Namespace(batch_norm=False, batch_size=32, crop_ratio=0.875, data_dir='~/.mxnet/datasets/imagenet', dtype='float32', input_size=224, label_smoothing=True, last_gamma=True, log_interval=50, logging_file='resnet152_v1_best.log', lr=0.1, lr_decay=0.1, lr_decay_epoch='40,60', lr_decay_period=0, lr_mode='cosine', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='resnet152_v1', momentum=0.9, no_wd=True, num_epochs=120, num_gpus=8, num_workers=60, rec_train='/media/ramdisk/rec/train.rec', rec_train_idx='/media/ramdisk/rec/train.idx', rec_val='/media/ramdisk/rec/val.rec', rec_val_idx='/media/ramdisk/rec/val.idx', resume_epoch=0, resume_params='', resume_states='', save_dir='params_resnet152_v1_best', save_frequency=10, use_pretrained=False, use_rec=True, use_se=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001)
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[Epoch 0] training: accuracy=0.020439
[Epoch 0] speed: 613 samples/sec	time cost: 2110.763361
[Epoch 0] validation: err-top1=0.941107 err-top5=0.840482
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Epoch[1] Batch [4799]	Speed: 614.843284 samples/sec	accuracy=0.080228	lr=0.039181
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Epoch[1] Batch [4999]	Speed: 643.958020 samples/sec	accuracy=0.082360	lr=0.039980
[Epoch 1] training: accuracy=0.082410
[Epoch 1] speed: 617 samples/sec	time cost: 2098.190732
[Epoch 1] validation: err-top1=0.837460 err-top5=0.640425
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Epoch[2] Batch [4499]	Speed: 612.719082 samples/sec	accuracy=0.196224	lr=0.057982
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Epoch[2] Batch [4649]	Speed: 627.969183 samples/sec	accuracy=0.198028	lr=0.058581
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Epoch[2] Batch [4749]	Speed: 601.277712 samples/sec	accuracy=0.199242	lr=0.058981
Epoch[2] Batch [4799]	Speed: 619.435279 samples/sec	accuracy=0.199847	lr=0.059181
Epoch[2] Batch [4849]	Speed: 553.155477 samples/sec	accuracy=0.200455	lr=0.059380
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Epoch[2] Batch [4999]	Speed: 621.539647 samples/sec	accuracy=0.202321	lr=0.059980
[Epoch 2] training: accuracy=0.202367
[Epoch 2] speed: 603 samples/sec	time cost: 2150.013390
[Epoch 2] validation: err-top1=0.713722 err-top5=0.463662
Epoch[3] Batch [49]	Speed: 607.262422 samples/sec	accuracy=0.275156	lr=0.060196
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Epoch[3] Batch [4999]	Speed: 635.130805 samples/sec	accuracy=0.310330	lr=0.079980
[Epoch 3] training: accuracy=0.310361
[Epoch 3] speed: 607 samples/sec	time cost: 2134.111175
[Epoch 3] validation: err-top1=0.611587 err-top5=0.345364
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[Epoch 4] training: accuracy=0.371913
[Epoch 4] speed: 601 samples/sec	time cost: 2155.919230
[Epoch 4] validation: err-top1=0.566186 err-top5=0.300321
Epoch[5] Batch [49]	Speed: 586.935379 samples/sec	accuracy=0.401016	lr=0.100000
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Epoch[5] Batch [4999]	Speed: 630.047304 samples/sec	accuracy=0.412827	lr=0.099981
[Epoch 5] training: accuracy=0.412857
[Epoch 5] speed: 611 samples/sec	time cost: 2119.122340
[Epoch 5] validation: err-top1=0.513562 err-top5=0.253506
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Epoch[6] Batch [4649]	Speed: 610.826526 samples/sec	accuracy=0.444152	lr=0.099931
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[Epoch 6] training: accuracy=0.444615
[Epoch 6] speed: 600 samples/sec	time cost: 2156.745401
[Epoch 6] validation: err-top1=0.500399 err-top5=0.240912
Epoch[7] Batch [49]	Speed: 590.133538 samples/sec	accuracy=0.462891	lr=0.099925
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Epoch[7] Batch [4999]	Speed: 601.590439 samples/sec	accuracy=0.465909	lr=0.099832
[Epoch 7] training: accuracy=0.465913
[Epoch 7] speed: 611 samples/sec	time cost: 2119.971574
[Epoch 7] validation: err-top1=0.507111 err-top5=0.249840
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Epoch[8] Batch [4999]	Speed: 618.691188 samples/sec	accuracy=0.481739	lr=0.099702
[Epoch 8] training: accuracy=0.481727
[Epoch 8] speed: 593 samples/sec	time cost: 2188.226715
[Epoch 8] validation: err-top1=0.466106 err-top5=0.212760
Epoch[9] Batch [49]	Speed: 599.991346 samples/sec	accuracy=0.498672	lr=0.099700
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Epoch[9] Batch [4999]	Speed: 486.249715 samples/sec	accuracy=0.493645	lr=0.099534
[Epoch 9] training: accuracy=0.493637
[Epoch 9] speed: 602 samples/sec	time cost: 2161.551837
[Epoch 9] validation: err-top1=0.444037 err-top5=0.194974
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Epoch[10] Batch [4999]	Speed: 637.952646 samples/sec	accuracy=0.503546	lr=0.099330
[Epoch 10] training: accuracy=0.503525
[Epoch 10] speed: 614 samples/sec	time cost: 2108.894727
[Epoch 10] validation: err-top1=0.431591 err-top5=0.189363
Epoch[11] Batch [49]	Speed: 590.894265 samples/sec	accuracy=0.515000	lr=0.099328
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Epoch[11] Batch [4799]	Speed: 605.825730 samples/sec	accuracy=0.510656	lr=0.099099
Epoch[11] Batch [4849]	Speed: 645.367006 samples/sec	accuracy=0.510641	lr=0.099097
Epoch[11] Batch [4899]	Speed: 623.079977 samples/sec	accuracy=0.510657	lr=0.099094
Epoch[11] Batch [4949]	Speed: 614.811127 samples/sec	accuracy=0.510648	lr=0.099091
Epoch[11] Batch [4999]	Speed: 625.991164 samples/sec	accuracy=0.510580	lr=0.099089
[Epoch 11] training: accuracy=0.510560
[Epoch 11] speed: 618 samples/sec	time cost: 2097.114899
[Epoch 11] validation: err-top1=0.433894 err-top5=0.187119
Epoch[12] Batch [49]	Speed: 640.962405 samples/sec	accuracy=0.520312	lr=0.099086
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Epoch[12] Batch [4549]	Speed: 629.822452 samples/sec	accuracy=0.516890	lr=0.098837
Epoch[12] Batch [4599]	Speed: 636.013023 samples/sec	accuracy=0.516799	lr=0.098835
Epoch[12] Batch [4649]	Speed: 618.140808 samples/sec	accuracy=0.516876	lr=0.098832
Epoch[12] Batch [4699]	Speed: 631.699276 samples/sec	accuracy=0.516844	lr=0.098829
Epoch[12] Batch [4749]	Speed: 664.813153 samples/sec	accuracy=0.516826	lr=0.098826
Epoch[12] Batch [4799]	Speed: 620.963496 samples/sec	accuracy=0.516769	lr=0.098823
Epoch[12] Batch [4849]	Speed: 615.793762 samples/sec	accuracy=0.516798	lr=0.098820
Epoch[12] Batch [4899]	Speed: 612.581907 samples/sec	accuracy=0.516921	lr=0.098817
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Epoch[12] Batch [4999]	Speed: 683.174179 samples/sec	accuracy=0.516982	lr=0.098811
[Epoch 12] training: accuracy=0.516985
[Epoch 12] speed: 622 samples/sec	time cost: 2081.783227
[Epoch 12] validation: err-top1=0.436663 err-top5=0.191685
Epoch[13] Batch [49]	Speed: 608.347586 samples/sec	accuracy=0.523750	lr=0.098808
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Epoch[13] Batch [4949]	Speed: 621.584443 samples/sec	accuracy=0.522798	lr=0.098500
Epoch[13] Batch [4999]	Speed: 606.954744 samples/sec	accuracy=0.522793	lr=0.098497
[Epoch 13] training: accuracy=0.522801
[Epoch 13] speed: 619 samples/sec	time cost: 2090.618746
[Epoch 13] validation: err-top1=0.453946 err-top5=0.208634
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Epoch[14] Batch [4499]	Speed: 645.984200 samples/sec	accuracy=0.527277	lr=0.098183
Epoch[14] Batch [4549]	Speed: 613.849759 samples/sec	accuracy=0.527271	lr=0.098179
Epoch[14] Batch [4599]	Speed: 613.822022 samples/sec	accuracy=0.527233	lr=0.098176
Epoch[14] Batch [4649]	Speed: 653.555192 samples/sec	accuracy=0.527290	lr=0.098172
Epoch[14] Batch [4699]	Speed: 621.217156 samples/sec	accuracy=0.527335	lr=0.098168
Epoch[14] Batch [4749]	Speed: 634.890621 samples/sec	accuracy=0.527303	lr=0.098165
Epoch[14] Batch [4799]	Speed: 613.938319 samples/sec	accuracy=0.527279	lr=0.098161
Epoch[14] Batch [4849]	Speed: 613.198830 samples/sec	accuracy=0.527295	lr=0.098157
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Epoch[14] Batch [4999]	Speed: 645.775072 samples/sec	accuracy=0.527265	lr=0.098146
[Epoch 14] training: accuracy=0.527234
[Epoch 14] speed: 623 samples/sec	time cost: 2079.593285
[Epoch 14] validation: err-top1=0.411579 err-top5=0.171254
Epoch[15] Batch [49]	Speed: 619.590772 samples/sec	accuracy=0.536797	lr=0.098142
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Epoch[15] Batch [4999]	Speed: 629.248315 samples/sec	accuracy=0.531334	lr=0.097760
[Epoch 15] training: accuracy=0.531329
[Epoch 15] speed: 621 samples/sec	time cost: 2084.368001
[Epoch 15] validation: err-top1=0.419912 err-top5=0.178586
Epoch[16] Batch [49]	Speed: 582.196480 samples/sec	accuracy=0.539141	lr=0.097755
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Epoch[16] Batch [4499]	Speed: 621.702397 samples/sec	accuracy=0.535661	lr=0.097382
Epoch[16] Batch [4549]	Speed: 623.910414 samples/sec	accuracy=0.535620	lr=0.097377
Epoch[16] Batch [4599]	Speed: 619.345541 samples/sec	accuracy=0.535574	lr=0.097373
Epoch[16] Batch [4649]	Speed: 627.318965 samples/sec	accuracy=0.535614	lr=0.097368
Epoch[16] Batch [4699]	Speed: 612.116062 samples/sec	accuracy=0.535515	lr=0.097364
Epoch[16] Batch [4749]	Speed: 631.605556 samples/sec	accuracy=0.535498	lr=0.097360
Epoch[16] Batch [4799]	Speed: 613.448273 samples/sec	accuracy=0.535414	lr=0.097355
Epoch[16] Batch [4849]	Speed: 646.331330 samples/sec	accuracy=0.535426	lr=0.097351
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Epoch[16] Batch [4999]	Speed: 636.836991 samples/sec	accuracy=0.535331	lr=0.097338
[Epoch 16] training: accuracy=0.535340
[Epoch 16] speed: 623 samples/sec	time cost: 2079.499189
[Epoch 16] validation: err-top1=0.416614 err-top5=0.175981
Epoch[17] Batch [49]	Speed: 647.944672 samples/sec	accuracy=0.547813	lr=0.097333
Epoch[17] Batch [99]	Speed: 614.808557 samples/sec	accuracy=0.545508	lr=0.097329
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Epoch[17] Batch [4999]	Speed: 635.501667 samples/sec	accuracy=0.538273	lr=0.096880
[Epoch 17] training: accuracy=0.538269
[Epoch 17] speed: 632 samples/sec	time cost: 2049.795892
[Epoch 17] validation: err-top1=0.444772 err-top5=0.194531
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Epoch[18] Batch [4999]	Speed: 659.134745 samples/sec	accuracy=0.541327	lr=0.096388
[Epoch 18] training: accuracy=0.541319
[Epoch 18] speed: 596 samples/sec	time cost: 2181.961444
[Epoch 18] validation: err-top1=0.399219 err-top5=0.164002
Epoch[19] Batch [49]	Speed: 660.275750 samples/sec	accuracy=0.550781	lr=0.096383
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Epoch[19] Batch [4999]	Speed: 631.563353 samples/sec	accuracy=0.543586	lr=0.095861
[Epoch 19] training: accuracy=0.543620
[Epoch 19] speed: 614 samples/sec	time cost: 2110.881215
[Epoch 19] validation: err-top1=0.421118 err-top5=0.183893
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Epoch[20] Batch [4999]	Speed: 660.007810 samples/sec	accuracy=0.546383	lr=0.095300
[Epoch 20] training: accuracy=0.546395
[Epoch 20] speed: 628 samples/sec	time cost: 2065.911541
[Epoch 20] validation: err-top1=0.396414 err-top5=0.160156
Epoch[21] Batch [49]	Speed: 590.069170 samples/sec	accuracy=0.558281	lr=0.095294
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Epoch[21] Batch [4999]	Speed: 631.771962 samples/sec	accuracy=0.548759	lr=0.094705
[Epoch 21] training: accuracy=0.548734
[Epoch 21] speed: 628 samples/sec	time cost: 2061.804483
[Epoch 21] validation: err-top1=0.405148 err-top5=0.164243
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[Epoch 22] training: accuracy=0.550848
[Epoch 22] speed: 625 samples/sec	time cost: 2071.437440
[Epoch 22] validation: err-top1=0.398617 err-top5=0.160057
Epoch[23] Batch [49]	Speed: 613.509430 samples/sec	accuracy=0.559766	lr=0.094070
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Epoch[23] Batch [4999]	Speed: 639.479336 samples/sec	accuracy=0.552705	lr=0.093415
[Epoch 23] training: accuracy=0.552740
[Epoch 23] speed: 628 samples/sec	time cost: 2061.715210
[Epoch 23] validation: err-top1=0.392849 err-top5=0.157732
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[Epoch 24] training: accuracy=0.555100
[Epoch 24] speed: 631 samples/sec	time cost: 2053.533971
[Epoch 24] validation: err-top1=0.389403 err-top5=0.153946
Epoch[25] Batch [49]	Speed: 630.343889 samples/sec	accuracy=0.561797	lr=0.092714
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Epoch[25] Batch [4999]	Speed: 669.033795 samples/sec	accuracy=0.556646	lr=0.091996
[Epoch 25] training: accuracy=0.556646
[Epoch 25] speed: 629 samples/sec	time cost: 2059.971388
[Epoch 25] validation: err-top1=0.394910 err-top5=0.158642
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Epoch[26] Batch [4999]	Speed: 653.471116 samples/sec	accuracy=0.558504	lr=0.091239
[Epoch 26] training: accuracy=0.558510
[Epoch 26] speed: 631 samples/sec	time cost: 2052.682103
[Epoch 26] validation: err-top1=0.382392 err-top5=0.152424
Epoch[27] Batch [49]	Speed: 606.095216 samples/sec	accuracy=0.564766	lr=0.091231
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Epoch[27] Batch [4999]	Speed: 655.070824 samples/sec	accuracy=0.561371	lr=0.090452
[Epoch 27] training: accuracy=0.561375
[Epoch 27] speed: 629 samples/sec	time cost: 2058.741780
[Epoch 27] validation: err-top1=0.389824 err-top5=0.156831
Epoch[28] Batch [49]	Speed: 639.589581 samples/sec	accuracy=0.573828	lr=0.090443
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Epoch[28] Batch [4849]	Speed: 631.053865 samples/sec	accuracy=0.562693	lr=0.089659
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Epoch[28] Batch [4999]	Speed: 656.522298 samples/sec	accuracy=0.562609	lr=0.089634
[Epoch 28] training: accuracy=0.562631
[Epoch 28] speed: 632 samples/sec	time cost: 2048.790247
[Epoch 28] validation: err-top1=0.400929 err-top5=0.164481
Epoch[29] Batch [49]	Speed: 628.149208 samples/sec	accuracy=0.575078	lr=0.089625
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Epoch[29] Batch [3999]	Speed: 605.712719 samples/sec	accuracy=0.565263	lr=0.088958
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Epoch[29] Batch [4549]	Speed: 629.941159 samples/sec	accuracy=0.564535	lr=0.088864
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Epoch[29] Batch [4649]	Speed: 622.215401 samples/sec	accuracy=0.564365	lr=0.088847
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Epoch[29] Batch [4799]	Speed: 616.455446 samples/sec	accuracy=0.564387	lr=0.088821
Epoch[29] Batch [4849]	Speed: 597.745439 samples/sec	accuracy=0.564355	lr=0.088812
Epoch[29] Batch [4899]	Speed: 618.462812 samples/sec	accuracy=0.564263	lr=0.088804
Epoch[29] Batch [4949]	Speed: 624.990999 samples/sec	accuracy=0.564141	lr=0.088795
Epoch[29] Batch [4999]	Speed: 664.824761 samples/sec	accuracy=0.564152	lr=0.088786
[Epoch 29] training: accuracy=0.564143
[Epoch 29] speed: 623 samples/sec	time cost: 2078.210206
[Epoch 29] validation: err-top1=0.380789 err-top5=0.149079
Epoch[30] Batch [49]	Speed: 634.529314 samples/sec	accuracy=0.567656	lr=0.088777
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Epoch[30] Batch [3599]	Speed: 662.159085 samples/sec	accuracy=0.567979	lr=0.088158
Epoch[30] Batch [3649]	Speed: 635.533601 samples/sec	accuracy=0.567928	lr=0.088149
Epoch[30] Batch [3699]	Speed: 619.146976 samples/sec	accuracy=0.567835	lr=0.088140
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Epoch[30] Batch [3799]	Speed: 643.764800 samples/sec	accuracy=0.567819	lr=0.088123
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Epoch[30] Batch [3899]	Speed: 630.375085 samples/sec	accuracy=0.567633	lr=0.088105
Epoch[30] Batch [3949]	Speed: 644.868791 samples/sec	accuracy=0.567614	lr=0.088096
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Epoch[30] Batch [4499]	Speed: 623.414439 samples/sec	accuracy=0.567401	lr=0.087999
Epoch[30] Batch [4549]	Speed: 647.749051 samples/sec	accuracy=0.567395	lr=0.087990
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Epoch[30] Batch [4649]	Speed: 632.063090 samples/sec	accuracy=0.567212	lr=0.087972
Epoch[30] Batch [4699]	Speed: 635.594982 samples/sec	accuracy=0.567179	lr=0.087963
Epoch[30] Batch [4749]	Speed: 631.461383 samples/sec	accuracy=0.567127	lr=0.087955
Epoch[30] Batch [4799]	Speed: 670.572333 samples/sec	accuracy=0.567096	lr=0.087946
Epoch[30] Batch [4849]	Speed: 626.504957 samples/sec	accuracy=0.567001	lr=0.087937
Epoch[30] Batch [4899]	Speed: 639.605681 samples/sec	accuracy=0.566883	lr=0.087928
Epoch[30] Batch [4949]	Speed: 652.207866 samples/sec	accuracy=0.566848	lr=0.087919
Epoch[30] Batch [4999]	Speed: 625.844860 samples/sec	accuracy=0.566731	lr=0.087910
[Epoch 30] training: accuracy=0.566716
[Epoch 30] speed: 631 samples/sec	time cost: 2052.422354
[Epoch 30] validation: err-top1=0.408233 err-top5=0.171234
Epoch[31] Batch [49]	Speed: 618.112333 samples/sec	accuracy=0.570391	lr=0.087900
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Epoch[31] Batch [4999]	Speed: 643.551467 samples/sec	accuracy=0.567799	lr=0.087005
[Epoch 31] training: accuracy=0.567785
[Epoch 31] speed: 628 samples/sec	time cost: 2062.609428
[Epoch 31] validation: err-top1=0.405148 err-top5=0.169351
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Epoch[32] Batch [4999]	Speed: 629.085712 samples/sec	accuracy=0.569706	lr=0.086073
[Epoch 32] training: accuracy=0.569721
[Epoch 32] speed: 626 samples/sec	time cost: 2069.177544
[Epoch 32] validation: err-top1=0.385184 err-top5=0.152822
Epoch[33] Batch [49]	Speed: 607.876401 samples/sec	accuracy=0.576797	lr=0.086063
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Epoch[33] Batch [4949]	Speed: 632.311534 samples/sec	accuracy=0.571934	lr=0.085124
Epoch[33] Batch [4999]	Speed: 634.549660 samples/sec	accuracy=0.571871	lr=0.085114
[Epoch 33] training: accuracy=0.571872
[Epoch 33] speed: 630 samples/sec	time cost: 2056.089612
[Epoch 33] validation: err-top1=0.375741 err-top5=0.148838
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Epoch[34] Batch [4999]	Speed: 630.708869 samples/sec	accuracy=0.572837	lr=0.084129
[Epoch 34] training: accuracy=0.572819
[Epoch 34] speed: 629 samples/sec	time cost: 2060.949705
[Epoch 34] validation: err-top1=0.371174 err-top5=0.140565
Epoch[35] Batch [49]	Speed: 623.220145 samples/sec	accuracy=0.586406	lr=0.084118
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Epoch[35] Batch [4999]	Speed: 657.923210 samples/sec	accuracy=0.575051	lr=0.083118
[Epoch 35] training: accuracy=0.575064
[Epoch 35] speed: 632 samples/sec	time cost: 2049.893086
[Epoch 35] validation: err-top1=0.369101 err-top5=0.141522
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Epoch[36] Batch [4999]	Speed: 640.947614 samples/sec	accuracy=0.576240	lr=0.082082
[Epoch 36] training: accuracy=0.576223
[Epoch 36] speed: 631 samples/sec	time cost: 2053.811698
[Epoch 36] validation: err-top1=0.384776 err-top5=0.153786
Epoch[37] Batch [49]	Speed: 612.249015 samples/sec	accuracy=0.582969	lr=0.082071
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Epoch[37] Batch [4999]	Speed: 632.630427 samples/sec	accuracy=0.578270	lr=0.081023
[Epoch 37] training: accuracy=0.578283
[Epoch 37] speed: 636 samples/sec	time cost: 2037.298544
[Epoch 37] validation: err-top1=0.389904 err-top5=0.158293
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Epoch[38] Batch [4999]	Speed: 635.295098 samples/sec	accuracy=0.580559	lr=0.079940
[Epoch 38] training: accuracy=0.580567
[Epoch 38] speed: 631 samples/sec	time cost: 2052.030892
[Epoch 38] validation: err-top1=0.388712 err-top5=0.156051
Epoch[39] Batch [49]	Speed: 609.449082 samples/sec	accuracy=0.586562	lr=0.079928
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Epoch[39] Batch [4849]	Speed: 619.784191 samples/sec	accuracy=0.582325	lr=0.078869
Epoch[39] Batch [4899]	Speed: 638.816812 samples/sec	accuracy=0.582279	lr=0.078857
Epoch[39] Batch [4949]	Speed: 631.873630 samples/sec	accuracy=0.582156	lr=0.078846
Epoch[39] Batch [4999]	Speed: 672.536224 samples/sec	accuracy=0.582120	lr=0.078835
[Epoch 39] training: accuracy=0.582109
[Epoch 39] speed: 628 samples/sec	time cost: 2062.263746
[Epoch 39] validation: err-top1=0.384696 err-top5=0.151983
Epoch[40] Batch [49]	Speed: 623.911966 samples/sec	accuracy=0.584063	lr=0.078823
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Epoch[40] Batch [4749]	Speed: 642.824252 samples/sec	accuracy=0.584127	lr=0.077765
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Epoch[40] Batch [4849]	Speed: 643.950829 samples/sec	accuracy=0.583871	lr=0.077743
Epoch[40] Batch [4899]	Speed: 641.965828 samples/sec	accuracy=0.583860	lr=0.077731
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Epoch[40] Batch [4999]	Speed: 654.295133 samples/sec	accuracy=0.583675	lr=0.077709
[Epoch 40] training: accuracy=0.583684
[Epoch 40] speed: 635 samples/sec	time cost: 2041.603318
[Epoch 40] validation: err-top1=0.366266 err-top5=0.140825
Epoch[41] Batch [49]	Speed: 622.485530 samples/sec	accuracy=0.597266	lr=0.077696
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Epoch[41] Batch [4999]	Speed: 653.584686 samples/sec	accuracy=0.584928	lr=0.076561
[Epoch 41] training: accuracy=0.584928
[Epoch 41] speed: 634 samples/sec	time cost: 2043.583392
[Epoch 41] validation: err-top1=0.366789 err-top5=0.141123
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Epoch[42] Batch [4999]	Speed: 675.833719 samples/sec	accuracy=0.587037	lr=0.075394
[Epoch 42] training: accuracy=0.587040
[Epoch 42] speed: 630 samples/sec	time cost: 2055.449564
[Epoch 42] validation: err-top1=0.363261 err-top5=0.137240
Epoch[43] Batch [49]	Speed: 631.647036 samples/sec	accuracy=0.594219	lr=0.075382
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[Epoch 43] training: accuracy=0.588816
[Epoch 43] speed: 633 samples/sec	time cost: 2045.997108
[Epoch 43] validation: err-top1=0.375721 err-top5=0.147977
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[Epoch 44] training: accuracy=0.590506
[Epoch 44] speed: 635 samples/sec	time cost: 2039.680702
[Epoch 44] validation: err-top1=0.357681 err-top5=0.135144
Epoch[45] Batch [49]	Speed: 600.786961 samples/sec	accuracy=0.612734	lr=0.072991
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[Epoch 45] training: accuracy=0.592642
[Epoch 45] speed: 629 samples/sec	time cost: 2060.375633
[Epoch 45] validation: err-top1=0.349199 err-top5=0.128285
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[Epoch 46] training: accuracy=0.594135
[Epoch 46] speed: 626 samples/sec	time cost: 2068.332987
[Epoch 46] validation: err-top1=0.361538 err-top5=0.135797
Epoch[47] Batch [49]	Speed: 619.784305 samples/sec	accuracy=0.606250	lr=0.070532
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[Epoch 47] training: accuracy=0.595931
[Epoch 47] speed: 628 samples/sec	time cost: 2062.282792
[Epoch 47] validation: err-top1=0.357672 err-top5=0.134275
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[Epoch 48] training: accuracy=0.597460
[Epoch 48] speed: 636 samples/sec	time cost: 2036.736634
[Epoch 48] validation: err-top1=0.351004 err-top5=0.130341
Epoch[49] Batch [49]	Speed: 621.591661 samples/sec	accuracy=0.616797	lr=0.068012
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[Epoch 49] training: accuracy=0.600516
[Epoch 49] speed: 633 samples/sec	time cost: 2045.348154
[Epoch 49] validation: err-top1=0.359195 err-top5=0.138061
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[Epoch 50] training: accuracy=0.602849
[Epoch 50] speed: 634 samples/sec	time cost: 2043.602759
[Epoch 50] validation: err-top1=0.372376 err-top5=0.144852
Epoch[51] Batch [49]	Speed: 603.312024 samples/sec	accuracy=0.616563	lr=0.065438
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[Epoch 51] training: accuracy=0.604097
[Epoch 51] speed: 632 samples/sec	time cost: 2049.841204
[Epoch 51] validation: err-top1=0.354034 err-top5=0.131896
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[Epoch 52] training: accuracy=0.606677
[Epoch 52] speed: 637 samples/sec	time cost: 2034.749167
[Epoch 52] validation: err-top1=0.343810 err-top5=0.126963
Epoch[53] Batch [49]	Speed: 606.101648 samples/sec	accuracy=0.616172	lr=0.062818
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Epoch[53] Batch [4999]	Speed: 646.799219 samples/sec	accuracy=0.608130	lr=0.061508
[Epoch 53] training: accuracy=0.608111
[Epoch 53] speed: 632 samples/sec	time cost: 2049.989870
[Epoch 53] validation: err-top1=0.357031 err-top5=0.134435
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[Epoch 54] training: accuracy=0.609747
[Epoch 54] speed: 632 samples/sec	time cost: 2050.330418
[Epoch 54] validation: err-top1=0.369340 err-top5=0.145289
Epoch[55] Batch [49]	Speed: 635.753553 samples/sec	accuracy=0.623516	lr=0.060160
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Epoch[55] Batch [4999]	Speed: 641.804113 samples/sec	accuracy=0.612698	lr=0.058833
[Epoch 55] training: accuracy=0.612701
[Epoch 55] speed: 634 samples/sec	time cost: 2043.554633
[Epoch 55] validation: err-top1=0.330228 err-top5=0.118570
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Epoch[56] Batch [4999]	Speed: 626.063485 samples/sec	accuracy=0.614498	lr=0.057486
[Epoch 56] training: accuracy=0.614504
[Epoch 56] speed: 634 samples/sec	time cost: 2042.275054
[Epoch 56] validation: err-top1=0.349179 err-top5=0.130168
Epoch[57] Batch [49]	Speed: 604.727452 samples/sec	accuracy=0.629531	lr=0.057471
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Epoch[57] Batch [4999]	Speed: 650.808495 samples/sec	accuracy=0.616856	lr=0.056132
[Epoch 57] training: accuracy=0.616872
[Epoch 57] speed: 632 samples/sec	time cost: 2048.813529
[Epoch 57] validation: err-top1=0.335081 err-top5=0.118144
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[Epoch 58] training: accuracy=0.619073
[Epoch 58] speed: 630 samples/sec	time cost: 2056.397191
[Epoch 58] validation: err-top1=0.344131 err-top5=0.125361
Epoch[59] Batch [49]	Speed: 628.856876 samples/sec	accuracy=0.636250	lr=0.054760
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[Epoch 59] training: accuracy=0.621048
[Epoch 59] speed: 636 samples/sec	time cost: 2036.071286
[Epoch 59] validation: err-top1=0.327885 err-top5=0.118189
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[Epoch 60] training: accuracy=0.623483
[Epoch 60] speed: 634 samples/sec	time cost: 2043.537564
[Epoch 60] validation: err-top1=0.336496 err-top5=0.122708
Epoch[61] Batch [49]	Speed: 646.479727 samples/sec	accuracy=0.636719	lr=0.052035
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[Epoch 61] training: accuracy=0.626142
[Epoch 61] speed: 633 samples/sec	time cost: 2046.570224
[Epoch 61] validation: err-top1=0.323778 err-top5=0.113161
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[Epoch 62] training: accuracy=0.628312
[Epoch 62] speed: 634 samples/sec	time cost: 2042.677862
[Epoch 62] validation: err-top1=0.323838 err-top5=0.114143
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Epoch[63] Batch [4999]	Speed: 643.617840 samples/sec	accuracy=0.631127	lr=0.047953
[Epoch 63] training: accuracy=0.631115
[Epoch 63] speed: 634 samples/sec	time cost: 2044.512277
[Epoch 63] validation: err-top1=0.315385 err-top5=0.107672
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[Epoch 64] training: accuracy=0.632943
[Epoch 64] speed: 631 samples/sec	time cost: 2053.422455
[Epoch 64] validation: err-top1=0.327946 err-top5=0.114836
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Epoch[65] Batch [4999]	Speed: 688.040134 samples/sec	accuracy=0.636291	lr=0.045228
[Epoch 65] training: accuracy=0.636303
[Epoch 65] speed: 635 samples/sec	time cost: 2039.334576
[Epoch 65] validation: err-top1=0.324780 err-top5=0.114764
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[Epoch 66] training: accuracy=0.638887
[Epoch 66] speed: 629 samples/sec	time cost: 2059.893305
[Epoch 66] validation: err-top1=0.315425 err-top5=0.107372
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[Epoch 67] training: accuracy=0.641211
[Epoch 67] speed: 628 samples/sec	time cost: 2062.838360
[Epoch 67] validation: err-top1=0.321648 err-top5=0.113301
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Epoch[68] Batch [4999]	Speed: 629.466077 samples/sec	accuracy=0.644284	lr=0.041170
[Epoch 68] training: accuracy=0.644265
[Epoch 68] speed: 631 samples/sec	time cost: 2051.891415
[Epoch 68] validation: err-top1=0.313722 err-top5=0.105990
Epoch[69] Batch [49]	Speed: 623.058053 samples/sec	accuracy=0.653750	lr=0.041155
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Epoch[69] Batch [4999]	Speed: 653.566768 samples/sec	accuracy=0.646282	lr=0.039829
[Epoch 69] training: accuracy=0.646287
[Epoch 69] speed: 637 samples/sec	time cost: 2033.888708
[Epoch 69] validation: err-top1=0.308013 err-top5=0.103806
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Epoch[70] Batch [4999]	Speed: 652.970409 samples/sec	accuracy=0.648787	lr=0.038495
[Epoch 70] training: accuracy=0.648769
[Epoch 70] speed: 634 samples/sec	time cost: 2044.061749
[Epoch 70] validation: err-top1=0.310248 err-top5=0.104672
Epoch[71] Batch [49]	Speed: 625.164567 samples/sec	accuracy=0.655859	lr=0.038481
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Epoch[71] Batch [4999]	Speed: 643.424854 samples/sec	accuracy=0.651513	lr=0.037170
[Epoch 71] training: accuracy=0.651518
[Epoch 71] speed: 635 samples/sec	time cost: 2041.671344
[Epoch 71] validation: err-top1=0.328025 err-top5=0.116627
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[Epoch 72] training: accuracy=0.655683
[Epoch 72] speed: 636 samples/sec	time cost: 2036.827630
[Epoch 72] validation: err-top1=0.313582 err-top5=0.109635
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[Epoch 73] training: accuracy=0.657788
[Epoch 73] speed: 633 samples/sec	time cost: 2046.989000
[Epoch 73] validation: err-top1=0.311145 err-top5=0.105927
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[Epoch 74] training: accuracy=0.660948
[Epoch 74] speed: 628 samples/sec	time cost: 2063.266449
[Epoch 74] validation: err-top1=0.297576 err-top5=0.097696
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[Epoch 75] training: accuracy=0.663417
[Epoch 75] speed: 632 samples/sec	time cost: 2049.846611
[Epoch 75] validation: err-top1=0.296354 err-top5=0.097536
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[Epoch 76] training: accuracy=0.666453
[Epoch 76] speed: 634 samples/sec	time cost: 2043.711122
[Epoch 76] validation: err-top1=0.291733 err-top5=0.095045
Epoch[77] Batch [49]	Speed: 617.328403 samples/sec	accuracy=0.675937	lr=0.030696
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[Epoch 77] training: accuracy=0.669725
[Epoch 77] speed: 637 samples/sec	time cost: 2034.794785
[Epoch 77] validation: err-top1=0.290164 err-top5=0.093269
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Epoch[78] Batch [4999]	Speed: 651.760361 samples/sec	accuracy=0.673531	lr=0.028219
[Epoch 78] training: accuracy=0.673517
[Epoch 78] speed: 633 samples/sec	time cost: 2047.436183
[Epoch 78] validation: err-top1=0.295573 err-top5=0.097376
Epoch[79] Batch [49]	Speed: 610.598112 samples/sec	accuracy=0.684375	lr=0.028206
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[Epoch 79] training: accuracy=0.676706
[Epoch 79] speed: 629 samples/sec	time cost: 2059.918456
[Epoch 79] validation: err-top1=0.288622 err-top5=0.093970
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[Epoch 80] training: accuracy=0.680089
[Epoch 80] speed: 635 samples/sec	time cost: 2041.383053
[Epoch 80] validation: err-top1=0.283064 err-top5=0.089226
Epoch[81] Batch [49]	Speed: 627.106619 samples/sec	accuracy=0.694531	lr=0.025781
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Epoch[81] Batch [4999]	Speed: 646.705296 samples/sec	accuracy=0.682972	lr=0.024608
[Epoch 81] training: accuracy=0.682969
[Epoch 81] speed: 633 samples/sec	time cost: 2045.359315
[Epoch 81] validation: err-top1=0.285877 err-top5=0.091687
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[Epoch 82] training: accuracy=0.686629
[Epoch 82] speed: 630 samples/sec	time cost: 2055.607143
[Epoch 82] validation: err-top1=0.282352 err-top5=0.088922
Epoch[83] Batch [49]	Speed: 635.852779 samples/sec	accuracy=0.695859	lr=0.023428
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Epoch[83] Batch [4999]	Speed: 646.871977 samples/sec	accuracy=0.689783	lr=0.022294
[Epoch 83] training: accuracy=0.689796
[Epoch 83] speed: 632 samples/sec	time cost: 2050.688714
[Epoch 83] validation: err-top1=0.286272 err-top5=0.093431
Epoch[84] Batch [49]	Speed: 604.510206 samples/sec	accuracy=0.701641	lr=0.022281
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Epoch[84] Batch [4999]	Speed: 657.944851 samples/sec	accuracy=0.694511	lr=0.021167
[Epoch 84] training: accuracy=0.694501
[Epoch 84] speed: 627 samples/sec	time cost: 2067.471686
[Epoch 84] validation: err-top1=0.272616 err-top5=0.083353
Epoch[85] Batch [49]	Speed: 595.440645 samples/sec	accuracy=0.712187	lr=0.021155
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[Epoch 85] training: accuracy=0.697964
[Epoch 85] speed: 631 samples/sec	time cost: 2052.814876
[Epoch 85] validation: err-top1=0.269571 err-top5=0.081310
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[Epoch 86] training: accuracy=0.702022
[Epoch 86] speed: 632 samples/sec	time cost: 2051.441308
[Epoch 86] validation: err-top1=0.271783 err-top5=0.083127
Epoch[87] Batch [49]	Speed: 625.738026 samples/sec	accuracy=0.716172	lr=0.018968
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[Epoch 87] training: accuracy=0.705502
[Epoch 87] speed: 634 samples/sec	time cost: 2042.633772
[Epoch 87] validation: err-top1=0.263462 err-top5=0.079107
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[Epoch 88] training: accuracy=0.709436
[Epoch 88] speed: 632 samples/sec	time cost: 2048.211584
[Epoch 88] validation: err-top1=0.260156 err-top5=0.078085
Epoch[89] Batch [49]	Speed: 614.942062 samples/sec	accuracy=0.722187	lr=0.016873
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[Epoch 89] training: accuracy=0.713522
[Epoch 89] speed: 632 samples/sec	time cost: 2050.563106
[Epoch 89] validation: err-top1=0.260443 err-top5=0.077786
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[Epoch 90] training: accuracy=0.717770
[Epoch 90] speed: 631 samples/sec	time cost: 2052.278377
[Epoch 90] validation: err-top1=0.261859 err-top5=0.079768
Epoch[91] Batch [49]	Speed: 615.700161 samples/sec	accuracy=0.726406	lr=0.014877
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[Epoch 91] training: accuracy=0.722120
[Epoch 91] speed: 629 samples/sec	time cost: 2058.880174
[Epoch 91] validation: err-top1=0.254487 err-top5=0.075441
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[Epoch 92] training: accuracy=0.726234
[Epoch 92] speed: 634 samples/sec	time cost: 2044.176494
[Epoch 92] validation: err-top1=0.251375 err-top5=0.073800
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[Epoch 93] training: accuracy=0.730584
[Epoch 93] speed: 636 samples/sec	time cost: 2036.658910
[Epoch 93] validation: err-top1=0.249199 err-top5=0.071494
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[Epoch 94] training: accuracy=0.735583
[Epoch 94] speed: 630 samples/sec	time cost: 2056.973109
[Epoch 94] validation: err-top1=0.253145 err-top5=0.074379
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Epoch[95] Batch [4999]	Speed: 643.409108 samples/sec	accuracy=0.740461	lr=0.010368
[Epoch 95] training: accuracy=0.740479
[Epoch 95] speed: 634 samples/sec	time cost: 2042.913971
[Epoch 95] validation: err-top1=0.251382 err-top5=0.073117
Epoch[96] Batch [49]	Speed: 632.167323 samples/sec	accuracy=0.743750	lr=0.010359
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Epoch[96] Batch [4999]	Speed: 645.271287 samples/sec	accuracy=0.745083	lr=0.009550
[Epoch 96] training: accuracy=0.745083
[Epoch 96] speed: 632 samples/sec	time cost: 2050.919648
[Epoch 96] validation: err-top1=0.246074 err-top5=0.070392
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[Epoch 97] training: accuracy=0.750014
[Epoch 97] speed: 635 samples/sec	time cost: 2040.941014
[Epoch 97] validation: err-top1=0.239563 err-top5=0.067187
Epoch[98] Batch [49]	Speed: 604.447148 samples/sec	accuracy=0.761719	lr=0.008754
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Epoch[98] Batch [4999]	Speed: 660.060733 samples/sec	accuracy=0.755362	lr=0.008005
[Epoch 98] training: accuracy=0.755378
[Epoch 98] speed: 632 samples/sec	time cost: 2050.445358
[Epoch 98] validation: err-top1=0.239042 err-top5=0.066907
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[Epoch 99] training: accuracy=0.759828
[Epoch 99] speed: 634 samples/sec	time cost: 2043.779904
[Epoch 99] validation: err-top1=0.237006 err-top5=0.065390
Epoch[100] Batch [49]	Speed: 626.168231 samples/sec	accuracy=0.770859	lr=0.007272
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Epoch[100] Batch [4699]	Speed: 653.258536 samples/sec	accuracy=0.765785	lr=0.006627
Epoch[100] Batch [4749]	Speed: 630.782342 samples/sec	accuracy=0.765770	lr=0.006620
Epoch[100] Batch [4799]	Speed: 641.265506 samples/sec	accuracy=0.765689	lr=0.006613
Epoch[100] Batch [4849]	Speed: 629.777178 samples/sec	accuracy=0.765684	lr=0.006606
Epoch[100] Batch [4899]	Speed: 646.465208 samples/sec	accuracy=0.765591	lr=0.006600
Epoch[100] Batch [4949]	Speed: 644.843548 samples/sec	accuracy=0.765544	lr=0.006593
Epoch[100] Batch [4999]	Speed: 660.641308 samples/sec	accuracy=0.765499	lr=0.006586
[Epoch 100] training: accuracy=0.765497
[Epoch 100] speed: 638 samples/sec	time cost: 2030.098726
[Epoch 100] validation: err-top1=0.233193 err-top5=0.064263
Epoch[101] Batch [49]	Speed: 595.040355 samples/sec	accuracy=0.777734	lr=0.006579
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Epoch[101] Batch [4499]	Speed: 626.031334 samples/sec	accuracy=0.770983	lr=0.005989
Epoch[101] Batch [4549]	Speed: 641.560344 samples/sec	accuracy=0.770955	lr=0.005983
Epoch[101] Batch [4599]	Speed: 653.019143 samples/sec	accuracy=0.770935	lr=0.005976
Epoch[101] Batch [4649]	Speed: 641.201646 samples/sec	accuracy=0.770905	lr=0.005970
Epoch[101] Batch [4699]	Speed: 628.997422 samples/sec	accuracy=0.770948	lr=0.005963
Epoch[101] Batch [4749]	Speed: 640.619098 samples/sec	accuracy=0.770966	lr=0.005957
Epoch[101] Batch [4799]	Speed: 643.896280 samples/sec	accuracy=0.770922	lr=0.005951
Epoch[101] Batch [4849]	Speed: 633.020631 samples/sec	accuracy=0.770940	lr=0.005944
Epoch[101] Batch [4899]	Speed: 631.003963 samples/sec	accuracy=0.770894	lr=0.005938
Epoch[101] Batch [4949]	Speed: 633.367123 samples/sec	accuracy=0.770900	lr=0.005931
Epoch[101] Batch [4999]	Speed: 656.829849 samples/sec	accuracy=0.770921	lr=0.005925
[Epoch 101] training: accuracy=0.770935
[Epoch 101] speed: 631 samples/sec	time cost: 2051.512407
[Epoch 101] validation: err-top1=0.232372 err-top5=0.063341
Epoch[102] Batch [49]	Speed: 640.886472 samples/sec	accuracy=0.776953	lr=0.005918
Epoch[102] Batch [99]	Speed: 644.072280 samples/sec	accuracy=0.781602	lr=0.005911
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Epoch[102] Batch [4999]	Speed: 607.934614 samples/sec	accuracy=0.775516	lr=0.005296
[Epoch 102] training: accuracy=0.775503
[Epoch 102] speed: 627 samples/sec	time cost: 2065.877480
[Epoch 102] validation: err-top1=0.229333 err-top5=0.062261
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Epoch[103] Batch [4999]	Speed: 659.170564 samples/sec	accuracy=0.781575	lr=0.004701
[Epoch 103] training: accuracy=0.781574
[Epoch 103] speed: 629 samples/sec	time cost: 2060.111904
[Epoch 103] validation: err-top1=0.226583 err-top5=0.061198
Epoch[104] Batch [49]	Speed: 645.440085 samples/sec	accuracy=0.795469	lr=0.004695
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Epoch[104] Batch [4999]	Speed: 641.285459 samples/sec	accuracy=0.786195	lr=0.004140
[Epoch 104] training: accuracy=0.786205
[Epoch 104] speed: 635 samples/sec	time cost: 2039.725417
[Epoch 104] validation: err-top1=0.222837 err-top5=0.060377
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[Epoch 105] training: accuracy=0.792095
[Epoch 105] speed: 635 samples/sec	time cost: 2040.141478
[Epoch 105] validation: err-top1=0.222278 err-top5=0.059989
Epoch[106] Batch [49]	Speed: 619.379881 samples/sec	accuracy=0.795859	lr=0.003607
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Epoch[106] Batch [4999]	Speed: 665.399054 samples/sec	accuracy=0.797969	lr=0.003121
[Epoch 106] training: accuracy=0.797974
[Epoch 106] speed: 632 samples/sec	time cost: 2048.220928
[Epoch 106] validation: err-top1=0.221454 err-top5=0.058093
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[Epoch 107] training: accuracy=0.803355
[Epoch 107] speed: 638 samples/sec	time cost: 2032.386775
[Epoch 107] validation: err-top1=0.218830 err-top5=0.057993
Epoch[108] Batch [49]	Speed: 623.623183 samples/sec	accuracy=0.811406	lr=0.002658
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Epoch[108] Batch [4549]	Speed: 632.392786 samples/sec	accuracy=0.808247	lr=0.002277
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Epoch[108] Batch [4649]	Speed: 626.440203 samples/sec	accuracy=0.808282	lr=0.002269
Epoch[108] Batch [4699]	Speed: 632.741321 samples/sec	accuracy=0.808353	lr=0.002265
Epoch[108] Batch [4749]	Speed: 627.181234 samples/sec	accuracy=0.808368	lr=0.002261
Epoch[108] Batch [4799]	Speed: 620.400887 samples/sec	accuracy=0.808383	lr=0.002257
Epoch[108] Batch [4849]	Speed: 632.803722 samples/sec	accuracy=0.808413	lr=0.002253
Epoch[108] Batch [4899]	Speed: 609.651311 samples/sec	accuracy=0.808449	lr=0.002249
Epoch[108] Batch [4949]	Speed: 628.959310 samples/sec	accuracy=0.808474	lr=0.002245
Epoch[108] Batch [4999]	Speed: 648.084860 samples/sec	accuracy=0.808403	lr=0.002241
[Epoch 108] training: accuracy=0.808413
[Epoch 108] speed: 635 samples/sec	time cost: 2039.700613
[Epoch 108] validation: err-top1=0.216259 err-top5=0.056920
Epoch[109] Batch [49]	Speed: 640.968275 samples/sec	accuracy=0.815312	lr=0.002237
Epoch[109] Batch [99]	Speed: 653.861705 samples/sec	accuracy=0.815977	lr=0.002233
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Epoch[109] Batch [4499]	Speed: 623.381402 samples/sec	accuracy=0.812956	lr=0.001892
Epoch[109] Batch [4549]	Speed: 618.288637 samples/sec	accuracy=0.812945	lr=0.001888
Epoch[109] Batch [4599]	Speed: 616.196486 samples/sec	accuracy=0.812899	lr=0.001884
Epoch[109] Batch [4649]	Speed: 616.186373 samples/sec	accuracy=0.812907	lr=0.001880
Epoch[109] Batch [4699]	Speed: 647.624063 samples/sec	accuracy=0.812894	lr=0.001877
Epoch[109] Batch [4749]	Speed: 645.212118 samples/sec	accuracy=0.812922	lr=0.001873
Epoch[109] Batch [4799]	Speed: 646.184993 samples/sec	accuracy=0.812894	lr=0.001869
Epoch[109] Batch [4849]	Speed: 641.370643 samples/sec	accuracy=0.812857	lr=0.001866
Epoch[109] Batch [4899]	Speed: 626.433610 samples/sec	accuracy=0.812796	lr=0.001862
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Epoch[109] Batch [4999]	Speed: 634.101934 samples/sec	accuracy=0.812778	lr=0.001855
[Epoch 109] training: accuracy=0.812770
[Epoch 109] speed: 634 samples/sec	time cost: 2042.938017
[Epoch 109] validation: err-top1=0.215705 err-top5=0.055769
Epoch[110] Batch [49]	Speed: 623.478685 samples/sec	accuracy=0.820703	lr=0.001851
Epoch[110] Batch [99]	Speed: 655.145758 samples/sec	accuracy=0.822070	lr=0.001847
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Epoch[110] Batch [4599]	Speed: 626.064091 samples/sec	accuracy=0.817479	lr=0.001531
Epoch[110] Batch [4649]	Speed: 641.605005 samples/sec	accuracy=0.817447	lr=0.001527
Epoch[110] Batch [4699]	Speed: 630.976034 samples/sec	accuracy=0.817416	lr=0.001524
Epoch[110] Batch [4749]	Speed: 624.202678 samples/sec	accuracy=0.817467	lr=0.001521
Epoch[110] Batch [4799]	Speed: 618.727381 samples/sec	accuracy=0.817460	lr=0.001517
Epoch[110] Batch [4849]	Speed: 644.421341 samples/sec	accuracy=0.817516	lr=0.001514
Epoch[110] Batch [4899]	Speed: 623.452570 samples/sec	accuracy=0.817479	lr=0.001511
Epoch[110] Batch [4949]	Speed: 623.081076 samples/sec	accuracy=0.817412	lr=0.001507
Epoch[110] Batch [4999]	Speed: 658.987132 samples/sec	accuracy=0.817398	lr=0.001504
[Epoch 110] training: accuracy=0.817411
[Epoch 110] speed: 634 samples/sec	time cost: 2043.281575
[Epoch 110] validation: err-top1=0.214002 err-top5=0.055389
Epoch[111] Batch [49]	Speed: 625.610152 samples/sec	accuracy=0.821953	lr=0.001500
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Epoch[111] Batch [4499]	Speed: 639.480646 samples/sec	accuracy=0.821872	lr=0.001219
Epoch[111] Batch [4549]	Speed: 657.874749 samples/sec	accuracy=0.821804	lr=0.001216
Epoch[111] Batch [4599]	Speed: 623.188763 samples/sec	accuracy=0.821862	lr=0.001213
Epoch[111] Batch [4649]	Speed: 650.860585 samples/sec	accuracy=0.821935	lr=0.001210
Epoch[111] Batch [4699]	Speed: 684.225539 samples/sec	accuracy=0.821926	lr=0.001207
Epoch[111] Batch [4749]	Speed: 624.450312 samples/sec	accuracy=0.821897	lr=0.001204
Epoch[111] Batch [4799]	Speed: 636.652006 samples/sec	accuracy=0.821947	lr=0.001201
Epoch[111] Batch [4849]	Speed: 632.356176 samples/sec	accuracy=0.821894	lr=0.001198
Epoch[111] Batch [4899]	Speed: 659.268370 samples/sec	accuracy=0.821948	lr=0.001196
Epoch[111] Batch [4949]	Speed: 646.086949 samples/sec	accuracy=0.821941	lr=0.001193
Epoch[111] Batch [4999]	Speed: 643.071016 samples/sec	accuracy=0.821870	lr=0.001190
[Epoch 111] training: accuracy=0.821868
[Epoch 111] speed: 635 samples/sec	time cost: 2038.979094
[Epoch 111] validation: err-top1=0.212280 err-top5=0.055308
Epoch[112] Batch [49]	Speed: 614.109749 samples/sec	accuracy=0.823359	lr=0.001186
Epoch[112] Batch [99]	Speed: 622.785187 samples/sec	accuracy=0.826289	lr=0.001183
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Epoch[112] Batch [4999]	Speed: 619.331758 samples/sec	accuracy=0.825770	lr=0.000912
[Epoch 112] training: accuracy=0.825787
[Epoch 112] speed: 632 samples/sec	time cost: 2049.024452
[Epoch 112] validation: err-top1=0.210778 err-top5=0.054867
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Epoch[113] Batch [4799]	Speed: 641.947766 samples/sec	accuracy=0.828893	lr=0.000679
Epoch[113] Batch [4849]	Speed: 646.895227 samples/sec	accuracy=0.828911	lr=0.000677
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Epoch[113] Batch [4999]	Speed: 671.168031 samples/sec	accuracy=0.828917	lr=0.000670
[Epoch 113] training: accuracy=0.828925
[Epoch 113] speed: 634 samples/sec	time cost: 2043.847158
[Epoch 113] validation: err-top1=0.209916 err-top5=0.054607
Epoch[114] Batch [49]	Speed: 626.307541 samples/sec	accuracy=0.831875	lr=0.000668
Epoch[114] Batch [99]	Speed: 623.897211 samples/sec	accuracy=0.831445	lr=0.000666
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Epoch[114] Batch [4999]	Speed: 644.497859 samples/sec	accuracy=0.832137	lr=0.000466
[Epoch 114] training: accuracy=0.832112
[Epoch 114] speed: 635 samples/sec	time cost: 2041.114103
[Epoch 114] validation: err-top1=0.208674 err-top5=0.054788
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[Epoch 115] training: accuracy=0.834440
[Epoch 115] speed: 635 samples/sec	time cost: 2039.068756
[Epoch 115] validation: err-top1=0.208367 err-top5=0.053910
Epoch[116] Batch [49]	Speed: 589.707339 samples/sec	accuracy=0.833594	lr=0.000297
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Epoch[116] Batch [4799]	Speed: 654.080822 samples/sec	accuracy=0.835522	lr=0.000172
Epoch[116] Batch [4849]	Speed: 655.849421 samples/sec	accuracy=0.835573	lr=0.000171
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Epoch[116] Batch [4999]	Speed: 635.002278 samples/sec	accuracy=0.835577	lr=0.000168
[Epoch 116] training: accuracy=0.835592
[Epoch 116] speed: 633 samples/sec	time cost: 2047.585932
[Epoch 116] validation: err-top1=0.207792 err-top5=0.054567
Epoch[117] Batch [49]	Speed: 601.953809 samples/sec	accuracy=0.835938	lr=0.000167
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Epoch[117] Batch [4649]	Speed: 641.405155 samples/sec	accuracy=0.837273	lr=0.000080
Epoch[117] Batch [4699]	Speed: 644.513790 samples/sec	accuracy=0.837258	lr=0.000079
Epoch[117] Batch [4749]	Speed: 655.138515 samples/sec	accuracy=0.837285	lr=0.000078
Epoch[117] Batch [4799]	Speed: 648.620131 samples/sec	accuracy=0.837345	lr=0.000078
Epoch[117] Batch [4849]	Speed: 615.860368 samples/sec	accuracy=0.837329	lr=0.000077
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Epoch[117] Batch [4999]	Speed: 674.697826 samples/sec	accuracy=0.837363	lr=0.000075
[Epoch 117] training: accuracy=0.837375
[Epoch 117] speed: 635 samples/sec	time cost: 2040.721322
[Epoch 117] validation: err-top1=0.208494 err-top5=0.053405
Epoch[118] Batch [49]	Speed: 621.619097 samples/sec	accuracy=0.837812	lr=0.000074
Epoch[118] Batch [99]	Speed: 634.973205 samples/sec	accuracy=0.838516	lr=0.000073
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Epoch[118] Batch [4449]	Speed: 607.966062 samples/sec	accuracy=0.838724	lr=0.000023
Epoch[118] Batch [4499]	Speed: 621.331900 samples/sec	accuracy=0.838701	lr=0.000023
Epoch[118] Batch [4549]	Speed: 613.862266 samples/sec	accuracy=0.838741	lr=0.000022
Epoch[118] Batch [4599]	Speed: 633.578676 samples/sec	accuracy=0.838670	lr=0.000022
Epoch[118] Batch [4649]	Speed: 629.138768 samples/sec	accuracy=0.838622	lr=0.000021
Epoch[118] Batch [4699]	Speed: 644.640739 samples/sec	accuracy=0.838593	lr=0.000021
Epoch[118] Batch [4749]	Speed: 613.397711 samples/sec	accuracy=0.838558	lr=0.000021
Epoch[118] Batch [4799]	Speed: 612.706559 samples/sec	accuracy=0.838594	lr=0.000020
Epoch[118] Batch [4849]	Speed: 620.718921 samples/sec	accuracy=0.838597	lr=0.000020
Epoch[118] Batch [4899]	Speed: 609.648410 samples/sec	accuracy=0.838590	lr=0.000019
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Epoch[118] Batch [4999]	Speed: 642.131042 samples/sec	accuracy=0.838602	lr=0.000019
[Epoch 118] training: accuracy=0.838611
[Epoch 118] speed: 629 samples/sec	time cost: 2059.682169
[Epoch 118] validation: err-top1=0.208446 err-top5=0.053831
Epoch[119] Batch [49]	Speed: 623.559971 samples/sec	accuracy=0.835547	lr=0.000018
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Epoch[119] Batch [3249]	Speed: 628.445186 samples/sec	accuracy=0.838960	lr=0.000002
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Epoch[119] Batch [3349]	Speed: 655.032036 samples/sec	accuracy=0.838846	lr=0.000002
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Epoch[119] Batch [3499]	Speed: 658.659125 samples/sec	accuracy=0.838728	lr=0.000002
Epoch[119] Batch [3549]	Speed: 593.518758 samples/sec	accuracy=0.838753	lr=0.000002
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Epoch[119] Batch [3899]	Speed: 609.629276 samples/sec	accuracy=0.838584	lr=0.000001
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Epoch[119] Batch [4449]	Speed: 650.673081 samples/sec	accuracy=0.838642	lr=0.000000
Epoch[119] Batch [4499]	Speed: 632.564609 samples/sec	accuracy=0.838628	lr=0.000000
Epoch[119] Batch [4549]	Speed: 623.400794 samples/sec	accuracy=0.838647	lr=0.000000
Epoch[119] Batch [4599]	Speed: 626.255874 samples/sec	accuracy=0.838657	lr=0.000000
Epoch[119] Batch [4649]	Speed: 621.416360 samples/sec	accuracy=0.838655	lr=0.000000
Epoch[119] Batch [4699]	Speed: 624.858100 samples/sec	accuracy=0.838684	lr=0.000000
Epoch[119] Batch [4749]	Speed: 632.597286 samples/sec	accuracy=0.838618	lr=0.000000
Epoch[119] Batch [4799]	Speed: 644.417094 samples/sec	accuracy=0.838599	lr=0.000000
Epoch[119] Batch [4849]	Speed: 626.746842 samples/sec	accuracy=0.838662	lr=0.000000
Epoch[119] Batch [4899]	Speed: 632.655342 samples/sec	accuracy=0.838643	lr=0.000000
Epoch[119] Batch [4949]	Speed: 610.678082 samples/sec	accuracy=0.838668	lr=0.000000
Epoch[119] Batch [4999]	Speed: 658.293351 samples/sec	accuracy=0.838689	lr=0.000000
[Epoch 119] training: accuracy=0.838699
[Epoch 119] speed: 626 samples/sec	time cost: 2068.255164
[Epoch 119] validation: err-top1=0.207792 err-top5=0.053466