Namespace(batch_norm=False, batch_size=128, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float16', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.4, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_gn=False, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=128, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float16', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.4, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_gn=False, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=128, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float16', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.4, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=128, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float16', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.4, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=128, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float16', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.4, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=64, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float32', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.2, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
Namespace(batch_norm=False, batch_size=32, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float32', input_size=299, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.1, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
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Namespace(batch_norm=False, batch_size=32, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float32', input_size=299, label_smoothing=False, last_gamma=False, log_interval=50, logging_file='xception.log', lr=0.1, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='xception', momentum=0.9, no_wd=True, num_epochs=200, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_xception', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
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[Epoch 0] training: accuracy=0.030564
[Epoch 0] speed: 527 samples/sec	time cost: 2463.907229
[Epoch 0] validation: err-top1=0.876594 err-top5=0.696767
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[Epoch 1] training: accuracy=0.210195
[Epoch 1] speed: 543 samples/sec	time cost: 2389.798527
[Epoch 1] validation: err-top1=0.637260 err-top5=0.380288
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[Epoch 2] training: accuracy=0.343177
[Epoch 2] speed: 542 samples/sec	time cost: 2396.196461
[Epoch 2] validation: err-top1=0.538982 err-top5=0.277344
Epoch[3] Batch [49]	Speed: 548.963743 samples/sec	accuracy=0.390859	lr=0.060196
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[Epoch 3] training: accuracy=0.405804
[Epoch 3] speed: 542 samples/sec	time cost: 2395.493141
[Epoch 3] validation: err-top1=0.501594 err-top5=0.245197
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[Epoch 4] training: accuracy=0.438996
[Epoch 4] speed: 542 samples/sec	time cost: 2394.880544
[Epoch 4] validation: err-top1=0.475260 err-top5=0.218089
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[Epoch 5] training: accuracy=0.466042
[Epoch 5] speed: 543 samples/sec	time cost: 2392.253160
[Epoch 5] validation: err-top1=0.437059 err-top5=0.192248
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[Epoch 6] training: accuracy=0.488768
[Epoch 6] speed: 542 samples/sec	time cost: 2395.145935
[Epoch 6] validation: err-top1=0.424107 err-top5=0.182876
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[Epoch 7] training: accuracy=0.503988
[Epoch 7] speed: 543 samples/sec	time cost: 2392.886559
[Epoch 7] validation: err-top1=0.413982 err-top5=0.173558
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[Epoch 8] training: accuracy=0.514990
[Epoch 8] speed: 543 samples/sec	time cost: 2389.353789
[Epoch 8] validation: err-top1=0.402444 err-top5=0.166947
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[Epoch 9] training: accuracy=0.523776
[Epoch 9] speed: 543 samples/sec	time cost: 2391.406049
[Epoch 9] validation: err-top1=0.390286 err-top5=0.158841
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[Epoch 10] training: accuracy=0.530314
[Epoch 10] speed: 544 samples/sec	time cost: 2387.938241
[Epoch 10] validation: err-top1=0.388662 err-top5=0.156971
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[Epoch 11] training: accuracy=0.536149
[Epoch 11] speed: 541 samples/sec	time cost: 2396.960507
[Epoch 11] validation: err-top1=0.380829 err-top5=0.151262
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[Epoch 12] training: accuracy=0.540680
[Epoch 12] speed: 542 samples/sec	time cost: 2393.707859
[Epoch 12] validation: err-top1=0.376834 err-top5=0.149255
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[Epoch 13] training: accuracy=0.544255
[Epoch 13] speed: 544 samples/sec	time cost: 2386.549111
[Epoch 13] validation: err-top1=0.375901 err-top5=0.147937
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[Epoch 14] training: accuracy=0.547478
[Epoch 14] speed: 543 samples/sec	time cost: 2389.567055
[Epoch 14] validation: err-top1=0.377043 err-top5=0.145192
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Epoch[15] Batch [4999]	Speed: 550.872782 samples/sec	accuracy=0.550424	lr=0.099217
[Epoch 15] training: accuracy=0.550420
[Epoch 15] speed: 543 samples/sec	time cost: 2390.402058
[Epoch 15] validation: err-top1=0.369171 err-top5=0.145052
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[Epoch 16] training: accuracy=0.553085
[Epoch 16] speed: 543 samples/sec	time cost: 2389.306207
[Epoch 16] validation: err-top1=0.370556 err-top5=0.144153
Epoch[17] Batch [49]	Speed: 543.432836 samples/sec	accuracy=0.569063	lr=0.099067
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[Epoch 17] training: accuracy=0.555167
[Epoch 17] speed: 546 samples/sec	time cost: 2380.184843
[Epoch 17] validation: err-top1=0.369331 err-top5=0.140405
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[Epoch 18] training: accuracy=0.556898
[Epoch 18] speed: 546 samples/sec	time cost: 2378.387041
[Epoch 18] validation: err-top1=0.359816 err-top5=0.137540
Epoch[19] Batch [49]	Speed: 541.022197 samples/sec	accuracy=0.577500	lr=0.098732
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Epoch[19] Batch [4999]	Speed: 551.727828 samples/sec	accuracy=0.559665	lr=0.098547
[Epoch 19] training: accuracy=0.559681
[Epoch 19] speed: 546 samples/sec	time cost: 2376.685998
[Epoch 19] validation: err-top1=0.361667 err-top5=0.139290
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Epoch[20] Batch [4949]	Speed: 554.064029 samples/sec	accuracy=0.561600	lr=0.098350
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[Epoch 20] training: accuracy=0.561513
[Epoch 20] speed: 546 samples/sec	time cost: 2379.709805
[Epoch 20] validation: err-top1=0.363882 err-top5=0.138001
Epoch[21] Batch [49]	Speed: 542.017060 samples/sec	accuracy=0.572578	lr=0.098346
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Epoch[21] Batch [4999]	Speed: 549.130408 samples/sec	accuracy=0.563338	lr=0.098137
[Epoch 21] training: accuracy=0.563330
[Epoch 21] speed: 545 samples/sec	time cost: 2384.763561
[Epoch 21] validation: err-top1=0.358594 err-top5=0.137340
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[Epoch 22] training: accuracy=0.564477
[Epoch 22] speed: 543 samples/sec	time cost: 2389.096009
[Epoch 22] validation: err-top1=0.360651 err-top5=0.136141
Epoch[23] Batch [49]	Speed: 545.444858 samples/sec	accuracy=0.577031	lr=0.097910
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[Epoch 23] training: accuracy=0.566218
[Epoch 23] speed: 546 samples/sec	time cost: 2380.539280
[Epoch 23] validation: err-top1=0.361579 err-top5=0.135096
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[Epoch 24] training: accuracy=0.566904
[Epoch 24] speed: 547 samples/sec	time cost: 2374.558229
[Epoch 24] validation: err-top1=0.350541 err-top5=0.130449
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Epoch[25] Batch [4999]	Speed: 553.043895 samples/sec	accuracy=0.568662	lr=0.097166
[Epoch 25] training: accuracy=0.568653
[Epoch 25] speed: 545 samples/sec	time cost: 2380.839433
[Epoch 25] validation: err-top1=0.360511 err-top5=0.134706
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[Epoch 26] training: accuracy=0.570021
[Epoch 26] speed: 545 samples/sec	time cost: 2383.821960
[Epoch 26] validation: err-top1=0.357372 err-top5=0.132853
Epoch[27] Batch [49]	Speed: 541.638189 samples/sec	accuracy=0.580234	lr=0.096889
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Epoch[27] Batch [4999]	Speed: 555.776627 samples/sec	accuracy=0.571045	lr=0.096607
[Epoch 27] training: accuracy=0.571066
[Epoch 27] speed: 544 samples/sec	time cost: 2387.047717
[Epoch 27] validation: err-top1=0.354046 err-top5=0.131190
Epoch[28] Batch [49]	Speed: 546.996033 samples/sec	accuracy=0.583438	lr=0.096604
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[Epoch 28] training: accuracy=0.571761
[Epoch 28] speed: 544 samples/sec	time cost: 2389.266103
[Epoch 28] validation: err-top1=0.354153 err-top5=0.131118
Epoch[29] Batch [49]	Speed: 543.553451 samples/sec	accuracy=0.586641	lr=0.096306
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Epoch[29] Batch [4999]	Speed: 556.518982 samples/sec	accuracy=0.572509	lr=0.095999
[Epoch 29] training: accuracy=0.572517
[Epoch 29] speed: 545 samples/sec	time cost: 2382.366904
[Epoch 29] validation: err-top1=0.352183 err-top5=0.133233
Epoch[30] Batch [49]	Speed: 538.695744 samples/sec	accuracy=0.583594	lr=0.095996
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Epoch[30] Batch [4849]	Speed: 550.931002 samples/sec	accuracy=0.574737	lr=0.095687
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Epoch[30] Batch [4999]	Speed: 552.905583 samples/sec	accuracy=0.574441	lr=0.095678
[Epoch 30] training: accuracy=0.574417
[Epoch 30] speed: 546 samples/sec	time cost: 2377.938961
[Epoch 30] validation: err-top1=0.351322 err-top5=0.125921
Epoch[31] Batch [49]	Speed: 552.435125 samples/sec	accuracy=0.584766	lr=0.095674
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Epoch[31] Batch [4999]	Speed: 549.773773 samples/sec	accuracy=0.575795	lr=0.095344
[Epoch 31] training: accuracy=0.575774
[Epoch 31] speed: 543 samples/sec	time cost: 2390.525376
[Epoch 31] validation: err-top1=0.351482 err-top5=0.132612
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[Epoch 32] training: accuracy=0.576669
[Epoch 32] speed: 544 samples/sec	time cost: 2385.824836
[Epoch 32] validation: err-top1=0.346720 err-top5=0.127910
Epoch[33] Batch [49]	Speed: 547.338470 samples/sec	accuracy=0.593828	lr=0.094995
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Epoch[33] Batch [4999]	Speed: 550.736101 samples/sec	accuracy=0.578137	lr=0.094642
[Epoch 33] training: accuracy=0.578145
[Epoch 33] speed: 544 samples/sec	time cost: 2385.470487
[Epoch 33] validation: err-top1=0.349980 err-top5=0.128345
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[Epoch 34] training: accuracy=0.578838
[Epoch 34] speed: 544 samples/sec	time cost: 2388.186838
[Epoch 34] validation: err-top1=0.347857 err-top5=0.125962
Epoch[35] Batch [49]	Speed: 544.704752 samples/sec	accuracy=0.588906	lr=0.094269
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[Epoch 35] training: accuracy=0.579849
[Epoch 35] speed: 542 samples/sec	time cost: 2395.432975
[Epoch 35] validation: err-top1=0.346799 err-top5=0.125598
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[Epoch 36] training: accuracy=0.580137
[Epoch 36] speed: 543 samples/sec	time cost: 2392.475289
[Epoch 36] validation: err-top1=0.346334 err-top5=0.124820
Epoch[37] Batch [49]	Speed: 546.125778 samples/sec	accuracy=0.589766	lr=0.093497
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Epoch[37] Batch [4999]	Speed: 550.305120 samples/sec	accuracy=0.581746	lr=0.093099
[Epoch 37] training: accuracy=0.581749
[Epoch 37] speed: 544 samples/sec	time cost: 2385.372393
[Epoch 37] validation: err-top1=0.350761 err-top5=0.129728
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[Epoch 38] training: accuracy=0.582771
[Epoch 38] speed: 545 samples/sec	time cost: 2381.076853
[Epoch 38] validation: err-top1=0.344567 err-top5=0.125359
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Epoch[39] Batch [4999]	Speed: 554.113723 samples/sec	accuracy=0.583527	lr=0.092260
[Epoch 39] training: accuracy=0.583506
[Epoch 39] speed: 546 samples/sec	time cost: 2378.186382
[Epoch 39] validation: err-top1=0.344010 err-top5=0.124740
Epoch[40] Batch [49]	Speed: 548.994214 samples/sec	accuracy=0.597812	lr=0.092255
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[Epoch 40] training: accuracy=0.584859
[Epoch 40] speed: 546 samples/sec	time cost: 2376.414887
[Epoch 40] validation: err-top1=0.343289 err-top5=0.125781
Epoch[41] Batch [49]	Speed: 544.275409 samples/sec	accuracy=0.602656	lr=0.091819
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[Epoch 41] training: accuracy=0.585228
[Epoch 41] speed: 545 samples/sec	time cost: 2383.011248
[Epoch 41] validation: err-top1=0.344846 err-top5=0.127392
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[Epoch 42] training: accuracy=0.586854
[Epoch 42] speed: 543 samples/sec	time cost: 2389.850111
[Epoch 42] validation: err-top1=0.342508 err-top5=0.123798
Epoch[43] Batch [49]	Speed: 546.600816 samples/sec	accuracy=0.596719	lr=0.090915
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Epoch[43] Batch [4999]	Speed: 557.234801 samples/sec	accuracy=0.587579	lr=0.090451
[Epoch 43] training: accuracy=0.587567
[Epoch 43] speed: 546 samples/sec	time cost: 2377.600957
[Epoch 43] validation: err-top1=0.335296 err-top5=0.121534
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[Epoch 44] training: accuracy=0.588259
[Epoch 44] speed: 545 samples/sec	time cost: 2383.726789
[Epoch 44] validation: err-top1=0.341498 err-top5=0.125219
Epoch[45] Batch [49]	Speed: 551.443875 samples/sec	accuracy=0.599688	lr=0.089967
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[Epoch 45] training: accuracy=0.588752
[Epoch 45] speed: 546 samples/sec	time cost: 2375.828171
[Epoch 45] validation: err-top1=0.341286 err-top5=0.124720
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[Epoch 46] training: accuracy=0.590022
[Epoch 46] speed: 546 samples/sec	time cost: 2380.419968
[Epoch 46] validation: err-top1=0.334155 err-top5=0.119992
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[Epoch 47] training: accuracy=0.591087
[Epoch 47] speed: 546 samples/sec	time cost: 2377.937643
[Epoch 47] validation: err-top1=0.336859 err-top5=0.120733
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[Epoch 48] training: accuracy=0.592417
[Epoch 48] speed: 544 samples/sec	time cost: 2389.345915
[Epoch 48] validation: err-top1=0.337273 err-top5=0.121951
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[Epoch 49] training: accuracy=0.592826
[Epoch 49] speed: 543 samples/sec	time cost: 2392.114789
[Epoch 49] validation: err-top1=0.340064 err-top5=0.120433
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[Epoch 50] training: accuracy=0.594058
[Epoch 50] speed: 544 samples/sec	time cost: 2385.040081
[Epoch 50] validation: err-top1=0.333854 err-top5=0.118550
Epoch[51] Batch [49]	Speed: 538.916445 samples/sec	accuracy=0.602656	lr=0.086881
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[Epoch 51] training: accuracy=0.595053
[Epoch 51] speed: 543 samples/sec	time cost: 2390.705714
[Epoch 51] validation: err-top1=0.338090 err-top5=0.121253
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[Epoch 52] training: accuracy=0.595019
[Epoch 52] speed: 545 samples/sec	time cost: 2384.019118
[Epoch 52] validation: err-top1=0.336218 err-top5=0.120653
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[Epoch 53] training: accuracy=0.597069
[Epoch 53] speed: 545 samples/sec	time cost: 2383.547872
[Epoch 53] validation: err-top1=0.336518 err-top5=0.121094
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[Epoch 54] training: accuracy=0.597789
[Epoch 54] speed: 545 samples/sec	time cost: 2383.208403
[Epoch 54] validation: err-top1=0.332629 err-top5=0.119619
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Epoch[55] Batch [4999]	Speed: 558.891226 samples/sec	accuracy=0.599189	lr=0.084051
[Epoch 55] training: accuracy=0.599181
[Epoch 55] speed: 546 samples/sec	time cost: 2378.525981
[Epoch 55] validation: err-top1=0.331691 err-top5=0.117548
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[Epoch 56] training: accuracy=0.599386
[Epoch 56] speed: 545 samples/sec	time cost: 2383.894123
[Epoch 56] validation: err-top1=0.331791 err-top5=0.117127
Epoch[57] Batch [49]	Speed: 555.513897 samples/sec	accuracy=0.602422	lr=0.083451
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[Epoch 57] training: accuracy=0.599799
[Epoch 57] speed: 544 samples/sec	time cost: 2386.463466
[Epoch 57] validation: err-top1=0.330716 err-top5=0.116510
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[Epoch 58] training: accuracy=0.601320
[Epoch 58] speed: 545 samples/sec	time cost: 2381.230836
[Epoch 58] validation: err-top1=0.332712 err-top5=0.115665
Epoch[59] Batch [49]	Speed: 546.140789 samples/sec	accuracy=0.609922	lr=0.082236
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[Epoch 59] training: accuracy=0.602803
[Epoch 59] speed: 546 samples/sec	time cost: 2377.108089
[Epoch 59] validation: err-top1=0.329667 err-top5=0.117869
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[Epoch 60] training: accuracy=0.603572
[Epoch 60] speed: 546 samples/sec	time cost: 2377.751257
[Epoch 60] validation: err-top1=0.328623 err-top5=0.114915
Epoch[61] Batch [49]	Speed: 552.307668 samples/sec	accuracy=0.620469	lr=0.080988
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Epoch[61] Batch [4999]	Speed: 554.335833 samples/sec	accuracy=0.604085	lr=0.080359
[Epoch 61] training: accuracy=0.604085
[Epoch 61] speed: 546 samples/sec	time cost: 2378.159241
[Epoch 61] validation: err-top1=0.327324 err-top5=0.115845
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Epoch[62] Batch [4999]	Speed: 550.497853 samples/sec	accuracy=0.605383	lr=0.079715
[Epoch 62] training: accuracy=0.605376
[Epoch 62] speed: 545 samples/sec	time cost: 2381.759063
[Epoch 62] validation: err-top1=0.329607 err-top5=0.114984
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[Epoch 63] training: accuracy=0.606053
[Epoch 63] speed: 547 samples/sec	time cost: 2373.896937
[Epoch 63] validation: err-top1=0.332212 err-top5=0.115705
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[Epoch 64] training: accuracy=0.607383
[Epoch 64] speed: 546 samples/sec	time cost: 2377.275588
[Epoch 64] validation: err-top1=0.329460 err-top5=0.113540
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[Epoch 65] training: accuracy=0.608680
[Epoch 65] speed: 547 samples/sec	time cost: 2374.114807
[Epoch 65] validation: err-top1=0.325781 err-top5=0.114042
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[Epoch 66] training: accuracy=0.609052
[Epoch 66] speed: 547 samples/sec	time cost: 2375.950398
[Epoch 66] validation: err-top1=0.323898 err-top5=0.113421
Epoch[67] Batch [49]	Speed: 544.201806 samples/sec	accuracy=0.623906	lr=0.077056
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Epoch[67] Batch [4999]	Speed: 552.970373 samples/sec	accuracy=0.609748	lr=0.076383
[Epoch 67] training: accuracy=0.609748
[Epoch 67] speed: 546 samples/sec	time cost: 2376.650445
[Epoch 67] validation: err-top1=0.326790 err-top5=0.114935
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[Epoch 68] training: accuracy=0.611011
[Epoch 68] speed: 546 samples/sec	time cost: 2376.371897
[Epoch 68] validation: err-top1=0.323698 err-top5=0.111458
Epoch[69] Batch [49]	Speed: 537.256528 samples/sec	accuracy=0.618906	lr=0.075688
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[Epoch 69] training: accuracy=0.612138
[Epoch 69] speed: 546 samples/sec	time cost: 2378.432016
[Epoch 69] validation: err-top1=0.322476 err-top5=0.110978
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Epoch[70] Batch [4999]	Speed: 556.845968 samples/sec	accuracy=0.613860	lr=0.074300
[Epoch 70] training: accuracy=0.613839
[Epoch 70] speed: 545 samples/sec	time cost: 2381.342155
[Epoch 70] validation: err-top1=0.320871 err-top5=0.111169
Epoch[71] Batch [49]	Speed: 544.983282 samples/sec	accuracy=0.626875	lr=0.074292
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Epoch[71] Batch [4999]	Speed: 554.384861 samples/sec	accuracy=0.614934	lr=0.073593
[Epoch 71] training: accuracy=0.614927
[Epoch 71] speed: 543 samples/sec	time cost: 2390.090803
[Epoch 71] validation: err-top1=0.325321 err-top5=0.112380
Epoch[72] Batch [49]	Speed: 542.736334 samples/sec	accuracy=0.619609	lr=0.073585
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Epoch[72] Batch [4999]	Speed: 553.217704 samples/sec	accuracy=0.615299	lr=0.072879
[Epoch 72] training: accuracy=0.615302
[Epoch 72] speed: 545 samples/sec	time cost: 2382.223489
[Epoch 72] validation: err-top1=0.318149 err-top5=0.110677
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Epoch[73] Batch [4999]	Speed: 553.237976 samples/sec	accuracy=0.616702	lr=0.072160
[Epoch 73] training: accuracy=0.616675
[Epoch 73] speed: 545 samples/sec	time cost: 2382.080009
[Epoch 73] validation: err-top1=0.319057 err-top5=0.110411
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[Epoch 74] training: accuracy=0.617351
[Epoch 74] speed: 545 samples/sec	time cost: 2380.854556
[Epoch 74] validation: err-top1=0.315184 err-top5=0.107993
Epoch[75] Batch [49]	Speed: 550.827300 samples/sec	accuracy=0.633906	lr=0.071428
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[Epoch 75] training: accuracy=0.618148
[Epoch 75] speed: 544 samples/sec	time cost: 2385.263640
[Epoch 75] validation: err-top1=0.320373 err-top5=0.109716
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[Epoch 76] training: accuracy=0.620419
[Epoch 76] speed: 544 samples/sec	time cost: 2387.468400
[Epoch 76] validation: err-top1=0.317702 err-top5=0.108737
Epoch[77] Batch [49]	Speed: 540.589084 samples/sec	accuracy=0.631953	lr=0.069961
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[Epoch 77] training: accuracy=0.621467
[Epoch 77] speed: 545 samples/sec	time cost: 2382.777568
[Epoch 77] validation: err-top1=0.314423 err-top5=0.107352
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Epoch[78] Batch [4999]	Speed: 553.739078 samples/sec	accuracy=0.621831	lr=0.068482
[Epoch 78] training: accuracy=0.621829
[Epoch 78] speed: 543 samples/sec	time cost: 2390.084893
[Epoch 78] validation: err-top1=0.314984 err-top5=0.106831
Epoch[79] Batch [49]	Speed: 549.953931 samples/sec	accuracy=0.631953	lr=0.068474
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Epoch[79] Batch [4999]	Speed: 552.739892 samples/sec	accuracy=0.623485	lr=0.067731
[Epoch 79] training: accuracy=0.623453
[Epoch 79] speed: 545 samples/sec	time cost: 2384.262237
[Epoch 79] validation: err-top1=0.310537 err-top5=0.108954
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Epoch[80] Batch [4849]	Speed: 533.665435 samples/sec	accuracy=0.624975	lr=0.066998
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Epoch[80] Batch [4999]	Speed: 547.368699 samples/sec	accuracy=0.624745	lr=0.066976
[Epoch 80] training: accuracy=0.624755
[Epoch 80] speed: 544 samples/sec	time cost: 2385.456127
[Epoch 80] validation: err-top1=0.316127 err-top5=0.109594
Epoch[81] Batch [49]	Speed: 540.703140 samples/sec	accuracy=0.636719	lr=0.066967
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[Epoch 81] training: accuracy=0.625908
[Epoch 81] speed: 544 samples/sec	time cost: 2384.063947
[Epoch 81] validation: err-top1=0.311619 err-top5=0.105068
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[Epoch 82] training: accuracy=0.626804
[Epoch 82] speed: 543 samples/sec	time cost: 2389.534181
[Epoch 82] validation: err-top1=0.315204 err-top5=0.106991
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Epoch[83] Batch [4799]	Speed: 540.945803 samples/sec	accuracy=0.628407	lr=0.064714
Epoch[83] Batch [4849]	Speed: 541.403504 samples/sec	accuracy=0.628404	lr=0.064707
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Epoch[83] Batch [4999]	Speed: 546.399902 samples/sec	accuracy=0.628289	lr=0.064684
[Epoch 83] training: accuracy=0.628291
[Epoch 83] speed: 544 samples/sec	time cost: 2385.746231
[Epoch 83] validation: err-top1=0.312002 err-top5=0.105010
Epoch[84] Batch [49]	Speed: 540.415046 samples/sec	accuracy=0.639922	lr=0.064675
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Epoch[84] Batch [4999]	Speed: 550.313790 samples/sec	accuracy=0.629318	lr=0.063912
[Epoch 84] training: accuracy=0.629301
[Epoch 84] speed: 545 samples/sec	time cost: 2382.581370
[Epoch 84] validation: err-top1=0.313061 err-top5=0.106010
Epoch[85] Batch [49]	Speed: 545.179596 samples/sec	accuracy=0.642656	lr=0.063903
Epoch[85] Batch [99]	Speed: 546.954070 samples/sec	accuracy=0.642305	lr=0.063896
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[Epoch 85] training: accuracy=0.630365
[Epoch 85] speed: 545 samples/sec	time cost: 2382.191083
[Epoch 85] validation: err-top1=0.306350 err-top5=0.102965
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[Epoch 86] training: accuracy=0.631780
[Epoch 86] speed: 546 samples/sec	time cost: 2377.869011
[Epoch 86] validation: err-top1=0.303771 err-top5=0.101104
Epoch[87] Batch [49]	Speed: 549.494740 samples/sec	accuracy=0.653516	lr=0.062349
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Epoch[87] Batch [4999]	Speed: 556.367919 samples/sec	accuracy=0.633202	lr=0.061575
[Epoch 87] training: accuracy=0.633193
[Epoch 87] speed: 547 samples/sec	time cost: 2376.177490
[Epoch 87] validation: err-top1=0.309355 err-top5=0.103045
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Epoch[88] Batch [4999]	Speed: 554.222796 samples/sec	accuracy=0.634596	lr=0.060790
[Epoch 88] training: accuracy=0.634585
[Epoch 88] speed: 546 samples/sec	time cost: 2378.884656
[Epoch 88] validation: err-top1=0.305028 err-top5=0.100561
Epoch[89] Batch [49]	Speed: 544.664997 samples/sec	accuracy=0.645469	lr=0.060782
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Epoch[89] Batch [4999]	Speed: 549.151634 samples/sec	accuracy=0.635589	lr=0.060002
[Epoch 89] training: accuracy=0.635605
[Epoch 89] speed: 546 samples/sec	time cost: 2378.533523
[Epoch 89] validation: err-top1=0.302874 err-top5=0.102041
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[Epoch 90] training: accuracy=0.636517
[Epoch 90] speed: 547 samples/sec	time cost: 2374.869613
[Epoch 90] validation: err-top1=0.305769 err-top5=0.101002
Epoch[91] Batch [49]	Speed: 554.155825 samples/sec	accuracy=0.654219	lr=0.059203
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[Epoch 91] training: accuracy=0.638177
[Epoch 91] speed: 547 samples/sec	time cost: 2374.007265
[Epoch 91] validation: err-top1=0.306631 err-top5=0.102664
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[Epoch 92] training: accuracy=0.639375
[Epoch 92] speed: 547 samples/sec	time cost: 2374.672506
[Epoch 92] validation: err-top1=0.303173 err-top5=0.100128
Epoch[93] Batch [49]	Speed: 551.341068 samples/sec	accuracy=0.647031	lr=0.057615
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[Epoch 93] training: accuracy=0.641041
[Epoch 93] speed: 546 samples/sec	time cost: 2377.619981
[Epoch 93] validation: err-top1=0.303185 err-top5=0.098698
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[Epoch 94] training: accuracy=0.641705
[Epoch 94] speed: 547 samples/sec	time cost: 2374.744885
[Epoch 94] validation: err-top1=0.302965 err-top5=0.097376
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Epoch[95] Batch [4999]	Speed: 550.280330 samples/sec	accuracy=0.643281	lr=0.055227
[Epoch 95] training: accuracy=0.643301
[Epoch 95] speed: 546 samples/sec	time cost: 2379.599874
[Epoch 95] validation: err-top1=0.297997 err-top5=0.097236
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Epoch[96] Batch [4999]	Speed: 555.028486 samples/sec	accuracy=0.644713	lr=0.054425
[Epoch 96] training: accuracy=0.644719
[Epoch 96] speed: 545 samples/sec	time cost: 2380.782194
[Epoch 96] validation: err-top1=0.299665 err-top5=0.099729
Epoch[97] Batch [49]	Speed: 546.889551 samples/sec	accuracy=0.654922	lr=0.054417
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[Epoch 97] training: accuracy=0.646224
[Epoch 97] speed: 547 samples/sec	time cost: 2375.165768
[Epoch 97] validation: err-top1=0.299159 err-top5=0.097977
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Epoch[98] Batch [4999]	Speed: 557.534634 samples/sec	accuracy=0.648338	lr=0.052819
[Epoch 98] training: accuracy=0.648342
[Epoch 98] speed: 546 samples/sec	time cost: 2378.782099
[Epoch 98] validation: err-top1=0.299299 err-top5=0.098157
Epoch[99] Batch [49]	Speed: 552.758979 samples/sec	accuracy=0.655625	lr=0.052810
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[Epoch 99] training: accuracy=0.648811
[Epoch 99] speed: 546 samples/sec	time cost: 2377.706494
[Epoch 99] validation: err-top1=0.297393 err-top5=0.096062
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[Epoch 100] training: accuracy=0.651280
[Epoch 100] speed: 547 samples/sec	time cost: 2374.586564
[Epoch 100] validation: err-top1=0.291827 err-top5=0.096074
Epoch[101] Batch [49]	Speed: 545.881033 samples/sec	accuracy=0.659844	lr=0.051200
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Epoch[101] Batch [4999]	Speed: 548.862150 samples/sec	accuracy=0.652236	lr=0.050404
[Epoch 101] training: accuracy=0.652260
[Epoch 101] speed: 546 samples/sec	time cost: 2378.817854
[Epoch 101] validation: err-top1=0.293890 err-top5=0.097115
Epoch[102] Batch [49]	Speed: 558.248601 samples/sec	accuracy=0.665078	lr=0.050395
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Epoch[102] Batch [4999]	Speed: 559.640956 samples/sec	accuracy=0.653103	lr=0.049598
[Epoch 102] training: accuracy=0.653143
[Epoch 102] speed: 547 samples/sec	time cost: 2375.333368
[Epoch 102] validation: err-top1=0.288923 err-top5=0.095882
Epoch[103] Batch [49]	Speed: 545.388739 samples/sec	accuracy=0.668125	lr=0.049589
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Epoch[103] Batch [4999]	Speed: 556.287833 samples/sec	accuracy=0.655591	lr=0.048793
[Epoch 103] training: accuracy=0.655584
[Epoch 103] speed: 546 samples/sec	time cost: 2380.182547
[Epoch 103] validation: err-top1=0.296955 err-top5=0.100901
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Epoch[104] Batch [4999]	Speed: 556.963718 samples/sec	accuracy=0.656578	lr=0.047988
[Epoch 104] training: accuracy=0.656574
[Epoch 104] speed: 547 samples/sec	time cost: 2375.888978
[Epoch 104] validation: err-top1=0.293550 err-top5=0.095353
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[Epoch 105] training: accuracy=0.657531
[Epoch 105] speed: 545 samples/sec	time cost: 2382.709565
[Epoch 105] validation: err-top1=0.291893 err-top5=0.094527
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Epoch[106] Batch [4999]	Speed: 555.748160 samples/sec	accuracy=0.659530	lr=0.046379
[Epoch 106] training: accuracy=0.659509
[Epoch 106] speed: 546 samples/sec	time cost: 2376.762726
[Epoch 106] validation: err-top1=0.292288 err-top5=0.093750
Epoch[107] Batch [49]	Speed: 551.972641 samples/sec	accuracy=0.666641	lr=0.046370
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Epoch[107] Batch [4999]	Speed: 550.270578 samples/sec	accuracy=0.661148	lr=0.045576
[Epoch 107] training: accuracy=0.661143
[Epoch 107] speed: 546 samples/sec	time cost: 2379.872824
[Epoch 107] validation: err-top1=0.291066 err-top5=0.093089
Epoch[108] Batch [49]	Speed: 546.759617 samples/sec	accuracy=0.673047	lr=0.045567
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Epoch[108] Batch [4999]	Speed: 552.817400 samples/sec	accuracy=0.662948	lr=0.044774
[Epoch 108] training: accuracy=0.662924
[Epoch 108] speed: 546 samples/sec	time cost: 2376.408546
[Epoch 108] validation: err-top1=0.284040 err-top5=0.091179
Epoch[109] Batch [49]	Speed: 549.202176 samples/sec	accuracy=0.684375	lr=0.044766
Epoch[109] Batch [99]	Speed: 541.873729 samples/sec	accuracy=0.680547	lr=0.044758
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Epoch[109] Batch [4999]	Speed: 559.010081 samples/sec	accuracy=0.664630	lr=0.043974
[Epoch 109] training: accuracy=0.664624
[Epoch 109] speed: 546 samples/sec	time cost: 2378.335400
[Epoch 109] validation: err-top1=0.289704 err-top5=0.091887
Epoch[110] Batch [49]	Speed: 546.108468 samples/sec	accuracy=0.679453	lr=0.043965
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Epoch[110] Batch [4999]	Speed: 557.190311 samples/sec	accuracy=0.665730	lr=0.043175
[Epoch 110] training: accuracy=0.665709
[Epoch 110] speed: 546 samples/sec	time cost: 2377.528314
[Epoch 110] validation: err-top1=0.282752 err-top5=0.090004
Epoch[111] Batch [49]	Speed: 550.066141 samples/sec	accuracy=0.681719	lr=0.043167
Epoch[111] Batch [99]	Speed: 556.856688 samples/sec	accuracy=0.679609	lr=0.043159
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Epoch[111] Batch [4999]	Speed: 559.850286 samples/sec	accuracy=0.667837	lr=0.042378
[Epoch 111] training: accuracy=0.667852
[Epoch 111] speed: 548 samples/sec	time cost: 2370.474496
[Epoch 111] validation: err-top1=0.279607 err-top5=0.089022
Epoch[112] Batch [49]	Speed: 552.196479 samples/sec	accuracy=0.685391	lr=0.042369
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Epoch[112] Batch [4999]	Speed: 552.750733 samples/sec	accuracy=0.669192	lr=0.041583
[Epoch 112] training: accuracy=0.669176
[Epoch 112] speed: 546 samples/sec	time cost: 2377.901634
[Epoch 112] validation: err-top1=0.281110 err-top5=0.089625
Epoch[113] Batch [49]	Speed: 543.652443 samples/sec	accuracy=0.675156	lr=0.041574
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Epoch[113] Batch [2999]	Speed: 558.288013 samples/sec	accuracy=0.674049	lr=0.041107
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Epoch[113] Batch [4999]	Speed: 558.318697 samples/sec	accuracy=0.671417	lr=0.040790
[Epoch 113] training: accuracy=0.671419
[Epoch 113] speed: 547 samples/sec	time cost: 2375.557406
[Epoch 113] validation: err-top1=0.276963 err-top5=0.086338
Epoch[114] Batch [49]	Speed: 546.416452 samples/sec	accuracy=0.689609	lr=0.040781
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Epoch[114] Batch [4799]	Speed: 538.149108 samples/sec	accuracy=0.672239	lr=0.040031
Epoch[114] Batch [4849]	Speed: 548.954201 samples/sec	accuracy=0.672192	lr=0.040023
Epoch[114] Batch [4899]	Speed: 550.394654 samples/sec	accuracy=0.672129	lr=0.040015
Epoch[114] Batch [4949]	Speed: 548.861735 samples/sec	accuracy=0.672080	lr=0.040007
Epoch[114] Batch [4999]	Speed: 554.410921 samples/sec	accuracy=0.672040	lr=0.040000
[Epoch 114] training: accuracy=0.672030
[Epoch 114] speed: 547 samples/sec	time cost: 2372.346628
[Epoch 114] validation: err-top1=0.277644 err-top5=0.086318
Epoch[115] Batch [49]	Speed: 552.283430 samples/sec	accuracy=0.692031	lr=0.039991
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Epoch[115] Batch [4999]	Speed: 549.822036 samples/sec	accuracy=0.674096	lr=0.039212
[Epoch 115] training: accuracy=0.674099
[Epoch 115] speed: 547 samples/sec	time cost: 2374.209087
[Epoch 115] validation: err-top1=0.281589 err-top5=0.087811
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[Epoch 116] training: accuracy=0.675503
[Epoch 116] speed: 547 samples/sec	time cost: 2375.535203
[Epoch 116] validation: err-top1=0.276402 err-top5=0.087039
Epoch[117] Batch [49]	Speed: 546.817333 samples/sec	accuracy=0.682734	lr=0.038418
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Epoch[117] Batch [4849]	Speed: 542.805716 samples/sec	accuracy=0.677036	lr=0.037668
Epoch[117] Batch [4899]	Speed: 550.342481 samples/sec	accuracy=0.676982	lr=0.037660
Epoch[117] Batch [4949]	Speed: 549.046052 samples/sec	accuracy=0.676968	lr=0.037652
Epoch[117] Batch [4999]	Speed: 557.695919 samples/sec	accuracy=0.676905	lr=0.037644
[Epoch 117] training: accuracy=0.676894
[Epoch 117] speed: 547 samples/sec	time cost: 2374.635391
[Epoch 117] validation: err-top1=0.275160 err-top5=0.087220
Epoch[118] Batch [49]	Speed: 549.521276 samples/sec	accuracy=0.687891	lr=0.037636
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Epoch[118] Batch [4499]	Speed: 540.444058 samples/sec	accuracy=0.680294	lr=0.036943
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Epoch[118] Batch [4999]	Speed: 555.099876 samples/sec	accuracy=0.679555	lr=0.036865
[Epoch 118] training: accuracy=0.679570
[Epoch 118] speed: 546 samples/sec	time cost: 2377.917050
[Epoch 118] validation: err-top1=0.277623 err-top5=0.086914
Epoch[119] Batch [49]	Speed: 547.375017 samples/sec	accuracy=0.689844	lr=0.036857
Epoch[119] Batch [99]	Speed: 543.154839 samples/sec	accuracy=0.691992	lr=0.036849
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Epoch[119] Batch [3149]	Speed: 533.953438 samples/sec	accuracy=0.683121	lr=0.036376
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Epoch[119] Batch [3399]	Speed: 537.107245 samples/sec	accuracy=0.682673	lr=0.036337
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Epoch[119] Batch [4799]	Speed: 548.534063 samples/sec	accuracy=0.680955	lr=0.036121
Epoch[119] Batch [4849]	Speed: 548.403369 samples/sec	accuracy=0.680904	lr=0.036113
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Epoch[119] Batch [4949]	Speed: 544.036945 samples/sec	accuracy=0.680871	lr=0.036098
Epoch[119] Batch [4999]	Speed: 551.970671 samples/sec	accuracy=0.680809	lr=0.036090
[Epoch 119] training: accuracy=0.680807
[Epoch 119] speed: 547 samples/sec	time cost: 2375.457737
[Epoch 119] validation: err-top1=0.271695 err-top5=0.083253
Epoch[120] Batch [49]	Speed: 547.546726 samples/sec	accuracy=0.687187	lr=0.036082
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Epoch[120] Batch [4549]	Speed: 545.607340 samples/sec	accuracy=0.683604	lr=0.035387
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Epoch[120] Batch [4649]	Speed: 553.021553 samples/sec	accuracy=0.683502	lr=0.035372
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Epoch[120] Batch [4749]	Speed: 557.134189 samples/sec	accuracy=0.683405	lr=0.035356
Epoch[120] Batch [4799]	Speed: 553.144073 samples/sec	accuracy=0.683333	lr=0.035349
Epoch[120] Batch [4849]	Speed: 546.721511 samples/sec	accuracy=0.683264	lr=0.035341
Epoch[120] Batch [4899]	Speed: 545.984563 samples/sec	accuracy=0.683194	lr=0.035333
Epoch[120] Batch [4949]	Speed: 542.019879 samples/sec	accuracy=0.683097	lr=0.035326
Epoch[120] Batch [4999]	Speed: 549.900620 samples/sec	accuracy=0.683073	lr=0.035318
[Epoch 120] training: accuracy=0.683069
[Epoch 120] speed: 546 samples/sec	time cost: 2377.547003
[Epoch 120] validation: err-top1=0.273758 err-top5=0.084475
Epoch[121] Batch [49]	Speed: 547.618137 samples/sec	accuracy=0.704063	lr=0.035310
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Epoch[121] Batch [4999]	Speed: 559.064009 samples/sec	accuracy=0.684892	lr=0.034550
[Epoch 121] training: accuracy=0.684878
[Epoch 121] speed: 547 samples/sec	time cost: 2373.947392
[Epoch 121] validation: err-top1=0.269790 err-top5=0.083725
Epoch[122] Batch [49]	Speed: 547.284053 samples/sec	accuracy=0.702734	lr=0.034542
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Epoch[122] Batch [4999]	Speed: 556.249043 samples/sec	accuracy=0.686455	lr=0.033786
[Epoch 122] training: accuracy=0.686435
[Epoch 122] speed: 546 samples/sec	time cost: 2377.212289
[Epoch 122] validation: err-top1=0.268930 err-top5=0.082893
Epoch[123] Batch [49]	Speed: 551.534952 samples/sec	accuracy=0.696250	lr=0.033778
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Epoch[123] Batch [4999]	Speed: 546.773711 samples/sec	accuracy=0.689059	lr=0.033026
[Epoch 123] training: accuracy=0.689033
[Epoch 123] speed: 547 samples/sec	time cost: 2376.184089
[Epoch 123] validation: err-top1=0.271254 err-top5=0.083794
Epoch[124] Batch [49]	Speed: 551.670046 samples/sec	accuracy=0.705937	lr=0.033018
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Epoch[124] Batch [4799]	Speed: 553.722561 samples/sec	accuracy=0.690697	lr=0.032301
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Epoch[124] Batch [4999]	Speed: 557.386237 samples/sec	accuracy=0.690519	lr=0.032271
[Epoch 124] training: accuracy=0.690523
[Epoch 124] speed: 545 samples/sec	time cost: 2382.501393
[Epoch 124] validation: err-top1=0.267299 err-top5=0.081513
Epoch[125] Batch [49]	Speed: 551.481623 samples/sec	accuracy=0.703125	lr=0.032262
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Epoch[125] Batch [4999]	Speed: 548.879478 samples/sec	accuracy=0.692328	lr=0.031520
[Epoch 125] training: accuracy=0.692315
[Epoch 125] speed: 546 samples/sec	time cost: 2378.116749
[Epoch 125] validation: err-top1=0.271254 err-top5=0.082993
Epoch[126] Batch [49]	Speed: 556.377161 samples/sec	accuracy=0.702656	lr=0.031512
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Epoch[126] Batch [4799]	Speed: 548.321241 samples/sec	accuracy=0.694540	lr=0.030803
Epoch[126] Batch [4849]	Speed: 549.565023 samples/sec	accuracy=0.694484	lr=0.030796
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Epoch[126] Batch [4949]	Speed: 552.595515 samples/sec	accuracy=0.694396	lr=0.030781
Epoch[126] Batch [4999]	Speed: 557.896908 samples/sec	accuracy=0.694314	lr=0.030774
[Epoch 126] training: accuracy=0.694320
[Epoch 126] speed: 547 samples/sec	time cost: 2372.199744
[Epoch 126] validation: err-top1=0.265705 err-top5=0.079627
Epoch[127] Batch [49]	Speed: 543.294148 samples/sec	accuracy=0.712656	lr=0.030766
Epoch[127] Batch [99]	Speed: 544.068685 samples/sec	accuracy=0.711523	lr=0.030758
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Epoch[127] Batch [3349]	Speed: 556.062889 samples/sec	accuracy=0.697435	lr=0.030276
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Epoch[127] Batch [3449]	Speed: 551.256428 samples/sec	accuracy=0.697195	lr=0.030262
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Epoch[127] Batch [3649]	Speed: 545.017634 samples/sec	accuracy=0.696982	lr=0.030232
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Epoch[127] Batch [4349]	Speed: 538.759934 samples/sec	accuracy=0.696408	lr=0.030128
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Epoch[127] Batch [4799]	Speed: 552.620138 samples/sec	accuracy=0.695933	lr=0.030062
Epoch[127] Batch [4849]	Speed: 552.480668 samples/sec	accuracy=0.695884	lr=0.030055
Epoch[127] Batch [4899]	Speed: 540.513574 samples/sec	accuracy=0.695839	lr=0.030047
Epoch[127] Batch [4949]	Speed: 555.961732 samples/sec	accuracy=0.695731	lr=0.030040
Epoch[127] Batch [4999]	Speed: 553.307566 samples/sec	accuracy=0.695636	lr=0.030033
[Epoch 127] training: accuracy=0.695646
[Epoch 127] speed: 547 samples/sec	time cost: 2372.329866
[Epoch 127] validation: err-top1=0.266847 err-top5=0.079207
Epoch[128] Batch [49]	Speed: 547.192679 samples/sec	accuracy=0.707109	lr=0.030025
Epoch[128] Batch [99]	Speed: 548.286119 samples/sec	accuracy=0.705234	lr=0.030017
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Epoch[128] Batch [4499]	Speed: 547.584434 samples/sec	accuracy=0.698915	lr=0.029370
Epoch[128] Batch [4549]	Speed: 536.338264 samples/sec	accuracy=0.698859	lr=0.029363
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Epoch[128] Batch [4649]	Speed: 555.758625 samples/sec	accuracy=0.698748	lr=0.029348
Epoch[128] Batch [4699]	Speed: 543.541272 samples/sec	accuracy=0.698728	lr=0.029341
Epoch[128] Batch [4749]	Speed: 544.488491 samples/sec	accuracy=0.698621	lr=0.029333
Epoch[128] Batch [4799]	Speed: 557.348955 samples/sec	accuracy=0.698604	lr=0.029326
Epoch[128] Batch [4849]	Speed: 549.332621 samples/sec	accuracy=0.698552	lr=0.029319
Epoch[128] Batch [4899]	Speed: 537.940699 samples/sec	accuracy=0.698484	lr=0.029311
Epoch[128] Batch [4949]	Speed: 550.929526 samples/sec	accuracy=0.698456	lr=0.029304
Epoch[128] Batch [4999]	Speed: 559.956087 samples/sec	accuracy=0.698502	lr=0.029297
[Epoch 128] training: accuracy=0.698500
[Epoch 128] speed: 547 samples/sec	time cost: 2376.278696
[Epoch 128] validation: err-top1=0.264808 err-top5=0.079500
Epoch[129] Batch [49]	Speed: 553.035783 samples/sec	accuracy=0.708047	lr=0.029289
Epoch[129] Batch [99]	Speed: 550.630400 samples/sec	accuracy=0.706367	lr=0.029281
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Epoch[129] Batch [4999]	Speed: 550.667755 samples/sec	accuracy=0.700496	lr=0.028566
[Epoch 129] training: accuracy=0.700507
[Epoch 129] speed: 547 samples/sec	time cost: 2373.979997
[Epoch 129] validation: err-top1=0.260537 err-top5=0.077704
Epoch[130] Batch [49]	Speed: 545.936932 samples/sec	accuracy=0.706562	lr=0.028558
Epoch[130] Batch [99]	Speed: 553.629984 samples/sec	accuracy=0.709492	lr=0.028551
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Epoch[130] Batch [4699]	Speed: 541.908931 samples/sec	accuracy=0.702601	lr=0.027884
Epoch[130] Batch [4749]	Speed: 541.107786 samples/sec	accuracy=0.702569	lr=0.027877
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Epoch[130] Batch [4849]	Speed: 544.051141 samples/sec	accuracy=0.702451	lr=0.027863
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Epoch[130] Batch [4949]	Speed: 550.324610 samples/sec	accuracy=0.702242	lr=0.027848
Epoch[130] Batch [4999]	Speed: 554.573251 samples/sec	accuracy=0.702220	lr=0.027841
[Epoch 130] training: accuracy=0.702213
[Epoch 130] speed: 547 samples/sec	time cost: 2373.987246
[Epoch 130] validation: err-top1=0.263021 err-top5=0.080288
Epoch[131] Batch [49]	Speed: 542.401454 samples/sec	accuracy=0.711875	lr=0.027833
Epoch[131] Batch [99]	Speed: 549.925731 samples/sec	accuracy=0.710742	lr=0.027826
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Epoch[131] Batch [4999]	Speed: 550.760440 samples/sec	accuracy=0.704176	lr=0.027122
[Epoch 131] training: accuracy=0.704172
[Epoch 131] speed: 546 samples/sec	time cost: 2376.445770
[Epoch 131] validation: err-top1=0.256936 err-top5=0.077308
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Epoch[132] Batch [4999]	Speed: 557.452018 samples/sec	accuracy=0.706267	lr=0.026409
[Epoch 132] training: accuracy=0.706276
[Epoch 132] speed: 546 samples/sec	time cost: 2376.837831
[Epoch 132] validation: err-top1=0.259716 err-top5=0.077584
Epoch[133] Batch [49]	Speed: 544.433143 samples/sec	accuracy=0.723437	lr=0.026401
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Epoch[133] Batch [4999]	Speed: 555.606640 samples/sec	accuracy=0.708804	lr=0.025702
[Epoch 133] training: accuracy=0.708806
[Epoch 133] speed: 546 samples/sec	time cost: 2376.966339
[Epoch 133] validation: err-top1=0.257272 err-top5=0.076603
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Epoch[134] Batch [4649]	Speed: 550.345900 samples/sec	accuracy=0.710806	lr=0.025050
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Epoch[134] Batch [4999]	Speed: 554.976395 samples/sec	accuracy=0.710515	lr=0.025001
[Epoch 134] training: accuracy=0.710517
[Epoch 134] speed: 546 samples/sec	time cost: 2377.756322
[Epoch 134] validation: err-top1=0.262237 err-top5=0.077687
Epoch[135] Batch [49]	Speed: 549.100422 samples/sec	accuracy=0.721641	lr=0.024993
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Epoch[135] Batch [4999]	Speed: 552.548225 samples/sec	accuracy=0.712819	lr=0.024306
[Epoch 135] training: accuracy=0.712811
[Epoch 135] speed: 545 samples/sec	time cost: 2382.288327
[Epoch 135] validation: err-top1=0.257752 err-top5=0.075441
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Epoch[136] Batch [4999]	Speed: 552.607323 samples/sec	accuracy=0.714978	lr=0.023619
[Epoch 136] training: accuracy=0.714977
[Epoch 136] speed: 546 samples/sec	time cost: 2380.662523
[Epoch 136] validation: err-top1=0.252584 err-top5=0.073858
Epoch[137] Batch [49]	Speed: 546.692349 samples/sec	accuracy=0.732344	lr=0.023611
Epoch[137] Batch [99]	Speed: 551.032457 samples/sec	accuracy=0.727305	lr=0.023604
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Epoch[137] Batch [4299]	Speed: 551.653289 samples/sec	accuracy=0.718954	lr=0.023033
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Epoch[137] Batch [4649]	Speed: 545.769609 samples/sec	accuracy=0.718353	lr=0.022985
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Epoch[137] Batch [4749]	Speed: 540.921407 samples/sec	accuracy=0.718173	lr=0.022972
Epoch[137] Batch [4799]	Speed: 550.579386 samples/sec	accuracy=0.718046	lr=0.022965
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Epoch[137] Batch [4949]	Speed: 547.642721 samples/sec	accuracy=0.717932	lr=0.022945
Epoch[137] Batch [4999]	Speed: 558.021071 samples/sec	accuracy=0.717827	lr=0.022938
[Epoch 137] training: accuracy=0.717842
[Epoch 137] speed: 546 samples/sec	time cost: 2378.941476
[Epoch 137] validation: err-top1=0.252551 err-top5=0.073501
Epoch[138] Batch [49]	Speed: 543.680967 samples/sec	accuracy=0.730547	lr=0.022931
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Epoch[138] Batch [3999]	Speed: 554.851760 samples/sec	accuracy=0.720542	lr=0.022398
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Epoch[138] Batch [4749]	Speed: 545.123532 samples/sec	accuracy=0.720008	lr=0.022298
Epoch[138] Batch [4799]	Speed: 543.827135 samples/sec	accuracy=0.719923	lr=0.022291
Epoch[138] Batch [4849]	Speed: 547.104045 samples/sec	accuracy=0.719851	lr=0.022284
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Epoch[138] Batch [4999]	Speed: 546.525092 samples/sec	accuracy=0.719722	lr=0.022264
[Epoch 138] training: accuracy=0.719710
[Epoch 138] speed: 546 samples/sec	time cost: 2377.471730
[Epoch 138] validation: err-top1=0.255509 err-top5=0.074679
Epoch[139] Batch [49]	Speed: 548.880225 samples/sec	accuracy=0.722891	lr=0.022257
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Epoch[139] Batch [4999]	Speed: 553.085738 samples/sec	accuracy=0.722142	lr=0.021597
[Epoch 139] training: accuracy=0.722151
[Epoch 139] speed: 547 samples/sec	time cost: 2372.522573
[Epoch 139] validation: err-top1=0.251482 err-top5=0.073277
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[Epoch 140] training: accuracy=0.724352
[Epoch 140] speed: 545 samples/sec	time cost: 2381.941534
[Epoch 140] validation: err-top1=0.252212 err-top5=0.073621
Epoch[141] Batch [49]	Speed: 544.356897 samples/sec	accuracy=0.736641	lr=0.020931
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Epoch[141] Batch [4999]	Speed: 551.995864 samples/sec	accuracy=0.726847	lr=0.020286
[Epoch 141] training: accuracy=0.726851
[Epoch 141] speed: 546 samples/sec	time cost: 2378.871187
[Epoch 141] validation: err-top1=0.249038 err-top5=0.072075
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[Epoch 142] training: accuracy=0.729349
[Epoch 142] speed: 547 samples/sec	time cost: 2375.184146
[Epoch 142] validation: err-top1=0.247937 err-top5=0.071755
Epoch[143] Batch [49]	Speed: 545.244421 samples/sec	accuracy=0.740781	lr=0.019636
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Epoch[143] Batch [4999]	Speed: 560.002504 samples/sec	accuracy=0.731822	lr=0.019006
[Epoch 143] training: accuracy=0.731798
[Epoch 143] speed: 546 samples/sec	time cost: 2376.849563
[Epoch 143] validation: err-top1=0.248838 err-top5=0.070753
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[Epoch 144] training: accuracy=0.734480
[Epoch 144] speed: 546 samples/sec	time cost: 2376.980585
[Epoch 144] validation: err-top1=0.243084 err-top5=0.070871
Epoch[145] Batch [49]	Speed: 551.230307 samples/sec	accuracy=0.751719	lr=0.018372
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Epoch[145] Batch [4999]	Speed: 552.551443 samples/sec	accuracy=0.737277	lr=0.017759
[Epoch 145] training: accuracy=0.737274
[Epoch 145] speed: 546 samples/sec	time cost: 2378.342483
[Epoch 145] validation: err-top1=0.245633 err-top5=0.069792
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[Epoch 146] training: accuracy=0.739742
[Epoch 146] speed: 546 samples/sec	time cost: 2377.411959
[Epoch 146] validation: err-top1=0.241787 err-top5=0.068550
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Epoch[147] Batch [4999]	Speed: 555.636944 samples/sec	accuracy=0.742648	lr=0.016544
[Epoch 147] training: accuracy=0.742629
[Epoch 147] speed: 546 samples/sec	time cost: 2379.872808
[Epoch 147] validation: err-top1=0.239736 err-top5=0.069416
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Epoch[148] Batch [4999]	Speed: 557.107294 samples/sec	accuracy=0.744960	lr=0.015950
[Epoch 148] training: accuracy=0.744971
[Epoch 148] speed: 547 samples/sec	time cost: 2375.603993
[Epoch 148] validation: err-top1=0.242208 err-top5=0.069111
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Epoch[149] Batch [4349]	Speed: 558.298138 samples/sec	accuracy=0.749224	lr=0.015440
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Epoch[149] Batch [4799]	Speed: 549.520731 samples/sec	accuracy=0.748820	lr=0.015388
Epoch[149] Batch [4849]	Speed: 550.657408 samples/sec	accuracy=0.748780	lr=0.015382
Epoch[149] Batch [4899]	Speed: 536.538301 samples/sec	accuracy=0.748740	lr=0.015376
Epoch[149] Batch [4949]	Speed: 543.831537 samples/sec	accuracy=0.748695	lr=0.015370
Epoch[149] Batch [4999]	Speed: 552.987466 samples/sec	accuracy=0.748700	lr=0.015364
[Epoch 149] training: accuracy=0.748697
[Epoch 149] speed: 547 samples/sec	time cost: 2375.119000
[Epoch 149] validation: err-top1=0.242228 err-top5=0.068149
Epoch[150] Batch [49]	Speed: 548.260749 samples/sec	accuracy=0.757656	lr=0.015358
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Epoch[150] Batch [3849]	Speed: 537.905412 samples/sec	accuracy=0.752353	lr=0.014920
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Epoch[150] Batch [3999]	Speed: 551.871712 samples/sec	accuracy=0.752181	lr=0.014902
Epoch[150] Batch [4049]	Speed: 538.121415 samples/sec	accuracy=0.752112	lr=0.014897
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Epoch[150] Batch [4849]	Speed: 546.612821 samples/sec	accuracy=0.751087	lr=0.014805
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Epoch[150] Batch [4999]	Speed: 552.609285 samples/sec	accuracy=0.750931	lr=0.014788
[Epoch 150] training: accuracy=0.750951
[Epoch 150] speed: 546 samples/sec	time cost: 2378.276482
[Epoch 150] validation: err-top1=0.237484 err-top5=0.067861
Epoch[151] Batch [49]	Speed: 548.196403 samples/sec	accuracy=0.762031	lr=0.014782
Epoch[151] Batch [99]	Speed: 548.535268 samples/sec	accuracy=0.764766	lr=0.014776
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Epoch[151] Batch [4349]	Speed: 543.844538 samples/sec	accuracy=0.754336	lr=0.014294
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Epoch[151] Batch [4499]	Speed: 552.237960 samples/sec	accuracy=0.754022	lr=0.014277
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Epoch[151] Batch [4649]	Speed: 548.378627 samples/sec	accuracy=0.753961	lr=0.014260
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Epoch[151] Batch [4799]	Speed: 539.553545 samples/sec	accuracy=0.753756	lr=0.014243
Epoch[151] Batch [4849]	Speed: 544.421058 samples/sec	accuracy=0.753727	lr=0.014237
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Epoch[151] Batch [4999]	Speed: 558.849368 samples/sec	accuracy=0.753556	lr=0.014221
[Epoch 151] training: accuracy=0.753554
[Epoch 151] speed: 546 samples/sec	time cost: 2376.904721
[Epoch 151] validation: err-top1=0.236619 err-top5=0.066006
Epoch[152] Batch [49]	Speed: 543.076967 samples/sec	accuracy=0.758516	lr=0.014215
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Epoch[152] Batch [4999]	Speed: 553.811096 samples/sec	accuracy=0.756072	lr=0.013663
[Epoch 152] training: accuracy=0.756092
[Epoch 152] speed: 546 samples/sec	time cost: 2376.864405
[Epoch 152] validation: err-top1=0.234275 err-top5=0.064503
Epoch[153] Batch [49]	Speed: 550.716757 samples/sec	accuracy=0.764922	lr=0.013657
Epoch[153] Batch [99]	Speed: 547.619276 samples/sec	accuracy=0.770352	lr=0.013651
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Epoch[153] Batch [4999]	Speed: 549.188850 samples/sec	accuracy=0.759671	lr=0.013114
[Epoch 153] training: accuracy=0.759675
[Epoch 153] speed: 546 samples/sec	time cost: 2378.632770
[Epoch 153] validation: err-top1=0.233638 err-top5=0.064473
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Epoch[154] Batch [4999]	Speed: 551.502635 samples/sec	accuracy=0.762153	lr=0.012575
[Epoch 154] training: accuracy=0.762157
[Epoch 154] speed: 546 samples/sec	time cost: 2379.224327
[Epoch 154] validation: err-top1=0.232732 err-top5=0.064583
Epoch[155] Batch [49]	Speed: 551.554597 samples/sec	accuracy=0.778516	lr=0.012569
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Epoch[155] Batch [4999]	Speed: 543.657839 samples/sec	accuracy=0.765131	lr=0.012046
[Epoch 155] training: accuracy=0.765128
[Epoch 155] speed: 546 samples/sec	time cost: 2377.177143
[Epoch 155] validation: err-top1=0.229026 err-top5=0.062200
Epoch[156] Batch [49]	Speed: 549.653641 samples/sec	accuracy=0.782422	lr=0.012040
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Epoch[156] Batch [4649]	Speed: 535.221504 samples/sec	accuracy=0.769577	lr=0.011562
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Epoch[156] Batch [4749]	Speed: 546.423042 samples/sec	accuracy=0.769479	lr=0.011552
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Epoch[156] Batch [4849]	Speed: 550.482974 samples/sec	accuracy=0.769205	lr=0.011542
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Epoch[156] Batch [4999]	Speed: 550.448032 samples/sec	accuracy=0.769030	lr=0.011526
[Epoch 156] training: accuracy=0.769017
[Epoch 156] speed: 547 samples/sec	time cost: 2374.188636
[Epoch 156] validation: err-top1=0.229871 err-top5=0.062679
Epoch[157] Batch [49]	Speed: 550.707058 samples/sec	accuracy=0.784531	lr=0.011521
Epoch[157] Batch [99]	Speed: 554.039070 samples/sec	accuracy=0.782852	lr=0.011516
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Epoch[157] Batch [4999]	Speed: 555.396162 samples/sec	accuracy=0.770843	lr=0.011017
[Epoch 157] training: accuracy=0.770842
[Epoch 157] speed: 544 samples/sec	time cost: 2388.036816
[Epoch 157] validation: err-top1=0.232292 err-top5=0.063181
Epoch[158] Batch [49]	Speed: 553.664652 samples/sec	accuracy=0.778672	lr=0.011011
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Epoch[158] Batch [4999]	Speed: 557.592800 samples/sec	accuracy=0.774228	lr=0.010517
[Epoch 158] training: accuracy=0.774220
[Epoch 158] speed: 547 samples/sec	time cost: 2373.729151
[Epoch 158] validation: err-top1=0.228786 err-top5=0.061358
Epoch[159] Batch [49]	Speed: 550.256400 samples/sec	accuracy=0.789375	lr=0.010512
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Epoch[159] Batch [4999]	Speed: 552.029845 samples/sec	accuracy=0.778310	lr=0.010028
[Epoch 159] training: accuracy=0.778305
[Epoch 159] speed: 547 samples/sec	time cost: 2376.302907
[Epoch 159] validation: err-top1=0.226182 err-top5=0.062320
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Epoch[160] Batch [4999]	Speed: 555.851771 samples/sec	accuracy=0.781341	lr=0.009550
[Epoch 160] training: accuracy=0.781355
[Epoch 160] speed: 547 samples/sec	time cost: 2374.352159
[Epoch 160] validation: err-top1=0.227101 err-top5=0.060985
Epoch[161] Batch [49]	Speed: 546.591807 samples/sec	accuracy=0.795781	lr=0.009545
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Epoch[161] Batch [4999]	Speed: 554.495381 samples/sec	accuracy=0.784696	lr=0.009081
[Epoch 161] training: accuracy=0.784703
[Epoch 161] speed: 546 samples/sec	time cost: 2377.580735
[Epoch 161] validation: err-top1=0.226743 err-top5=0.060176
Epoch[162] Batch [49]	Speed: 540.900654 samples/sec	accuracy=0.796875	lr=0.009076
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Epoch[162] Batch [4999]	Speed: 554.706656 samples/sec	accuracy=0.788080	lr=0.008624
[Epoch 162] training: accuracy=0.788081
[Epoch 162] speed: 546 samples/sec	time cost: 2378.460592
[Epoch 162] validation: err-top1=0.222336 err-top5=0.060256
Epoch[163] Batch [49]	Speed: 547.994314 samples/sec	accuracy=0.800859	lr=0.008619
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Epoch[163] Batch [4999]	Speed: 559.267110 samples/sec	accuracy=0.791732	lr=0.008177
[Epoch 163] training: accuracy=0.791757
[Epoch 163] speed: 547 samples/sec	time cost: 2373.326621
[Epoch 163] validation: err-top1=0.225626 err-top5=0.060108
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[Epoch 164] training: accuracy=0.794898
[Epoch 164] speed: 546 samples/sec	time cost: 2377.492381
[Epoch 164] validation: err-top1=0.220833 err-top5=0.057772
Epoch[165] Batch [49]	Speed: 542.296409 samples/sec	accuracy=0.804219	lr=0.007736
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Epoch[165] Batch [4999]	Speed: 546.914939 samples/sec	accuracy=0.799584	lr=0.007316
[Epoch 165] training: accuracy=0.799573
[Epoch 165] speed: 546 samples/sec	time cost: 2377.237200
[Epoch 165] validation: err-top1=0.221575 err-top5=0.060397
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Epoch[166] Batch [4999]	Speed: 547.842873 samples/sec	accuracy=0.802186	lr=0.006902
[Epoch 166] training: accuracy=0.802196
[Epoch 166] speed: 546 samples/sec	time cost: 2379.380645
[Epoch 166] validation: err-top1=0.222636 err-top5=0.059371
Epoch[167] Batch [49]	Speed: 540.437611 samples/sec	accuracy=0.809688	lr=0.006898
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Epoch[167] Batch [4899]	Speed: 548.636414 samples/sec	accuracy=0.806181	lr=0.006507
Epoch[167] Batch [4949]	Speed: 550.020821 samples/sec	accuracy=0.806146	lr=0.006503
Epoch[167] Batch [4999]	Speed: 559.349985 samples/sec	accuracy=0.806166	lr=0.006499
[Epoch 167] training: accuracy=0.806159
[Epoch 167] speed: 547 samples/sec	time cost: 2374.782192
[Epoch 167] validation: err-top1=0.219812 err-top5=0.058714
Epoch[168] Batch [49]	Speed: 544.060740 samples/sec	accuracy=0.814844	lr=0.006495
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Epoch[168] Batch [4549]	Speed: 539.129601 samples/sec	accuracy=0.810016	lr=0.006142
Epoch[168] Batch [4599]	Speed: 538.230029 samples/sec	accuracy=0.809980	lr=0.006139
Epoch[168] Batch [4649]	Speed: 543.052759 samples/sec	accuracy=0.809966	lr=0.006135
Epoch[168] Batch [4699]	Speed: 550.405521 samples/sec	accuracy=0.809899	lr=0.006131
Epoch[168] Batch [4749]	Speed: 542.281416 samples/sec	accuracy=0.809757	lr=0.006127
Epoch[168] Batch [4799]	Speed: 541.377075 samples/sec	accuracy=0.809707	lr=0.006123
Epoch[168] Batch [4849]	Speed: 540.536533 samples/sec	accuracy=0.809689	lr=0.006119
Epoch[168] Batch [4899]	Speed: 546.853537 samples/sec	accuracy=0.809696	lr=0.006115
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Epoch[168] Batch [4999]	Speed: 552.813626 samples/sec	accuracy=0.809657	lr=0.006108
[Epoch 168] training: accuracy=0.809665
[Epoch 168] speed: 544 samples/sec	time cost: 2387.565830
[Epoch 168] validation: err-top1=0.217608 err-top5=0.057953
Epoch[169] Batch [49]	Speed: 539.106176 samples/sec	accuracy=0.821406	lr=0.006104
Epoch[169] Batch [99]	Speed: 544.677154 samples/sec	accuracy=0.821484	lr=0.006100
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Epoch[169] Batch [4649]	Speed: 548.977491 samples/sec	accuracy=0.813501	lr=0.005754
Epoch[169] Batch [4699]	Speed: 542.121516 samples/sec	accuracy=0.813484	lr=0.005750
Epoch[169] Batch [4749]	Speed: 544.173613 samples/sec	accuracy=0.813521	lr=0.005746
Epoch[169] Batch [4799]	Speed: 535.940407 samples/sec	accuracy=0.813487	lr=0.005743
Epoch[169] Batch [4849]	Speed: 548.623918 samples/sec	accuracy=0.813465	lr=0.005739
Epoch[169] Batch [4899]	Speed: 541.672536 samples/sec	accuracy=0.813482	lr=0.005735
Epoch[169] Batch [4949]	Speed: 553.813833 samples/sec	accuracy=0.813368	lr=0.005731
Epoch[169] Batch [4999]	Speed: 555.217083 samples/sec	accuracy=0.813277	lr=0.005728
[Epoch 169] training: accuracy=0.813286
[Epoch 169] speed: 546 samples/sec	time cost: 2378.125816
[Epoch 169] validation: err-top1=0.220285 err-top5=0.059291
Epoch[170] Batch [49]	Speed: 542.094655 samples/sec	accuracy=0.822031	lr=0.005724
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Epoch[170] Batch [4499]	Speed: 544.834048 samples/sec	accuracy=0.817789	lr=0.005395
Epoch[170] Batch [4549]	Speed: 558.367206 samples/sec	accuracy=0.817731	lr=0.005392
Epoch[170] Batch [4599]	Speed: 551.592922 samples/sec	accuracy=0.817666	lr=0.005388
Epoch[170] Batch [4649]	Speed: 554.106534 samples/sec	accuracy=0.817577	lr=0.005384
Epoch[170] Batch [4699]	Speed: 549.516406 samples/sec	accuracy=0.817565	lr=0.005381
Epoch[170] Batch [4749]	Speed: 541.291221 samples/sec	accuracy=0.817498	lr=0.005377
Epoch[170] Batch [4799]	Speed: 553.342085 samples/sec	accuracy=0.817498	lr=0.005373
Epoch[170] Batch [4849]	Speed: 549.490809 samples/sec	accuracy=0.817443	lr=0.005370
Epoch[170] Batch [4899]	Speed: 543.689628 samples/sec	accuracy=0.817372	lr=0.005366
Epoch[170] Batch [4949]	Speed: 544.576396 samples/sec	accuracy=0.817342	lr=0.005363
Epoch[170] Batch [4999]	Speed: 548.965326 samples/sec	accuracy=0.817317	lr=0.005359
[Epoch 170] training: accuracy=0.817321
[Epoch 170] speed: 546 samples/sec	time cost: 2376.529342
[Epoch 170] validation: err-top1=0.215705 err-top5=0.056791
Epoch[171] Batch [49]	Speed: 541.027371 samples/sec	accuracy=0.826953	lr=0.005355
Epoch[171] Batch [99]	Speed: 543.566037 samples/sec	accuracy=0.830039	lr=0.005351
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Epoch[171] Batch [4549]	Speed: 548.593219 samples/sec	accuracy=0.821816	lr=0.005034
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Epoch[171] Batch [4799]	Speed: 547.302380 samples/sec	accuracy=0.821606	lr=0.005016
Epoch[171] Batch [4849]	Speed: 539.490505 samples/sec	accuracy=0.821538	lr=0.005012
Epoch[171] Batch [4899]	Speed: 545.344818 samples/sec	accuracy=0.821487	lr=0.005009
Epoch[171] Batch [4949]	Speed: 548.158588 samples/sec	accuracy=0.821450	lr=0.005005
Epoch[171] Batch [4999]	Speed: 543.788109 samples/sec	accuracy=0.821434	lr=0.005002
[Epoch 171] training: accuracy=0.821428
[Epoch 171] speed: 546 samples/sec	time cost: 2378.410222
[Epoch 171] validation: err-top1=0.214904 err-top5=0.057151
Epoch[172] Batch [49]	Speed: 545.040641 samples/sec	accuracy=0.828203	lr=0.004998
Epoch[172] Batch [99]	Speed: 551.477516 samples/sec	accuracy=0.829414	lr=0.004995
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Epoch[172] Batch [4499]	Speed: 554.091814 samples/sec	accuracy=0.825608	lr=0.004691
Epoch[172] Batch [4549]	Speed: 550.440227 samples/sec	accuracy=0.825576	lr=0.004687
Epoch[172] Batch [4599]	Speed: 553.126589 samples/sec	accuracy=0.825521	lr=0.004684
Epoch[172] Batch [4649]	Speed: 542.801825 samples/sec	accuracy=0.825485	lr=0.004680
Epoch[172] Batch [4699]	Speed: 548.798701 samples/sec	accuracy=0.825513	lr=0.004677
Epoch[172] Batch [4749]	Speed: 549.001725 samples/sec	accuracy=0.825426	lr=0.004674
Epoch[172] Batch [4799]	Speed: 549.747004 samples/sec	accuracy=0.825295	lr=0.004670
Epoch[172] Batch [4849]	Speed: 550.670138 samples/sec	accuracy=0.825256	lr=0.004667
Epoch[172] Batch [4899]	Speed: 555.269420 samples/sec	accuracy=0.825239	lr=0.004663
Epoch[172] Batch [4949]	Speed: 554.526778 samples/sec	accuracy=0.825117	lr=0.004660
Epoch[172] Batch [4999]	Speed: 558.233486 samples/sec	accuracy=0.825102	lr=0.004657
[Epoch 172] training: accuracy=0.825109
[Epoch 172] speed: 547 samples/sec	time cost: 2374.757555
[Epoch 172] validation: err-top1=0.216020 err-top5=0.057717
Epoch[173] Batch [49]	Speed: 547.640017 samples/sec	accuracy=0.836484	lr=0.004653
Epoch[173] Batch [99]	Speed: 543.026887 samples/sec	accuracy=0.835859	lr=0.004650
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Epoch[173] Batch [4549]	Speed: 539.574981 samples/sec	accuracy=0.829202	lr=0.004353
Epoch[173] Batch [4599]	Speed: 554.166721 samples/sec	accuracy=0.829138	lr=0.004349
Epoch[173] Batch [4649]	Speed: 547.867305 samples/sec	accuracy=0.829113	lr=0.004346
Epoch[173] Batch [4699]	Speed: 545.193592 samples/sec	accuracy=0.829118	lr=0.004343
Epoch[173] Batch [4749]	Speed: 550.346024 samples/sec	accuracy=0.829123	lr=0.004339
Epoch[173] Batch [4799]	Speed: 552.696213 samples/sec	accuracy=0.829102	lr=0.004336
Epoch[173] Batch [4849]	Speed: 552.112127 samples/sec	accuracy=0.829008	lr=0.004333
Epoch[173] Batch [4899]	Speed: 545.815968 samples/sec	accuracy=0.828971	lr=0.004330
Epoch[173] Batch [4949]	Speed: 552.306651 samples/sec	accuracy=0.828949	lr=0.004326
Epoch[173] Batch [4999]	Speed: 559.577842 samples/sec	accuracy=0.828930	lr=0.004323
[Epoch 173] training: accuracy=0.828943
[Epoch 173] speed: 547 samples/sec	time cost: 2375.868026
[Epoch 173] validation: err-top1=0.213782 err-top5=0.056330
Epoch[174] Batch [49]	Speed: 552.927040 samples/sec	accuracy=0.840938	lr=0.004320
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Epoch[174] Batch [4499]	Speed: 548.466985 samples/sec	accuracy=0.833188	lr=0.004033
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Epoch[174] Batch [4599]	Speed: 548.377176 samples/sec	accuracy=0.833028	lr=0.004027
Epoch[174] Batch [4649]	Speed: 544.113878 samples/sec	accuracy=0.832921	lr=0.004023
Epoch[174] Batch [4699]	Speed: 548.590848 samples/sec	accuracy=0.832866	lr=0.004020
Epoch[174] Batch [4749]	Speed: 546.822190 samples/sec	accuracy=0.832888	lr=0.004017
Epoch[174] Batch [4799]	Speed: 548.368869 samples/sec	accuracy=0.832832	lr=0.004014
Epoch[174] Batch [4849]	Speed: 544.343640 samples/sec	accuracy=0.832749	lr=0.004011
Epoch[174] Batch [4899]	Speed: 545.804776 samples/sec	accuracy=0.832749	lr=0.004008
Epoch[174] Batch [4949]	Speed: 544.268429 samples/sec	accuracy=0.832749	lr=0.004004
Epoch[174] Batch [4999]	Speed: 547.299217 samples/sec	accuracy=0.832735	lr=0.004001
[Epoch 174] training: accuracy=0.832730
[Epoch 174] speed: 546 samples/sec	time cost: 2376.557830
[Epoch 174] validation: err-top1=0.214483 err-top5=0.056631
Epoch[175] Batch [49]	Speed: 550.464083 samples/sec	accuracy=0.845938	lr=0.003998
Epoch[175] Batch [99]	Speed: 547.182991 samples/sec	accuracy=0.842852	lr=0.003995
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Epoch[175] Batch [4649]	Speed: 552.842783 samples/sec	accuracy=0.836238	lr=0.003713
Epoch[175] Batch [4699]	Speed: 539.404928 samples/sec	accuracy=0.836205	lr=0.003710
Epoch[175] Batch [4749]	Speed: 549.357573 samples/sec	accuracy=0.836223	lr=0.003707
Epoch[175] Batch [4799]	Speed: 548.883867 samples/sec	accuracy=0.836187	lr=0.003704
Epoch[175] Batch [4849]	Speed: 543.754843 samples/sec	accuracy=0.836186	lr=0.003701
Epoch[175] Batch [4899]	Speed: 542.652292 samples/sec	accuracy=0.836156	lr=0.003698
Epoch[175] Batch [4949]	Speed: 547.171431 samples/sec	accuracy=0.836050	lr=0.003695
Epoch[175] Batch [4999]	Speed: 555.832406 samples/sec	accuracy=0.835973	lr=0.003692
[Epoch 175] training: accuracy=0.835975
[Epoch 175] speed: 546 samples/sec	time cost: 2376.388563
[Epoch 175] validation: err-top1=0.214503 err-top5=0.057071
Epoch[176] Batch [49]	Speed: 544.979327 samples/sec	accuracy=0.844219	lr=0.003688
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Epoch[176] Batch [4749]	Speed: 552.352877 samples/sec	accuracy=0.840056	lr=0.003408
Epoch[176] Batch [4799]	Speed: 551.599337 samples/sec	accuracy=0.840077	lr=0.003405
Epoch[176] Batch [4849]	Speed: 543.608466 samples/sec	accuracy=0.840051	lr=0.003403
Epoch[176] Batch [4899]	Speed: 548.609504 samples/sec	accuracy=0.840013	lr=0.003400
Epoch[176] Batch [4949]	Speed: 543.926201 samples/sec	accuracy=0.839962	lr=0.003397
Epoch[176] Batch [4999]	Speed: 550.705798 samples/sec	accuracy=0.839983	lr=0.003394
[Epoch 176] training: accuracy=0.839990
[Epoch 176] speed: 547 samples/sec	time cost: 2374.294271
[Epoch 176] validation: err-top1=0.212552 err-top5=0.054289
Epoch[177] Batch [49]	Speed: 543.457371 samples/sec	accuracy=0.847500	lr=0.003391
Epoch[177] Batch [99]	Speed: 548.614325 samples/sec	accuracy=0.848008	lr=0.003388
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Epoch[177] Batch [4749]	Speed: 548.787105 samples/sec	accuracy=0.844369	lr=0.003122
Epoch[177] Batch [4799]	Speed: 540.781002 samples/sec	accuracy=0.844319	lr=0.003119
Epoch[177] Batch [4849]	Speed: 549.070344 samples/sec	accuracy=0.844333	lr=0.003117
Epoch[177] Batch [4899]	Speed: 545.172831 samples/sec	accuracy=0.844266	lr=0.003114
Epoch[177] Batch [4949]	Speed: 552.175284 samples/sec	accuracy=0.844253	lr=0.003111
Epoch[177] Batch [4999]	Speed: 552.475676 samples/sec	accuracy=0.844255	lr=0.003108
[Epoch 177] training: accuracy=0.844275
[Epoch 177] speed: 547 samples/sec	time cost: 2373.571938
[Epoch 177] validation: err-top1=0.213602 err-top5=0.054768
Epoch[178] Batch [49]	Speed: 548.836374 samples/sec	accuracy=0.851875	lr=0.003105
Epoch[178] Batch [99]	Speed: 547.363939 samples/sec	accuracy=0.850977	lr=0.003102
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Epoch[178] Batch [4799]	Speed: 545.556233 samples/sec	accuracy=0.848254	lr=0.002845
Epoch[178] Batch [4849]	Speed: 545.386694 samples/sec	accuracy=0.848215	lr=0.002843
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Epoch[178] Batch [4949]	Speed: 547.197570 samples/sec	accuracy=0.848164	lr=0.002837
Epoch[178] Batch [4999]	Speed: 557.013714 samples/sec	accuracy=0.848108	lr=0.002835
[Epoch 178] training: accuracy=0.848115
[Epoch 178] speed: 546 samples/sec	time cost: 2376.270342
[Epoch 178] validation: err-top1=0.210697 err-top5=0.054187
Epoch[179] Batch [49]	Speed: 548.675658 samples/sec	accuracy=0.853594	lr=0.002832
Epoch[179] Batch [99]	Speed: 555.281394 samples/sec	accuracy=0.853242	lr=0.002829
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Epoch[179] Batch [4949]	Speed: 544.215277 samples/sec	accuracy=0.851406	lr=0.002576
Epoch[179] Batch [4999]	Speed: 555.625656 samples/sec	accuracy=0.851323	lr=0.002573
[Epoch 179] training: accuracy=0.851322
[Epoch 179] speed: 547 samples/sec	time cost: 2374.871087
[Epoch 179] validation: err-top1=0.210778 err-top5=0.055704
Epoch[180] Batch [49]	Speed: 553.463350 samples/sec	accuracy=0.858516	lr=0.002571
Epoch[180] Batch [99]	Speed: 549.285618 samples/sec	accuracy=0.860391	lr=0.002568
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Epoch[180] Batch [4699]	Speed: 552.947615 samples/sec	accuracy=0.855470	lr=0.002339
Epoch[180] Batch [4749]	Speed: 550.169623 samples/sec	accuracy=0.855474	lr=0.002337
Epoch[180] Batch [4799]	Speed: 548.333248 samples/sec	accuracy=0.855432	lr=0.002334
Epoch[180] Batch [4849]	Speed: 540.223414 samples/sec	accuracy=0.855358	lr=0.002332
Epoch[180] Batch [4899]	Speed: 549.055311 samples/sec	accuracy=0.855297	lr=0.002329
Epoch[180] Batch [4949]	Speed: 546.981699 samples/sec	accuracy=0.855277	lr=0.002327
Epoch[180] Batch [4999]	Speed: 555.125756 samples/sec	accuracy=0.855195	lr=0.002324
[Epoch 180] training: accuracy=0.855185
[Epoch 180] speed: 546 samples/sec	time cost: 2378.096817
[Epoch 180] validation: err-top1=0.210196 err-top5=0.054948
Epoch[181] Batch [49]	Speed: 533.671116 samples/sec	accuracy=0.859766	lr=0.002322
Epoch[181] Batch [99]	Speed: 544.654786 samples/sec	accuracy=0.861602	lr=0.002319
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Epoch[181] Batch [4749]	Speed: 550.038476 samples/sec	accuracy=0.859247	lr=0.002099
Epoch[181] Batch [4799]	Speed: 550.508076 samples/sec	accuracy=0.859192	lr=0.002097
Epoch[181] Batch [4849]	Speed: 537.750284 samples/sec	accuracy=0.859158	lr=0.002095
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Epoch[181] Batch [4999]	Speed: 549.874971 samples/sec	accuracy=0.859097	lr=0.002088
[Epoch 181] training: accuracy=0.859103
[Epoch 181] speed: 547 samples/sec	time cost: 2373.051903
[Epoch 181] validation: err-top1=0.209776 err-top5=0.055308
Epoch[182] Batch [49]	Speed: 541.951452 samples/sec	accuracy=0.863359	lr=0.002085
Epoch[182] Batch [99]	Speed: 551.518465 samples/sec	accuracy=0.863516	lr=0.002083
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Epoch[182] Batch [1499]	Speed: 536.945859 samples/sec	accuracy=0.863880	lr=0.002019
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Epoch[182] Batch [4549]	Speed: 554.686987 samples/sec	accuracy=0.862597	lr=0.001883
Epoch[182] Batch [4599]	Speed: 537.304425 samples/sec	accuracy=0.862513	lr=0.001881
Epoch[182] Batch [4649]	Speed: 555.722969 samples/sec	accuracy=0.862513	lr=0.001879
Epoch[182] Batch [4699]	Speed: 551.385348 samples/sec	accuracy=0.862433	lr=0.001877
Epoch[182] Batch [4749]	Speed: 541.175427 samples/sec	accuracy=0.862405	lr=0.001875
Epoch[182] Batch [4799]	Speed: 546.843272 samples/sec	accuracy=0.862313	lr=0.001873
Epoch[182] Batch [4849]	Speed: 553.774759 samples/sec	accuracy=0.862265	lr=0.001870
Epoch[182] Batch [4899]	Speed: 541.320785 samples/sec	accuracy=0.862191	lr=0.001868
Epoch[182] Batch [4949]	Speed: 550.688140 samples/sec	accuracy=0.862158	lr=0.001866
Epoch[182] Batch [4999]	Speed: 554.326201 samples/sec	accuracy=0.862107	lr=0.001864
[Epoch 182] training: accuracy=0.862111
[Epoch 182] speed: 546 samples/sec	time cost: 2376.699819
[Epoch 182] validation: err-top1=0.210220 err-top5=0.052954
Epoch[183] Batch [49]	Speed: 546.429594 samples/sec	accuracy=0.868906	lr=0.001861
Epoch[183] Batch [99]	Speed: 538.621886 samples/sec	accuracy=0.868516	lr=0.001859
Epoch[183] Batch [149]	Speed: 543.776724 samples/sec	accuracy=0.867734	lr=0.001857
Epoch[183] Batch [199]	Speed: 549.704590 samples/sec	accuracy=0.867754	lr=0.001855
Epoch[183] Batch [249]	Speed: 556.472310 samples/sec	accuracy=0.867875	lr=0.001853
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Epoch[183] Batch [399]	Speed: 550.813274 samples/sec	accuracy=0.866943	lr=0.001846
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Epoch[183] Batch [2649]	Speed: 544.432916 samples/sec	accuracy=0.865740	lr=0.001750
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Epoch[183] Batch [4549]	Speed: 546.545071 samples/sec	accuracy=0.865144	lr=0.001671
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Epoch[183] Batch [4749]	Speed: 544.417933 samples/sec	accuracy=0.865014	lr=0.001662
Epoch[183] Batch [4799]	Speed: 548.465085 samples/sec	accuracy=0.865023	lr=0.001660
Epoch[183] Batch [4849]	Speed: 557.103351 samples/sec	accuracy=0.864958	lr=0.001658
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Epoch[183] Batch [4949]	Speed: 543.329893 samples/sec	accuracy=0.864976	lr=0.001654
Epoch[183] Batch [4999]	Speed: 552.617653 samples/sec	accuracy=0.864926	lr=0.001652
[Epoch 183] training: accuracy=0.864928
[Epoch 183] speed: 547 samples/sec	time cost: 2374.081725
[Epoch 183] validation: err-top1=0.207692 err-top5=0.054087
Epoch[184] Batch [49]	Speed: 544.630066 samples/sec	accuracy=0.868828	lr=0.001650
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[Epoch 184] training: accuracy=0.868349
[Epoch 184] speed: 547 samples/sec	time cost: 2373.972683
[Epoch 184] validation: err-top1=0.207372 err-top5=0.053906
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[Epoch 185] training: accuracy=0.871908
[Epoch 185] speed: 547 samples/sec	time cost: 2372.888300
[Epoch 185] validation: err-top1=0.206732 err-top5=0.054269
Epoch[186] Batch [49]	Speed: 541.761578 samples/sec	accuracy=0.876641	lr=0.001265
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[Epoch 186] training: accuracy=0.874359
[Epoch 186] speed: 546 samples/sec	time cost: 2376.388595
[Epoch 186] validation: err-top1=0.206731 err-top5=0.053325
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[Epoch 187] training: accuracy=0.876661
[Epoch 187] speed: 546 samples/sec	time cost: 2377.367065
[Epoch 187] validation: err-top1=0.205308 err-top5=0.053466
Epoch[188] Batch [49]	Speed: 549.686743 samples/sec	accuracy=0.882031	lr=0.000930
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[Epoch 188] training: accuracy=0.878997
[Epoch 188] speed: 548 samples/sec	time cost: 2370.952971
[Epoch 188] validation: err-top1=0.206234 err-top5=0.053731
Epoch[189] Batch [49]	Speed: 555.253708 samples/sec	accuracy=0.883750	lr=0.000782
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[Epoch 189] training: accuracy=0.881286
[Epoch 189] speed: 546 samples/sec	time cost: 2376.735818
[Epoch 189] validation: err-top1=0.205028 err-top5=0.053225
Epoch[190] Batch [49]	Speed: 551.591448 samples/sec	accuracy=0.885078	lr=0.000646
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[Epoch 190] training: accuracy=0.883928
[Epoch 190] speed: 547 samples/sec	time cost: 2373.525652
[Epoch 190] validation: err-top1=0.204968 err-top5=0.053185
Epoch[191] Batch [49]	Speed: 545.388733 samples/sec	accuracy=0.886406	lr=0.000524
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Epoch[191] Batch [4999]	Speed: 554.723122 samples/sec	accuracy=0.885311	lr=0.000415
[Epoch 191] training: accuracy=0.885314
[Epoch 191] speed: 546 samples/sec	time cost: 2377.078911
[Epoch 191] validation: err-top1=0.206310 err-top5=0.053225
Epoch[192] Batch [49]	Speed: 550.839400 samples/sec	accuracy=0.887422	lr=0.000414
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Epoch[192] Batch [1249]	Speed: 547.071894 samples/sec	accuracy=0.887441	lr=0.000389
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Epoch[192] Batch [4599]	Speed: 539.059640 samples/sec	accuracy=0.887078	lr=0.000325
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Epoch[192] Batch [4699]	Speed: 542.844317 samples/sec	accuracy=0.887050	lr=0.000323
Epoch[192] Batch [4749]	Speed: 547.166027 samples/sec	accuracy=0.887033	lr=0.000322
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Epoch[192] Batch [4999]	Speed: 551.016096 samples/sec	accuracy=0.886942	lr=0.000318
[Epoch 192] training: accuracy=0.886935
[Epoch 192] speed: 547 samples/sec	time cost: 2375.413157
[Epoch 192] validation: err-top1=0.205038 err-top5=0.053133
Epoch[193] Batch [49]	Speed: 547.722567 samples/sec	accuracy=0.886719	lr=0.000317
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Epoch[193] Batch [4849]	Speed: 538.807094 samples/sec	accuracy=0.888177	lr=0.000236
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Epoch[193] Batch [4999]	Speed: 552.316492 samples/sec	accuracy=0.888161	lr=0.000233
[Epoch 193] training: accuracy=0.888156
[Epoch 193] speed: 546 samples/sec	time cost: 2376.961111
[Epoch 193] validation: err-top1=0.205369 err-top5=0.053285
Epoch[194] Batch [49]	Speed: 547.782772 samples/sec	accuracy=0.887422	lr=0.000233
Epoch[194] Batch [99]	Speed: 553.517063 samples/sec	accuracy=0.886484	lr=0.000232
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[Epoch 194] training: accuracy=0.888999
[Epoch 194] speed: 548 samples/sec	time cost: 2370.661610
[Epoch 194] validation: err-top1=0.204728 err-top5=0.052384
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[Epoch 195] training: accuracy=0.889769
[Epoch 195] speed: 546 samples/sec	time cost: 2376.929919
[Epoch 195] validation: err-top1=0.204680 err-top5=0.052296
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[Epoch 196] training: accuracy=0.890552
[Epoch 196] speed: 547 samples/sec	time cost: 2373.931185
[Epoch 196] validation: err-top1=0.204607 err-top5=0.052424
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Epoch[197] Batch [4999]	Speed: 558.311915 samples/sec	accuracy=0.890844	lr=0.000026
[Epoch 197] training: accuracy=0.890844
[Epoch 197] speed: 547 samples/sec	time cost: 2375.325708
[Epoch 197] validation: err-top1=0.204387 err-top5=0.052384
Epoch[198] Batch [49]	Speed: 551.529519 samples/sec	accuracy=0.888281	lr=0.000026
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[Epoch 198] training: accuracy=0.891138
[Epoch 198] speed: 546 samples/sec	time cost: 2376.656341
[Epoch 198] validation: err-top1=0.205038 err-top5=0.052515
Epoch[199] Batch [49]	Speed: 542.254956 samples/sec	accuracy=0.890234	lr=0.000006
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[Epoch 199] training: accuracy=0.891152
[Epoch 199] speed: 546 samples/sec	time cost: 2376.755307
[Epoch 199] validation: err-top1=0.204547 err-top5=0.052344