INFO:root:Namespace(batch_size=128, drop_rate=0.0, lr=0.1, lr_decay=0.1, lr_decay_epoch='100,150', lr_decay_period=0, mode='hybrid', model='cifar_resnet110_v2', momentum=0.9, num_epochs=200, num_gpus=1, num_workers=2, resume_from=None, save_dir='params', save_period=10, save_plot_dir='.', wd=0.0001)
[21:48:37] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:107: Running performance tests to find the best convolution algorithm, this can take a while... (setting env variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
INFO:root:[Epoch 0] train=0.473598 val=0.461600 loss=1.428271 time: 57.949105
INFO:root:[Epoch 1] train=0.672316 val=0.671600 loss=0.920287 time: 60.982816
INFO:root:[Epoch 2] train=0.742648 val=0.661200 loss=0.736463 time: 56.873630
INFO:root:[Epoch 3] train=0.778906 val=0.748900 loss=0.635767 time: 57.463883
INFO:root:[Epoch 4] train=0.802103 val=0.799100 loss=0.571779 time: 57.900493
INFO:root:[Epoch 5] train=0.820092 val=0.794400 loss=0.522603 time: 60.854111
INFO:root:[Epoch 6] train=0.833333 val=0.756200 loss=0.481844 time: 60.254611
INFO:root:[Epoch 7] train=0.844852 val=0.810600 loss=0.448899 time: 59.039970
INFO:root:[Epoch 8] train=0.853606 val=0.819800 loss=0.427216 time: 62.388456
INFO:root:[Epoch 9] train=0.859956 val=0.829300 loss=0.404207 time: 57.972297
INFO:root:[Epoch 10] train=0.866767 val=0.818200 loss=0.383755 time: 61.433780
INFO:root:[Epoch 11] train=0.873057 val=0.822800 loss=0.366134 time: 56.704709
INFO:root:[Epoch 12] train=0.880789 val=0.850500 loss=0.348207 time: 58.162212
INFO:root:[Epoch 13] train=0.883293 val=0.852700 loss=0.334211 time: 58.347650
INFO:root:[Epoch 14] train=0.887680 val=0.818600 loss=0.323679 time: 60.878748
INFO:root:[Epoch 15] train=0.891166 val=0.837900 loss=0.315467 time: 62.443568
INFO:root:[Epoch 16] train=0.894171 val=0.848500 loss=0.302570 time: 57.382874
INFO:root:[Epoch 17] train=0.899459 val=0.844900 loss=0.290568 time: 58.618785
INFO:root:[Epoch 18] train=0.899840 val=0.869000 loss=0.287240 time: 58.347784
INFO:root:[Epoch 19] train=0.902885 val=0.848700 loss=0.281088 time: 59.241853
INFO:root:[Epoch 20] train=0.903826 val=0.874500 loss=0.275575 time: 57.636861
INFO:root:[Epoch 21] train=0.906450 val=0.880900 loss=0.266060 time: 58.158768
INFO:root:[Epoch 22] train=0.909515 val=0.860300 loss=0.260003 time: 57.873705
INFO:root:[Epoch 23] train=0.911098 val=0.870400 loss=0.256939 time: 59.604836
INFO:root:[Epoch 24] train=0.913442 val=0.871800 loss=0.249789 time: 58.873778
INFO:root:[Epoch 25] train=0.916306 val=0.881200 loss=0.243309 time: 59.797326
INFO:root:[Epoch 26] train=0.916546 val=0.859900 loss=0.240232 time: 61.132922
INFO:root:[Epoch 27] train=0.920232 val=0.870900 loss=0.229139 time: 61.517086
INFO:root:[Epoch 28] train=0.916887 val=0.863600 loss=0.237870 time: 59.646824
INFO:root:[Epoch 29] train=0.920052 val=0.876000 loss=0.227297 time: 59.762588
INFO:root:[Epoch 30] train=0.922496 val=0.865500 loss=0.222194 time: 60.087432
INFO:root:[Epoch 31] train=0.921895 val=0.881200 loss=0.224904 time: 60.200475
INFO:root:[Epoch 32] train=0.924018 val=0.879300 loss=0.220930 time: 57.976933
INFO:root:[Epoch 33] train=0.924239 val=0.856800 loss=0.215239 time: 59.807428
INFO:root:[Epoch 34] train=0.924038 val=0.885600 loss=0.215091 time: 57.898086
INFO:root:[Epoch 35] train=0.923938 val=0.876500 loss=0.214955 time: 57.996159
INFO:root:[Epoch 36] train=0.926022 val=0.882900 loss=0.209434 time: 57.816369
INFO:root:[Epoch 37] train=0.927564 val=0.853800 loss=0.207530 time: 58.058006
INFO:root:[Epoch 38] train=0.930048 val=0.876300 loss=0.200102 time: 59.301496
INFO:root:[Epoch 39] train=0.930829 val=0.885200 loss=0.198722 time: 60.485463
INFO:root:[Epoch 40] train=0.931090 val=0.876900 loss=0.197454 time: 61.325932
INFO:root:[Epoch 41] train=0.930509 val=0.873300 loss=0.198275 time: 58.267452
INFO:root:[Epoch 42] train=0.932131 val=0.841900 loss=0.195421 time: 57.374234
INFO:root:[Epoch 43] train=0.934675 val=0.879900 loss=0.186082 time: 57.537664
INFO:root:[Epoch 44] train=0.933614 val=0.857100 loss=0.189886 time: 60.188124
INFO:root:[Epoch 45] train=0.934075 val=0.881100 loss=0.190479 time: 59.264221
INFO:root:[Epoch 46] train=0.934375 val=0.882400 loss=0.187264 time: 56.909123
INFO:root:[Epoch 47] train=0.933834 val=0.889600 loss=0.188184 time: 57.450553
INFO:root:[Epoch 48] train=0.936939 val=0.876700 loss=0.181223 time: 59.967866
INFO:root:[Epoch 49] train=0.936518 val=0.875600 loss=0.180543 time: 57.486720
INFO:root:[Epoch 50] train=0.936198 val=0.890200 loss=0.181853 time: 57.367887
INFO:root:[Epoch 51] train=0.938802 val=0.871900 loss=0.176775 time: 59.743495
INFO:root:[Epoch 52] train=0.937320 val=0.888500 loss=0.179802 time: 60.963740
INFO:root:[Epoch 53] train=0.937500 val=0.879200 loss=0.178095 time: 57.445270
INFO:root:[Epoch 54] train=0.936959 val=0.840100 loss=0.178956 time: 66.985358
INFO:root:[Epoch 55] train=0.937440 val=0.884600 loss=0.177852 time: 57.982378
INFO:root:[Epoch 56] train=0.936899 val=0.893600 loss=0.177296 time: 60.667304
INFO:root:[Epoch 57] train=0.940785 val=0.891900 loss=0.167763 time: 57.002365
INFO:root:[Epoch 58] train=0.942688 val=0.871100 loss=0.167302 time: 58.057482
INFO:root:[Epoch 59] train=0.939183 val=0.884600 loss=0.172032 time: 59.915868
INFO:root:[Epoch 60] train=0.941446 val=0.889600 loss=0.167899 time: 59.564607
INFO:root:[Epoch 61] train=0.941066 val=0.891300 loss=0.167564 time: 58.561421
INFO:root:[Epoch 62] train=0.941767 val=0.881000 loss=0.166481 time: 59.378979
INFO:root:[Epoch 63] train=0.943409 val=0.886400 loss=0.162796 time: 57.529740
INFO:root:[Epoch 64] train=0.941366 val=0.886600 loss=0.166591 time: 60.201238
INFO:root:[Epoch 65] train=0.944772 val=0.873800 loss=0.158947 time: 57.686598
INFO:root:[Epoch 66] train=0.942448 val=0.889900 loss=0.164077 time: 56.763921
INFO:root:[Epoch 67] train=0.941827 val=0.872800 loss=0.164456 time: 59.725118
INFO:root:[Epoch 68] train=0.944571 val=0.898400 loss=0.159157 time: 58.200405
INFO:root:[Epoch 69] train=0.944992 val=0.878700 loss=0.157063 time: 59.212173
INFO:root:[Epoch 70] train=0.944651 val=0.890500 loss=0.158336 time: 57.002796
INFO:root:[Epoch 71] train=0.944952 val=0.885700 loss=0.156404 time: 57.970676
INFO:root:[Epoch 72] train=0.945693 val=0.893000 loss=0.155400 time: 60.165212
INFO:root:[Epoch 73] train=0.943690 val=0.882100 loss=0.161578 time: 60.560928
INFO:root:[Epoch 74] train=0.945853 val=0.873800 loss=0.152247 time: 57.780874
INFO:root:[Epoch 75] train=0.944712 val=0.884800 loss=0.159075 time: 58.406782
INFO:root:[Epoch 76] train=0.944431 val=0.885900 loss=0.158564 time: 57.196479
INFO:root:[Epoch 77] train=0.948738 val=0.877400 loss=0.145904 time: 59.159842
INFO:root:[Epoch 78] train=0.944071 val=0.877500 loss=0.157672 time: 60.787005
INFO:root:[Epoch 79] train=0.946715 val=0.882000 loss=0.152993 time: 59.312307
INFO:root:[Epoch 80] train=0.946675 val=0.881100 loss=0.150798 time: 62.560454
INFO:root:[Epoch 81] train=0.944772 val=0.897100 loss=0.156274 time: 58.435123
INFO:root:[Epoch 82] train=0.947736 val=0.867600 loss=0.148127 time: 60.318092
INFO:root:[Epoch 83] train=0.946575 val=0.894200 loss=0.153337 time: 58.403970
INFO:root:[Epoch 84] train=0.948337 val=0.884400 loss=0.147166 time: 60.926208
INFO:root:[Epoch 85] train=0.946374 val=0.895500 loss=0.151759 time: 59.229638
INFO:root:[Epoch 86] train=0.945893 val=0.866400 loss=0.152515 time: 57.263889
INFO:root:[Epoch 87] train=0.947576 val=0.892200 loss=0.151116 time: 60.376845
INFO:root:[Epoch 88] train=0.950861 val=0.888500 loss=0.141282 time: 59.990622
INFO:root:[Epoch 89] train=0.949058 val=0.882800 loss=0.144711 time: 60.763241
INFO:root:[Epoch 90] train=0.947656 val=0.876500 loss=0.147133 time: 59.214983
INFO:root:[Epoch 91] train=0.948938 val=0.887200 loss=0.145427 time: 59.015237
INFO:root:[Epoch 92] train=0.949079 val=0.887700 loss=0.146698 time: 58.731408
INFO:root:[Epoch 93] train=0.949880 val=0.891000 loss=0.142505 time: 58.103575
INFO:root:[Epoch 94] train=0.950701 val=0.887700 loss=0.142150 time: 57.857036
INFO:root:[Epoch 95] train=0.947496 val=0.880700 loss=0.149917 time: 57.753356
INFO:root:[Epoch 96] train=0.950921 val=0.894800 loss=0.142404 time: 57.568325
INFO:root:[Epoch 97] train=0.951182 val=0.885300 loss=0.140579 time: 60.125012
INFO:root:[Epoch 98] train=0.948698 val=0.897400 loss=0.147046 time: 56.916132
INFO:root:[Epoch 99] train=0.948918 val=0.890100 loss=0.144967 time: 56.933578
INFO:root:[Epoch 100] train=0.978325 val=0.933300 loss=0.067056 time: 59.480672
INFO:root:[Epoch 101] train=0.987460 val=0.935900 loss=0.040795 time: 57.981594
INFO:root:[Epoch 102] train=0.989343 val=0.936500 loss=0.033314 time: 56.943626
INFO:root:[Epoch 103] train=0.991767 val=0.938200 loss=0.027965 time: 57.177341
INFO:root:[Epoch 104] train=0.992808 val=0.938600 loss=0.023833 time: 60.555840
INFO:root:[Epoch 105] train=0.994291 val=0.937800 loss=0.020456 time: 60.077476
INFO:root:[Epoch 106] train=0.995313 val=0.936400 loss=0.017534 time: 57.983260
INFO:root:[Epoch 107] train=0.995433 val=0.939700 loss=0.016540 time: 58.375436
INFO:root:[Epoch 108] train=0.995713 val=0.936600 loss=0.015345 time: 60.224379
INFO:root:[Epoch 109] train=0.995793 val=0.938100 loss=0.014982 time: 57.092103
INFO:root:[Epoch 110] train=0.995994 val=0.937300 loss=0.013547 time: 59.960498
INFO:root:[Epoch 111] train=0.996494 val=0.937300 loss=0.012445 time: 58.830368
INFO:root:[Epoch 112] train=0.996715 val=0.937800 loss=0.011490 time: 59.148540
INFO:root:[Epoch 113] train=0.996615 val=0.939000 loss=0.011222 time: 58.683987
INFO:root:[Epoch 114] train=0.997636 val=0.937400 loss=0.009326 time: 58.811727
INFO:root:[Epoch 115] train=0.997196 val=0.938200 loss=0.009789 time: 58.172976
INFO:root:[Epoch 116] train=0.997316 val=0.936400 loss=0.009671 time: 59.158751
INFO:root:[Epoch 117] train=0.997817 val=0.936800 loss=0.008164 time: 58.644106
INFO:root:[Epoch 118] train=0.998097 val=0.939900 loss=0.007952 time: 59.378270
INFO:root:[Epoch 119] train=0.998117 val=0.938900 loss=0.007676 time: 57.944185
INFO:root:[Epoch 120] train=0.998498 val=0.938200 loss=0.007112 time: 59.000065
INFO:root:[Epoch 121] train=0.998297 val=0.936800 loss=0.006947 time: 61.065335
INFO:root:[Epoch 122] train=0.998197 val=0.937900 loss=0.006959 time: 59.670094
INFO:root:[Epoch 123] train=0.998758 val=0.937700 loss=0.006128 time: 60.990517
INFO:root:[Epoch 124] train=0.998758 val=0.938700 loss=0.005734 time: 58.396631
INFO:root:[Epoch 125] train=0.998758 val=0.938600 loss=0.005653 time: 58.896625
INFO:root:[Epoch 126] train=0.998417 val=0.938200 loss=0.006079 time: 57.434055
INFO:root:[Epoch 127] train=0.998598 val=0.939100 loss=0.005937 time: 58.191738
INFO:root:[Epoch 128] train=0.998357 val=0.939200 loss=0.006340 time: 57.078708
INFO:root:[Epoch 129] train=0.998538 val=0.939200 loss=0.005590 time: 58.861937
INFO:root:[Epoch 130] train=0.998638 val=0.939600 loss=0.005605 time: 57.368922
INFO:root:[Epoch 131] train=0.998377 val=0.938300 loss=0.006162 time: 58.406558
INFO:root:[Epoch 132] train=0.999159 val=0.938800 loss=0.004452 time: 58.148598
INFO:root:[Epoch 133] train=0.998838 val=0.937400 loss=0.004958 time: 58.877033
INFO:root:[Epoch 134] train=0.998718 val=0.937200 loss=0.004663 time: 58.781111
INFO:root:[Epoch 135] train=0.998738 val=0.938500 loss=0.005010 time: 57.622572
INFO:root:[Epoch 136] train=0.998437 val=0.938400 loss=0.006010 time: 59.019783
INFO:root:[Epoch 137] train=0.998798 val=0.937700 loss=0.004866 time: 58.845146
INFO:root:[Epoch 138] train=0.999139 val=0.939900 loss=0.004506 time: 58.238715
INFO:root:[Epoch 139] train=0.998818 val=0.940000 loss=0.004752 time: 59.067493
INFO:root:[Epoch 140] train=0.998818 val=0.940700 loss=0.004848 time: 57.135881
INFO:root:[Epoch 141] train=0.998998 val=0.938500 loss=0.004248 time: 57.888883
INFO:root:[Epoch 142] train=0.999099 val=0.939500 loss=0.004140 time: 58.918099
INFO:root:[Epoch 143] train=0.998998 val=0.939600 loss=0.004031 time: 60.136984
INFO:root:[Epoch 144] train=0.999079 val=0.938900 loss=0.003996 time: 59.833028
INFO:root:[Epoch 145] train=0.999339 val=0.939800 loss=0.003260 time: 58.318021
INFO:root:[Epoch 146] train=0.998798 val=0.939600 loss=0.004459 time: 57.460288
INFO:root:[Epoch 147] train=0.998838 val=0.937300 loss=0.004757 time: 59.963775
INFO:root:[Epoch 148] train=0.999259 val=0.938300 loss=0.003627 time: 57.873523
INFO:root:[Epoch 149] train=0.998738 val=0.938900 loss=0.004589 time: 60.215890
INFO:root:[Epoch 150] train=0.999018 val=0.940500 loss=0.003773 time: 57.820271
INFO:root:[Epoch 151] train=0.999319 val=0.940800 loss=0.003361 time: 57.791474
INFO:root:[Epoch 152] train=0.999279 val=0.941200 loss=0.003099 time: 62.446680
INFO:root:[Epoch 153] train=0.999339 val=0.940700 loss=0.002975 time: 59.164999
INFO:root:[Epoch 154] train=0.999459 val=0.942100 loss=0.002920 time: 58.076027
INFO:root:[Epoch 155] train=0.999539 val=0.942300 loss=0.002633 time: 62.297961
INFO:root:[Epoch 156] train=0.999459 val=0.941800 loss=0.002645 time: 57.906290
INFO:root:[Epoch 157] train=0.999519 val=0.942100 loss=0.002649 time: 57.660583
INFO:root:[Epoch 158] train=0.999399 val=0.942500 loss=0.002600 time: 57.633093
INFO:root:[Epoch 159] train=0.999559 val=0.941900 loss=0.002358 time: 59.287751
INFO:root:[Epoch 160] train=0.999579 val=0.940700 loss=0.002395 time: 57.493443
INFO:root:[Epoch 161] train=0.999539 val=0.941600 loss=0.002615 time: 58.389180
INFO:root:[Epoch 162] train=0.999519 val=0.942300 loss=0.002380 time: 59.146956
INFO:root:[Epoch 163] train=0.999579 val=0.941900 loss=0.002318 time: 58.435192
INFO:root:[Epoch 164] train=0.999399 val=0.941700 loss=0.002753 time: 59.552516
INFO:root:[Epoch 165] train=0.999619 val=0.941100 loss=0.002194 time: 59.148080
INFO:root:[Epoch 166] train=0.999599 val=0.941500 loss=0.002178 time: 58.880552
INFO:root:[Epoch 167] train=0.999700 val=0.941400 loss=0.002086 time: 58.396296
INFO:root:[Epoch 168] train=0.999579 val=0.941900 loss=0.002272 time: 57.271844
INFO:root:[Epoch 169] train=0.999539 val=0.941200 loss=0.002252 time: 57.679778
INFO:root:[Epoch 170] train=0.999539 val=0.942300 loss=0.002403 time: 57.721264
INFO:root:[Epoch 171] train=0.999559 val=0.941400 loss=0.002400 time: 59.152108
INFO:root:[Epoch 172] train=0.999800 val=0.941800 loss=0.001895 time: 57.452343
INFO:root:[Epoch 173] train=0.999760 val=0.941000 loss=0.002073 time: 56.597687
INFO:root:[Epoch 174] train=0.999579 val=0.941400 loss=0.002126 time: 58.649846
INFO:root:[Epoch 175] train=0.999619 val=0.940600 loss=0.002258 time: 58.650191
INFO:root:[Epoch 176] train=0.999720 val=0.940200 loss=0.001992 time: 60.623768
INFO:root:[Epoch 177] train=0.999519 val=0.941100 loss=0.002099 time: 58.548954
INFO:root:[Epoch 178] train=0.999720 val=0.941000 loss=0.001950 time: 57.710021
INFO:root:[Epoch 179] train=0.999820 val=0.941100 loss=0.001877 time: 58.857271
INFO:root:[Epoch 180] train=0.999659 val=0.939700 loss=0.002144 time: 57.893411
INFO:root:[Epoch 181] train=0.999740 val=0.941700 loss=0.001887 time: 58.320577
INFO:root:[Epoch 182] train=0.999760 val=0.941100 loss=0.001907 time: 59.229154
INFO:root:[Epoch 183] train=0.999780 val=0.940400 loss=0.001767 time: 58.177949
INFO:root:[Epoch 184] train=0.999860 val=0.941400 loss=0.001649 time: 59.663200
INFO:root:[Epoch 185] train=0.999679 val=0.941200 loss=0.001946 time: 58.228571
INFO:root:[Epoch 186] train=0.999740 val=0.941000 loss=0.001934 time: 59.602502
INFO:root:[Epoch 187] train=0.999740 val=0.941600 loss=0.001789 time: 60.049539
INFO:root:[Epoch 188] train=0.999800 val=0.940000 loss=0.001722 time: 60.405763
INFO:root:[Epoch 189] train=0.999639 val=0.941400 loss=0.001887 time: 58.257117
INFO:root:[Epoch 190] train=0.999639 val=0.941200 loss=0.002100 time: 58.814007
INFO:root:[Epoch 191] train=0.999679 val=0.940400 loss=0.001957 time: 59.384787
INFO:root:[Epoch 192] train=0.999679 val=0.939700 loss=0.002029 time: 59.211630
INFO:root:[Epoch 193] train=0.999760 val=0.941100 loss=0.001783 time: 59.249755
INFO:root:[Epoch 194] train=0.999840 val=0.940100 loss=0.001630 time: 58.436918
INFO:root:[Epoch 195] train=0.999679 val=0.940900 loss=0.001921 time: 59.364427
INFO:root:[Epoch 196] train=0.999700 val=0.939600 loss=0.001625 time: 59.446809
INFO:root:[Epoch 197] train=0.999619 val=0.941100 loss=0.001798 time: 59.342611
INFO:root:[Epoch 198] train=0.999659 val=0.940800 loss=0.001887 time: 59.287828
INFO:root:[Epoch 199] train=0.999679 val=0.940500 loss=0.001884 time: 58.314472