	LR: 0.100000
Training Epoch: 5 [3072/9756]	Loss: 0.6850	LR: 0.100000
Training Epoch: 5 [3328/9756]	Loss: 0.6772	LR: 0.100000
Training Epoch: 5 [3584/9756]	Loss: 0.6757	LR: 0.100000
Training Epoch: 5 [3840/9756]	Loss: 0.6767	LR: 0.100000
Training Epoch: 5 [4096/9756]	Loss: 0.6660	LR: 0.100000
Training Epoch: 5 [4352/9756]	Loss: 0.6716	LR: 0.100000
Training Epoch: 5 [4608/9756]	Loss: 0.6657	LR: 0.100000
Training Epoch: 5 [4864/9756]	Loss: 0.6614	LR: 0.100000
Training Epoch: 5 [5120/9756]	Loss: 0.6840	LR: 0.100000
Training Epoch: 5 [5376/9756]	Loss: 0.7093	LR: 0.100000
Training Epoch: 5 [5632/9756]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [5888/9756]	Loss: 0.6668	LR: 0.100000
Training Epoch: 5 [6144/9756]	Loss: 0.6625	LR: 0.100000
Training Epoch: 5 [6400/9756]	Loss: 0.6950	LR: 0.100000
Training Epoch: 5 [6656/9756]	Loss: 0.6677	LR: 0.100000
Training Epoch: 5 [6912/9756]	Loss: 0.6702	LR: 0.100000
Training Epoch: 5 [7168/9756]	Loss: 0.6734	LR: 0.100000
Training Epoch: 5 [7424/9756]	Loss: 0.6601	LR: 0.100000
Training Epoch: 5 [7680/9756]	Loss: 0.6693	LR: 0.100000
Training Epoch: 5 [7936/9756]	Loss: 0.6837	LR: 0.100000
Training Epoch: 5 [8192/9756]	Loss: 0.6859	LR: 0.100000
Training Epoch: 5 [8448/9756]	Loss: 0.6752	LR: 0.100000
Training Epoch: 5 [8704/9756]	Loss: 0.6974	LR: 0.100000
Training Epoch: 5 [8960/9756]	Loss: 0.6784	LR: 0.100000
Training Epoch: 5 [9216/9756]	Loss: 0.6772	LR: 0.100000
Training Epoch: 5 [9472/9756]	Loss: 0.6731	LR: 0.100000
Training Epoch: 5 [9728/9756]	Loss: 0.6680	LR: 0.100000
Training Epoch: 5 [9756/9756]	Loss: 0.6798	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6782, Train Accuracy: 0.5809
Epoch 5 training time consumed: 141.38s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0030, Accuracy: 0.5806, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-5-best.pth
Training Epoch: 6 [256/9756]	Loss: 0.6729	LR: 0.100000
Training Epoch: 6 [512/9756]	Loss: 0.6889	LR: 0.100000
Training Epoch: 6 [768/9756]	Loss: 0.7016	LR: 0.100000
Training Epoch: 6 [1024/9756]	Loss: 0.6777	LR: 0.100000
Training Epoch: 6 [1280/9756]	Loss: 0.6873	LR: 0.100000
Training Epoch: 6 [1536/9756]	Loss: 0.6919	LR: 0.100000
Training Epoch: 6 [1792/9756]	Loss: 0.6690	LR: 0.100000
Training Epoch: 6 [2048/9756]	Loss: 0.6600	LR: 0.100000
Training Epoch: 6 [2304/9756]	Loss: 0.6701	LR: 0.100000
Training Epoch: 6 [2560/9756]	Loss: 0.6715	LR: 0.100000
Training Epoch: 6 [2816/9756]	Loss: 0.6865	LR: 0.100000
Training Epoch: 6 [3072/9756]	Loss: 0.6730	LR: 0.100000
Training Epoch: 6 [3328/9756]	Loss: 0.6657	LR: 0.100000
Training Epoch: 6 [3584/9756]	Loss: 0.6680	LR: 0.100000
Training Epoch: 6 [3840/9756]	Loss: 0.7072	LR: 0.100000
Training Epoch: 6 [4096/9756]	Loss: 0.6718	LR: 0.100000
Training Epoch: 6 [4352/9756]	Loss: 0.6501	LR: 0.100000
Training Epoch: 6 [4608/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 6 [4864/9756]	Loss: 0.6495	LR: 0.100000
Training Epoch: 6 [5120/9756]	Loss: 0.6479	LR: 0.100000
Training Epoch: 6 [5376/9756]	Loss: 0.7283	LR: 0.100000
Training Epoch: 6 [5632/9756]	Loss: 0.7179	LR: 0.100000
Training Epoch: 6 [5888/9756]	Loss: 0.6859	LR: 0.100000
Training Epoch: 6 [6144/9756]	Loss: 0.7002	LR: 0.100000
Training Epoch: 6 [6400/9756]	Loss: 0.7010	LR: 0.100000
Training Epoch: 6 [6656/9756]	Loss: 0.7361	LR: 0.100000
Training Epoch: 6 [6912/9756]	Loss: 0.6467	LR: 0.100000
Training Epoch: 6 [7168/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 6 [7424/9756]	Loss: 0.6985	LR: 0.100000
Training Epoch: 6 [7680/9756]	Loss: 0.6879	LR: 0.100000
Training Epoch: 6 [7936/9756]	Loss: 0.6754	LR: 0.100000
Training Epoch: 6 [8192/9756]	Loss: 0.6846	LR: 0.100000
Training Epoch: 6 [8448/9756]	Loss: 0.6776	LR: 0.100000
Training Epoch: 6 [8704/9756]	Loss: 0.6551	LR: 0.100000
Training Epoch: 6 [8960/9756]	Loss: 0.6717	LR: 0.100000
Training Epoch: 6 [9216/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 6 [9472/9756]	Loss: 0.6855	LR: 0.100000
Training Epoch: 6 [9728/9756]	Loss: 0.7065	LR: 0.100000
Training Epoch: 6 [9756/9756]	Loss: 0.6816	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6804, Train Accuracy: 0.5888
Epoch 6 training time consumed: 141.40s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0033, Accuracy: 0.5554, Time consumed:7.86s
Training Epoch: 7 [256/9756]	Loss: 0.7121	LR: 0.100000
Training Epoch: 7 [512/9756]	Loss: 0.6620	LR: 0.100000
Training Epoch: 7 [768/9756]	Loss: 0.6704	LR: 0.100000
Training Epoch: 7 [1024/9756]	Loss: 0.6806	LR: 0.100000
Training Epoch: 7 [1280/9756]	Loss: 0.6927	LR: 0.100000
Training Epoch: 7 [1536/9756]	Loss: 0.6763	LR: 0.100000
Training Epoch: 7 [1792/9756]	Loss: 0.6776	LR: 0.100000
Training Epoch: 7 [2048/9756]	Loss: 0.6726	LR: 0.100000
Training Epoch: 7 [2304/9756]	Loss: 0.6882	LR: 0.100000
Training Epoch: 7 [2560/9756]	Loss: 0.7081	LR: 0.100000
Training Epoch: 7 [2816/9756]	Loss: 0.6751	LR: 0.100000
Training Epoch: 7 [3072/9756]	Loss: 0.6975	LR: 0.100000
Training Epoch: 7 [3328/9756]	Loss: 0.6823	LR: 0.100000
Training Epoch: 7 [3584/9756]	Loss: 0.6886	LR: 0.100000
Training Epoch: 7 [3840/9756]	Loss: 0.7204	LR: 0.100000
Training Epoch: 7 [4096/9756]	Loss: 0.7059	LR: 0.100000
Training Epoch: 7 [4352/9756]	Loss: 0.6679	LR: 0.100000
Training Epoch: 7 [4608/9756]	Loss: 0.6937	LR: 0.100000
Training Epoch: 7 [4864/9756]	Loss: 0.6453	LR: 0.100000
Training Epoch: 7 [5120/9756]	Loss: 0.6526	LR: 0.100000
Training Epoch: 7 [5376/9756]	Loss: 0.6611	LR: 0.100000
Training Epoch: 7 [5632/9756]	Loss: 0.6914	LR: 0.100000
Training Epoch: 7 [5888/9756]	Loss: 0.6415	LR: 0.100000
Training Epoch: 7 [6144/9756]	Loss: 0.6547	LR: 0.100000
Training Epoch: 7 [6400/9756]	Loss: 0.6601	LR: 0.100000
Training Epoch: 7 [6656/9756]	Loss: 0.6510	LR: 0.100000
Training Epoch: 7 [6912/9756]	Loss: 0.6647	LR: 0.100000
Training Epoch: 7 [7168/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 7 [7424/9756]	Loss: 0.6449	LR: 0.100000
Training Epoch: 7 [7680/9756]	Loss: 0.6607	LR: 0.100000
Training Epoch: 7 [7936/9756]	Loss: 0.6740	LR: 0.100000
Training Epoch: 7 [8192/9756]	Loss: 0.6787	LR: 0.100000
Training Epoch: 7 [8448/9756]	Loss: 0.6710	LR: 0.100000
Training Epoch: 7 [8704/9756]	Loss: 0.6645	LR: 0.100000
Training Epoch: 7 [8960/9756]	Loss: 0.6596	LR: 0.100000
Training Epoch: 7 [9216/9756]	Loss: 0.6587	LR: 0.100000
Training Epoch: 7 [9472/9756]	Loss: 0.6809	LR: 0.100000
Training Epoch: 7 [9728/9756]	Loss: 0.6753	LR: 0.100000
Training Epoch: 7 [9756/9756]	Loss: 0.7590	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6749, Train Accuracy: 0.5884
Epoch 7 training time consumed: 141.34s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0033, Accuracy: 0.5153, Time consumed:7.95s
Training Epoch: 8 [256/9756]	Loss: 0.6303	LR: 0.100000
Training Epoch: 8 [512/9756]	Loss: 0.6560	LR: 0.100000
Training Epoch: 8 [768/9756]	Loss: 0.6805	LR: 0.100000
Training Epoch: 8 [1024/9756]	Loss: 0.7244	LR: 0.100000
Training Epoch: 8 [1280/9756]	Loss: 0.7109	LR: 0.100000
Training Epoch: 8 [1536/9756]	Loss: 0.6404	LR: 0.100000
Training Epoch: 8 [1792/9756]	Loss: 0.6992	LR: 0.100000
Training Epoch: 8 [2048/9756]	Loss: 0.6660	LR: 0.100000
Training Epoch: 8 [2304/9756]	Loss: 0.6821	LR: 0.100000
Training Epoch: 8 [2560/9756]	Loss: 0.7012	LR: 0.100000
Training Epoch: 8 [2816/9756]	Loss: 0.6698	LR: 0.100000
Training Epoch: 8 [3072/9756]	Loss: 0.6640	LR: 0.100000
Training Epoch: 8 [3328/9756]	Loss: 0.6931	LR: 0.100000
Training Epoch: 8 [3584/9756]	Loss: 0.6717	LR: 0.100000
Training Epoch: 8 [3840/9756]	Loss: 0.6752	LR: 0.100000
Training Epoch: 8 [4096/9756]	Loss: 0.6752	LR: 0.100000
Training Epoch: 8 [4352/9756]	Loss: 0.7826	LR: 0.100000
Training Epoch: 8 [4608/9756]	Loss: 0.6570	LR: 0.100000
Training Epoch: 8 [4864/9756]	Loss: 0.7191	LR: 0.100000
Training Epoch: 8 [5120/9756]	Loss: 0.6788	LR: 0.100000
Training Epoch: 8 [5376/9756]	Loss: 0.6595	LR: 0.100000
Training Epoch: 8 [5632/9756]	Loss: 0.6929	LR: 0.100000
Training Epoch: 8 [5888/9756]	Loss: 0.6985	LR: 0.100000
Training Epoch: 8 [6144/9756]	Loss: 0.6749	LR: 0.100000
Training Epoch: 8 [6400/9756]	Loss: 0.6644	LR: 0.100000
Training Epoch: 8 [6656/9756]	Loss: 0.6621	LR: 0.100000
Training Epoch: 8 [6912/9756]	Loss: 0.6552	LR: 0.100000
Training Epoch: 8 [7168/9756]	Loss: 0.6679	LR: 0.100000
Training Epoch: 8 [7424/9756]	Loss: 0.6471	LR: 0.100000
Training Epoch: 8 [7680/9756]	Loss: 0.6617	LR: 0.100000
Training Epoch: 8 [7936/9756]	Loss: 0.6580	LR: 0.100000
Training Epoch: 8 [8192/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 8 [8448/9756]	Loss: 0.6141	LR: 0.100000
Training Epoch: 8 [8704/9756]	Loss: 0.6617	LR: 0.100000
Training Epoch: 8 [8960/9756]	Loss: 0.6444	LR: 0.100000
Training Epoch: 8 [9216/9756]	Loss: 0.6569	LR: 0.100000
Training Epoch: 8 [9472/9756]	Loss: 0.6540	LR: 0.100000
Training Epoch: 8 [9728/9756]	Loss: 0.6847	LR: 0.100000
Training Epoch: 8 [9756/9756]	Loss: 0.5506	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6736, Train Accuracy: 0.5915
Epoch 8 training time consumed: 141.19s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0032, Accuracy: 0.5545, Time consumed:8.07s
Training Epoch: 9 [256/9756]	Loss: 0.6299	LR: 0.100000
Training Epoch: 9 [512/9756]	Loss: 0.7472	LR: 0.100000
Training Epoch: 9 [768/9756]	Loss: 0.6486	LR: 0.100000
Training Epoch: 9 [1024/9756]	Loss: 0.6639	LR: 0.100000
Training Epoch: 9 [1280/9756]	Loss: 0.6399	LR: 0.100000
Training Epoch: 9 [1536/9756]	Loss: 0.6900	LR: 0.100000
Training Epoch: 9 [1792/9756]	Loss: 0.6912	LR: 0.100000
Training Epoch: 9 [2048/9756]	Loss: 0.6541	LR: 0.100000
Training Epoch: 9 [2304/9756]	Loss: 0.6641	LR: 0.100000
Training Epoch: 9 [2560/9756]	Loss: 0.6401	LR: 0.100000
Training Epoch: 9 [2816/9756]	Loss: 0.6531	LR: 0.100000
Training Epoch: 9 [3072/9756]	Loss: 0.6428	LR: 0.100000
Training Epoch: 9 [3328/9756]	Loss: 0.6632	LR: 0.100000
Training Epoch: 9 [3584/9756]	Loss: 0.6186	LR: 0.100000
Training Epoch: 9 [3840/9756]	Loss: 0.5974	LR: 0.100000
Training Epoch: 9 [4096/9756]	Loss: 0.6597	LR: 0.100000
Training Epoch: 9 [4352/9756]	Loss: 0.6507	LR: 0.100000
Training Epoch: 9 [4608/9756]	Loss: 0.6385	LR: 0.100000
Training Epoch: 9 [4864/9756]	Loss: 0.6735	LR: 0.100000
Training Epoch: 9 [5120/9756]	Loss: 0.6489	LR: 0.100000
Training Epoch: 9 [5376/9756]	Loss: 0.6490	LR: 0.100000
Training Epoch: 9 [5632/9756]	Loss: 0.6525	LR: 0.100000
Training Epoch: 9 [5888/9756]	Loss: 0.5925	LR: 0.100000
Training Epoch: 9 [6144/9756]	Loss: 0.6240	LR: 0.100000
Training Epoch: 9 [6400/9756]	Loss: 0.6576	LR: 0.100000
Training Epoch: 9 [6656/9756]	Loss: 0.6387	LR: 0.100000
Training Epoch: 9 [6912/9756]	Loss: 0.5911	LR: 0.100000
Training Epoch: 9 [7168/9756]	Loss: 0.5955	LR: 0.100000
Training Epoch: 9 [7424/9756]	Loss: 0.6207	LR: 0.100000
Training Epoch: 9 [7680/9756]	Loss: 0.6396	LR: 0.100000
Training Epoch: 9 [7936/9756]	Loss: 0.6210	LR: 0.100000
Training Epoch: 9 [8192/9756]	Loss: 0.6486	LR: 0.100000
Training Epoch: 9 [8448/9756]	Loss: 0.6246	LR: 0.100000
Training Epoch: 9 [8704/9756]	Loss: 0.6594	LR: 0.100000
Training Epoch: 9 [8960/9756]	Loss: 0.6308	LR: 0.100000
Training Epoch: 9 [9216/9756]	Loss: 0.6370	LR: 0.100000
Training Epoch: 9 [9472/9756]	Loss: 0.6317	LR: 0.100000
Training Epoch: 9 [9728/9756]	Loss: 0.5996	LR: 0.100000
Training Epoch: 9 [9756/9756]	Loss: 0.6847	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6430, Train Accuracy: 0.6355
Epoch 9 training time consumed: 141.14s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0032, Accuracy: 0.5884, Time consumed:8.28s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-9-best.pth
Training Epoch: 10 [256/9756]	Loss: 0.6448	LR: 0.020000
Training Epoch: 10 [512/9756]	Loss: 0.6529	LR: 0.020000
Training Epoch: 10 [768/9756]	Loss: 0.6340	LR: 0.020000
Training Epoch: 10 [1024/9756]	Loss: 0.6589	LR: 0.020000
Training Epoch: 10 [1280/9756]	Loss: 0.6200	LR: 0.020000
Training Epoch: 10 [1536/9756]	Loss: 0.6293	LR: 0.020000
Training Epoch: 10 [1792/9756]	Loss: 0.6264	LR: 0.020000
Training Epoch: 10 [2048/9756]	Loss: 0.5873	LR: 0.020000
Training Epoch: 10 [2304/9756]	Loss: 0.6370	LR: 0.020000
Training Epoch: 10 [2560/9756]	Loss: 0.5953	LR: 0.020000
Training Epoch: 10 [2816/9756]	Loss: 0.6086	LR: 0.020000
Training Epoch: 10 [3072/9756]	Loss: 0.6216	LR: 0.020000
Training Epoch: 10 [3328/9756]	Loss: 0.5958	LR: 0.020000
Training Epoch: 10 [3584/9756]	Loss: 0.5769	LR: 0.020000
Training Epoch: 10 [3840/9756]	Loss: 0.6439	LR: 0.020000
Training Epoch: 10 [4096/9756]	Loss: 0.6088	LR: 0.020000
Training Epoch: 10 [4352/9756]	Loss: 0.6095	LR: 0.020000
Training Epoch: 10 [4608/9756]	Loss: 0.6034	LR: 0.020000
Training Epoch: 10 [4864/9756]	Loss: 0.5990	LR: 0.020000
Training Epoch: 10 [5120/9756]	Loss: 0.6033	LR: 0.020000
Training Epoch: 10 [5376/9756]	Loss: 0.6195	LR: 0.020000
Training Epoch: 10 [5632/9756]	Loss: 0.5671	LR: 0.020000
Training Epoch: 10 [5888/9756]	Loss: 0.6167	LR: 0.020000
Training Epoch: 10 [6144/9756]	Loss: 0.6044	LR: 0.020000
Training Epoch: 10 [6400/9756]	Loss: 0.5749	LR: 0.020000
Training Epoch: 10 [6656/9756]	Loss: 0.5948	LR: 0.020000
Training Epoch: 10 [6912/9756]	Loss: 0.5778	LR: 0.020000
Training Epoch: 10 [7168/9756]	Loss: 0.6049	LR: 0.020000
Training Epoch: 10 [7424/9756]	Loss: 0.5971	LR: 0.020000
Training Epoch: 10 [7680/9756]	Loss: 0.6329	LR: 0.020000
Training Epoch: 10 [7936/9756]	Loss: 0.5699	LR: 0.020000
Training Epoch: 10 [8192/9756]	Loss: 0.6241	LR: 0.020000
Training Epoch: 10 [8448/9756]	Loss: 0.5898	LR: 0.020000
Training Epoch: 10 [8704/9756]	Loss: 0.5581	LR: 0.020000
Training Epoch: 10 [8960/9756]	Loss: 0.5830	LR: 0.020000
Training Epoch: 10 [9216/9756]	Loss: 0.5996	LR: 0.020000
Training Epoch: 10 [9472/9756]	Loss: 0.5781	LR: 0.020000
Training Epoch: 10 [9728/9756]	Loss: 0.6061	LR: 0.020000
Training Epoch: 10 [9756/9756]	Loss: 0.5815	LR: 0.020000
Epoch 10 - Average Train Loss: 0.6067, Train Accuracy: 0.6768
Epoch 10 training time consumed: 141.51s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0026, Accuracy: 0.6872, Time consumed:7.84s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-10-best.pth
Training Epoch: 11 [256/9756]	Loss: 0.6127	LR: 0.020000
Training Epoch: 11 [512/9756]	Loss: 0.6345	LR: 0.020000
Training Epoch: 11 [768/9756]	Loss: 0.5660	LR: 0.020000
Training Epoch: 11 [1024/9756]	Loss: 0.6332	LR: 0.020000
Training Epoch: 11 [1280/9756]	Loss: 0.6230	LR: 0.020000
Training Epoch: 11 [1536/9756]	Loss: 0.6076	LR: 0.020000
Training Epoch: 11 [1792/9756]	Loss: 0.6188	LR: 0.020000
Training Epoch: 11 [2048/9756]	Loss: 0.5762	LR: 0.020000
Training Epoch: 11 [2304/9756]	Loss: 0.5771	LR: 0.020000
Training Epoch: 11 [2560/9756]	Loss: 0.5930	LR: 0.020000
Training Epoch: 11 [2816/9756]	Loss: 0.5917	LR: 0.020000
Training Epoch: 11 [3072/9756]	Loss: 0.5267	LR: 0.020000
Training Epoch: 11 [3328/9756]	Loss: 0.5685	LR: 0.020000
Training Epoch: 11 [3584/9756]	Loss: 0.6113	LR: 0.020000
Training Epoch: 11 [3840/9756]	Loss: 0.5662	LR: 0.020000
Training Epoch: 11 [4096/9756]	Loss: 0.5699	LR: 0.020000
Training Epoch: 11 [4352/9756]	Loss: 0.5534	LR: 0.020000
Training Epoch: 11 [4608/9756]	Loss: 0.6051	LR: 0.020000
Training Epoch: 11 [4864/9756]	Loss: 0.5457	LR: 0.020000
Training Epoch: 11 [5120/9756]	Loss: 0.5438	LR: 0.020000
Training Epoch: 11 [5376/9756]	Loss: 0.5565	LR: 0.020000
Training Epoch: 11 [5632/9756]	Loss: 0.5833	LR: 0.020000
Training Epoch: 11 [5888/9756]	Loss: 0.5498	LR: 0.020000
Training Epoch: 11 [6144/9756]	Loss: 0.5007	LR: 0.020000
Training Epoch: 11 [6400/9756]	Loss: 0.6024	LR: 0.020000
Training Epoch: 11 [6656/9756]	Loss: 0.5805	LR: 0.020000
Training Epoch: 11 [6912/9756]	Loss: 0.5853	LR: 0.020000
Training Epoch: 11 [7168/9756]	Loss: 0.5513	LR: 0.020000
Training Epoch: 11 [7424/9756]	Loss: 0.6141	LR: 0.020000
Training Epoch: 11 [7680/9756]	Loss: 0.5822	LR: 0.020000
Training Epoch: 11 [7936/9756]	Loss: 0.5606	LR: 0.020000
Training Epoch: 11 [8192/9756]	Loss: 0.5960	LR: 0.020000
Training Epoch: 11 [8448/9756]	Loss: 0.5557	LR: 0.020000
Training Epoch: 11 [8704/9756]	Loss: 0.5477	LR: 0.020000
Training Epoch: 11 [8960/9756]	Loss: 0.5770	LR: 0.020000
Training Epoch: 11 [9216/9756]	Loss: 0.5465	LR: 0.020000
Training Epoch: 11 [9472/9756]	Loss: 0.5962	LR: 0.020000
Training Epoch: 11 [9728/9756]	Loss: 0.5992	LR: 0.020000
Training Epoch: 11 [9756/9756]	Loss: 0.5680	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5792, Train Accuracy: 0.6958
Epoch 11 training time consumed: 141.39s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0025, Accuracy: 0.7196, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-11-best.pth
Training Epoch: 12 [256/9756]	Loss: 0.5663	LR: 0.020000
Training Epoch: 12 [512/9756]	Loss: 0.5421	LR: 0.020000
Training Epoch: 12 [768/9756]	Loss: 0.5352	LR: 0.020000
Training Epoch: 12 [1024/9756]	Loss: 0.6032	LR: 0.020000
Training Epoch: 12 [1280/9756]	Loss: 0.5752	LR: 0.020000
Training Epoch: 12 [1536/9756]	Loss: 0.5636	LR: 0.020000
Training Epoch: 12 [1792/9756]	Loss: 0.5533	LR: 0.020000
Training Epoch: 12 [2048/9756]	Loss: 0.5579	LR: 0.020000
Training Epoch: 12 [2304/9756]	Loss: 0.5738	LR: 0.020000
Training Epoch: 12 [2560/9756]	Loss: 0.5724	LR: 0.020000
Training Epoch: 12 [2816/9756]	Loss: 0.5434	LR: 0.020000
Training Epoch: 12 [3072/9756]	Loss: 0.5489	LR: 0.020000
Training Epoch: 12 [3328/9756]	Loss: 0.5262	LR: 0.020000
Training Epoch: 12 [3584/9756]	Loss: 0.4986	LR: 0.020000
Training Epoch: 12 [3840/9756]	Loss: 0.5246	LR: 0.020000
Training Epoch: 12 [4096/9756]	Loss: 0.4973	LR: 0.020000
Training Epoch: 12 [4352/9756]	Loss: 0.4645	LR: 0.020000
Training Epoch: 12 [4608/9756]	Loss: 0.5746	LR: 0.020000
Training Epoch: 12 [4864/9756]	Loss: 0.5590	LR: 0.020000
Training Epoch: 12 [5120/9756]	Loss: 0.5918	LR: 0.020000
Training Epoch: 12 [5376/9756]	Loss: 0.5852	LR: 0.020000
Training Epoch: 12 [5632/9756]	Loss: 0.5111	LR: 0.020000
Training Epoch: 12 [5888/9756]	Loss: 0.5203	LR: 0.020000
Training Epoch: 12 [6144/9756]	Loss: 0.4954	LR: 0.020000
Training Epoch: 12 [6400/9756]	Loss: 0.4924	LR: 0.020000
Training Epoch: 12 [6656/9756]	Loss: 0.4836	LR: 0.020000
Training Epoch: 12 [6912/9756]	Loss: 0.4932	LR: 0.020000
Training Epoch: 12 [7168/9756]	Loss: 0.4704	LR: 0.020000
Training Epoch: 12 [7424/9756]	Loss: 0.5764	LR: 0.020000
Training Epoch: 12 [7680/9756]	Loss: 0.5547	LR: 0.020000
Training Epoch: 12 [7936/9756]	Loss: 0.4732	LR: 0.020000
Training Epoch: 12 [8192/9756]	Loss: 0.5334	LR: 0.020000
Training Epoch: 12 [8448/9756]	Loss: 0.4923	LR: 0.020000
Training Epoch: 12 [8704/9756]	Loss: 0.4914	LR: 0.020000
Training Epoch: 12 [8960/9756]	Loss: 0.4814	LR: 0.020000
Training Epoch: 12 [9216/9756]	Loss: 0.4324	LR: 0.020000
Training Epoch: 12 [9472/9756]	Loss: 0.4606	LR: 0.020000
Training Epoch: 12 [9728/9756]	Loss: 0.5431	LR: 0.020000
Training Epoch: 12 [9756/9756]	Loss: 0.6717	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5284, Train Accuracy: 0.7427
Epoch 12 training time consumed: 141.11s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0029, Accuracy: 0.6930, Time consumed:7.96s
Training Epoch: 13 [256/9756]	Loss: 0.6926	LR: 0.020000
Training Epoch: 13 [512/9756]	Loss: 0.6061	LR: 0.020000
Training Epoch: 13 [768/9756]	Loss: 0.5290	LR: 0.020000
Training Epoch: 13 [1024/9756]	Loss: 0.5261	LR: 0.020000
Training Epoch: 13 [1280/9756]	Loss: 0.5075	LR: 0.020000
Training Epoch: 13 [1536/9756]	Loss: 0.5840	LR: 0.020000
Training Epoch: 13 [1792/9756]	Loss: 0.5987	LR: 0.020000
Training Epoch: 13 [2048/9756]	Loss: 0.5269	LR: 0.020000
Training Epoch: 13 [2304/9756]	Loss: 0.5660	LR: 0.020000
Training Epoch: 13 [2560/9756]	Loss: 0.5468	LR: 0.020000
Training Epoch: 13 [2816/9756]	Loss: 0.5242	LR: 0.020000
Training Epoch: 13 [3072/9756]	Loss: 0.5621	LR: 0.020000
Training Epoch: 13 [3328/9756]	Loss: 0.5359	LR: 0.020000
Training Epoch: 13 [3584/9756]	Loss: 0.5379	LR: 0.020000
Training Epoch: 13 [3840/9756]	Loss: 0.5166	LR: 0.020000
Training Epoch: 13 [4096/9756]	Loss: 0.5097	LR: 0.020000
Training Epoch: 13 [4352/9756]	Loss: 0.5252	LR: 0.020000
Training Epoch: 13 [4608/9756]	Loss: 0.5409	LR: 0.020000
Training Epoch: 13 [4864/9756]	Loss: 0.5082	LR: 0.020000
Training Epoch: 13 [5120/9756]	Loss: 0.4576	LR: 0.020000
Training Epoch: 13 [5376/9756]	Loss: 0.4429	LR: 0.020000
Training Epoch: 13 [5632/9756]	Loss: 0.5602	LR: 0.020000
Training Epoch: 13 [5888/9756]	Loss: 0.4960	LR: 0.020000
Training Epoch: 13 [6144/9756]	Loss: 0.5023	LR: 0.020000
Training Epoch: 13 [6400/9756]	Loss: 0.4671	LR: 0.020000
Training Epoch: 13 [6656/9756]	Loss: 0.4866	LR: 0.020000
Training Epoch: 13 [6912/9756]	Loss: 0.5030	LR: 0.020000
Training Epoch: 13 [7168/9756]	Loss: 0.4555	LR: 0.020000
Training Epoch: 13 [7424/9756]	Loss: 0.4860	LR: 0.020000
Training Epoch: 13 [7680/9756]	Loss: 0.4204	LR: 0.020000
Training Epoch: 13 [7936/9756]	Loss: 0.4168	LR: 0.020000
Training Epoch: 13 [8192/9756]	Loss: 0.4610	LR: 0.020000
Training Epoch: 13 [8448/9756]	Loss: 0.4331	LR: 0.020000
Training Epoch: 13 [8704/9756]	Loss: 0.4647	LR: 0.020000
Training Epoch: 13 [8960/9756]	Loss: 0.4978	LR: 0.020000
Training Epoch: 13 [9216/9756]	Loss: 0.4818	LR: 0.020000
Training Epoch: 13 [9472/9756]	Loss: 0.4331	LR: 0.020000
Training Epoch: 13 [9728/9756]	Loss: 0.5007	LR: 0.020000
Training Epoch: 13 [9756/9756]	Loss: 0.5127	LR: 0.020000
Epoch 13 - Average Train Loss: 0.5108, Train Accuracy: 0.7539
Epoch 13 training time consumed: 142.44s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0024, Accuracy: 0.7337, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-13-best.pth
Training Epoch: 14 [256/9756]	Loss: 0.5327	LR: 0.020000
Training Epoch: 14 [512/9756]	Loss: 0.5887	LR: 0.020000
Training Epoch: 14 [768/9756]	Loss: 0.4890	LR: 0.020000
Training Epoch: 14 [1024/9756]	Loss: 0.5225	LR: 0.020000
Training Epoch: 14 [1280/9756]	Loss: 0.4813	LR: 0.020000
Training Epoch: 14 [1536/9756]	Loss: 0.4651	LR: 0.020000
Training Epoch: 14 [1792/9756]	Loss: 0.4688	LR: 0.020000
Training Epoch: 14 [2048/9756]	Loss: 0.4664	LR: 0.020000
Training Epoch: 14 [2304/9756]	Loss: 0.4836	LR: 0.020000
Training Epoch: 14 [2560/9756]	Loss: 0.5014	LR: 0.020000
Training Epoch: 14 [2816/9756]	Loss: 0.4614	LR: 0.020000
Training Epoch: 14 [3072/9756]	Loss: 0.4393	LR: 0.020000
Training Epoch: 14 [3328/9756]	Loss: 0.4453	LR: 0.020000
Training Epoch: 14 [3584/9756]	Loss: 0.4244	LR: 0.020000
Training Epoch: 14 [3840/9756]	Loss: 0.3676	LR: 0.020000
Training Epoch: 14 [4096/9756]	Loss: 0.3992	LR: 0.020000
Training Epoch: 14 [4352/9756]	Loss: 0.4274	LR: 0.020000
Training Epoch: 14 [4608/9756]	Loss: 0.3848	LR: 0.020000
Training Epoch: 14 [4864/9756]	Loss: 0.4126	LR: 0.020000
Training Epoch: 14 [5120/9756]	Loss: 0.3185	LR: 0.020000
Training Epoch: 14 [5376/9756]	Loss: 0.3838	LR: 0.020000
Training Epoch: 14 [5632/9756]	Loss: 0.4584	LR: 0.020000
Training Epoch: 14 [5888/9756]	Loss: 0.4450	LR: 0.020000
Training Epoch: 14 [6144/9756]	Loss: 0.4631	LR: 0.020000
Training Epoch: 14 [6400/9756]	Loss: 0.3865	LR: 0.020000
Training Epoch: 14 [6656/9756]	Loss: 0.4028	LR: 0.020000
Training Epoch: 14 [6912/9756]	Loss: 0.4089	LR: 0.020000
Training Epoch: 14 [7168/9756]	Loss: 0.3928	LR: 0.020000
Training Epoch: 14 [7424/9756]	Loss: 0.3619	LR: 0.020000
Training Epoch: 14 [7680/9756]	Loss: 0.3954	LR: 0.020000
Training Epoch: 14 [7936/9756]	Loss: 0.3622	LR: 0.020000
Training Epoch: 14 [8192/9756]	Loss: 0.3400	LR: 0.020000
Training Epoch: 14 [8448/9756]	Loss: 0.3026	LR: 0.020000
Training Epoch: 14 [8704/9756]	Loss: 0.4182	LR: 0.020000
Training Epoch: 14 [8960/9756]	Loss: 0.3564	LR: 0.020000
Training Epoch: 14 [9216/9756]	Loss: 0.3101	LR: 0.020000
Training Epoch: 14 [9472/9756]	Loss: 0.3659	LR: 0.020000
Training Epoch: 14 [9728/9756]	Loss: 0.3445	LR: 0.020000
Training Epoch: 14 [9756/9756]	Loss: 0.3849	LR: 0.020000
Epoch 14 - Average Train Loss: 0.4204, Train Accuracy: 0.8151
Epoch 14 training time consumed: 148.37s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0035, Accuracy: 0.5680, Time consumed:8.07s
Training Epoch: 15 [256/9756]	Loss: 0.3801	LR: 0.020000
Training Epoch: 15 [512/9756]	Loss: 0.4031	LR: 0.020000
Training Epoch: 15 [768/9756]	Loss: 0.3796	LR: 0.020000
Training Epoch: 15 [1024/9756]	Loss: 0.3365	LR: 0.020000
Training Epoch: 15 [1280/9756]	Loss: 0.3553	LR: 0.020000
Training Epoch: 15 [1536/9756]	Loss: 0.3775	LR: 0.020000
Training Epoch: 15 [1792/9756]	Loss: 0.3537	LR: 0.020000
Training Epoch: 15 [2048/9756]	Loss: 0.3504	LR: 0.020000
Training Epoch: 15 [2304/9756]	Loss: 0.3879	LR: 0.020000
Training Epoch: 15 [2560/9756]	Loss: 0.3896	LR: 0.020000
Training Epoch: 15 [2816/9756]	Loss: 0.2994	LR: 0.020000
Training Epoch: 15 [3072/9756]	Loss: 0.3515	LR: 0.020000
Training Epoch: 15 [3328/9756]	Loss: 0.3408	LR: 0.020000
Training Epoch: 15 [3584/9756]	Loss: 0.3194	LR: 0.020000
Training Epoch: 15 [3840/9756]	Loss: 0.3924	LR: 0.020000
Training Epoch: 15 [4096/9756]	Loss: 0.3577	LR: 0.020000
Training Epoch: 15 [4352/9756]	Loss: 0.3006	LR: 0.020000
Training Epoch: 15 [4608/9756]	Loss: 0.3022	LR: 0.020000
Training Epoch: 15 [4864/9756]	Loss: 0.3925	LR: 0.020000
Training Epoch: 15 [5120/9756]	Loss: 0.3549	LR: 0.020000
Training Epoch: 15 [5376/9756]	Loss: 0.3578	LR: 0.020000
Training Epoch: 15 [5632/9756]	Loss: 0.2782	LR: 0.020000
Training Epoch: 15 [5888/9756]	Loss: 0.3849	LR: 0.020000
Training Epoch: 15 [6144/9756]	Loss: 0.2813	LR: 0.020000
Training Epoch: 15 [6400/9756]	Loss: 0.3649	LR: 0.020000
Training Epoch: 15 [6656/9756]	Loss: 0.3068	LR: 0.020000
Training Epoch: 15 [6912/9756]	Loss: 0.3513	LR: 0.020000
Training Epoch: 15 [7168/9756]	Loss: 0.3497	LR: 0.020000
Training Epoch: 15 [7424/9756]	Loss: 0.3178	LR: 0.020000
Training Epoch: 15 [7680/9756]	Loss: 0.3582	LR: 0.020000
Training Epoch: 15 [7936/9756]	Loss: 0.4249	LR: 0.020000
Training Epoch: 15 [8192/9756]	Loss: 0.3487	LR: 0.020000
Training Epoch: 15 [8448/9756]	Loss: 0.3152	LR: 0.020000
Training Epoch: 15 [8704/9756]	Loss: 0.3188	LR: 0.020000
Training Epoch: 15 [8960/9756]	Loss: 0.3493	LR: 0.020000
Training Epoch: 15 [9216/9756]	Loss: 0.2693	LR: 0.020000
Training Epoch: 15 [9472/9756]	Loss: 0.2987	LR: 0.020000
Training Epoch: 15 [9728/9756]	Loss: 0.2691	LR: 0.020000
Training Epoch: 15 [9756/9756]	Loss: 0.2143	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3436, Train Accuracy: 0.8556
Epoch 15 training time consumed: 142.74s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0021, Accuracy: 0.8155, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-15-best.pth
Training Epoch: 16 [256/9756]	Loss: 0.4171	LR: 0.020000
Training Epoch: 16 [512/9756]	Loss: 0.3235	LR: 0.020000
Training Epoch: 16 [768/9756]	Loss: 0.2441	LR: 0.020000
Training Epoch: 16 [1024/9756]	Loss: 0.2560	LR: 0.020000
Training Epoch: 16 [1280/9756]	Loss: 0.3385	LR: 0.020000
Training Epoch: 16 [1536/9756]	Loss: 0.3523	LR: 0.020000
Training Epoch: 16 [1792/9756]	Loss: 0.3153	LR: 0.020000
Training Epoch: 16 [2048/9756]	Loss: 0.2899	LR: 0.020000
Training Epoch: 16 [2304/9756]	Loss: 0.2792	LR: 0.020000
Training Epoch: 16 [2560/9756]	Loss: 0.2533	LR: 0.020000
Training Epoch: 16 [2816/9756]	Loss: 0.3287	LR: 0.020000
Training Epoch: 16 [3072/9756]	Loss: 0.2510	LR: 0.020000
Training Epoch: 16 [3328/9756]	Loss: 0.2812	LR: 0.020000
Training Epoch: 16 [3584/9756]	Loss: 0.2872	LR: 0.020000
Training Epoch: 16 [3840/9756]	Loss: 0.2899	LR: 0.020000
Training Epoch: 16 [4096/9756]	Loss: 0.3379	LR: 0.020000
Training Epoch: 16 [4352/9756]	Loss: 0.3086	LR: 0.020000
Training Epoch: 16 [4608/9756]	Loss: 0.2598	LR: 0.020000
Training Epoch: 16 [4864/9756]	Loss: 0.2858	LR: 0.020000
Training Epoch: 16 [5120/9756]	Loss: 0.2999	LR: 0.020000
Training Epoch: 16 [5376/9756]	Loss: 0.2603	LR: 0.020000
Training Epoch: 16 [5632/9756]	Loss: 0.2665	LR: 0.020000
Training Epoch: 16 [5888/9756]	Loss: 0.2556	LR: 0.020000
Training Epoch: 16 [6144/9756]	Loss: 0.3180	LR: 0.020000
Training Epoch: 16 [6400/9756]	Loss: 0.3002	LR: 0.020000
Training Epoch: 16 [6656/9756]	Loss: 0.2622	LR: 0.020000
Training Epoch: 16 [6912/9756]	Loss: 0.2909	LR: 0.020000
Training Epoch: 16 [7168/9756]	Loss: 0.2165	LR: 0.020000
Training Epoch: 16 [7424/9756]	Loss: 0.2726	LR: 0.020000
Training Epoch: 16 [7680/9756]	Loss: 0.2573	LR: 0.020000
Training Epoch: 16 [7936/9756]	Loss: 0.2748	LR: 0.020000
Training Epoch: 16 [8192/9756]	Loss: 0.3707	LR: 0.020000
Training Epoch: 16 [8448/9756]	Loss: 0.3011	LR: 0.020000
Training Epoch: 16 [8704/9756]	Loss: 0.2975	LR: 0.020000
Training Epoch: 16 [8960/9756]	Loss: 0.2617	LR: 0.020000
Training Epoch: 16 [9216/9756]	Loss: 0.3094	LR: 0.020000
Training Epoch: 16 [9472/9756]	Loss: 0.2975	LR: 0.020000
Training Epoch: 16 [9728/9756]	Loss: 0.3268	LR: 0.020000
Training Epoch: 16 [9756/9756]	Loss: 0.2837	LR: 0.020000
Epoch 16 - Average Train Loss: 0.2931, Train Accuracy: 0.8773
Epoch 16 training time consumed: 141.35s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0035, Accuracy: 0.6121, Time consumed:8.12s
Training Epoch: 17 [256/9756]	Loss: 0.2835	LR: 0.020000
Training Epoch: 17 [512/9756]	Loss: 0.3088	LR: 0.020000
Training Epoch: 17 [768/9756]	Loss: 0.2295	LR: 0.020000
Training Epoch: 17 [1024/9756]	Loss: 0.1954	LR: 0.020000
Training Epoch: 17 [1280/9756]	Loss: 0.2482	LR: 0.020000
Training Epoch: 17 [1536/9756]	Loss: 0.3147	LR: 0.020000
Training Epoch: 17 [1792/9756]	Loss: 0.2095	LR: 0.020000
Training Epoch: 17 [2048/9756]	Loss: 0.3027	LR: 0.020000
Training Epoch: 17 [2304/9756]	Loss: 0.2711	LR: 0.020000
Training Epoch: 17 [2560/9756]	Loss: 0.3169	LR: 0.020000
Training Epoch: 17 [2816/9756]	Loss: 0.2900	LR: 0.020000
Training Epoch: 17 [3072/9756]	Loss: 0.2666	LR: 0.020000
Training Epoch: 17 [3328/9756]	Loss: 0.2844	LR: 0.020000
Training Epoch: 17 [3584/9756]	Loss: 0.3329	LR: 0.020000
Training Epoch: 17 [3840/9756]	Loss: 0.2954	LR: 0.020000
Training Epoch: 17 [4096/9756]	Loss: 0.2377	LR: 0.020000
Training Epoch: 17 [4352/9756]	Loss: 0.2438	LR: 0.020000
Training Epoch: 17 [4608/9756]	Loss: 0.2592	LR: 0.020000
Training Epoch: 17 [4864/9756]	Loss: 0.3246	LR: 0.020000
Training Epoch: 17 [5120/9756]	Loss: 0.3278	LR: 0.020000
Training Epoch: 17 [5376/9756]	Loss: 0.2403	LR: 0.020000
Training Epoch: 17 [5632/9756]	Loss: 0.2696	LR: 0.020000
Training Epoch: 17 [5888/9756]	Loss: 0.2867	LR: 0.020000
Training Epoch: 17 [6144/9756]	Loss: 0.3011	LR: 0.020000
Training Epoch: 17 [6400/9756]	Loss: 0.2852	LR: 0.020000
Training Epoch: 17 [6656/9756]	Loss: 0.2430	LR: 0.020000
Training Epoch: 17 [6912/9756]	Loss: 0.2639	LR: 0.020000
Training Epoch: 17 [7168/9756]	Loss: 0.2296	LR: 0.020000
Training Epoch: 17 [7424/9756]	Loss: 0.2381	LR: 0.020000
Training Epoch: 17 [7680/9756]	Loss: 0.2685	LR: 0.020000
Training Epoch: 17 [7936/9756]	Loss: 0.2561	LR: 0.020000
Training Epoch: 17 [8192/9756]	Loss: 0.2458	LR: 0.020000
Training Epoch: 17 [8448/9756]	Loss: 0.2916	LR: 0.020000
Training Epoch: 17 [8704/9756]	Loss: 0.2653	LR: 0.020000
Training Epoch: 17 [8960/9756]	Loss: 0.2144	LR: 0.020000
Training Epoch: 17 [9216/9756]	Loss: 0.2414	LR: 0.020000
Training Epoch: 17 [9472/9756]	Loss: 0.2303	LR: 0.020000
Training Epoch: 17 [9728/9756]	Loss: 0.2787	LR: 0.020000
Training Epoch: 17 [9756/9756]	Loss: 0.1314	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2678, Train Accuracy: 0.8878
Epoch 17 training time consumed: 141.30s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0023, Accuracy: 0.7952, Time consumed:7.93s
Training Epoch: 18 [256/9756]	Loss: 0.2549	LR: 0.020000
Training Epoch: 18 [512/9756]	Loss: 0.2377	LR: 0.020000
Training Epoch: 18 [768/9756]	Loss: 0.1965	LR: 0.020000
Training Epoch: 18 [1024/9756]	Loss: 0.2323	LR: 0.020000
Training Epoch: 18 [1280/9756]	Loss: 0.2001	LR: 0.020000
Training Epoch: 18 [1536/9756]	Loss: 0.2349	LR: 0.020000
Training Epoch: 18 [1792/9756]	Loss: 0.1854	LR: 0.020000
Training Epoch: 18 [2048/9756]	Loss: 0.2641	LR: 0.020000
Training Epoch: 18 [2304/9756]	Loss: 0.2214	LR: 0.020000
Training Epoch: 18 [2560/9756]	Loss: 0.2616	LR: 0.020000
Training Epoch: 18 [2816/9756]	Loss: 0.2049	LR: 0.020000
Training Epoch: 18 [3072/9756]	Loss: 0.2848	LR: 0.020000
Training Epoch: 18 [3328/9756]	Loss: 0.2422	LR: 0.020000
Training Epoch: 18 [3584/9756]	Loss: 0.2654	LR: 0.020000
Training Epoch: 18 [3840/9756]	Loss: 0.2802	LR: 0.020000
Training Epoch: 18 [4096/9756]	Loss: 0.2315	LR: 0.020000
Training Epoch: 18 [4352/9756]	Loss: 0.3010	LR: 0.020000
Training Epoch: 18 [4608/9756]	Loss: 0.2116	LR: 0.020000
Training Epoch: 18 [4864/9756]	Loss: 0.2907	LR: 0.020000
Training Epoch: 18 [5120/9756]	Loss: 0.2160	LR: 0.020000
Training Epoch: 18 [5376/9756]	Loss: 0.2131	LR: 0.020000
Training Epoch: 18 [5632/9756]	Loss: 0.2437	LR: 0.020000
Training Epoch: 18 [5888/9756]	Loss: 0.2040	LR: 0.020000
Training Epoch: 18 [6144/9756]	Loss: 0.2045	LR: 0.020000
Training Epoch: 18 [6400/9756]	Loss: 0.1617	LR: 0.020000
Training Epoch: 18 [6656/9756]	Loss: 0.2735	LR: 0.020000
Training Epoch: 18 [6912/9756]	Loss: 0.2150	LR: 0.020000
Training Epoch: 18 [7168/9756]	Loss: 0.2190	LR: 0.020000
Training Epoch: 18 [7424/9756]	Loss: 0.2513	LR: 0.020000
Training Epoch: 18 [7680/9756]	Loss: 0.1436	LR: 0.020000
Training Epoch: 18 [7936/9756]	Loss: 0.2292	LR: 0.020000
Training Epoch: 18 [8192/9756]	Loss: 0.2258	LR: 0.020000
Training Epoch: 18 [8448/9756]	Loss: 0.2387	LR: 0.020000
Training Epoch: 18 [8704/9756]	Loss: 0.1862	LR: 0.020000
Training Epoch: 18 [8960/9756]	Loss: 0.2305	LR: 0.020000
Training Epoch: 18 [9216/9756]	Loss: 0.2443	LR: 0.020000
Training Epoch: 18 [9472/9756]	Loss: 0.2612	LR: 0.020000
Training Epoch: 18 [9728/9756]	Loss: 0.2405	LR: 0.020000
Training Epoch: 18 [9756/9756]	Loss: 0.5427	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2325, Train Accuracy: 0.9045
Epoch 18 training time consumed: 141.25s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0011, Accuracy: 0.9041, Time consumed:7.90s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-18-best.pth
Training Epoch: 19 [256/9756]	Loss: 0.3245	LR: 0.020000
Training Epoch: 19 [512/9756]	Loss: 0.4470	LR: 0.020000
Training Epoch: 19 [768/9756]	Loss: 0.3149	LR: 0.020000
Training Epoch: 19 [1024/9756]	Loss: 0.2595	LR: 0.020000
Training Epoch: 19 [1280/9756]	Loss: 0.2862	LR: 0.020000
Training Epoch: 19 [1536/9756]	Loss: 0.3113	LR: 0.020000
Training Epoch: 19 [1792/9756]	Loss: 0.2744	LR: 0.020000
Training Epoch: 19 [2048/9756]	Loss: 0.2508	LR: 0.020000
Training Epoch: 19 [2304/9756]	Loss: 0.2859	LR: 0.020000
Training Epoch: 19 [2560/9756]	Loss: 0.2535	LR: 0.020000
Training Epoch: 19 [2816/9756]	Loss: 0.2484	LR: 0.020000
Training Epoch: 19 [3072/9756]	Loss: 0.1942	LR: 0.020000
Training Epoch: 19 [3328/9756]	Loss: 0.3228	LR: 0.020000
Training Epoch: 19 [3584/9756]	Loss: 0.2431	LR: 0.020000
Training Epoch: 19 [3840/9756]	Loss: 0.2559	LR: 0.020000
Training Epoch: 19 [4096/9756]	Loss: 0.2236	LR: 0.020000
Training Epoch: 19 [4352/9756]	Loss: 0.2588	LR: 0.020000
Training Epoch: 19 [4608/9756]	Loss: 0.2229	LR: 0.020000
Training Epoch: 19 [4864/9756]	Loss: 0.2554	LR: 0.020000
Training Epoch: 19 [5120/9756]	Loss: 0.2326	LR: 0.020000
Training Epoch: 19 [5376/9756]	Loss: 0.2512	LR: 0.020000
Training Epoch: 19 [5632/9756]	Loss: 0.2052	LR: 0.020000
Training Epoch: 19 [5888/9756]	Loss: 0.2268	LR: 0.020000
Training Epoch: 19 [6144/9756]	Loss: 0.2569	LR: 0.020000
Training Epoch: 19 [6400/9756]	Loss: 0.2452	LR: 0.020000
Training Epoch: 19 [6656/9756]	Loss: 0.2117	LR: 0.020000
Training Epoch: 19 [6912/9756]	Loss: 0.1920	LR: 0.020000
Training Epoch: 19 [7168/9756]	Loss: 0.2094	LR: 0.020000
Training Epoch: 19 [7424/9756]	Loss: 0.2032	LR: 0.020000
Training Epoch: 19 [7680/9756]	Loss: 0.2456	LR: 0.020000
Training Epoch: 19 [7936/9756]	Loss: 0.2230	LR: 0.020000
Training Epoch: 19 [8192/9756]	Loss: 0.2099	LR: 0.020000
Training Epoch: 19 [8448/9756]	Loss: 0.1849	LR: 0.020000
Training Epoch: 19 [8704/9756]	Loss: 0.2472	LR: 0.020000
Training Epoch: 19 [8960/9756]	Loss: 0.1641	LR: 0.020000
Training Epoch: 19 [9216/9756]	Loss: 0.2415	LR: 0.020000
Training Epoch: 19 [9472/9756]	Loss: 0.1621	LR: 0.020000
Training Epoch: 19 [9728/9756]	Loss: 0.2082	LR: 0.020000
Training Epoch: 19 [9756/9756]	Loss: 0.0693	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2456, Train Accuracy: 0.8963
Epoch 19 training time consumed: 141.24s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0009, Accuracy: 0.9148, Time consumed:8.12s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-19-best.pth
Training Epoch: 20 [256/9756]	Loss: 0.2881	LR: 0.004000
Training Epoch: 20 [512/9756]	Loss: 0.2262	LR: 0.004000
Training Epoch: 20 [768/9756]	Loss: 0.2185	LR: 0.004000
Training Epoch: 20 [1024/9756]	Loss: 0.2209	LR: 0.004000
Training Epoch: 20 [1280/9756]	Loss: 0.2040	LR: 0.004000
Training Epoch: 20 [1536/9756]	Loss: 0.1708	LR: 0.004000
Training Epoch: 20 [1792/9756]	Loss: 0.1938	LR: 0.004000
Training Epoch: 20 [2048/9756]	Loss: 0.2599	LR: 0.004000
Training Epoch: 20 [2304/9756]	Loss: 0.1507	LR: 0.004000
Training Epoch: 20 [2560/9756]	Loss: 0.1927	LR: 0.004000
Training Epoch: 20 [2816/9756]	Loss: 0.2033	LR: 0.004000
Training Epoch: 20 [3072/9756]	Loss: 0.1471	LR: 0.004000
Training Epoch: 20 [3328/9756]	Loss: 0.1645	LR: 0.004000
Training Epoch: 20 [3584/9756]	Loss: 0.1904	LR: 0.004000
Training Epoch: 20 [3840/9756]	Loss: 0.1911	LR: 0.004000
Training Epoch: 20 [4096/9756]	Loss: 0.2078	LR: 0.004000
Training Epoch: 20 [4352/9756]	Loss: 0.2309	LR: 0.004000
Training Epoch: 20 [4608/9756]	Loss: 0.2132	LR: 0.004000
Training Epoch: 20 [4864/9756]	Loss: 0.1386	LR: 0.004000
Training Epoch: 20 [5120/9756]	Loss: 0.1850	LR: 0.004000
Training Epoch: 20 [5376/9756]	Loss: 0.1686	LR: 0.004000
Training Epoch: 20 [5632/9756]	Loss: 0.1935	LR: 0.004000
Training Epoch: 20 [5888/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 20 [6144/9756]	Loss: 0.1864	LR: 0.004000
Training Epoch: 20 [6400/9756]	Loss: 0.1940	LR: 0.004000
Training Epoch: 20 [6656/9756]	Loss: 0.1799	LR: 0.004000
Training Epoch: 20 [6912/9756]	Loss: 0.2258	LR: 0.004000
Training Epoch: 20 [7168/9756]	Loss: 0.1840	LR: 0.004000
Training Epoch: 20 [7424/9756]	Loss: 0.1362	LR: 0.004000
Training Epoch: 20 [7680/9756]	Loss: 0.1762	LR: 0.004000
Training Epoch: 20 [7936/9756]	Loss: 0.1323	LR: 0.004000
Training Epoch: 20 [8192/9756]	Loss: 0.1961	LR: 0.004000
Training Epoch: 20 [8448/9756]	Loss: 0.1537	LR: 0.004000
Training Epoch: 20 [8704/9756]	Loss: 0.1806	LR: 0.004000
Training Epoch: 20 [8960/9756]	Loss: 0.1487	LR: 0.004000
Training Epoch: 20 [9216/9756]	Loss: 0.1596	LR: 0.004000
Training Epoch: 20 [9472/9756]	Loss: 0.1715	LR: 0.004000
Training Epoch: 20 [9728/9756]	Loss: 0.1937	LR: 0.004000
Training Epoch: 20 [9756/9756]	Loss: 0.1765	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1873, Train Accuracy: 0.9258
Epoch 20 training time consumed: 141.21s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0007, Accuracy: 0.9400, Time consumed:8.11s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-20-best.pth
Training Epoch: 21 [256/9756]	Loss: 0.1494	LR: 0.004000
Training Epoch: 21 [512/9756]	Loss: 0.1720	LR: 0.004000
Training Epoch: 21 [768/9756]	Loss: 0.1366	LR: 0.004000
Training Epoch: 21 [1024/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 21 [1280/9756]	Loss: 0.1941	LR: 0.004000
Training Epoch: 21 [1536/9756]	Loss: 0.2017	LR: 0.004000
Training Epoch: 21 [1792/9756]	Loss: 0.1538	LR: 0.004000
Training Epoch: 21 [2048/9756]	Loss: 0.1972	LR: 0.004000
Training Epoch: 21 [2304/9756]	Loss: 0.1877	LR: 0.004000
Training Epoch: 21 [2560/9756]	Loss: 0.1521	LR: 0.004000
Training Epoch: 21 [2816/9756]	Loss: 0.1496	LR: 0.004000
Training Epoch: 21 [3072/9756]	Loss: 0.1366	LR: 0.004000
Training Epoch: 21 [3328/9756]	Loss: 0.1835	LR: 0.004000
Training Epoch: 21 [3584/9756]	Loss: 0.2036	LR: 0.004000
Training Epoch: 21 [3840/9756]	Loss: 0.1867	LR: 0.004000
Training Epoch: 21 [4096/9756]	Loss: 0.2396	LR: 0.004000
Training Epoch: 21 [4352/9756]	Loss: 0.2655	LR: 0.004000
Training Epoch: 21 [4608/9756]	Loss: 0.2579	LR: 0.004000
Training Epoch: 21 [4864/9756]	Loss: 0.1988	LR: 0.004000
Training Epoch: 21 [5120/9756]	Loss: 0.1790	LR: 0.004000
Training Epoch: 21 [5376/9756]	Loss: 0.1710	LR: 0.004000
Training Epoch: 21 [5632/9756]	Loss: 0.1430	LR: 0.004000
Training Epoch: 21 [5888/9756]	Loss: 0.1312	LR: 0.004000
Training Epoch: 21 [6144/9756]	Loss: 0.2274	LR: 0.004000
Training Epoch: 21 [6400/9756]	Loss: 0.1641	LR: 0.004000
Training Epoch: 21 [6656/9756]	Loss: 0.1429	LR: 0.004000
Training Epoch: 21 [6912/9756]	Loss: 0.1967	LR: 0.004000
Training Epoch: 21 [7168/9756]	Loss: 0.1682	LR: 0.004000
Training Epoch: 21 [7424/9756]	Loss: 0.1529	LR: 0.004000
Training Epoch: 21 [7680/9756]	Loss: 0.1923	LR: 0.004000
Training Epoch: 21 [7936/9756]	Loss: 0.1245	LR: 0.004000
Training Epoch: 21 [8192/9756]	Loss: 0.2051	LR: 0.004000
Training Epoch: 21 [8448/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 21 [8704/9756]	Loss: 0.1857	LR: 0.004000
Training Epoch: 21 [8960/9756]	Loss: 0.1571	LR: 0.004000
Training Epoch: 21 [9216/9756]	Loss: 0.1904	LR: 0.004000
Training Epoch: 21 [9472/9756]	Loss: 0.1662	LR: 0.004000
Training Epoch: 21 [9728/9756]	Loss: 0.2145	LR: 0.004000
Training Epoch: 21 [9756/9756]	Loss: 0.2135	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1797, Train Accuracy: 0.9265
Epoch 21 training time consumed: 140.39s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0007, Accuracy: 0.9414, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-21-best.pth
Training Epoch: 22 [256/9756]	Loss: 0.1367	LR: 0.004000
Training Epoch: 22 [512/9756]	Loss: 0.1632	LR: 0.004000
Training Epoch: 22 [768/9756]	Loss: 0.1369	LR: 0.004000
Training Epoch: 22 [1024/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 22 [1280/9756]	Loss: 0.2079	LR: 0.004000
Training Epoch: 22 [1536/9756]	Loss: 0.2012	LR: 0.004000
Training Epoch: 22 [1792/9756]	Loss: 0.1940	LR: 0.004000
Training Epoch: 22 [2048/9756]	Loss: 0.1659	LR: 0.004000
Training Epoch: 22 [2304/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 22 [2560/9756]	Loss: 0.2137	LR: 0.004000
Training Epoch: 22 [2816/9756]	Loss: 0.2078	LR: 0.004000
Training Epoch: 22 [3072/9756]	Loss: 0.1468	LR: 0.004000
Training Epoch: 22 [3328/9756]	Loss: 0.1463	LR: 0.004000
Training Epoch: 22 [3584/9756]	Loss: 0.2441	LR: 0.004000
Training Epoch: 22 [3840/9756]	Loss: 0.2066	LR: 0.004000
Training Epoch: 22 [4096/9756]	Loss: 0.1084	LR: 0.004000
Training Epoch: 22 [4352/9756]	Loss: 0.1630	LR: 0.004000
Training Epoch: 22 [4608/9756]	Loss: 0.1619	LR: 0.004000
Training Epoch: 22 [4864/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 22 [5120/9756]	Loss: 0.1695	LR: 0.004000
Training Epoch: 22 [5376/9756]	Loss: 0.1504	LR: 0.004000
Training Epoch: 22 [5632/9756]	Loss: 0.1389	LR: 0.004000
Training Epoch: 22 [5888/9756]	Loss: 0.2547	LR: 0.004000
Training Epoch: 22 [6144/9756]	Loss: 0.1609	LR: 0.004000
Training Epoch: 22 [6400/9756]	Loss: 0.1941	LR: 0.004000
Training Epoch: 22 [6656/9756]	Loss: 0.1618	LR: 0.004000
Training Epoch: 22 [6912/9756]	Loss: 0.2421	LR: 0.004000
Training Epoch: 22 [7168/9756]	Loss: 0.1668	LR: 0.004000
Training Epoch: 22 [7424/9756]	Loss: 0.1663	LR: 0.004000
Training Epoch: 22 [7680/9756]	Loss: 0.2268	LR: 0.004000
Training Epoch: 22 [7936/9756]	Loss: 0.1379	LR: 0.004000
Training Epoch: 22 [8192/9756]	Loss: 0.2575	LR: 0.004000
Training Epoch: 22 [8448/9756]	Loss: 0.2091	LR: 0.004000
Training Epoch: 22 [8704/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 22 [8960/9756]	Loss: 0.1712	LR: 0.004000
Training Epoch: 22 [9216/9756]	Loss: 0.1488	LR: 0.004000
Training Epoch: 22 [9472/9756]	Loss: 0.1315	LR: 0.004000
Training Epoch: 22 [9728/9756]	Loss: 0.1645	LR: 0.004000
Training Epoch: 22 [9756/9756]	Loss: 0.1817	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1758, Train Accuracy: 0.9275
Epoch 22 training time consumed: 140.50s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9385, Time consumed:7.98s
Training Epoch: 23 [256/9756]	Loss: 0.1911	LR: 0.004000
Training Epoch: 23 [512/9756]	Loss: 0.1643	LR: 0.004000
Training Epoch: 23 [768/9756]	Loss: 0.2207	LR: 0.004000
Training Epoch: 23 [1024/9756]	Loss: 0.1806	LR: 0.004000
Training Epoch: 23 [1280/9756]	Loss: 0.1664	LR: 0.004000
Training Epoch: 23 [1536/9756]	Loss: 0.1752	LR: 0.004000
Training Epoch: 23 [1792/9756]	Loss: 0.1602	LR: 0.004000
Training Epoch: 23 [2048/9756]	Loss: 0.1799	LR: 0.004000
Training Epoch: 23 [2304/9756]	Loss: 0.1874	LR: 0.004000
Training Epoch: 23 [2560/9756]	Loss: 0.1567	LR: 0.004000
Training Epoch: 23 [2816/9756]	Loss: 0.1676	LR: 0.004000
Training Epoch: 23 [3072/9756]	Loss: 0.1644	LR: 0.004000
Training Epoch: 23 [3328/9756]	Loss: 0.1762	LR: 0.004000
Training Epoch: 23 [3584/9756]	Loss: 0.2060	LR: 0.004000
Training Epoch: 23 [3840/9756]	Loss: 0.1399	LR: 0.004000
Training Epoch: 23 [4096/9756]	Loss: 0.1785	LR: 0.004000
Training Epoch: 23 [4352/9756]	Loss: 0.1417	LR: 0.004000
Training Epoch: 23 [4608/9756]	Loss: 0.1739	LR: 0.004000
Training Epoch: 23 [4864/9756]	Loss: 0.1951	LR: 0.004000
Training Epoch: 23 [5120/9756]	Loss: 0.1788	LR: 0.004000
Training Epoch: 23 [5376/9756]	Loss: 0.1936	LR: 0.004000
Training Epoch: 23 [5632/9756]	Loss: 0.1674	LR: 0.004000
Training Epoch: 23 [5888/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 23 [6144/9756]	Loss: 0.1861	LR: 0.004000
Training Epoch: 23 [6400/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 23 [6656/9756]	Loss: 0.1268	LR: 0.004000
Training Epoch: 23 [6912/9756]	Loss: 0.2159	LR: 0.004000
Training Epoch: 23 [7168/9756]	Loss: 0.2118	LR: 0.004000
Training Epoch: 23 [7424/9756]	Loss: 0.1641	LR: 0.004000
Training Epoch: 23 [7680/9756]	Loss: 0.1428	LR: 0.004000
Training Epoch: 23 [7936/9756]	Loss: 0.2252	LR: 0.004000
Training Epoch: 23 [8192/9756]	Loss: 0.1794	LR: 0.004000
Training Epoch: 23 [8448/9756]	Loss: 0.1688	LR: 0.004000
Training Epoch: 23 [8704/9756]	Loss: 0.1667	LR: 0.004000
Training Epoch: 23 [8960/9756]	Loss: 0.1394	LR: 0.004000
Training Epoch: 23 [9216/9756]	Loss: 0.2310	LR: 0.004000
Training Epoch: 23 [9472/9756]	Loss: 0.0867	LR: 0.004000
Training Epoch: 23 [9728/9756]	Loss: 0.1147	LR: 0.004000
Training Epoch: 23 [9756/9756]	Loss: 0.2330	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1711, Train Accuracy: 0.9290
Epoch 23 training time consumed: 141.69s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0007, Accuracy: 0.9293, Time consumed:8.19s
Training Epoch: 24 [256/9756]	Loss: 0.1850	LR: 0.004000
Training Epoch: 24 [512/9756]	Loss: 0.1364	LR: 0.004000
Training Epoch: 24 [768/9756]	Loss: 0.1602	LR: 0.004000
Training Epoch: 24 [1024/9756]	Loss: 0.2186	LR: 0.004000
Training Epoch: 24 [1280/9756]	Loss: 0.1209	LR: 0.004000
Training Epoch: 24 [1536/9756]	Loss: 0.1943	LR: 0.004000
Training Epoch: 24 [1792/9756]	Loss: 0.1251	LR: 0.004000
Training Epoch: 24 [2048/9756]	Loss: 0.1765	LR: 0.004000
Training Epoch: 24 [2304/9756]	Loss: 0.1881	LR: 0.004000
Training Epoch: 24 [2560/9756]	Loss: 0.1409	LR: 0.004000
Training Epoch: 24 [2816/9756]	Loss: 0.1593	LR: 0.004000
Training Epoch: 24 [3072/9756]	Loss: 0.1802	LR: 0.004000
Training Epoch: 24 [3328/9756]	Loss: 0.1613	LR: 0.004000
Training Epoch: 24 [3584/9756]	Loss: 0.1083	LR: 0.004000
Training Epoch: 24 [3840/9756]	Loss: 0.1325	LR: 0.004000
Training Epoch: 24 [4096/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 24 [4352/9756]	Loss: 0.2292	LR: 0.004000
Training Epoch: 24 [4608/9756]	Loss: 0.1523	LR: 0.004000
Training Epoch: 24 [4864/9756]	Loss: 0.1728	LR: 0.004000
Training Epoch: 24 [5120/9756]	Loss: 0.1760	LR: 0.004000
Training Epoch: 24 [5376/9756]	Loss: 0.2255	LR: 0.004000
Training Epoch: 24 [5632/9756]	Loss: 0.1759	LR: 0.004000
Training Epoch: 24 [5888/9756]	Loss: 0.1006	LR: 0.004000
Training Epoch: 24 [6144/9756]	Loss: 0.1762	LR: 0.004000
Training Epoch: 24 [6400/9756]	Loss: 0.1929	LR: 0.004000
Training Epoch: 24 [6656/9756]	Loss: 0.1532	LR: 0.004000
Training Epoch: 24 [6912/9756]	Loss: 0.1911	LR: 0.004000
Training Epoch: 24 [7168/9756]	Loss: 0.1978	LR: 0.004000
Training Epoch: 24 [7424/9756]	Loss: 0.1343	LR: 0.004000
Training Epoch: 24 [7680/9756]	Loss: 0.2276	LR: 0.004000
Training Epoch: 24 [7936/9756]	Loss: 0.2371	LR: 0.004000
Training Epoch: 24 [8192/9756]	Loss: 0.1291	LR: 0.004000
Training Epoch: 24 [8448/9756]	Loss: 0.1552	LR: 0.004000
Training Epoch: 24 [8704/9756]	Loss: 0.1912	LR: 0.004000
Training Epoch: 24 [8960/9756]	Loss: 0.1700	LR: 0.004000
Training Epoch: 24 [9216/9756]	Loss: 0.1940	LR: 0.004000
Training Epoch: 24 [9472/9756]	Loss: 0.1595	LR: 0.004000
Training Epoch: 24 [9728/9756]	Loss: 0.1778	LR: 0.004000
Training Epoch: 24 [9756/9756]	Loss: 0.1998	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1701, Train Accuracy: 0.9297
Epoch 24 training time consumed: 140.96s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:7.98s
Training Epoch: 25 [256/9756]	Loss: 0.1408	LR: 0.004000
Training Epoch: 25 [512/9756]	Loss: 0.1983	LR: 0.004000
Training Epoch: 25 [768/9756]	Loss: 0.2210	LR: 0.004000
Training Epoch: 25 [1024/9756]	Loss: 0.2091	LR: 0.004000
Training Epoch: 25 [1280/9756]	Loss: 0.1591	LR: 0.004000
Training Epoch: 25 [1536/9756]	Loss: 0.1578	LR: 0.004000
Training Epoch: 25 [1792/9756]	Loss: 0.1686	LR: 0.004000
Training Epoch: 25 [2048/9756]	Loss: 0.1920	LR: 0.004000
Training Epoch: 25 [2304/9756]	Loss: 0.1418	LR: 0.004000
Training Epoch: 25 [2560/9756]	Loss: 0.1343	LR: 0.004000
Training Epoch: 25 [2816/9756]	Loss: 0.1961	LR: 0.004000
Training Epoch: 25 [3072/9756]	Loss: 0.1326	LR: 0.004000
Training Epoch: 25 [3328/9756]	Loss: 0.1412	LR: 0.004000
Training Epoch: 25 [3584/9756]	Loss: 0.1724	LR: 0.004000
Training Epoch: 25 [3840/9756]	Loss: 0.2027	LR: 0.004000
Training Epoch: 25 [4096/9756]	Loss: 0.1445	LR: 0.004000
Training Epoch: 25 [4352/9756]	Loss: 0.1070	LR: 0.004000
Training Epoch: 25 [4608/9756]	Loss: 0.1277	LR: 0.004000
Training Epoch: 25 [4864/9756]	Loss: 0.1238	LR: 0.004000
Training Epoch: 25 [5120/9756]	Loss: 0.1568	LR: 0.004000
Training Epoch: 25 [5376/9756]	Loss: 0.2071	LR: 0.004000
Training Epoch: 25 [5632/9756]	Loss: 0.1336	LR: 0.004000
Training Epoch: 25 [5888/9756]	Loss: 0.1653	LR: 0.004000
Training Epoch: 25 [6144/9756]	Loss: 0.1544	LR: 0.004000
Training Epoch: 25 [6400/9756]	Loss: 0.1843	LR: 0.004000
Training Epoch: 25 [6656/9756]	Loss: 0.1753	LR: 0.004000
Training Epoch: 25 [6912/9756]	Loss: 0.1831	LR: 0.004000
Training Epoch: 25 [7168/9756]	Loss: 0.1860	LR: 0.004000
Training Epoch: 25 [7424/9756]	Loss: 0.1914	LR: 0.004000
Training Epoch: 25 [7680/9756]	Loss: 0.1700	LR: 0.004000
Training Epoch: 25 [7936/9756]	Loss: 0.1982	LR: 0.004000
Training Epoch: 25 [8192/9756]	Loss: 0.1480	LR: 0.004000
Training Epoch: 25 [8448/9756]	Loss: 0.1803	LR: 0.004000
Training Epoch: 25 [8704/9756]	Loss: 0.2006	LR: 0.004000
Training Epoch: 25 [8960/9756]	Loss: 0.1430	LR: 0.004000
Training Epoch: 25 [9216/9756]	Loss: 0.1517	LR: 0.004000
Training Epoch: 25 [9472/9756]	Loss: 0.1773	LR: 0.004000
Training Epoch: 25 [9728/9756]	Loss: 0.1605	LR: 0.004000
Training Epoch: 25 [9756/9756]	Loss: 0.1985	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1669, Train Accuracy: 0.9305
Epoch 25 training time consumed: 141.63s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9303, Time consumed:7.85s
Training Epoch: 26 [256/9756]	Loss: 0.2388	LR: 0.004000
Training Epoch: 26 [512/9756]	Loss: 0.1903	LR: 0.004000
Training Epoch: 26 [768/9756]	Loss: 0.1743	LR: 0.004000
Training Epoch: 26 [1024/9756]	Loss: 0.1576	LR: 0.004000
Training Epoch: 26 [1280/9756]	Loss: 0.2162	LR: 0.004000
Training Epoch: 26 [1536/9756]	Loss: 0.1587	LR: 0.004000
Training Epoch: 26 [1792/9756]	Loss: 0.1577	LR: 0.004000
Training Epoch: 26 [2048/9756]	Loss: 0.1572	LR: 0.004000
Training Epoch: 26 [2304/9756]	Loss: 0.1718	LR: 0.004000
Training Epoch: 26 [2560/9756]	Loss: 0.1345	LR: 0.004000
Training Epoch: 26 [2816/9756]	Loss: 0.1810	LR: 0.004000
Training Epoch: 26 [3072/9756]	Loss: 0.1622	LR: 0.004000
Training Epoch: 26 [3328/9756]	Loss: 0.1038	LR: 0.004000
Training Epoch: 26 [3584/9756]	Loss: 0.1392	LR: 0.004000
Training Epoch: 26 [3840/9756]	Loss: 0.1499	LR: 0.004000
Training Epoch: 26 [4096/9756]	Loss: 0.1430	LR: 0.004000
Training Epoch: 26 [4352/9756]	Loss: 0.1700	LR: 0.004000
Training Epoch: 26 [4608/9756]	Loss: 0.1752	LR: 0.004000
Training Epoch: 26 [4864/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 26 [5120/9756]	Loss: 0.0839	LR: 0.004000
Training Epoch: 26 [5376/9756]	Loss: 0.1725	LR: 0.004000
Training Epoch: 26 [5632/9756]	Loss: 0.1733	LR: 0.004000
Training Epoch: 26 [5888/9756]	Loss: 0.1307	LR: 0.004000
Training Epoch: 26 [6144/9756]	Loss: 0.2045	LR: 0.004000
Training Epoch: 26 [6400/9756]	Loss: 0.1937	LR: 0.004000
Training Epoch: 26 [6656/9756]	Loss: 0.1539	LR: 0.004000
Training Epoch: 26 [6912/9756]	Loss: 0.1513	LR: 0.004000
Training Epoch: 26 [7168/9756]	Loss: 0.1687	LR: 0.004000
Training Epoch: 26 [7424/9756]	Loss: 0.1561	LR: 0.004000
Training Epoch: 26 [7680/9756]	Loss: 0.1415	LR: 0.004000
Training Epoch: 26 [7936/9756]	Loss: 0.1407	LR: 0.004000
Training Epoch: 26 [8192/9756]	Loss: 0.1667	LR: 0.004000
Training Epoch: 26 [8448/9756]	Loss: 0.1413	LR: 0.004000
Training Epoch: 26 [8704/9756]	Loss: 0.1665	LR: 0.004000
Training Epoch: 26 [8960/9756]	Loss: 0.2154	LR: 0.004000
Training Epoch: 26 [9216/9756]	Loss: 0.1749	LR: 0.004000
Training Epoch: 26 [9472/9756]	Loss: 0.1659	LR: 0.004000
Training Epoch: 26 [9728/9756]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [9756/9756]	Loss: 0.2591	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1624, Train Accuracy: 0.9312
Epoch 26 training time consumed: 141.27s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:7.92s
Training Epoch: 27 [256/9756]	Loss: 0.1473	LR: 0.004000
Training Epoch: 27 [512/9756]	Loss: 0.1650	LR: 0.004000
Training Epoch: 27 [768/9756]	Loss: 0.1758	LR: 0.004000
Training Epoch: 27 [1024/9756]	Loss: 0.1615	LR: 0.004000
Training Epoch: 27 [1280/9756]	Loss: 0.2031	LR: 0.004000
Training Epoch: 27 [1536/9756]	Loss: 0.1559	LR: 0.004000
Training Epoch: 27 [1792/9756]	Loss: 0.1946	LR: 0.004000
Training Epoch: 27 [2048/9756]	Loss: 0.1772	LR: 0.004000
Training Epoch: 27 [2304/9756]	Loss: 0.1504	LR: 0.004000
Training Epoch: 27 [2560/9756]	Loss: 0.2213	LR: 0.004000
Training Epoch: 27 [2816/9756]	Loss: 0.1657	LR: 0.004000
Training Epoch: 27 [3072/9756]	Loss: 0.1609	LR: 0.004000
Training Epoch: 27 [3328/9756]	Loss: 0.1923	LR: 0.004000
Training Epoch: 27 [3584/9756]	Loss: 0.1342	LR: 0.004000
Training Epoch: 27 [3840/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 27 [4096/9756]	Loss: 0.1713	LR: 0.004000
Training Epoch: 27 [4352/9756]	Loss: 0.1638	LR: 0.004000
Training Epoch: 27 [4608/9756]	Loss: 0.1511	LR: 0.004000
Training Epoch: 27 [4864/9756]	Loss: 0.1635	LR: 0.004000
Training Epoch: 27 [5120/9756]	Loss: 0.1588	LR: 0.004000
Training Epoch: 27 [5376/9756]	Loss: 0.1740	LR: 0.004000
Training Epoch: 27 [5632/9756]	Loss: 0.1797	LR: 0.004000
Training Epoch: 27 [5888/9756]	Loss: 0.1415	LR: 0.004000
Training Epoch: 27 [6144/9756]	Loss: 0.2308	LR: 0.004000
Training Epoch: 27 [6400/9756]	Loss: 0.1390	LR: 0.004000
Training Epoch: 27 [6656/9756]	Loss: 0.2016	LR: 0.004000
Training Epoch: 27 [6912/9756]	Loss: 0.2059	LR: 0.004000
Training Epoch: 27 [7168/9756]	Loss: 0.1944	LR: 0.004000
Training Epoch: 27 [7424/9756]	Loss: 0.1273	LR: 0.004000
Training Epoch: 27 [7680/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 27 [7936/9756]	Loss: 0.1746	LR: 0.004000
Training Epoch: 27 [8192/9756]	Loss: 0.1414	LR: 0.004000
Training Epoch: 27 [8448/9756]	Loss: 0.1893	LR: 0.004000
Training Epoch: 27 [8704/9756]	Loss: 0.1649	LR: 0.004000
Training Epoch: 27 [8960/9756]	Loss: 0.1681	LR: 0.004000
Training Epoch: 27 [9216/9756]	Loss: 0.1920	LR: 0.004000
Training Epoch: 27 [9472/9756]	Loss: 0.1947	LR: 0.004000
Training Epoch: 27 [9728/9756]	Loss: 0.1626	LR: 0.004000
Training Epoch: 27 [9756/9756]	Loss: 0.2474	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1715, Train Accuracy: 0.9261
Epoch 27 training time consumed: 140.80s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0006, Accuracy: 0.9482, Time consumed:8.20s
Saving weights file to checkpoint/retrain/ResNet18/Saturday_26_July_2025_10h_01m_18s/ResNet18-MUCAC-seed9-ret25-27-best.pth
Training Epoch: 28 [256/9756]	Loss: 0.1604	LR: 0.004000
Training Epoch: 28 [512/9756]	Loss: 0.1443	LR: 0.004000
Training Epoch: 28 [768/9756]	Loss: 0.1582	LR: 0.004000
Training Epoch: 28 [1024/9756]	Loss: 0.1681	LR: 0.004000
Training Epoch: 28 [1280/9756]	Loss: 0.1513	LR: 0.004000
Training Epoch: 28 [1536/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 28 [1792/9756]	Loss: 0.1831	LR: 0.004000
Training Epoch: 28 [2048/9756]	Loss: 0.1819	LR: 0.004000
Training Epoch: 28 [2304/9756]	Loss: 0.1371	LR: 0.004000
Training Epoch: 28 [2560/9756]	Loss: 0.1905	LR: 0.004000
Training Epoch: 28 [2816/9756]	Loss: 0.1159	LR: 0.004000
Training Epoch: 28 [3072/9756]	Loss: 0.1735	LR: 0.004000
Training Epoch: 28 [3328/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 28 [3584/9756]	Loss: 0.1894	LR: 0.004000
Training Epoch: 28 [3840/9756]	Loss: 0.1154	LR: 0.004000
Training Epoch: 28 [4096/9756]	Loss: 0.1689	LR: 0.004000
Training Epoch: 28 [4352/9756]	Loss: 0.1592	LR: 0.004000
Training Epoch: 28 [4608/9756]	Loss: 0.1582	LR: 0.004000
Training Epoch: 28 [4864/9756]	Loss: 0.1370	LR: 0.004000
Training Epoch: 28 [5120/9756]	Loss: 0.1273	LR: 0.004000
Training Epoch: 28 [5376/9756]	Loss: 0.1506	LR: 0.004000
Training Epoch: 28 [5632/9756]	Loss: 0.1478	LR: 0.004000
Training Epoch: 28 [5888/9756]	Loss: 0.2135	LR: 0.004000
Training Epoch: 28 [6144/9756]	Loss: 0.1343	LR: 0.004000
Training Epoch: 28 [6400/9756]	Loss: 0.1211	LR: 0.004000
Training Epoch: 28 [6656/9756]	Loss: 0.1544	LR: 0.004000
Training Epoch: 28 [6912/9756]	Loss: 0.1215	LR: 0.004000
Training Epoch: 28 [7168/9756]	Loss: 0.1331	LR: 0.004000
Training Epoch: 28 [7424/9756]	Loss: 0.2027	LR: 0.004000
Training Epoch: 28 [7680/9756]	Loss: 0.1644	LR: 0.004000
Training Epoch: 28 [7936/9756]	Loss: 0.2273	LR: 0.004000
Training Epoch: 28 [8192/9756]	Loss: 0.2090	LR: 0.004000
Training Epoch: 28 [8448/9756]	Loss: 0.1479	LR: 0.004000
Training Epoch: 28 [8704/9756]	Loss: 0.1604	LR: 0.004000
Training Epoch: 28 [8960/9756]	Loss: 0.1268	LR: 0.004000
Training Epoch: 28 [9216/9756]	Loss: 0.1786	LR: 0.004000
Training Epoch: 28 [9472/9756]	Loss: 0.1395	LR: 0.004000
Training Epoch: 28 [9728/9756]	Loss: 0.1815	LR: 0.004000
Training Epoch: 28 [9756/9756]	Loss: 0.4492	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1603, Train Accuracy: 0.9339
Epoch 28 training time consumed: 140.91s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0006, Accuracy: 0.9380, Time consumed:8.07s
Training Epoch: 29 [256/9756]	Loss: 0.1460	LR: 0.004000
Training Epoch: 29 [512/9756]	Loss: 0.1449	LR: 0.004000
Training Epoch: 29 [768/9756]	Loss: 0.1229	LR: 0.004000
Training Epoch: 29 [1024/9756]	Loss: 0.1265	LR: 0.004000
Training Epoch: 29 [1280/9756]	Loss: 0.1521	LR: 0.004000
Training Epoch: 29 [1536/9756]	Loss: 0.1361	LR: 0.004000
Training Epoch: 29 [1792/9756]	Loss: 0.1760	LR: 0.004000
Training Epoch: 29 [2048/9756]	Loss: 0.2177	LR: 0.004000
Training Epoch: 29 [2304/9756]	Loss: 0.1497	LR: 0.004000
Training Epoch: 29 [2560/9756]	Loss: 0.1177	LR: 0.004000
Training Epoch: 29 [2816/9756]	Loss: 0.1434	LR: 0.004000
Training Epoch: 29 [3072/9756]	Loss: 0.1666	LR: 0.004000
Training Epoch: 29 [3328/9756]	Loss: 0.2319	LR: 0.004000
Training Epoch: 29 [3584/9756]	Loss: 0.1671	LR: 0.004000
Training Epoch: 29 [3840/9756]	Loss: 0.1743	LR: 0.004000
Training Epoch: 29 [4096/9756]	Loss: 0.2167	LR: 0.004000
Training Epoch: 29 [4352/9756]	Loss: 0.1373	LR: 0.004000
Training Epoch: 29 [4608/9756]	Loss: 0.1480	LR: 0.004000
Training Epoch: 29 [4864/9756]	Loss: 0.1379	LR: 0.004000
Training Epoch: 29 [5120/9756]	Loss: 0.1531	LR: 0.004000
Training Epoch: 29 [5376/9756]	Loss: 0.1658	LR: 0.004000
Training Epoch: 29 [5632/9756]	Loss: 0.1780	LR: 0.004000
Training Epoch: 29 [5888/9756]	Loss: 0.1391	LR: 0.004000
Training Epoch: 29 [6144/9756]	Loss: 0.1829	LR: 0.004000
Training Epoch: 29 [6400/9756]	Loss: 0.2199	LR: 0.004000
Training Epoch: 29 [6656/9756]	Loss: 0.1834	LR: 0.004000
Training Epoch: 29 [6912/9756]	Loss: 0.1754	LR: 0.004000
Training Epoch: 29 [7168/9756]	Loss: 0.1933	LR: 0.004000
Training Epoch: 29 [7424/9756]	Loss: 0.1633	LR: 0.004000
Training Epoch: 29 [7680/9756]	Loss: 0.1870	LR: 0.004000
Training Epoch: 29 [7936/9756]	Loss: 0.1160	LR: 0.004000
Training Epoch: 29 [8192/9756]	Loss: 0.1496	LR: 0.004000
Training Epoch: 29 [8448/9756]	Loss: 0.1400	LR: 0.004000
Training Epoch: 29 [8704/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 29 [8960/9756]	Loss: 0.1334	LR: 0.004000
Training Epoch: 29 [9216/9756]	Loss: 0.1452	LR: 0.004000
Training Epoch: 29 [9472/9756]	Loss: 0.1335	LR: 0.004000
Training Epoch: 29 [9728/9756]	Loss: 0.1355	LR: 0.004000
Training Epoch: 29 [9756/9756]	Loss: 0.2014	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1589, Train Accuracy: 0.9334
Epoch 29 training time consumed: 141.19s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9400, Time consumed:7.86s
Training Epoch: 30 [256/9756]	Loss: 0.1490	LR: 0.004000
Training Epoch: 30 [512/9756]	Loss: 0.1545	LR: 0.004000
Training Epoch: 30 [768/9756]	Loss: 0.1211	LR: 0.004000
Training Epoch: 30 [1024/9756]	Loss: 0.1507	LR: 0.004000
Training Epoch: 30 [1280/9756]	Loss: 0.1397	LR: 0.004000
Training Epoch: 30 [1536/9756]	Loss: 0.1659	LR: 0.004000
Training Epoch: 30 [1792/9756]	Loss: 0.1270	LR: 0.004000
Training Epoch: 30 [2048/9756]	Loss: 0.1400	LR: 0.004000
Training Epoch: 30 [2304/9756]	Loss: 0.1368	LR: 0.004000
Training Epoch: 30 [2560/9756]	Loss: 0.1447	LR: 0.004000
Training Epoch: 30 [2816/9756]	Loss: 0.1346	LR: 0.004000
Training Epoch: 30 [3072/9756]	Loss: 0.1136	LR: 0.004000
Training Epoch: 30 [3328/9756]	Loss: 0.1731	LR: 0.004000
Training Epoch: 30 [3584/9756]	Loss: 0.1888	LR: 0.004000
Training Epoch: 30 [3840/9756]	Loss: 0.1564	LR: 0.004000
Training Epoch: 30 [4096/9756]	Loss: 0.1389	LR: 0.004000
Training Epoch: 30 [4352/9756]	Loss: 0.1639	LR: 0.004000
Training Epoch: 30 [4608/9756]	Loss: 0.1908	LR: 0.004000
Training Epoch: 30 [4864/9756]	Loss: 0.1678	LR: 0.004000
Training Epoch: 30 [5120/9756]	Loss: 0.1633	LR: 0.004000
Training Epoch: 30 [5376/9756]	Loss: 0.1144	LR: 0.004000
Training Epoch: 30 [5632/9756]	Loss: 0.2167	LR: 0.004000
Training Epoch: 30 [5888/9756]	Loss: 0.1543	LR: 0.004000
Training Epoch: 30 [6144/9756]	Loss: 0.1580	LR: 0.004000
Training Epoch: 30 [6400/9756]	Loss: 0.1617	LR: 0.004000
Training Epoch: 30 [6656/9756]	Loss: 0.2052	LR: 0.004000
Training Epoch: 30 [6912/9756]	Loss: 0.1796	LR: 0.004000
Training Epoch: 30 [7168/9756]	Loss: 0.1396	LR: 0.004000
Training Epoch: 30 [7424/9756]	Loss: 0.1382	LR: 0.004000
Training Epoch: 30 [7680/9756]	Loss: 0.1752	LR: 0.004000
Training Epoch: 30 [7936/9756]	Loss: 0.1506	LR: 0.004000
Training Epoch: 30 [8192/9756]	Loss: 0.2041	LR: 0.004000
Training Epoch: 30 [8448/9756]	Loss: 0.1548	LR: 0.004000
Training Epoch: 30 [8704/9756]	Loss: 0.1959	LR: 0.004000
Training Epoch: 30 [8960/9756]	Loss: 0.1839	LR: 0.004000
Training Epoch: 30 [9216/9756]	Loss: 0.1743	LR: 0.004000
Training Epoch: 30 [9472/9756]	Loss: 0.1378	LR: 0.004000
Training Epoch: 30 [9728/9756]	Loss: 0.1607	LR: 0.004000
Training Epoch: 30 [9756/9756]	Loss: 0.1076	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1584, Train Accuracy: 0.9333
Epoch 30 training time consumed: 140.89s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:7.94s
Training Epoch: 31 [256/9756]	Loss: 0.1327	LR: 0.004000
Training Epoch: 31 [512/9756]	Loss: 0.2088	LR: 0.004000
Training Epoch: 31 [768/9756]	Loss: 0.1386	LR: 0.004000
Training Epoch: 31 [1024/9756]	Loss: 0.1358	LR: 0.004000
Training Epoch: 31 [1280/9756]	Loss: 0.1162	LR: 0.004000
Training Epoch: 31 [1536/9756]	Loss: 0.1746	LR: 0.004000
Training Epoch: 31 [1792/9756]	Loss: 0.1402	LR: 0.004000
Training Epoch: 31 [2048/9756]	Loss: 0.1796	LR: 0.004000
Training Epoch: 31 [2304/9756]	Loss: 0.1878	LR: 0.004000
Training Epoch: 31 [2560/9756]	Loss: 0.1510	LR: 0.004000
Training Epoch: 31 [2816/9756]	Loss: 0.1512	LR: 0.004000
Training Epoch: 31 [3072/9756]	Loss: 0.1663	LR: 0.004000
Training Epoch: 31 [3328/9756]	Loss: 0.1247	LR: 0.004000
Training Epoch: 31 [3584/9756]	Loss: 0.1730	LR: 0.004000
Training Epoch: 31 [3840/9756]	Loss: 0.1429	LR: 0.004000
Training Epoch: 31 [4096/9756]	Loss: 0.1701	LR: 0.004000
Training Epoch: 31 [4352/9756]	Loss: 0.1054	LR: 0.004000
Training Epoch: 31 [4608/9756]	Loss: 0.1289	LR: 0.004000
Training Epoch: 31 [4864/9756]	Loss: 0.1783	LR: 0.004000
Training Epoch: 31 [5120/9756]	Loss: 0.1838	LR: 0.004000
Training Epoch: 31 [5376/9756]	Loss: 0.1368	LR: 0.004000
Training Epoch: 31 [5632/9756]	Loss: 0.1263	LR: 0.004000
Training Epoch: 31 [5888/9756]	Loss: 0.0954	LR: 0.004000
Training Epoch: 31 [6144/9756]	Loss: 0.1265	LR: 0.004000
Training Epoch: 31 [6400/9756]	Loss: 0.1433	LR: 0.004000
Training Epoch: 31 [6656/9756]	Loss: 0.1440	LR: 0.004000
Training Epoch: 31 [6912/9756]	Loss: 0.2167	LR: 0.004000
Training Epoch: 31 [7168/9756]	Loss: 0.1429	LR: 0.004000
Training Epoch: 31 [7424/9756]	Loss: 0.1455	LR: 0.004000
Training Epoch: 31 [7680/9756]	Loss: 0.1420	LR: 0.004000
Training Epoch: 31 [7936/9756]	Loss: 0.1506	LR: 0.004000
Training Epoch: 31 [8192/9756]	Loss: 0.1091	LR: 0.004000
Training Epoch: 31 [8448/9756]	Loss: 0.1515	LR: 0.004000
Training Epoch: 31 [8704/9756]	Loss: 0.1516	LR: 0.004000
Training Epoch: 31 [8960/9756]	Loss: 0.2584	LR: 0.004000
Training Epoch: 31 [9216/9756]	Loss: 0.1573	LR: 0.004000
Training Epoch: 31 [9472/9756]	Loss: 0.1458	LR: 0.004000
Training Epoch: 31 [9728/9756]	Loss: 0.1120	LR: 0.004000
Training Epoch: 31 [9756/9756]	Loss: 0.1809	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1513, Train Accuracy: 0.9374
Epoch 31 training time consumed: 140.61s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0008, Accuracy: 0.9283, 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: 93.57638549804688
Retain Accuracy: 91.7238998413086
Zero-Retain Forget (ZRF): 0.7946021556854248
Membership Inference Attack (MIA): 0.32954545454545453
Forget vs Retain Membership Inference Attack (MIA): 0.5078864353312302
Forget vs Test Membership Inference Attack (MIA): 0.580441640378549
Test vs Retain Membership Inference Attack (MIA): 0.549636803874092
Train vs Test Membership Inference Attack (MIA): 0.5217917675544794
Forget Set Accuracy (Df): 88.15104675292969
Method Execution Time: 5785.15 seconds
