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

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

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

📊 Updated class distribution:
Retain set:
  Class 0: 5679
  Class 1: 4605
Forget set:
  Class 0: 132
  Class 1: 132
./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 [256/10284]	Loss: 0.6987	LR: 0.000000
Training Epoch: 1 [512/10284]	Loss: 0.6917	LR: 0.002439
Training Epoch: 1 [768/10284]	Loss: 0.6859	LR: 0.004878
Training Epoch: 1 [1024/10284]	Loss: 0.6979	LR: 0.007317
Training Epoch: 1 [1280/10284]	Loss: 0.6997	LR: 0.009756
Training Epoch: 1 [1536/10284]	Loss: 0.7233	LR: 0.012195
Training Epoch: 1 [1792/10284]	Loss: 0.6736	LR: 0.014634
Training Epoch: 1 [2048/10284]	Loss: 0.6876	LR: 0.017073
Training Epoch: 1 [2304/10284]	Loss: 0.6630	LR: 0.019512
Training Epoch: 1 [2560/10284]	Loss: 0.6679	LR: 0.021951
Training Epoch: 1 [2816/10284]	Loss: 0.6849	LR: 0.024390
Training Epoch: 1 [3072/10284]	Loss: 0.7056	LR: 0.026829
Training Epoch: 1 [3328/10284]	Loss: 0.7419	LR: 0.029268
Training Epoch: 1 [3584/10284]	Loss: 0.6726	LR: 0.031707
Training Epoch: 1 [3840/10284]	Loss: 0.7198	LR: 0.034146
Training Epoch: 1 [4096/10284]	Loss: 0.7000	LR: 0.036585
Training Epoch: 1 [4352/10284]	Loss: 0.9335	LR: 0.039024
Training Epoch: 1 [4608/10284]	Loss: 2.1022	LR: 0.041463
Training Epoch: 1 [4864/10284]	Loss: 0.9356	LR: 0.043902
Training Epoch: 1 [5120/10284]	Loss: 1.8052	LR: 0.046341
Training Epoch: 1 [5376/10284]	Loss: 1.3494	LR: 0.048780
Training Epoch: 1 [5632/10284]	Loss: 0.9529	LR: 0.051220
Training Epoch: 1 [5888/10284]	Loss: 1.7271	LR: 0.053659
Training Epoch: 1 [6144/10284]	Loss: 0.8869	LR: 0.056098
Training Epoch: 1 [6400/10284]	Loss: 1.1200	LR: 0.058537
Training Epoch: 1 [6656/10284]	Loss: 1.8578	LR: 0.060976
Training Epoch: 1 [6912/10284]	Loss: 1.1154	LR: 0.063415
Training Epoch: 1 [7168/10284]	Loss: 0.9145	LR: 0.065854
Training Epoch: 1 [7424/10284]	Loss: 1.5541	LR: 0.068293
Training Epoch: 1 [7680/10284]	Loss: 0.9960	LR: 0.070732
Training Epoch: 1 [7936/10284]	Loss: 0.7959	LR: 0.073171
Training Epoch: 1 [8192/10284]	Loss: 0.9451	LR: 0.075610
Training Epoch: 1 [8448/10284]	Loss: 0.9432	LR: 0.078049
Training Epoch: 1 [8704/10284]	Loss: 0.7103	LR: 0.080488
Training Epoch: 1 [8960/10284]	Loss: 0.9791	LR: 0.082927
Training Epoch: 1 [9216/10284]	Loss: 0.9584	LR: 0.085366
Training Epoch: 1 [9472/10284]	Loss: 0.7256	LR: 0.087805
Training Epoch: 1 [9728/10284]	Loss: 0.6840	LR: 0.090244
Training Epoch: 1 [9984/10284]	Loss: 0.7155	LR: 0.092683
Training Epoch: 1 [10240/10284]	Loss: 0.8631	LR: 0.095122
Training Epoch: 1 [10284/10284]	Loss: 1.1086	LR: 0.097561
Epoch 1 - Average Train Loss: 0.9428, Train Accuracy: 0.5188
Epoch 1 training time consumed: 606.32s
Evaluating Network.....
Test set: Epoch: 1, Average loss: 0.4206, Accuracy: 0.4450, Time consumed:8.25s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-1-best.pth
Training Epoch: 2 [256/10284]	Loss: 0.7362	LR: 0.100000
Training Epoch: 2 [512/10284]	Loss: 0.9972	LR: 0.100000
Training Epoch: 2 [768/10284]	Loss: 1.0961	LR: 0.100000
Training Epoch: 2 [1024/10284]	Loss: 0.9377	LR: 0.100000
Training Epoch: 2 [1280/10284]	Loss: 0.7155	LR: 0.100000
Training Epoch: 2 [1536/10284]	Loss: 0.6921	LR: 0.100000
Training Epoch: 2 [1792/10284]	Loss: 0.7638	LR: 0.100000
Training Epoch: 2 [2048/10284]	Loss: 0.7207	LR: 0.100000
Training Epoch: 2 [2304/10284]	Loss: 0.6858	LR: 0.100000
Training Epoch: 2 [2560/10284]	Loss: 0.6976	LR: 0.100000
Training Epoch: 2 [2816/10284]	Loss: 0.7345	LR: 0.100000
Training Epoch: 2 [3072/10284]	Loss: 0.7722	LR: 0.100000
Training Epoch: 2 [3328/10284]	Loss: 0.7237	LR: 0.100000
Training Epoch: 2 [3584/10284]	Loss: 0.7486	LR: 0.100000
Training Epoch: 2 [3840/10284]	Loss: 0.7138	LR: 0.100000
Training Epoch: 2 [4096/10284]	Loss: 0.7066	LR: 0.100000
Training Epoch: 2 [4352/10284]	Loss: 0.7442	LR: 0.100000
Training Epoch: 2 [4608/10284]	Loss: 0.7088	LR: 0.100000
Training Epoch: 2 [4864/10284]	Loss: 0.6984	LR: 0.100000
Training Epoch: 2 [5120/10284]	Loss: 0.6944	LR: 0.100000
Training Epoch: 2 [5376/10284]	Loss: 0.7393	LR: 0.100000
Training Epoch: 2 [5632/10284]	Loss: 0.6853	LR: 0.100000
Training Epoch: 2 [5888/10284]	Loss: 0.7482	LR: 0.100000
Training Epoch: 2 [6144/10284]	Loss: 0.7530	LR: 0.100000
Training Epoch: 2 [6400/10284]	Loss: 0.7400	LR: 0.100000
Training Epoch: 2 [6656/10284]	Loss: 0.6914	LR: 0.100000
Training Epoch: 2 [6912/10284]	Loss: 0.6944	LR: 0.100000
Training Epoch: 2 [7168/10284]	Loss: 0.7256	LR: 0.100000
Training Epoch: 2 [7424/10284]	Loss: 0.7157	LR: 0.100000
Training Epoch: 2 [7680/10284]	Loss: 0.7497	LR: 0.100000
Training Epoch: 2 [7936/10284]	Loss: 0.6999	LR: 0.100000
Training Epoch: 2 [8192/10284]	Loss: 0.7007	LR: 0.100000
Training Epoch: 2 [8448/10284]	Loss: 0.6953	LR: 0.100000
Training Epoch: 2 [8704/10284]	Loss: 0.6862	LR: 0.100000
Training Epoch: 2 [8960/10284]	Loss: 0.7035	LR: 0.100000
Training Epoch: 2 [9216/10284]	Loss: 0.6687	LR: 0.100000
Training Epoch: 2 [9472/10284]	Loss: 0.6811	LR: 0.100000
Training Epoch: 2 [9728/10284]	Loss: 0.6806	LR: 0.100000
Training Epoch: 2 [9984/10284]	Loss: 0.6935	LR: 0.100000
Training Epoch: 2 [10240/10284]	Loss: 0.6945	LR: 0.100000
Training Epoch: 2 [10284/10284]	Loss: 0.7008	LR: 0.100000
Epoch 2 - Average Train Loss: 0.7357, Train Accuracy: 0.5210
Epoch 2 training time consumed: 149.03s
Evaluating Network.....
Test set: Epoch: 2, Average loss: 0.0032, Accuracy: 0.4896, Time consumed:8.01s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-2-best.pth
Training Epoch: 3 [256/10284]	Loss: 0.6985	LR: 0.100000
Training Epoch: 3 [512/10284]	Loss: 0.7267	LR: 0.100000
Training Epoch: 3 [768/10284]	Loss: 0.6704	LR: 0.100000
Training Epoch: 3 [1024/10284]	Loss: 0.6964	LR: 0.100000
Training Epoch: 3 [1280/10284]	Loss: 0.6968	LR: 0.100000
Training Epoch: 3 [1536/10284]	Loss: 0.6752	LR: 0.100000
Training Epoch: 3 [1792/10284]	Loss: 0.7157	LR: 0.100000
Training Epoch: 3 [2048/10284]	Loss: 0.6782	LR: 0.100000
Training Epoch: 3 [2304/10284]	Loss: 0.6843	LR: 0.100000
Training Epoch: 3 [2560/10284]	Loss: 0.6775	LR: 0.100000
Training Epoch: 3 [2816/10284]	Loss: 0.6707	LR: 0.100000
Training Epoch: 3 [3072/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 3 [3328/10284]	Loss: 0.6855	LR: 0.100000
Training Epoch: 3 [3584/10284]	Loss: 0.6846	LR: 0.100000
Training Epoch: 3 [3840/10284]	Loss: 0.6620	LR: 0.100000
Training Epoch: 3 [4096/10284]	Loss: 0.6772	LR: 0.100000
Training Epoch: 3 [4352/10284]	Loss: 0.6866	LR: 0.100000
Training Epoch: 3 [4608/10284]	Loss: 0.6912	LR: 0.100000
Training Epoch: 3 [4864/10284]	Loss: 0.7159	LR: 0.100000
Training Epoch: 3 [5120/10284]	Loss: 0.6796	LR: 0.100000
Training Epoch: 3 [5376/10284]	Loss: 0.6839	LR: 0.100000
Training Epoch: 3 [5632/10284]	Loss: 0.6768	LR: 0.100000
Training Epoch: 3 [5888/10284]	Loss: 0.6627	LR: 0.100000
Training Epoch: 3 [6144/10284]	Loss: 0.6823	LR: 0.100000
Training Epoch: 3 [6400/10284]	Loss: 0.6708	LR: 0.100000
Training Epoch: 3 [6656/10284]	Loss: 0.6795	LR: 0.100000
Training Epoch: 3 [6912/10284]	Loss: 0.6678	LR: 0.100000
Training Epoch: 3 [7168/10284]	Loss: 0.7358	LR: 0.100000
Training Epoch: 3 [7424/10284]	Loss: 0.6866	LR: 0.100000
Training Epoch: 3 [7680/10284]	Loss: 0.6931	LR: 0.100000
Training Epoch: 3 [7936/10284]	Loss: 0.6757	LR: 0.100000
Training Epoch: 3 [8192/10284]	Loss: 0.6742	LR: 0.100000
Training Epoch: 3 [8448/10284]	Loss: 0.7005	LR: 0.100000
Training Epoch: 3 [8704/10284]	Loss: 0.6771	LR: 0.100000
Training Epoch: 3 [8960/10284]	Loss: 0.6786	LR: 0.100000
Training Epoch: 3 [9216/10284]	Loss: 0.6590	LR: 0.100000
Training Epoch: 3 [9472/10284]	Loss: 0.6795	LR: 0.100000
Training Epoch: 3 [9728/10284]	Loss: 0.6578	LR: 0.100000
Training Epoch: 3 [9984/10284]	Loss: 0.6761	LR: 0.100000
Training Epoch: 3 [10240/10284]	Loss: 0.6663	LR: 0.100000
Training Epoch: 3 [10284/10284]	Loss: 0.6620	LR: 0.100000
Epoch 3 - Average Train Loss: 0.6831, Train Accuracy: 0.5617
Epoch 3 training time consumed: 148.68s
Evaluating Network.....
Test set: Epoch: 3, Average loss: 0.0030, Accuracy: 0.5714, Time consumed:7.84s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-3-best.pth
Training Epoch: 4 [256/10284]	Loss: 0.6993	LR: 0.100000
Training Epoch: 4 [512/10284]	Loss: 0.6896	LR: 0.100000
Training Epoch: 4 [768/10284]	Loss: 0.6863	LR: 0.100000
Training Epoch: 4 [1024/10284]	Loss: 0.6890	LR: 0.100000
Training Epoch: 4 [1280/10284]	Loss: 0.6583	LR: 0.100000
Training Epoch: 4 [1536/10284]	Loss: 0.6615	LR: 0.100000
Training Epoch: 4 [1792/10284]	Loss: 0.6708	LR: 0.100000
Training Epoch: 4 [2048/10284]	Loss: 0.6623	LR: 0.100000
Training Epoch: 4 [2304/10284]	Loss: 0.6695	LR: 0.100000
Training Epoch: 4 [2560/10284]	Loss: 0.7114	LR: 0.100000
Training Epoch: 4 [2816/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 4 [3072/10284]	Loss: 0.6853	LR: 0.100000
Training Epoch: 4 [3328/10284]	Loss: 0.6911	LR: 0.100000
Training Epoch: 4 [3584/10284]	Loss: 0.6905	LR: 0.100000
Training Epoch: 4 [3840/10284]	Loss: 0.6734	LR: 0.100000
Training Epoch: 4 [4096/10284]	Loss: 0.6821	LR: 0.100000
Training Epoch: 4 [4352/10284]	Loss: 0.6780	LR: 0.100000
Training Epoch: 4 [4608/10284]	Loss: 0.6680	LR: 0.100000
Training Epoch: 4 [4864/10284]	Loss: 0.6710	LR: 0.100000
Training Epoch: 4 [5120/10284]	Loss: 0.6785	LR: 0.100000
Training Epoch: 4 [5376/10284]	Loss: 0.6901	LR: 0.100000
Training Epoch: 4 [5632/10284]	Loss: 0.6568	LR: 0.100000
Training Epoch: 4 [5888/10284]	Loss: 0.6658	LR: 0.100000
Training Epoch: 4 [6144/10284]	Loss: 0.7009	LR: 0.100000
Training Epoch: 4 [6400/10284]	Loss: 0.6553	LR: 0.100000
Training Epoch: 4 [6656/10284]	Loss: 0.6719	LR: 0.100000
Training Epoch: 4 [6912/10284]	Loss: 0.6830	LR: 0.100000
Training Epoch: 4 [7168/10284]	Loss: 0.6713	LR: 0.100000
Training Epoch: 4 [7424/10284]	Loss: 0.6489	LR: 0.100000
Training Epoch: 4 [7680/10284]	Loss: 0.6565	LR: 0.100000
Training Epoch: 4 [7936/10284]	Loss: 0.6529	LR: 0.100000
Training Epoch: 4 [8192/10284]	Loss: 0.7067	LR: 0.100000
Training Epoch: 4 [8448/10284]	Loss: 0.6736	LR: 0.100000
Training Epoch: 4 [8704/10284]	Loss: 0.6692	LR: 0.100000
Training Epoch: 4 [8960/10284]	Loss: 0.6945	LR: 0.100000
Training Epoch: 4 [9216/10284]	Loss: 0.6774	LR: 0.100000
Training Epoch: 4 [9472/10284]	Loss: 0.6789	LR: 0.100000
Training Epoch: 4 [9728/10284]	Loss: 0.6865	LR: 0.100000
Training Epoch: 4 [9984/10284]	Loss: 0.6754	LR: 0.100000
Training Epoch: 4 [10240/10284]	Loss: 0.6386	LR: 0.100000
Training Epoch: 4 [10284/10284]	Loss: 0.6941	LR: 0.100000
Epoch 4 - Average Train Loss: 0.6761, Train Accuracy: 0.5764
Epoch 4 training time consumed: 148.72s
Evaluating Network.....
Test set: Epoch: 4, Average loss: 0.0032, Accuracy: 0.5506, Time consumed:7.94s
Training Epoch: 5 [256/10284]	Loss: 0.6552	LR: 0.100000
Training Epoch: 5 [512/10284]	Loss: 0.6872	LR: 0.100000
Training Epoch: 5 [768/10284]	Loss: 0.6922	LR: 0.100000
Training Epoch: 5 [1024/10284]	Loss: 0.6778	LR: 0.100000
Training Epoch: 5 [1280/10284]	Loss: 0.6539	LR: 0.100000
Training Epoch: 5 [1536/10284]	Loss: 0.6634	LR: 0.100000
Training Epoch: 5 [1792/10284]	Loss: 0.6798	LR: 0.100000
Training Epoch: 5 [2048/10284]	Loss: 0.6642	LR: 0.100000
Training Epoch: 5 [2304/10284]	Loss: 0.6646	LR: 0.100000
Training Epoch: 5 [2560/10284]	Loss: 0.6726	LR: 0.100000
Training Epoch: 5 [2816/10284]	Loss: 0.6691	LR: 0.100000
Training Epoch: 5 [3072/10284]	Loss: 0.6883	LR: 0.100000
Training Epoch: 5 [3328/10284]	Loss: 0.6798	LR: 0.100000
Training Epoch: 5 [3584/10284]	Loss: 0.6581	LR: 0.100000
Training Epoch: 5 [3840/10284]	Loss: 0.6598	LR: 0.100000
Training Epoch: 5 [4096/10284]	Loss: 0.6428	LR: 0.100000
Training Epoch: 5 [4352/10284]	Loss: 0.6622	LR: 0.100000
Training Epoch: 5 [4608/10284]	Loss: 0.6809	LR: 0.100000
Training Epoch: 5 [4864/10284]	Loss: 0.6755	LR: 0.100000
Training Epoch: 5 [5120/10284]	Loss: 0.6874	LR: 0.100000
Training Epoch: 5 [5376/10284]	Loss: 0.6405	LR: 0.100000
Training Epoch: 5 [5632/10284]	Loss: 0.6804	LR: 0.100000
Training Epoch: 5 [5888/10284]	Loss: 0.6711	LR: 0.100000
Training Epoch: 5 [6144/10284]	Loss: 0.6754	LR: 0.100000
Training Epoch: 5 [6400/10284]	Loss: 0.6591	LR: 0.100000
Training Epoch: 5 [6656/10284]	Loss: 0.6918	LR: 0.100000
Training Epoch: 5 [6912/10284]	Loss: 0.6848	LR: 0.100000
Training Epoch: 5 [7168/10284]	Loss: 0.6542	LR: 0.100000
Training Epoch: 5 [7424/10284]	Loss: 0.6751	LR: 0.100000
Training Epoch: 5 [7680/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 5 [7936/10284]	Loss: 0.6884	LR: 0.100000
Training Epoch: 5 [8192/10284]	Loss: 0.6787	LR: 0.100000
Training Epoch: 5 [8448/10284]	Loss: 0.6696	LR: 0.100000
Training Epoch: 5 [8704/10284]	Loss: 0.6607	LR: 0.100000
Training Epoch: 5 [8960/10284]	Loss: 0.6781	LR: 0.100000
Training Epoch: 5 [9216/10284]	Loss: 0.6642	LR: 0.100000
Training Epoch: 5 [9472/10284]	Loss: 0.6454	LR: 0.100000
Training Epoch: 5 [9728/10284]	Loss: 0.6767	LR: 0.100000
Training Epoch: 5 [9984/10284]	Loss: 0.6504	LR: 0.100000
Training Epoch: 5 [10240/10284]	Loss: 0.6826	LR: 0.100000
Training Epoch: 5 [10284/10284]	Loss: 0.7397	LR: 0.100000
Epoch 5 - Average Train Loss: 0.6708, Train Accuracy: 0.5873
Epoch 5 training time consumed: 148.44s
Evaluating Network.....
Test set: Epoch: 5, Average loss: 0.0033, Accuracy: 0.5545, Time consumed:8.07s
Training Epoch: 6 [256/10284]	Loss: 0.6853	LR: 0.100000
Training Epoch: 6 [512/10284]	Loss: 0.6816	LR: 0.100000
Training Epoch: 6 [768/10284]	Loss: 0.6646	LR: 0.100000
Training Epoch: 6 [1024/10284]	Loss: 0.7007	LR: 0.100000
Training Epoch: 6 [1280/10284]	Loss: 0.6916	LR: 0.100000
Training Epoch: 6 [1536/10284]	Loss: 0.6551	LR: 0.100000
Training Epoch: 6 [1792/10284]	Loss: 0.6681	LR: 0.100000
Training Epoch: 6 [2048/10284]	Loss: 0.6750	LR: 0.100000
Training Epoch: 6 [2304/10284]	Loss: 0.6666	LR: 0.100000
Training Epoch: 6 [2560/10284]	Loss: 0.6819	LR: 0.100000
Training Epoch: 6 [2816/10284]	Loss: 0.6783	LR: 0.100000
Training Epoch: 6 [3072/10284]	Loss: 0.6683	LR: 0.100000
Training Epoch: 6 [3328/10284]	Loss: 0.6639	LR: 0.100000
Training Epoch: 6 [3584/10284]	Loss: 0.6626	LR: 0.100000
Training Epoch: 6 [3840/10284]	Loss: 0.6820	LR: 0.100000
Training Epoch: 6 [4096/10284]	Loss: 0.6805	LR: 0.100000
Training Epoch: 6 [4352/10284]	Loss: 0.6719	LR: 0.100000
Training Epoch: 6 [4608/10284]	Loss: 0.6537	LR: 0.100000
Training Epoch: 6 [4864/10284]	Loss: 0.6405	LR: 0.100000
Training Epoch: 6 [5120/10284]	Loss: 0.6597	LR: 0.100000
Training Epoch: 6 [5376/10284]	Loss: 0.7015	LR: 0.100000
Training Epoch: 6 [5632/10284]	Loss: 0.6827	LR: 0.100000
Training Epoch: 6 [5888/10284]	Loss: 0.6331	LR: 0.100000
Training Epoch: 6 [6144/10284]	Loss: 0.6845	LR: 0.100000
Training Epoch: 6 [6400/10284]	Loss: 0.6705	LR: 0.100000
Training Epoch: 6 [6656/10284]	Loss: 0.6731	LR: 0.100000
Training Epoch: 6 [6912/10284]	Loss: 0.6598	LR: 0.100000
Training Epoch: 6 [7168/10284]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [7424/10284]	Loss: 0.6871	LR: 0.100000
Training Epoch: 6 [7680/10284]	Loss: 0.6663	LR: 0.100000
Training Epoch: 6 [7936/10284]	Loss: 0.6635	LR: 0.100000
Training Epoch: 6 [8192/10284]	Loss: 0.6558	LR: 0.100000
Training Epoch: 6 [8448/10284]	Loss: 0.6577	LR: 0.100000
Training Epoch: 6 [8704/10284]	Loss: 0.6788	LR: 0.100000
Training Epoch: 6 [8960/10284]	Loss: 0.6859	LR: 0.100000
Training Epoch: 6 [9216/10284]	Loss: 0.6738	LR: 0.100000
Training Epoch: 6 [9472/10284]	Loss: 0.6538	LR: 0.100000
Training Epoch: 6 [9728/10284]	Loss: 0.6683	LR: 0.100000
Training Epoch: 6 [9984/10284]	Loss: 0.6686	LR: 0.100000
Training Epoch: 6 [10240/10284]	Loss: 0.6598	LR: 0.100000
Training Epoch: 6 [10284/10284]	Loss: 0.6600	LR: 0.100000
Epoch 6 - Average Train Loss: 0.6706, Train Accuracy: 0.5901
Epoch 6 training time consumed: 148.31s
Evaluating Network.....
Test set: Epoch: 6, Average loss: 0.0031, Accuracy: 0.5559, Time consumed:7.97s
Training Epoch: 7 [256/10284]	Loss: 0.6797	LR: 0.100000
Training Epoch: 7 [512/10284]	Loss: 0.6781	LR: 0.100000
Training Epoch: 7 [768/10284]	Loss: 0.6739	LR: 0.100000
Training Epoch: 7 [1024/10284]	Loss: 0.6557	LR: 0.100000
Training Epoch: 7 [1280/10284]	Loss: 0.6564	LR: 0.100000
Training Epoch: 7 [1536/10284]	Loss: 0.6646	LR: 0.100000
Training Epoch: 7 [1792/10284]	Loss: 0.6501	LR: 0.100000
Training Epoch: 7 [2048/10284]	Loss: 0.6765	LR: 0.100000
Training Epoch: 7 [2304/10284]	Loss: 0.6878	LR: 0.100000
Training Epoch: 7 [2560/10284]	Loss: 0.6514	LR: 0.100000
Training Epoch: 7 [2816/10284]	Loss: 0.6529	LR: 0.100000
Training Epoch: 7 [3072/10284]	Loss: 0.6590	LR: 0.100000
Training Epoch: 7 [3328/10284]	Loss: 0.6416	LR: 0.100000
Training Epoch: 7 [3584/10284]	Loss: 0.6510	LR: 0.100000
Training Epoch: 7 [3840/10284]	Loss: 0.6996	LR: 0.100000
Training Epoch: 7 [4096/10284]	Loss: 0.6650	LR: 0.100000
Training Epoch: 7 [4352/10284]	Loss: 0.6615	LR: 0.100000
Training Epoch: 7 [4608/10284]	Loss: 0.6591	LR: 0.100000
Training Epoch: 7 [4864/10284]	Loss: 0.6457	LR: 0.100000
Training Epoch: 7 [5120/10284]	Loss: 0.6656	LR: 0.100000
Training Epoch: 7 [5376/10284]	Loss: 0.6576	LR: 0.100000
Training Epoch: 7 [5632/10284]	Loss: 0.6902	LR: 0.100000
Training Epoch: 7 [5888/10284]	Loss: 0.6405	LR: 0.100000
Training Epoch: 7 [6144/10284]	Loss: 0.6639	LR: 0.100000
Training Epoch: 7 [6400/10284]	Loss: 0.6558	LR: 0.100000
Training Epoch: 7 [6656/10284]	Loss: 0.6159	LR: 0.100000
Training Epoch: 7 [6912/10284]	Loss: 0.6370	LR: 0.100000
Training Epoch: 7 [7168/10284]	Loss: 0.6384	LR: 0.100000
Training Epoch: 7 [7424/10284]	Loss: 0.6448	LR: 0.100000
Training Epoch: 7 [7680/10284]	Loss: 0.6699	LR: 0.100000
Training Epoch: 7 [7936/10284]	Loss: 0.6756	LR: 0.100000
Training Epoch: 7 [8192/10284]	Loss: 0.6444	LR: 0.100000
Training Epoch: 7 [8448/10284]	Loss: 0.6572	LR: 0.100000
Training Epoch: 7 [8704/10284]	Loss: 0.6447	LR: 0.100000
Training Epoch: 7 [8960/10284]	Loss: 0.6695	LR: 0.100000
Training Epoch: 7 [9216/10284]	Loss: 0.6738	LR: 0.100000
Training Epoch: 7 [9472/10284]	Loss: 0.6583	LR: 0.100000
Training Epoch: 7 [9728/10284]	Loss: 0.6466	LR: 0.100000
Training Epoch: 7 [9984/10284]	Loss: 0.6628	LR: 0.100000
Training Epoch: 7 [10240/10284]	Loss: 0.6455	LR: 0.100000
Training Epoch: 7 [10284/10284]	Loss: 0.6730	LR: 0.100000
Epoch 7 - Average Train Loss: 0.6592, Train Accuracy: 0.6144
Epoch 7 training time consumed: 148.81s
Evaluating Network.....
Test set: Epoch: 7, Average loss: 0.0030, Accuracy: 0.5535, Time consumed:7.95s
Training Epoch: 8 [256/10284]	Loss: 0.6485	LR: 0.100000
Training Epoch: 8 [512/10284]	Loss: 0.6984	LR: 0.100000
Training Epoch: 8 [768/10284]	Loss: 0.6535	LR: 0.100000
Training Epoch: 8 [1024/10284]	Loss: 0.6482	LR: 0.100000
Training Epoch: 8 [1280/10284]	Loss: 0.6732	LR: 0.100000
Training Epoch: 8 [1536/10284]	Loss: 0.6618	LR: 0.100000
Training Epoch: 8 [1792/10284]	Loss: 0.6920	LR: 0.100000
Training Epoch: 8 [2048/10284]	Loss: 0.6561	LR: 0.100000
Training Epoch: 8 [2304/10284]	Loss: 0.6241	LR: 0.100000
Training Epoch: 8 [2560/10284]	Loss: 0.6415	LR: 0.100000
Training Epoch: 8 [2816/10284]	Loss: 0.6559	LR: 0.100000
Training Epoch: 8 [3072/10284]	Loss: 0.6545	LR: 0.100000
Training Epoch: 8 [3328/10284]	Loss: 0.6405	LR: 0.100000
Training Epoch: 8 [3584/10284]	Loss: 0.6449	LR: 0.100000
Training Epoch: 8 [3840/10284]	Loss: 0.6578	LR: 0.100000
Training Epoch: 8 [4096/10284]	Loss: 0.6376	LR: 0.100000
Training Epoch: 8 [4352/10284]	Loss: 0.6721	LR: 0.100000
Training Epoch: 8 [4608/10284]	Loss: 0.6423	LR: 0.100000
Training Epoch: 8 [4864/10284]	Loss: 0.6355	LR: 0.100000
Training Epoch: 8 [5120/10284]	Loss: 0.6653	LR: 0.100000
Training Epoch: 8 [5376/10284]	Loss: 0.6487	LR: 0.100000
Training Epoch: 8 [5632/10284]	Loss: 0.6479	LR: 0.100000
Training Epoch: 8 [5888/10284]	Loss: 0.6389	LR: 0.100000
Training Epoch: 8 [6144/10284]	Loss: 0.6467	LR: 0.100000
Training Epoch: 8 [6400/10284]	Loss: 0.6323	LR: 0.100000
Training Epoch: 8 [6656/10284]	Loss: 0.6746	LR: 0.100000
Training Epoch: 8 [6912/10284]	Loss: 0.6624	LR: 0.100000
Training Epoch: 8 [7168/10284]	Loss: 0.6220	LR: 0.100000
Training Epoch: 8 [7424/10284]	Loss: 0.6200	LR: 0.100000
Training Epoch: 8 [7680/10284]	Loss: 0.6330	LR: 0.100000
Training Epoch: 8 [7936/10284]	Loss: 0.6904	LR: 0.100000
Training Epoch: 8 [8192/10284]	Loss: 0.6429	LR: 0.100000
Training Epoch: 8 [8448/10284]	Loss: 0.6536	LR: 0.100000
Training Epoch: 8 [8704/10284]	Loss: 0.6423	LR: 0.100000
Training Epoch: 8 [8960/10284]	Loss: 0.6733	LR: 0.100000
Training Epoch: 8 [9216/10284]	Loss: 0.6391	LR: 0.100000
Training Epoch: 8 [9472/10284]	Loss: 0.6377	LR: 0.100000
Training Epoch: 8 [9728/10284]	Loss: 0.6557	LR: 0.100000
Training Epoch: 8 [9984/10284]	Loss: 0.6178	LR: 0.100000
Training Epoch: 8 [10240/10284]	Loss: 0.6714	LR: 0.100000
Training Epoch: 8 [10284/10284]	Loss: 0.6987	LR: 0.100000
Epoch 8 - Average Train Loss: 0.6516, Train Accuracy: 0.6244
Epoch 8 training time consumed: 149.50s
Evaluating Network.....
Test set: Epoch: 8, Average loss: 0.0028, Accuracy: 0.6416, Time consumed:8.06s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-8-best.pth
Training Epoch: 9 [256/10284]	Loss: 0.6220	LR: 0.100000
Training Epoch: 9 [512/10284]	Loss: 0.6423	LR: 0.100000
Training Epoch: 9 [768/10284]	Loss: 0.6749	LR: 0.100000
Training Epoch: 9 [1024/10284]	Loss: 0.6598	LR: 0.100000
Training Epoch: 9 [1280/10284]	Loss: 0.6358	LR: 0.100000
Training Epoch: 9 [1536/10284]	Loss: 0.6243	LR: 0.100000
Training Epoch: 9 [1792/10284]	Loss: 0.6232	LR: 0.100000
Training Epoch: 9 [2048/10284]	Loss: 0.6173	LR: 0.100000
Training Epoch: 9 [2304/10284]	Loss: 0.6272	LR: 0.100000
Training Epoch: 9 [2560/10284]	Loss: 0.6869	LR: 0.100000
Training Epoch: 9 [2816/10284]	Loss: 0.6160	LR: 0.100000
Training Epoch: 9 [3072/10284]	Loss: 0.6178	LR: 0.100000
Training Epoch: 9 [3328/10284]	Loss: 0.6270	LR: 0.100000
Training Epoch: 9 [3584/10284]	Loss: 0.6223	LR: 0.100000
Training Epoch: 9 [3840/10284]	Loss: 0.6740	LR: 0.100000
Training Epoch: 9 [4096/10284]	Loss: 0.6330	LR: 0.100000
Training Epoch: 9 [4352/10284]	Loss: 0.6493	LR: 0.100000
Training Epoch: 9 [4608/10284]	Loss: 0.6408	LR: 0.100000
Training Epoch: 9 [4864/10284]	Loss: 0.6099	LR: 0.100000
Training Epoch: 9 [5120/10284]	Loss: 0.6409	LR: 0.100000
Training Epoch: 9 [5376/10284]	Loss: 0.6278	LR: 0.100000
Training Epoch: 9 [5632/10284]	Loss: 0.6451	LR: 0.100000
Training Epoch: 9 [5888/10284]	Loss: 0.6079	LR: 0.100000
Training Epoch: 9 [6144/10284]	Loss: 0.6110	LR: 0.100000
Training Epoch: 9 [6400/10284]	Loss: 0.5917	LR: 0.100000
Training Epoch: 9 [6656/10284]	Loss: 0.6508	LR: 0.100000
Training Epoch: 9 [6912/10284]	Loss: 0.6445	LR: 0.100000
Training Epoch: 9 [7168/10284]	Loss: 0.6087	LR: 0.100000
Training Epoch: 9 [7424/10284]	Loss: 0.5840	LR: 0.100000
Training Epoch: 9 [7680/10284]	Loss: 0.6345	LR: 0.100000
Training Epoch: 9 [7936/10284]	Loss: 0.6172	LR: 0.100000
Training Epoch: 9 [8192/10284]	Loss: 0.5605	LR: 0.100000
Training Epoch: 9 [8448/10284]	Loss: 0.6215	LR: 0.100000
Training Epoch: 9 [8704/10284]	Loss: 0.6338	LR: 0.100000
Training Epoch: 9 [8960/10284]	Loss: 0.6272	LR: 0.100000
Training Epoch: 9 [9216/10284]	Loss: 0.6318	LR: 0.100000
Training Epoch: 9 [9472/10284]	Loss: 0.6687	LR: 0.100000
Training Epoch: 9 [9728/10284]	Loss: 0.6123	LR: 0.100000
Training Epoch: 9 [9984/10284]	Loss: 0.6359	LR: 0.100000
Training Epoch: 9 [10240/10284]	Loss: 0.5636	LR: 0.100000
Training Epoch: 9 [10284/10284]	Loss: 0.6502	LR: 0.100000
Epoch 9 - Average Train Loss: 0.6282, Train Accuracy: 0.6495
Epoch 9 training time consumed: 148.59s
Evaluating Network.....
Test set: Epoch: 9, Average loss: 0.0028, Accuracy: 0.6218, Time consumed:7.93s
Training Epoch: 10 [256/10284]	Loss: 0.6382	LR: 0.020000
Training Epoch: 10 [512/10284]	Loss: 0.6526	LR: 0.020000
Training Epoch: 10 [768/10284]	Loss: 0.5999	LR: 0.020000
Training Epoch: 10 [1024/10284]	Loss: 0.6287	LR: 0.020000
Training Epoch: 10 [1280/10284]	Loss: 0.6469	LR: 0.020000
Training Epoch: 10 [1536/10284]	Loss: 0.5866	LR: 0.020000
Training Epoch: 10 [1792/10284]	Loss: 0.6045	LR: 0.020000
Training Epoch: 10 [2048/10284]	Loss: 0.5917	LR: 0.020000
Training Epoch: 10 [2304/10284]	Loss: 0.5668	LR: 0.020000
Training Epoch: 10 [2560/10284]	Loss: 0.5719	LR: 0.020000
Training Epoch: 10 [2816/10284]	Loss: 0.6182	LR: 0.020000
Training Epoch: 10 [3072/10284]	Loss: 0.5889	LR: 0.020000
Training Epoch: 10 [3328/10284]	Loss: 0.5876	LR: 0.020000
Training Epoch: 10 [3584/10284]	Loss: 0.6144	LR: 0.020000
Training Epoch: 10 [3840/10284]	Loss: 0.5788	LR: 0.020000
Training Epoch: 10 [4096/10284]	Loss: 0.6128	LR: 0.020000
Training Epoch: 10 [4352/10284]	Loss: 0.5423	LR: 0.020000
Training Epoch: 10 [4608/10284]	Loss: 0.6378	LR: 0.020000
Training Epoch: 10 [4864/10284]	Loss: 0.5966	LR: 0.020000
Training Epoch: 10 [5120/10284]	Loss: 0.6041	LR: 0.020000
Training Epoch: 10 [5376/10284]	Loss: 0.6303	LR: 0.020000
Training Epoch: 10 [5632/10284]	Loss: 0.5846	LR: 0.020000
Training Epoch: 10 [5888/10284]	Loss: 0.5792	LR: 0.020000
Training Epoch: 10 [6144/10284]	Loss: 0.5507	LR: 0.020000
Training Epoch: 10 [6400/10284]	Loss: 0.5466	LR: 0.020000
Training Epoch: 10 [6656/10284]	Loss: 0.5770	LR: 0.020000
Training Epoch: 10 [6912/10284]	Loss: 0.6278	LR: 0.020000
Training Epoch: 10 [7168/10284]	Loss: 0.5439	LR: 0.020000
Training Epoch: 10 [7424/10284]	Loss: 0.5861	LR: 0.020000
Training Epoch: 10 [7680/10284]	Loss: 0.5406	LR: 0.020000
Training Epoch: 10 [7936/10284]	Loss: 0.5658	LR: 0.020000
Training Epoch: 10 [8192/10284]	Loss: 0.5530	LR: 0.020000
Training Epoch: 10 [8448/10284]	Loss: 0.6425	LR: 0.020000
Training Epoch: 10 [8704/10284]	Loss: 0.5841	LR: 0.020000
Training Epoch: 10 [8960/10284]	Loss: 0.5673	LR: 0.020000
Training Epoch: 10 [9216/10284]	Loss: 0.5996	LR: 0.020000
Training Epoch: 10 [9472/10284]	Loss: 0.5744	LR: 0.020000
Training Epoch: 10 [9728/10284]	Loss: 0.5839	LR: 0.020000
Training Epoch: 10 [9984/10284]	Loss: 0.5820	LR: 0.020000
Training Epoch: 10 [10240/10284]	Loss: 0.5508	LR: 0.020000
Training Epoch: 10 [10284/10284]	Loss: 0.6429	LR: 0.020000
Epoch 10 - Average Train Loss: 0.5912, Train Accuracy: 0.6888
Epoch 10 training time consumed: 148.80s
Evaluating Network.....
Test set: Epoch: 10, Average loss: 0.0026, Accuracy: 0.6804, Time consumed:7.99s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-10-best.pth
Training Epoch: 11 [256/10284]	Loss: 0.5998	LR: 0.020000
Training Epoch: 11 [512/10284]	Loss: 0.5003	LR: 0.020000
Training Epoch: 11 [768/10284]	Loss: 0.5962	LR: 0.020000
Training Epoch: 11 [1024/10284]	Loss: 0.5708	LR: 0.020000
Training Epoch: 11 [1280/10284]	Loss: 0.6360	LR: 0.020000
Training Epoch: 11 [1536/10284]	Loss: 0.5398	LR: 0.020000
Training Epoch: 11 [1792/10284]	Loss: 0.6019	LR: 0.020000
Training Epoch: 11 [2048/10284]	Loss: 0.5781	LR: 0.020000
Training Epoch: 11 [2304/10284]	Loss: 0.5970	LR: 0.020000
Training Epoch: 11 [2560/10284]	Loss: 0.5874	LR: 0.020000
Training Epoch: 11 [2816/10284]	Loss: 0.6083	LR: 0.020000
Training Epoch: 11 [3072/10284]	Loss: 0.5837	LR: 0.020000
Training Epoch: 11 [3328/10284]	Loss: 0.5796	LR: 0.020000
Training Epoch: 11 [3584/10284]	Loss: 0.5724	LR: 0.020000
Training Epoch: 11 [3840/10284]	Loss: 0.5764	LR: 0.020000
Training Epoch: 11 [4096/10284]	Loss: 0.5548	LR: 0.020000
Training Epoch: 11 [4352/10284]	Loss: 0.6124	LR: 0.020000
Training Epoch: 11 [4608/10284]	Loss: 0.5422	LR: 0.020000
Training Epoch: 11 [4864/10284]	Loss: 0.5661	LR: 0.020000
Training Epoch: 11 [5120/10284]	Loss: 0.5605	LR: 0.020000
Training Epoch: 11 [5376/10284]	Loss: 0.5614	LR: 0.020000
Training Epoch: 11 [5632/10284]	Loss: 0.5922	LR: 0.020000
Training Epoch: 11 [5888/10284]	Loss: 0.5846	LR: 0.020000
Training Epoch: 11 [6144/10284]	Loss: 0.5457	LR: 0.020000
Training Epoch: 11 [6400/10284]	Loss: 0.5368	LR: 0.020000
Training Epoch: 11 [6656/10284]	Loss: 0.5343	LR: 0.020000
Training Epoch: 11 [6912/10284]	Loss: 0.5464	LR: 0.020000
Training Epoch: 11 [7168/10284]	Loss: 0.5705	LR: 0.020000
Training Epoch: 11 [7424/10284]	Loss: 0.5758	LR: 0.020000
Training Epoch: 11 [7680/10284]	Loss: 0.6653	LR: 0.020000
Training Epoch: 11 [7936/10284]	Loss: 0.5374	LR: 0.020000
Training Epoch: 11 [8192/10284]	Loss: 0.5600	LR: 0.020000
Training Epoch: 11 [8448/10284]	Loss: 0.5710	LR: 0.020000
Training Epoch: 11 [8704/10284]	Loss: 0.5510	LR: 0.020000
Training Epoch: 11 [8960/10284]	Loss: 0.5271	LR: 0.020000
Training Epoch: 11 [9216/10284]	Loss: 0.5989	LR: 0.020000
Training Epoch: 11 [9472/10284]	Loss: 0.5345	LR: 0.020000
Training Epoch: 11 [9728/10284]	Loss: 0.5434	LR: 0.020000
Training Epoch: 11 [9984/10284]	Loss: 0.5346	LR: 0.020000
Training Epoch: 11 [10240/10284]	Loss: 0.5434	LR: 0.020000
Training Epoch: 11 [10284/10284]	Loss: 0.5707	LR: 0.020000
Epoch 11 - Average Train Loss: 0.5695, Train Accuracy: 0.7083
Epoch 11 training time consumed: 148.51s
Evaluating Network.....
Test set: Epoch: 11, Average loss: 0.0024, Accuracy: 0.7240, Time consumed:7.78s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-11-best.pth
Training Epoch: 12 [256/10284]	Loss: 0.5286	LR: 0.020000
Training Epoch: 12 [512/10284]	Loss: 0.5159	LR: 0.020000
Training Epoch: 12 [768/10284]	Loss: 0.5545	LR: 0.020000
Training Epoch: 12 [1024/10284]	Loss: 0.5981	LR: 0.020000
Training Epoch: 12 [1280/10284]	Loss: 0.5607	LR: 0.020000
Training Epoch: 12 [1536/10284]	Loss: 0.4963	LR: 0.020000
Training Epoch: 12 [1792/10284]	Loss: 0.5367	LR: 0.020000
Training Epoch: 12 [2048/10284]	Loss: 0.5628	LR: 0.020000
Training Epoch: 12 [2304/10284]	Loss: 0.5232	LR: 0.020000
Training Epoch: 12 [2560/10284]	Loss: 0.5085	LR: 0.020000
Training Epoch: 12 [2816/10284]	Loss: 0.5321	LR: 0.020000
Training Epoch: 12 [3072/10284]	Loss: 0.5541	LR: 0.020000
Training Epoch: 12 [3328/10284]	Loss: 0.5023	LR: 0.020000
Training Epoch: 12 [3584/10284]	Loss: 0.5492	LR: 0.020000
Training Epoch: 12 [3840/10284]	Loss: 0.5236	LR: 0.020000
Training Epoch: 12 [4096/10284]	Loss: 0.5296	LR: 0.020000
Training Epoch: 12 [4352/10284]	Loss: 0.5550	LR: 0.020000
Training Epoch: 12 [4608/10284]	Loss: 0.5506	LR: 0.020000
Training Epoch: 12 [4864/10284]	Loss: 0.5384	LR: 0.020000
Training Epoch: 12 [5120/10284]	Loss: 0.5914	LR: 0.020000
Training Epoch: 12 [5376/10284]	Loss: 0.5373	LR: 0.020000
Training Epoch: 12 [5632/10284]	Loss: 0.5192	LR: 0.020000
Training Epoch: 12 [5888/10284]	Loss: 0.5206	LR: 0.020000
Training Epoch: 12 [6144/10284]	Loss: 0.4948	LR: 0.020000
Training Epoch: 12 [6400/10284]	Loss: 0.5147	LR: 0.020000
Training Epoch: 12 [6656/10284]	Loss: 0.5503	LR: 0.020000
Training Epoch: 12 [6912/10284]	Loss: 0.5042	LR: 0.020000
Training Epoch: 12 [7168/10284]	Loss: 0.4871	LR: 0.020000
Training Epoch: 12 [7424/10284]	Loss: 0.4972	LR: 0.020000
Training Epoch: 12 [7680/10284]	Loss: 0.4729	LR: 0.020000
Training Epoch: 12 [7936/10284]	Loss: 0.4603	LR: 0.020000
Training Epoch: 12 [8192/10284]	Loss: 0.4588	LR: 0.020000
Training Epoch: 12 [8448/10284]	Loss: 0.4509	LR: 0.020000
Training Epoch: 12 [8704/10284]	Loss: 0.5440	LR: 0.020000
Training Epoch: 12 [8960/10284]	Loss: 0.5276	LR: 0.020000
Training Epoch: 12 [9216/10284]	Loss: 0.5351	LR: 0.020000
Training Epoch: 12 [9472/10284]	Loss: 0.4946	LR: 0.020000
Training Epoch: 12 [9728/10284]	Loss: 0.5228	LR: 0.020000
Training Epoch: 12 [9984/10284]	Loss: 0.5041	LR: 0.020000
Training Epoch: 12 [10240/10284]	Loss: 0.5188	LR: 0.020000
Training Epoch: 12 [10284/10284]	Loss: 0.6888	LR: 0.020000
Epoch 12 - Average Train Loss: 0.5239, Train Accuracy: 0.7431
Epoch 12 training time consumed: 148.49s
Evaluating Network.....
Test set: Epoch: 12, Average loss: 0.0025, Accuracy: 0.7254, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-12-best.pth
Training Epoch: 13 [256/10284]	Loss: 0.4800	LR: 0.020000
Training Epoch: 13 [512/10284]	Loss: 0.4879	LR: 0.020000
Training Epoch: 13 [768/10284]	Loss: 0.4857	LR: 0.020000
Training Epoch: 13 [1024/10284]	Loss: 0.4830	LR: 0.020000
Training Epoch: 13 [1280/10284]	Loss: 0.4910	LR: 0.020000
Training Epoch: 13 [1536/10284]	Loss: 0.5855	LR: 0.020000
Training Epoch: 13 [1792/10284]	Loss: 0.4693	LR: 0.020000
Training Epoch: 13 [2048/10284]	Loss: 0.4367	LR: 0.020000
Training Epoch: 13 [2304/10284]	Loss: 0.4449	LR: 0.020000
Training Epoch: 13 [2560/10284]	Loss: 0.4414	LR: 0.020000
Training Epoch: 13 [2816/10284]	Loss: 0.4910	LR: 0.020000
Training Epoch: 13 [3072/10284]	Loss: 0.4850	LR: 0.020000
Training Epoch: 13 [3328/10284]	Loss: 0.4758	LR: 0.020000
Training Epoch: 13 [3584/10284]	Loss: 0.4289	LR: 0.020000
Training Epoch: 13 [3840/10284]	Loss: 0.3910	LR: 0.020000
Training Epoch: 13 [4096/10284]	Loss: 0.4051	LR: 0.020000
Training Epoch: 13 [4352/10284]	Loss: 0.3834	LR: 0.020000
Training Epoch: 13 [4608/10284]	Loss: 0.4210	LR: 0.020000
Training Epoch: 13 [4864/10284]	Loss: 0.4682	LR: 0.020000
Training Epoch: 13 [5120/10284]	Loss: 0.4579	LR: 0.020000
Training Epoch: 13 [5376/10284]	Loss: 0.4631	LR: 0.020000
Training Epoch: 13 [5632/10284]	Loss: 0.4133	LR: 0.020000
Training Epoch: 13 [5888/10284]	Loss: 0.3969	LR: 0.020000
Training Epoch: 13 [6144/10284]	Loss: 0.4943	LR: 0.020000
Training Epoch: 13 [6400/10284]	Loss: 0.4544	LR: 0.020000
Training Epoch: 13 [6656/10284]	Loss: 0.4408	LR: 0.020000
Training Epoch: 13 [6912/10284]	Loss: 0.3586	LR: 0.020000
Training Epoch: 13 [7168/10284]	Loss: 0.5581	LR: 0.020000
Training Epoch: 13 [7424/10284]	Loss: 0.4958	LR: 0.020000
Training Epoch: 13 [7680/10284]	Loss: 0.5060	LR: 0.020000
Training Epoch: 13 [7936/10284]	Loss: 0.4249	LR: 0.020000
Training Epoch: 13 [8192/10284]	Loss: 0.4644	LR: 0.020000
Training Epoch: 13 [8448/10284]	Loss: 0.3850	LR: 0.020000
Training Epoch: 13 [8704/10284]	Loss: 0.4242	LR: 0.020000
Training Epoch: 13 [8960/10284]	Loss: 0.3968	LR: 0.020000
Training Epoch: 13 [9216/10284]	Loss: 0.4043	LR: 0.020000
Training Epoch: 13 [9472/10284]	Loss: 0.4140	LR: 0.020000
Training Epoch: 13 [9728/10284]	Loss: 0.4173	LR: 0.020000
Training Epoch: 13 [9984/10284]	Loss: 0.3414	LR: 0.020000
Training Epoch: 13 [10240/10284]	Loss: 0.4468	LR: 0.020000
Training Epoch: 13 [10284/10284]	Loss: 0.3350	LR: 0.020000
Epoch 13 - Average Train Loss: 0.4473, Train Accuracy: 0.7961
Epoch 13 training time consumed: 149.06s
Evaluating Network.....
Test set: Epoch: 13, Average loss: 0.0022, Accuracy: 0.7705, Time consumed:7.93s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-13-best.pth
Training Epoch: 14 [256/10284]	Loss: 0.4192	LR: 0.020000
Training Epoch: 14 [512/10284]	Loss: 0.3106	LR: 0.020000
Training Epoch: 14 [768/10284]	Loss: 0.4223	LR: 0.020000
Training Epoch: 14 [1024/10284]	Loss: 0.3399	LR: 0.020000
Training Epoch: 14 [1280/10284]	Loss: 0.4125	LR: 0.020000
Training Epoch: 14 [1536/10284]	Loss: 0.4642	LR: 0.020000
Training Epoch: 14 [1792/10284]	Loss: 0.4084	LR: 0.020000
Training Epoch: 14 [2048/10284]	Loss: 0.4394	LR: 0.020000
Training Epoch: 14 [2304/10284]	Loss: 0.4381	LR: 0.020000
Training Epoch: 14 [2560/10284]	Loss: 0.3531	LR: 0.020000
Training Epoch: 14 [2816/10284]	Loss: 0.3709	LR: 0.020000
Training Epoch: 14 [3072/10284]	Loss: 0.3620	LR: 0.020000
Training Epoch: 14 [3328/10284]	Loss: 0.4247	LR: 0.020000
Training Epoch: 14 [3584/10284]	Loss: 0.3855	LR: 0.020000
Training Epoch: 14 [3840/10284]	Loss: 0.3104	LR: 0.020000
Training Epoch: 14 [4096/10284]	Loss: 0.3720	LR: 0.020000
Training Epoch: 14 [4352/10284]	Loss: 0.3302	LR: 0.020000
Training Epoch: 14 [4608/10284]	Loss: 0.3374	LR: 0.020000
Training Epoch: 14 [4864/10284]	Loss: 0.3745	LR: 0.020000
Training Epoch: 14 [5120/10284]	Loss: 0.3690	LR: 0.020000
Training Epoch: 14 [5376/10284]	Loss: 0.3707	LR: 0.020000
Training Epoch: 14 [5632/10284]	Loss: 0.4317	LR: 0.020000
Training Epoch: 14 [5888/10284]	Loss: 0.3394	LR: 0.020000
Training Epoch: 14 [6144/10284]	Loss: 0.3534	LR: 0.020000
Training Epoch: 14 [6400/10284]	Loss: 0.3511	LR: 0.020000
Training Epoch: 14 [6656/10284]	Loss: 0.3873	LR: 0.020000
Training Epoch: 14 [6912/10284]	Loss: 0.3372	LR: 0.020000
Training Epoch: 14 [7168/10284]	Loss: 0.3576	LR: 0.020000
Training Epoch: 14 [7424/10284]	Loss: 0.3788	LR: 0.020000
Training Epoch: 14 [7680/10284]	Loss: 0.3910	LR: 0.020000
Training Epoch: 14 [7936/10284]	Loss: 0.3745	LR: 0.020000
Training Epoch: 14 [8192/10284]	Loss: 0.4232	LR: 0.020000
Training Epoch: 14 [8448/10284]	Loss: 0.4352	LR: 0.020000
Training Epoch: 14 [8704/10284]	Loss: 0.3844	LR: 0.020000
Training Epoch: 14 [8960/10284]	Loss: 0.3791	LR: 0.020000
Training Epoch: 14 [9216/10284]	Loss: 0.4509	LR: 0.020000
Training Epoch: 14 [9472/10284]	Loss: 0.3926	LR: 0.020000
Training Epoch: 14 [9728/10284]	Loss: 0.4496	LR: 0.020000
Training Epoch: 14 [9984/10284]	Loss: 0.3540	LR: 0.020000
Training Epoch: 14 [10240/10284]	Loss: 0.3776	LR: 0.020000
Training Epoch: 14 [10284/10284]	Loss: 0.2396	LR: 0.020000
Epoch 14 - Average Train Loss: 0.3835, Train Accuracy: 0.8337
Epoch 14 training time consumed: 148.76s
Evaluating Network.....
Test set: Epoch: 14, Average loss: 0.0036, Accuracy: 0.5797, Time consumed:7.86s
Training Epoch: 15 [256/10284]	Loss: 0.3940	LR: 0.020000
Training Epoch: 15 [512/10284]	Loss: 0.3639	LR: 0.020000
Training Epoch: 15 [768/10284]	Loss: 0.3755	LR: 0.020000
Training Epoch: 15 [1024/10284]	Loss: 0.4145	LR: 0.020000
Training Epoch: 15 [1280/10284]	Loss: 0.3410	LR: 0.020000
Training Epoch: 15 [1536/10284]	Loss: 0.3414	LR: 0.020000
Training Epoch: 15 [1792/10284]	Loss: 0.3307	LR: 0.020000
Training Epoch: 15 [2048/10284]	Loss: 0.3110	LR: 0.020000
Training Epoch: 15 [2304/10284]	Loss: 0.3510	LR: 0.020000
Training Epoch: 15 [2560/10284]	Loss: 0.3413	LR: 0.020000
Training Epoch: 15 [2816/10284]	Loss: 0.2798	LR: 0.020000
Training Epoch: 15 [3072/10284]	Loss: 0.3603	LR: 0.020000
Training Epoch: 15 [3328/10284]	Loss: 0.3168	LR: 0.020000
Training Epoch: 15 [3584/10284]	Loss: 0.3399	LR: 0.020000
Training Epoch: 15 [3840/10284]	Loss: 0.3384	LR: 0.020000
Training Epoch: 15 [4096/10284]	Loss: 0.3381	LR: 0.020000
Training Epoch: 15 [4352/10284]	Loss: 0.2924	LR: 0.020000
Training Epoch: 15 [4608/10284]	Loss: 0.3175	LR: 0.020000
Training Epoch: 15 [4864/10284]	Loss: 0.3986	LR: 0.020000
Training Epoch: 15 [5120/10284]	Loss: 0.3091	LR: 0.020000
Training Epoch: 15 [5376/10284]	Loss: 0.3837	LR: 0.020000
Training Epoch: 15 [5632/10284]	Loss: 0.3348	LR: 0.020000
Training Epoch: 15 [5888/10284]	Loss: 0.3161	LR: 0.020000
Training Epoch: 15 [6144/10284]	Loss: 0.3336	LR: 0.020000
Training Epoch: 15 [6400/10284]	Loss: 0.2719	LR: 0.020000
Training Epoch: 15 [6656/10284]	Loss: 0.2503	LR: 0.020000
Training Epoch: 15 [6912/10284]	Loss: 0.3308	LR: 0.020000
Training Epoch: 15 [7168/10284]	Loss: 0.3215	LR: 0.020000
Training Epoch: 15 [7424/10284]	Loss: 0.3200	LR: 0.020000
Training Epoch: 15 [7680/10284]	Loss: 0.2806	LR: 0.020000
Training Epoch: 15 [7936/10284]	Loss: 0.3086	LR: 0.020000
Training Epoch: 15 [8192/10284]	Loss: 0.3443	LR: 0.020000
Training Epoch: 15 [8448/10284]	Loss: 0.2996	LR: 0.020000
Training Epoch: 15 [8704/10284]	Loss: 0.3181	LR: 0.020000
Training Epoch: 15 [8960/10284]	Loss: 0.3412	LR: 0.020000
Training Epoch: 15 [9216/10284]	Loss: 0.3406	LR: 0.020000
Training Epoch: 15 [9472/10284]	Loss: 0.2722	LR: 0.020000
Training Epoch: 15 [9728/10284]	Loss: 0.3777	LR: 0.020000
Training Epoch: 15 [9984/10284]	Loss: 0.3766	LR: 0.020000
Training Epoch: 15 [10240/10284]	Loss: 0.3077	LR: 0.020000
Training Epoch: 15 [10284/10284]	Loss: 0.2693	LR: 0.020000
Epoch 15 - Average Train Loss: 0.3319, Train Accuracy: 0.8575
Epoch 15 training time consumed: 148.61s
Evaluating Network.....
Test set: Epoch: 15, Average loss: 0.0031, Accuracy: 0.6276, Time consumed:8.05s
Training Epoch: 16 [256/10284]	Loss: 0.3034	LR: 0.020000
Training Epoch: 16 [512/10284]	Loss: 0.2955	LR: 0.020000
Training Epoch: 16 [768/10284]	Loss: 0.3477	LR: 0.020000
Training Epoch: 16 [1024/10284]	Loss: 0.3622	LR: 0.020000
Training Epoch: 16 [1280/10284]	Loss: 0.3283	LR: 0.020000
Training Epoch: 16 [1536/10284]	Loss: 0.2690	LR: 0.020000
Training Epoch: 16 [1792/10284]	Loss: 0.3774	LR: 0.020000
Training Epoch: 16 [2048/10284]	Loss: 0.3463	LR: 0.020000
Training Epoch: 16 [2304/10284]	Loss: 0.3499	LR: 0.020000
Training Epoch: 16 [2560/10284]	Loss: 0.2796	LR: 0.020000
Training Epoch: 16 [2816/10284]	Loss: 0.3020	LR: 0.020000
Training Epoch: 16 [3072/10284]	Loss: 0.4086	LR: 0.020000
Training Epoch: 16 [3328/10284]	Loss: 0.3194	LR: 0.020000
Training Epoch: 16 [3584/10284]	Loss: 0.3033	LR: 0.020000
Training Epoch: 16 [3840/10284]	Loss: 0.3014	LR: 0.020000
Training Epoch: 16 [4096/10284]	Loss: 0.3201	LR: 0.020000
Training Epoch: 16 [4352/10284]	Loss: 0.3010	LR: 0.020000
Training Epoch: 16 [4608/10284]	Loss: 0.2967	LR: 0.020000
Training Epoch: 16 [4864/10284]	Loss: 0.3249	LR: 0.020000
Training Epoch: 16 [5120/10284]	Loss: 0.3569	LR: 0.020000
Training Epoch: 16 [5376/10284]	Loss: 0.2481	LR: 0.020000
Training Epoch: 16 [5632/10284]	Loss: 0.2608	LR: 0.020000
Training Epoch: 16 [5888/10284]	Loss: 0.3652	LR: 0.020000
Training Epoch: 16 [6144/10284]	Loss: 0.2647	LR: 0.020000
Training Epoch: 16 [6400/10284]	Loss: 0.3247	LR: 0.020000
Training Epoch: 16 [6656/10284]	Loss: 0.2703	LR: 0.020000
Training Epoch: 16 [6912/10284]	Loss: 0.2715	LR: 0.020000
Training Epoch: 16 [7168/10284]	Loss: 0.2981	LR: 0.020000
Training Epoch: 16 [7424/10284]	Loss: 0.2917	LR: 0.020000
Training Epoch: 16 [7680/10284]	Loss: 0.2438	LR: 0.020000
Training Epoch: 16 [7936/10284]	Loss: 0.3109	LR: 0.020000
Training Epoch: 16 [8192/10284]	Loss: 0.2511	LR: 0.020000
Training Epoch: 16 [8448/10284]	Loss: 0.2636	LR: 0.020000
Training Epoch: 16 [8704/10284]	Loss: 0.2728	LR: 0.020000
Training Epoch: 16 [8960/10284]	Loss: 0.2856	LR: 0.020000
Training Epoch: 16 [9216/10284]	Loss: 0.2305	LR: 0.020000
Training Epoch: 16 [9472/10284]	Loss: 0.2788	LR: 0.020000
Training Epoch: 16 [9728/10284]	Loss: 0.3278	LR: 0.020000
Training Epoch: 16 [9984/10284]	Loss: 0.2494	LR: 0.020000
Training Epoch: 16 [10240/10284]	Loss: 0.2783	LR: 0.020000
Training Epoch: 16 [10284/10284]	Loss: 0.1200	LR: 0.020000
Epoch 16 - Average Train Loss: 0.3012, Train Accuracy: 0.8752
Epoch 16 training time consumed: 148.60s
Evaluating Network.....
Test set: Epoch: 16, Average loss: 0.0022, Accuracy: 0.7738, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-16-best.pth
Training Epoch: 17 [256/10284]	Loss: 0.2140	LR: 0.020000
Training Epoch: 17 [512/10284]	Loss: 0.2844	LR: 0.020000
Training Epoch: 17 [768/10284]	Loss: 0.2279	LR: 0.020000
Training Epoch: 17 [1024/10284]	Loss: 0.2244	LR: 0.020000
Training Epoch: 17 [1280/10284]	Loss: 0.2710	LR: 0.020000
Training Epoch: 17 [1536/10284]	Loss: 0.3008	LR: 0.020000
Training Epoch: 17 [1792/10284]	Loss: 0.2814	LR: 0.020000
Training Epoch: 17 [2048/10284]	Loss: 0.2716	LR: 0.020000
Training Epoch: 17 [2304/10284]	Loss: 0.3323	LR: 0.020000
Training Epoch: 17 [2560/10284]	Loss: 0.3712	LR: 0.020000
Training Epoch: 17 [2816/10284]	Loss: 0.2517	LR: 0.020000
Training Epoch: 17 [3072/10284]	Loss: 0.2375	LR: 0.020000
Training Epoch: 17 [3328/10284]	Loss: 0.2773	LR: 0.020000
Training Epoch: 17 [3584/10284]	Loss: 0.2707	LR: 0.020000
Training Epoch: 17 [3840/10284]	Loss: 0.2985	LR: 0.020000
Training Epoch: 17 [4096/10284]	Loss: 0.3142	LR: 0.020000
Training Epoch: 17 [4352/10284]	Loss: 0.2835	LR: 0.020000
Training Epoch: 17 [4608/10284]	Loss: 0.2597	LR: 0.020000
Training Epoch: 17 [4864/10284]	Loss: 0.2241	LR: 0.020000
Training Epoch: 17 [5120/10284]	Loss: 0.3509	LR: 0.020000
Training Epoch: 17 [5376/10284]	Loss: 0.3497	LR: 0.020000
Training Epoch: 17 [5632/10284]	Loss: 0.2872	LR: 0.020000
Training Epoch: 17 [5888/10284]	Loss: 0.2766	LR: 0.020000
Training Epoch: 17 [6144/10284]	Loss: 0.2971	LR: 0.020000
Training Epoch: 17 [6400/10284]	Loss: 0.2971	LR: 0.020000
Training Epoch: 17 [6656/10284]	Loss: 0.2751	LR: 0.020000
Training Epoch: 17 [6912/10284]	Loss: 0.2552	LR: 0.020000
Training Epoch: 17 [7168/10284]	Loss: 0.2429	LR: 0.020000
Training Epoch: 17 [7424/10284]	Loss: 0.2514	LR: 0.020000
Training Epoch: 17 [7680/10284]	Loss: 0.2655	LR: 0.020000
Training Epoch: 17 [7936/10284]	Loss: 0.3295	LR: 0.020000
Training Epoch: 17 [8192/10284]	Loss: 0.2706	LR: 0.020000
Training Epoch: 17 [8448/10284]	Loss: 0.2934	LR: 0.020000
Training Epoch: 17 [8704/10284]	Loss: 0.2659	LR: 0.020000
Training Epoch: 17 [8960/10284]	Loss: 0.2905	LR: 0.020000
Training Epoch: 17 [9216/10284]	Loss: 0.2544	LR: 0.020000
Training Epoch: 17 [9472/10284]	Loss: 0.2443	LR: 0.020000
Training Epoch: 17 [9728/10284]	Loss: 0.2329	LR: 0.020000
Training Epoch: 17 [9984/10284]	Loss: 0.2262	LR: 0.020000
Training Epoch: 17 [10240/10284]	Loss: 0.2631	LR: 0.020000
Training Epoch: 17 [10284/10284]	Loss: 0.3398	LR: 0.020000
Epoch 17 - Average Train Loss: 0.2757, Train Accuracy: 0.8849
Epoch 17 training time consumed: 149.12s
Evaluating Network.....
Test set: Epoch: 17, Average loss: 0.0010, Accuracy: 0.9080, Time consumed:8.10s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-17-best.pth
Training Epoch: 18 [256/10284]	Loss: 0.2745	LR: 0.020000
Training Epoch: 18 [512/10284]	Loss: 0.2276	LR: 0.020000
Training Epoch: 18 [768/10284]	Loss: 0.2980	LR: 0.020000
Training Epoch: 18 [1024/10284]	Loss: 0.2978	LR: 0.020000
Training Epoch: 18 [1280/10284]	Loss: 0.2804	LR: 0.020000
Training Epoch: 18 [1536/10284]	Loss: 0.2416	LR: 0.020000
Training Epoch: 18 [1792/10284]	Loss: 0.2087	LR: 0.020000
Training Epoch: 18 [2048/10284]	Loss: 0.2233	LR: 0.020000
Training Epoch: 18 [2304/10284]	Loss: 0.2016	LR: 0.020000
Training Epoch: 18 [2560/10284]	Loss: 0.2817	LR: 0.020000
Training Epoch: 18 [2816/10284]	Loss: 0.2189	LR: 0.020000
Training Epoch: 18 [3072/10284]	Loss: 0.2610	LR: 0.020000
Training Epoch: 18 [3328/10284]	Loss: 0.1904	LR: 0.020000
Training Epoch: 18 [3584/10284]	Loss: 0.2957	LR: 0.020000
Training Epoch: 18 [3840/10284]	Loss: 0.2563	LR: 0.020000
Training Epoch: 18 [4096/10284]	Loss: 0.2319	LR: 0.020000
Training Epoch: 18 [4352/10284]	Loss: 0.1866	LR: 0.020000
Training Epoch: 18 [4608/10284]	Loss: 0.2354	LR: 0.020000
Training Epoch: 18 [4864/10284]	Loss: 0.2041	LR: 0.020000
Training Epoch: 18 [5120/10284]	Loss: 0.1773	LR: 0.020000
Training Epoch: 18 [5376/10284]	Loss: 0.2229	LR: 0.020000
Training Epoch: 18 [5632/10284]	Loss: 0.1905	LR: 0.020000
Training Epoch: 18 [5888/10284]	Loss: 0.1981	LR: 0.020000
Training Epoch: 18 [6144/10284]	Loss: 0.2135	LR: 0.020000
Training Epoch: 18 [6400/10284]	Loss: 0.1595	LR: 0.020000
Training Epoch: 18 [6656/10284]	Loss: 0.1870	LR: 0.020000
Training Epoch: 18 [6912/10284]	Loss: 0.2356	LR: 0.020000
Training Epoch: 18 [7168/10284]	Loss: 0.2493	LR: 0.020000
Training Epoch: 18 [7424/10284]	Loss: 0.2268	LR: 0.020000
Training Epoch: 18 [7680/10284]	Loss: 0.2392	LR: 0.020000
Training Epoch: 18 [7936/10284]	Loss: 0.3324	LR: 0.020000
Training Epoch: 18 [8192/10284]	Loss: 0.2058	LR: 0.020000
Training Epoch: 18 [8448/10284]	Loss: 0.2203	LR: 0.020000
Training Epoch: 18 [8704/10284]	Loss: 0.2002	LR: 0.020000
Training Epoch: 18 [8960/10284]	Loss: 0.2513	LR: 0.020000
Training Epoch: 18 [9216/10284]	Loss: 0.2625	LR: 0.020000
Training Epoch: 18 [9472/10284]	Loss: 0.2670	LR: 0.020000
Training Epoch: 18 [9728/10284]	Loss: 0.2041	LR: 0.020000
Training Epoch: 18 [9984/10284]	Loss: 0.2408	LR: 0.020000
Training Epoch: 18 [10240/10284]	Loss: 0.2511	LR: 0.020000
Training Epoch: 18 [10284/10284]	Loss: 0.1554	LR: 0.020000
Epoch 18 - Average Train Loss: 0.2334, Train Accuracy: 0.9026
Epoch 18 training time consumed: 149.24s
Evaluating Network.....
Test set: Epoch: 18, Average loss: 0.0008, Accuracy: 0.9201, Time consumed:8.13s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-18-best.pth
Training Epoch: 19 [256/10284]	Loss: 0.1781	LR: 0.020000
Training Epoch: 19 [512/10284]	Loss: 0.2851	LR: 0.020000
Training Epoch: 19 [768/10284]	Loss: 0.2595	LR: 0.020000
Training Epoch: 19 [1024/10284]	Loss: 0.2308	LR: 0.020000
Training Epoch: 19 [1280/10284]	Loss: 0.2188	LR: 0.020000
Training Epoch: 19 [1536/10284]	Loss: 0.2491	LR: 0.020000
Training Epoch: 19 [1792/10284]	Loss: 0.2118	LR: 0.020000
Training Epoch: 19 [2048/10284]	Loss: 0.2237	LR: 0.020000
Training Epoch: 19 [2304/10284]	Loss: 0.2091	LR: 0.020000
Training Epoch: 19 [2560/10284]	Loss: 0.2400	LR: 0.020000
Training Epoch: 19 [2816/10284]	Loss: 0.2127	LR: 0.020000
Training Epoch: 19 [3072/10284]	Loss: 0.2505	LR: 0.020000
Training Epoch: 19 [3328/10284]	Loss: 0.2470	LR: 0.020000
Training Epoch: 19 [3584/10284]	Loss: 0.2258	LR: 0.020000
Training Epoch: 19 [3840/10284]	Loss: 0.1881	LR: 0.020000
Training Epoch: 19 [4096/10284]	Loss: 0.1858	LR: 0.020000
Training Epoch: 19 [4352/10284]	Loss: 0.2317	LR: 0.020000
Training Epoch: 19 [4608/10284]	Loss: 0.2623	LR: 0.020000
Training Epoch: 19 [4864/10284]	Loss: 0.2395	LR: 0.020000
Training Epoch: 19 [5120/10284]	Loss: 0.2346	LR: 0.020000
Training Epoch: 19 [5376/10284]	Loss: 0.1895	LR: 0.020000
Training Epoch: 19 [5632/10284]	Loss: 0.2216	LR: 0.020000
Training Epoch: 19 [5888/10284]	Loss: 0.2216	LR: 0.020000
Training Epoch: 19 [6144/10284]	Loss: 0.2176	LR: 0.020000
Training Epoch: 19 [6400/10284]	Loss: 0.2425	LR: 0.020000
Training Epoch: 19 [6656/10284]	Loss: 0.2305	LR: 0.020000
Training Epoch: 19 [6912/10284]	Loss: 0.2231	LR: 0.020000
Training Epoch: 19 [7168/10284]	Loss: 0.2293	LR: 0.020000
Training Epoch: 19 [7424/10284]	Loss: 0.2315	LR: 0.020000
Training Epoch: 19 [7680/10284]	Loss: 0.2010	LR: 0.020000
Training Epoch: 19 [7936/10284]	Loss: 0.2042	LR: 0.020000
Training Epoch: 19 [8192/10284]	Loss: 0.2455	LR: 0.020000
Training Epoch: 19 [8448/10284]	Loss: 0.1938	LR: 0.020000
Training Epoch: 19 [8704/10284]	Loss: 0.1891	LR: 0.020000
Training Epoch: 19 [8960/10284]	Loss: 0.2368	LR: 0.020000
Training Epoch: 19 [9216/10284]	Loss: 0.1309	LR: 0.020000
Training Epoch: 19 [9472/10284]	Loss: 0.1837	LR: 0.020000
Training Epoch: 19 [9728/10284]	Loss: 0.2033	LR: 0.020000
Training Epoch: 19 [9984/10284]	Loss: 0.2009	LR: 0.020000
Training Epoch: 19 [10240/10284]	Loss: 0.1761	LR: 0.020000
Training Epoch: 19 [10284/10284]	Loss: 0.4326	LR: 0.020000
Epoch 19 - Average Train Loss: 0.2198, Train Accuracy: 0.9076
Epoch 19 training time consumed: 148.36s
Evaluating Network.....
Test set: Epoch: 19, Average loss: 0.0012, Accuracy: 0.8925, Time consumed:7.83s
Training Epoch: 20 [256/10284]	Loss: 0.1865	LR: 0.004000
Training Epoch: 20 [512/10284]	Loss: 0.1818	LR: 0.004000
Training Epoch: 20 [768/10284]	Loss: 0.2120	LR: 0.004000
Training Epoch: 20 [1024/10284]	Loss: 0.1963	LR: 0.004000
Training Epoch: 20 [1280/10284]	Loss: 0.1831	LR: 0.004000
Training Epoch: 20 [1536/10284]	Loss: 0.2498	LR: 0.004000
Training Epoch: 20 [1792/10284]	Loss: 0.1632	LR: 0.004000
Training Epoch: 20 [2048/10284]	Loss: 0.1690	LR: 0.004000
Training Epoch: 20 [2304/10284]	Loss: 0.2011	LR: 0.004000
Training Epoch: 20 [2560/10284]	Loss: 0.1681	LR: 0.004000
Training Epoch: 20 [2816/10284]	Loss: 0.1757	LR: 0.004000
Training Epoch: 20 [3072/10284]	Loss: 0.2114	LR: 0.004000
Training Epoch: 20 [3328/10284]	Loss: 0.1878	LR: 0.004000
Training Epoch: 20 [3584/10284]	Loss: 0.1767	LR: 0.004000
Training Epoch: 20 [3840/10284]	Loss: 0.1669	LR: 0.004000
Training Epoch: 20 [4096/10284]	Loss: 0.1609	LR: 0.004000
Training Epoch: 20 [4352/10284]	Loss: 0.1616	LR: 0.004000
Training Epoch: 20 [4608/10284]	Loss: 0.2460	LR: 0.004000
Training Epoch: 20 [4864/10284]	Loss: 0.2228	LR: 0.004000
Training Epoch: 20 [5120/10284]	Loss: 0.1961	LR: 0.004000
Training Epoch: 20 [5376/10284]	Loss: 0.1211	LR: 0.004000
Training Epoch: 20 [5632/10284]	Loss: 0.2107	LR: 0.004000
Training Epoch: 20 [5888/10284]	Loss: 0.2222	LR: 0.004000
Training Epoch: 20 [6144/10284]	Loss: 0.1859	LR: 0.004000
Training Epoch: 20 [6400/10284]	Loss: 0.2238	LR: 0.004000
Training Epoch: 20 [6656/10284]	Loss: 0.1891	LR: 0.004000
Training Epoch: 20 [6912/10284]	Loss: 0.1949	LR: 0.004000
Training Epoch: 20 [7168/10284]	Loss: 0.2494	LR: 0.004000
Training Epoch: 20 [7424/10284]	Loss: 0.1724	LR: 0.004000
Training Epoch: 20 [7680/10284]	Loss: 0.1776	LR: 0.004000
Training Epoch: 20 [7936/10284]	Loss: 0.2197	LR: 0.004000
Training Epoch: 20 [8192/10284]	Loss: 0.1679	LR: 0.004000
Training Epoch: 20 [8448/10284]	Loss: 0.2336	LR: 0.004000
Training Epoch: 20 [8704/10284]	Loss: 0.1910	LR: 0.004000
Training Epoch: 20 [8960/10284]	Loss: 0.1927	LR: 0.004000
Training Epoch: 20 [9216/10284]	Loss: 0.1688	LR: 0.004000
Training Epoch: 20 [9472/10284]	Loss: 0.1597	LR: 0.004000
Training Epoch: 20 [9728/10284]	Loss: 0.2124	LR: 0.004000
Training Epoch: 20 [9984/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 20 [10240/10284]	Loss: 0.1788	LR: 0.004000
Training Epoch: 20 [10284/10284]	Loss: 0.1081	LR: 0.004000
Epoch 20 - Average Train Loss: 0.1908, Train Accuracy: 0.9201
Epoch 20 training time consumed: 148.02s
Evaluating Network.....
Test set: Epoch: 20, Average loss: 0.0006, Accuracy: 0.9395, Time consumed:7.96s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-20-best.pth
Training Epoch: 21 [256/10284]	Loss: 0.1546	LR: 0.004000
Training Epoch: 21 [512/10284]	Loss: 0.2274	LR: 0.004000
Training Epoch: 21 [768/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 21 [1024/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 21 [1280/10284]	Loss: 0.1561	LR: 0.004000
Training Epoch: 21 [1536/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 21 [1792/10284]	Loss: 0.1602	LR: 0.004000
Training Epoch: 21 [2048/10284]	Loss: 0.1684	LR: 0.004000
Training Epoch: 21 [2304/10284]	Loss: 0.1698	LR: 0.004000
Training Epoch: 21 [2560/10284]	Loss: 0.1494	LR: 0.004000
Training Epoch: 21 [2816/10284]	Loss: 0.1900	LR: 0.004000
Training Epoch: 21 [3072/10284]	Loss: 0.1308	LR: 0.004000
Training Epoch: 21 [3328/10284]	Loss: 0.1745	LR: 0.004000
Training Epoch: 21 [3584/10284]	Loss: 0.1681	LR: 0.004000
Training Epoch: 21 [3840/10284]	Loss: 0.1946	LR: 0.004000
Training Epoch: 21 [4096/10284]	Loss: 0.1510	LR: 0.004000
Training Epoch: 21 [4352/10284]	Loss: 0.1768	LR: 0.004000
Training Epoch: 21 [4608/10284]	Loss: 0.1501	LR: 0.004000
Training Epoch: 21 [4864/10284]	Loss: 0.1642	LR: 0.004000
Training Epoch: 21 [5120/10284]	Loss: 0.2362	LR: 0.004000
Training Epoch: 21 [5376/10284]	Loss: 0.2270	LR: 0.004000
Training Epoch: 21 [5632/10284]	Loss: 0.1226	LR: 0.004000
Training Epoch: 21 [5888/10284]	Loss: 0.1833	LR: 0.004000
Training Epoch: 21 [6144/10284]	Loss: 0.2222	LR: 0.004000
Training Epoch: 21 [6400/10284]	Loss: 0.1544	LR: 0.004000
Training Epoch: 21 [6656/10284]	Loss: 0.1797	LR: 0.004000
Training Epoch: 21 [6912/10284]	Loss: 0.2136	LR: 0.004000
Training Epoch: 21 [7168/10284]	Loss: 0.1853	LR: 0.004000
Training Epoch: 21 [7424/10284]	Loss: 0.1653	LR: 0.004000
Training Epoch: 21 [7680/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 21 [7936/10284]	Loss: 0.1581	LR: 0.004000
Training Epoch: 21 [8192/10284]	Loss: 0.1426	LR: 0.004000
Training Epoch: 21 [8448/10284]	Loss: 0.1587	LR: 0.004000
Training Epoch: 21 [8704/10284]	Loss: 0.1687	LR: 0.004000
Training Epoch: 21 [8960/10284]	Loss: 0.1775	LR: 0.004000
Training Epoch: 21 [9216/10284]	Loss: 0.1610	LR: 0.004000
Training Epoch: 21 [9472/10284]	Loss: 0.1707	LR: 0.004000
Training Epoch: 21 [9728/10284]	Loss: 0.1927	LR: 0.004000
Training Epoch: 21 [9984/10284]	Loss: 0.2019	LR: 0.004000
Training Epoch: 21 [10240/10284]	Loss: 0.1421	LR: 0.004000
Training Epoch: 21 [10284/10284]	Loss: 0.2096	LR: 0.004000
Epoch 21 - Average Train Loss: 0.1716, Train Accuracy: 0.9277
Epoch 21 training time consumed: 148.99s
Evaluating Network.....
Test set: Epoch: 21, Average loss: 0.0006, Accuracy: 0.9419, Time consumed:7.81s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-21-best.pth
Training Epoch: 22 [256/10284]	Loss: 0.1791	LR: 0.004000
Training Epoch: 22 [512/10284]	Loss: 0.2050	LR: 0.004000
Training Epoch: 22 [768/10284]	Loss: 0.1896	LR: 0.004000
Training Epoch: 22 [1024/10284]	Loss: 0.2002	LR: 0.004000
Training Epoch: 22 [1280/10284]	Loss: 0.1311	LR: 0.004000
Training Epoch: 22 [1536/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 22 [1792/10284]	Loss: 0.1380	LR: 0.004000
Training Epoch: 22 [2048/10284]	Loss: 0.1550	LR: 0.004000
Training Epoch: 22 [2304/10284]	Loss: 0.1627	LR: 0.004000
Training Epoch: 22 [2560/10284]	Loss: 0.1459	LR: 0.004000
Training Epoch: 22 [2816/10284]	Loss: 0.1447	LR: 0.004000
Training Epoch: 22 [3072/10284]	Loss: 0.1558	LR: 0.004000
Training Epoch: 22 [3328/10284]	Loss: 0.1854	LR: 0.004000
Training Epoch: 22 [3584/10284]	Loss: 0.1561	LR: 0.004000
Training Epoch: 22 [3840/10284]	Loss: 0.1604	LR: 0.004000
Training Epoch: 22 [4096/10284]	Loss: 0.1647	LR: 0.004000
Training Epoch: 22 [4352/10284]	Loss: 0.1540	LR: 0.004000
Training Epoch: 22 [4608/10284]	Loss: 0.1499	LR: 0.004000
Training Epoch: 22 [4864/10284]	Loss: 0.1944	LR: 0.004000
Training Epoch: 22 [5120/10284]	Loss: 0.1603	LR: 0.004000
Training Epoch: 22 [5376/10284]	Loss: 0.1779	LR: 0.004000
Training Epoch: 22 [5632/10284]	Loss: 0.1239	LR: 0.004000
Training Epoch: 22 [5888/10284]	Loss: 0.2001	LR: 0.004000
Training Epoch: 22 [6144/10284]	Loss: 0.1921	LR: 0.004000
Training Epoch: 22 [6400/10284]	Loss: 0.1777	LR: 0.004000
Training Epoch: 22 [6656/10284]	Loss: 0.1755	LR: 0.004000
Training Epoch: 22 [6912/10284]	Loss: 0.1750	LR: 0.004000
Training Epoch: 22 [7168/10284]	Loss: 0.1653	LR: 0.004000
Training Epoch: 22 [7424/10284]	Loss: 0.2129	LR: 0.004000
Training Epoch: 22 [7680/10284]	Loss: 0.2488	LR: 0.004000
Training Epoch: 22 [7936/10284]	Loss: 0.1716	LR: 0.004000
Training Epoch: 22 [8192/10284]	Loss: 0.2515	LR: 0.004000
Training Epoch: 22 [8448/10284]	Loss: 0.1360	LR: 0.004000
Training Epoch: 22 [8704/10284]	Loss: 0.1548	LR: 0.004000
Training Epoch: 22 [8960/10284]	Loss: 0.1462	LR: 0.004000
Training Epoch: 22 [9216/10284]	Loss: 0.1755	LR: 0.004000
Training Epoch: 22 [9472/10284]	Loss: 0.1569	LR: 0.004000
Training Epoch: 22 [9728/10284]	Loss: 0.1929	LR: 0.004000
Training Epoch: 22 [9984/10284]	Loss: 0.1411	LR: 0.004000
Training Epoch: 22 [10240/10284]	Loss: 0.2242	LR: 0.004000
Training Epoch: 22 [10284/10284]	Loss: 0.1647	LR: 0.004000
Epoch 22 - Average Train Loss: 0.1720, Train Accuracy: 0.9292
Epoch 22 training time consumed: 148.63s
Evaluating Network.....
Test set: Epoch: 22, Average loss: 0.0006, Accuracy: 0.9366, Time consumed:7.88s
Training Epoch: 23 [256/10284]	Loss: 0.1794	LR: 0.004000
Training Epoch: 23 [512/10284]	Loss: 0.2046	LR: 0.004000
Training Epoch: 23 [768/10284]	Loss: 0.1850	LR: 0.004000
Training Epoch: 23 [1024/10284]	Loss: 0.1937	LR: 0.004000
Training Epoch: 23 [1280/10284]	Loss: 0.1614	LR: 0.004000
Training Epoch: 23 [1536/10284]	Loss: 0.1282	LR: 0.004000
Training Epoch: 23 [1792/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 23 [2048/10284]	Loss: 0.1954	LR: 0.004000
Training Epoch: 23 [2304/10284]	Loss: 0.1814	LR: 0.004000
Training Epoch: 23 [2560/10284]	Loss: 0.1496	LR: 0.004000
Training Epoch: 23 [2816/10284]	Loss: 0.2235	LR: 0.004000
Training Epoch: 23 [3072/10284]	Loss: 0.1596	LR: 0.004000
Training Epoch: 23 [3328/10284]	Loss: 0.1787	LR: 0.004000
Training Epoch: 23 [3584/10284]	Loss: 0.1523	LR: 0.004000
Training Epoch: 23 [3840/10284]	Loss: 0.1201	LR: 0.004000
Training Epoch: 23 [4096/10284]	Loss: 0.1539	LR: 0.004000
Training Epoch: 23 [4352/10284]	Loss: 0.1183	LR: 0.004000
Training Epoch: 23 [4608/10284]	Loss: 0.1877	LR: 0.004000
Training Epoch: 23 [4864/10284]	Loss: 0.1780	LR: 0.004000
Training Epoch: 23 [5120/10284]	Loss: 0.1394	LR: 0.004000
Training Epoch: 23 [5376/10284]	Loss: 0.1968	LR: 0.004000
Training Epoch: 23 [5632/10284]	Loss: 0.1415	LR: 0.004000
Training Epoch: 23 [5888/10284]	Loss: 0.1417	LR: 0.004000
Training Epoch: 23 [6144/10284]	Loss: 0.1933	LR: 0.004000
Training Epoch: 23 [6400/10284]	Loss: 0.1166	LR: 0.004000
Training Epoch: 23 [6656/10284]	Loss: 0.1379	LR: 0.004000
Training Epoch: 23 [6912/10284]	Loss: 0.1379	LR: 0.004000
Training Epoch: 23 [7168/10284]	Loss: 0.1265	LR: 0.004000
Training Epoch: 23 [7424/10284]	Loss: 0.1433	LR: 0.004000
Training Epoch: 23 [7680/10284]	Loss: 0.1505	LR: 0.004000
Training Epoch: 23 [7936/10284]	Loss: 0.1868	LR: 0.004000
Training Epoch: 23 [8192/10284]	Loss: 0.2035	LR: 0.004000
Training Epoch: 23 [8448/10284]	Loss: 0.1997	LR: 0.004000
Training Epoch: 23 [8704/10284]	Loss: 0.1213	LR: 0.004000
Training Epoch: 23 [8960/10284]	Loss: 0.1703	LR: 0.004000
Training Epoch: 23 [9216/10284]	Loss: 0.1564	LR: 0.004000
Training Epoch: 23 [9472/10284]	Loss: 0.1418	LR: 0.004000
Training Epoch: 23 [9728/10284]	Loss: 0.1820	LR: 0.004000
Training Epoch: 23 [9984/10284]	Loss: 0.1729	LR: 0.004000
Training Epoch: 23 [10240/10284]	Loss: 0.2211	LR: 0.004000
Training Epoch: 23 [10284/10284]	Loss: 0.0989	LR: 0.004000
Epoch 23 - Average Train Loss: 0.1638, Train Accuracy: 0.9295
Epoch 23 training time consumed: 148.66s
Evaluating Network.....
Test set: Epoch: 23, Average loss: 0.0006, Accuracy: 0.9404, Time consumed:7.97s
Training Epoch: 24 [256/10284]	Loss: 0.1980	LR: 0.004000
Training Epoch: 24 [512/10284]	Loss: 0.1515	LR: 0.004000
Training Epoch: 24 [768/10284]	Loss: 0.1706	LR: 0.004000
Training Epoch: 24 [1024/10284]	Loss: 0.1578	LR: 0.004000
Training Epoch: 24 [1280/10284]	Loss: 0.1803	LR: 0.004000
Training Epoch: 24 [1536/10284]	Loss: 0.1495	LR: 0.004000
Training Epoch: 24 [1792/10284]	Loss: 0.1598	LR: 0.004000
Training Epoch: 24 [2048/10284]	Loss: 0.1406	LR: 0.004000
Training Epoch: 24 [2304/10284]	Loss: 0.1244	LR: 0.004000
Training Epoch: 24 [2560/10284]	Loss: 0.1722	LR: 0.004000
Training Epoch: 24 [2816/10284]	Loss: 0.2030	LR: 0.004000
Training Epoch: 24 [3072/10284]	Loss: 0.1822	LR: 0.004000
Training Epoch: 24 [3328/10284]	Loss: 0.1472	LR: 0.004000
Training Epoch: 24 [3584/10284]	Loss: 0.1473	LR: 0.004000
Training Epoch: 24 [3840/10284]	Loss: 0.1901	LR: 0.004000
Training Epoch: 24 [4096/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 24 [4352/10284]	Loss: 0.1896	LR: 0.004000
Training Epoch: 24 [4608/10284]	Loss: 0.1122	LR: 0.004000
Training Epoch: 24 [4864/10284]	Loss: 0.1562	LR: 0.004000
Training Epoch: 24 [5120/10284]	Loss: 0.1422	LR: 0.004000
Training Epoch: 24 [5376/10284]	Loss: 0.1490	LR: 0.004000
Training Epoch: 24 [5632/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 24 [5888/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 24 [6144/10284]	Loss: 0.1567	LR: 0.004000
Training Epoch: 24 [6400/10284]	Loss: 0.1130	LR: 0.004000
Training Epoch: 24 [6656/10284]	Loss: 0.1575	LR: 0.004000
Training Epoch: 24 [6912/10284]	Loss: 0.1579	LR: 0.004000
Training Epoch: 24 [7168/10284]	Loss: 0.2128	LR: 0.004000
Training Epoch: 24 [7424/10284]	Loss: 0.1609	LR: 0.004000
Training Epoch: 24 [7680/10284]	Loss: 0.1573	LR: 0.004000
Training Epoch: 24 [7936/10284]	Loss: 0.1685	LR: 0.004000
Training Epoch: 24 [8192/10284]	Loss: 0.1792	LR: 0.004000
Training Epoch: 24 [8448/10284]	Loss: 0.1312	LR: 0.004000
Training Epoch: 24 [8704/10284]	Loss: 0.2180	LR: 0.004000
Training Epoch: 24 [8960/10284]	Loss: 0.1237	LR: 0.004000
Training Epoch: 24 [9216/10284]	Loss: 0.2059	LR: 0.004000
Training Epoch: 24 [9472/10284]	Loss: 0.1534	LR: 0.004000
Training Epoch: 24 [9728/10284]	Loss: 0.1792	LR: 0.004000
Training Epoch: 24 [9984/10284]	Loss: 0.1546	LR: 0.004000
Training Epoch: 24 [10240/10284]	Loss: 0.1382	LR: 0.004000
Training Epoch: 24 [10284/10284]	Loss: 0.3228	LR: 0.004000
Epoch 24 - Average Train Loss: 0.1612, Train Accuracy: 0.9318
Epoch 24 training time consumed: 148.34s
Evaluating Network.....
Test set: Epoch: 24, Average loss: 0.0006, Accuracy: 0.9433, Time consumed:8.05s
Saving weights file to checkpoint/retrain/ResNet18/Monday_28_July_2025_00h_17m_14s/ResNet18-MUCAC-seed1-ret75-24-best.pth
Training Epoch: 25 [256/10284]	Loss: 0.1358	LR: 0.004000
Training Epoch: 25 [512/10284]	Loss: 0.2084	LR: 0.004000
Training Epoch: 25 [768/10284]	Loss: 0.1742	LR: 0.004000
Training Epoch: 25 [1024/10284]	Loss: 0.1444	LR: 0.004000
Training Epoch: 25 [1280/10284]	Loss: 0.1870	LR: 0.004000
Training Epoch: 25 [1536/10284]	Loss: 0.1605	LR: 0.004000
Training Epoch: 25 [1792/10284]	Loss: 0.1685	LR: 0.004000
Training Epoch: 25 [2048/10284]	Loss: 0.1560	LR: 0.004000
Training Epoch: 25 [2304/10284]	Loss: 0.1727	LR: 0.004000
Training Epoch: 25 [2560/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 25 [2816/10284]	Loss: 0.1247	LR: 0.004000
Training Epoch: 25 [3072/10284]	Loss: 0.1671	LR: 0.004000
Training Epoch: 25 [3328/10284]	Loss: 0.2093	LR: 0.004000
Training Epoch: 25 [3584/10284]	Loss: 0.1746	LR: 0.004000
Training Epoch: 25 [3840/10284]	Loss: 0.1348	LR: 0.004000
Training Epoch: 25 [4096/10284]	Loss: 0.1593	LR: 0.004000
Training Epoch: 25 [4352/10284]	Loss: 0.1657	LR: 0.004000
Training Epoch: 25 [4608/10284]	Loss: 0.1143	LR: 0.004000
Training Epoch: 25 [4864/10284]	Loss: 0.2049	LR: 0.004000
Training Epoch: 25 [5120/10284]	Loss: 0.1481	LR: 0.004000
Training Epoch: 25 [5376/10284]	Loss: 0.1552	LR: 0.004000
Training Epoch: 25 [5632/10284]	Loss: 0.1305	LR: 0.004000
Training Epoch: 25 [5888/10284]	Loss: 0.1841	LR: 0.004000
Training Epoch: 25 [6144/10284]	Loss: 0.1559	LR: 0.004000
Training Epoch: 25 [6400/10284]	Loss: 0.1345	LR: 0.004000
Training Epoch: 25 [6656/10284]	Loss: 0.1491	LR: 0.004000
Training Epoch: 25 [6912/10284]	Loss: 0.1492	LR: 0.004000
Training Epoch: 25 [7168/10284]	Loss: 0.1864	LR: 0.004000
Training Epoch: 25 [7424/10284]	Loss: 0.1435	LR: 0.004000
Training Epoch: 25 [7680/10284]	Loss: 0.1584	LR: 0.004000
Training Epoch: 25 [7936/10284]	Loss: 0.1575	LR: 0.004000
Training Epoch: 25 [8192/10284]	Loss: 0.1394	LR: 0.004000
Training Epoch: 25 [8448/10284]	Loss: 0.1822	LR: 0.004000
Training Epoch: 25 [8704/10284]	Loss: 0.1385	LR: 0.004000
Training Epoch: 25 [8960/10284]	Loss: 0.1731	LR: 0.004000
Training Epoch: 25 [9216/10284]	Loss: 0.1413	LR: 0.004000
Training Epoch: 25 [9472/10284]	Loss: 0.1234	LR: 0.004000
Training Epoch: 25 [9728/10284]	Loss: 0.1205	LR: 0.004000
Training Epoch: 25 [9984/10284]	Loss: 0.1662	LR: 0.004000
Training Epoch: 25 [10240/10284]	Loss: 0.1534	LR: 0.004000
Training Epoch: 25 [10284/10284]	Loss: 0.2168	LR: 0.004000
Epoch 25 - Average Train Loss: 0.1579, Train Accuracy: 0.9344
Epoch 25 training time consumed: 148.72s
Evaluating Network.....
Test set: Epoch: 25, Average loss: 0.0007, Accuracy: 0.9361, Time consumed:8.01s
Training Epoch: 26 [256/10284]	Loss: 0.1959	LR: 0.004000
Training Epoch: 26 [512/10284]	Loss: 0.1707	LR: 0.004000
Training Epoch: 26 [768/10284]	Loss: 0.1499	LR: 0.004000
Training Epoch: 26 [1024/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 26 [1280/10284]	Loss: 0.1033	LR: 0.004000
Training Epoch: 26 [1536/10284]	Loss: 0.1040	LR: 0.004000
Training Epoch: 26 [1792/10284]	Loss: 0.1416	LR: 0.004000
Training Epoch: 26 [2048/10284]	Loss: 0.1880	LR: 0.004000
Training Epoch: 26 [2304/10284]	Loss: 0.1627	LR: 0.004000
Training Epoch: 26 [2560/10284]	Loss: 0.1846	LR: 0.004000
Training Epoch: 26 [2816/10284]	Loss: 0.1606	LR: 0.004000
Training Epoch: 26 [3072/10284]	Loss: 0.1437	LR: 0.004000
Training Epoch: 26 [3328/10284]	Loss: 0.1842	LR: 0.004000
Training Epoch: 26 [3584/10284]	Loss: 0.1173	LR: 0.004000
Training Epoch: 26 [3840/10284]	Loss: 0.1202	LR: 0.004000
Training Epoch: 26 [4096/10284]	Loss: 0.1321	LR: 0.004000
Training Epoch: 26 [4352/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 26 [4608/10284]	Loss: 0.1717	LR: 0.004000
Training Epoch: 26 [4864/10284]	Loss: 0.1621	LR: 0.004000
Training Epoch: 26 [5120/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 26 [5376/10284]	Loss: 0.1524	LR: 0.004000
Training Epoch: 26 [5632/10284]	Loss: 0.1800	LR: 0.004000
Training Epoch: 26 [5888/10284]	Loss: 0.2003	LR: 0.004000
Training Epoch: 26 [6144/10284]	Loss: 0.1772	LR: 0.004000
Training Epoch: 26 [6400/10284]	Loss: 0.1739	LR: 0.004000
Training Epoch: 26 [6656/10284]	Loss: 0.1829	LR: 0.004000
Training Epoch: 26 [6912/10284]	Loss: 0.1910	LR: 0.004000
Training Epoch: 26 [7168/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [7424/10284]	Loss: 0.1692	LR: 0.004000
Training Epoch: 26 [7680/10284]	Loss: 0.1251	LR: 0.004000
Training Epoch: 26 [7936/10284]	Loss: 0.1210	LR: 0.004000
Training Epoch: 26 [8192/10284]	Loss: 0.1125	LR: 0.004000
Training Epoch: 26 [8448/10284]	Loss: 0.1651	LR: 0.004000
Training Epoch: 26 [8704/10284]	Loss: 0.1878	LR: 0.004000
Training Epoch: 26 [8960/10284]	Loss: 0.2052	LR: 0.004000
Training Epoch: 26 [9216/10284]	Loss: 0.1644	LR: 0.004000
Training Epoch: 26 [9472/10284]	Loss: 0.1332	LR: 0.004000
Training Epoch: 26 [9728/10284]	Loss: 0.1345	LR: 0.004000
Training Epoch: 26 [9984/10284]	Loss: 0.1372	LR: 0.004000
Training Epoch: 26 [10240/10284]	Loss: 0.1850	LR: 0.004000
Training Epoch: 26 [10284/10284]	Loss: 0.4047	LR: 0.004000
Epoch 26 - Average Train Loss: 0.1573, Train Accuracy: 0.9344
Epoch 26 training time consumed: 148.62s
Evaluating Network.....
Test set: Epoch: 26, Average loss: 0.0007, Accuracy: 0.9322, Time consumed:8.04s
Training Epoch: 27 [256/10284]	Loss: 0.1766	LR: 0.004000
Training Epoch: 27 [512/10284]	Loss: 0.1835	LR: 0.004000
Training Epoch: 27 [768/10284]	Loss: 0.1456	LR: 0.004000
Training Epoch: 27 [1024/10284]	Loss: 0.1825	LR: 0.004000
Training Epoch: 27 [1280/10284]	Loss: 0.1741	LR: 0.004000
Training Epoch: 27 [1536/10284]	Loss: 0.1637	LR: 0.004000
Training Epoch: 27 [1792/10284]	Loss: 0.2181	LR: 0.004000
Training Epoch: 27 [2048/10284]	Loss: 0.1718	LR: 0.004000
Training Epoch: 27 [2304/10284]	Loss: 0.1612	LR: 0.004000
Training Epoch: 27 [2560/10284]	Loss: 0.2143	LR: 0.004000
Training Epoch: 27 [2816/10284]	Loss: 0.1258	LR: 0.004000
Training Epoch: 27 [3072/10284]	Loss: 0.1337	LR: 0.004000
Training Epoch: 27 [3328/10284]	Loss: 0.1544	LR: 0.004000
Training Epoch: 27 [3584/10284]	Loss: 0.1324	LR: 0.004000
Training Epoch: 27 [3840/10284]	Loss: 0.1613	LR: 0.004000
Training Epoch: 27 [4096/10284]	Loss: 0.1509	LR: 0.004000
Training Epoch: 27 [4352/10284]	Loss: 0.1654	LR: 0.004000
Training Epoch: 27 [4608/10284]	Loss: 0.1113	LR: 0.004000
Training Epoch: 27 [4864/10284]	Loss: 0.1751	LR: 0.004000
Training Epoch: 27 [5120/10284]	Loss: 0.1819	LR: 0.004000
Training Epoch: 27 [5376/10284]	Loss: 0.1611	LR: 0.004000
Training Epoch: 27 [5632/10284]	Loss: 0.1912	LR: 0.004000
Training Epoch: 27 [5888/10284]	Loss: 0.1654	LR: 0.004000
Training Epoch: 27 [6144/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 27 [6400/10284]	Loss: 0.1539	LR: 0.004000
Training Epoch: 27 [6656/10284]	Loss: 0.1361	LR: 0.004000
Training Epoch: 27 [6912/10284]	Loss: 0.1859	LR: 0.004000
Training Epoch: 27 [7168/10284]	Loss: 0.1443	LR: 0.004000
Training Epoch: 27 [7424/10284]	Loss: 0.1598	LR: 0.004000
Training Epoch: 27 [7680/10284]	Loss: 0.1764	LR: 0.004000
Training Epoch: 27 [7936/10284]	Loss: 0.1095	LR: 0.004000
Training Epoch: 27 [8192/10284]	Loss: 0.1729	LR: 0.004000
Training Epoch: 27 [8448/10284]	Loss: 0.1148	LR: 0.004000
Training Epoch: 27 [8704/10284]	Loss: 0.1316	LR: 0.004000
Training Epoch: 27 [8960/10284]	Loss: 0.1528	LR: 0.004000
Training Epoch: 27 [9216/10284]	Loss: 0.1669	LR: 0.004000
Training Epoch: 27 [9472/10284]	Loss: 0.1085	LR: 0.004000
Training Epoch: 27 [9728/10284]	Loss: 0.2238	LR: 0.004000
Training Epoch: 27 [9984/10284]	Loss: 0.1767	LR: 0.004000
Training Epoch: 27 [10240/10284]	Loss: 0.1411	LR: 0.004000
Training Epoch: 27 [10284/10284]	Loss: 0.1839	LR: 0.004000
Epoch 27 - Average Train Loss: 0.1603, Train Accuracy: 0.9348
Epoch 27 training time consumed: 148.54s
Evaluating Network.....
Test set: Epoch: 27, Average loss: 0.0007, Accuracy: 0.9274, Time consumed:7.93s
Training Epoch: 28 [256/10284]	Loss: 0.1193	LR: 0.004000
Training Epoch: 28 [512/10284]	Loss: 0.1766	LR: 0.004000
Training Epoch: 28 [768/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 28 [1024/10284]	Loss: 0.1816	LR: 0.004000
Training Epoch: 28 [1280/10284]	Loss: 0.1717	LR: 0.004000
Training Epoch: 28 [1536/10284]	Loss: 0.1271	LR: 0.004000
Training Epoch: 28 [1792/10284]	Loss: 0.1996	LR: 0.004000
Training Epoch: 28 [2048/10284]	Loss: 0.1110	LR: 0.004000
Training Epoch: 28 [2304/10284]	Loss: 0.1880	LR: 0.004000
Training Epoch: 28 [2560/10284]	Loss: 0.1814	LR: 0.004000
Training Epoch: 28 [2816/10284]	Loss: 0.1848	LR: 0.004000
Training Epoch: 28 [3072/10284]	Loss: 0.1507	LR: 0.004000
Training Epoch: 28 [3328/10284]	Loss: 0.1719	LR: 0.004000
Training Epoch: 28 [3584/10284]	Loss: 0.1478	LR: 0.004000
Training Epoch: 28 [3840/10284]	Loss: 0.2138	LR: 0.004000
Training Epoch: 28 [4096/10284]	Loss: 0.1465	LR: 0.004000
Training Epoch: 28 [4352/10284]	Loss: 0.1333	LR: 0.004000
Training Epoch: 28 [4608/10284]	Loss: 0.1367	LR: 0.004000
Training Epoch: 28 [4864/10284]	Loss: 0.1549	LR: 0.004000
Training Epoch: 28 [5120/10284]	Loss: 0.1425	LR: 0.004000
Training Epoch: 28 [5376/10284]	Loss: 0.1495	LR: 0.004000
Training Epoch: 28 [5632/10284]	Loss: 0.0959	LR: 0.004000
Training Epoch: 28 [5888/10284]	Loss: 0.1081	LR: 0.004000
Training Epoch: 28 [6144/10284]	Loss: 0.1677	LR: 0.004000
Training Epoch: 28 [6400/10284]	Loss: 0.1861	LR: 0.004000
Training Epoch: 28 [6656/10284]	Loss: 0.1294	LR: 0.004000
Training Epoch: 28 [6912/10284]	Loss: 0.1491	LR: 0.004000
Training Epoch: 28 [7168/10284]	Loss: 0.1622	LR: 0.004000
Training Epoch: 28 [7424/10284]	Loss: 0.1350	LR: 0.004000
Training Epoch: 28 [7680/10284]	Loss: 0.1264	LR: 0.004000
Training Epoch: 28 [7936/10284]	Loss: 0.1686	LR: 0.004000
Training Epoch: 28 [8192/10284]	Loss: 0.1269	LR: 0.004000
Training Epoch: 28 [8448/10284]	Loss: 0.1914	LR: 0.004000
Training Epoch: 28 [8704/10284]	Loss: 0.1514	LR: 0.004000
Training Epoch: 28 [8960/10284]	Loss: 0.1363	LR: 0.004000
Training Epoch: 28 [9216/10284]	Loss: 0.1033	LR: 0.004000
Training Epoch: 28 [9472/10284]	Loss: 0.1208	LR: 0.004000
Training Epoch: 28 [9728/10284]	Loss: 0.1175	LR: 0.004000
Training Epoch: 28 [9984/10284]	Loss: 0.1793	LR: 0.004000
Training Epoch: 28 [10240/10284]	Loss: 0.1630	LR: 0.004000
Training Epoch: 28 [10284/10284]	Loss: 0.3397	LR: 0.004000
Epoch 28 - Average Train Loss: 0.1522, Train Accuracy: 0.9350
Epoch 28 training time consumed: 148.76s
Evaluating Network.....
Test set: Epoch: 28, Average loss: 0.0008, Accuracy: 0.9249, Time consumed:7.82s
Training Epoch: 29 [256/10284]	Loss: 0.1240	LR: 0.004000
Training Epoch: 29 [512/10284]	Loss: 0.1431	LR: 0.004000
Training Epoch: 29 [768/10284]	Loss: 0.1346	LR: 0.004000
Training Epoch: 29 [1024/10284]	Loss: 0.1314	LR: 0.004000
Training Epoch: 29 [1280/10284]	Loss: 0.1537	LR: 0.004000
Training Epoch: 29 [1536/10284]	Loss: 0.0949	LR: 0.004000
Training Epoch: 29 [1792/10284]	Loss: 0.1152	LR: 0.004000
Training Epoch: 29 [2048/10284]	Loss: 0.1335	LR: 0.004000
Training Epoch: 29 [2304/10284]	Loss: 0.2021	LR: 0.004000
Training Epoch: 29 [2560/10284]	Loss: 0.1133	LR: 0.004000
Training Epoch: 29 [2816/10284]	Loss: 0.1462	LR: 0.004000
Training Epoch: 29 [3072/10284]	Loss: 0.1049	LR: 0.004000
Training Epoch: 29 [3328/10284]	Loss: 0.1191	LR: 0.004000
Training Epoch: 29 [3584/10284]	Loss: 0.1805	LR: 0.004000
Training Epoch: 29 [3840/10284]	Loss: 0.1337	LR: 0.004000
Training Epoch: 29 [4096/10284]	Loss: 0.1702	LR: 0.004000
Training Epoch: 29 [4352/10284]	Loss: 0.1274	LR: 0.004000
Training Epoch: 29 [4608/10284]	Loss: 0.2133	LR: 0.004000
Training Epoch: 29 [4864/10284]	Loss: 0.1798	LR: 0.004000
Training Epoch: 29 [5120/10284]	Loss: 0.1041	LR: 0.004000
Training Epoch: 29 [5376/10284]	Loss: 0.1625	LR: 0.004000
Training Epoch: 29 [5632/10284]	Loss: 0.1539	LR: 0.004000
Training Epoch: 29 [5888/10284]	Loss: 0.1652	LR: 0.004000
Training Epoch: 29 [6144/10284]	Loss: 0.1752	LR: 0.004000
Training Epoch: 29 [6400/10284]	Loss: 0.1933	LR: 0.004000
Training Epoch: 29 [6656/10284]	Loss: 0.1558	LR: 0.004000
Training Epoch: 29 [6912/10284]	Loss: 0.1589	LR: 0.004000
Training Epoch: 29 [7168/10284]	Loss: 0.1217	LR: 0.004000
Training Epoch: 29 [7424/10284]	Loss: 0.1671	LR: 0.004000
Training Epoch: 29 [7680/10284]	Loss: 0.1679	LR: 0.004000
Training Epoch: 29 [7936/10284]	Loss: 0.1215	LR: 0.004000
Training Epoch: 29 [8192/10284]	Loss: 0.1527	LR: 0.004000
Training Epoch: 29 [8448/10284]	Loss: 0.1387	LR: 0.004000
Training Epoch: 29 [8704/10284]	Loss: 0.1874	LR: 0.004000
Training Epoch: 29 [8960/10284]	Loss: 0.1638	LR: 0.004000
Training Epoch: 29 [9216/10284]	Loss: 0.1258	LR: 0.004000
Training Epoch: 29 [9472/10284]	Loss: 0.1694	LR: 0.004000
Training Epoch: 29 [9728/10284]	Loss: 0.1483	LR: 0.004000
Training Epoch: 29 [9984/10284]	Loss: 0.1533	LR: 0.004000
Training Epoch: 29 [10240/10284]	Loss: 0.1517	LR: 0.004000
Training Epoch: 29 [10284/10284]	Loss: 0.0379	LR: 0.004000
Epoch 29 - Average Train Loss: 0.1485, Train Accuracy: 0.9358
Epoch 29 training time consumed: 149.29s
Evaluating Network.....
Test set: Epoch: 29, Average loss: 0.0006, Accuracy: 0.9390, Time consumed:7.94s
Training Epoch: 30 [256/10284]	Loss: 0.1218	LR: 0.004000
Training Epoch: 30 [512/10284]	Loss: 0.1606	LR: 0.004000
Training Epoch: 30 [768/10284]	Loss: 0.1585	LR: 0.004000
Training Epoch: 30 [1024/10284]	Loss: 0.1358	LR: 0.004000
Training Epoch: 30 [1280/10284]	Loss: 0.1930	LR: 0.004000
Training Epoch: 30 [1536/10284]	Loss: 0.0798	LR: 0.004000
Training Epoch: 30 [1792/10284]	Loss: 0.0952	LR: 0.004000
Training Epoch: 30 [2048/10284]	Loss: 0.1399	LR: 0.004000
Training Epoch: 30 [2304/10284]	Loss: 0.1153	LR: 0.004000
Training Epoch: 30 [2560/10284]	Loss: 0.1070	LR: 0.004000
Training Epoch: 30 [2816/10284]	Loss: 0.1943	LR: 0.004000
Training Epoch: 30 [3072/10284]	Loss: 0.2082	LR: 0.004000
Training Epoch: 30 [3328/10284]	Loss: 0.1242	LR: 0.004000
Training Epoch: 30 [3584/10284]	Loss: 0.1500	LR: 0.004000
Training Epoch: 30 [3840/10284]	Loss: 0.1829	LR: 0.004000
Training Epoch: 30 [4096/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 30 [4352/10284]	Loss: 0.1896	LR: 0.004000
Training Epoch: 30 [4608/10284]	Loss: 0.1424	LR: 0.004000
Training Epoch: 30 [4864/10284]	Loss: 0.1247	LR: 0.004000
Training Epoch: 30 [5120/10284]	Loss: 0.1427	LR: 0.004000
Training Epoch: 30 [5376/10284]	Loss: 0.1068	LR: 0.004000
Training Epoch: 30 [5632/10284]	Loss: 0.1234	LR: 0.004000
Training Epoch: 30 [5888/10284]	Loss: 0.1825	LR: 0.004000
Training Epoch: 30 [6144/10284]	Loss: 0.1402	LR: 0.004000
Training Epoch: 30 [6400/10284]	Loss: 0.1464	LR: 0.004000
Training Epoch: 30 [6656/10284]	Loss: 0.1476	LR: 0.004000
Training Epoch: 30 [6912/10284]	Loss: 0.1647	LR: 0.004000
Training Epoch: 30 [7168/10284]	Loss: 0.1869	LR: 0.004000
Training Epoch: 30 [7424/10284]	Loss: 0.1600	LR: 0.004000
Training Epoch: 30 [7680/10284]	Loss: 0.1201	LR: 0.004000
Training Epoch: 30 [7936/10284]	Loss: 0.1622	LR: 0.004000
Training Epoch: 30 [8192/10284]	Loss: 0.1994	LR: 0.004000
Training Epoch: 30 [8448/10284]	Loss: 0.2125	LR: 0.004000
Training Epoch: 30 [8704/10284]	Loss: 0.1560	LR: 0.004000
Training Epoch: 30 [8960/10284]	Loss: 0.1342	LR: 0.004000
Training Epoch: 30 [9216/10284]	Loss: 0.1696	LR: 0.004000
Training Epoch: 30 [9472/10284]	Loss: 0.1223	LR: 0.004000
Training Epoch: 30 [9728/10284]	Loss: 0.1386	LR: 0.004000
Training Epoch: 30 [9984/10284]	Loss: 0.1262	LR: 0.004000
Training Epoch: 30 [10240/10284]	Loss: 0.1157	LR: 0.004000
Training Epoch: 30 [10284/10284]	Loss: 0.1228	LR: 0.004000
Epoch 30 - Average Train Loss: 0.1479, Train Accuracy: 0.9364
Epoch 30 training time consumed: 148.48s
Evaluating Network.....
Test set: Epoch: 30, Average loss: 0.0006, Accuracy: 0.9409, Time consumed:8.10s
Training Epoch: 31 [256/10284]	Loss: 0.1493	LR: 0.004000
Training Epoch: 31 [512/10284]	Loss: 0.1489	LR: 0.004000
Training Epoch: 31 [768/10284]	Loss: 0.0851	LR: 0.004000
Training Epoch: 31 [1024/10284]	Loss: 0.1642	LR: 0.004000
Training Epoch: 31 [1280/10284]	Loss: 0.1293	LR: 0.004000
Training Epoch: 31 [1536/10284]	Loss: 0.1386	LR: 0.004000
Training Epoch: 31 [1792/10284]	Loss: 0.1529	LR: 0.004000
Training Epoch: 31 [2048/10284]	Loss: 0.1391	LR: 0.004000
Training Epoch: 31 [2304/10284]	Loss: 0.1878	LR: 0.004000
Training Epoch: 31 [2560/10284]	Loss: 0.1495	LR: 0.004000
Training Epoch: 31 [2816/10284]	Loss: 0.1527	LR: 0.004000
Training Epoch: 31 [3072/10284]	Loss: 0.1551	LR: 0.004000
Training Epoch: 31 [3328/10284]	Loss: 0.1537	LR: 0.004000
Training Epoch: 31 [3584/10284]	Loss: 0.0903	LR: 0.004000
Training Epoch: 31 [3840/10284]	Loss: 0.1011	LR: 0.004000
Training Epoch: 31 [4096/10284]	Loss: 0.1201	LR: 0.004000
Training Epoch: 31 [4352/10284]	Loss: 0.1953	LR: 0.004000
Training Epoch: 31 [4608/10284]	Loss: 0.2011	LR: 0.004000
Training Epoch: 31 [4864/10284]	Loss: 0.1258	LR: 0.004000
Training Epoch: 31 [5120/10284]	Loss: 0.1141	LR: 0.004000
Training Epoch: 31 [5376/10284]	Loss: 0.1386	LR: 0.004000
Training Epoch: 31 [5632/10284]	Loss: 0.1664	LR: 0.004000
Training Epoch: 31 [5888/10284]	Loss: 0.1319	LR: 0.004000
Training Epoch: 31 [6144/10284]	Loss: 0.1777	LR: 0.004000
Training Epoch: 31 [6400/10284]	Loss: 0.1220	LR: 0.004000
Training Epoch: 31 [6656/10284]	Loss: 0.1917	LR: 0.004000
Training Epoch: 31 [6912/10284]	Loss: 0.1943	LR: 0.004000
Training Epoch: 31 [7168/10284]	Loss: 0.1374	LR: 0.004000
Training Epoch: 31 [7424/10284]	Loss: 0.1689	LR: 0.004000
Training Epoch: 31 [7680/10284]	Loss: 0.1599	LR: 0.004000
Training Epoch: 31 [7936/10284]	Loss: 0.1219	LR: 0.004000
Training Epoch: 31 [8192/10284]	Loss: 0.1535	LR: 0.004000
Training Epoch: 31 [8448/10284]	Loss: 0.1221	LR: 0.004000
Training Epoch: 31 [8704/10284]	Loss: 0.1271	LR: 0.004000
Training Epoch: 31 [8960/10284]	Loss: 0.1566	LR: 0.004000
Training Epoch: 31 [9216/10284]	Loss: 0.1837	LR: 0.004000
Training Epoch: 31 [9472/10284]	Loss: 0.1496	LR: 0.004000
Training Epoch: 31 [9728/10284]	Loss: 0.1292	LR: 0.004000
Training Epoch: 31 [9984/10284]	Loss: 0.1717	LR: 0.004000
Training Epoch: 31 [10240/10284]	Loss: 0.1257	LR: 0.004000
Training Epoch: 31 [10284/10284]	Loss: 0.1687	LR: 0.004000
Epoch 31 - Average Train Loss: 0.1472, Train Accuracy: 0.9371
Epoch 31 training time consumed: 148.23s
Evaluating Network.....
Test set: Epoch: 31, Average loss: 0.0009, Accuracy: 0.9133, Time consumed:7.99s
Valid (Test) Dl:  2065
Train Dl:  10548
Retain Train Dl:  10284
Forget Train Dl:  264
Retain Valid Dl:  10284
Forget Valid Dl:  264
retain_prob Distribution: 2065 samples
test_prob Distribution: 2065 samples
forget_prob Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 264 samples
Set2 Distribution: 264 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Set1 Distribution: 2065 samples
Set2 Distribution: 2065 samples
Test Accuracy: 91.62071228027344
Retain Accuracy: 91.83238983154297
Zero-Retain Forget (ZRF): 0.7836576700210571
Membership Inference Attack (MIA): 0.2878787878787879
Forget vs Retain Membership Inference Attack (MIA): 0.5377358490566038
Forget vs Test Membership Inference Attack (MIA): 0.49056603773584906
Test vs Retain Membership Inference Attack (MIA): 0.5060532687651331
Train vs Test Membership Inference Attack (MIA): 0.5278450363196125
Forget Set Accuracy (Df): 90.625
Method Execution Time: 6270.54 seconds
