INFO:root:Namespace(batch_size=32, drop_rate=0.0, logging_dir='logs', lr=0.1, lr_decay=0.1, lr_decay_epoch='150,225', lr_decay_period=0, mode='hybrid', model='cifar_resnext29_16x64d', momentum=0.9, num_epochs=320, num_gpus=4, num_workers=4, resume_from=None, save_dir='params', save_period=10, save_plot_dir='.', wd=0.0001)
[16:29:36] 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=0.240656 val=0.253400 loss=2.589169 time: 127.853926
INFO:root:[Epoch 1] train=0.230200 val=0.348500 loss=2.003688 time: 114.284424
INFO:root:[Epoch 2] train=0.221231 val=0.466800 loss=1.887624 time: 113.849994
INFO:root:[Epoch 3] train=0.211831 val=0.524900 loss=1.807613 time: 113.876443
INFO:root:[Epoch 4] train=0.204862 val=0.559500 loss=1.716536 time: 113.746807
INFO:root:[Epoch 5] train=0.197550 val=0.601100 loss=1.629813 time: 113.695383
INFO:root:[Epoch 6] train=0.192367 val=0.621500 loss=1.572740 time: 114.090267
INFO:root:[Epoch 7] train=0.185923 val=0.644400 loss=1.550100 time: 113.747572
INFO:root:[Epoch 8] train=0.182316 val=0.691100 loss=1.485737 time: 114.190591
INFO:root:[Epoch 9] train=0.179628 val=0.713800 loss=1.481928 time: 113.765652
INFO:root:[Epoch 10] train=0.176085 val=0.734900 loss=1.452480 time: 113.841319
INFO:root:[Epoch 11] train=0.173356 val=0.731800 loss=1.417171 time: 114.570541
INFO:root:[Epoch 12] train=0.170018 val=0.751300 loss=1.409881 time: 113.771971
INFO:root:[Epoch 13] train=0.166975 val=0.757200 loss=1.355290 time: 114.586837
INFO:root:[Epoch 14] train=0.164334 val=0.778900 loss=1.354710 time: 113.855059
INFO:root:[Epoch 15] train=0.161669 val=0.800200 loss=1.348136 time: 114.042456
INFO:root:[Epoch 16] train=0.160079 val=0.786400 loss=1.312715 time: 113.447410
INFO:root:[Epoch 17] train=0.156082 val=0.814700 loss=1.264863 time: 113.744263
INFO:root:[Epoch 18] train=0.155078 val=0.817200 loss=1.283686 time: 114.182842
INFO:root:[Epoch 19] train=0.152608 val=0.800000 loss=1.268462 time: 113.452969
INFO:root:[Epoch 20] train=0.150287 val=0.830600 loss=1.246649 time: 113.588124
INFO:root:[Epoch 21] train=0.148751 val=0.841500 loss=1.232118 time: 113.923130
INFO:root:[Epoch 22] train=0.147294 val=0.838100 loss=1.249609 time: 113.392183
INFO:root:[Epoch 23] train=0.145353 val=0.841900 loss=1.204908 time: 113.815067
INFO:root:[Epoch 24] train=0.143016 val=0.847100 loss=1.175927 time: 113.846491
INFO:root:[Epoch 25] train=0.140501 val=0.841000 loss=1.169261 time: 113.961034
INFO:root:[Epoch 26] train=0.141362 val=0.852400 loss=1.191833 time: 113.994308
INFO:root:[Epoch 27] train=0.139994 val=0.866400 loss=1.184088 time: 114.136326
INFO:root:[Epoch 28] train=0.139254 val=0.860900 loss=1.181381 time: 113.464796
INFO:root:[Epoch 29] train=0.136869 val=0.880800 loss=1.159545 time: 113.874653
INFO:root:[Epoch 30] train=0.134431 val=0.888500 loss=1.141750 time: 113.897230
INFO:root:[Epoch 31] train=0.132113 val=0.870800 loss=1.108814 time: 114.003274
INFO:root:[Epoch 32] train=0.132344 val=0.881100 loss=1.117563 time: 113.618722
INFO:root:[Epoch 33] train=0.132596 val=0.880100 loss=1.143266 time: 113.484903
INFO:root:[Epoch 34] train=0.128465 val=0.891900 loss=1.094328 time: 113.721135
INFO:root:[Epoch 35] train=0.131178 val=0.893100 loss=1.132600 time: 114.174851
INFO:root:[Epoch 36] train=0.127795 val=0.898200 loss=1.085751 time: 113.819064
INFO:root:[Epoch 37] train=0.127365 val=0.904500 loss=1.094666 time: 113.873589
INFO:root:[Epoch 38] train=0.126946 val=0.867500 loss=1.098252 time: 113.714222
INFO:root:[Epoch 39] train=0.127234 val=0.907200 loss=1.111341 time: 114.168358
INFO:root:[Epoch 40] train=0.124480 val=0.891500 loss=1.053113 time: 113.262000
INFO:root:[Epoch 41] train=0.125283 val=0.891900 loss=1.085774 time: 113.439718
INFO:root:[Epoch 42] train=0.122928 val=0.901100 loss=1.058122 time: 113.849151
INFO:root:[Epoch 43] train=0.123667 val=0.902600 loss=1.072942 time: 113.861930
INFO:root:[Epoch 44] train=0.123072 val=0.907400 loss=1.077520 time: 114.108043
INFO:root:[Epoch 45] train=0.122054 val=0.909700 loss=1.070374 time: 113.792227
INFO:root:[Epoch 46] train=0.119634 val=0.907900 loss=1.032643 time: 113.994315
INFO:root:[Epoch 47] train=0.120123 val=0.885100 loss=1.046855 time: 113.523504
INFO:root:[Epoch 48] train=0.120341 val=0.905000 loss=1.047557 time: 113.183071
INFO:root:[Epoch 49] train=0.117494 val=0.910300 loss=1.007604 time: 114.574212
INFO:root:[Epoch 50] train=0.121765 val=0.904600 loss=1.085769 time: 113.343655
INFO:root:[Epoch 51] train=0.118495 val=0.917000 loss=1.020369 time: 113.862690
INFO:root:[Epoch 52] train=0.117971 val=0.918700 loss=1.036937 time: 113.552696
INFO:root:[Epoch 53] train=0.116346 val=0.895900 loss=1.017441 time: 113.542101
INFO:root:[Epoch 54] train=0.118241 val=0.911500 loss=1.043569 time: 113.671206
INFO:root:[Epoch 55] train=0.116998 val=0.911500 loss=1.019272 time: 113.578203
INFO:root:[Epoch 56] train=0.116824 val=0.907700 loss=1.018824 time: 113.636137
INFO:root:[Epoch 57] train=0.114593 val=0.907400 loss=1.009096 time: 113.578235
INFO:root:[Epoch 58] train=0.114526 val=0.903800 loss=0.999683 time: 113.505734
INFO:root:[Epoch 59] train=0.115708 val=0.918300 loss=1.015301 time: 113.657608
INFO:root:[Epoch 60] train=0.115748 val=0.906100 loss=1.020206 time: 113.581261
INFO:root:[Epoch 61] train=0.116693 val=0.924800 loss=1.039998 time: 113.588439
INFO:root:[Epoch 62] train=0.112550 val=0.923700 loss=0.971311 time: 113.592293
INFO:root:[Epoch 63] train=0.111147 val=0.924300 loss=0.968952 time: 113.674930
INFO:root:[Epoch 64] train=0.112247 val=0.921500 loss=0.998185 time: 113.233179
INFO:root:[Epoch 65] train=0.111734 val=0.923900 loss=0.979244 time: 113.386486
INFO:root:[Epoch 66] train=0.111160 val=0.912000 loss=0.985111 time: 113.607820
INFO:root:[Epoch 67] train=0.112411 val=0.919900 loss=0.980373 time: 113.961361
INFO:root:[Epoch 68] train=0.110203 val=0.926300 loss=0.957261 time: 113.802264
INFO:root:[Epoch 69] train=0.113590 val=0.925200 loss=1.002972 time: 113.557787
INFO:root:[Epoch 70] train=0.110756 val=0.904100 loss=0.976072 time: 113.722143
INFO:root:[Epoch 71] train=0.110805 val=0.911800 loss=0.981095 time: 113.534445
INFO:root:[Epoch 72] train=0.109336 val=0.928700 loss=0.962501 time: 113.788887
INFO:root:[Epoch 73] train=0.110925 val=0.926400 loss=0.981793 time: 113.669877
INFO:root:[Epoch 74] train=0.109016 val=0.922900 loss=0.970550 time: 113.275875
INFO:root:[Epoch 75] train=0.112544 val=0.916200 loss=0.997035 time: 113.222676
INFO:root:[Epoch 76] train=0.111965 val=0.918500 loss=1.003568 time: 114.650907
INFO:root:[Epoch 77] train=0.109504 val=0.934600 loss=0.965570 time: 114.312780
INFO:root:[Epoch 78] train=0.107823 val=0.922500 loss=0.959725 time: 114.172274
INFO:root:[Epoch 79] train=0.109483 val=0.920700 loss=0.971305 time: 113.529074
INFO:root:[Epoch 80] train=0.111297 val=0.920600 loss=0.987325 time: 113.742001
INFO:root:[Epoch 81] train=0.109170 val=0.923300 loss=0.967357 time: 113.444322
INFO:root:[Epoch 82] train=0.110268 val=0.922500 loss=0.991352 time: 114.093887
INFO:root:[Epoch 83] train=0.108013 val=0.929200 loss=0.956507 time: 113.445926
INFO:root:[Epoch 84] train=0.110275 val=0.924200 loss=0.987197 time: 113.609284
INFO:root:[Epoch 85] train=0.106800 val=0.906800 loss=0.947113 time: 113.532015
INFO:root:[Epoch 86] train=0.108094 val=0.929800 loss=0.959127 time: 113.479226
INFO:root:[Epoch 87] train=0.108651 val=0.931800 loss=0.960600 time: 113.749842
INFO:root:[Epoch 88] train=0.108122 val=0.925900 loss=0.955869 time: 113.448132
INFO:root:[Epoch 89] train=0.104446 val=0.920500 loss=0.924070 time: 113.585502
INFO:root:[Epoch 90] train=0.105255 val=0.930300 loss=0.930365 time: 113.391647
INFO:root:[Epoch 91] train=0.107186 val=0.932100 loss=0.970968 time: 113.461425
INFO:root:[Epoch 92] train=0.106759 val=0.928500 loss=0.948318 time: 113.514222
INFO:root:[Epoch 93] train=0.107190 val=0.917000 loss=0.947553 time: 113.756038
INFO:root:[Epoch 94] train=0.108626 val=0.934000 loss=0.982369 time: 113.601995
INFO:root:[Epoch 95] train=0.104218 val=0.928000 loss=0.933228 time: 113.673043
INFO:root:[Epoch 96] train=0.103070 val=0.927200 loss=0.920169 time: 113.825788
INFO:root:[Epoch 97] train=0.107070 val=0.912900 loss=0.959092 time: 113.355187
INFO:root:[Epoch 98] train=0.105426 val=0.919000 loss=0.943074 time: 113.298639
INFO:root:[Epoch 99] train=0.105942 val=0.915400 loss=0.945170 time: 113.281604
INFO:root:[Epoch 100] train=0.106562 val=0.933100 loss=0.964149 time: 113.331776
INFO:root:[Epoch 101] train=0.103093 val=0.933200 loss=0.924282 time: 113.636344
INFO:root:[Epoch 102] train=0.104449 val=0.925300 loss=0.945820 time: 113.320373
INFO:root:[Epoch 103] train=0.106975 val=0.927800 loss=0.970337 time: 113.575411
INFO:root:[Epoch 104] train=0.103416 val=0.915900 loss=0.919182 time: 113.620833
INFO:root:[Epoch 105] train=0.104988 val=0.929600 loss=0.939663 time: 113.862127
INFO:root:[Epoch 106] train=0.103394 val=0.931900 loss=0.928687 time: 113.759210
INFO:root:[Epoch 107] train=0.102669 val=0.918600 loss=0.922269 time: 113.524468
INFO:root:[Epoch 108] train=0.106185 val=0.920900 loss=0.949649 time: 113.568942
INFO:root:[Epoch 109] train=0.103295 val=0.935700 loss=0.919894 time: 113.879633
INFO:root:[Epoch 110] train=0.106527 val=0.931400 loss=0.964848 time: 113.396690
INFO:root:[Epoch 111] train=0.100850 val=0.922000 loss=0.900998 time: 113.535955
INFO:root:[Epoch 112] train=0.103762 val=0.932600 loss=0.938186 time: 113.436298
INFO:root:[Epoch 113] train=0.104899 val=0.925600 loss=0.956989 time: 114.571300
INFO:root:[Epoch 114] train=0.103579 val=0.931200 loss=0.933963 time: 113.596980
INFO:root:[Epoch 115] train=0.102870 val=0.936700 loss=0.926392 time: 114.193508
INFO:root:[Epoch 116] train=0.100505 val=0.940400 loss=0.901327 time: 113.862247
INFO:root:[Epoch 117] train=0.101755 val=0.932900 loss=0.925825 time: 113.488924
INFO:root:[Epoch 118] train=0.103177 val=0.937000 loss=0.929248 time: 113.720258
INFO:root:[Epoch 119] train=0.102411 val=0.939000 loss=0.927023 time: 113.757096
INFO:root:[Epoch 120] train=0.104747 val=0.939300 loss=0.951886 time: 113.729628
INFO:root:[Epoch 121] train=0.104266 val=0.928600 loss=0.953062 time: 113.438734
INFO:root:[Epoch 122] train=0.101674 val=0.927000 loss=0.920543 time: 113.703647
INFO:root:[Epoch 123] train=0.102777 val=0.930500 loss=0.917621 time: 114.180767
INFO:root:[Epoch 124] train=0.102382 val=0.930600 loss=0.920054 time: 113.598387
INFO:root:[Epoch 125] train=0.102834 val=0.919300 loss=0.926244 time: 113.662830
INFO:root:[Epoch 126] train=0.103800 val=0.924500 loss=0.942542 time: 114.179241
INFO:root:[Epoch 127] train=0.102247 val=0.931200 loss=0.933117 time: 113.971979
INFO:root:[Epoch 128] train=0.102011 val=0.931500 loss=0.929964 time: 113.389696
INFO:root:[Epoch 129] train=0.101545 val=0.935100 loss=0.914957 time: 113.807972
INFO:root:[Epoch 130] train=0.099983 val=0.932800 loss=0.890285 time: 113.836593
INFO:root:[Epoch 131] train=0.102984 val=0.918400 loss=0.937264 time: 113.905856
INFO:root:[Epoch 132] train=0.100264 val=0.926200 loss=0.897791 time: 114.138950
INFO:root:[Epoch 133] train=0.099921 val=0.928700 loss=0.901443 time: 114.354635
INFO:root:[Epoch 134] train=0.100097 val=0.928800 loss=0.907057 time: 113.865581
INFO:root:[Epoch 135] train=0.102566 val=0.925500 loss=0.938785 time: 113.548206
INFO:root:[Epoch 136] train=0.100166 val=0.930600 loss=0.900900 time: 113.645234
INFO:root:[Epoch 137] train=0.102247 val=0.924400 loss=0.926604 time: 113.623831
INFO:root:[Epoch 138] train=0.100428 val=0.928600 loss=0.912076 time: 114.072175
INFO:root:[Epoch 139] train=0.103171 val=0.928700 loss=0.936894 time: 113.862923
INFO:root:[Epoch 140] train=0.098288 val=0.934700 loss=0.876343 time: 113.800978
INFO:root:[Epoch 141] train=0.102622 val=0.920200 loss=0.938845 time: 113.590320
INFO:root:[Epoch 142] train=0.100754 val=0.937200 loss=0.911948 time: 113.752664
INFO:root:[Epoch 143] train=0.101010 val=0.939100 loss=0.915831 time: 113.694877
INFO:root:[Epoch 144] train=0.099825 val=0.931300 loss=0.908101 time: 113.446001
INFO:root:[Epoch 145] train=0.100712 val=0.936600 loss=0.909900 time: 114.807531
INFO:root:[Epoch 146] train=0.103022 val=0.923000 loss=0.923428 time: 113.747813
INFO:root:[Epoch 147] train=0.102136 val=0.937500 loss=0.931453 time: 113.632968
INFO:root:[Epoch 148] train=0.098356 val=0.935200 loss=0.885745 time: 113.817284
INFO:root:[Epoch 149] train=0.100383 val=0.940400 loss=0.906947 time: 114.218856
INFO:root:[Epoch 150] train=0.082238 val=0.960000 loss=0.799181 time: 114.021697
INFO:root:[Epoch 151] train=0.083015 val=0.960200 loss=0.821220 time: 113.815030
INFO:root:[Epoch 152] train=0.078326 val=0.963100 loss=0.777804 time: 113.984839
INFO:root:[Epoch 153] train=0.080470 val=0.964500 loss=0.802933 time: 113.786452
INFO:root:[Epoch 154] train=0.077685 val=0.962600 loss=0.780748 time: 113.852652
INFO:root:[Epoch 155] train=0.077268 val=0.963700 loss=0.782994 time: 113.853311
INFO:root:[Epoch 156] train=0.076610 val=0.965000 loss=0.772097 time: 114.271077
INFO:root:[Epoch 157] train=0.076936 val=0.963900 loss=0.777247 time: 114.002738
INFO:root:[Epoch 158] train=0.075812 val=0.963900 loss=0.766110 time: 114.246979
INFO:root:[Epoch 159] train=0.074026 val=0.966300 loss=0.762238 time: 113.929775
INFO:root:[Epoch 160] train=0.076739 val=0.963900 loss=0.777386 time: 113.616478
INFO:root:[Epoch 161] train=0.075568 val=0.967600 loss=0.772410 time: 114.527231
INFO:root:[Epoch 162] train=0.074941 val=0.966100 loss=0.766837 time: 114.003922
INFO:root:[Epoch 163] train=0.073001 val=0.968400 loss=0.748633 time: 114.596210
INFO:root:[Epoch 164] train=0.074730 val=0.966300 loss=0.766681 time: 113.590058
INFO:root:[Epoch 165] train=0.074216 val=0.968000 loss=0.766429 time: 113.717038
INFO:root:[Epoch 166] train=0.070924 val=0.968000 loss=0.734107 time: 113.533495
INFO:root:[Epoch 167] train=0.069833 val=0.965800 loss=0.726275 time: 113.522817
INFO:root:[Epoch 168] train=0.070396 val=0.968100 loss=0.733348 time: 114.136191
INFO:root:[Epoch 169] train=0.067352 val=0.967400 loss=0.704928 time: 114.180590
INFO:root:[Epoch 170] train=0.073254 val=0.967100 loss=0.749920 time: 113.886366
INFO:root:[Epoch 171] train=0.073413 val=0.968500 loss=0.757430 time: 114.005423
INFO:root:[Epoch 172] train=0.068191 val=0.966700 loss=0.707973 time: 113.626973
INFO:root:[Epoch 173] train=0.071739 val=0.966800 loss=0.744808 time: 114.109195
INFO:root:[Epoch 174] train=0.074311 val=0.965800 loss=0.758774 time: 114.910288
INFO:root:[Epoch 175] train=0.071121 val=0.968300 loss=0.738731 time: 113.634757
INFO:root:[Epoch 176] train=0.069395 val=0.966100 loss=0.720402 time: 113.667204
INFO:root:[Epoch 177] train=0.072287 val=0.964600 loss=0.748035 time: 113.763379
INFO:root:[Epoch 178] train=0.072531 val=0.966700 loss=0.752045 time: 113.791242
INFO:root:[Epoch 179] train=0.070766 val=0.965600 loss=0.736423 time: 113.667044
INFO:root:[Epoch 180] train=0.071063 val=0.966800 loss=0.735934 time: 113.568720
INFO:root:[Epoch 181] train=0.071207 val=0.965600 loss=0.736179 time: 113.433572
INFO:root:[Epoch 182] train=0.072889 val=0.966900 loss=0.751653 time: 113.876579
INFO:root:[Epoch 183] train=0.068162 val=0.965600 loss=0.706957 time: 113.841666
INFO:root:[Epoch 184] train=0.068739 val=0.968700 loss=0.716610 time: 115.274321
INFO:root:[Epoch 185] train=0.070541 val=0.969600 loss=0.731625 time: 114.229072
INFO:root:[Epoch 186] train=0.068127 val=0.969200 loss=0.714671 time: 114.236716
INFO:root:[Epoch 187] train=0.069590 val=0.965800 loss=0.725649 time: 113.716364
INFO:root:[Epoch 188] train=0.069900 val=0.967200 loss=0.725554 time: 113.912016
INFO:root:[Epoch 189] train=0.073428 val=0.968400 loss=0.761131 time: 114.335278
INFO:root:[Epoch 190] train=0.070448 val=0.966300 loss=0.739834 time: 113.770773
INFO:root:[Epoch 191] train=0.069453 val=0.966000 loss=0.725320 time: 113.792820
INFO:root:[Epoch 192] train=0.071778 val=0.966300 loss=0.743831 time: 113.497953
INFO:root:[Epoch 193] train=0.072025 val=0.967700 loss=0.741625 time: 114.189081
INFO:root:[Epoch 194] train=0.069749 val=0.964700 loss=0.730018 time: 113.810301
INFO:root:[Epoch 195] train=0.068370 val=0.964000 loss=0.711156 time: 113.718937
INFO:root:[Epoch 196] train=0.067748 val=0.967100 loss=0.708059 time: 113.668348
INFO:root:[Epoch 197] train=0.067728 val=0.966000 loss=0.706824 time: 113.535009
INFO:root:[Epoch 198] train=0.068445 val=0.964900 loss=0.717577 time: 114.303171
INFO:root:[Epoch 199] train=0.067565 val=0.964500 loss=0.711733 time: 113.916750
INFO:root:[Epoch 200] train=0.067549 val=0.966200 loss=0.712620 time: 113.637970
INFO:root:[Epoch 201] train=0.067690 val=0.967900 loss=0.711581 time: 113.721158
INFO:root:[Epoch 202] train=0.069440 val=0.966600 loss=0.721625 time: 113.982622
INFO:root:[Epoch 203] train=0.068241 val=0.966900 loss=0.718143 time: 114.931804
INFO:root:[Epoch 204] train=0.068131 val=0.968200 loss=0.708018 time: 113.789536
INFO:root:[Epoch 205] train=0.064305 val=0.966700 loss=0.683637 time: 114.038823
INFO:root:[Epoch 206] train=0.068788 val=0.963200 loss=0.716702 time: 114.286547
INFO:root:[Epoch 207] train=0.067108 val=0.966500 loss=0.698937 time: 113.839813
INFO:root:[Epoch 208] train=0.067672 val=0.967400 loss=0.711848 time: 114.063600
INFO:root:[Epoch 209] train=0.068078 val=0.966600 loss=0.717027 time: 114.144048
INFO:root:[Epoch 210] train=0.068874 val=0.965100 loss=0.718605 time: 114.149115
INFO:root:[Epoch 211] train=0.069970 val=0.968000 loss=0.726893 time: 114.164710
INFO:root:[Epoch 212] train=0.064709 val=0.966100 loss=0.689277 time: 114.095921
INFO:root:[Epoch 213] train=0.068352 val=0.966400 loss=0.719723 time: 113.946486
INFO:root:[Epoch 214] train=0.067335 val=0.967000 loss=0.708866 time: 113.901646
INFO:root:[Epoch 215] train=0.071852 val=0.965600 loss=0.743909 time: 113.848000
INFO:root:[Epoch 216] train=0.070415 val=0.965700 loss=0.735523 time: 113.820582
INFO:root:[Epoch 217] train=0.064551 val=0.967600 loss=0.680900 time: 113.813615
INFO:root:[Epoch 218] train=0.069573 val=0.965900 loss=0.730684 time: 113.901264
INFO:root:[Epoch 219] train=0.063932 val=0.966900 loss=0.676402 time: 113.840565
INFO:root:[Epoch 220] train=0.069527 val=0.963900 loss=0.723495 time: 113.784911
INFO:root:[Epoch 221] train=0.067977 val=0.962800 loss=0.716029 time: 113.578496
INFO:root:[Epoch 222] train=0.068147 val=0.965900 loss=0.717535 time: 113.913037
INFO:root:[Epoch 223] train=0.064240 val=0.964300 loss=0.685889 time: 113.981326
INFO:root:[Epoch 224] train=0.067648 val=0.968300 loss=0.710541 time: 113.854168
INFO:root:[Epoch 225] train=0.067935 val=0.969500 loss=0.721404 time: 114.260041
INFO:root:[Epoch 226] train=0.064678 val=0.970300 loss=0.693407 time: 114.025000
INFO:root:[Epoch 227] train=0.063058 val=0.971800 loss=0.674769 time: 114.110528
INFO:root:[Epoch 228] train=0.064711 val=0.971300 loss=0.688853 time: 114.145765
INFO:root:[Epoch 229] train=0.065872 val=0.969100 loss=0.699901 time: 113.695987
INFO:root:[Epoch 230] train=0.061724 val=0.970300 loss=0.671653 time: 113.960973
INFO:root:[Epoch 231] train=0.064840 val=0.971600 loss=0.697389 time: 114.172692
INFO:root:[Epoch 232] train=0.064040 val=0.972200 loss=0.683776 time: 113.798784
INFO:root:[Epoch 233] train=0.064433 val=0.969100 loss=0.689728 time: 113.862645
INFO:root:[Epoch 234] train=0.061435 val=0.970200 loss=0.666232 time: 113.944793
INFO:root:[Epoch 235] train=0.062155 val=0.969600 loss=0.672151 time: 113.984236
INFO:root:[Epoch 236] train=0.066610 val=0.970400 loss=0.706530 time: 113.862012
INFO:root:[Epoch 237] train=0.062520 val=0.969100 loss=0.678518 time: 113.939649
INFO:root:[Epoch 238] train=0.061567 val=0.971100 loss=0.669486 time: 113.855777
INFO:root:[Epoch 239] train=0.062376 val=0.972300 loss=0.674757 time: 114.195425
INFO:root:[Epoch 240] train=0.062046 val=0.971700 loss=0.667275 time: 114.185414
INFO:root:[Epoch 241] train=0.062889 val=0.971100 loss=0.675606 time: 114.037305
INFO:root:[Epoch 242] train=0.059965 val=0.970500 loss=0.654446 time: 113.767458
INFO:root:[Epoch 243] train=0.063732 val=0.967800 loss=0.686634 time: 113.864527
INFO:root:[Epoch 244] train=0.062511 val=0.971200 loss=0.676329 time: 114.148862
INFO:root:[Epoch 245] train=0.062759 val=0.969200 loss=0.674782 time: 114.023577
INFO:root:[Epoch 246] train=0.061520 val=0.972700 loss=0.667251 time: 114.468141
INFO:root:[Epoch 247] train=0.061495 val=0.970200 loss=0.665546 time: 113.809200
INFO:root:[Epoch 248] train=0.063049 val=0.969200 loss=0.679012 time: 114.306150
INFO:root:[Epoch 249] train=0.060673 val=0.970800 loss=0.660531 time: 113.844232
INFO:root:[Epoch 250] train=0.061366 val=0.968800 loss=0.668083 time: 113.893642
INFO:root:[Epoch 251] train=0.063048 val=0.970800 loss=0.674297 time: 113.684895
INFO:root:[Epoch 252] train=0.062654 val=0.968900 loss=0.673977 time: 113.837937
INFO:root:[Epoch 253] train=0.061397 val=0.969200 loss=0.670778 time: 114.066730
INFO:root:[Epoch 254] train=0.062733 val=0.969600 loss=0.678567 time: 113.990149
INFO:root:[Epoch 255] train=0.061571 val=0.971700 loss=0.666976 time: 113.858971
INFO:root:[Epoch 256] train=0.061945 val=0.971000 loss=0.672062 time: 114.147923
INFO:root:[Epoch 257] train=0.062362 val=0.970100 loss=0.674105 time: 113.817666
INFO:root:[Epoch 258] train=0.059651 val=0.970400 loss=0.652924 time: 114.077863
INFO:root:[Epoch 259] train=0.059558 val=0.970500 loss=0.658568 time: 113.920860
INFO:root:[Epoch 260] train=0.062897 val=0.970200 loss=0.680635 time: 114.552698
INFO:root:[Epoch 261] train=0.061228 val=0.970300 loss=0.664212 time: 114.194298
INFO:root:[Epoch 262] train=0.060321 val=0.971100 loss=0.659953 time: 113.807962
INFO:root:[Epoch 263] train=0.063026 val=0.969500 loss=0.687677 time: 113.916019
INFO:root:[Epoch 264] train=0.062088 val=0.969500 loss=0.674086 time: 114.186722
INFO:root:[Epoch 265] train=0.061432 val=0.969700 loss=0.667516 time: 114.203692
INFO:root:[Epoch 266] train=0.061648 val=0.970100 loss=0.664693 time: 113.973977
INFO:root:[Epoch 267] train=0.062056 val=0.970700 loss=0.674274 time: 113.807295
INFO:root:[Epoch 268] train=0.059865 val=0.969700 loss=0.656728 time: 114.088066
INFO:root:[Epoch 269] train=0.059594 val=0.969400 loss=0.651165 time: 114.066790
INFO:root:[Epoch 270] train=0.060233 val=0.969500 loss=0.659502 time: 113.890428
INFO:root:[Epoch 271] train=0.058858 val=0.969800 loss=0.648277 time: 113.748351
INFO:root:[Epoch 272] train=0.061851 val=0.968700 loss=0.669774 time: 113.944486
INFO:root:[Epoch 273] train=0.062404 val=0.969000 loss=0.671466 time: 113.898641
INFO:root:[Epoch 274] train=0.059748 val=0.969500 loss=0.655655 time: 113.811831
INFO:root:[Epoch 275] train=0.061767 val=0.969600 loss=0.671300 time: 114.297585
INFO:root:[Epoch 276] train=0.060787 val=0.970700 loss=0.661887 time: 113.877025
INFO:root:[Epoch 277] train=0.063426 val=0.970100 loss=0.688249 time: 114.143596
INFO:root:[Epoch 278] train=0.061814 val=0.968600 loss=0.670191 time: 114.125366
INFO:root:[Epoch 279] train=0.061991 val=0.968400 loss=0.673850 time: 114.097493
INFO:root:[Epoch 280] train=0.060672 val=0.972100 loss=0.662556 time: 114.232811
INFO:root:[Epoch 281] train=0.063892 val=0.970000 loss=0.689037 time: 113.923986
INFO:root:[Epoch 282] train=0.062899 val=0.969800 loss=0.681143 time: 113.830634
INFO:root:[Epoch 283] train=0.060804 val=0.971900 loss=0.664022 time: 113.965565
INFO:root:[Epoch 284] train=0.064001 val=0.968700 loss=0.689685 time: 113.710028
INFO:root:[Epoch 285] train=0.058814 val=0.969700 loss=0.648426 time: 114.247186
INFO:root:[Epoch 286] train=0.057472 val=0.970700 loss=0.636891 time: 113.769634
INFO:root:[Epoch 287] train=0.062374 val=0.970200 loss=0.677764 time: 114.878864
INFO:root:[Epoch 288] train=0.058666 val=0.971400 loss=0.642749 time: 114.089253
INFO:root:[Epoch 289] train=0.061133 val=0.970700 loss=0.663682 time: 115.097054
INFO:root:[Epoch 290] train=0.061338 val=0.970100 loss=0.665234 time: 113.986245
INFO:root:[Epoch 291] train=0.061104 val=0.971100 loss=0.664340 time: 114.031048
INFO:root:[Epoch 292] train=0.061672 val=0.970200 loss=0.673718 time: 114.063807
INFO:root:[Epoch 293] train=0.061794 val=0.968400 loss=0.670342 time: 114.117184
INFO:root:[Epoch 294] train=0.057598 val=0.969400 loss=0.635658 time: 113.868985
INFO:root:[Epoch 295] train=0.061882 val=0.969700 loss=0.670810 time: 114.643993
INFO:root:[Epoch 296] train=0.061057 val=0.971200 loss=0.664430 time: 114.096781
INFO:root:[Epoch 297] train=0.059311 val=0.970100 loss=0.648851 time: 114.028793
INFO:root:[Epoch 298] train=0.062222 val=0.968900 loss=0.673841 time: 114.253090
INFO:root:[Epoch 299] train=0.061194 val=0.968100 loss=0.665734 time: 114.550593
INFO:root:[Epoch 300] train=0.001545 val=0.971100 loss=0.002602 time: 114.116077
INFO:root:[Epoch 301] train=0.001271 val=0.970800 loss=0.001639 time: 114.112843
INFO:root:[Epoch 302] train=0.001162 val=0.970300 loss=0.001343 time: 114.080416
INFO:root:[Epoch 303] train=0.001088 val=0.970800 loss=0.001237 time: 114.358394
INFO:root:[Epoch 304] train=0.001093 val=0.971300 loss=0.001138 time: 113.934419
INFO:root:[Epoch 305] train=0.000967 val=0.970500 loss=0.001036 time: 113.835742
INFO:root:[Epoch 306] train=0.000857 val=0.971800 loss=0.000935 time: 113.622920
INFO:root:[Epoch 307] train=0.000823 val=0.971900 loss=0.000891 time: 113.897977
INFO:root:[Epoch 308] train=0.000845 val=0.970800 loss=0.000895 time: 114.030919
INFO:root:[Epoch 309] train=0.000730 val=0.972200 loss=0.000811 time: 114.142163
INFO:root:[Epoch 310] train=0.000758 val=0.972000 loss=0.000801 time: 113.851862
INFO:root:[Epoch 311] train=0.000759 val=0.972200 loss=0.000775 time: 113.709584
INFO:root:[Epoch 312] train=0.000767 val=0.971600 loss=0.000779 time: 114.032738
INFO:root:[Epoch 313] train=0.000758 val=0.971600 loss=0.000776 time: 113.897228
INFO:root:[Epoch 314] train=0.000694 val=0.971800 loss=0.000731 time: 113.834433
INFO:root:[Epoch 315] train=0.000728 val=0.972400 loss=0.000731 time: 114.186292
INFO:root:[Epoch 316] train=0.000665 val=0.971900 loss=0.000698 time: 113.737017
INFO:root:[Epoch 317] train=0.000564 val=0.971800 loss=0.000631 time: 113.916794
INFO:root:[Epoch 318] train=0.000671 val=0.971300 loss=0.000695 time: 114.112297
INFO:root:[Epoch 319] train=0.000617 val=0.972000 loss=0.000640 time: 114.235789