Namespace(batch_norm=False, batch_size=64, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float32', hard_weight=0.5, input_size=224, label_smoothing=True, last_gamma=False, log_interval=50, logging_file='mobilenetv2_0.5.log', lr=0.05, 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='mobilenetv2_0.5', momentum=0.9, no_wd=True, num_epochs=150, num_gpus=4, num_workers=32, 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_mobilenetv2_0.5', save_frequency=10, teacher=None, temperature=20, use_gn=False, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=4e-05)
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[Epoch 0] training: accuracy=0.008744
[Epoch 0] speed: 1604 samples/sec	time cost: 812.961638
[Epoch 0] validation: err-top1=0.965641 err-top5=0.888134
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Epoch[1] Batch [4999]	Speed: 1820.932847 samples/sec	accuracy=0.067199	lr=0.019995
[Epoch 1] training: accuracy=0.067240
[Epoch 1] speed: 1751 samples/sec	time cost: 746.162767
[Epoch 1] validation: err-top1=0.868830 err-top5=0.686138
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Epoch[2] Batch [4549]	Speed: 1738.059757 samples/sec	accuracy=0.148238	lr=0.029098
Epoch[2] Batch [4599]	Speed: 1743.296572 samples/sec	accuracy=0.148586	lr=0.029198
Epoch[2] Batch [4649]	Speed: 1759.918252 samples/sec	accuracy=0.148921	lr=0.029298
Epoch[2] Batch [4699]	Speed: 1792.125756 samples/sec	accuracy=0.149294	lr=0.029398
Epoch[2] Batch [4749]	Speed: 1763.013783 samples/sec	accuracy=0.149711	lr=0.029498
Epoch[2] Batch [4799]	Speed: 1727.654875 samples/sec	accuracy=0.150135	lr=0.029598
Epoch[2] Batch [4849]	Speed: 1765.192922 samples/sec	accuracy=0.150586	lr=0.029697
Epoch[2] Batch [4899]	Speed: 1740.314626 samples/sec	accuracy=0.150931	lr=0.029797
Epoch[2] Batch [4949]	Speed: 1752.483591 samples/sec	accuracy=0.151275	lr=0.029897
Epoch[2] Batch [4999]	Speed: 1840.259974 samples/sec	accuracy=0.151618	lr=0.029997
[Epoch 2] training: accuracy=0.151643
[Epoch 2] speed: 1755 samples/sec	time cost: 743.975872
[Epoch 2] validation: err-top1=0.779567 err-top5=0.549038
Epoch[3] Batch [49]	Speed: 1642.755397 samples/sec	accuracy=0.193281	lr=0.030105
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Epoch[3] Batch [4999]	Speed: 1814.712242 samples/sec	accuracy=0.218971	lr=0.039998
[Epoch 3] training: accuracy=0.219018
[Epoch 3] speed: 1756 samples/sec	time cost: 744.071927
[Epoch 3] validation: err-top1=0.706752 err-top5=0.454341
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Epoch[4] Batch [4999]	Speed: 1852.642040 samples/sec	accuracy=0.267955	lr=0.050000
[Epoch 4] training: accuracy=0.267961
[Epoch 4] speed: 1752 samples/sec	time cost: 745.268916
[Epoch 4] validation: err-top1=0.683013 err-top5=0.427925
Epoch[5] Batch [49]	Speed: 1642.041827 samples/sec	accuracy=0.299297	lr=0.050000
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[Epoch 5] training: accuracy=0.308974
[Epoch 5] speed: 1750 samples/sec	time cost: 746.312288
[Epoch 5] validation: err-top1=0.610837 err-top5=0.352544
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[Epoch 6] training: accuracy=0.340859
[Epoch 6] speed: 1747 samples/sec	time cost: 747.215951
[Epoch 6] validation: err-top1=0.596799 err-top5=0.340342
Epoch[7] Batch [49]	Speed: 1647.568572 samples/sec	accuracy=0.356250	lr=0.049976
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Epoch[7] Batch [4999]	Speed: 1843.182352 samples/sec	accuracy=0.363100	lr=0.049947
[Epoch 7] training: accuracy=0.363104
[Epoch 7] speed: 1749 samples/sec	time cost: 746.558507
[Epoch 7] validation: err-top1=0.565725 err-top5=0.309435
Epoch[8] Batch [49]	Speed: 1629.574943 samples/sec	accuracy=0.380078	lr=0.049947
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Epoch[8] Batch [4999]	Speed: 1808.742985 samples/sec	accuracy=0.380706	lr=0.049906
[Epoch 8] training: accuracy=0.380709
[Epoch 8] speed: 1750 samples/sec	time cost: 746.140623
[Epoch 8] validation: err-top1=0.545312 err-top5=0.291286
Epoch[9] Batch [49]	Speed: 1637.973761 samples/sec	accuracy=0.392500	lr=0.049906
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Epoch[9] Batch [4999]	Speed: 1853.451316 samples/sec	accuracy=0.394069	lr=0.049853
[Epoch 9] training: accuracy=0.394064
[Epoch 9] speed: 1758 samples/sec	time cost: 742.835450
[Epoch 9] validation: err-top1=0.543766 err-top5=0.289760
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Epoch[10] Batch [4999]	Speed: 1871.858412 samples/sec	accuracy=0.405321	lr=0.049789
[Epoch 10] training: accuracy=0.405324
[Epoch 10] speed: 1762 samples/sec	time cost: 741.397369
[Epoch 10] validation: err-top1=0.526663 err-top5=0.275501
Epoch[11] Batch [49]	Speed: 1638.252163 samples/sec	accuracy=0.421094	lr=0.049788
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Epoch[11] Batch [4999]	Speed: 1876.636901 samples/sec	accuracy=0.415601	lr=0.049713
[Epoch 11] training: accuracy=0.415595
[Epoch 11] speed: 1760 samples/sec	time cost: 742.368166
[Epoch 11] validation: err-top1=0.517408 err-top5=0.267648
Epoch[12] Batch [49]	Speed: 1629.035136 samples/sec	accuracy=0.425391	lr=0.049712
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Epoch[12] Batch [4999]	Speed: 1862.843216 samples/sec	accuracy=0.423323	lr=0.049625
[Epoch 12] training: accuracy=0.423320
[Epoch 12] speed: 1761 samples/sec	time cost: 741.777001
[Epoch 12] validation: err-top1=0.518375 err-top5=0.266980
Epoch[13] Batch [49]	Speed: 1656.982599 samples/sec	accuracy=0.433281	lr=0.049624
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[Epoch 13] training: accuracy=0.430700
[Epoch 13] speed: 1761 samples/sec	time cost: 741.763699
[Epoch 13] validation: err-top1=0.498397 err-top5=0.248978
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Epoch[14] Batch [4999]	Speed: 1851.815139 samples/sec	accuracy=0.436047	lr=0.049415
[Epoch 14] training: accuracy=0.436031
[Epoch 14] speed: 1758 samples/sec	time cost: 742.744937
[Epoch 14] validation: err-top1=0.502664 err-top5=0.254367
Epoch[15] Batch [49]	Speed: 1638.904505 samples/sec	accuracy=0.447578	lr=0.049414
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Epoch[15] Batch [4999]	Speed: 1887.252579 samples/sec	accuracy=0.442116	lr=0.049293
[Epoch 15] training: accuracy=0.442113
[Epoch 15] speed: 1760 samples/sec	time cost: 741.905269
[Epoch 15] validation: err-top1=0.499058 err-top5=0.250421
Epoch[16] Batch [49]	Speed: 1644.634584 samples/sec	accuracy=0.446719	lr=0.049292
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Epoch[16] Batch [4999]	Speed: 1842.082568 samples/sec	accuracy=0.447258	lr=0.049160
[Epoch 16] training: accuracy=0.447264
[Epoch 16] speed: 1760 samples/sec	time cost: 742.090379
[Epoch 16] validation: err-top1=0.493682 err-top5=0.246014
Epoch[17] Batch [49]	Speed: 1629.043786 samples/sec	accuracy=0.461641	lr=0.049158
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Epoch[17] Batch [3499]	Speed: 1723.422289 samples/sec	accuracy=0.451348	lr=0.049059
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Epoch[17] Batch [4799]	Speed: 1758.251439 samples/sec	accuracy=0.451128	lr=0.049021
Epoch[17] Batch [4849]	Speed: 1745.440548 samples/sec	accuracy=0.451124	lr=0.049019
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Epoch[17] Batch [4999]	Speed: 1858.671842 samples/sec	accuracy=0.450910	lr=0.049015
[Epoch 17] training: accuracy=0.450901
[Epoch 17] speed: 1761 samples/sec	time cost: 741.826542
[Epoch 17] validation: err-top1=0.484215 err-top5=0.238822
Epoch[18] Batch [49]	Speed: 1655.781614 samples/sec	accuracy=0.455859	lr=0.049013
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Epoch[18] Batch [4949]	Speed: 1778.155431 samples/sec	accuracy=0.454856	lr=0.048860
Epoch[18] Batch [4999]	Speed: 1873.779284 samples/sec	accuracy=0.454856	lr=0.048858
[Epoch 18] training: accuracy=0.454868
[Epoch 18] speed: 1760 samples/sec	time cost: 741.889268
[Epoch 18] validation: err-top1=0.481430 err-top5=0.235156
Epoch[19] Batch [49]	Speed: 1624.518665 samples/sec	accuracy=0.467734	lr=0.048857
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Epoch[19] Batch [4999]	Speed: 1852.026779 samples/sec	accuracy=0.458911	lr=0.048691
[Epoch 19] training: accuracy=0.458927
[Epoch 19] speed: 1762 samples/sec	time cost: 741.430261
[Epoch 19] validation: err-top1=0.474709 err-top5=0.232721
Epoch[20] Batch [49]	Speed: 1683.157251 samples/sec	accuracy=0.459531	lr=0.048689
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Epoch[20] Batch [4999]	Speed: 1872.311848 samples/sec	accuracy=0.461791	lr=0.048513
[Epoch 20] training: accuracy=0.461794
[Epoch 20] speed: 1755 samples/sec	time cost: 744.172104
[Epoch 20] validation: err-top1=0.489183 err-top5=0.241426
Epoch[21] Batch [49]	Speed: 1649.500908 samples/sec	accuracy=0.471172	lr=0.048511
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Epoch[21] Batch [4999]	Speed: 1852.611162 samples/sec	accuracy=0.464436	lr=0.048323
[Epoch 21] training: accuracy=0.464424
[Epoch 21] speed: 1756 samples/sec	time cost: 743.837328
[Epoch 21] validation: err-top1=0.495052 err-top5=0.247656
Epoch[22] Batch [49]	Speed: 1644.122921 samples/sec	accuracy=0.466641	lr=0.048321
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Epoch[22] Batch [4849]	Speed: 1758.201862 samples/sec	accuracy=0.467558	lr=0.048129
Epoch[22] Batch [4899]	Speed: 1750.291360 samples/sec	accuracy=0.467490	lr=0.048127
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Epoch[22] Batch [4999]	Speed: 1841.298976 samples/sec	accuracy=0.467485	lr=0.048122
[Epoch 22] training: accuracy=0.467492
[Epoch 22] speed: 1760 samples/sec	time cost: 742.026357
[Epoch 22] validation: err-top1=0.473533 err-top5=0.232342
Epoch[23] Batch [49]	Speed: 1638.670995 samples/sec	accuracy=0.475625	lr=0.048120
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Epoch[23] Batch [4999]	Speed: 1866.299500 samples/sec	accuracy=0.469723	lr=0.047911
[Epoch 23] training: accuracy=0.469734
[Epoch 23] speed: 1762 samples/sec	time cost: 741.455547
[Epoch 23] validation: err-top1=0.471194 err-top5=0.227784
Epoch[24] Batch [49]	Speed: 1644.338547 samples/sec	accuracy=0.468984	lr=0.047909
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Epoch[24] Batch [4849]	Speed: 1769.169822 samples/sec	accuracy=0.472615	lr=0.047696
Epoch[24] Batch [4899]	Speed: 1779.986202 samples/sec	accuracy=0.472598	lr=0.047693
Epoch[24] Batch [4949]	Speed: 1753.991910 samples/sec	accuracy=0.472584	lr=0.047691
Epoch[24] Batch [4999]	Speed: 1777.544205 samples/sec	accuracy=0.472484	lr=0.047689
[Epoch 24] training: accuracy=0.472493
[Epoch 24] speed: 1757 samples/sec	time cost: 743.249617
[Epoch 24] validation: err-top1=0.468229 err-top5=0.224559
Epoch[25] Batch [49]	Speed: 1666.018497 samples/sec	accuracy=0.475938	lr=0.047686
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[Epoch 25] training: accuracy=0.474330
[Epoch 25] speed: 1759 samples/sec	time cost: 742.523745
[Epoch 25] validation: err-top1=0.460639 err-top5=0.221919
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[Epoch 26] training: accuracy=0.475975
[Epoch 26] speed: 1756 samples/sec	time cost: 744.201152
[Epoch 26] validation: err-top1=0.469531 err-top5=0.227344
Epoch[27] Batch [49]	Speed: 1658.801825 samples/sec	accuracy=0.486094	lr=0.047210
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Epoch[27] Batch [4549]	Speed: 1758.320483 samples/sec	accuracy=0.478509	lr=0.046982
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Epoch[27] Batch [4849]	Speed: 1763.869945 samples/sec	accuracy=0.478360	lr=0.046967
Epoch[27] Batch [4899]	Speed: 1771.799386 samples/sec	accuracy=0.478350	lr=0.046964
Epoch[27] Batch [4949]	Speed: 1746.094855 samples/sec	accuracy=0.478343	lr=0.046962
Epoch[27] Batch [4999]	Speed: 1849.823005 samples/sec	accuracy=0.478421	lr=0.046959
[Epoch 27] training: accuracy=0.478420
[Epoch 27] speed: 1755 samples/sec	time cost: 744.126041
[Epoch 27] validation: err-top1=0.455308 err-top5=0.216186
Epoch[28] Batch [49]	Speed: 1659.086276 samples/sec	accuracy=0.492578	lr=0.046956
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Epoch[28] Batch [4749]	Speed: 1774.983895 samples/sec	accuracy=0.480420	lr=0.046708
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Epoch[28] Batch [4849]	Speed: 1768.036146 samples/sec	accuracy=0.480296	lr=0.046703
Epoch[28] Batch [4899]	Speed: 1790.259613 samples/sec	accuracy=0.480251	lr=0.046700
Epoch[28] Batch [4949]	Speed: 1748.448073 samples/sec	accuracy=0.480236	lr=0.046698
Epoch[28] Batch [4999]	Speed: 1842.910351 samples/sec	accuracy=0.480224	lr=0.046695
[Epoch 28] training: accuracy=0.480228
[Epoch 28] speed: 1761 samples/sec	time cost: 741.673523
[Epoch 28] validation: err-top1=0.460878 err-top5=0.219846
Epoch[29] Batch [49]	Speed: 1646.409364 samples/sec	accuracy=0.488750	lr=0.046692
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Epoch[29] Batch [4699]	Speed: 1765.572516 samples/sec	accuracy=0.482116	lr=0.046437
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Epoch[29] Batch [4849]	Speed: 1760.312549 samples/sec	accuracy=0.482067	lr=0.046429
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Epoch[29] Batch [4949]	Speed: 1767.499064 samples/sec	accuracy=0.481936	lr=0.046423
Epoch[29] Batch [4999]	Speed: 1839.103697 samples/sec	accuracy=0.481934	lr=0.046421
[Epoch 29] training: accuracy=0.481929
[Epoch 29] speed: 1761 samples/sec	time cost: 741.803127
[Epoch 29] validation: err-top1=0.458273 err-top5=0.218990
Epoch[30] Batch [49]	Speed: 1669.056381 samples/sec	accuracy=0.478672	lr=0.046418
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Epoch[30] Batch [4649]	Speed: 1751.837692 samples/sec	accuracy=0.484225	lr=0.046157
Epoch[30] Batch [4699]	Speed: 1775.606632 samples/sec	accuracy=0.484205	lr=0.046154
Epoch[30] Batch [4749]	Speed: 1781.013067 samples/sec	accuracy=0.484184	lr=0.046151
Epoch[30] Batch [4799]	Speed: 1767.778769 samples/sec	accuracy=0.484190	lr=0.046148
Epoch[30] Batch [4849]	Speed: 1743.891322 samples/sec	accuracy=0.484220	lr=0.046145
Epoch[30] Batch [4899]	Speed: 1719.523870 samples/sec	accuracy=0.484161	lr=0.046142
Epoch[30] Batch [4949]	Speed: 1788.222281 samples/sec	accuracy=0.484099	lr=0.046139
Epoch[30] Batch [4999]	Speed: 1844.292446 samples/sec	accuracy=0.484082	lr=0.046136
[Epoch 30] training: accuracy=0.484071
[Epoch 30] speed: 1760 samples/sec	time cost: 741.952546
[Epoch 30] validation: err-top1=0.463161 err-top5=0.220252
Epoch[31] Batch [49]	Speed: 1643.535648 samples/sec	accuracy=0.482734	lr=0.046133
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Epoch[31] Batch [4999]	Speed: 1857.958753 samples/sec	accuracy=0.485194	lr=0.045842
[Epoch 31] training: accuracy=0.485203
[Epoch 31] speed: 1755 samples/sec	time cost: 743.732027
[Epoch 31] validation: err-top1=0.454026 err-top5=0.214984
Epoch[32] Batch [49]	Speed: 1640.343402 samples/sec	accuracy=0.497578	lr=0.045839
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Epoch[32] Batch [4999]	Speed: 1851.485416 samples/sec	accuracy=0.486716	lr=0.045538
[Epoch 32] training: accuracy=0.486700
[Epoch 32] speed: 1758 samples/sec	time cost: 743.117056
[Epoch 32] validation: err-top1=0.451830 err-top5=0.213987
Epoch[33] Batch [49]	Speed: 1653.360572 samples/sec	accuracy=0.499688	lr=0.045535
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Epoch[33] Batch [4849]	Speed: 1755.579464 samples/sec	accuracy=0.488297	lr=0.045234
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Epoch[33] Batch [4999]	Speed: 1875.548868 samples/sec	accuracy=0.488297	lr=0.045224
[Epoch 33] training: accuracy=0.488296
[Epoch 33] speed: 1761 samples/sec	time cost: 741.595122
[Epoch 33] validation: err-top1=0.448117 err-top5=0.212580
Epoch[34] Batch [49]	Speed: 1617.027874 samples/sec	accuracy=0.492734	lr=0.045221
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[Epoch 34] training: accuracy=0.490246
[Epoch 34] speed: 1756 samples/sec	time cost: 743.714705
[Epoch 34] validation: err-top1=0.455268 err-top5=0.215405
Epoch[35] Batch [49]	Speed: 1675.119250 samples/sec	accuracy=0.498906	lr=0.044898
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[Epoch 35] training: accuracy=0.491180
[Epoch 35] speed: 1756 samples/sec	time cost: 743.941276
[Epoch 35] validation: err-top1=0.456174 err-top5=0.217016
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[Epoch 36] training: accuracy=0.492784
[Epoch 36] speed: 1759 samples/sec	time cost: 742.293291
[Epoch 36] validation: err-top1=0.444291 err-top5=0.208353
Epoch[37] Batch [49]	Speed: 1648.455539 samples/sec	accuracy=0.500391	lr=0.044223
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Epoch[37] Batch [4999]	Speed: 1837.591674 samples/sec	accuracy=0.494539	lr=0.043876
[Epoch 37] training: accuracy=0.494548
[Epoch 37] speed: 1758 samples/sec	time cost: 743.108847
[Epoch 37] validation: err-top1=0.444591 err-top5=0.206911
Epoch[38] Batch [49]	Speed: 1648.071557 samples/sec	accuracy=0.501016	lr=0.043872
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Epoch[38] Batch [4999]	Speed: 1814.572520 samples/sec	accuracy=0.495457	lr=0.043517
[Epoch 38] training: accuracy=0.495465
[Epoch 38] speed: 1760 samples/sec	time cost: 741.789096
[Epoch 38] validation: err-top1=0.447943 err-top5=0.211057
Epoch[39] Batch [49]	Speed: 1646.215000 samples/sec	accuracy=0.500469	lr=0.043513
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Epoch[39] Batch [4999]	Speed: 1837.080780 samples/sec	accuracy=0.496566	lr=0.043149
[Epoch 39] training: accuracy=0.496544
[Epoch 39] speed: 1760 samples/sec	time cost: 742.260792
[Epoch 39] validation: err-top1=0.443810 err-top5=0.208113
Epoch[40] Batch [49]	Speed: 1636.292365 samples/sec	accuracy=0.505469	lr=0.043144
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[Epoch 40] training: accuracy=0.497964
[Epoch 40] speed: 1759 samples/sec	time cost: 742.350208
[Epoch 40] validation: err-top1=0.444111 err-top5=0.208994
Epoch[41] Batch [49]	Speed: 1638.071866 samples/sec	accuracy=0.505781	lr=0.042768
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[Epoch 41] training: accuracy=0.498633
[Epoch 41] speed: 1760 samples/sec	time cost: 742.048645
[Epoch 41] validation: err-top1=0.440928 err-top5=0.203583
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[Epoch 42] training: accuracy=0.500624
[Epoch 42] speed: 1761 samples/sec	time cost: 741.892322
[Epoch 42] validation: err-top1=0.438502 err-top5=0.204026
Epoch[43] Batch [49]	Speed: 1653.761949 samples/sec	accuracy=0.506484	lr=0.041989
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[Epoch 43] training: accuracy=0.501186
[Epoch 43] speed: 1761 samples/sec	time cost: 741.564524
[Epoch 43] validation: err-top1=0.441546 err-top5=0.208133
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Epoch[44] Batch [4999]	Speed: 1887.692663 samples/sec	accuracy=0.502567	lr=0.041183
[Epoch 44] training: accuracy=0.502581
[Epoch 44] speed: 1760 samples/sec	time cost: 742.428265
[Epoch 44] validation: err-top1=0.438536 err-top5=0.203942
Epoch[45] Batch [49]	Speed: 1658.997480 samples/sec	accuracy=0.514844	lr=0.041178
Epoch[45] Batch [99]	Speed: 1776.754392 samples/sec	accuracy=0.513125	lr=0.041174
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Epoch[45] Batch [2249]	Speed: 1752.371818 samples/sec	accuracy=0.504852	lr=0.040996
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Epoch[45] Batch [3499]	Speed: 1776.331302 samples/sec	accuracy=0.503732	lr=0.040892
Epoch[45] Batch [3549]	Speed: 1752.202928 samples/sec	accuracy=0.503691	lr=0.040888
Epoch[45] Batch [3599]	Speed: 1749.691097 samples/sec	accuracy=0.503717	lr=0.040884
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Epoch[45] Batch [3949]	Speed: 1786.702644 samples/sec	accuracy=0.503838	lr=0.040854
Epoch[45] Batch [3999]	Speed: 1786.706093 samples/sec	accuracy=0.503804	lr=0.040850
Epoch[45] Batch [4049]	Speed: 1745.087485 samples/sec	accuracy=0.503763	lr=0.040846
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Epoch[45] Batch [4449]	Speed: 1756.958794 samples/sec	accuracy=0.503386	lr=0.040812
Epoch[45] Batch [4499]	Speed: 1771.278657 samples/sec	accuracy=0.503348	lr=0.040808
Epoch[45] Batch [4549]	Speed: 1758.434053 samples/sec	accuracy=0.503403	lr=0.040804
Epoch[45] Batch [4599]	Speed: 1750.312930 samples/sec	accuracy=0.503333	lr=0.040800
Epoch[45] Batch [4649]	Speed: 1729.480799 samples/sec	accuracy=0.503295	lr=0.040796
Epoch[45] Batch [4699]	Speed: 1750.746495 samples/sec	accuracy=0.503238	lr=0.040791
Epoch[45] Batch [4749]	Speed: 1751.406958 samples/sec	accuracy=0.503234	lr=0.040787
Epoch[45] Batch [4799]	Speed: 1748.858439 samples/sec	accuracy=0.503222	lr=0.040783
Epoch[45] Batch [4849]	Speed: 1786.731781 samples/sec	accuracy=0.503185	lr=0.040779
Epoch[45] Batch [4899]	Speed: 1788.662259 samples/sec	accuracy=0.503114	lr=0.040775
Epoch[45] Batch [4949]	Speed: 1789.383193 samples/sec	accuracy=0.503119	lr=0.040770
Epoch[45] Batch [4999]	Speed: 1868.156058 samples/sec	accuracy=0.503092	lr=0.040766
[Epoch 45] training: accuracy=0.503071
[Epoch 45] speed: 1765 samples/sec	time cost: 740.009560
[Epoch 45] validation: err-top1=0.431631 err-top5=0.198758
Epoch[46] Batch [49]	Speed: 1680.808247 samples/sec	accuracy=0.511406	lr=0.040762
Epoch[46] Batch [99]	Speed: 1755.034718 samples/sec	accuracy=0.510312	lr=0.040757
Epoch[46] Batch [149]	Speed: 1724.828000 samples/sec	accuracy=0.510729	lr=0.040753
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Epoch[46] Batch [399]	Speed: 1751.820429 samples/sec	accuracy=0.508789	lr=0.040732
Epoch[46] Batch [449]	Speed: 1749.321664 samples/sec	accuracy=0.508672	lr=0.040728
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Epoch[46] Batch [749]	Speed: 1740.356486 samples/sec	accuracy=0.508240	lr=0.040703
Epoch[46] Batch [799]	Speed: 1779.121519 samples/sec	accuracy=0.507817	lr=0.040699
Epoch[46] Batch [849]	Speed: 1771.708932 samples/sec	accuracy=0.507900	lr=0.040694
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Epoch[46] Batch [949]	Speed: 1766.320745 samples/sec	accuracy=0.507800	lr=0.040686
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Epoch[46] Batch [1049]	Speed: 1778.859431 samples/sec	accuracy=0.507954	lr=0.040677
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Epoch[46] Batch [1399]	Speed: 1756.700034 samples/sec	accuracy=0.507380	lr=0.040648
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Epoch[46] Batch [1499]	Speed: 1752.453158 samples/sec	accuracy=0.507391	lr=0.040640
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Epoch[46] Batch [1599]	Speed: 1732.820695 samples/sec	accuracy=0.507578	lr=0.040631
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Epoch[46] Batch [4999]	Speed: 1860.363483 samples/sec	accuracy=0.504938	lr=0.040342
[Epoch 46] training: accuracy=0.504943
[Epoch 46] speed: 1755 samples/sec	time cost: 744.216744
[Epoch 46] validation: err-top1=0.436599 err-top5=0.203125
Epoch[47] Batch [49]	Speed: 1627.313628 samples/sec	accuracy=0.504219	lr=0.040337
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Epoch[47] Batch [4999]	Speed: 1867.924338 samples/sec	accuracy=0.505166	lr=0.039911
[Epoch 47] training: accuracy=0.505151
[Epoch 47] speed: 1758 samples/sec	time cost: 742.893617
[Epoch 47] validation: err-top1=0.440905 err-top5=0.207993
Epoch[48] Batch [49]	Speed: 1645.877169 samples/sec	accuracy=0.518516	lr=0.039906
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Epoch[48] Batch [4999]	Speed: 1812.167190 samples/sec	accuracy=0.506945	lr=0.039473
[Epoch 48] training: accuracy=0.506940
[Epoch 48] speed: 1756 samples/sec	time cost: 743.990399
[Epoch 48] validation: err-top1=0.434371 err-top5=0.199478
Epoch[49] Batch [49]	Speed: 1606.069951 samples/sec	accuracy=0.522500	lr=0.039468
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[Epoch 49] training: accuracy=0.507400
[Epoch 49] speed: 1760 samples/sec	time cost: 742.190467
[Epoch 49] validation: err-top1=0.438201 err-top5=0.202845
Epoch[50] Batch [49]	Speed: 1652.999495 samples/sec	accuracy=0.523281	lr=0.039023
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Epoch[50] Batch [4999]	Speed: 1888.218087 samples/sec	accuracy=0.509418	lr=0.038576
[Epoch 50] training: accuracy=0.509405
[Epoch 50] speed: 1757 samples/sec	time cost: 743.529504
[Epoch 50] validation: err-top1=0.434836 err-top5=0.202684
Epoch[51] Batch [49]	Speed: 1651.719712 samples/sec	accuracy=0.509922	lr=0.038571
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Epoch[51] Batch [4999]	Speed: 1801.474632 samples/sec	accuracy=0.509642	lr=0.038118
[Epoch 51] training: accuracy=0.509629
[Epoch 51] speed: 1755 samples/sec	time cost: 744.472228
[Epoch 51] validation: err-top1=0.428651 err-top5=0.200355
Epoch[52] Batch [49]	Speed: 1650.540550 samples/sec	accuracy=0.521641	lr=0.038113
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Epoch[52] Batch [4999]	Speed: 1794.062158 samples/sec	accuracy=0.510377	lr=0.037654
[Epoch 52] training: accuracy=0.510380
[Epoch 52] speed: 1760 samples/sec	time cost: 742.135897
[Epoch 52] validation: err-top1=0.433934 err-top5=0.200942
Epoch[53] Batch [49]	Speed: 1658.994456 samples/sec	accuracy=0.524375	lr=0.037649
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Epoch[53] Batch [4599]	Speed: 1755.513218 samples/sec	accuracy=0.512003	lr=0.037221
Epoch[53] Batch [4649]	Speed: 1797.356755 samples/sec	accuracy=0.512024	lr=0.037217
Epoch[53] Batch [4699]	Speed: 1742.738093 samples/sec	accuracy=0.512033	lr=0.037212
Epoch[53] Batch [4749]	Speed: 1758.439812 samples/sec	accuracy=0.512104	lr=0.037207
Epoch[53] Batch [4799]	Speed: 1797.676087 samples/sec	accuracy=0.512093	lr=0.037202
Epoch[53] Batch [4849]	Speed: 1738.786928 samples/sec	accuracy=0.512063	lr=0.037198
Epoch[53] Batch [4899]	Speed: 1758.124651 samples/sec	accuracy=0.512056	lr=0.037193
Epoch[53] Batch [4949]	Speed: 1771.282338 samples/sec	accuracy=0.512065	lr=0.037188
Epoch[53] Batch [4999]	Speed: 1798.472746 samples/sec	accuracy=0.512027	lr=0.037183
[Epoch 53] training: accuracy=0.512032
[Epoch 53] speed: 1759 samples/sec	time cost: 742.634931
[Epoch 53] validation: err-top1=0.432292 err-top5=0.200581
Epoch[54] Batch [49]	Speed: 1661.362424 samples/sec	accuracy=0.520625	lr=0.037178
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Epoch[54] Batch [4999]	Speed: 1869.636386 samples/sec	accuracy=0.512931	lr=0.036708
[Epoch 54] training: accuracy=0.512940
[Epoch 54] speed: 1759 samples/sec	time cost: 742.254166
[Epoch 54] validation: err-top1=0.427555 err-top5=0.195851
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Epoch[55] Batch [4649]	Speed: 1745.131957 samples/sec	accuracy=0.513659	lr=0.036260
Epoch[55] Batch [4699]	Speed: 1775.247777 samples/sec	accuracy=0.513617	lr=0.036255
Epoch[55] Batch [4749]	Speed: 1772.606454 samples/sec	accuracy=0.513561	lr=0.036250
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Epoch[55] Batch [4849]	Speed: 1766.986675 samples/sec	accuracy=0.513437	lr=0.036241
Epoch[55] Batch [4899]	Speed: 1766.481615 samples/sec	accuracy=0.513313	lr=0.036236
Epoch[55] Batch [4949]	Speed: 1769.423639 samples/sec	accuracy=0.513264	lr=0.036231
Epoch[55] Batch [4999]	Speed: 1869.450973 samples/sec	accuracy=0.513142	lr=0.036226
[Epoch 55] training: accuracy=0.513134
[Epoch 55] speed: 1758 samples/sec	time cost: 743.092200
[Epoch 55] validation: err-top1=0.421514 err-top5=0.191887
Epoch[56] Batch [49]	Speed: 1639.222112 samples/sec	accuracy=0.515547	lr=0.036221
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Epoch[56] Batch [4999]	Speed: 1857.409290 samples/sec	accuracy=0.515129	lr=0.035740
[Epoch 56] training: accuracy=0.515137
[Epoch 56] speed: 1758 samples/sec	time cost: 743.129518
[Epoch 56] validation: err-top1=0.427825 err-top5=0.195693
Epoch[57] Batch [49]	Speed: 1678.624910 samples/sec	accuracy=0.517422	lr=0.035734
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Epoch[57] Batch [4799]	Speed: 1760.380370 samples/sec	accuracy=0.515763	lr=0.035268
Epoch[57] Batch [4849]	Speed: 1790.364032 samples/sec	accuracy=0.515725	lr=0.035263
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Epoch[57] Batch [4999]	Speed: 1869.949420 samples/sec	accuracy=0.515602	lr=0.035248
[Epoch 57] training: accuracy=0.515616
[Epoch 57] speed: 1760 samples/sec	time cost: 742.249731
[Epoch 57] validation: err-top1=0.435387 err-top5=0.199817
Epoch[58] Batch [49]	Speed: 1647.568421 samples/sec	accuracy=0.516797	lr=0.035243
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Epoch[58] Batch [4999]	Speed: 1876.846313 samples/sec	accuracy=0.516823	lr=0.034751
[Epoch 58] training: accuracy=0.516840
[Epoch 58] speed: 1754 samples/sec	time cost: 744.395590
[Epoch 58] validation: err-top1=0.429647 err-top5=0.193329
Epoch[59] Batch [49]	Speed: 1642.396173 samples/sec	accuracy=0.521719	lr=0.034746
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Epoch[59] Batch [4799]	Speed: 1774.377838 samples/sec	accuracy=0.517310	lr=0.034271
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Epoch[59] Batch [4999]	Speed: 1857.678839 samples/sec	accuracy=0.517260	lr=0.034250
[Epoch 59] training: accuracy=0.517261
[Epoch 59] speed: 1759 samples/sec	time cost: 742.570111
[Epoch 59] validation: err-top1=0.421695 err-top5=0.192989
Epoch[60] Batch [49]	Speed: 1621.591723 samples/sec	accuracy=0.521328	lr=0.034245
Epoch[60] Batch [99]	Speed: 1756.159705 samples/sec	accuracy=0.523008	lr=0.034240
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Epoch[60] Batch [4999]	Speed: 1845.141620 samples/sec	accuracy=0.518383	lr=0.033745
[Epoch 60] training: accuracy=0.518406
[Epoch 60] speed: 1761 samples/sec	time cost: 741.704779
[Epoch 60] validation: err-top1=0.422034 err-top5=0.194196
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Epoch[61] Batch [4999]	Speed: 1868.044838 samples/sec	accuracy=0.518985	lr=0.033236
[Epoch 61] training: accuracy=0.518996
[Epoch 61] speed: 1761 samples/sec	time cost: 741.497429
[Epoch 61] validation: err-top1=0.423758 err-top5=0.193209
Epoch[62] Batch [49]	Speed: 1632.784662 samples/sec	accuracy=0.526328	lr=0.033230
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Epoch[62] Batch [4999]	Speed: 1874.217425 samples/sec	accuracy=0.520152	lr=0.032722
[Epoch 62] training: accuracy=0.520163
[Epoch 62] speed: 1758 samples/sec	time cost: 742.902958
[Epoch 62] validation: err-top1=0.422115 err-top5=0.191727
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Epoch[63] Batch [4999]	Speed: 1885.875921 samples/sec	accuracy=0.521698	lr=0.032205
[Epoch 63] training: accuracy=0.521678
[Epoch 63] speed: 1757 samples/sec	time cost: 743.463064
[Epoch 63] validation: err-top1=0.421034 err-top5=0.190244
Epoch[64] Batch [49]	Speed: 1662.015810 samples/sec	accuracy=0.530234	lr=0.032200
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Epoch[64] Batch [4999]	Speed: 1827.968998 samples/sec	accuracy=0.522932	lr=0.031685
[Epoch 64] training: accuracy=0.522942
[Epoch 64] speed: 1759 samples/sec	time cost: 742.440996
[Epoch 64] validation: err-top1=0.421476 err-top5=0.189991
Epoch[65] Batch [49]	Speed: 1630.311133 samples/sec	accuracy=0.527891	lr=0.031679
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Epoch[65] Batch [4649]	Speed: 1768.819916 samples/sec	accuracy=0.523969	lr=0.031198
Epoch[65] Batch [4699]	Speed: 1785.734960 samples/sec	accuracy=0.524019	lr=0.031193
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Epoch[65] Batch [4849]	Speed: 1752.494174 samples/sec	accuracy=0.524027	lr=0.031177
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Epoch[65] Batch [4999]	Speed: 1902.678016 samples/sec	accuracy=0.524100	lr=0.031161
[Epoch 65] training: accuracy=0.524113
[Epoch 65] speed: 1760 samples/sec	time cost: 742.270871
[Epoch 65] validation: err-top1=0.420212 err-top5=0.189784
Epoch[66] Batch [49]	Speed: 1630.785801 samples/sec	accuracy=0.535078	lr=0.031156
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Epoch[66] Batch [4999]	Speed: 1824.055854 samples/sec	accuracy=0.524730	lr=0.030635
[Epoch 66] training: accuracy=0.524731
[Epoch 66] speed: 1757 samples/sec	time cost: 743.302064
[Epoch 66] validation: err-top1=0.419932 err-top5=0.188622
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Epoch[67] Batch [4999]	Speed: 1907.092096 samples/sec	accuracy=0.525573	lr=0.030106
[Epoch 67] training: accuracy=0.525569
[Epoch 67] speed: 1755 samples/sec	time cost: 744.006080
[Epoch 67] validation: err-top1=0.420679 err-top5=0.191048
Epoch[68] Batch [49]	Speed: 1617.949734 samples/sec	accuracy=0.527734	lr=0.030100
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Epoch[68] Batch [4999]	Speed: 1861.302183 samples/sec	accuracy=0.526354	lr=0.029574
[Epoch 68] training: accuracy=0.526339
[Epoch 68] speed: 1759 samples/sec	time cost: 742.640189
[Epoch 68] validation: err-top1=0.420172 err-top5=0.190405
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Epoch[69] Batch [4849]	Speed: 1743.805054 samples/sec	accuracy=0.527364	lr=0.029057
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Epoch[69] Batch [4949]	Speed: 1740.380351 samples/sec	accuracy=0.527352	lr=0.029046
Epoch[69] Batch [4999]	Speed: 1793.010673 samples/sec	accuracy=0.527319	lr=0.029041
[Epoch 69] training: accuracy=0.527316
[Epoch 69] speed: 1754 samples/sec	time cost: 744.531440
[Epoch 69] validation: err-top1=0.418409 err-top5=0.189744
Epoch[70] Batch [49]	Speed: 1657.143656 samples/sec	accuracy=0.533438	lr=0.029035
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Epoch[70] Batch [4849]	Speed: 1786.309632 samples/sec	accuracy=0.528489	lr=0.028521
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Epoch[70] Batch [4999]	Speed: 1858.144852 samples/sec	accuracy=0.528405	lr=0.028505
[Epoch 70] training: accuracy=0.528401
[Epoch 70] speed: 1761 samples/sec	time cost: 741.420174
[Epoch 70] validation: err-top1=0.414421 err-top5=0.187141
Epoch[71] Batch [49]	Speed: 1648.813722 samples/sec	accuracy=0.535937	lr=0.028499
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Epoch[71] Batch [3649]	Speed: 1740.149236 samples/sec	accuracy=0.529957	lr=0.028113
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Epoch[71] Batch [4749]	Speed: 1761.139687 samples/sec	accuracy=0.529701	lr=0.027995
Epoch[71] Batch [4799]	Speed: 1725.104617 samples/sec	accuracy=0.529695	lr=0.027990
Epoch[71] Batch [4849]	Speed: 1739.830392 samples/sec	accuracy=0.529709	lr=0.027984
Epoch[71] Batch [4899]	Speed: 1724.458909 samples/sec	accuracy=0.529767	lr=0.027979
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Epoch[71] Batch [4999]	Speed: 1857.400422 samples/sec	accuracy=0.529717	lr=0.027968
[Epoch 71] training: accuracy=0.529719
[Epoch 71] speed: 1754 samples/sec	time cost: 744.580140
[Epoch 71] validation: err-top1=0.421474 err-top5=0.190505
Epoch[72] Batch [49]	Speed: 1662.132408 samples/sec	accuracy=0.529297	lr=0.027962
Epoch[72] Batch [99]	Speed: 1756.619047 samples/sec	accuracy=0.533164	lr=0.027957
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Epoch[72] Batch [4999]	Speed: 1849.435948 samples/sec	accuracy=0.530217	lr=0.027430
[Epoch 72] training: accuracy=0.530223
[Epoch 72] speed: 1756 samples/sec	time cost: 743.571718
[Epoch 72] validation: err-top1=0.414603 err-top5=0.185236
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Epoch[73] Batch [4999]	Speed: 1865.279538 samples/sec	accuracy=0.531383	lr=0.026890
[Epoch 73] training: accuracy=0.531377
[Epoch 73] speed: 1758 samples/sec	time cost: 742.825683
[Epoch 73] validation: err-top1=0.413903 err-top5=0.187221
Epoch[74] Batch [49]	Speed: 1656.790639 samples/sec	accuracy=0.541250	lr=0.026884
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Epoch[74] Batch [4999]	Speed: 1849.514251 samples/sec	accuracy=0.532665	lr=0.026349
[Epoch 74] training: accuracy=0.532671
[Epoch 74] speed: 1758 samples/sec	time cost: 742.853756
[Epoch 74] validation: err-top1=0.411659 err-top5=0.185096
Epoch[75] Batch [49]	Speed: 1625.015049 samples/sec	accuracy=0.539141	lr=0.026343
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Epoch[75] Batch [4999]	Speed: 1850.399557 samples/sec	accuracy=0.533200	lr=0.025808
[Epoch 75] training: accuracy=0.533204
[Epoch 75] speed: 1758 samples/sec	time cost: 743.020774
[Epoch 75] validation: err-top1=0.411158 err-top5=0.184435
Epoch[76] Batch [49]	Speed: 1632.240841 samples/sec	accuracy=0.541094	lr=0.025802
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Epoch[76] Batch [4999]	Speed: 1822.613817 samples/sec	accuracy=0.534454	lr=0.025267
[Epoch 76] training: accuracy=0.534470
[Epoch 76] speed: 1756 samples/sec	time cost: 743.726107
[Epoch 76] validation: err-top1=0.406609 err-top5=0.179269
Epoch[77] Batch [49]	Speed: 1662.695251 samples/sec	accuracy=0.537969	lr=0.025261
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Epoch[77] Batch [4999]	Speed: 1863.542401 samples/sec	accuracy=0.535786	lr=0.024725
[Epoch 77] training: accuracy=0.535789
[Epoch 77] speed: 1758 samples/sec	time cost: 742.881065
[Epoch 77] validation: err-top1=0.409956 err-top5=0.182772
Epoch[78] Batch [49]	Speed: 1657.539196 samples/sec	accuracy=0.543750	lr=0.024719
Epoch[78] Batch [99]	Speed: 1750.269619 samples/sec	accuracy=0.544414	lr=0.024714
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Epoch[78] Batch [4849]	Speed: 1760.263664 samples/sec	accuracy=0.536354	lr=0.024200
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Epoch[78] Batch [4999]	Speed: 1878.276774 samples/sec	accuracy=0.536395	lr=0.024183
[Epoch 78] training: accuracy=0.536387
[Epoch 78] speed: 1760 samples/sec	time cost: 742.385360
[Epoch 78] validation: err-top1=0.409535 err-top5=0.182432
Epoch[79] Batch [49]	Speed: 1654.659626 samples/sec	accuracy=0.540703	lr=0.024177
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Epoch[79] Batch [4499]	Speed: 1776.878000 samples/sec	accuracy=0.538497	lr=0.023696
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Epoch[79] Batch [4649]	Speed: 1770.651651 samples/sec	accuracy=0.538483	lr=0.023680
Epoch[79] Batch [4699]	Speed: 1749.491652 samples/sec	accuracy=0.538501	lr=0.023674
Epoch[79] Batch [4749]	Speed: 1780.842510 samples/sec	accuracy=0.538392	lr=0.023669
Epoch[79] Batch [4799]	Speed: 1764.460261 samples/sec	accuracy=0.538355	lr=0.023664
Epoch[79] Batch [4849]	Speed: 1765.113355 samples/sec	accuracy=0.538387	lr=0.023658
Epoch[79] Batch [4899]	Speed: 1790.446429 samples/sec	accuracy=0.538356	lr=0.023653
Epoch[79] Batch [4949]	Speed: 1758.851540 samples/sec	accuracy=0.538371	lr=0.023647
Epoch[79] Batch [4999]	Speed: 1859.289274 samples/sec	accuracy=0.538389	lr=0.023642
[Epoch 79] training: accuracy=0.538369
[Epoch 79] speed: 1762 samples/sec	time cost: 741.191296
[Epoch 79] validation: err-top1=0.407853 err-top5=0.184155
Epoch[80] Batch [49]	Speed: 1658.843751 samples/sec	accuracy=0.544922	lr=0.023636
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Epoch[80] Batch [4699]	Speed: 1772.926595 samples/sec	accuracy=0.539022	lr=0.023134
Epoch[80] Batch [4749]	Speed: 1774.413788 samples/sec	accuracy=0.538971	lr=0.023129
Epoch[80] Batch [4799]	Speed: 1757.945728 samples/sec	accuracy=0.538934	lr=0.023123
Epoch[80] Batch [4849]	Speed: 1736.602688 samples/sec	accuracy=0.538851	lr=0.023118
Epoch[80] Batch [4899]	Speed: 1774.281257 samples/sec	accuracy=0.538775	lr=0.023112
Epoch[80] Batch [4949]	Speed: 1736.941536 samples/sec	accuracy=0.538792	lr=0.023107
Epoch[80] Batch [4999]	Speed: 1885.298702 samples/sec	accuracy=0.538752	lr=0.023102
[Epoch 80] training: accuracy=0.538751
[Epoch 80] speed: 1757 samples/sec	time cost: 743.632648
[Epoch 80] validation: err-top1=0.402663 err-top5=0.181501
Epoch[81] Batch [49]	Speed: 1642.950805 samples/sec	accuracy=0.543906	lr=0.023096
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Epoch[81] Batch [4549]	Speed: 1743.502704 samples/sec	accuracy=0.540211	lr=0.022610
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Epoch[81] Batch [4649]	Speed: 1761.851842 samples/sec	accuracy=0.540117	lr=0.022600
Epoch[81] Batch [4699]	Speed: 1780.645822 samples/sec	accuracy=0.540067	lr=0.022594
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Epoch[81] Batch [4849]	Speed: 1752.400818 samples/sec	accuracy=0.539857	lr=0.022578
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Epoch[81] Batch [4949]	Speed: 1769.533923 samples/sec	accuracy=0.539794	lr=0.022567
Epoch[81] Batch [4999]	Speed: 1892.180578 samples/sec	accuracy=0.539818	lr=0.022562
[Epoch 81] training: accuracy=0.539812
[Epoch 81] speed: 1757 samples/sec	time cost: 743.378728
[Epoch 81] validation: err-top1=0.401402 err-top5=0.177664
Epoch[82] Batch [49]	Speed: 1650.529488 samples/sec	accuracy=0.544609	lr=0.022556
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Epoch[82] Batch [4999]	Speed: 1808.450899 samples/sec	accuracy=0.540775	lr=0.022023
[Epoch 82] training: accuracy=0.540787
[Epoch 82] speed: 1761 samples/sec	time cost: 741.800453
[Epoch 82] validation: err-top1=0.405028 err-top5=0.179327
Epoch[83] Batch [49]	Speed: 1666.289552 samples/sec	accuracy=0.547734	lr=0.022017
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Epoch[83] Batch [4999]	Speed: 1843.569137 samples/sec	accuracy=0.541983	lr=0.021486
[Epoch 83] training: accuracy=0.541991
[Epoch 83] speed: 1756 samples/sec	time cost: 743.691025
[Epoch 83] validation: err-top1=0.405831 err-top5=0.180445
Epoch[84] Batch [49]	Speed: 1667.296464 samples/sec	accuracy=0.548359	lr=0.021480
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Epoch[84] Batch [4999]	Speed: 1835.535179 samples/sec	accuracy=0.543902	lr=0.020951
[Epoch 84] training: accuracy=0.543909
[Epoch 84] speed: 1757 samples/sec	time cost: 743.658251
[Epoch 84] validation: err-top1=0.404147 err-top5=0.178325
Epoch[85] Batch [49]	Speed: 1652.922036 samples/sec	accuracy=0.553125	lr=0.020945
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Epoch[85] Batch [4999]	Speed: 1879.386529 samples/sec	accuracy=0.543887	lr=0.020417
[Epoch 85] training: accuracy=0.543883
[Epoch 85] speed: 1759 samples/sec	time cost: 742.531601
[Epoch 85] validation: err-top1=0.401563 err-top5=0.176422
Epoch[86] Batch [49]	Speed: 1624.874585 samples/sec	accuracy=0.549531	lr=0.020411
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Epoch[86] Batch [4999]	Speed: 1862.272709 samples/sec	accuracy=0.545348	lr=0.019886
[Epoch 86] training: accuracy=0.545342
[Epoch 86] speed: 1756 samples/sec	time cost: 743.659128
[Epoch 86] validation: err-top1=0.403121 err-top5=0.176718
Epoch[87] Batch [49]	Speed: 1637.967264 samples/sec	accuracy=0.548516	lr=0.019880
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Epoch[87] Batch [4999]	Speed: 1821.847253 samples/sec	accuracy=0.546410	lr=0.019357
[Epoch 87] training: accuracy=0.546407
[Epoch 87] speed: 1756 samples/sec	time cost: 743.959425
[Epoch 87] validation: err-top1=0.397456 err-top5=0.174119
Epoch[88] Batch [49]	Speed: 1642.052525 samples/sec	accuracy=0.549063	lr=0.019351
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Epoch[88] Batch [4999]	Speed: 1850.914058 samples/sec	accuracy=0.547687	lr=0.018830
[Epoch 88] training: accuracy=0.547707
[Epoch 88] speed: 1756 samples/sec	time cost: 743.662841
[Epoch 88] validation: err-top1=0.395312 err-top5=0.173958
Epoch[89] Batch [49]	Speed: 1667.603831 samples/sec	accuracy=0.557500	lr=0.018825
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[Epoch 89] training: accuracy=0.548671
[Epoch 89] speed: 1756 samples/sec	time cost: 743.597275
[Epoch 89] validation: err-top1=0.398916 err-top5=0.175482
Epoch[90] Batch [49]	Speed: 1666.478495 samples/sec	accuracy=0.551094	lr=0.018301
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Epoch[90] Batch [4849]	Speed: 1775.080905 samples/sec	accuracy=0.549871	lr=0.017802
Epoch[90] Batch [4899]	Speed: 1764.658261 samples/sec	accuracy=0.549794	lr=0.017797
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Epoch[90] Batch [4999]	Speed: 1843.992439 samples/sec	accuracy=0.549895	lr=0.017787
[Epoch 90] training: accuracy=0.549877
[Epoch 90] speed: 1757 samples/sec	time cost: 743.605039
[Epoch 90] validation: err-top1=0.397456 err-top5=0.173998
Epoch[91] Batch [49]	Speed: 1652.545178 samples/sec	accuracy=0.551406	lr=0.017781
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Epoch[91] Batch [4799]	Speed: 1791.723358 samples/sec	accuracy=0.551137	lr=0.017290
Epoch[91] Batch [4849]	Speed: 1775.538631 samples/sec	accuracy=0.551110	lr=0.017285
Epoch[91] Batch [4899]	Speed: 1776.194724 samples/sec	accuracy=0.551099	lr=0.017280
Epoch[91] Batch [4949]	Speed: 1788.934814 samples/sec	accuracy=0.551008	lr=0.017275
Epoch[91] Batch [4999]	Speed: 1896.321548 samples/sec	accuracy=0.551020	lr=0.017270
[Epoch 91] training: accuracy=0.551011
[Epoch 91] speed: 1760 samples/sec	time cost: 742.153369
[Epoch 91] validation: err-top1=0.397095 err-top5=0.174179
Epoch[92] Batch [49]	Speed: 1627.043122 samples/sec	accuracy=0.561094	lr=0.017264
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[Epoch 92] training: accuracy=0.551182
[Epoch 92] speed: 1762 samples/sec	time cost: 741.009624
[Epoch 92] validation: err-top1=0.396405 err-top5=0.172812
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[Epoch 93] training: accuracy=0.553167
[Epoch 93] speed: 1761 samples/sec	time cost: 741.664784
[Epoch 93] validation: err-top1=0.397055 err-top5=0.173357
Epoch[94] Batch [49]	Speed: 1666.391750 samples/sec	accuracy=0.560000	lr=0.016241
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[Epoch 94] training: accuracy=0.553576
[Epoch 94] speed: 1758 samples/sec	time cost: 742.785847
[Epoch 94] validation: err-top1=0.396875 err-top5=0.173898
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[Epoch 95] training: accuracy=0.554310
[Epoch 95] speed: 1759 samples/sec	time cost: 742.399279
[Epoch 95] validation: err-top1=0.395893 err-top5=0.174259
Epoch[96] Batch [49]	Speed: 1644.737268 samples/sec	accuracy=0.554453	lr=0.015235
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Epoch[96] Batch [4999]	Speed: 1831.527749 samples/sec	accuracy=0.555549	lr=0.014744
[Epoch 96] training: accuracy=0.555545
[Epoch 96] speed: 1757 samples/sec	time cost: 743.615390
[Epoch 96] validation: err-top1=0.393375 err-top5=0.171456
Epoch[97] Batch [49]	Speed: 1628.168940 samples/sec	accuracy=0.562109	lr=0.014739
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Epoch[97] Batch [4999]	Speed: 1855.869725 samples/sec	accuracy=0.557944	lr=0.014253
[Epoch 97] training: accuracy=0.557946
[Epoch 97] speed: 1757 samples/sec	time cost: 743.439954
[Epoch 97] validation: err-top1=0.392949 err-top5=0.172015
Epoch[98] Batch [49]	Speed: 1654.860682 samples/sec	accuracy=0.559453	lr=0.014247
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[Epoch 98] training: accuracy=0.558339
[Epoch 98] speed: 1760 samples/sec	time cost: 742.221583
[Epoch 98] validation: err-top1=0.389123 err-top5=0.170813
Epoch[99] Batch [49]	Speed: 1658.703579 samples/sec	accuracy=0.564219	lr=0.013761
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Epoch[99] Batch [4999]	Speed: 1863.462906 samples/sec	accuracy=0.559628	lr=0.013285
[Epoch 99] training: accuracy=0.559605
[Epoch 99] speed: 1759 samples/sec	time cost: 742.503226
[Epoch 99] validation: err-top1=0.389728 err-top5=0.167750
Epoch[100] Batch [49]	Speed: 1629.850744 samples/sec	accuracy=0.566641	lr=0.013280
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Epoch[100] Batch [4999]	Speed: 1846.217062 samples/sec	accuracy=0.560708	lr=0.012809
[Epoch 100] training: accuracy=0.560704
[Epoch 100] speed: 1760 samples/sec	time cost: 742.238276
[Epoch 100] validation: err-top1=0.390244 err-top5=0.167268
Epoch[101] Batch [49]	Speed: 1660.011918 samples/sec	accuracy=0.573906	lr=0.012804
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Epoch[101] Batch [4999]	Speed: 1892.615958 samples/sec	accuracy=0.562372	lr=0.012339
[Epoch 101] training: accuracy=0.562388
[Epoch 101] speed: 1765 samples/sec	time cost: 739.855147
[Epoch 101] validation: err-top1=0.386098 err-top5=0.167408
Epoch[102] Batch [49]	Speed: 1681.060765 samples/sec	accuracy=0.568047	lr=0.012334
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Epoch[102] Batch [4999]	Speed: 1844.926416 samples/sec	accuracy=0.563411	lr=0.011875
[Epoch 102] training: accuracy=0.563415
[Epoch 102] speed: 1755 samples/sec	time cost: 744.219789
[Epoch 102] validation: err-top1=0.385264 err-top5=0.167670
Epoch[103] Batch [49]	Speed: 1664.731234 samples/sec	accuracy=0.572812	lr=0.011870
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Epoch[103] Batch [4999]	Speed: 1845.485582 samples/sec	accuracy=0.564977	lr=0.011417
[Epoch 103] training: accuracy=0.564955
[Epoch 103] speed: 1759 samples/sec	time cost: 742.615685
[Epoch 103] validation: err-top1=0.384635 err-top5=0.168069
Epoch[104] Batch [49]	Speed: 1650.902280 samples/sec	accuracy=0.571953	lr=0.011412
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Epoch[104] Batch [4999]	Speed: 1856.658964 samples/sec	accuracy=0.566077	lr=0.010965
[Epoch 104] training: accuracy=0.566072
[Epoch 104] speed: 1759 samples/sec	time cost: 742.307735
[Epoch 104] validation: err-top1=0.383994 err-top5=0.164964
Epoch[105] Batch [49]	Speed: 1648.380580 samples/sec	accuracy=0.570234	lr=0.010960
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Epoch[105] Batch [4999]	Speed: 1889.518695 samples/sec	accuracy=0.567620	lr=0.010520
[Epoch 105] training: accuracy=0.567634
[Epoch 105] speed: 1763 samples/sec	time cost: 740.632200
[Epoch 105] validation: err-top1=0.385025 err-top5=0.165976
Epoch[106] Batch [49]	Speed: 1653.616878 samples/sec	accuracy=0.576406	lr=0.010516
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Epoch[106] Batch [4999]	Speed: 1840.794792 samples/sec	accuracy=0.568351	lr=0.010082
[Epoch 106] training: accuracy=0.568338
[Epoch 106] speed: 1758 samples/sec	time cost: 742.949257
[Epoch 106] validation: err-top1=0.382752 err-top5=0.165244
Epoch[107] Batch [49]	Speed: 1655.963942 samples/sec	accuracy=0.567344	lr=0.010078
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Epoch[107] Batch [4999]	Speed: 1829.949369 samples/sec	accuracy=0.568829	lr=0.009651
[Epoch 107] training: accuracy=0.568816
[Epoch 107] speed: 1754 samples/sec	time cost: 744.736097
[Epoch 107] validation: err-top1=0.381771 err-top5=0.166106
Epoch[108] Batch [49]	Speed: 1662.652255 samples/sec	accuracy=0.572187	lr=0.009646
Epoch[108] Batch [99]	Speed: 1756.732339 samples/sec	accuracy=0.572734	lr=0.009642
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Epoch[108] Batch [1499]	Speed: 1810.952162 samples/sec	accuracy=0.572430	lr=0.009523
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Epoch[108] Batch [1599]	Speed: 1750.125039 samples/sec	accuracy=0.572249	lr=0.009514
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Epoch[108] Batch [1699]	Speed: 1721.657713 samples/sec	accuracy=0.572178	lr=0.009506
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Epoch[108] Batch [1799]	Speed: 1723.682628 samples/sec	accuracy=0.572131	lr=0.009497
Epoch[108] Batch [1849]	Speed: 1775.266268 samples/sec	accuracy=0.572213	lr=0.009493
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Epoch[108] Batch [2249]	Speed: 1748.388855 samples/sec	accuracy=0.571774	lr=0.009459
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Epoch[108] Batch [2949]	Speed: 1748.907947 samples/sec	accuracy=0.571104	lr=0.009400
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Epoch[108] Batch [3249]	Speed: 1785.730980 samples/sec	accuracy=0.570957	lr=0.009375
Epoch[108] Batch [3299]	Speed: 1772.217980 samples/sec	accuracy=0.570911	lr=0.009370
Epoch[108] Batch [3349]	Speed: 1766.477198 samples/sec	accuracy=0.570954	lr=0.009366
Epoch[108] Batch [3399]	Speed: 1776.131143 samples/sec	accuracy=0.570916	lr=0.009362
Epoch[108] Batch [3449]	Speed: 1781.502115 samples/sec	accuracy=0.570885	lr=0.009358
Epoch[108] Batch [3499]	Speed: 1752.096395 samples/sec	accuracy=0.570911	lr=0.009353
Epoch[108] Batch [3549]	Speed: 1759.673211 samples/sec	accuracy=0.570890	lr=0.009349
Epoch[108] Batch [3599]	Speed: 1778.891083 samples/sec	accuracy=0.570867	lr=0.009345
Epoch[108] Batch [3649]	Speed: 1739.270807 samples/sec	accuracy=0.570879	lr=0.009341
Epoch[108] Batch [3699]	Speed: 1770.620584 samples/sec	accuracy=0.570894	lr=0.009337
Epoch[108] Batch [3749]	Speed: 1744.766091 samples/sec	accuracy=0.570856	lr=0.009332
Epoch[108] Batch [3799]	Speed: 1770.679332 samples/sec	accuracy=0.570810	lr=0.009328
Epoch[108] Batch [3849]	Speed: 1755.590774 samples/sec	accuracy=0.570837	lr=0.009324
Epoch[108] Batch [3899]	Speed: 1754.662280 samples/sec	accuracy=0.570771	lr=0.009320
Epoch[108] Batch [3949]	Speed: 1768.407411 samples/sec	accuracy=0.570728	lr=0.009315
Epoch[108] Batch [3999]	Speed: 1742.246347 samples/sec	accuracy=0.570688	lr=0.009311
Epoch[108] Batch [4049]	Speed: 1734.047080 samples/sec	accuracy=0.570726	lr=0.009307
Epoch[108] Batch [4099]	Speed: 1751.251678 samples/sec	accuracy=0.570731	lr=0.009303
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Epoch[108] Batch [4299]	Speed: 1780.907491 samples/sec	accuracy=0.570680	lr=0.009286
Epoch[108] Batch [4349]	Speed: 1735.798713 samples/sec	accuracy=0.570715	lr=0.009282
Epoch[108] Batch [4399]	Speed: 1718.933459 samples/sec	accuracy=0.570641	lr=0.009278
Epoch[108] Batch [4449]	Speed: 1750.238236 samples/sec	accuracy=0.570585	lr=0.009273
Epoch[108] Batch [4499]	Speed: 1761.131195 samples/sec	accuracy=0.570598	lr=0.009269
Epoch[108] Batch [4549]	Speed: 1763.871394 samples/sec	accuracy=0.570564	lr=0.009265
Epoch[108] Batch [4599]	Speed: 1740.707976 samples/sec	accuracy=0.570557	lr=0.009261
Epoch[108] Batch [4649]	Speed: 1759.293728 samples/sec	accuracy=0.570569	lr=0.009257
Epoch[108] Batch [4699]	Speed: 1754.848508 samples/sec	accuracy=0.570570	lr=0.009252
Epoch[108] Batch [4749]	Speed: 1753.386702 samples/sec	accuracy=0.570648	lr=0.009248
Epoch[108] Batch [4799]	Speed: 1739.902282 samples/sec	accuracy=0.570562	lr=0.009244
Epoch[108] Batch [4849]	Speed: 1747.725204 samples/sec	accuracy=0.570532	lr=0.009240
Epoch[108] Batch [4899]	Speed: 1750.713896 samples/sec	accuracy=0.570440	lr=0.009235
Epoch[108] Batch [4949]	Speed: 1754.142862 samples/sec	accuracy=0.570464	lr=0.009231
Epoch[108] Batch [4999]	Speed: 1906.954584 samples/sec	accuracy=0.570595	lr=0.009227
[Epoch 108] training: accuracy=0.570584
[Epoch 108] speed: 1756 samples/sec	time cost: 743.772165
[Epoch 108] validation: err-top1=0.381397 err-top5=0.165816
Epoch[109] Batch [49]	Speed: 1637.430224 samples/sec	accuracy=0.579922	lr=0.009223
Epoch[109] Batch [99]	Speed: 1802.373467 samples/sec	accuracy=0.578008	lr=0.009218
Epoch[109] Batch [149]	Speed: 1777.129622 samples/sec	accuracy=0.577552	lr=0.009214
Epoch[109] Batch [199]	Speed: 1745.474880 samples/sec	accuracy=0.579512	lr=0.009210
Epoch[109] Batch [249]	Speed: 1757.111465 samples/sec	accuracy=0.578734	lr=0.009206
Epoch[109] Batch [299]	Speed: 1777.940965 samples/sec	accuracy=0.577383	lr=0.009202
Epoch[109] Batch [349]	Speed: 1764.130243 samples/sec	accuracy=0.577400	lr=0.009197
Epoch[109] Batch [399]	Speed: 1747.155924 samples/sec	accuracy=0.576533	lr=0.009193
Epoch[109] Batch [449]	Speed: 1757.639663 samples/sec	accuracy=0.575877	lr=0.009189
Epoch[109] Batch [499]	Speed: 1725.474817 samples/sec	accuracy=0.576523	lr=0.009185
Epoch[109] Batch [549]	Speed: 1762.449139 samples/sec	accuracy=0.576207	lr=0.009181
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Epoch[109] Batch [649]	Speed: 1759.917098 samples/sec	accuracy=0.576106	lr=0.009172
Epoch[109] Batch [699]	Speed: 1746.502981 samples/sec	accuracy=0.575854	lr=0.009168
Epoch[109] Batch [749]	Speed: 1743.236514 samples/sec	accuracy=0.575036	lr=0.009164
Epoch[109] Batch [799]	Speed: 1747.584115 samples/sec	accuracy=0.574922	lr=0.009160
Epoch[109] Batch [849]	Speed: 1743.334330 samples/sec	accuracy=0.574375	lr=0.009155
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Epoch[109] Batch [949]	Speed: 1766.582581 samples/sec	accuracy=0.574696	lr=0.009147
Epoch[109] Batch [999]	Speed: 1757.440760 samples/sec	accuracy=0.574684	lr=0.009143
Epoch[109] Batch [1049]	Speed: 1773.609820 samples/sec	accuracy=0.574669	lr=0.009139
Epoch[109] Batch [1099]	Speed: 1780.943942 samples/sec	accuracy=0.574879	lr=0.009135
Epoch[109] Batch [1149]	Speed: 1775.614031 samples/sec	accuracy=0.574800	lr=0.009130
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Epoch[109] Batch [1299]	Speed: 1771.078934 samples/sec	accuracy=0.574020	lr=0.009118
Epoch[109] Batch [1349]	Speed: 1770.183250 samples/sec	accuracy=0.573747	lr=0.009114
Epoch[109] Batch [1399]	Speed: 1745.344651 samples/sec	accuracy=0.573730	lr=0.009109
Epoch[109] Batch [1449]	Speed: 1717.777707 samples/sec	accuracy=0.573621	lr=0.009105
Epoch[109] Batch [1499]	Speed: 1746.628837 samples/sec	accuracy=0.573862	lr=0.009101
Epoch[109] Batch [1549]	Speed: 1767.859100 samples/sec	accuracy=0.573851	lr=0.009097
Epoch[109] Batch [1599]	Speed: 1751.120357 samples/sec	accuracy=0.573796	lr=0.009093
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Epoch[109] Batch [1699]	Speed: 1763.631740 samples/sec	accuracy=0.574019	lr=0.009084
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Epoch[109] Batch [1799]	Speed: 1729.156105 samples/sec	accuracy=0.574004	lr=0.009076
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Epoch[109] Batch [1899]	Speed: 1765.072211 samples/sec	accuracy=0.573902	lr=0.009068
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Epoch[109] Batch [4999]	Speed: 1835.296486 samples/sec	accuracy=0.571824	lr=0.008811
[Epoch 109] training: accuracy=0.571838
[Epoch 109] speed: 1756 samples/sec	time cost: 743.933473
[Epoch 109] validation: err-top1=0.381070 err-top5=0.162961
Epoch[110] Batch [49]	Speed: 1646.584330 samples/sec	accuracy=0.584141	lr=0.008806
Epoch[110] Batch [99]	Speed: 1773.441205 samples/sec	accuracy=0.580586	lr=0.008802
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Epoch[110] Batch [4549]	Speed: 1746.434123 samples/sec	accuracy=0.573911	lr=0.008438
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Epoch[110] Batch [4649]	Speed: 1768.369025 samples/sec	accuracy=0.573910	lr=0.008430
Epoch[110] Batch [4699]	Speed: 1760.080901 samples/sec	accuracy=0.573799	lr=0.008426
Epoch[110] Batch [4749]	Speed: 1773.594527 samples/sec	accuracy=0.573735	lr=0.008422
Epoch[110] Batch [4799]	Speed: 1767.660614 samples/sec	accuracy=0.573739	lr=0.008418
Epoch[110] Batch [4849]	Speed: 1771.507359 samples/sec	accuracy=0.573667	lr=0.008414
Epoch[110] Batch [4899]	Speed: 1751.111504 samples/sec	accuracy=0.573697	lr=0.008410
Epoch[110] Batch [4949]	Speed: 1766.499634 samples/sec	accuracy=0.573733	lr=0.008406
Epoch[110] Batch [4999]	Speed: 1832.894193 samples/sec	accuracy=0.573655	lr=0.008402
[Epoch 110] training: accuracy=0.573663
[Epoch 110] speed: 1758 samples/sec	time cost: 743.208697
[Epoch 110] validation: err-top1=0.379587 err-top5=0.162720
Epoch[111] Batch [49]	Speed: 1636.269723 samples/sec	accuracy=0.583047	lr=0.008397
Epoch[111] Batch [99]	Speed: 1745.064852 samples/sec	accuracy=0.577969	lr=0.008393
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Epoch[111] Batch [399]	Speed: 1753.008723 samples/sec	accuracy=0.579199	lr=0.008369
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Epoch[111] Batch [4849]	Speed: 1773.837659 samples/sec	accuracy=0.574452	lr=0.008012
Epoch[111] Batch [4899]	Speed: 1762.027456 samples/sec	accuracy=0.574417	lr=0.008008
Epoch[111] Batch [4949]	Speed: 1735.507828 samples/sec	accuracy=0.574471	lr=0.008004
Epoch[111] Batch [4999]	Speed: 1880.262541 samples/sec	accuracy=0.574357	lr=0.008000
[Epoch 111] training: accuracy=0.574348
[Epoch 111] speed: 1759 samples/sec	time cost: 742.320044
[Epoch 111] validation: err-top1=0.377123 err-top5=0.162280
Epoch[112] Batch [49]	Speed: 1622.447795 samples/sec	accuracy=0.572500	lr=0.007996
Epoch[112] Batch [99]	Speed: 1776.875236 samples/sec	accuracy=0.572812	lr=0.007992
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Epoch[112] Batch [4499]	Speed: 1748.584688 samples/sec	accuracy=0.576123	lr=0.007646
Epoch[112] Batch [4549]	Speed: 1779.164795 samples/sec	accuracy=0.576037	lr=0.007642
Epoch[112] Batch [4599]	Speed: 1755.235659 samples/sec	accuracy=0.576033	lr=0.007638
Epoch[112] Batch [4649]	Speed: 1757.225281 samples/sec	accuracy=0.576018	lr=0.007634
Epoch[112] Batch [4699]	Speed: 1755.039021 samples/sec	accuracy=0.575903	lr=0.007631
Epoch[112] Batch [4749]	Speed: 1782.917049 samples/sec	accuracy=0.575911	lr=0.007627
Epoch[112] Batch [4799]	Speed: 1753.774468 samples/sec	accuracy=0.575887	lr=0.007623
Epoch[112] Batch [4849]	Speed: 1747.473649 samples/sec	accuracy=0.575842	lr=0.007619
Epoch[112] Batch [4899]	Speed: 1750.409887 samples/sec	accuracy=0.575853	lr=0.007615
Epoch[112] Batch [4949]	Speed: 1742.899732 samples/sec	accuracy=0.575836	lr=0.007611
Epoch[112] Batch [4999]	Speed: 1855.051478 samples/sec	accuracy=0.575816	lr=0.007607
[Epoch 112] training: accuracy=0.575809
[Epoch 112] speed: 1754 samples/sec	time cost: 744.798255
[Epoch 112] validation: err-top1=0.375618 err-top5=0.162030
Epoch[113] Batch [49]	Speed: 1638.676847 samples/sec	accuracy=0.589531	lr=0.007603
Epoch[113] Batch [99]	Speed: 1743.112844 samples/sec	accuracy=0.584141	lr=0.007599
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Epoch[113] Batch [4999]	Speed: 1838.226269 samples/sec	accuracy=0.576890	lr=0.007222
[Epoch 113] training: accuracy=0.576890
[Epoch 113] speed: 1757 samples/sec	time cost: 743.313435
[Epoch 113] validation: err-top1=0.377183 err-top5=0.159736
Epoch[114] Batch [49]	Speed: 1652.755540 samples/sec	accuracy=0.579766	lr=0.007218
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Epoch[114] Batch [4999]	Speed: 1861.238559 samples/sec	accuracy=0.578404	lr=0.006846
[Epoch 114] training: accuracy=0.578380
[Epoch 114] speed: 1758 samples/sec	time cost: 743.112430
[Epoch 114] validation: err-top1=0.377484 err-top5=0.159876
Epoch[115] Batch [49]	Speed: 1637.154847 samples/sec	accuracy=0.586562	lr=0.006841
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Epoch[115] Batch [4999]	Speed: 1865.852473 samples/sec	accuracy=0.579852	lr=0.006477
[Epoch 115] training: accuracy=0.579860
[Epoch 115] speed: 1755 samples/sec	time cost: 744.379250
[Epoch 115] validation: err-top1=0.375897 err-top5=0.159778
Epoch[116] Batch [49]	Speed: 1634.207406 samples/sec	accuracy=0.577578	lr=0.006473
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Epoch[116] Batch [4999]	Speed: 1868.847787 samples/sec	accuracy=0.580432	lr=0.006118
[Epoch 116] training: accuracy=0.580452
[Epoch 116] speed: 1756 samples/sec	time cost: 743.949952
[Epoch 116] validation: err-top1=0.372456 err-top5=0.160156
Epoch[117] Batch [49]	Speed: 1653.118598 samples/sec	accuracy=0.588203	lr=0.006114
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Epoch[117] Batch [4849]	Speed: 1755.892737 samples/sec	accuracy=0.582575	lr=0.005778
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Epoch[117] Batch [4949]	Speed: 1740.147149 samples/sec	accuracy=0.582509	lr=0.005771
Epoch[117] Batch [4999]	Speed: 1864.831768 samples/sec	accuracy=0.582483	lr=0.005767
[Epoch 117] training: accuracy=0.582473
[Epoch 117] speed: 1753 samples/sec	time cost: 744.877397
[Epoch 117] validation: err-top1=0.369331 err-top5=0.156130
Epoch[118] Batch [49]	Speed: 1657.415771 samples/sec	accuracy=0.586172	lr=0.005764
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Epoch[118] Batch [4999]	Speed: 1880.134929 samples/sec	accuracy=0.584212	lr=0.005426
[Epoch 118] training: accuracy=0.584210
[Epoch 118] speed: 1757 samples/sec	time cost: 743.290039
[Epoch 118] validation: err-top1=0.371851 err-top5=0.158103
Epoch[119] Batch [49]	Speed: 1632.768871 samples/sec	accuracy=0.584375	lr=0.005422
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Epoch[119] Batch [4149]	Speed: 1774.537540 samples/sec	accuracy=0.584951	lr=0.005149
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Epoch[119] Batch [4249]	Speed: 1764.514773 samples/sec	accuracy=0.584951	lr=0.005143
Epoch[119] Batch [4299]	Speed: 1753.555820 samples/sec	accuracy=0.584990	lr=0.005139
Epoch[119] Batch [4349]	Speed: 1790.175980 samples/sec	accuracy=0.584978	lr=0.005136
Epoch[119] Batch [4399]	Speed: 1771.252184 samples/sec	accuracy=0.585021	lr=0.005133
Epoch[119] Batch [4449]	Speed: 1774.354264 samples/sec	accuracy=0.585075	lr=0.005130
Epoch[119] Batch [4499]	Speed: 1756.750676 samples/sec	accuracy=0.585021	lr=0.005126
Epoch[119] Batch [4549]	Speed: 1762.328745 samples/sec	accuracy=0.584922	lr=0.005123
Epoch[119] Batch [4599]	Speed: 1774.222211 samples/sec	accuracy=0.584928	lr=0.005120
Epoch[119] Batch [4649]	Speed: 1741.061019 samples/sec	accuracy=0.584908	lr=0.005116
Epoch[119] Batch [4699]	Speed: 1790.662608 samples/sec	accuracy=0.584881	lr=0.005113
Epoch[119] Batch [4749]	Speed: 1764.668992 samples/sec	accuracy=0.584753	lr=0.005110
Epoch[119] Batch [4799]	Speed: 1758.279425 samples/sec	accuracy=0.584705	lr=0.005107
Epoch[119] Batch [4849]	Speed: 1751.048050 samples/sec	accuracy=0.584661	lr=0.005103
Epoch[119] Batch [4899]	Speed: 1734.641139 samples/sec	accuracy=0.584554	lr=0.005100
Epoch[119] Batch [4949]	Speed: 1751.087344 samples/sec	accuracy=0.584651	lr=0.005097
Epoch[119] Batch [4999]	Speed: 1851.846758 samples/sec	accuracy=0.584621	lr=0.005093
[Epoch 119] training: accuracy=0.584633
[Epoch 119] speed: 1760 samples/sec	time cost: 742.072158
[Epoch 119] validation: err-top1=0.372175 err-top5=0.157592
Epoch[120] Batch [49]	Speed: 1624.358037 samples/sec	accuracy=0.587500	lr=0.005090
Epoch[120] Batch [99]	Speed: 1779.737724 samples/sec	accuracy=0.588281	lr=0.005087
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Epoch[120] Batch [1299]	Speed: 1772.052320 samples/sec	accuracy=0.587620	lr=0.005008
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Epoch[120] Batch [2399]	Speed: 1772.270223 samples/sec	accuracy=0.586875	lr=0.004937
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Epoch[120] Batch [2499]	Speed: 1729.439460 samples/sec	accuracy=0.586950	lr=0.004931
Epoch[120] Batch [2549]	Speed: 1738.413359 samples/sec	accuracy=0.586978	lr=0.004927
Epoch[120] Batch [2599]	Speed: 1723.888797 samples/sec	accuracy=0.587015	lr=0.004924
Epoch[120] Batch [2649]	Speed: 1739.762735 samples/sec	accuracy=0.586972	lr=0.004921
Epoch[120] Batch [2699]	Speed: 1764.431324 samples/sec	accuracy=0.586824	lr=0.004918
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Epoch[120] Batch [2999]	Speed: 1741.304010 samples/sec	accuracy=0.586349	lr=0.004898
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Epoch[120] Batch [3249]	Speed: 1769.191277 samples/sec	accuracy=0.586216	lr=0.004882
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Epoch[120] Batch [3399]	Speed: 1759.388742 samples/sec	accuracy=0.585975	lr=0.004873
Epoch[120] Batch [3449]	Speed: 1726.786734 samples/sec	accuracy=0.585892	lr=0.004869
Epoch[120] Batch [3499]	Speed: 1730.324827 samples/sec	accuracy=0.585888	lr=0.004866
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Epoch[120] Batch [3599]	Speed: 1724.739397 samples/sec	accuracy=0.585826	lr=0.004860
Epoch[120] Batch [3649]	Speed: 1795.972769 samples/sec	accuracy=0.585810	lr=0.004857
Epoch[120] Batch [3699]	Speed: 1768.600239 samples/sec	accuracy=0.585796	lr=0.004853
Epoch[120] Batch [3749]	Speed: 1744.553935 samples/sec	accuracy=0.585788	lr=0.004850
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Epoch[120] Batch [3899]	Speed: 1736.745942 samples/sec	accuracy=0.585646	lr=0.004841
Epoch[120] Batch [3949]	Speed: 1775.660015 samples/sec	accuracy=0.585654	lr=0.004837
Epoch[120] Batch [3999]	Speed: 1793.511366 samples/sec	accuracy=0.585751	lr=0.004834
Epoch[120] Batch [4049]	Speed: 1744.204517 samples/sec	accuracy=0.585743	lr=0.004831
Epoch[120] Batch [4099]	Speed: 1755.080158 samples/sec	accuracy=0.585809	lr=0.004828
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Epoch[120] Batch [4249]	Speed: 1779.062917 samples/sec	accuracy=0.585758	lr=0.004818
Epoch[120] Batch [4299]	Speed: 1731.684683 samples/sec	accuracy=0.585783	lr=0.004815
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Epoch[120] Batch [4399]	Speed: 1778.449124 samples/sec	accuracy=0.585726	lr=0.004809
Epoch[120] Batch [4449]	Speed: 1743.352842 samples/sec	accuracy=0.585706	lr=0.004805
Epoch[120] Batch [4499]	Speed: 1786.081787 samples/sec	accuracy=0.585707	lr=0.004802
Epoch[120] Batch [4549]	Speed: 1724.848171 samples/sec	accuracy=0.585683	lr=0.004799
Epoch[120] Batch [4599]	Speed: 1764.983371 samples/sec	accuracy=0.585696	lr=0.004796
Epoch[120] Batch [4649]	Speed: 1740.225158 samples/sec	accuracy=0.585723	lr=0.004793
Epoch[120] Batch [4699]	Speed: 1755.903592 samples/sec	accuracy=0.585729	lr=0.004790
Epoch[120] Batch [4749]	Speed: 1765.831400 samples/sec	accuracy=0.585715	lr=0.004786
Epoch[120] Batch [4799]	Speed: 1752.100740 samples/sec	accuracy=0.585658	lr=0.004783
Epoch[120] Batch [4849]	Speed: 1784.638216 samples/sec	accuracy=0.585733	lr=0.004780
Epoch[120] Batch [4899]	Speed: 1767.583210 samples/sec	accuracy=0.585699	lr=0.004777
Epoch[120] Batch [4949]	Speed: 1736.551122 samples/sec	accuracy=0.585586	lr=0.004774
Epoch[120] Batch [4999]	Speed: 1847.931956 samples/sec	accuracy=0.585524	lr=0.004770
[Epoch 120] training: accuracy=0.585518
[Epoch 120] speed: 1754 samples/sec	time cost: 744.397252
[Epoch 120] validation: err-top1=0.368650 err-top5=0.155809
Epoch[121] Batch [49]	Speed: 1645.715922 samples/sec	accuracy=0.591406	lr=0.004767
Epoch[121] Batch [99]	Speed: 1770.510515 samples/sec	accuracy=0.587930	lr=0.004764
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Epoch[121] Batch [4999]	Speed: 1826.092655 samples/sec	accuracy=0.586762	lr=0.004457
[Epoch 121] training: accuracy=0.586758
[Epoch 121] speed: 1756 samples/sec	time cost: 743.802030
[Epoch 121] validation: err-top1=0.369559 err-top5=0.157864
Epoch[122] Batch [49]	Speed: 1636.482497 samples/sec	accuracy=0.597266	lr=0.004454
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Epoch[122] Batch [4999]	Speed: 1854.814155 samples/sec	accuracy=0.588529	lr=0.004153
[Epoch 122] training: accuracy=0.588507
[Epoch 122] speed: 1756 samples/sec	time cost: 743.840378
[Epoch 122] validation: err-top1=0.368690 err-top5=0.154788
Epoch[123] Batch [49]	Speed: 1644.604558 samples/sec	accuracy=0.588672	lr=0.004150
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Epoch[123] Batch [4999]	Speed: 1820.836998 samples/sec	accuracy=0.589553	lr=0.003859
[Epoch 123] training: accuracy=0.589521
[Epoch 123] speed: 1754 samples/sec	time cost: 744.721906
[Epoch 123] validation: err-top1=0.367248 err-top5=0.156190
Epoch[124] Batch [49]	Speed: 1657.279932 samples/sec	accuracy=0.598672	lr=0.003856
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[Epoch 124] training: accuracy=0.590108
[Epoch 124] speed: 1755 samples/sec	time cost: 744.287076
[Epoch 124] validation: err-top1=0.367486 err-top5=0.154835
Epoch[125] Batch [49]	Speed: 1628.758375 samples/sec	accuracy=0.599375	lr=0.003572
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Epoch[125] Batch [4999]	Speed: 1816.624268 samples/sec	accuracy=0.592099	lr=0.003301
[Epoch 125] training: accuracy=0.592099
[Epoch 125] speed: 1757 samples/sec	time cost: 743.653467
[Epoch 125] validation: err-top1=0.366847 err-top5=0.153886
Epoch[126] Batch [49]	Speed: 1678.722643 samples/sec	accuracy=0.598672	lr=0.003298
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Epoch[126] Batch [4999]	Speed: 1855.455958 samples/sec	accuracy=0.593016	lr=0.003037
[Epoch 126] training: accuracy=0.593021
[Epoch 126] speed: 1760 samples/sec	time cost: 742.039002
[Epoch 126] validation: err-top1=0.364103 err-top5=0.153385
Epoch[127] Batch [49]	Speed: 1645.926316 samples/sec	accuracy=0.595859	lr=0.003034
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Epoch[127] Batch [3799]	Speed: 1780.702816 samples/sec	accuracy=0.594632	lr=0.002843
Epoch[127] Batch [3849]	Speed: 1763.172603 samples/sec	accuracy=0.594621	lr=0.002841
Epoch[127] Batch [3899]	Speed: 1722.591005 samples/sec	accuracy=0.594538	lr=0.002838
Epoch[127] Batch [3949]	Speed: 1767.775102 samples/sec	accuracy=0.594569	lr=0.002836
Epoch[127] Batch [3999]	Speed: 1780.804409 samples/sec	accuracy=0.594466	lr=0.002833
Epoch[127] Batch [4049]	Speed: 1762.970073 samples/sec	accuracy=0.594433	lr=0.002831
Epoch[127] Batch [4099]	Speed: 1776.639502 samples/sec	accuracy=0.594403	lr=0.002828
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Epoch[127] Batch [4249]	Speed: 1772.406666 samples/sec	accuracy=0.594160	lr=0.002821
Epoch[127] Batch [4299]	Speed: 1762.984141 samples/sec	accuracy=0.594220	lr=0.002818
Epoch[127] Batch [4349]	Speed: 1766.752452 samples/sec	accuracy=0.594187	lr=0.002816
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Epoch[127] Batch [4499]	Speed: 1767.771959 samples/sec	accuracy=0.594191	lr=0.002808
Epoch[127] Batch [4549]	Speed: 1740.118497 samples/sec	accuracy=0.594248	lr=0.002806
Epoch[127] Batch [4599]	Speed: 1791.192826 samples/sec	accuracy=0.594300	lr=0.002803
Epoch[127] Batch [4649]	Speed: 1772.395841 samples/sec	accuracy=0.594253	lr=0.002801
Epoch[127] Batch [4699]	Speed: 1752.178452 samples/sec	accuracy=0.594245	lr=0.002798
Epoch[127] Batch [4749]	Speed: 1751.949682 samples/sec	accuracy=0.594199	lr=0.002796
Epoch[127] Batch [4799]	Speed: 1745.176659 samples/sec	accuracy=0.594188	lr=0.002793
Epoch[127] Batch [4849]	Speed: 1777.474114 samples/sec	accuracy=0.594138	lr=0.002791
Epoch[127] Batch [4899]	Speed: 1748.410549 samples/sec	accuracy=0.594089	lr=0.002788
Epoch[127] Batch [4949]	Speed: 1743.413870 samples/sec	accuracy=0.594044	lr=0.002786
Epoch[127] Batch [4999]	Speed: 1859.160501 samples/sec	accuracy=0.593963	lr=0.002783
[Epoch 127] training: accuracy=0.593958
[Epoch 127] speed: 1757 samples/sec	time cost: 743.283858
[Epoch 127] validation: err-top1=0.364704 err-top5=0.153566
Epoch[128] Batch [49]	Speed: 1649.853208 samples/sec	accuracy=0.605859	lr=0.002781
Epoch[128] Batch [99]	Speed: 1777.643261 samples/sec	accuracy=0.602812	lr=0.002778
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Epoch[128] Batch [1599]	Speed: 1722.222704 samples/sec	accuracy=0.597102	lr=0.002704
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Epoch[128] Batch [1699]	Speed: 1738.564456 samples/sec	accuracy=0.596648	lr=0.002699
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Epoch[128] Batch [2549]	Speed: 1757.582640 samples/sec	accuracy=0.595888	lr=0.002658
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Epoch[128] Batch [2649]	Speed: 1766.676640 samples/sec	accuracy=0.595827	lr=0.002653
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Epoch[128] Batch [3549]	Speed: 1766.276116 samples/sec	accuracy=0.595734	lr=0.002609
Epoch[128] Batch [3599]	Speed: 1780.066938 samples/sec	accuracy=0.595687	lr=0.002607
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Epoch[128] Batch [3749]	Speed: 1754.866577 samples/sec	accuracy=0.595883	lr=0.002600
Epoch[128] Batch [3799]	Speed: 1760.241155 samples/sec	accuracy=0.595834	lr=0.002597
Epoch[128] Batch [3849]	Speed: 1738.067747 samples/sec	accuracy=0.595821	lr=0.002595
Epoch[128] Batch [3899]	Speed: 1757.978539 samples/sec	accuracy=0.595830	lr=0.002593
Epoch[128] Batch [3949]	Speed: 1773.981436 samples/sec	accuracy=0.595862	lr=0.002590
Epoch[128] Batch [3999]	Speed: 1743.108769 samples/sec	accuracy=0.595852	lr=0.002588
Epoch[128] Batch [4049]	Speed: 1736.322596 samples/sec	accuracy=0.595843	lr=0.002585
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Epoch[128] Batch [4149]	Speed: 1753.641795 samples/sec	accuracy=0.595896	lr=0.002581
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Epoch[128] Batch [4249]	Speed: 1763.250547 samples/sec	accuracy=0.595851	lr=0.002576
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Epoch[128] Batch [4399]	Speed: 1772.812434 samples/sec	accuracy=0.595851	lr=0.002569
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Epoch[128] Batch [4499]	Speed: 1764.950994 samples/sec	accuracy=0.595785	lr=0.002564
Epoch[128] Batch [4549]	Speed: 1779.436409 samples/sec	accuracy=0.595853	lr=0.002562
Epoch[128] Batch [4599]	Speed: 1742.540457 samples/sec	accuracy=0.595761	lr=0.002559
Epoch[128] Batch [4649]	Speed: 1763.009383 samples/sec	accuracy=0.595781	lr=0.002557
Epoch[128] Batch [4699]	Speed: 1777.504480 samples/sec	accuracy=0.595862	lr=0.002554
Epoch[128] Batch [4749]	Speed: 1739.224942 samples/sec	accuracy=0.595854	lr=0.002552
Epoch[128] Batch [4799]	Speed: 1736.471926 samples/sec	accuracy=0.595795	lr=0.002550
Epoch[128] Batch [4849]	Speed: 1758.851598 samples/sec	accuracy=0.595798	lr=0.002547
Epoch[128] Batch [4899]	Speed: 1748.899515 samples/sec	accuracy=0.595741	lr=0.002545
Epoch[128] Batch [4949]	Speed: 1737.165953 samples/sec	accuracy=0.595719	lr=0.002542
Epoch[128] Batch [4999]	Speed: 1861.660589 samples/sec	accuracy=0.595670	lr=0.002540
[Epoch 128] training: accuracy=0.595650
[Epoch 128] speed: 1758 samples/sec	time cost: 742.968923
[Epoch 128] validation: err-top1=0.362624 err-top5=0.152065
Epoch[129] Batch [49]	Speed: 1663.197777 samples/sec	accuracy=0.599453	lr=0.002537
Epoch[129] Batch [99]	Speed: 1774.459533 samples/sec	accuracy=0.596719	lr=0.002535
Epoch[129] Batch [149]	Speed: 1731.534053 samples/sec	accuracy=0.597083	lr=0.002533
Epoch[129] Batch [199]	Speed: 1736.823478 samples/sec	accuracy=0.596660	lr=0.002530
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Epoch[129] Batch [399]	Speed: 1764.123229 samples/sec	accuracy=0.596836	lr=0.002521
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Epoch[129] Batch [3999]	Speed: 1751.205922 samples/sec	accuracy=0.595928	lr=0.002353
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Epoch[129] Batch [4549]	Speed: 1712.039267 samples/sec	accuracy=0.595950	lr=0.002328
Epoch[129] Batch [4599]	Speed: 1711.232451 samples/sec	accuracy=0.595913	lr=0.002326
Epoch[129] Batch [4649]	Speed: 1745.142622 samples/sec	accuracy=0.595878	lr=0.002323
Epoch[129] Batch [4699]	Speed: 1754.781571 samples/sec	accuracy=0.595918	lr=0.002321
Epoch[129] Batch [4749]	Speed: 1735.493466 samples/sec	accuracy=0.595848	lr=0.002319
Epoch[129] Batch [4799]	Speed: 1734.723139 samples/sec	accuracy=0.595859	lr=0.002317
Epoch[129] Batch [4849]	Speed: 1790.076597 samples/sec	accuracy=0.595877	lr=0.002314
Epoch[129] Batch [4899]	Speed: 1740.888318 samples/sec	accuracy=0.595830	lr=0.002312
Epoch[129] Batch [4949]	Speed: 1753.915527 samples/sec	accuracy=0.595825	lr=0.002310
Epoch[129] Batch [4999]	Speed: 1852.594541 samples/sec	accuracy=0.595845	lr=0.002307
[Epoch 129] training: accuracy=0.595838
[Epoch 129] speed: 1756 samples/sec	time cost: 743.755375
[Epoch 129] validation: err-top1=0.363161 err-top5=0.152063
Epoch[130] Batch [49]	Speed: 1649.256515 samples/sec	accuracy=0.595313	lr=0.002305
Epoch[130] Batch [99]	Speed: 1758.704386 samples/sec	accuracy=0.600117	lr=0.002303
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Epoch[130] Batch [1749]	Speed: 1742.590738 samples/sec	accuracy=0.596632	lr=0.002228
Epoch[130] Batch [1799]	Speed: 1769.643812 samples/sec	accuracy=0.596782	lr=0.002226
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Epoch[130] Batch [2249]	Speed: 1741.857501 samples/sec	accuracy=0.596981	lr=0.002206
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Epoch[130] Batch [2599]	Speed: 1776.120860 samples/sec	accuracy=0.597018	lr=0.002191
Epoch[130] Batch [2649]	Speed: 1761.222825 samples/sec	accuracy=0.596997	lr=0.002188
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Epoch[130] Batch [3199]	Speed: 1730.051662 samples/sec	accuracy=0.597059	lr=0.002164
Epoch[130] Batch [3249]	Speed: 1743.819328 samples/sec	accuracy=0.597121	lr=0.002162
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Epoch[130] Batch [3349]	Speed: 1754.362860 samples/sec	accuracy=0.597324	lr=0.002157
Epoch[130] Batch [3399]	Speed: 1754.732075 samples/sec	accuracy=0.597243	lr=0.002155
Epoch[130] Batch [3449]	Speed: 1789.877327 samples/sec	accuracy=0.597285	lr=0.002153
Epoch[130] Batch [3499]	Speed: 1768.333611 samples/sec	accuracy=0.597296	lr=0.002151
Epoch[130] Batch [3549]	Speed: 1761.199772 samples/sec	accuracy=0.597279	lr=0.002149
Epoch[130] Batch [3599]	Speed: 1733.163552 samples/sec	accuracy=0.597386	lr=0.002147
Epoch[130] Batch [3649]	Speed: 1768.589519 samples/sec	accuracy=0.597428	lr=0.002144
Epoch[130] Batch [3699]	Speed: 1756.858236 samples/sec	accuracy=0.597340	lr=0.002142
Epoch[130] Batch [3749]	Speed: 1763.446075 samples/sec	accuracy=0.597465	lr=0.002140
Epoch[130] Batch [3799]	Speed: 1763.288711 samples/sec	accuracy=0.597436	lr=0.002138
Epoch[130] Batch [3849]	Speed: 1783.115482 samples/sec	accuracy=0.597447	lr=0.002136
Epoch[130] Batch [3899]	Speed: 1757.942850 samples/sec	accuracy=0.597412	lr=0.002133
Epoch[130] Batch [3949]	Speed: 1759.576667 samples/sec	accuracy=0.597541	lr=0.002131
Epoch[130] Batch [3999]	Speed: 1733.532685 samples/sec	accuracy=0.597508	lr=0.002129
Epoch[130] Batch [4049]	Speed: 1747.645440 samples/sec	accuracy=0.597553	lr=0.002127
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Epoch[130] Batch [4249]	Speed: 1757.212052 samples/sec	accuracy=0.597547	lr=0.002118
Epoch[130] Batch [4299]	Speed: 1754.370600 samples/sec	accuracy=0.597589	lr=0.002116
Epoch[130] Batch [4349]	Speed: 1758.968060 samples/sec	accuracy=0.597581	lr=0.002114
Epoch[130] Batch [4399]	Speed: 1749.764546 samples/sec	accuracy=0.597658	lr=0.002112
Epoch[130] Batch [4449]	Speed: 1785.456254 samples/sec	accuracy=0.597642	lr=0.002109
Epoch[130] Batch [4499]	Speed: 1743.113806 samples/sec	accuracy=0.597593	lr=0.002107
Epoch[130] Batch [4549]	Speed: 1781.461208 samples/sec	accuracy=0.597533	lr=0.002105
Epoch[130] Batch [4599]	Speed: 1739.553541 samples/sec	accuracy=0.597614	lr=0.002103
Epoch[130] Batch [4649]	Speed: 1759.948022 samples/sec	accuracy=0.597619	lr=0.002101
Epoch[130] Batch [4699]	Speed: 1713.016047 samples/sec	accuracy=0.597659	lr=0.002099
Epoch[130] Batch [4749]	Speed: 1779.476929 samples/sec	accuracy=0.597729	lr=0.002096
Epoch[130] Batch [4799]	Speed: 1743.038085 samples/sec	accuracy=0.597672	lr=0.002094
Epoch[130] Batch [4849]	Speed: 1764.179865 samples/sec	accuracy=0.597681	lr=0.002092
Epoch[130] Batch [4899]	Speed: 1760.317398 samples/sec	accuracy=0.597546	lr=0.002090
Epoch[130] Batch [4949]	Speed: 1768.258886 samples/sec	accuracy=0.597543	lr=0.002088
Epoch[130] Batch [4999]	Speed: 1866.062793 samples/sec	accuracy=0.597586	lr=0.002085
[Epoch 130] training: accuracy=0.597605
[Epoch 130] speed: 1756 samples/sec	time cost: 743.690601
[Epoch 130] validation: err-top1=0.362220 err-top5=0.150962
Epoch[131] Batch [49]	Speed: 1648.317319 samples/sec	accuracy=0.591250	lr=0.002083
Epoch[131] Batch [99]	Speed: 1746.575708 samples/sec	accuracy=0.596055	lr=0.002081
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Epoch[131] Batch [249]	Speed: 1743.682720 samples/sec	accuracy=0.600734	lr=0.002074
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Epoch[131] Batch [3599]	Speed: 1784.617868 samples/sec	accuracy=0.598234	lr=0.001932
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Epoch[131] Batch [4649]	Speed: 1760.140163 samples/sec	accuracy=0.598118	lr=0.001889
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Epoch[131] Batch [4799]	Speed: 1737.789545 samples/sec	accuracy=0.598201	lr=0.001883
Epoch[131] Batch [4849]	Speed: 1761.785180 samples/sec	accuracy=0.598193	lr=0.001880
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Epoch[131] Batch [4949]	Speed: 1729.180164 samples/sec	accuracy=0.598147	lr=0.001876
Epoch[131] Batch [4999]	Speed: 1831.902094 samples/sec	accuracy=0.598162	lr=0.001874
[Epoch 131] training: accuracy=0.598153
[Epoch 131] speed: 1760 samples/sec	time cost: 742.276397
[Epoch 131] validation: err-top1=0.360910 err-top5=0.150710
Epoch[132] Batch [49]	Speed: 1619.373986 samples/sec	accuracy=0.595859	lr=0.001872
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Epoch[132] Batch [4649]	Speed: 1753.324973 samples/sec	accuracy=0.599209	lr=0.001688
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Epoch[132] Batch [4849]	Speed: 1740.113759 samples/sec	accuracy=0.599113	lr=0.001680
Epoch[132] Batch [4899]	Speed: 1776.844656 samples/sec	accuracy=0.599090	lr=0.001678
Epoch[132] Batch [4949]	Speed: 1752.681601 samples/sec	accuracy=0.599133	lr=0.001676
Epoch[132] Batch [4999]	Speed: 1841.707779 samples/sec	accuracy=0.599034	lr=0.001674
[Epoch 132] training: accuracy=0.599051
[Epoch 132] speed: 1757 samples/sec	time cost: 743.258194
[Epoch 132] validation: err-top1=0.359696 err-top5=0.150521
Epoch[133] Batch [49]	Speed: 1629.125104 samples/sec	accuracy=0.613594	lr=0.001672
Epoch[133] Batch [99]	Speed: 1766.106278 samples/sec	accuracy=0.606328	lr=0.001670
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Epoch[133] Batch [4649]	Speed: 1771.782779 samples/sec	accuracy=0.600690	lr=0.001497
Epoch[133] Batch [4699]	Speed: 1772.937192 samples/sec	accuracy=0.600691	lr=0.001496
Epoch[133] Batch [4749]	Speed: 1776.063631 samples/sec	accuracy=0.600637	lr=0.001494
Epoch[133] Batch [4799]	Speed: 1750.517357 samples/sec	accuracy=0.600618	lr=0.001492
Epoch[133] Batch [4849]	Speed: 1721.825349 samples/sec	accuracy=0.600640	lr=0.001490
Epoch[133] Batch [4899]	Speed: 1753.390539 samples/sec	accuracy=0.600592	lr=0.001488
Epoch[133] Batch [4949]	Speed: 1757.762007 samples/sec	accuracy=0.600579	lr=0.001486
Epoch[133] Batch [4999]	Speed: 1867.886450 samples/sec	accuracy=0.600561	lr=0.001485
[Epoch 133] training: accuracy=0.600579
[Epoch 133] speed: 1758 samples/sec	time cost: 742.632814
[Epoch 133] validation: err-top1=0.361158 err-top5=0.150581
Epoch[134] Batch [49]	Speed: 1649.473896 samples/sec	accuracy=0.602578	lr=0.001483
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Epoch[134] Batch [3599]	Speed: 1755.820496 samples/sec	accuracy=0.602161	lr=0.001355
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Epoch[134] Batch [4799]	Speed: 1752.641492 samples/sec	accuracy=0.601608	lr=0.001313
Epoch[134] Batch [4849]	Speed: 1724.333736 samples/sec	accuracy=0.601658	lr=0.001311
Epoch[134] Batch [4899]	Speed: 1750.761110 samples/sec	accuracy=0.601743	lr=0.001310
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Epoch[134] Batch [4999]	Speed: 1857.059007 samples/sec	accuracy=0.601683	lr=0.001306
[Epoch 134] training: accuracy=0.601685
[Epoch 134] speed: 1758 samples/sec	time cost: 743.039141
[Epoch 134] validation: err-top1=0.358638 err-top5=0.149753
Epoch[135] Batch [49]	Speed: 1679.519788 samples/sec	accuracy=0.604922	lr=0.001304
Epoch[135] Batch [99]	Speed: 1756.202790 samples/sec	accuracy=0.604727	lr=0.001303
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Epoch[135] Batch [3849]	Speed: 1740.308928 samples/sec	accuracy=0.602309	lr=0.001176
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Epoch[135] Batch [4649]	Speed: 1742.042208 samples/sec	accuracy=0.602088	lr=0.001150
Epoch[135] Batch [4699]	Speed: 1765.871418 samples/sec	accuracy=0.602158	lr=0.001149
Epoch[135] Batch [4749]	Speed: 1743.244099 samples/sec	accuracy=0.602092	lr=0.001147
Epoch[135] Batch [4799]	Speed: 1779.687222 samples/sec	accuracy=0.602170	lr=0.001145
Epoch[135] Batch [4849]	Speed: 1787.169597 samples/sec	accuracy=0.602069	lr=0.001144
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Epoch[135] Batch [4949]	Speed: 1758.757276 samples/sec	accuracy=0.602061	lr=0.001141
Epoch[135] Batch [4999]	Speed: 1865.540096 samples/sec	accuracy=0.602199	lr=0.001139
[Epoch 135] training: accuracy=0.602189
[Epoch 135] speed: 1756 samples/sec	time cost: 743.557503
[Epoch 135] validation: err-top1=0.358874 err-top5=0.149820
Epoch[136] Batch [49]	Speed: 1654.218260 samples/sec	accuracy=0.600703	lr=0.001137
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Epoch[136] Batch [4499]	Speed: 1753.470541 samples/sec	accuracy=0.603038	lr=0.000998
Epoch[136] Batch [4549]	Speed: 1729.862020 samples/sec	accuracy=0.603010	lr=0.000996
Epoch[136] Batch [4599]	Speed: 1758.622984 samples/sec	accuracy=0.603007	lr=0.000995
Epoch[136] Batch [4649]	Speed: 1754.292865 samples/sec	accuracy=0.602984	lr=0.000993
Epoch[136] Batch [4699]	Speed: 1759.255506 samples/sec	accuracy=0.603005	lr=0.000992
Epoch[136] Batch [4749]	Speed: 1780.904242 samples/sec	accuracy=0.602965	lr=0.000990
Epoch[136] Batch [4799]	Speed: 1776.880176 samples/sec	accuracy=0.602994	lr=0.000989
Epoch[136] Batch [4849]	Speed: 1747.338174 samples/sec	accuracy=0.602940	lr=0.000987
Epoch[136] Batch [4899]	Speed: 1718.006215 samples/sec	accuracy=0.603022	lr=0.000986
Epoch[136] Batch [4949]	Speed: 1758.006574 samples/sec	accuracy=0.602988	lr=0.000984
Epoch[136] Batch [4999]	Speed: 1857.052262 samples/sec	accuracy=0.602943	lr=0.000983
[Epoch 136] training: accuracy=0.602936
[Epoch 136] speed: 1751 samples/sec	time cost: 745.750261
[Epoch 136] validation: err-top1=0.357292 err-top5=0.148718
Epoch[137] Batch [49]	Speed: 1660.486734 samples/sec	accuracy=0.606016	lr=0.000981
Epoch[137] Batch [99]	Speed: 1767.772192 samples/sec	accuracy=0.607578	lr=0.000980
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Epoch[137] Batch [3449]	Speed: 1755.702785 samples/sec	accuracy=0.603988	lr=0.000882
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Epoch[137] Batch [3549]	Speed: 1743.065305 samples/sec	accuracy=0.603875	lr=0.000879
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Epoch[137] Batch [4699]	Speed: 1752.943701 samples/sec	accuracy=0.603828	lr=0.000847
Epoch[137] Batch [4749]	Speed: 1779.771353 samples/sec	accuracy=0.603776	lr=0.000845
Epoch[137] Batch [4799]	Speed: 1760.095673 samples/sec	accuracy=0.603682	lr=0.000844
Epoch[137] Batch [4849]	Speed: 1753.605537 samples/sec	accuracy=0.603635	lr=0.000842
Epoch[137] Batch [4899]	Speed: 1735.843836 samples/sec	accuracy=0.603604	lr=0.000841
Epoch[137] Batch [4949]	Speed: 1732.743517 samples/sec	accuracy=0.603571	lr=0.000840
Epoch[137] Batch [4999]	Speed: 1870.248551 samples/sec	accuracy=0.603587	lr=0.000838
[Epoch 137] training: accuracy=0.603568
[Epoch 137] speed: 1756 samples/sec	time cost: 743.887003
[Epoch 137] validation: err-top1=0.358498 err-top5=0.150171
Epoch[138] Batch [49]	Speed: 1652.096397 samples/sec	accuracy=0.609688	lr=0.000837
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Epoch[138] Batch [3249]	Speed: 1746.804725 samples/sec	accuracy=0.604883	lr=0.000750
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Epoch[138] Batch [3599]	Speed: 1757.750900 samples/sec	accuracy=0.604696	lr=0.000741
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Epoch[138] Batch [3949]	Speed: 1778.063031 samples/sec	accuracy=0.604737	lr=0.000732
Epoch[138] Batch [3999]	Speed: 1740.266845 samples/sec	accuracy=0.604777	lr=0.000730
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Epoch[138] Batch [4549]	Speed: 1781.603031 samples/sec	accuracy=0.604560	lr=0.000716
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Epoch[138] Batch [4649]	Speed: 1755.672183 samples/sec	accuracy=0.604557	lr=0.000714
Epoch[138] Batch [4699]	Speed: 1733.739145 samples/sec	accuracy=0.604524	lr=0.000712
Epoch[138] Batch [4749]	Speed: 1787.287400 samples/sec	accuracy=0.604523	lr=0.000711
Epoch[138] Batch [4799]	Speed: 1783.250165 samples/sec	accuracy=0.604521	lr=0.000710
Epoch[138] Batch [4849]	Speed: 1792.994865 samples/sec	accuracy=0.604483	lr=0.000709
Epoch[138] Batch [4899]	Speed: 1776.736458 samples/sec	accuracy=0.604467	lr=0.000707
Epoch[138] Batch [4949]	Speed: 1749.487604 samples/sec	accuracy=0.604545	lr=0.000706
Epoch[138] Batch [4999]	Speed: 1872.983070 samples/sec	accuracy=0.604516	lr=0.000705
[Epoch 138] training: accuracy=0.604516
[Epoch 138] speed: 1759 samples/sec	time cost: 742.606208
[Epoch 138] validation: err-top1=0.357893 err-top5=0.147556
Epoch[139] Batch [49]	Speed: 1648.438329 samples/sec	accuracy=0.600547	lr=0.000703
Epoch[139] Batch [99]	Speed: 1778.229522 samples/sec	accuracy=0.602695	lr=0.000702
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Epoch[139] Batch [4799]	Speed: 1766.311738 samples/sec	accuracy=0.605285	lr=0.000587
Epoch[139] Batch [4849]	Speed: 1762.951085 samples/sec	accuracy=0.605270	lr=0.000586
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Epoch[139] Batch [4999]	Speed: 1847.372388 samples/sec	accuracy=0.605210	lr=0.000583
[Epoch 139] training: accuracy=0.605233
[Epoch 139] speed: 1757 samples/sec	time cost: 743.319921
[Epoch 139] validation: err-top1=0.357352 err-top5=0.147796
Epoch[140] Batch [49]	Speed: 1643.744326 samples/sec	accuracy=0.607422	lr=0.000581
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Epoch[140] Batch [4649]	Speed: 1765.836569 samples/sec	accuracy=0.605981	lr=0.000480
Epoch[140] Batch [4699]	Speed: 1734.650050 samples/sec	accuracy=0.605933	lr=0.000478
Epoch[140] Batch [4749]	Speed: 1769.067045 samples/sec	accuracy=0.605975	lr=0.000477
Epoch[140] Batch [4799]	Speed: 1753.336482 samples/sec	accuracy=0.606008	lr=0.000476
Epoch[140] Batch [4849]	Speed: 1755.393827 samples/sec	accuracy=0.605984	lr=0.000475
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Epoch[140] Batch [4999]	Speed: 1876.201759 samples/sec	accuracy=0.605927	lr=0.000472
[Epoch 140] training: accuracy=0.605926
[Epoch 140] speed: 1756 samples/sec	time cost: 743.592108
[Epoch 140] validation: err-top1=0.357422 err-top5=0.149275
Epoch[141] Batch [49]	Speed: 1669.085283 samples/sec	accuracy=0.612734	lr=0.000471
Epoch[141] Batch [99]	Speed: 1756.147412 samples/sec	accuracy=0.610000	lr=0.000470
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Epoch[141] Batch [4999]	Speed: 1863.175899 samples/sec	accuracy=0.605731	lr=0.000373
[Epoch 141] training: accuracy=0.605739
[Epoch 141] speed: 1755 samples/sec	time cost: 744.248151
[Epoch 141] validation: err-top1=0.356691 err-top5=0.148397
Epoch[142] Batch [49]	Speed: 1652.972775 samples/sec	accuracy=0.602344	lr=0.000372
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Epoch[142] Batch [4999]	Speed: 1837.497711 samples/sec	accuracy=0.607020	lr=0.000286
[Epoch 142] training: accuracy=0.607019
[Epoch 142] speed: 1755 samples/sec	time cost: 743.978018
[Epoch 142] validation: err-top1=0.356510 err-top5=0.149018
Epoch[143] Batch [49]	Speed: 1665.862791 samples/sec	accuracy=0.603203	lr=0.000285
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Epoch[143] Batch [3999]	Speed: 1757.090705 samples/sec	accuracy=0.607456	lr=0.000224
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Epoch[143] Batch [4699]	Speed: 1757.920113 samples/sec	accuracy=0.607093	lr=0.000214
Epoch[143] Batch [4749]	Speed: 1792.412533 samples/sec	accuracy=0.606997	lr=0.000213
Epoch[143] Batch [4799]	Speed: 1767.961155 samples/sec	accuracy=0.606901	lr=0.000213
Epoch[143] Batch [4849]	Speed: 1756.314880 samples/sec	accuracy=0.606897	lr=0.000212
Epoch[143] Batch [4899]	Speed: 1781.024411 samples/sec	accuracy=0.606941	lr=0.000211
Epoch[143] Batch [4949]	Speed: 1771.787399 samples/sec	accuracy=0.606972	lr=0.000211
Epoch[143] Batch [4999]	Speed: 1874.890080 samples/sec	accuracy=0.607024	lr=0.000210
[Epoch 143] training: accuracy=0.607012
[Epoch 143] speed: 1763 samples/sec	time cost: 740.963973
[Epoch 143] validation: err-top1=0.356130 err-top5=0.147636
Epoch[144] Batch [49]	Speed: 1649.097139 samples/sec	accuracy=0.605234	lr=0.000209
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Epoch[144] Batch [4749]	Speed: 1748.320987 samples/sec	accuracy=0.607420	lr=0.000149
Epoch[144] Batch [4799]	Speed: 1778.931636 samples/sec	accuracy=0.607441	lr=0.000148
Epoch[144] Batch [4849]	Speed: 1766.151073 samples/sec	accuracy=0.607420	lr=0.000147
Epoch[144] Batch [4899]	Speed: 1753.619456 samples/sec	accuracy=0.607400	lr=0.000147
Epoch[144] Batch [4949]	Speed: 1719.273760 samples/sec	accuracy=0.607405	lr=0.000146
Epoch[144] Batch [4999]	Speed: 1884.650514 samples/sec	accuracy=0.607380	lr=0.000146
[Epoch 144] training: accuracy=0.607395
[Epoch 144] speed: 1758 samples/sec	time cost: 742.783703
[Epoch 144] validation: err-top1=0.356206 err-top5=0.147561
Epoch[145] Batch [49]	Speed: 1637.654389 samples/sec	accuracy=0.609844	lr=0.000145
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Epoch[145] Batch [4999]	Speed: 1847.402011 samples/sec	accuracy=0.607944	lr=0.000093
[Epoch 145] training: accuracy=0.607945
[Epoch 145] speed: 1757 samples/sec	time cost: 743.710636
[Epoch 145] validation: err-top1=0.356290 err-top5=0.147837
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Epoch[146] Batch [4999]	Speed: 1850.865881 samples/sec	accuracy=0.608068	lr=0.000052
[Epoch 146] training: accuracy=0.608047
[Epoch 146] speed: 1756 samples/sec	time cost: 743.696890
[Epoch 146] validation: err-top1=0.354868 err-top5=0.147616
Epoch[147] Batch [49]	Speed: 1643.823745 samples/sec	accuracy=0.602656	lr=0.000052
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Epoch[147] Batch [4649]	Speed: 1741.375288 samples/sec	accuracy=0.607385	lr=0.000025
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Epoch[147] Batch [4799]	Speed: 1775.482437 samples/sec	accuracy=0.607268	lr=0.000024
Epoch[147] Batch [4849]	Speed: 1752.382629 samples/sec	accuracy=0.607246	lr=0.000024
Epoch[147] Batch [4899]	Speed: 1752.888470 samples/sec	accuracy=0.607302	lr=0.000024
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Epoch[147] Batch [4999]	Speed: 1872.825999 samples/sec	accuracy=0.607336	lr=0.000023
[Epoch 147] training: accuracy=0.607324
[Epoch 147] speed: 1758 samples/sec	time cost: 743.109022
[Epoch 147] validation: err-top1=0.356027 err-top5=0.146624
Epoch[148] Batch [49]	Speed: 1680.482949 samples/sec	accuracy=0.618125	lr=0.000023
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Epoch[148] Batch [2599]	Speed: 1748.996087 samples/sec	accuracy=0.608690	lr=0.000013
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Epoch[148] Batch [3199]	Speed: 1758.562325 samples/sec	accuracy=0.608590	lr=0.000011
Epoch[148] Batch [3249]	Speed: 1789.173584 samples/sec	accuracy=0.608617	lr=0.000010
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Epoch[148] Batch [3399]	Speed: 1743.582713 samples/sec	accuracy=0.608589	lr=0.000010
Epoch[148] Batch [3449]	Speed: 1770.289426 samples/sec	accuracy=0.608665	lr=0.000010
Epoch[148] Batch [3499]	Speed: 1751.460152 samples/sec	accuracy=0.608654	lr=0.000010
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Epoch[148] Batch [3599]	Speed: 1756.781776 samples/sec	accuracy=0.608679	lr=0.000009
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Epoch[148] Batch [3899]	Speed: 1747.702048 samples/sec	accuracy=0.608474	lr=0.000009
Epoch[148] Batch [3949]	Speed: 1775.123221 samples/sec	accuracy=0.608541	lr=0.000008
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Epoch[148] Batch [4499]	Speed: 1730.218372 samples/sec	accuracy=0.608474	lr=0.000007
Epoch[148] Batch [4549]	Speed: 1744.645492 samples/sec	accuracy=0.608430	lr=0.000007
Epoch[148] Batch [4599]	Speed: 1770.458142 samples/sec	accuracy=0.608448	lr=0.000007
Epoch[148] Batch [4649]	Speed: 1762.479920 samples/sec	accuracy=0.608480	lr=0.000007
Epoch[148] Batch [4699]	Speed: 1767.277213 samples/sec	accuracy=0.608509	lr=0.000006
Epoch[148] Batch [4749]	Speed: 1763.186906 samples/sec	accuracy=0.608501	lr=0.000006
Epoch[148] Batch [4799]	Speed: 1768.246190 samples/sec	accuracy=0.608485	lr=0.000006
Epoch[148] Batch [4849]	Speed: 1772.106600 samples/sec	accuracy=0.608464	lr=0.000006
Epoch[148] Batch [4899]	Speed: 1761.328969 samples/sec	accuracy=0.608424	lr=0.000006
Epoch[148] Batch [4949]	Speed: 1740.930262 samples/sec	accuracy=0.608471	lr=0.000006
Epoch[148] Batch [4999]	Speed: 1893.910809 samples/sec	accuracy=0.608398	lr=0.000006
[Epoch 148] training: accuracy=0.608390
[Epoch 148] speed: 1758 samples/sec	time cost: 742.929553
[Epoch 148] validation: err-top1=0.355369 err-top5=0.147236
Epoch[149] Batch [49]	Speed: 1670.576648 samples/sec	accuracy=0.600313	lr=0.000006
Epoch[149] Batch [99]	Speed: 1751.015954 samples/sec	accuracy=0.605039	lr=0.000005
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Epoch[149] Batch [3049]	Speed: 1759.957945 samples/sec	accuracy=0.609023	lr=0.000001
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Epoch[149] Batch [3199]	Speed: 1773.975047 samples/sec	accuracy=0.608776	lr=0.000001
Epoch[149] Batch [3249]	Speed: 1737.343538 samples/sec	accuracy=0.608787	lr=0.000001
Epoch[149] Batch [3299]	Speed: 1758.509390 samples/sec	accuracy=0.608795	lr=0.000001
Epoch[149] Batch [3349]	Speed: 1764.044686 samples/sec	accuracy=0.608738	lr=0.000001
Epoch[149] Batch [3399]	Speed: 1778.679210 samples/sec	accuracy=0.608778	lr=0.000001
Epoch[149] Batch [3449]	Speed: 1790.438666 samples/sec	accuracy=0.608714	lr=0.000001
Epoch[149] Batch [3499]	Speed: 1762.726496 samples/sec	accuracy=0.608786	lr=0.000000
Epoch[149] Batch [3549]	Speed: 1767.150574 samples/sec	accuracy=0.608623	lr=0.000000
Epoch[149] Batch [3599]	Speed: 1773.414199 samples/sec	accuracy=0.608627	lr=0.000000
Epoch[149] Batch [3649]	Speed: 1763.376628 samples/sec	accuracy=0.608623	lr=0.000000
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Epoch[149] Batch [3749]	Speed: 1757.112213 samples/sec	accuracy=0.608674	lr=0.000000
Epoch[149] Batch [3799]	Speed: 1779.110140 samples/sec	accuracy=0.608550	lr=0.000000
Epoch[149] Batch [3849]	Speed: 1763.071795 samples/sec	accuracy=0.608554	lr=0.000000
Epoch[149] Batch [3899]	Speed: 1761.910588 samples/sec	accuracy=0.608498	lr=0.000000
Epoch[149] Batch [3949]	Speed: 1775.711580 samples/sec	accuracy=0.608519	lr=0.000000
Epoch[149] Batch [3999]	Speed: 1787.840091 samples/sec	accuracy=0.608516	lr=0.000000
Epoch[149] Batch [4049]	Speed: 1786.784408 samples/sec	accuracy=0.608600	lr=0.000000
Epoch[149] Batch [4099]	Speed: 1750.168171 samples/sec	accuracy=0.608663	lr=0.000000
Epoch[149] Batch [4149]	Speed: 1771.347267 samples/sec	accuracy=0.608570	lr=0.000000
Epoch[149] Batch [4199]	Speed: 1764.008981 samples/sec	accuracy=0.608622	lr=0.000000
Epoch[149] Batch [4249]	Speed: 1785.545385 samples/sec	accuracy=0.608584	lr=0.000000
Epoch[149] Batch [4299]	Speed: 1754.547305 samples/sec	accuracy=0.608569	lr=0.000000
Epoch[149] Batch [4349]	Speed: 1759.860158 samples/sec	accuracy=0.608507	lr=0.000000
Epoch[149] Batch [4399]	Speed: 1727.577544 samples/sec	accuracy=0.608431	lr=0.000000
Epoch[149] Batch [4449]	Speed: 1757.495818 samples/sec	accuracy=0.608493	lr=0.000000
Epoch[149] Batch [4499]	Speed: 1749.087200 samples/sec	accuracy=0.608481	lr=0.000000
Epoch[149] Batch [4549]	Speed: 1763.791656 samples/sec	accuracy=0.608529	lr=0.000000
Epoch[149] Batch [4599]	Speed: 1761.409409 samples/sec	accuracy=0.608458	lr=0.000000
Epoch[149] Batch [4649]	Speed: 1762.930476 samples/sec	accuracy=0.608519	lr=0.000000
Epoch[149] Batch [4699]	Speed: 1752.284709 samples/sec	accuracy=0.608439	lr=0.000000
Epoch[149] Batch [4749]	Speed: 1780.928050 samples/sec	accuracy=0.608464	lr=0.000000
Epoch[149] Batch [4799]	Speed: 1765.286427 samples/sec	accuracy=0.608495	lr=0.000000
Epoch[149] Batch [4849]	Speed: 1763.307360 samples/sec	accuracy=0.608406	lr=0.000000
Epoch[149] Batch [4899]	Speed: 1755.353881 samples/sec	accuracy=0.608425	lr=0.000000
Epoch[149] Batch [4949]	Speed: 1774.904910 samples/sec	accuracy=0.608408	lr=0.000000
Epoch[149] Batch [4999]	Speed: 1872.853178 samples/sec	accuracy=0.608466	lr=0.000000
[Epoch 149] training: accuracy=0.608475
[Epoch 149] speed: 1763 samples/sec	time cost: 740.834132
[Epoch 149] validation: err-top1=0.355469 err-top5=0.147616