And here is another log. Using dist_sync
again, exact same config as previous example. Accuracy rises through early epochs, but slowly and not very steadily, then collapses and bounces up and down for rest of job.
2017-11-04 09:19:31,445 INFO - mxnet_container.train - Starting distributed training task
[09:19:31] src/io/iter_image_recordio_2.cc:169: ImageRecordIOParser2: /opt/ml/input/data/training/train.rec, use 31 threads for decoding..
2017-11-04 09:19:31,850 INFO - mxnet_container.train - Starting distributed training task
[09:19:31] src/io/iter_image_recordio_2.cc:169: ImageRecordIOParser2: /opt/ml/input/data/training/train.rec, use 31 threads for decoding..
[09:20:17] src/io/iter_image_recordio_2.cc:169: ImageRecordIOParser2: /opt/ml/input/data/training/test.rec, use 31 threads for decoding..
[09:20:16] src/io/iter_image_recordio_2.cc:169: ImageRecordIOParser2: /opt/ml/input/data/training/test.rec, use 31 threads for decoding..
[09:20:35] src/operator/././cudnn_algoreg-inl.h:106: 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)
[09:20:35] src/operator/././cudnn_algoreg-inl.h:106: 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)
2017-11-04 09:21:01,013 INFO - root - [Epoch 0] training: accuracy=0.098574
2017-11-04 09:21:01,013 INFO - root - [Epoch 0] time cost: 43.719973
2017-11-04 09:21:01,296 INFO - root - [Epoch 0] training: accuracy=0.097988
2017-11-04 09:21:01,296 INFO - root - [Epoch 0] time cost: 44.116472
2017-11-04 09:21:02,137 INFO - root - [Epoch 0] validation: accuracy=0.091406
2017-11-04 09:21:02,331 INFO - root - [Epoch 0] validation: accuracy=0.090332
2017-11-04 09:21:14,716 INFO - root - [Epoch 1] training: accuracy=0.104736
2017-11-04 09:21:14,717 INFO - root - [Epoch 1] time cost: 12.086653
2017-11-04 09:21:14,975 INFO - root - [Epoch 1] training: accuracy=0.104533
2017-11-04 09:21:14,975 INFO - root - [Epoch 1] time cost: 12.642990
2017-11-04 09:21:15,856 INFO - root - [Epoch 1] validation: accuracy=0.105469
2017-11-04 09:21:15,970 INFO - root - [Epoch 1] validation: accuracy=0.105566
2017-11-04 09:21:28,916 INFO - root - [Epoch 2] training: accuracy=0.110625
2017-11-04 09:21:28,916 INFO - root - [Epoch 2] time cost: 12.602215
2017-11-04 09:21:29,183 INFO - root - [Epoch 2] training: accuracy=0.110273
2017-11-04 09:21:29,183 INFO - root - [Epoch 2] time cost: 13.212795
2017-11-04 09:21:30,050 INFO - root - [Epoch 2] validation: accuracy=0.105371
2017-11-04 09:21:30,192 INFO - root - [Epoch 2] validation: accuracy=0.105176
2017-11-04 09:21:42,421 INFO - root - [Epoch 3] training: accuracy=0.114237
2017-11-04 09:21:42,421 INFO - root - [Epoch 3] time cost: 12.370330
2017-11-04 09:21:42,681 INFO - root - [Epoch 3] training: accuracy=0.114156
2017-11-04 09:21:42,681 INFO - root - [Epoch 3] time cost: 12.488236
2017-11-04 09:21:43,546 INFO - root - [Epoch 3] validation: accuracy=0.116406
2017-11-04 09:21:43,667 INFO - root - [Epoch 3] validation: accuracy=0.116406
2017-11-04 09:21:56,602 INFO - root - [Epoch 4] training: accuracy=0.124805
2017-11-04 09:21:56,603 INFO - root - [Epoch 4] time cost: 12.611940
2017-11-04 09:21:56,845 INFO - root - [Epoch 4] training: accuracy=0.124961
2017-11-04 09:21:56,845 INFO - root - [Epoch 4] time cost: 13.177747
2017-11-04 09:21:57,834 INFO - root - [Epoch 4] validation: accuracy=0.104785
2017-11-04 09:21:57,731 INFO - root - [Epoch 4] validation: accuracy=0.105566
2017-11-04 09:22:10,009 INFO - root - [Epoch 5] training: accuracy=0.130127
2017-11-04 09:22:10,010 INFO - root - [Epoch 5] time cost: 12.278370
2017-11-04 09:22:10,263 INFO - root - [Epoch 5] training: accuracy=0.130452
2017-11-04 09:22:10,263 INFO - root - [Epoch 5] time cost: 12.428541
2017-11-04 09:22:11,118 INFO - root - [Epoch 5] validation: accuracy=0.135742
2017-11-04 09:22:11,242 INFO - root - [Epoch 5] validation: accuracy=0.135352
2017-11-04 09:22:23,704 INFO - root - [Epoch 6] training: accuracy=0.142761
2017-11-04 09:22:23,705 INFO - root - [Epoch 6] time cost: 12.126450
2017-11-04 09:22:23,982 INFO - root - [Epoch 6] training: accuracy=0.142924
2017-11-04 09:22:23,982 INFO - root - [Epoch 6] time cost: 12.739633
2017-11-04 09:22:24,820 INFO - root - [Epoch 6] validation: accuracy=0.104980
2017-11-04 09:22:24,955 INFO - root - [Epoch 6] validation: accuracy=0.104883
2017-11-04 09:22:37,612 INFO - root - [Epoch 7] training: accuracy=0.142891
2017-11-04 09:22:37,612 INFO - root - [Epoch 7] time cost: 12.791654
2017-11-04 09:22:37,849 INFO - root - [Epoch 7] training: accuracy=0.143535
2017-11-04 09:22:37,849 INFO - root - [Epoch 7] time cost: 12.893820
2017-11-04 09:22:38,538 INFO - root - [Epoch 7] validation: accuracy=0.158569
2017-11-04 09:22:38,642 INFO - root - [Epoch 7] validation: accuracy=0.159058
2017-11-04 09:22:51,132 INFO - root - [Epoch 8] training: accuracy=0.159078
2017-11-04 09:22:51,133 INFO - root - [Epoch 8] time cost: 12.111735
2017-11-04 09:22:51,390 INFO - root - [Epoch 8] training: accuracy=0.159770
2017-11-04 09:22:51,390 INFO - root - [Epoch 8] time cost: 12.747310
2017-11-04 09:22:52,283 INFO - root - [Epoch 8] validation: accuracy=0.170313
2017-11-04 09:22:52,382 INFO - root - [Epoch 8] validation: accuracy=0.170605
2017-11-04 09:23:05,664 INFO - root - [Epoch 9] training: accuracy=0.170234
2017-11-04 09:23:05,664 INFO - root - [Epoch 9] time cost: 13.281223
2017-11-04 09:23:06,650 INFO - root - [Epoch 9] validation: accuracy=0.153320
2017-11-04 09:23:05,403 INFO - root - [Epoch 9] training: accuracy=0.170059
2017-11-04 09:23:05,403 INFO - root - [Epoch 9] time cost: 12.627474
2017-11-04 09:23:06,528 INFO - root - [Epoch 9] validation: accuracy=0.153027
2017-11-04 09:23:18,769 INFO - root - [Epoch 10] training: accuracy=0.179036
2017-11-04 09:23:18,769 INFO - root - [Epoch 10] time cost: 12.240948
2017-11-04 09:23:19,041 INFO - root - [Epoch 10] training: accuracy=0.179016
2017-11-04 09:23:19,041 INFO - root - [Epoch 10] time cost: 12.390525
2017-11-04 09:23:19,899 INFO - root - [Epoch 10] validation: accuracy=0.186914
2017-11-04 09:23:20,031 INFO - root - [Epoch 10] validation: accuracy=0.186914
2017-11-04 09:23:32,326 INFO - root - [Epoch 11] training: accuracy=0.197062
2017-11-04 09:23:32,326 INFO - root - [Epoch 11] time cost: 11.943790
2017-11-04 09:23:32,572 INFO - root - [Epoch 11] training: accuracy=0.196391
2017-11-04 09:23:32,572 INFO - root - [Epoch 11] time cost: 12.540984
2017-11-04 09:23:33,437 INFO - root - [Epoch 11] validation: accuracy=0.177832
2017-11-04 09:23:33,566 INFO - root - [Epoch 11] validation: accuracy=0.177539
2017-11-04 09:23:46,132 INFO - root - [Epoch 12] training: accuracy=0.192344
2017-11-04 09:23:46,132 INFO - root - [Epoch 12] time cost: 12.695587
2017-11-04 09:23:46,411 INFO - root - [Epoch 12] training: accuracy=0.192246
2017-11-04 09:23:46,411 INFO - root - [Epoch 12] time cost: 12.845486
2017-11-04 09:23:47,312 INFO - root - [Epoch 12] validation: accuracy=0.184180
2017-11-04 09:23:47,412 INFO - root - [Epoch 12] validation: accuracy=0.184473
2017-11-04 09:23:59,553 INFO - root - [Epoch 13] training: accuracy=0.194967
2017-11-04 09:23:59,553 INFO - root - [Epoch 13] time cost: 12.240608
2017-11-04 09:23:59,786 INFO - root - [Epoch 13] training: accuracy=0.195089
2017-11-04 09:23:59,787 INFO - root - [Epoch 13] time cost: 12.374072
2017-11-04 09:24:00,665 INFO - root - [Epoch 13] validation: accuracy=0.211719
2017-11-04 09:24:00,797 INFO - root - [Epoch 13] validation: accuracy=0.211523
2017-11-04 09:24:13,738 INFO - root - [Epoch 14] training: accuracy=0.200664
2017-11-04 09:24:13,738 INFO - root - [Epoch 14] time cost: 12.615486
2017-11-04 09:24:14,023 INFO - root - [Epoch 14] training: accuracy=0.200723
2017-11-04 09:24:14,023 INFO - root - [Epoch 14] time cost: 13.225932
2017-11-04 09:24:14,912 INFO - root - [Epoch 14] validation: accuracy=0.211426
2017-11-04 09:24:15,019 INFO - root - [Epoch 14] validation: accuracy=0.211523
2017-11-04 09:24:27,153 INFO - root - [Epoch 15] training: accuracy=0.213908
2017-11-04 09:24:27,153 INFO - root - [Epoch 15] time cost: 12.240951
2017-11-04 09:24:27,349 INFO - root - [Epoch 15] training: accuracy=0.214274
2017-11-04 09:24:27,349 INFO - root - [Epoch 15] time cost: 12.329125
2017-11-04 09:24:28,227 INFO - root - [Epoch 15] validation: accuracy=0.196191
2017-11-04 09:24:28,336 INFO - root - [Epoch 15] validation: accuracy=0.196289
2017-11-04 09:24:40,983 INFO - root - [Epoch 16] training: accuracy=0.219297
2017-11-04 09:24:40,983 INFO - root - [Epoch 16] time cost: 12.755961
2017-11-04 09:24:41,253 INFO - root - [Epoch 16] training: accuracy=0.220059
2017-11-04 09:24:41,253 INFO - root - [Epoch 16] time cost: 12.916951
2017-11-04 09:24:41,952 INFO - root - [Epoch 16] validation: accuracy=0.223022
2017-11-04 09:24:42,085 INFO - root - [Epoch 16] validation: accuracy=0.223511
2017-11-04 09:24:54,514 INFO - root - [Epoch 17] training: accuracy=0.207581
2017-11-04 09:24:54,514 INFO - root - [Epoch 17] time cost: 12.063521
2017-11-04 09:24:54,789 INFO - root - [Epoch 17] training: accuracy=0.207723
2017-11-04 09:24:54,789 INFO - root - [Epoch 17] time cost: 12.703974
2017-11-04 09:24:55,671 INFO - root - [Epoch 17] validation: accuracy=0.099805
2017-11-04 09:24:55,790 INFO - root - [Epoch 17] validation: accuracy=0.099805
2017-11-04 09:25:08,027 INFO - root - [Epoch 18] training: accuracy=0.101542
2017-11-04 09:25:08,027 INFO - root - [Epoch 18] time cost: 12.355660
2017-11-04 09:25:08,254 INFO - root - [Epoch 18] training: accuracy=0.101420
2017-11-04 09:25:08,254 INFO - root - [Epoch 18] time cost: 12.463921
2017-11-04 09:25:09,120 INFO - root - [Epoch 18] validation: accuracy=0.132812
2017-11-04 09:25:09,244 INFO - root - [Epoch 18] validation: accuracy=0.132422
2017-11-04 09:25:21,767 INFO - root - [Epoch 19] training: accuracy=0.165957
2017-11-04 09:25:21,767 INFO - root - [Epoch 19] time cost: 12.647036
2017-11-04 09:25:22,021 INFO - root - [Epoch 19] training: accuracy=0.166895
2017-11-04 09:25:22,021 INFO - root - [Epoch 19] time cost: 12.776301
2017-11-04 09:25:22,887 INFO - root - [Epoch 19] validation: accuracy=0.178711
2017-11-04 09:25:23,014 INFO - root - [Epoch 19] validation: accuracy=0.178711
2017-11-04 09:25:35,266 INFO - root - [Epoch 20] training: accuracy=0.174316
2017-11-04 09:25:35,266 INFO - root - [Epoch 20] time cost: 12.379125
2017-11-04 09:25:36,353 INFO - root - [Epoch 20] validation: accuracy=0.099609
2017-11-04 09:25:35,476 INFO - root - [Epoch 20] training: accuracy=0.174377
2017-11-04 09:25:35,476 INFO - root - [Epoch 20] time cost: 12.461397
2017-11-04 09:25:36,447 INFO - root - [Epoch 20] validation: accuracy=0.099609
2017-11-04 09:25:49,051 INFO - root - [Epoch 21] training: accuracy=0.125703
2017-11-04 09:25:49,051 INFO - root - [Epoch 21] time cost: 12.697860
2017-11-04 09:25:49,324 INFO - root - [Epoch 21] training: accuracy=0.125938
2017-11-04 09:25:49,324 INFO - root - [Epoch 21] time cost: 12.877100
2017-11-04 09:25:50,191 INFO - root - [Epoch 21] validation: accuracy=0.103027
2017-11-04 09:25:50,326 INFO - root - [Epoch 21] validation: accuracy=0.103027
2017-11-04 09:26:02,858 INFO - root - [Epoch 22] training: accuracy=0.141866
2017-11-04 09:26:02,858 INFO - root - [Epoch 22] time cost: 12.531573
2017-11-04 09:26:03,849 INFO - root - [Epoch 22] validation: accuracy=0.164355
2017-11-04 09:26:02,566 INFO - root - [Epoch 22] training: accuracy=0.141703
2017-11-04 09:26:02,566 INFO - root - [Epoch 22] time cost: 12.374612
2017-11-04 09:26:03,704 INFO - root - [Epoch 22] validation: accuracy=0.164551
2017-11-04 09:26:15,989 INFO - root - [Epoch 23] training: accuracy=0.161458
2017-11-04 09:26:15,989 INFO - root - [Epoch 23] time cost: 12.284893
2017-11-04 09:26:16,260 INFO - root - [Epoch 23] training: accuracy=0.161580
2017-11-04 09:26:16,260 INFO - root - [Epoch 23] time cost: 12.410921
2017-11-04 09:26:17,149 INFO - root - [Epoch 23] validation: accuracy=0.127930
2017-11-04 09:26:17,250 INFO - root - [Epoch 23] validation: accuracy=0.127930
2017-11-04 09:26:30,197 INFO - root - [Epoch 24] training: accuracy=0.150918
2017-11-04 09:26:30,197 INFO - root - [Epoch 24] time cost: 12.947518
2017-11-04 09:26:30,986 INFO - root - [Epoch 24] validation: accuracy=0.186768
2017-11-04 09:26:29,924 INFO - root - [Epoch 24] training: accuracy=0.150742
2017-11-04 09:26:29,924 INFO - root - [Epoch 24] time cost: 12.774948
2017-11-04 09:26:30,893 INFO - root - [Epoch 24] validation: accuracy=0.186768
2017-11-04 09:26:43,268 INFO - root - [Epoch 25] training: accuracy=0.173706
2017-11-04 09:26:43,268 INFO - root - [Epoch 25] time cost: 12.374998
2017-11-04 09:26:43,386 INFO - root - [Epoch 25] training: accuracy=0.173889
2017-11-04 09:26:43,386 INFO - root - [Epoch 25] time cost: 12.399672
2017-11-04 09:26:44,430 INFO - root - [Epoch 25] validation: accuracy=0.177734
2017-11-04 09:26:44,411 INFO - root - [Epoch 25] validation: accuracy=0.178125
2017-11-04 09:26:57,201 INFO - root - [Epoch 26] training: accuracy=0.214102
2017-11-04 09:26:57,201 INFO - root - [Epoch 26] time cost: 12.770151
2017-11-04 09:26:57,416 INFO - root - [Epoch 26] training: accuracy=0.214609
2017-11-04 09:26:57,416 INFO - root - [Epoch 26] time cost: 13.004954
2017-11-04 09:26:58,310 INFO - root - [Epoch 26] validation: accuracy=0.189648
2017-11-04 09:26:58,407 INFO - root - [Epoch 26] validation: accuracy=0.188477
2017-11-04 09:27:10,548 INFO - root - [Epoch 27] training: accuracy=0.207926
2017-11-04 09:27:10,548 INFO - root - [Epoch 27] time cost: 12.237620
2017-11-04 09:27:10,724 INFO - root - [Epoch 27] training: accuracy=0.207642
2017-11-04 09:27:10,724 INFO - root - [Epoch 27] time cost: 12.317256
2017-11-04 09:27:11,691 INFO - root - [Epoch 27] validation: accuracy=0.176953
2017-11-04 09:27:11,794 INFO - root - [Epoch 27] validation: accuracy=0.176660
2017-11-04 09:27:24,447 INFO - root - [Epoch 28] training: accuracy=0.187891
2017-11-04 09:27:24,447 INFO - root - [Epoch 28] time cost: 12.756263
2017-11-04 09:27:24,702 INFO - root - [Epoch 28] training: accuracy=0.187422
2017-11-04 09:27:24,702 INFO - root - [Epoch 28] time cost: 12.907530
2017-11-04 09:27:25,578 INFO - root - [Epoch 28] validation: accuracy=0.173535
2017-11-04 09:27:25,700 INFO - root - [Epoch 28] validation: accuracy=0.173730
2017-11-04 09:27:38,035 INFO - root - [Epoch 29] training: accuracy=0.160156
2017-11-04 09:27:38,035 INFO - root - [Epoch 29] time cost: 12.457565
2017-11-04 09:27:38,300 INFO - root - [Epoch 29] training: accuracy=0.159688
2017-11-04 09:27:38,300 INFO - root - [Epoch 29] time cost: 12.599412
2017-11-04 09:27:39,178 INFO - root - [Epoch 29] validation: accuracy=0.105859
2017-11-04 09:27:39,281 INFO - root - [Epoch 29] validation: accuracy=0.105762
2017-11-04 09:27:51,418 INFO - root - [Epoch 30] training: accuracy=0.163391
2017-11-04 09:27:51,419 INFO - root - [Epoch 30] time cost: 12.240153
2017-11-04 09:27:51,648 INFO - root - [Epoch 30] training: accuracy=0.163554
2017-11-04 09:27:51,649 INFO - root - [Epoch 30] time cost: 12.367119
2017-11-04 09:27:52,531 INFO - root - [Epoch 30] validation: accuracy=0.181250
2017-11-04 09:27:52,646 INFO - root - [Epoch 30] validation: accuracy=0.181348
2017-11-04 09:28:05,408 INFO - root - [Epoch 31] training: accuracy=0.189805
2017-11-04 09:28:05,408 INFO - root - [Epoch 31] time cost: 12.876806
2017-11-04 09:28:05,695 INFO - root - [Epoch 31] training: accuracy=0.189043
2017-11-04 09:28:05,695 INFO - root - [Epoch 31] time cost: 13.048735
2017-11-04 09:28:06,599 INFO - root - [Epoch 31] validation: accuracy=0.101270
2017-11-04 09:28:06,692 INFO - root - [Epoch 31] validation: accuracy=0.101465
2017-11-04 09:28:18,842 INFO - root - [Epoch 32] training: accuracy=0.118795
2017-11-04 09:28:18,842 INFO - root - [Epoch 32] time cost: 12.242412
2017-11-04 09:28:19,118 INFO - root - [Epoch 32] training: accuracy=0.118835
2017-11-04 09:28:19,118 INFO - root - [Epoch 32] time cost: 12.425529
2017-11-04 09:28:19,966 INFO - root - [Epoch 32] validation: accuracy=0.124316
2017-11-04 09:28:20,107 INFO - root - [Epoch 32] validation: accuracy=0.124316
2017-11-04 09:28:32,794 INFO - root - [Epoch 33] training: accuracy=0.151797
2017-11-04 09:28:32,794 INFO - root - [Epoch 33] time cost: 12.827599
2017-11-04 09:28:33,057 INFO - root - [Epoch 33] training: accuracy=0.152500
2017-11-04 09:28:33,057 INFO - root - [Epoch 33] time cost: 12.949730
2017-11-04 09:28:33,737 INFO - root - [Epoch 33] validation: accuracy=0.164429
2017-11-04 09:28:33,858 INFO - root - [Epoch 33] validation: accuracy=0.164551
2017-11-04 09:28:46,166 INFO - root - [Epoch 34] training: accuracy=0.171570
2017-11-04 09:28:46,166 INFO - root - [Epoch 34] time cost: 12.428155
2017-11-04 09:28:46,314 INFO - root - [Epoch 34] training: accuracy=0.170939
2017-11-04 09:28:46,314 INFO - root - [Epoch 34] time cost: 12.456010
2017-11-04 09:28:47,284 INFO - root - [Epoch 34] validation: accuracy=0.091113
2017-11-04 09:28:47,331 INFO - root - [Epoch 34] validation: accuracy=0.091211
2017-11-04 09:28:59,454 INFO - root - [Epoch 35] training: accuracy=0.200175
2017-11-04 09:28:59,454 INFO - root - [Epoch 35] time cost: 12.169878
2017-11-04 09:28:59,660 INFO - root - [Epoch 35] training: accuracy=0.199219
2017-11-04 09:28:59,661 INFO - root - [Epoch 35] time cost: 12.329283
2017-11-04 09:29:00,544 INFO - root - [Epoch 35] validation: accuracy=0.166016
2017-11-04 09:29:00,644 INFO - root - [Epoch 35] validation: accuracy=0.165918
2017-11-04 09:29:13,445 INFO - root - [Epoch 36] training: accuracy=0.207461
2017-11-04 09:29:13,446 INFO - root - [Epoch 36] time cost: 12.901035
2017-11-04 09:29:13,628 INFO - root - [Epoch 36] training: accuracy=0.207129
2017-11-04 09:29:13,628 INFO - root - [Epoch 36] time cost: 12.984184
2017-11-04 09:29:14,531 INFO - root - [Epoch 36] validation: accuracy=0.219141
2017-11-04 09:29:14,617 INFO - root - [Epoch 36] validation: accuracy=0.218652
2017-11-04 09:29:26,817 INFO - root - [Epoch 37] training: accuracy=0.220561
2017-11-04 09:29:26,817 INFO - root - [Epoch 37] time cost: 12.285670
2017-11-04 09:29:27,083 INFO - root - [Epoch 37] training: accuracy=0.220988
2017-11-04 09:29:27,083 INFO - root - [Epoch 37] time cost: 12.465264
2017-11-04 09:29:28,053 INFO - root - [Epoch 37] validation: accuracy=0.211719
2017-11-04 09:29:27,992 INFO - root - [Epoch 37] validation: accuracy=0.211914
2017-11-04 09:29:41,097 INFO - root - [Epoch 38] training: accuracy=0.233086
2017-11-04 09:29:41,097 INFO - root - [Epoch 38] time cost: 13.043344
2017-11-04 09:29:41,048 INFO - root - [Epoch 38] training: accuracy=0.232734
2017-11-04 09:29:41,048 INFO - root - [Epoch 38] time cost: 13.055960
2017-11-04 09:29:42,184 INFO - root - [Epoch 38] validation: accuracy=0.208789
2017-11-04 09:29:42,150 INFO - root - [Epoch 38] validation: accuracy=0.208496
2017-11-04 09:29:54,349 INFO - root - [Epoch 39] training: accuracy=0.251506
2017-11-04 09:29:54,349 INFO - root - [Epoch 39] time cost: 12.164769
2017-11-04 09:29:54,587 INFO - root - [Epoch 39] training: accuracy=0.250997
2017-11-04 09:29:54,587 INFO - root - [Epoch 39] time cost: 12.436299
2017-11-04 09:29:55,494 INFO - root - [Epoch 39] validation: accuracy=0.221582
2017-11-04 09:29:55,560 INFO - root - [Epoch 39] validation: accuracy=0.221094
2017-11-04 09:30:07,752 INFO - root - [Epoch 40] training: accuracy=0.264648
2017-11-04 09:30:07,753 INFO - root - [Epoch 40] time cost: 12.258241
2017-11-04 09:30:08,011 INFO - root - [Epoch 40] training: accuracy=0.264364
2017-11-04 09:30:08,011 INFO - root - [Epoch 40] time cost: 12.451312
2017-11-04 09:30:08,926 INFO - root - [Epoch 40] validation: accuracy=0.243848
2017-11-04 09:30:08,999 INFO - root - [Epoch 40] validation: accuracy=0.243457
2017-11-04 09:30:22,040 INFO - root - [Epoch 41] training: accuracy=0.276797
2017-11-04 09:30:22,040 INFO - root - [Epoch 41] time cost: 12.609574
2017-11-04 09:30:23,007 INFO - root - [Epoch 41] validation: accuracy=0.267090
2017-11-04 09:30:22,285 INFO - root - [Epoch 41] training: accuracy=0.276582
2017-11-04 09:30:22,285 INFO - root - [Epoch 41] time cost: 13.285149
2017-11-04 09:30:23,081 INFO - root - [Epoch 41] validation: accuracy=0.266846
2017-11-04 09:30:35,615 INFO - root - [Epoch 42] training: accuracy=0.293233
2017-11-04 09:30:35,615 INFO - root - [Epoch 42] time cost: 12.138875
2017-11-04 09:30:35,850 INFO - root - [Epoch 42] training: accuracy=0.292664
2017-11-04 09:30:35,850 INFO - root - [Epoch 42] time cost: 12.769114
2017-11-04 09:30:36,715 INFO - root - [Epoch 42] validation: accuracy=0.276660
2017-11-04 09:30:36,861 INFO - root - [Epoch 42] validation: accuracy=0.276953
2017-11-04 09:30:49,848 INFO - root - [Epoch 43] training: accuracy=0.304004
2017-11-04 09:30:49,848 INFO - root - [Epoch 43] time cost: 12.644325
2017-11-04 09:30:50,106 INFO - root - [Epoch 43] training: accuracy=0.305586
2017-11-04 09:30:50,106 INFO - root - [Epoch 43] time cost: 13.245051
2017-11-04 09:30:50,984 INFO - root - [Epoch 43] validation: accuracy=0.279199
2017-11-04 09:30:51,086 INFO - root - [Epoch 43] validation: accuracy=0.279395
2017-11-04 09:31:03,438 INFO - root - [Epoch 44] training: accuracy=0.312724
2017-11-04 09:31:03,438 INFO - root - [Epoch 44] time cost: 12.003252
2017-11-04 09:31:03,627 INFO - root - [Epoch 44] training: accuracy=0.312154
2017-11-04 09:31:03,627 INFO - root - [Epoch 44] time cost: 12.540570
2017-11-04 09:31:04,502 INFO - root - [Epoch 44] validation: accuracy=0.254102
2017-11-04 09:31:04,610 INFO - root - [Epoch 44] validation: accuracy=0.253809
2017-11-04 09:31:17,423 INFO - root - [Epoch 45] training: accuracy=0.338047
2017-11-04 09:31:17,423 INFO - root - [Epoch 45] time cost: 12.921498
2017-11-04 09:31:18,579 INFO - root - [Epoch 45] validation: accuracy=0.342383
2017-11-04 09:31:17,697 INFO - root - [Epoch 45] training: accuracy=0.337578
2017-11-04 09:31:17,697 INFO - root - [Epoch 45] time cost: 13.086395
2017-11-04 09:31:18,679 INFO - root - [Epoch 45] validation: accuracy=0.341992
2017-11-04 09:31:31,281 INFO - root - [Epoch 46] training: accuracy=0.300313
2017-11-04 09:31:31,281 INFO - root - [Epoch 46] time cost: 12.208615
2017-11-04 09:31:31,563 INFO - root - [Epoch 46] training: accuracy=0.299886
2017-11-04 09:31:31,563 INFO - root - [Epoch 46] time cost: 12.883930
2017-11-04 09:31:32,430 INFO - root - [Epoch 46] validation: accuracy=0.106934
2017-11-04 09:31:32,562 INFO - root - [Epoch 46] validation: accuracy=0.106738
2017-11-04 09:31:44,819 INFO - root - [Epoch 47] training: accuracy=0.116252
2017-11-04 09:31:44,819 INFO - root - [Epoch 47] time cost: 12.388544
2017-11-04 09:31:45,095 INFO - root - [Epoch 47] training: accuracy=0.116577
2017-11-04 09:31:45,095 INFO - root - [Epoch 47] time cost: 12.532603
2017-11-04 09:31:45,963 INFO - root - [Epoch 47] validation: accuracy=0.120801
2017-11-04 09:31:46,069 INFO - root - [Epoch 47] validation: accuracy=0.120898
2017-11-04 09:31:58,771 INFO - root - [Epoch 48] training: accuracy=0.176543
2017-11-04 09:31:58,771 INFO - root - [Epoch 48] time cost: 12.807537
2017-11-04 09:31:59,021 INFO - root - [Epoch 48] training: accuracy=0.175898
2017-11-04 09:31:59,021 INFO - root - [Epoch 48] time cost: 12.951865
2017-11-04 09:31:59,902 INFO - root - [Epoch 48] validation: accuracy=0.141211
2017-11-04 09:32:00,015 INFO - root - [Epoch 48] validation: accuracy=0.140332
2017-11-04 09:32:12,181 INFO - root - [Epoch 49] training: accuracy=0.219889
2017-11-04 09:32:12,181 INFO - root - [Epoch 49] time cost: 12.279304
2017-11-04 09:32:12,433 INFO - root - [Epoch 49] training: accuracy=0.220398
2017-11-04 09:32:12,433 INFO - root - [Epoch 49] time cost: 12.417594
2017-11-04 09:32:13,295 INFO - root - [Epoch 49] validation: accuracy=0.226074
2017-11-04 09:32:13,436 INFO - root - [Epoch 49] validation: accuracy=0.225977