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_v1', momentum=0.9, num_epochs=200, num_gpus=1, num_workers=4, resume_from=None, save_dir='params', save_period=10, save_plot_dir='.', wd=0.0001)
[04:58:48] 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=0.104067 val=0.116500 loss=2.499243 time: 60.370274
INFO:root:[Epoch 1] train=0.113822 val=0.173300 loss=2.282750 time: 56.693866
INFO:root:[Epoch 2] train=0.278906 val=0.339500 loss=1.902463 time: 55.932017
INFO:root:[Epoch 3] train=0.395633 val=0.405800 loss=1.643934 time: 59.492170
INFO:root:[Epoch 4] train=0.458353 val=0.490200 loss=1.483419 time: 55.750688
INFO:root:[Epoch 5] train=0.508133 val=0.490600 loss=1.354449 time: 56.253702
INFO:root:[Epoch 6] train=0.548618 val=0.577800 loss=1.247302 time: 56.113920
INFO:root:[Epoch 7] train=0.603646 val=0.604200 loss=1.109237 time: 56.398431
INFO:root:[Epoch 8] train=0.657833 val=0.530800 loss=0.965835 time: 57.136892
INFO:root:[Epoch 9] train=0.700240 val=0.667600 loss=0.851265 time: 56.410130
INFO:root:[Epoch 10] train=0.731951 val=0.710600 loss=0.767830 time: 56.288123
INFO:root:[Epoch 11] train=0.760236 val=0.748500 loss=0.690403 time: 56.985588
INFO:root:[Epoch 12] train=0.776963 val=0.751000 loss=0.637027 time: 55.443338
INFO:root:[Epoch 13] train=0.797977 val=0.765100 loss=0.582922 time: 58.230970
INFO:root:[Epoch 14] train=0.812059 val=0.743900 loss=0.544901 time: 57.439673
INFO:root:[Epoch 15] train=0.821735 val=0.793700 loss=0.519844 time: 56.644431
INFO:root:[Epoch 16] train=0.830769 val=0.811000 loss=0.485674 time: 55.508668
INFO:root:[Epoch 17] train=0.838622 val=0.814500 loss=0.467493 time: 56.030341
INFO:root:[Epoch 18] train=0.847436 val=0.798900 loss=0.442849 time: 56.671854
INFO:root:[Epoch 19] train=0.855028 val=0.802500 loss=0.421149 time: 55.497379
INFO:root:[Epoch 20] train=0.858854 val=0.818900 loss=0.407494 time: 56.326582
INFO:root:[Epoch 21] train=0.863301 val=0.830900 loss=0.399253 time: 56.740135
INFO:root:[Epoch 22] train=0.866066 val=0.806000 loss=0.384656 time: 59.676587
INFO:root:[Epoch 23] train=0.870753 val=0.825300 loss=0.372147 time: 59.775851
INFO:root:[Epoch 24] train=0.875180 val=0.826900 loss=0.359026 time: 59.689475
INFO:root:[Epoch 25] train=0.875641 val=0.810000 loss=0.356428 time: 58.969295
INFO:root:[Epoch 26] train=0.874219 val=0.822300 loss=0.361250 time: 55.168893
INFO:root:[Epoch 27] train=0.880509 val=0.832100 loss=0.342996 time: 55.305341
INFO:root:[Epoch 28] train=0.886458 val=0.830000 loss=0.324964 time: 56.120136
INFO:root:[Epoch 29] train=0.889784 val=0.837700 loss=0.317580 time: 58.450253
INFO:root:[Epoch 30] train=0.892087 val=0.821700 loss=0.310906 time: 58.534146
INFO:root:[Epoch 31] train=0.892889 val=0.834700 loss=0.308643 time: 56.085154
INFO:root:[Epoch 32] train=0.895032 val=0.831300 loss=0.300665 time: 56.140002
INFO:root:[Epoch 33] train=0.899539 val=0.852300 loss=0.291313 time: 56.427656
INFO:root:[Epoch 34] train=0.896294 val=0.843600 loss=0.298174 time: 57.529920
INFO:root:[Epoch 35] train=0.899259 val=0.866800 loss=0.288228 time: 56.218544
INFO:root:[Epoch 36] train=0.904567 val=0.849400 loss=0.274774 time: 60.691363
INFO:root:[Epoch 37] train=0.904407 val=0.844800 loss=0.274261 time: 59.746681
INFO:root:[Epoch 38] train=0.904467 val=0.835700 loss=0.273743 time: 58.417671
INFO:root:[Epoch 39] train=0.909956 val=0.852400 loss=0.264212 time: 57.083480
INFO:root:[Epoch 40] train=0.906651 val=0.862900 loss=0.267801 time: 56.758820
INFO:root:[Epoch 41] train=0.911078 val=0.869700 loss=0.258405 time: 56.572958
INFO:root:[Epoch 42] train=0.910597 val=0.860100 loss=0.259294 time: 56.407476
INFO:root:[Epoch 43] train=0.912360 val=0.829900 loss=0.252825 time: 56.475201
INFO:root:[Epoch 44] train=0.913021 val=0.824000 loss=0.250530 time: 55.897872
INFO:root:[Epoch 45] train=0.914163 val=0.840700 loss=0.248818 time: 56.411832
INFO:root:[Epoch 46] train=0.916326 val=0.848400 loss=0.242743 time: 56.222702
INFO:root:[Epoch 47] train=0.916126 val=0.854400 loss=0.241203 time: 56.106460
INFO:root:[Epoch 48] train=0.917969 val=0.859500 loss=0.235977 time: 56.159456
INFO:root:[Epoch 49] train=0.917748 val=0.835600 loss=0.234638 time: 56.522168
INFO:root:[Epoch 50] train=0.917909 val=0.860300 loss=0.236066 time: 57.766861
INFO:root:[Epoch 51] train=0.919671 val=0.862500 loss=0.232866 time: 56.661246
INFO:root:[Epoch 52] train=0.919091 val=0.840700 loss=0.232158 time: 56.930452
INFO:root:[Epoch 53] train=0.922095 val=0.864600 loss=0.222840 time: 57.215661
INFO:root:[Epoch 54] train=0.923277 val=0.871400 loss=0.220018 time: 56.418728
INFO:root:[Epoch 55] train=0.922316 val=0.848400 loss=0.223533 time: 56.237329
INFO:root:[Epoch 56] train=0.922997 val=0.861000 loss=0.221000 time: 59.482514
INFO:root:[Epoch 57] train=0.922356 val=0.844500 loss=0.218272 time: 59.886784
INFO:root:[Epoch 58] train=0.923778 val=0.860200 loss=0.216076 time: 58.367580
INFO:root:[Epoch 59] train=0.925721 val=0.871100 loss=0.212171 time: 56.170247
INFO:root:[Epoch 60] train=0.924579 val=0.869300 loss=0.216461 time: 56.040217
INFO:root:[Epoch 61] train=0.925962 val=0.852700 loss=0.208438 time: 55.389114
INFO:root:[Epoch 62] train=0.925461 val=0.870900 loss=0.214206 time: 58.527531
INFO:root:[Epoch 63] train=0.926202 val=0.864800 loss=0.206694 time: 57.000882
INFO:root:[Epoch 64] train=0.927704 val=0.862900 loss=0.205818 time: 56.227458
INFO:root:[Epoch 65] train=0.926322 val=0.852200 loss=0.208791 time: 55.910366
INFO:root:[Epoch 66] train=0.928886 val=0.862700 loss=0.203464 time: 55.765368
INFO:root:[Epoch 67] train=0.929227 val=0.869900 loss=0.202675 time: 56.176372
INFO:root:[Epoch 68] train=0.931030 val=0.860600 loss=0.197253 time: 56.772560
INFO:root:[Epoch 69] train=0.928506 val=0.849500 loss=0.200526 time: 55.966162
INFO:root:[Epoch 70] train=0.930068 val=0.874900 loss=0.198366 time: 56.469595
INFO:root:[Epoch 71] train=0.929728 val=0.846100 loss=0.199981 time: 56.100928
INFO:root:[Epoch 72] train=0.931070 val=0.878300 loss=0.194587 time: 56.409308
INFO:root:[Epoch 73] train=0.932813 val=0.866900 loss=0.190108 time: 56.010072
INFO:root:[Epoch 74] train=0.931711 val=0.863000 loss=0.193877 time: 56.163429
INFO:root:[Epoch 75] train=0.932332 val=0.877000 loss=0.193347 time: 56.284853
INFO:root:[Epoch 76] train=0.930970 val=0.885200 loss=0.193209 time: 55.847956
INFO:root:[Epoch 77] train=0.932792 val=0.865400 loss=0.190465 time: 56.651999
INFO:root:[Epoch 78] train=0.934415 val=0.871000 loss=0.186903 time: 56.666220
INFO:root:[Epoch 79] train=0.934054 val=0.840600 loss=0.190943 time: 55.857785
INFO:root:[Epoch 80] train=0.934716 val=0.875500 loss=0.185655 time: 56.011597
INFO:root:[Epoch 81] train=0.934475 val=0.877100 loss=0.186939 time: 56.532962
INFO:root:[Epoch 82] train=0.936038 val=0.868700 loss=0.185005 time: 58.621850
INFO:root:[Epoch 83] train=0.939042 val=0.862300 loss=0.179307 time: 59.900912
INFO:root:[Epoch 84] train=0.935877 val=0.861600 loss=0.180708 time: 56.883108
INFO:root:[Epoch 85] train=0.937159 val=0.882300 loss=0.178829 time: 55.920048
INFO:root:[Epoch 86] train=0.939663 val=0.887700 loss=0.176794 time: 56.888677
INFO:root:[Epoch 87] train=0.935397 val=0.887100 loss=0.184296 time: 56.340617
INFO:root:[Epoch 88] train=0.937380 val=0.884300 loss=0.177351 time: 58.988554
INFO:root:[Epoch 89] train=0.938762 val=0.882600 loss=0.174821 time: 59.204571
INFO:root:[Epoch 90] train=0.937280 val=0.871300 loss=0.176990 time: 59.497475
INFO:root:[Epoch 91] train=0.937300 val=0.869600 loss=0.181717 time: 59.052168
INFO:root:[Epoch 92] train=0.939163 val=0.880500 loss=0.173020 time: 59.109145
INFO:root:[Epoch 93] train=0.939403 val=0.874800 loss=0.175677 time: 59.382949
INFO:root:[Epoch 94] train=0.938982 val=0.865600 loss=0.177705 time: 58.311876
INFO:root:[Epoch 95] train=0.940184 val=0.880700 loss=0.173682 time: 56.413499
INFO:root:[Epoch 96] train=0.939964 val=0.860800 loss=0.171819 time: 56.656733
INFO:root:[Epoch 97] train=0.939964 val=0.882400 loss=0.173797 time: 56.308693
INFO:root:[Epoch 98] train=0.941867 val=0.848600 loss=0.168208 time: 57.078964
INFO:root:[Epoch 99] train=0.942468 val=0.885800 loss=0.167860 time: 56.255200
INFO:root:[Epoch 100] train=0.972115 val=0.920300 loss=0.086178 time: 55.977668
INFO:root:[Epoch 101] train=0.982973 val=0.922800 loss=0.056906 time: 56.044328
INFO:root:[Epoch 102] train=0.984475 val=0.922000 loss=0.049479 time: 56.149558
INFO:root:[Epoch 103] train=0.987360 val=0.922200 loss=0.041669 time: 56.681972
INFO:root:[Epoch 104] train=0.988241 val=0.924600 loss=0.038569 time: 56.589668
INFO:root:[Epoch 105] train=0.989904 val=0.923800 loss=0.033949 time: 57.488907
INFO:root:[Epoch 106] train=0.991466 val=0.925500 loss=0.030929 time: 59.898797
INFO:root:[Epoch 107] train=0.991266 val=0.925900 loss=0.028877 time: 58.780883
INFO:root:[Epoch 108] train=0.992448 val=0.924400 loss=0.026335 time: 58.374731
INFO:root:[Epoch 109] train=0.993089 val=0.923700 loss=0.024376 time: 58.347538
INFO:root:[Epoch 110] train=0.993690 val=0.924900 loss=0.022268 time: 58.417617
INFO:root:[Epoch 111] train=0.994391 val=0.924600 loss=0.020749 time: 58.372143
INFO:root:[Epoch 112] train=0.995172 val=0.927200 loss=0.019064 time: 58.455128
INFO:root:[Epoch 113] train=0.995132 val=0.926400 loss=0.018201 time: 59.289533
INFO:root:[Epoch 114] train=0.995713 val=0.927600 loss=0.016746 time: 56.887329
INFO:root:[Epoch 115] train=0.995933 val=0.924900 loss=0.015518 time: 56.034742
INFO:root:[Epoch 116] train=0.996254 val=0.925100 loss=0.015181 time: 56.211026
INFO:root:[Epoch 117] train=0.996174 val=0.926900 loss=0.014318 time: 56.476436
INFO:root:[Epoch 118] train=0.996334 val=0.925800 loss=0.013674 time: 56.139883
INFO:root:[Epoch 119] train=0.996534 val=0.926800 loss=0.013611 time: 55.561074
INFO:root:[Epoch 120] train=0.997216 val=0.925800 loss=0.012048 time: 57.056968
INFO:root:[Epoch 121] train=0.996615 val=0.923800 loss=0.012703 time: 59.454661
INFO:root:[Epoch 122] train=0.997476 val=0.928500 loss=0.011275 time: 59.452461
INFO:root:[Epoch 123] train=0.997376 val=0.925900 loss=0.010963 time: 58.302286
INFO:root:[Epoch 124] train=0.997536 val=0.927400 loss=0.010592 time: 57.368789
INFO:root:[Epoch 125] train=0.997456 val=0.928800 loss=0.010888 time: 57.256035
INFO:root:[Epoch 126] train=0.997676 val=0.927300 loss=0.009689 time: 56.006821
INFO:root:[Epoch 127] train=0.997977 val=0.926900 loss=0.009418 time: 56.724256
INFO:root:[Epoch 128] train=0.997756 val=0.926700 loss=0.009299 time: 56.212945
INFO:root:[Epoch 129] train=0.997977 val=0.926900 loss=0.009031 time: 55.479938
INFO:root:[Epoch 130] train=0.998057 val=0.925100 loss=0.008488 time: 56.496445
INFO:root:[Epoch 131] train=0.998217 val=0.926100 loss=0.007888 time: 58.414800
INFO:root:[Epoch 132] train=0.998117 val=0.926400 loss=0.008459 time: 59.499361
INFO:root:[Epoch 133] train=0.998317 val=0.926500 loss=0.007605 time: 59.718268
INFO:root:[Epoch 134] train=0.998057 val=0.926900 loss=0.007914 time: 56.751668
INFO:root:[Epoch 135] train=0.998377 val=0.927900 loss=0.007599 time: 56.391502
INFO:root:[Epoch 136] train=0.998277 val=0.927200 loss=0.007374 time: 56.880853
INFO:root:[Epoch 137] train=0.998758 val=0.927000 loss=0.006189 time: 56.274999
INFO:root:[Epoch 138] train=0.998538 val=0.929000 loss=0.007098 time: 56.579936
INFO:root:[Epoch 139] train=0.998818 val=0.927500 loss=0.006426 time: 58.712127
INFO:root:[Epoch 140] train=0.998918 val=0.928900 loss=0.006391 time: 56.175790
INFO:root:[Epoch 141] train=0.998618 val=0.926400 loss=0.006299 time: 56.006755
INFO:root:[Epoch 142] train=0.998558 val=0.926900 loss=0.006533 time: 56.131399
INFO:root:[Epoch 143] train=0.998578 val=0.928400 loss=0.006466 time: 59.464162
INFO:root:[Epoch 144] train=0.998838 val=0.929600 loss=0.005909 time: 59.233657
INFO:root:[Epoch 145] train=0.998738 val=0.927200 loss=0.006016 time: 58.768894
INFO:root:[Epoch 146] train=0.999139 val=0.929500 loss=0.005053 time: 58.604714
INFO:root:[Epoch 147] train=0.998678 val=0.928400 loss=0.006213 time: 59.949113
INFO:root:[Epoch 148] train=0.998958 val=0.928200 loss=0.005227 time: 56.602250
INFO:root:[Epoch 149] train=0.999079 val=0.928100 loss=0.004940 time: 55.821090
INFO:root:[Epoch 150] train=0.999139 val=0.928900 loss=0.004836 time: 55.679520
INFO:root:[Epoch 151] train=0.999139 val=0.928000 loss=0.004399 time: 59.535435
INFO:root:[Epoch 152] train=0.999339 val=0.927700 loss=0.004268 time: 59.304961
INFO:root:[Epoch 153] train=0.999299 val=0.929000 loss=0.004386 time: 57.233624
INFO:root:[Epoch 154] train=0.999319 val=0.928800 loss=0.004089 time: 55.872802
INFO:root:[Epoch 155] train=0.999379 val=0.929100 loss=0.003799 time: 55.763675
INFO:root:[Epoch 156] train=0.999379 val=0.929100 loss=0.004015 time: 56.040711
INFO:root:[Epoch 157] train=0.999499 val=0.929100 loss=0.003762 time: 55.771612
INFO:root:[Epoch 158] train=0.999479 val=0.930000 loss=0.003782 time: 55.344423
INFO:root:[Epoch 159] train=0.999519 val=0.928500 loss=0.003710 time: 55.654125
INFO:root:[Epoch 160] train=0.999299 val=0.929400 loss=0.004219 time: 55.779201
INFO:root:[Epoch 161] train=0.999479 val=0.929500 loss=0.003335 time: 56.039253
INFO:root:[Epoch 162] train=0.999579 val=0.929100 loss=0.003694 time: 56.657962
INFO:root:[Epoch 163] train=0.999459 val=0.928400 loss=0.003651 time: 56.747376
INFO:root:[Epoch 164] train=0.999279 val=0.928700 loss=0.003914 time: 56.682172
INFO:root:[Epoch 165] train=0.999659 val=0.929200 loss=0.003540 time: 56.420901
INFO:root:[Epoch 166] train=0.999700 val=0.928500 loss=0.003422 time: 57.114429
INFO:root:[Epoch 167] train=0.999539 val=0.928700 loss=0.003376 time: 58.979339
INFO:root:[Epoch 168] train=0.999319 val=0.927900 loss=0.003762 time: 56.169456
INFO:root:[Epoch 169] train=0.999499 val=0.929500 loss=0.003662 time: 56.986526
INFO:root:[Epoch 170] train=0.999700 val=0.929100 loss=0.003235 time: 59.550247
INFO:root:[Epoch 171] train=0.999339 val=0.929800 loss=0.003894 time: 55.925209
INFO:root:[Epoch 172] train=0.999579 val=0.930000 loss=0.003418 time: 56.109065
INFO:root:[Epoch 173] train=0.999559 val=0.930300 loss=0.003620 time: 56.389778
INFO:root:[Epoch 174] train=0.999479 val=0.929900 loss=0.003400 time: 56.539621
INFO:root:[Epoch 175] train=0.999639 val=0.928900 loss=0.003311 time: 56.405798
INFO:root:[Epoch 176] train=0.999479 val=0.930000 loss=0.003345 time: 56.295145
INFO:root:[Epoch 177] train=0.999499 val=0.929400 loss=0.003337 time: 56.437039
INFO:root:[Epoch 178] train=0.999619 val=0.929600 loss=0.003271 time: 55.991283
INFO:root:[Epoch 179] train=0.999740 val=0.929200 loss=0.003018 time: 55.917220
INFO:root:[Epoch 180] train=0.999619 val=0.929000 loss=0.003248 time: 56.110188
INFO:root:[Epoch 181] train=0.999419 val=0.929700 loss=0.003507 time: 56.022751
INFO:root:[Epoch 182] train=0.999479 val=0.928500 loss=0.003518 time: 55.931591
INFO:root:[Epoch 183] train=0.999579 val=0.928600 loss=0.003487 time: 56.184442
INFO:root:[Epoch 184] train=0.999559 val=0.928000 loss=0.003321 time: 56.239540
INFO:root:[Epoch 185] train=0.999599 val=0.928300 loss=0.003132 time: 56.391353
INFO:root:[Epoch 186] train=0.999559 val=0.928800 loss=0.003086 time: 58.805319
INFO:root:[Epoch 187] train=0.999539 val=0.929000 loss=0.003242 time: 56.588982
INFO:root:[Epoch 188] train=0.999639 val=0.929800 loss=0.003170 time: 56.204777
INFO:root:[Epoch 189] train=0.999519 val=0.928600 loss=0.003326 time: 58.507539
INFO:root:[Epoch 190] train=0.999659 val=0.929200 loss=0.003148 time: 57.856423
INFO:root:[Epoch 191] train=0.999639 val=0.928600 loss=0.003291 time: 56.389101
INFO:root:[Epoch 192] train=0.999559 val=0.929800 loss=0.003455 time: 56.339643
INFO:root:[Epoch 193] train=0.999579 val=0.929300 loss=0.003429 time: 56.295236
INFO:root:[Epoch 194] train=0.999519 val=0.927900 loss=0.003390 time: 56.074968
INFO:root:[Epoch 195] train=0.999579 val=0.928200 loss=0.003122 time: 56.125727
INFO:root:[Epoch 196] train=0.999659 val=0.928600 loss=0.003147 time: 55.909181
INFO:root:[Epoch 197] train=0.999679 val=0.929000 loss=0.003092 time: 55.554405
INFO:root:[Epoch 198] train=0.999659 val=0.928400 loss=0.003047 time: 56.603915
INFO:root:[Epoch 199] train=0.999760 val=0.929800 loss=0.002961 time: 56.257500