训练:Epoch[000/200] Iteration[200/800] Loss: 0.5753 Acc: 0.6747
训练:Epoch[000/200] Iteration[400/800] Loss: 0.5501 Acc: 0.7017
训练:Epoch[000/200] Iteration[600/800] Loss: 0.5616 Acc: 0.6958
训练:Epoch[000/200] Iteration[800/800] Loss: 0.5595 Acc: 0.6993
训练:Epoch[001/200] Iteration[200/800] Loss: 0.5214 Acc: 0.7328
训练:Epoch[001/200] Iteration[400/800] Loss: 0.5032 Acc: 0.7430
训练:Epoch[001/200] Iteration[600/800] Loss: 0.5030 Acc: 0.7440
训练:Epoch[001/200] Iteration[800/800] Loss: 0.5041 Acc: 0.7437
训练:Epoch[002/200] Iteration[200/800] Loss: 0.5001 Acc: 0.7472
训练:Epoch[002/200] Iteration[400/800] Loss: 0.5077 Acc: 0.7441
训练:Epoch[002/200] Iteration[600/800] Loss: 0.5084 Acc: 0.7432
训练:Epoch[002/200] Iteration[800/800] Loss: 0.5088 Acc: 0.7433
训练:Epoch[003/200] Iteration[200/800] Loss: 0.5138 Acc: 0.7403
训练:Epoch[003/200] Iteration[400/800] Loss: 0.5046 Acc: 0.7456
训练:Epoch[003/200] Iteration[600/800] Loss: 0.5087 Acc: 0.7440
训练:Epoch[003/200] Iteration[800/800] Loss: 0.5069 Acc: 0.7451
训练:Epoch[004/200] Iteration[200/800] Loss: 0.5064 Acc: 0.7466
训练:Epoch[004/200] Iteration[400/800] Loss: 0.5103 Acc: 0.7425
训练:Epoch[004/200] Iteration[600/800] Loss: 0.5076 Acc: 0.7441
训练:Epoch[004/200] Iteration[800/800] Loss: 0.5028 Acc: 0.7468
训练:Epoch[005/200] Iteration[200/800] Loss: 0.5255 Acc: 0.7347
训练:Epoch[005/200] Iteration[400/800] Loss: 0.5055 Acc: 0.7453
训练:Epoch[005/200] Iteration[600/800] Loss: 0.5151 Acc: 0.7410
训练:Epoch[005/200] Iteration[800/800] Loss: 0.5147 Acc: 0.7413
训练:Epoch[006/200] Iteration[200/800] Loss: 0.4990 Acc: 0.7500
训练:Epoch[006/200] Iteration[400/800] Loss: 0.5069 Acc: 0.7455
训练:Epoch[006/200] Iteration[600/800] Loss: 0.5163 Acc: 0.7399
训练:Epoch[006/200] Iteration[800/800] Loss: 0.5043 Acc: 0.7462
训练:Epoch[007/200] Iteration[200/800] Loss: 0.5064 Acc: 0.7459
训练:Epoch[007/200] Iteration[400/800] Loss: 0.5154 Acc: 0.7416
训练:Epoch[007/200] Iteration[600/800] Loss: 0.5054 Acc: 0.7466
训练:Epoch[007/200] Iteration[800/800] Loss: 0.5001 Acc: 0.7494
训练:Epoch[008/200] Iteration[200/800] Loss: 0.5161 Acc: 0.7419
训练:Epoch[008/200] Iteration[400/800] Loss: 0.5208 Acc: 0.7378
训练:Epoch[008/200] Iteration[600/800] Loss: 0.5136 Acc: 0.7418
训练:Epoch[008/200] Iteration[800/800] Loss: 0.5136 Acc: 0.7420
训练:Epoch[009/200] Iteration[200/800] Loss: 0.5326 Acc: 0.7328
训练:Epoch[009/200] Iteration[400/800] Loss: 0.5077 Acc: 0.7455
训练:Epoch[009/200] Iteration[600/800] Loss: 0.5064 Acc: 0.7460
训练:Epoch[009/200] Iteration[800/800] Loss: 0.5030 Acc: 0.7480
测试:	Epoch[009/200] Iteration[200/200] Loss: 0.4806 Acc: 0.7584
训练:Epoch[010/200] Iteration[200/800] Loss: 0.4713 Acc: 0.7641
训练:Epoch[010/200] Iteration[400/800] Loss: 0.4703 Acc: 0.7645
训练:Epoch[010/200] Iteration[600/800] Loss: 0.4733 Acc: 0.7630
训练:Epoch[010/200] Iteration[800/800] Loss: 0.4787 Acc: 0.7593
训练:Epoch[011/200] Iteration[200/800] Loss: 0.4954 Acc: 0.7512
训练:Epoch[011/200] Iteration[400/800] Loss: 0.4903 Acc: 0.7542
训练:Epoch[011/200] Iteration[600/800] Loss: 0.4951 Acc: 0.7519
训练:Epoch[011/200] Iteration[800/800] Loss: 0.4928 Acc: 0.7531
训练:Epoch[012/200] Iteration[200/800] Loss: 0.5046 Acc: 0.7472
训练:Epoch[012/200] Iteration[400/800] Loss: 0.5003 Acc: 0.7494
训练:Epoch[012/200] Iteration[600/800] Loss: 0.4927 Acc: 0.7526
训练:Epoch[012/200] Iteration[800/800] Loss: 0.4954 Acc: 0.7515
训练:Epoch[013/200] Iteration[200/800] Loss: 0.4827 Acc: 0.7584
训练:Epoch[013/200] Iteration[400/800] Loss: 0.4938 Acc: 0.7525
训练:Epoch[013/200] Iteration[600/800] Loss: 0.4905 Acc: 0.7542
训练:Epoch[013/200] Iteration[800/800] Loss: 0.4951 Acc: 0.7520
训练:Epoch[014/200] Iteration[200/800] Loss: 0.4689 Acc: 0.7656
训练:Epoch[014/200] Iteration[400/800] Loss: 0.4959 Acc: 0.7519
训练:Epoch[014/200] Iteration[600/800] Loss: 0.4924 Acc: 0.7533
训练:Epoch[014/200] Iteration[800/800] Loss: 0.4965 Acc: 0.7513
训练:Epoch[015/200] Iteration[200/800] Loss: 0.5057 Acc: 0.7456
训练:Epoch[015/200] Iteration[400/800] Loss: 0.5073 Acc: 0.7456
训练:Epoch[015/200] Iteration[600/800] Loss: 0.5039 Acc: 0.7474
训练:Epoch[015/200] Iteration[800/800] Loss: 0.4988 Acc: 0.7497
训练:Epoch[016/200] Iteration[200/800] Loss: 0.4875 Acc: 0.7541
训练:Epoch[016/200] Iteration[400/800] Loss: 0.4836 Acc: 0.7569
训练:Epoch[016/200] Iteration[600/800] Loss: 0.4852 Acc: 0.7564
训练:Epoch[016/200] Iteration[800/800] Loss: 0.4926 Acc: 0.7526
训练:Epoch[017/200] Iteration[200/800] Loss: 0.4934 Acc: 0.7528
训练:Epoch[017/200] Iteration[400/800] Loss: 0.4949 Acc: 0.7519
训练:Epoch[017/200] Iteration[600/800] Loss: 0.4960 Acc: 0.7515
训练:Epoch[017/200] Iteration[800/800] Loss: 0.4992 Acc: 0.7499
训练:Epoch[018/200] Iteration[200/800] Loss: 0.5052 Acc: 0.7469
训练:Epoch[018/200] Iteration[400/800] Loss: 0.5013 Acc: 0.7491
训练:Epoch[018/200] Iteration[600/800] Loss: 0.4977 Acc: 0.7509
训练:Epoch[018/200] Iteration[800/800] Loss: 0.4926 Acc: 0.7535
训练:Epoch[019/200] Iteration[200/800] Loss: 0.4948 Acc: 0.7519
训练:Epoch[019/200] Iteration[400/800] Loss: 0.5102 Acc: 0.7439
训练:Epoch[019/200] Iteration[600/800] Loss: 0.5067 Acc: 0.7453
训练:Epoch[019/200] Iteration[800/800] Loss: 0.5010 Acc: 0.7484
测试:	Epoch[019/200] Iteration[200/200] Loss: 0.5305 Acc: 0.7338
训练:Epoch[020/200] Iteration[200/800] Loss: 0.5047 Acc: 0.7466
训练:Epoch[020/200] Iteration[400/800] Loss: 0.5120 Acc: 0.7431
训练:Epoch[020/200] Iteration[600/800] Loss: 0.5116 Acc: 0.7435
训练:Epoch[020/200] Iteration[800/800] Loss: 0.5014 Acc: 0.7487
训练:Epoch[021/200] Iteration[200/800] Loss: 0.4902 Acc: 0.7544
训练:Epoch[021/200] Iteration[400/800] Loss: 0.4975 Acc: 0.7506
训练:Epoch[021/200] Iteration[600/800] Loss: 0.5077 Acc: 0.7453
训练:Epoch[021/200] Iteration[800/800] Loss: 0.5055 Acc: 0.7464
训练:Epoch[022/200] Iteration[200/800] Loss: 0.4966 Acc: 0.7516
训练:Epoch[022/200] Iteration[400/800] Loss: 0.4997 Acc: 0.7497
训练:Epoch[022/200] Iteration[600/800] Loss: 0.5026 Acc: 0.7483
训练:Epoch[022/200] Iteration[800/800] Loss: 0.5038 Acc: 0.7476
训练:Epoch[023/200] Iteration[200/800] Loss: 0.5158 Acc: 0.7412
训练:Epoch[023/200] Iteration[400/800] Loss: 0.5032 Acc: 0.7478
训练:Epoch[023/200] Iteration[600/800] Loss: 0.5060 Acc: 0.7465
训练:Epoch[023/200] Iteration[800/800] Loss: 0.5025 Acc: 0.7483
训练:Epoch[024/200] Iteration[200/800] Loss: 0.4771 Acc: 0.7609
训练:Epoch[024/200] Iteration[400/800] Loss: 0.4793 Acc: 0.7600
训练:Epoch[024/200] Iteration[600/800] Loss: 0.4930 Acc: 0.7531
训练:Epoch[024/200] Iteration[800/800] Loss: 0.4946 Acc: 0.7519
训练:Epoch[025/200] Iteration[200/800] Loss: 0.4974 Acc: 0.7512
训练:Epoch[025/200] Iteration[400/800] Loss: 0.4941 Acc: 0.7522
训练:Epoch[025/200] Iteration[600/800] Loss: 0.4961 Acc: 0.7509
训练:Epoch[025/200] Iteration[800/800] Loss: 0.4934 Acc: 0.7525
训练:Epoch[026/200] Iteration[200/800] Loss: 0.5029 Acc: 0.7484
训练:Epoch[026/200] Iteration[400/800] Loss: 0.5088 Acc: 0.7453
训练:Epoch[026/200] Iteration[600/800] Loss: 0.5165 Acc: 0.7412
训练:Epoch[026/200] Iteration[800/800] Loss: 0.5142 Acc: 0.7424
训练:Epoch[027/200] Iteration[200/800] Loss: 0.4806 Acc: 0.7591
训练:Epoch[027/200] Iteration[400/800] Loss: 0.4910 Acc: 0.7538
训练:Epoch[027/200] Iteration[600/800] Loss: 0.4917 Acc: 0.7534
训练:Epoch[027/200] Iteration[800/800] Loss: 0.4856 Acc: 0.7565
训练:Epoch[028/200] Iteration[200/800] Loss: 0.5008 Acc: 0.7494
训练:Epoch[028/200] Iteration[400/800] Loss: 0.5011 Acc: 0.7492
训练:Epoch[028/200] Iteration[600/800] Loss: 0.5017 Acc: 0.7489
训练:Epoch[028/200] Iteration[800/800] Loss: 0.5011 Acc: 0.7493
训练:Epoch[029/200] Iteration[200/800] Loss: 0.5205 Acc: 0.7394
训练:Epoch[029/200] Iteration[400/800] Loss: 0.5400 Acc: 0.7228
训练:Epoch[029/200] Iteration[600/800] Loss: 0.5220 Acc: 0.7343
训练:Epoch[029/200] Iteration[800/800] Loss: 0.5177 Acc: 0.7375
测试:	Epoch[029/200] Iteration[200/200] Loss: 0.5110 Acc: 0.7434
训练:Epoch[030/200] Iteration[200/800] Loss: 0.4983 Acc: 0.7509
训练:Epoch[030/200] Iteration[400/800] Loss: 0.5047 Acc: 0.7475
训练:Epoch[030/200] Iteration[600/800] Loss: 0.4984 Acc: 0.7505
训练:Epoch[030/200] Iteration[800/800] Loss: 0.5035 Acc: 0.7480
训练:Epoch[031/200] Iteration[200/800] Loss: 0.4877 Acc: 0.7559
训练:Epoch[031/200] Iteration[400/800] Loss: 0.4996 Acc: 0.7498
训练:Epoch[031/200] Iteration[600/800] Loss: 0.4957 Acc: 0.7516
训练:Epoch[031/200] Iteration[800/800] Loss: 0.4978 Acc: 0.7505
训练:Epoch[032/200] Iteration[200/800] Loss: 0.4914 Acc: 0.7544
训练:Epoch[032/200] Iteration[400/800] Loss: 0.4931 Acc: 0.7534
训练:Epoch[032/200] Iteration[600/800] Loss: 0.5047 Acc: 0.7476
训练:Epoch[032/200] Iteration[800/800] Loss: 0.4981 Acc: 0.7508
训练:Epoch[033/200] Iteration[200/800] Loss: 0.4948 Acc: 0.7525
训练:Epoch[033/200] Iteration[400/800] Loss: 0.4810 Acc: 0.7589
训练:Epoch[033/200] Iteration[600/800] Loss: 0.4915 Acc: 0.7538
训练:Epoch[033/200] Iteration[800/800] Loss: 0.4908 Acc: 0.7540
训练:Epoch[034/200] Iteration[200/800] Loss: 0.4818 Acc: 0.7581
训练:Epoch[034/200] Iteration[400/800] Loss: 0.4957 Acc: 0.7516
训练:Epoch[034/200] Iteration[600/800] Loss: 0.5004 Acc: 0.7493
训练:Epoch[034/200] Iteration[800/800] Loss: 0.5016 Acc: 0.7488
训练:Epoch[035/200] Iteration[200/800] Loss: 0.4930 Acc: 0.7531
训练:Epoch[035/200] Iteration[400/800] Loss: 0.4962 Acc: 0.7514
训练:Epoch[035/200] Iteration[600/800] Loss: 0.4980 Acc: 0.7504
训练:Epoch[035/200] Iteration[800/800] Loss: 0.5043 Acc: 0.7474
训练:Epoch[036/200] Iteration[200/800] Loss: 0.4994 Acc: 0.7500
训练:Epoch[036/200] Iteration[400/800] Loss: 0.4917 Acc: 0.7536
训练:Epoch[036/200] Iteration[600/800] Loss: 0.4966 Acc: 0.7511
训练:Epoch[036/200] Iteration[800/800] Loss: 0.5010 Acc: 0.7490
训练:Epoch[037/200] Iteration[200/800] Loss: 0.4836 Acc: 0.7572
训练:Epoch[037/200] Iteration[400/800] Loss: 0.4820 Acc: 0.7581
训练:Epoch[037/200] Iteration[600/800] Loss: 0.4945 Acc: 0.7521
训练:Epoch[037/200] Iteration[800/800] Loss: 0.4986 Acc: 0.7499
训练:Epoch[038/200] Iteration[200/800] Loss: 0.5025 Acc: 0.7488
训练:Epoch[038/200] Iteration[400/800] Loss: 0.4993 Acc: 0.7500
训练:Epoch[038/200] Iteration[600/800] Loss: 0.4973 Acc: 0.7510
训练:Epoch[038/200] Iteration[800/800] Loss: 0.5013 Acc: 0.7491
训练:Epoch[039/200] Iteration[200/800] Loss: 0.4999 Acc: 0.7500
训练:Epoch[039/200] Iteration[400/800] Loss: 0.4993 Acc: 0.7502
训练:Epoch[039/200] Iteration[600/800] Loss: 0.4979 Acc: 0.7507
训练:Epoch[039/200] Iteration[800/800] Loss: 0.4937 Acc: 0.7529
测试:	Epoch[039/200] Iteration[200/200] Loss: 0.4972 Acc: 0.7512
训练:Epoch[040/200] Iteration[200/800] Loss: 0.5121 Acc: 0.7438
训练:Epoch[040/200] Iteration[400/800] Loss: 0.4953 Acc: 0.7522
训练:Epoch[040/200] Iteration[600/800] Loss: 0.4920 Acc: 0.7539
训练:Epoch[040/200] Iteration[800/800] Loss: 0.4896 Acc: 0.7551
训练:Epoch[041/200] Iteration[200/800] Loss: 0.4965 Acc: 0.7506
训练:Epoch[041/200] Iteration[400/800] Loss: 0.4999 Acc: 0.7491
训练:Epoch[041/200] Iteration[600/800] Loss: 0.5010 Acc: 0.7488
训练:Epoch[041/200] Iteration[800/800] Loss: 0.4939 Acc: 0.7525
训练:Epoch[042/200] Iteration[200/800] Loss: 0.4783 Acc: 0.7606
训练:Epoch[042/200] Iteration[400/800] Loss: 0.5056 Acc: 0.7464
训练:Epoch[042/200] Iteration[600/800] Loss: 0.5035 Acc: 0.7467
训练:Epoch[042/200] Iteration[800/800] Loss: 0.5002 Acc: 0.7486
训练:Epoch[043/200] Iteration[200/800] Loss: 0.5144 Acc: 0.7425
训练:Epoch[043/200] Iteration[400/800] Loss: 0.5115 Acc: 0.7439
训练:Epoch[043/200] Iteration[600/800] Loss: 0.5001 Acc: 0.7496
训练:Epoch[043/200] Iteration[800/800] Loss: 0.5043 Acc: 0.7476
训练:Epoch[044/200] Iteration[200/800] Loss: 0.4871 Acc: 0.7562
训练:Epoch[044/200] Iteration[400/800] Loss: 0.5094 Acc: 0.7450
训练:Epoch[044/200] Iteration[600/800] Loss: 0.5074 Acc: 0.7460
训练:Epoch[044/200] Iteration[800/800] Loss: 0.5057 Acc: 0.7469
训练:Epoch[045/200] Iteration[200/800] Loss: 0.4821 Acc: 0.7588
训练:Epoch[045/200] Iteration[400/800] Loss: 0.4851 Acc: 0.7572
训练:Epoch[045/200] Iteration[600/800] Loss: 0.4923 Acc: 0.7535
训练:Epoch[045/200] Iteration[800/800] Loss: 0.4962 Acc: 0.7515
训练:Epoch[046/200] Iteration[200/800] Loss: 0.4890 Acc: 0.7556
训练:Epoch[046/200] Iteration[400/800] Loss: 0.5019 Acc: 0.7467
训练:Epoch[046/200] Iteration[600/800] Loss: 0.5144 Acc: 0.7404
训练:Epoch[046/200] Iteration[800/800] Loss: 0.5128 Acc: 0.7416
训练:Epoch[047/200] Iteration[200/800] Loss: 0.5083 Acc: 0.7447
训练:Epoch[047/200] Iteration[400/800] Loss: 0.5139 Acc: 0.7423
训练:Epoch[047/200] Iteration[600/800] Loss: 0.5022 Acc: 0.7484
训练:Epoch[047/200] Iteration[800/800] Loss: 0.5027 Acc: 0.7483
训练:Epoch[048/200] Iteration[200/800] Loss: 0.5056 Acc: 0.7472
训练:Epoch[048/200] Iteration[400/800] Loss: 0.5049 Acc: 0.7473
训练:Epoch[048/200] Iteration[600/800] Loss: 0.4964 Acc: 0.7515
训练:Epoch[048/200] Iteration[800/800] Loss: 0.5004 Acc: 0.7494
训练:Epoch[049/200] Iteration[200/800] Loss: 0.5119 Acc: 0.7438
训练:Epoch[049/200] Iteration[400/800] Loss: 0.4995 Acc: 0.7502
训练:Epoch[049/200] Iteration[600/800] Loss: 0.4973 Acc: 0.7511
训练:Epoch[049/200] Iteration[800/800] Loss: 0.4983 Acc: 0.7505
测试:	Epoch[049/200] Iteration[200/200] Loss: 0.5130 Acc: 0.7431
训练:Epoch[050/200] Iteration[200/800] Loss: 0.5097 Acc: 0.7450
训练:Epoch[050/200] Iteration[400/800] Loss: 0.4935 Acc: 0.7530
训练:Epoch[050/200] Iteration[600/800] Loss: 0.4936 Acc: 0.7529
训练:Epoch[050/200] Iteration[800/800] Loss: 0.5016 Acc: 0.7489
训练:Epoch[051/200] Iteration[200/800] Loss: 0.4951 Acc: 0.7522
训练:Epoch[051/200] Iteration[400/800] Loss: 0.4948 Acc: 0.7522
训练:Epoch[051/200] Iteration[600/800] Loss: 0.4943 Acc: 0.7525
训练:Epoch[051/200] Iteration[800/800] Loss: 0.4983 Acc: 0.7505
训练:Epoch[052/200] Iteration[200/800] Loss: 0.5337 Acc: 0.7331
训练:Epoch[052/200] Iteration[400/800] Loss: 0.5158 Acc: 0.7419
训练:Epoch[052/200] Iteration[600/800] Loss: 0.5089 Acc: 0.7453
训练:Epoch[052/200] Iteration[800/800] Loss: 0.5087 Acc: 0.7454
训练:Epoch[053/200] Iteration[200/800] Loss: 0.4795 Acc: 0.7600
训练:Epoch[053/200] Iteration[400/800] Loss: 0.5024 Acc: 0.7484
训练:Epoch[053/200] Iteration[600/800] Loss: 0.5022 Acc: 0.7486
训练:Epoch[053/200] Iteration[800/800] Loss: 0.5003 Acc: 0.7496
训练:Epoch[054/200] Iteration[200/800] Loss: 0.4972 Acc: 0.7512
训练:Epoch[054/200] Iteration[400/800] Loss: 0.5146 Acc: 0.7425
训练:Epoch[054/200] Iteration[600/800] Loss: 0.5126 Acc: 0.7434
训练:Epoch[054/200] Iteration[800/800] Loss: 0.5054 Acc: 0.7471
训练:Epoch[055/200] Iteration[200/800] Loss: 0.5503 Acc: 0.7097
训练:Epoch[055/200] Iteration[400/800] Loss: 0.5433 Acc: 0.7114
训练:Epoch[055/200] Iteration[600/800] Loss: 0.5307 Acc: 0.7229
训练:Epoch[055/200] Iteration[800/800] Loss: 0.5298 Acc: 0.7261
训练:Epoch[056/200] Iteration[200/800] Loss: 0.4927 Acc: 0.7534
训练:Epoch[056/200] Iteration[400/800] Loss: 0.4942 Acc: 0.7527
训练:Epoch[056/200] Iteration[600/800] Loss: 0.4998 Acc: 0.7499
训练:Epoch[056/200] Iteration[800/800] Loss: 0.4976 Acc: 0.7510
训练:Epoch[057/200] Iteration[200/800] Loss: 0.4842 Acc: 0.7578
训练:Epoch[057/200] Iteration[400/800] Loss: 0.4968 Acc: 0.7512
训练:Epoch[057/200] Iteration[600/800] Loss: 0.4938 Acc: 0.7528
训练:Epoch[057/200] Iteration[800/800] Loss: 0.4956 Acc: 0.7519
训练:Epoch[058/200] Iteration[200/800] Loss: 0.5176 Acc: 0.7409
训练:Epoch[058/200] Iteration[400/800] Loss: 0.5103 Acc: 0.7447
训练:Epoch[058/200] Iteration[600/800] Loss: 0.5049 Acc: 0.7472
训练:Epoch[058/200] Iteration[800/800] Loss: 0.5038 Acc: 0.7477
训练:Epoch[059/200] Iteration[200/800] Loss: 0.4770 Acc: 0.7616
训练:Epoch[059/200] Iteration[400/800] Loss: 0.4865 Acc: 0.7567
训练:Epoch[059/200] Iteration[600/800] Loss: 0.4926 Acc: 0.7536
训练:Epoch[059/200] Iteration[800/800] Loss: 0.4967 Acc: 0.7515
测试:	Epoch[059/200] Iteration[200/200] Loss: 0.5110 Acc: 0.7438
训练:Epoch[060/200] Iteration[200/800] Loss: 0.4996 Acc: 0.7500
训练:Epoch[060/200] Iteration[400/800] Loss: 0.4871 Acc: 0.7562
训练:Epoch[060/200] Iteration[600/800] Loss: 0.4902 Acc: 0.7547
训练:Epoch[060/200] Iteration[800/800] Loss: 0.4864 Acc: 0.7565
训练:Epoch[061/200] Iteration[200/800] Loss: 0.4624 Acc: 0.7684
训练:Epoch[061/200] Iteration[400/800] Loss: 0.4799 Acc: 0.7598
训练:Epoch[061/200] Iteration[600/800] Loss: 0.4824 Acc: 0.7585
训练:Epoch[061/200] Iteration[800/800] Loss: 0.4898 Acc: 0.7549
训练:Epoch[062/200] Iteration[200/800] Loss: 0.4703 Acc: 0.7644
训练:Epoch[062/200] Iteration[400/800] Loss: 0.4937 Acc: 0.7528
训练:Epoch[062/200] Iteration[600/800] Loss: 0.4968 Acc: 0.7512
训练:Epoch[062/200] Iteration[800/800] Loss: 0.5002 Acc: 0.7496
训练:Epoch[063/200] Iteration[200/800] Loss: 0.5045 Acc: 0.7472
训练:Epoch[063/200] Iteration[400/800] Loss: 0.5172 Acc: 0.7411
训练:Epoch[063/200] Iteration[600/800] Loss: 0.5118 Acc: 0.7439
训练:Epoch[063/200] Iteration[800/800] Loss: 0.5078 Acc: 0.7458
训练:Epoch[064/200] Iteration[200/800] Loss: 0.5032 Acc: 0.7481
训练:Epoch[064/200] Iteration[400/800] Loss: 0.4921 Acc: 0.7534
训练:Epoch[064/200] Iteration[600/800] Loss: 0.4839 Acc: 0.7576
训练:Epoch[064/200] Iteration[800/800] Loss: 0.4912 Acc: 0.7540
训练:Epoch[065/200] Iteration[200/800] Loss: 0.5120 Acc: 0.7434
训练:Epoch[065/200] Iteration[400/800] Loss: 0.5031 Acc: 0.7478
训练:Epoch[065/200] Iteration[600/800] Loss: 0.4969 Acc: 0.7511
训练:Epoch[065/200] Iteration[800/800] Loss: 0.5000 Acc: 0.7497
训练:Epoch[066/200] Iteration[200/800] Loss: 0.4835 Acc: 0.7584
训练:Epoch[066/200] Iteration[400/800] Loss: 0.4894 Acc: 0.7553
训练:Epoch[066/200] Iteration[600/800] Loss: 0.4965 Acc: 0.7516
训练:Epoch[066/200] Iteration[800/800] Loss: 0.5009 Acc: 0.7493
训练:Epoch[067/200] Iteration[200/800] Loss: 0.4934 Acc: 0.7531
训练:Epoch[067/200] Iteration[400/800] Loss: 0.5046 Acc: 0.7475
训练:Epoch[067/200] Iteration[600/800] Loss: 0.5080 Acc: 0.7458
训练:Epoch[067/200] Iteration[800/800] Loss: 0.5033 Acc: 0.7482
训练:Epoch[068/200] Iteration[200/800] Loss: 0.4736 Acc: 0.7628
训练:Epoch[068/200] Iteration[400/800] Loss: 0.4845 Acc: 0.7572
训练:Epoch[068/200] Iteration[600/800] Loss: 0.4868 Acc: 0.7561
训练:Epoch[068/200] Iteration[800/800] Loss: 0.4888 Acc: 0.7551
训练:Epoch[069/200] Iteration[200/800] Loss: 0.4860 Acc: 0.7569
训练:Epoch[069/200] Iteration[400/800] Loss: 0.5083 Acc: 0.7456
训练:Epoch[069/200] Iteration[600/800] Loss: 0.4993 Acc: 0.7502
训练:Epoch[069/200] Iteration[800/800] Loss: 0.5058 Acc: 0.7469
测试:	Epoch[069/200] Iteration[200/200] Loss: 0.4961 Acc: 0.7516
训练:Epoch[070/200] Iteration[200/800] Loss: 0.5011 Acc: 0.7491
训练:Epoch[070/200] Iteration[400/800] Loss: 0.4934 Acc: 0.7530
训练:Epoch[070/200] Iteration[600/800] Loss: 0.4990 Acc: 0.7501
训练:Epoch[070/200] Iteration[800/800] Loss: 0.4993 Acc: 0.7501
训练:Epoch[071/200] Iteration[200/800] Loss: 0.4957 Acc: 0.7519
训练:Epoch[071/200] Iteration[400/800] Loss: 0.5081 Acc: 0.7456
训练:Epoch[071/200] Iteration[600/800] Loss: 0.5052 Acc: 0.7471
训练:Epoch[071/200] Iteration[800/800] Loss: 0.4979 Acc: 0.7508
训练:Epoch[072/200] Iteration[200/800] Loss: 0.5082 Acc: 0.7456
训练:Epoch[072/200] Iteration[400/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[072/200] Iteration[600/800] Loss: 0.4975 Acc: 0.7510
训练:Epoch[072/200] Iteration[800/800] Loss: 0.5001 Acc: 0.7497
训练:Epoch[073/200] Iteration[200/800] Loss: 0.5023 Acc: 0.7484
训练:Epoch[073/200] Iteration[400/800] Loss: 0.4928 Acc: 0.7533
训练:Epoch[073/200] Iteration[600/800] Loss: 0.4937 Acc: 0.7529
训练:Epoch[073/200] Iteration[800/800] Loss: 0.4949 Acc: 0.7522
训练:Epoch[074/200] Iteration[200/800] Loss: 0.5104 Acc: 0.7447
训练:Epoch[074/200] Iteration[400/800] Loss: 0.5076 Acc: 0.7461
训练:Epoch[074/200] Iteration[600/800] Loss: 0.5016 Acc: 0.7490
训练:Epoch[074/200] Iteration[800/800] Loss: 0.4996 Acc: 0.7499
训练:Epoch[075/200] Iteration[200/800] Loss: 0.4832 Acc: 0.7581
训练:Epoch[075/200] Iteration[400/800] Loss: 0.4989 Acc: 0.7503
训练:Epoch[075/200] Iteration[600/800] Loss: 0.4983 Acc: 0.7504
训练:Epoch[075/200] Iteration[800/800] Loss: 0.4991 Acc: 0.7500
训练:Epoch[076/200] Iteration[200/800] Loss: 0.5092 Acc: 0.7453
训练:Epoch[076/200] Iteration[400/800] Loss: 0.4979 Acc: 0.7509
训练:Epoch[076/200] Iteration[600/800] Loss: 0.4996 Acc: 0.7501
训练:Epoch[076/200] Iteration[800/800] Loss: 0.5009 Acc: 0.7494
训练:Epoch[077/200] Iteration[200/800] Loss: 0.5137 Acc: 0.7431
训练:Epoch[077/200] Iteration[400/800] Loss: 0.5100 Acc: 0.7450
训练:Epoch[077/200] Iteration[600/800] Loss: 0.5055 Acc: 0.7472
训练:Epoch[077/200] Iteration[800/800] Loss: 0.5086 Acc: 0.7456
训练:Epoch[078/200] Iteration[200/800] Loss: 0.5142 Acc: 0.7425
训练:Epoch[078/200] Iteration[400/800] Loss: 0.5011 Acc: 0.7491
训练:Epoch[078/200] Iteration[600/800] Loss: 0.4950 Acc: 0.7522
训练:Epoch[078/200] Iteration[800/800] Loss: 0.5004 Acc: 0.7495
训练:Epoch[079/200] Iteration[200/800] Loss: 0.5154 Acc: 0.7422
训练:Epoch[079/200] Iteration[400/800] Loss: 0.5076 Acc: 0.7459
训练:Epoch[079/200] Iteration[600/800] Loss: 0.5090 Acc: 0.7453
训练:Epoch[079/200] Iteration[800/800] Loss: 0.5041 Acc: 0.7478
测试:	Epoch[079/200] Iteration[200/200] Loss: 0.4804 Acc: 0.7591
训练:Epoch[080/200] Iteration[200/800] Loss: 0.4852 Acc: 0.7572
训练:Epoch[080/200] Iteration[400/800] Loss: 0.4887 Acc: 0.7553
训练:Epoch[080/200] Iteration[600/800] Loss: 0.4888 Acc: 0.7552
训练:Epoch[080/200] Iteration[800/800] Loss: 0.4886 Acc: 0.7554
训练:Epoch[081/200] Iteration[200/800] Loss: 0.4782 Acc: 0.7606
训练:Epoch[081/200] Iteration[400/800] Loss: 0.4840 Acc: 0.7577
训练:Epoch[081/200] Iteration[600/800] Loss: 0.4934 Acc: 0.7530
训练:Epoch[081/200] Iteration[800/800] Loss: 0.4959 Acc: 0.7519
训练:Epoch[082/200] Iteration[200/800] Loss: 0.4960 Acc: 0.7519
训练:Epoch[082/200] Iteration[400/800] Loss: 0.4982 Acc: 0.7502
训练:Epoch[082/200] Iteration[600/800] Loss: 0.4970 Acc: 0.7506
训练:Epoch[082/200] Iteration[800/800] Loss: 0.4934 Acc: 0.7526
训练:Epoch[083/200] Iteration[200/800] Loss: 0.4835 Acc: 0.7581
训练:Epoch[083/200] Iteration[400/800] Loss: 0.4956 Acc: 0.7520
训练:Epoch[083/200] Iteration[600/800] Loss: 0.4893 Acc: 0.7552
训练:Epoch[083/200] Iteration[800/800] Loss: 0.4986 Acc: 0.7504
训练:Epoch[084/200] Iteration[200/800] Loss: 0.5054 Acc: 0.7462
训练:Epoch[084/200] Iteration[400/800] Loss: 0.4996 Acc: 0.7497
训练:Epoch[084/200] Iteration[600/800] Loss: 0.4928 Acc: 0.7532
训练:Epoch[084/200] Iteration[800/800] Loss: 0.4961 Acc: 0.7516
训练:Epoch[085/200] Iteration[200/800] Loss: 0.4855 Acc: 0.7572
训练:Epoch[085/200] Iteration[400/800] Loss: 0.4837 Acc: 0.7580
训练:Epoch[085/200] Iteration[600/800] Loss: 0.4921 Acc: 0.7538
训练:Epoch[085/200] Iteration[800/800] Loss: 0.4926 Acc: 0.7536
训练:Epoch[086/200] Iteration[200/800] Loss: 0.5014 Acc: 0.7491
训练:Epoch[086/200] Iteration[400/800] Loss: 0.5133 Acc: 0.7430
训练:Epoch[086/200] Iteration[600/800] Loss: 0.5135 Acc: 0.7429
训练:Epoch[086/200] Iteration[800/800] Loss: 0.5119 Acc: 0.7437
训练:Epoch[087/200] Iteration[200/800] Loss: 0.4950 Acc: 0.7525
训练:Epoch[087/200] Iteration[400/800] Loss: 0.5126 Acc: 0.7436
训练:Epoch[087/200] Iteration[600/800] Loss: 0.5060 Acc: 0.7469
训练:Epoch[087/200] Iteration[800/800] Loss: 0.5009 Acc: 0.7494
训练:Epoch[088/200] Iteration[200/800] Loss: 0.5237 Acc: 0.7381
训练:Epoch[088/200] Iteration[400/800] Loss: 0.5171 Acc: 0.7412
训练:Epoch[088/200] Iteration[600/800] Loss: 0.5070 Acc: 0.7464
训练:Epoch[088/200] Iteration[800/800] Loss: 0.5057 Acc: 0.7470
训练:Epoch[089/200] Iteration[200/800] Loss: 0.5125 Acc: 0.7438
训练:Epoch[089/200] Iteration[400/800] Loss: 0.5113 Acc: 0.7442
训练:Epoch[089/200] Iteration[600/800] Loss: 0.5063 Acc: 0.7468
训练:Epoch[089/200] Iteration[800/800] Loss: 0.5052 Acc: 0.7473
测试:	Epoch[089/200] Iteration[200/200] Loss: 0.5330 Acc: 0.7325
训练:Epoch[090/200] Iteration[200/800] Loss: 0.4995 Acc: 0.7500
训练:Epoch[090/200] Iteration[400/800] Loss: 0.4934 Acc: 0.7531
训练:Epoch[090/200] Iteration[600/800] Loss: 0.4939 Acc: 0.7529
训练:Epoch[090/200] Iteration[800/800] Loss: 0.4928 Acc: 0.7535
训练:Epoch[091/200] Iteration[200/800] Loss: 0.4913 Acc: 0.7544
训练:Epoch[091/200] Iteration[400/800] Loss: 0.4947 Acc: 0.7527
训练:Epoch[091/200] Iteration[600/800] Loss: 0.4860 Acc: 0.7570
训练:Epoch[091/200] Iteration[800/800] Loss: 0.4893 Acc: 0.7553
训练:Epoch[092/200] Iteration[200/800] Loss: 0.5131 Acc: 0.7434
训练:Epoch[092/200] Iteration[400/800] Loss: 0.5086 Acc: 0.7455
训练:Epoch[092/200] Iteration[600/800] Loss: 0.5103 Acc: 0.7447
训练:Epoch[092/200] Iteration[800/800] Loss: 0.5122 Acc: 0.7438
训练:Epoch[093/200] Iteration[200/800] Loss: 0.4641 Acc: 0.7678
训练:Epoch[093/200] Iteration[400/800] Loss: 0.4760 Acc: 0.7617
训练:Epoch[093/200] Iteration[600/800] Loss: 0.4809 Acc: 0.7594
训练:Epoch[093/200] Iteration[800/800] Loss: 0.4897 Acc: 0.7549
训练:Epoch[094/200] Iteration[200/800] Loss: 0.4984 Acc: 0.7503
训练:Epoch[094/200] Iteration[400/800] Loss: 0.5045 Acc: 0.7473
训练:Epoch[094/200] Iteration[600/800] Loss: 0.5002 Acc: 0.7495
训练:Epoch[094/200] Iteration[800/800] Loss: 0.4944 Acc: 0.7525
训练:Epoch[095/200] Iteration[200/800] Loss: 0.5163 Acc: 0.7416
训练:Epoch[095/200] Iteration[400/800] Loss: 0.5229 Acc: 0.7383
训练:Epoch[095/200] Iteration[600/800] Loss: 0.5132 Acc: 0.7431
训练:Epoch[095/200] Iteration[800/800] Loss: 0.5084 Acc: 0.7456
训练:Epoch[096/200] Iteration[200/800] Loss: 0.4784 Acc: 0.7606
训练:Epoch[096/200] Iteration[400/800] Loss: 0.4951 Acc: 0.7523
训练:Epoch[096/200] Iteration[600/800] Loss: 0.4983 Acc: 0.7505
训练:Epoch[096/200] Iteration[800/800] Loss: 0.4931 Acc: 0.7532
训练:Epoch[097/200] Iteration[200/800] Loss: 0.5228 Acc: 0.7381
训练:Epoch[097/200] Iteration[400/800] Loss: 0.5063 Acc: 0.7464
训练:Epoch[097/200] Iteration[600/800] Loss: 0.5062 Acc: 0.7465
训练:Epoch[097/200] Iteration[800/800] Loss: 0.5014 Acc: 0.7489
训练:Epoch[098/200] Iteration[200/800] Loss: 0.5228 Acc: 0.7378
训练:Epoch[098/200] Iteration[400/800] Loss: 0.5129 Acc: 0.7431
训练:Epoch[098/200] Iteration[600/800] Loss: 0.5027 Acc: 0.7483
训练:Epoch[098/200] Iteration[800/800] Loss: 0.4995 Acc: 0.7500
训练:Epoch[099/200] Iteration[200/800] Loss: 0.4847 Acc: 0.7575
训练:Epoch[099/200] Iteration[400/800] Loss: 0.4946 Acc: 0.7525
训练:Epoch[099/200] Iteration[600/800] Loss: 0.4953 Acc: 0.7522
训练:Epoch[099/200] Iteration[800/800] Loss: 0.4937 Acc: 0.7530
测试:	Epoch[099/200] Iteration[200/200] Loss: 0.5015 Acc: 0.7488
训练:Epoch[100/200] Iteration[200/800] Loss: 0.5063 Acc: 0.7466
训练:Epoch[100/200] Iteration[400/800] Loss: 0.5169 Acc: 0.7412
训练:Epoch[100/200] Iteration[600/800] Loss: 0.5042 Acc: 0.7477
训练:Epoch[100/200] Iteration[800/800] Loss: 0.5027 Acc: 0.7485
训练:Epoch[101/200] Iteration[200/800] Loss: 0.4657 Acc: 0.7669
训练:Epoch[101/200] Iteration[400/800] Loss: 0.4765 Acc: 0.7616
训练:Epoch[101/200] Iteration[600/800] Loss: 0.4816 Acc: 0.7591
训练:Epoch[101/200] Iteration[800/800] Loss: 0.4854 Acc: 0.7572
训练:Epoch[102/200] Iteration[200/800] Loss: 0.5250 Acc: 0.7375
训练:Epoch[102/200] Iteration[400/800] Loss: 0.5041 Acc: 0.7478
训练:Epoch[102/200] Iteration[600/800] Loss: 0.4973 Acc: 0.7512
训练:Epoch[102/200] Iteration[800/800] Loss: 0.4980 Acc: 0.7508
训练:Epoch[103/200] Iteration[200/800] Loss: 0.4864 Acc: 0.7569
训练:Epoch[103/200] Iteration[400/800] Loss: 0.4962 Acc: 0.7517
训练:Epoch[103/200] Iteration[600/800] Loss: 0.5012 Acc: 0.7493
训练:Epoch[103/200] Iteration[800/800] Loss: 0.5022 Acc: 0.7488
训练:Epoch[104/200] Iteration[200/800] Loss: 0.4854 Acc: 0.7572
训练:Epoch[104/200] Iteration[400/800] Loss: 0.5027 Acc: 0.7484
训练:Epoch[104/200] Iteration[600/800] Loss: 0.5027 Acc: 0.7483
训练:Epoch[104/200] Iteration[800/800] Loss: 0.5021 Acc: 0.7487
训练:Epoch[105/200] Iteration[200/800] Loss: 0.5176 Acc: 0.7409
训练:Epoch[105/200] Iteration[400/800] Loss: 0.5021 Acc: 0.7488
训练:Epoch[105/200] Iteration[600/800] Loss: 0.4987 Acc: 0.7504
训练:Epoch[105/200] Iteration[800/800] Loss: 0.4933 Acc: 0.7532
训练:Epoch[106/200] Iteration[200/800] Loss: 0.4919 Acc: 0.7541
训练:Epoch[106/200] Iteration[400/800] Loss: 0.4871 Acc: 0.7564
训练:Epoch[106/200] Iteration[600/800] Loss: 0.4913 Acc: 0.7543
训练:Epoch[106/200] Iteration[800/800] Loss: 0.4953 Acc: 0.7523
训练:Epoch[107/200] Iteration[200/800] Loss: 0.4888 Acc: 0.7556
训练:Epoch[107/200] Iteration[400/800] Loss: 0.4998 Acc: 0.7498
训练:Epoch[107/200] Iteration[600/800] Loss: 0.4954 Acc: 0.7521
训练:Epoch[107/200] Iteration[800/800] Loss: 0.4921 Acc: 0.7537
训练:Epoch[108/200] Iteration[200/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[108/200] Iteration[400/800] Loss: 0.4969 Acc: 0.7514
训练:Epoch[108/200] Iteration[600/800] Loss: 0.4934 Acc: 0.7532
训练:Epoch[108/200] Iteration[800/800] Loss: 0.4914 Acc: 0.7541
训练:Epoch[109/200] Iteration[200/800] Loss: 0.5008 Acc: 0.7494
训练:Epoch[109/200] Iteration[400/800] Loss: 0.4998 Acc: 0.7498
训练:Epoch[109/200] Iteration[600/800] Loss: 0.4955 Acc: 0.7521
训练:Epoch[109/200] Iteration[800/800] Loss: 0.5048 Acc: 0.7473
测试:	Epoch[109/200] Iteration[200/200] Loss: 0.5149 Acc: 0.7416
训练:Epoch[110/200] Iteration[200/800] Loss: 0.4976 Acc: 0.7512
训练:Epoch[110/200] Iteration[400/800] Loss: 0.4759 Acc: 0.7620
训练:Epoch[110/200] Iteration[600/800] Loss: 0.4877 Acc: 0.7561
训练:Epoch[110/200] Iteration[800/800] Loss: 0.4928 Acc: 0.7536
训练:Epoch[111/200] Iteration[200/800] Loss: 0.4957 Acc: 0.7519
训练:Epoch[111/200] Iteration[400/800] Loss: 0.4916 Acc: 0.7541
训练:Epoch[111/200] Iteration[600/800] Loss: 0.5044 Acc: 0.7476
训练:Epoch[111/200] Iteration[800/800] Loss: 0.5027 Acc: 0.7485
训练:Epoch[112/200] Iteration[200/800] Loss: 0.5216 Acc: 0.7391
训练:Epoch[112/200] Iteration[400/800] Loss: 0.5069 Acc: 0.7464
训练:Epoch[112/200] Iteration[600/800] Loss: 0.5032 Acc: 0.7482
训练:Epoch[112/200] Iteration[800/800] Loss: 0.5019 Acc: 0.7489
训练:Epoch[113/200] Iteration[200/800] Loss: 0.4910 Acc: 0.7544
训练:Epoch[113/200] Iteration[400/800] Loss: 0.5057 Acc: 0.7469
训练:Epoch[113/200] Iteration[600/800] Loss: 0.5045 Acc: 0.7476
训练:Epoch[113/200] Iteration[800/800] Loss: 0.5020 Acc: 0.7483
训练:Epoch[114/200] Iteration[200/800] Loss: 0.5169 Acc: 0.7412
训练:Epoch[114/200] Iteration[400/800] Loss: 0.5137 Acc: 0.7430
训练:Epoch[114/200] Iteration[600/800] Loss: 0.5071 Acc: 0.7461
训练:Epoch[114/200] Iteration[800/800] Loss: 0.5079 Acc: 0.7458
训练:Epoch[115/200] Iteration[200/800] Loss: 0.5075 Acc: 0.7459
训练:Epoch[115/200] Iteration[400/800] Loss: 0.5059 Acc: 0.7467
训练:Epoch[115/200] Iteration[600/800] Loss: 0.5064 Acc: 0.7466
训练:Epoch[115/200] Iteration[800/800] Loss: 0.5073 Acc: 0.7459
训练:Epoch[116/200] Iteration[200/800] Loss: 0.4766 Acc: 0.7606
训练:Epoch[116/200] Iteration[400/800] Loss: 0.4863 Acc: 0.7562
训练:Epoch[116/200] Iteration[600/800] Loss: 0.4850 Acc: 0.7569
训练:Epoch[116/200] Iteration[800/800] Loss: 0.4908 Acc: 0.7540
训练:Epoch[117/200] Iteration[200/800] Loss: 0.4948 Acc: 0.7525
训练:Epoch[117/200] Iteration[400/800] Loss: 0.5054 Acc: 0.7472
训练:Epoch[117/200] Iteration[600/800] Loss: 0.4997 Acc: 0.7499
训练:Epoch[117/200] Iteration[800/800] Loss: 0.5017 Acc: 0.7490
训练:Epoch[118/200] Iteration[200/800] Loss: 0.4949 Acc: 0.7519
训练:Epoch[118/200] Iteration[400/800] Loss: 0.5006 Acc: 0.7494
训练:Epoch[118/200] Iteration[600/800] Loss: 0.5016 Acc: 0.7490
训练:Epoch[118/200] Iteration[800/800] Loss: 0.5090 Acc: 0.7453
训练:Epoch[119/200] Iteration[200/800] Loss: 0.4870 Acc: 0.7566
训练:Epoch[119/200] Iteration[400/800] Loss: 0.4918 Acc: 0.7541
训练:Epoch[119/200] Iteration[600/800] Loss: 0.4986 Acc: 0.7506
训练:Epoch[119/200] Iteration[800/800] Loss: 0.5040 Acc: 0.7479
测试:	Epoch[119/200] Iteration[200/200] Loss: 0.4657 Acc: 0.7666
训练:Epoch[120/200] Iteration[200/800] Loss: 0.4756 Acc: 0.7622
训练:Epoch[120/200] Iteration[400/800] Loss: 0.4810 Acc: 0.7594
训练:Epoch[120/200] Iteration[600/800] Loss: 0.4902 Acc: 0.7548
训练:Epoch[120/200] Iteration[800/800] Loss: 0.4934 Acc: 0.7532
训练:Epoch[121/200] Iteration[200/800] Loss: 0.5216 Acc: 0.7391
训练:Epoch[121/200] Iteration[400/800] Loss: 0.5242 Acc: 0.7378
训练:Epoch[121/200] Iteration[600/800] Loss: 0.5160 Acc: 0.7420
训练:Epoch[121/200] Iteration[800/800] Loss: 0.5091 Acc: 0.7454
训练:Epoch[122/200] Iteration[200/800] Loss: 0.5204 Acc: 0.7397
训练:Epoch[122/200] Iteration[400/800] Loss: 0.5088 Acc: 0.7455
训练:Epoch[122/200] Iteration[600/800] Loss: 0.5082 Acc: 0.7458
训练:Epoch[122/200] Iteration[800/800] Loss: 0.5087 Acc: 0.7455
训练:Epoch[123/200] Iteration[200/800] Loss: 0.4913 Acc: 0.7544
训练:Epoch[123/200] Iteration[400/800] Loss: 0.4847 Acc: 0.7575
训练:Epoch[123/200] Iteration[600/800] Loss: 0.4885 Acc: 0.7556
训练:Epoch[123/200] Iteration[800/800] Loss: 0.4854 Acc: 0.7572
训练:Epoch[124/200] Iteration[200/800] Loss: 0.4872 Acc: 0.7562
训练:Epoch[124/200] Iteration[400/800] Loss: 0.5016 Acc: 0.7491
训练:Epoch[124/200] Iteration[600/800] Loss: 0.5004 Acc: 0.7497
训练:Epoch[124/200] Iteration[800/800] Loss: 0.5018 Acc: 0.7489
训练:Epoch[125/200] Iteration[200/800] Loss: 0.5143 Acc: 0.7425
训练:Epoch[125/200] Iteration[400/800] Loss: 0.5171 Acc: 0.7412
训练:Epoch[125/200] Iteration[600/800] Loss: 0.5191 Acc: 0.7402
训练:Epoch[125/200] Iteration[800/800] Loss: 0.5032 Acc: 0.7482
训练:Epoch[126/200] Iteration[200/800] Loss: 0.5166 Acc: 0.7416
训练:Epoch[126/200] Iteration[400/800] Loss: 0.5136 Acc: 0.7431
训练:Epoch[126/200] Iteration[600/800] Loss: 0.5140 Acc: 0.7429
训练:Epoch[126/200] Iteration[800/800] Loss: 0.5044 Acc: 0.7476
训练:Epoch[127/200] Iteration[200/800] Loss: 0.4795 Acc: 0.7600
训练:Epoch[127/200] Iteration[400/800] Loss: 0.5043 Acc: 0.7475
训练:Epoch[127/200] Iteration[600/800] Loss: 0.4960 Acc: 0.7518
训练:Epoch[127/200] Iteration[800/800] Loss: 0.4991 Acc: 0.7502
训练:Epoch[128/200] Iteration[200/800] Loss: 0.5111 Acc: 0.7441
训练:Epoch[128/200] Iteration[400/800] Loss: 0.5070 Acc: 0.7462
训练:Epoch[128/200] Iteration[600/800] Loss: 0.5097 Acc: 0.7449
训练:Epoch[128/200] Iteration[800/800] Loss: 0.5049 Acc: 0.7473
训练:Epoch[129/200] Iteration[200/800] Loss: 0.5106 Acc: 0.7447
训练:Epoch[129/200] Iteration[400/800] Loss: 0.5082 Acc: 0.7458
训练:Epoch[129/200] Iteration[600/800] Loss: 0.5061 Acc: 0.7469
训练:Epoch[129/200] Iteration[800/800] Loss: 0.5041 Acc: 0.7479
测试:	Epoch[129/200] Iteration[200/200] Loss: 0.4696 Acc: 0.7644
训练:Epoch[130/200] Iteration[200/800] Loss: 0.5129 Acc: 0.7431
训练:Epoch[130/200] Iteration[400/800] Loss: 0.5143 Acc: 0.7427
训练:Epoch[130/200] Iteration[600/800] Loss: 0.5112 Acc: 0.7443
训练:Epoch[130/200] Iteration[800/800] Loss: 0.5097 Acc: 0.7451
训练:Epoch[131/200] Iteration[200/800] Loss: 0.5334 Acc: 0.7328
训练:Epoch[131/200] Iteration[400/800] Loss: 0.5202 Acc: 0.7395
训练:Epoch[131/200] Iteration[600/800] Loss: 0.5197 Acc: 0.7398
训练:Epoch[131/200] Iteration[800/800] Loss: 0.5162 Acc: 0.7416
训练:Epoch[132/200] Iteration[200/800] Loss: 0.4906 Acc: 0.7547
训练:Epoch[132/200] Iteration[400/800] Loss: 0.5051 Acc: 0.7475
训练:Epoch[132/200] Iteration[600/800] Loss: 0.5023 Acc: 0.7489
训练:Epoch[132/200] Iteration[800/800] Loss: 0.4953 Acc: 0.7523
训练:Epoch[133/200] Iteration[200/800] Loss: 0.4913 Acc: 0.7544
训练:Epoch[133/200] Iteration[400/800] Loss: 0.4921 Acc: 0.7538
训练:Epoch[133/200] Iteration[600/800] Loss: 0.4928 Acc: 0.7533
训练:Epoch[133/200] Iteration[800/800] Loss: 0.4972 Acc: 0.7512
训练:Epoch[134/200] Iteration[200/800] Loss: 0.4848 Acc: 0.7575
训练:Epoch[134/200] Iteration[400/800] Loss: 0.4853 Acc: 0.7572
训练:Epoch[134/200] Iteration[600/800] Loss: 0.5032 Acc: 0.7483
训练:Epoch[134/200] Iteration[800/800] Loss: 0.5008 Acc: 0.7495
训练:Epoch[135/200] Iteration[200/800] Loss: 0.5063 Acc: 0.7469
训练:Epoch[135/200] Iteration[400/800] Loss: 0.4969 Acc: 0.7516
训练:Epoch[135/200] Iteration[600/800] Loss: 0.4971 Acc: 0.7515
训练:Epoch[135/200] Iteration[800/800] Loss: 0.5006 Acc: 0.7497
训练:Epoch[136/200] Iteration[200/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[136/200] Iteration[400/800] Loss: 0.4937 Acc: 0.7530
训练:Epoch[136/200] Iteration[600/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[136/200] Iteration[800/800] Loss: 0.5039 Acc: 0.7479
训练:Epoch[137/200] Iteration[200/800] Loss: 0.5295 Acc: 0.7350
训练:Epoch[137/200] Iteration[400/800] Loss: 0.5102 Acc: 0.7447
训练:Epoch[137/200] Iteration[600/800] Loss: 0.4933 Acc: 0.7532
训练:Epoch[137/200] Iteration[800/800] Loss: 0.4920 Acc: 0.7539
训练:Epoch[138/200] Iteration[200/800] Loss: 0.4947 Acc: 0.7525
训练:Epoch[138/200] Iteration[400/800] Loss: 0.4951 Acc: 0.7522
训练:Epoch[138/200] Iteration[600/800] Loss: 0.4942 Acc: 0.7526
训练:Epoch[138/200] Iteration[800/800] Loss: 0.5022 Acc: 0.7487
训练:Epoch[139/200] Iteration[200/800] Loss: 0.4916 Acc: 0.7538
训练:Epoch[139/200] Iteration[400/800] Loss: 0.4952 Acc: 0.7520
训练:Epoch[139/200] Iteration[600/800] Loss: 0.4934 Acc: 0.7529
训练:Epoch[139/200] Iteration[800/800] Loss: 0.4937 Acc: 0.7529
测试:	Epoch[139/200] Iteration[200/200] Loss: 0.4944 Acc: 0.7519
训练:Epoch[140/200] Iteration[200/800] Loss: 0.5016 Acc: 0.7491
训练:Epoch[140/200] Iteration[400/800] Loss: 0.5007 Acc: 0.7495
训练:Epoch[140/200] Iteration[600/800] Loss: 0.4996 Acc: 0.7500
训练:Epoch[140/200] Iteration[800/800] Loss: 0.4999 Acc: 0.7497
训练:Epoch[141/200] Iteration[200/800] Loss: 0.4974 Acc: 0.7512
训练:Epoch[141/200] Iteration[400/800] Loss: 0.5032 Acc: 0.7480
训练:Epoch[141/200] Iteration[600/800] Loss: 0.5045 Acc: 0.7473
训练:Epoch[141/200] Iteration[800/800] Loss: 0.5024 Acc: 0.7484
训练:Epoch[142/200] Iteration[200/800] Loss: 0.4979 Acc: 0.7506
训练:Epoch[142/200] Iteration[400/800] Loss: 0.4963 Acc: 0.7514
训练:Epoch[142/200] Iteration[600/800] Loss: 0.4983 Acc: 0.7505
训练:Epoch[142/200] Iteration[800/800] Loss: 0.4975 Acc: 0.7510
训练:Epoch[143/200] Iteration[200/800] Loss: 0.4748 Acc: 0.7622
训练:Epoch[143/200] Iteration[400/800] Loss: 0.4806 Acc: 0.7594
训练:Epoch[143/200] Iteration[600/800] Loss: 0.4768 Acc: 0.7614
训练:Epoch[143/200] Iteration[800/800] Loss: 0.4833 Acc: 0.7581
训练:Epoch[144/200] Iteration[200/800] Loss: 0.4956 Acc: 0.7522
训练:Epoch[144/200] Iteration[400/800] Loss: 0.4902 Acc: 0.7547
训练:Epoch[144/200] Iteration[600/800] Loss: 0.4947 Acc: 0.7525
训练:Epoch[144/200] Iteration[800/800] Loss: 0.4992 Acc: 0.7502
训练:Epoch[145/200] Iteration[200/800] Loss: 0.5332 Acc: 0.7331
训练:Epoch[145/200] Iteration[400/800] Loss: 0.5133 Acc: 0.7431
训练:Epoch[145/200] Iteration[600/800] Loss: 0.5164 Acc: 0.7416
训练:Epoch[145/200] Iteration[800/800] Loss: 0.5121 Acc: 0.7437
训练:Epoch[146/200] Iteration[200/800] Loss: 0.4938 Acc: 0.7531
训练:Epoch[146/200] Iteration[400/800] Loss: 0.4857 Acc: 0.7569
训练:Epoch[146/200] Iteration[600/800] Loss: 0.4892 Acc: 0.7551
训练:Epoch[146/200] Iteration[800/800] Loss: 0.4899 Acc: 0.7548
训练:Epoch[147/200] Iteration[200/800] Loss: 0.5051 Acc: 0.7472
训练:Epoch[147/200] Iteration[400/800] Loss: 0.5035 Acc: 0.7480
训练:Epoch[147/200] Iteration[600/800] Loss: 0.4973 Acc: 0.7511
训练:Epoch[147/200] Iteration[800/800] Loss: 0.4931 Acc: 0.7532
训练:Epoch[148/200] Iteration[200/800] Loss: 0.5129 Acc: 0.7434
训练:Epoch[148/200] Iteration[400/800] Loss: 0.5049 Acc: 0.7473
训练:Epoch[148/200] Iteration[600/800] Loss: 0.5155 Acc: 0.7421
训练:Epoch[148/200] Iteration[800/800] Loss: 0.5083 Acc: 0.7457
训练:Epoch[149/200] Iteration[200/800] Loss: 0.4910 Acc: 0.7544
训练:Epoch[149/200] Iteration[400/800] Loss: 0.5010 Acc: 0.7492
训练:Epoch[149/200] Iteration[600/800] Loss: 0.5121 Acc: 0.7438
训练:Epoch[149/200] Iteration[800/800] Loss: 0.5139 Acc: 0.7429
测试:	Epoch[149/200] Iteration[200/200] Loss: 0.4997 Acc: 0.7500
训练:Epoch[150/200] Iteration[200/800] Loss: 0.4716 Acc: 0.7641
训练:Epoch[150/200] Iteration[400/800] Loss: 0.4774 Acc: 0.7612
训练:Epoch[150/200] Iteration[600/800] Loss: 0.4896 Acc: 0.7550
训练:Epoch[150/200] Iteration[800/800] Loss: 0.4939 Acc: 0.7528
训练:Epoch[151/200] Iteration[200/800] Loss: 0.4963 Acc: 0.7519
训练:Epoch[151/200] Iteration[400/800] Loss: 0.5005 Acc: 0.7495
训练:Epoch[151/200] Iteration[600/800] Loss: 0.4953 Acc: 0.7521
训练:Epoch[151/200] Iteration[800/800] Loss: 0.5008 Acc: 0.7494
训练:Epoch[152/200] Iteration[200/800] Loss: 0.5093 Acc: 0.7450
训练:Epoch[152/200] Iteration[400/800] Loss: 0.4831 Acc: 0.7581
训练:Epoch[152/200] Iteration[600/800] Loss: 0.4909 Acc: 0.7542
训练:Epoch[152/200] Iteration[800/800] Loss: 0.4943 Acc: 0.7525
训练:Epoch[153/200] Iteration[200/800] Loss: 0.5024 Acc: 0.7488
训练:Epoch[153/200] Iteration[400/800] Loss: 0.4932 Acc: 0.7531
训练:Epoch[153/200] Iteration[600/800] Loss: 0.4956 Acc: 0.7519
训练:Epoch[153/200] Iteration[800/800] Loss: 0.4954 Acc: 0.7519
训练:Epoch[154/200] Iteration[200/800] Loss: 0.4713 Acc: 0.7644
训练:Epoch[154/200] Iteration[400/800] Loss: 0.4865 Acc: 0.7566
训练:Epoch[154/200] Iteration[600/800] Loss: 0.4857 Acc: 0.7570
训练:Epoch[154/200] Iteration[800/800] Loss: 0.4857 Acc: 0.7569
训练:Epoch[155/200] Iteration[200/800] Loss: 0.5179 Acc: 0.7409
训练:Epoch[155/200] Iteration[400/800] Loss: 0.5119 Acc: 0.7439
训练:Epoch[155/200] Iteration[600/800] Loss: 0.5086 Acc: 0.7456
训练:Epoch[155/200] Iteration[800/800] Loss: 0.5074 Acc: 0.7462
训练:Epoch[156/200] Iteration[200/800] Loss: 0.4899 Acc: 0.7544
训练:Epoch[156/200] Iteration[400/800] Loss: 0.4994 Acc: 0.7498
训练:Epoch[156/200] Iteration[600/800] Loss: 0.4926 Acc: 0.7532
训练:Epoch[156/200] Iteration[800/800] Loss: 0.4974 Acc: 0.7508
训练:Epoch[157/200] Iteration[200/800] Loss: 0.4931 Acc: 0.7528
训练:Epoch[157/200] Iteration[400/800] Loss: 0.5001 Acc: 0.7497
训练:Epoch[157/200] Iteration[600/800] Loss: 0.4927 Acc: 0.7534
训练:Epoch[157/200] Iteration[800/800] Loss: 0.4948 Acc: 0.7524
训练:Epoch[158/200] Iteration[200/800] Loss: 0.5178 Acc: 0.7409
训练:Epoch[158/200] Iteration[400/800] Loss: 0.5130 Acc: 0.7434
训练:Epoch[158/200] Iteration[600/800] Loss: 0.5187 Acc: 0.7406
训练:Epoch[158/200] Iteration[800/800] Loss: 0.5096 Acc: 0.7451
训练:Epoch[159/200] Iteration[200/800] Loss: 0.4866 Acc: 0.7566
训练:Epoch[159/200] Iteration[400/800] Loss: 0.4877 Acc: 0.7559
训练:Epoch[159/200] Iteration[600/800] Loss: 0.4874 Acc: 0.7560
训练:Epoch[159/200] Iteration[800/800] Loss: 0.4902 Acc: 0.7546
测试:	Epoch[159/200] Iteration[200/200] Loss: 0.4889 Acc: 0.7547
训练:Epoch[160/200] Iteration[200/800] Loss: 0.5094 Acc: 0.7447
训练:Epoch[160/200] Iteration[400/800] Loss: 0.5108 Acc: 0.7442
训练:Epoch[160/200] Iteration[600/800] Loss: 0.5056 Acc: 0.7470
训练:Epoch[160/200] Iteration[800/800] Loss: 0.5018 Acc: 0.7489
训练:Epoch[161/200] Iteration[200/800] Loss: 0.5173 Acc: 0.7412
训练:Epoch[161/200] Iteration[400/800] Loss: 0.4942 Acc: 0.7528
训练:Epoch[161/200] Iteration[600/800] Loss: 0.4963 Acc: 0.7518
训练:Epoch[161/200] Iteration[800/800] Loss: 0.4899 Acc: 0.7550
训练:Epoch[162/200] Iteration[200/800] Loss: 0.4842 Acc: 0.7575
训练:Epoch[162/200] Iteration[400/800] Loss: 0.4971 Acc: 0.7511
训练:Epoch[162/200] Iteration[600/800] Loss: 0.4965 Acc: 0.7514
训练:Epoch[162/200] Iteration[800/800] Loss: 0.4903 Acc: 0.7546
训练:Epoch[163/200] Iteration[200/800] Loss: 0.5188 Acc: 0.7406
训练:Epoch[163/200] Iteration[400/800] Loss: 0.5103 Acc: 0.7448
训练:Epoch[163/200] Iteration[600/800] Loss: 0.5075 Acc: 0.7462
训练:Epoch[163/200] Iteration[800/800] Loss: 0.5056 Acc: 0.7472
训练:Epoch[164/200] Iteration[200/800] Loss: 0.5066 Acc: 0.7466
训练:Epoch[164/200] Iteration[400/800] Loss: 0.4973 Acc: 0.7511
训练:Epoch[164/200] Iteration[600/800] Loss: 0.4893 Acc: 0.7551
训练:Epoch[164/200] Iteration[800/800] Loss: 0.4973 Acc: 0.7512
训练:Epoch[165/200] Iteration[200/800] Loss: 0.4974 Acc: 0.7509
训练:Epoch[165/200] Iteration[400/800] Loss: 0.4975 Acc: 0.7511
训练:Epoch[165/200] Iteration[600/800] Loss: 0.4939 Acc: 0.7529
训练:Epoch[165/200] Iteration[800/800] Loss: 0.4974 Acc: 0.7512
训练:Epoch[166/200] Iteration[200/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[166/200] Iteration[400/800] Loss: 0.5005 Acc: 0.7495
训练:Epoch[166/200] Iteration[600/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[166/200] Iteration[800/800] Loss: 0.4967 Acc: 0.7514
训练:Epoch[167/200] Iteration[200/800] Loss: 0.4970 Acc: 0.7512
训练:Epoch[167/200] Iteration[400/800] Loss: 0.4883 Acc: 0.7555
训练:Epoch[167/200] Iteration[600/800] Loss: 0.4954 Acc: 0.7520
训练:Epoch[167/200] Iteration[800/800] Loss: 0.4962 Acc: 0.7516
训练:Epoch[168/200] Iteration[200/800] Loss: 0.5251 Acc: 0.7372
训练:Epoch[168/200] Iteration[400/800] Loss: 0.4993 Acc: 0.7502
训练:Epoch[168/200] Iteration[600/800] Loss: 0.4980 Acc: 0.7507
训练:Epoch[168/200] Iteration[800/800] Loss: 0.4885 Acc: 0.7555
训练:Epoch[169/200] Iteration[200/800] Loss: 0.4863 Acc: 0.7569
训练:Epoch[169/200] Iteration[400/800] Loss: 0.4853 Acc: 0.7572
训练:Epoch[169/200] Iteration[600/800] Loss: 0.4872 Acc: 0.7561
训练:Epoch[169/200] Iteration[800/800] Loss: 0.4972 Acc: 0.7512
测试:	Epoch[169/200] Iteration[200/200] Loss: 0.5010 Acc: 0.7484
训练:Epoch[170/200] Iteration[200/800] Loss: 0.5083 Acc: 0.7456
训练:Epoch[170/200] Iteration[400/800] Loss: 0.4845 Acc: 0.7575
训练:Epoch[170/200] Iteration[600/800] Loss: 0.4899 Acc: 0.7548
训练:Epoch[170/200] Iteration[800/800] Loss: 0.4948 Acc: 0.7524
训练:Epoch[171/200] Iteration[200/800] Loss: 0.4813 Acc: 0.7591
训练:Epoch[171/200] Iteration[400/800] Loss: 0.4966 Acc: 0.7516
训练:Epoch[171/200] Iteration[600/800] Loss: 0.4949 Acc: 0.7524
训练:Epoch[171/200] Iteration[800/800] Loss: 0.4908 Acc: 0.7544
训练:Epoch[172/200] Iteration[200/800] Loss: 0.4947 Acc: 0.7525
训练:Epoch[172/200] Iteration[400/800] Loss: 0.4986 Acc: 0.7505
训练:Epoch[172/200] Iteration[600/800] Loss: 0.4983 Acc: 0.7507
训练:Epoch[172/200] Iteration[800/800] Loss: 0.4945 Acc: 0.7526
训练:Epoch[173/200] Iteration[200/800] Loss: 0.5081 Acc: 0.7459
训练:Epoch[173/200] Iteration[400/800] Loss: 0.5034 Acc: 0.7483
训练:Epoch[173/200] Iteration[600/800] Loss: 0.5027 Acc: 0.7485
训练:Epoch[173/200] Iteration[800/800] Loss: 0.5086 Acc: 0.7455
训练:Epoch[174/200] Iteration[200/800] Loss: 0.5191 Acc: 0.7403
训练:Epoch[174/200] Iteration[400/800] Loss: 0.5058 Acc: 0.7470
训练:Epoch[174/200] Iteration[600/800] Loss: 0.5000 Acc: 0.7499
训练:Epoch[174/200] Iteration[800/800] Loss: 0.5027 Acc: 0.7486
训练:Epoch[175/200] Iteration[200/800] Loss: 0.5060 Acc: 0.7469
训练:Epoch[175/200] Iteration[400/800] Loss: 0.4965 Acc: 0.7516
训练:Epoch[175/200] Iteration[600/800] Loss: 0.4853 Acc: 0.7572
训练:Epoch[175/200] Iteration[800/800] Loss: 0.4832 Acc: 0.7583
训练:Epoch[176/200] Iteration[200/800] Loss: 0.4819 Acc: 0.7591
训练:Epoch[176/200] Iteration[400/800] Loss: 0.4971 Acc: 0.7512
训练:Epoch[176/200] Iteration[600/800] Loss: 0.4940 Acc: 0.7528
训练:Epoch[176/200] Iteration[800/800] Loss: 0.4979 Acc: 0.7509
训练:Epoch[177/200] Iteration[200/800] Loss: 0.4779 Acc: 0.7606
训练:Epoch[177/200] Iteration[400/800] Loss: 0.4916 Acc: 0.7539
训练:Epoch[177/200] Iteration[600/800] Loss: 0.4950 Acc: 0.7523
训练:Epoch[177/200] Iteration[800/800] Loss: 0.4923 Acc: 0.7537
训练:Epoch[178/200] Iteration[200/800] Loss: 0.4972 Acc: 0.7512
训练:Epoch[178/200] Iteration[400/800] Loss: 0.5046 Acc: 0.7475
训练:Epoch[178/200] Iteration[600/800] Loss: 0.5093 Acc: 0.7450
训练:Epoch[178/200] Iteration[800/800] Loss: 0.5088 Acc: 0.7454
训练:Epoch[179/200] Iteration[200/800] Loss: 0.4907 Acc: 0.7541
训练:Epoch[179/200] Iteration[400/800] Loss: 0.4891 Acc: 0.7552
训练:Epoch[179/200] Iteration[600/800] Loss: 0.5073 Acc: 0.7461
训练:Epoch[179/200] Iteration[800/800] Loss: 0.5097 Acc: 0.7450
测试:	Epoch[179/200] Iteration[200/200] Loss: 0.5158 Acc: 0.7419
训练:Epoch[180/200] Iteration[200/800] Loss: 0.5156 Acc: 0.7422
训练:Epoch[180/200] Iteration[400/800] Loss: 0.5081 Acc: 0.7458
训练:Epoch[180/200] Iteration[600/800] Loss: 0.5036 Acc: 0.7480
训练:Epoch[180/200] Iteration[800/800] Loss: 0.4946 Acc: 0.7525
训练:Epoch[181/200] Iteration[200/800] Loss: 0.5231 Acc: 0.7384
训练:Epoch[181/200] Iteration[400/800] Loss: 0.5113 Acc: 0.7444
训练:Epoch[181/200] Iteration[600/800] Loss: 0.5089 Acc: 0.7455
训练:Epoch[181/200] Iteration[800/800] Loss: 0.5093 Acc: 0.7453
训练:Epoch[182/200] Iteration[200/800] Loss: 0.4850 Acc: 0.7575
训练:Epoch[182/200] Iteration[400/800] Loss: 0.4996 Acc: 0.7502
训练:Epoch[182/200] Iteration[600/800] Loss: 0.4999 Acc: 0.7500
训练:Epoch[182/200] Iteration[800/800] Loss: 0.4954 Acc: 0.7523
训练:Epoch[183/200] Iteration[200/800] Loss: 0.5376 Acc: 0.7297
训练:Epoch[183/200] Iteration[400/800] Loss: 0.5192 Acc: 0.7395
训练:Epoch[183/200] Iteration[600/800] Loss: 0.5076 Acc: 0.7456
训练:Epoch[183/200] Iteration[800/800] Loss: 0.5117 Acc: 0.7437
训练:Epoch[184/200] Iteration[200/800] Loss: 0.5038 Acc: 0.7481
训练:Epoch[184/200] Iteration[400/800] Loss: 0.5100 Acc: 0.7450
训练:Epoch[184/200] Iteration[600/800] Loss: 0.4995 Acc: 0.7502
训练:Epoch[184/200] Iteration[800/800] Loss: 0.4995 Acc: 0.7501
训练:Epoch[185/200] Iteration[200/800] Loss: 0.4837 Acc: 0.7581
训练:Epoch[185/200] Iteration[400/800] Loss: 0.4900 Acc: 0.7548
训练:Epoch[185/200] Iteration[600/800] Loss: 0.4826 Acc: 0.7585
训练:Epoch[185/200] Iteration[800/800] Loss: 0.4862 Acc: 0.7568
训练:Epoch[186/200] Iteration[200/800] Loss: 0.4997 Acc: 0.7500
训练:Epoch[186/200] Iteration[400/800] Loss: 0.4888 Acc: 0.7555
训练:Epoch[186/200] Iteration[600/800] Loss: 0.4927 Acc: 0.7535
训练:Epoch[186/200] Iteration[800/800] Loss: 0.4910 Acc: 0.7544
训练:Epoch[187/200] Iteration[200/800] Loss: 0.4897 Acc: 0.7550
训练:Epoch[187/200] Iteration[400/800] Loss: 0.4910 Acc: 0.7544
训练:Epoch[187/200] Iteration[600/800] Loss: 0.4928 Acc: 0.7534
训练:Epoch[187/200] Iteration[800/800] Loss: 0.4959 Acc: 0.7519
训练:Epoch[188/200] Iteration[200/800] Loss: 0.4866 Acc: 0.7566
训练:Epoch[188/200] Iteration[400/800] Loss: 0.5008 Acc: 0.7495
训练:Epoch[188/200] Iteration[600/800] Loss: 0.5041 Acc: 0.7479
训练:Epoch[188/200] Iteration[800/800] Loss: 0.5104 Acc: 0.7447
训练:Epoch[189/200] Iteration[200/800] Loss: 0.5094 Acc: 0.7450
训练:Epoch[189/200] Iteration[400/800] Loss: 0.5066 Acc: 0.7464
训练:Epoch[189/200] Iteration[600/800] Loss: 0.4983 Acc: 0.7505
训练:Epoch[189/200] Iteration[800/800] Loss: 0.4938 Acc: 0.7528
测试:	Epoch[189/200] Iteration[200/200] Loss: 0.5043 Acc: 0.7475
训练:Epoch[190/200] Iteration[200/800] Loss: 0.4847 Acc: 0.7575
训练:Epoch[190/200] Iteration[400/800] Loss: 0.4886 Acc: 0.7556
训练:Epoch[190/200] Iteration[600/800] Loss: 0.4864 Acc: 0.7568
训练:Epoch[190/200] Iteration[800/800] Loss: 0.4852 Acc: 0.7573
训练:Epoch[191/200] Iteration[200/800] Loss: 0.5121 Acc: 0.7438
训练:Epoch[191/200] Iteration[400/800] Loss: 0.5054 Acc: 0.7472
训练:Epoch[191/200] Iteration[600/800] Loss: 0.5134 Acc: 0.7431
训练:Epoch[191/200] Iteration[800/800] Loss: 0.5059 Acc: 0.7469
训练:Epoch[192/200] Iteration[200/800] Loss: 0.4994 Acc: 0.7503
训练:Epoch[192/200] Iteration[400/800] Loss: 0.4913 Acc: 0.7544
训练:Epoch[192/200] Iteration[600/800] Loss: 0.5040 Acc: 0.7480
训练:Epoch[192/200] Iteration[800/800] Loss: 0.5136 Acc: 0.7432
训练:Epoch[193/200] Iteration[200/800] Loss: 0.4700 Acc: 0.7650
训练:Epoch[193/200] Iteration[400/800] Loss: 0.4789 Acc: 0.7605
训练:Epoch[193/200] Iteration[600/800] Loss: 0.4897 Acc: 0.7551
训练:Epoch[193/200] Iteration[800/800] Loss: 0.4919 Acc: 0.7540
训练:Epoch[194/200] Iteration[200/800] Loss: 0.5354 Acc: 0.7319
训练:Epoch[194/200] Iteration[400/800] Loss: 0.5119 Acc: 0.7438
训练:Epoch[194/200] Iteration[600/800] Loss: 0.5077 Acc: 0.7459
训练:Epoch[194/200] Iteration[800/800] Loss: 0.5051 Acc: 0.7473
训练:Epoch[195/200] Iteration[200/800] Loss: 0.5079 Acc: 0.7459
训练:Epoch[195/200] Iteration[400/800] Loss: 0.4966 Acc: 0.7516
训练:Epoch[195/200] Iteration[600/800] Loss: 0.4957 Acc: 0.7521
训练:Epoch[195/200] Iteration[800/800] Loss: 0.5065 Acc: 0.7466
训练:Epoch[196/200] Iteration[200/800] Loss: 0.4875 Acc: 0.7562
训练:Epoch[196/200] Iteration[400/800] Loss: 0.4821 Acc: 0.7589
训练:Epoch[196/200] Iteration[600/800] Loss: 0.4908 Acc: 0.7545
训练:Epoch[196/200] Iteration[800/800] Loss: 0.4908 Acc: 0.7543
训练:Epoch[197/200] Iteration[200/800] Loss: 0.5261 Acc: 0.7369
训练:Epoch[197/200] Iteration[400/800] Loss: 0.5098 Acc: 0.7448
训练:Epoch[197/200] Iteration[600/800] Loss: 0.5038 Acc: 0.7479
训练:Epoch[197/200] Iteration[800/800] Loss: 0.4985 Acc: 0.7506
训练:Epoch[198/200] Iteration[200/800] Loss: 0.4929 Acc: 0.7534
训练:Epoch[198/200] Iteration[400/800] Loss: 0.4875 Acc: 0.7561
训练:Epoch[198/200] Iteration[600/800] Loss: 0.4873 Acc: 0.7561
训练:Epoch[198/200] Iteration[800/800] Loss: 0.4864 Acc: 0.7566
训练:Epoch[199/200] Iteration[200/800] Loss: 0.5119 Acc: 0.7441
训练:Epoch[199/200] Iteration[400/800] Loss: 0.5122 Acc: 0.7438
训练:Epoch[199/200] Iteration[600/800] Loss: 0.5100 Acc: 0.7448
训练:Epoch[199/200] Iteration[800/800] Loss: 0.5122 Acc: 0.7437
测试:	Epoch[199/200] Iteration[200/200] Loss: 0.4777 Acc: 0.7600
