Skip to content

Instantly share code, notes, and snippets.

@Answeror
Last active January 7, 2022 06:07
Show Gist options
  • Save Answeror/f9160145e1c64bb509f52c00014bdb77 to your computer and use it in GitHub Desktop.
Save Answeror/f9160145e1c64bb509f52c00014bdb77 to your computer and use it in GitHub Desktop.
Exactly reproduce 56 layers ResNet on CIFAR10 in mxnet
FROM dmlc/mxnet:cuda
MAINTAINER answeror <[email protected]>
ENV LD_LIBRARY_PATH /usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
RUN cd /mxnet && git pull origin master && git submodule update
ADD src/io/image_aug_default.cc /mxnet/src/io/image_aug_default.cc
RUN cd /mxnet && make -j8 ADD_LDFLAGS=-L/usr/local/cuda/lib64/stubs
ADD example/image-classification/symbol_resnet.py /mxnet/example/image-classification/symbol_resnet.py
ADD example/image-classification/train_cifar10_resnet.py /mxnet/example/image-classification/train_cifar10_resnet.py
WORKDIR /mxnet
CMD ["python", "example/image-classification/train_cifar10_resnet.py", "--save-model-prefix", "cifar10/resnet"]
This file has been truncated, but you can view the full file.
2016-05-02 12:04:38,432 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-02 12:04:38,830 Node[0] Start training with [gpu(0)]
2016-05-02 12:05:00,230 Node[0] Epoch[0] Batch [50] Speed: 643.90 samples/sec Train-accuracy=0.103594
2016-05-02 12:05:10,343 Node[0] Epoch[0] Batch [100] Speed: 632.90 samples/sec Train-accuracy=0.113750
2016-05-02 12:05:20,510 Node[0] Epoch[0] Batch [150] Speed: 629.44 samples/sec Train-accuracy=0.107031
2016-05-02 12:05:30,765 Node[0] Epoch[0] Batch [200] Speed: 624.15 samples/sec Train-accuracy=0.117969
2016-05-02 12:05:41,514 Node[0] Epoch[0] Batch [250] Speed: 595.42 samples/sec Train-accuracy=0.124844
2016-05-02 12:05:52,326 Node[0] Epoch[0] Batch [300] Speed: 591.97 samples/sec Train-accuracy=0.150156
2016-05-02 12:06:20,190 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-02 12:06:20,540 Node[0] Start training with [gpu(0)]
2016-05-02 12:06:41,491 Node[0] Epoch[0] Batch [50] Speed: 644.91 samples/sec Train-accuracy=0.105625
2016-05-02 12:06:51,655 Node[0] Epoch[0] Batch [100] Speed: 629.69 samples/sec Train-accuracy=0.171719
2016-05-02 12:07:01,852 Node[0] Epoch[0] Batch [150] Speed: 627.68 samples/sec Train-accuracy=0.242344
2016-05-02 12:07:12,031 Node[0] Epoch[0] Batch [200] Speed: 628.70 samples/sec Train-accuracy=0.267969
2016-05-02 12:07:22,826 Node[0] Epoch[0] Batch [250] Speed: 592.91 samples/sec Train-accuracy=0.302344
2016-05-02 12:07:33,798 Node[0] Epoch[0] Batch [300] Speed: 583.30 samples/sec Train-accuracy=0.333750
2016-05-02 12:07:44,730 Node[0] Epoch[0] Batch [350] Speed: 585.48 samples/sec Train-accuracy=0.350625
2016-05-02 12:07:53,633 Node[0] Epoch[0] Resetting Data Iterator
2016-05-02 12:07:53,634 Node[0] Epoch[0] Time cost=82.413
2016-05-02 12:07:53,807 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-02 12:07:55,961 Node[0] Epoch[0] Validation-accuracy=0.314280
2016-05-02 12:08:06,748 Node[0] Epoch[1] Batch [50] Speed: 596.34 samples/sec Train-accuracy=0.383594
2016-05-02 12:08:17,506 Node[0] Epoch[1] Batch [100] Speed: 594.91 samples/sec Train-accuracy=0.411406
2016-05-02 12:08:28,141 Node[0] Epoch[1] Batch [150] Speed: 601.82 samples/sec Train-accuracy=0.447656
2016-05-02 12:08:38,789 Node[0] Epoch[1] Batch [200] Speed: 601.07 samples/sec Train-accuracy=0.452656
2016-05-02 12:08:49,512 Node[0] Epoch[1] Batch [250] Speed: 596.87 samples/sec Train-accuracy=0.475000
2016-05-02 12:09:00,306 Node[0] Epoch[1] Batch [300] Speed: 592.91 samples/sec Train-accuracy=0.490625
2016-05-02 12:09:11,052 Node[0] Epoch[1] Batch [350] Speed: 595.60 samples/sec Train-accuracy=0.504375
2016-05-02 12:09:19,764 Node[0] Epoch[1] Resetting Data Iterator
2016-05-02 12:09:19,764 Node[0] Epoch[1] Time cost=83.803
2016-05-02 12:09:19,929 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-02 12:09:21,864 Node[0] Epoch[1] Validation-accuracy=0.445212
2016-05-02 12:09:32,586 Node[0] Epoch[2] Batch [50] Speed: 600.17 samples/sec Train-accuracy=0.537500
2016-05-02 12:09:43,194 Node[0] Epoch[2] Batch [100] Speed: 603.32 samples/sec Train-accuracy=0.566094
2016-05-02 12:09:53,813 Node[0] Epoch[2] Batch [150] Speed: 602.70 samples/sec Train-accuracy=0.571250
2016-05-02 12:10:04,408 Node[0] Epoch[2] Batch [200] Speed: 604.06 samples/sec Train-accuracy=0.576875
2016-05-02 12:10:15,064 Node[0] Epoch[2] Batch [250] Speed: 600.65 samples/sec Train-accuracy=0.599688
2016-05-02 12:10:25,718 Node[0] Epoch[2] Batch [300] Speed: 600.72 samples/sec Train-accuracy=0.606719
2016-05-02 12:10:36,331 Node[0] Epoch[2] Batch [350] Speed: 603.02 samples/sec Train-accuracy=0.610781
2016-05-02 12:10:44,792 Node[0] Epoch[2] Resetting Data Iterator
2016-05-02 12:10:44,792 Node[0] Epoch[2] Time cost=82.928
2016-05-02 12:10:44,956 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-02 12:10:46,850 Node[0] Epoch[2] Validation-accuracy=0.629407
2016-05-02 12:10:57,406 Node[0] Epoch[3] Batch [50] Speed: 609.50 samples/sec Train-accuracy=0.635781
2016-05-02 12:11:07,926 Node[0] Epoch[3] Batch [100] Speed: 608.35 samples/sec Train-accuracy=0.655156
2016-05-02 12:11:18,440 Node[0] Epoch[3] Batch [150] Speed: 608.75 samples/sec Train-accuracy=0.667969
2016-05-02 12:11:28,968 Node[0] Epoch[3] Batch [200] Speed: 607.88 samples/sec Train-accuracy=0.666406
2016-05-02 12:11:39,513 Node[0] Epoch[3] Batch [250] Speed: 606.95 samples/sec Train-accuracy=0.666250
2016-05-02 12:11:50,086 Node[0] Epoch[3] Batch [300] Speed: 605.37 samples/sec Train-accuracy=0.683594
2016-05-02 12:12:00,690 Node[0] Epoch[3] Batch [350] Speed: 603.54 samples/sec Train-accuracy=0.688438
2016-05-02 12:12:09,360 Node[0] Epoch[3] Resetting Data Iterator
2016-05-02 12:12:09,360 Node[0] Epoch[3] Time cost=82.510
2016-05-02 12:12:09,528 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-02 12:12:11,435 Node[0] Epoch[3] Validation-accuracy=0.710337
2016-05-02 12:12:21,927 Node[0] Epoch[4] Batch [50] Speed: 613.20 samples/sec Train-accuracy=0.701250
2016-05-02 12:12:32,366 Node[0] Epoch[4] Batch [100] Speed: 613.12 samples/sec Train-accuracy=0.714688
2016-05-02 12:12:42,766 Node[0] Epoch[4] Batch [150] Speed: 615.41 samples/sec Train-accuracy=0.724531
2016-05-02 12:12:53,265 Node[0] Epoch[4] Batch [200] Speed: 609.58 samples/sec Train-accuracy=0.720313
2016-05-02 12:13:03,871 Node[0] Epoch[4] Batch [250] Speed: 603.46 samples/sec Train-accuracy=0.728906
2016-05-02 12:13:14,344 Node[0] Epoch[4] Batch [300] Speed: 611.09 samples/sec Train-accuracy=0.734688
2016-05-02 12:13:24,765 Node[0] Epoch[4] Batch [350] Speed: 614.15 samples/sec Train-accuracy=0.736719
2016-05-02 12:13:33,333 Node[0] Epoch[4] Resetting Data Iterator
2016-05-02 12:13:33,334 Node[0] Epoch[4] Time cost=81.899
2016-05-02 12:13:33,504 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-02 12:13:35,462 Node[0] Epoch[4] Validation-accuracy=0.753005
2016-05-02 12:13:46,073 Node[0] Epoch[5] Batch [50] Speed: 606.47 samples/sec Train-accuracy=0.745625
2016-05-02 12:13:56,512 Node[0] Epoch[5] Batch [100] Speed: 613.09 samples/sec Train-accuracy=0.750938
2016-05-02 12:14:06,902 Node[0] Epoch[5] Batch [150] Speed: 615.99 samples/sec Train-accuracy=0.756094
2016-05-02 12:14:17,261 Node[0] Epoch[5] Batch [200] Speed: 617.86 samples/sec Train-accuracy=0.762969
2016-05-02 12:14:27,739 Node[0] Epoch[5] Batch [250] Speed: 610.77 samples/sec Train-accuracy=0.757031
2016-05-02 12:14:38,282 Node[0] Epoch[5] Batch [300] Speed: 607.08 samples/sec Train-accuracy=0.764375
2016-05-02 12:14:48,797 Node[0] Epoch[5] Batch [350] Speed: 608.68 samples/sec Train-accuracy=0.765312
2016-05-02 12:14:57,147 Node[0] Epoch[5] Resetting Data Iterator
2016-05-02 12:14:57,147 Node[0] Epoch[5] Time cost=81.686
2016-05-02 12:14:57,319 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-02 12:14:59,206 Node[0] Epoch[5] Validation-accuracy=0.768429
2016-05-02 12:15:09,568 Node[0] Epoch[6] Batch [50] Speed: 620.99 samples/sec Train-accuracy=0.768437
2016-05-02 12:15:19,987 Node[0] Epoch[6] Batch [100] Speed: 614.26 samples/sec Train-accuracy=0.781563
2016-05-02 12:15:30,405 Node[0] Epoch[6] Batch [150] Speed: 614.33 samples/sec Train-accuracy=0.784375
2016-05-02 12:15:40,794 Node[0] Epoch[6] Batch [200] Speed: 616.06 samples/sec Train-accuracy=0.776719
2016-05-02 12:15:51,192 Node[0] Epoch[6] Batch [250] Speed: 615.49 samples/sec Train-accuracy=0.778594
2016-05-02 12:16:01,591 Node[0] Epoch[6] Batch [300] Speed: 615.51 samples/sec Train-accuracy=0.785781
2016-05-02 12:16:12,008 Node[0] Epoch[6] Batch [350] Speed: 614.40 samples/sec Train-accuracy=0.796562
2016-05-02 12:16:20,511 Node[0] Epoch[6] Resetting Data Iterator
2016-05-02 12:16:20,511 Node[0] Epoch[6] Time cost=81.305
2016-05-02 12:16:20,675 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-02 12:16:22,615 Node[0] Epoch[6] Validation-accuracy=0.766326
2016-05-02 12:16:33,119 Node[0] Epoch[7] Batch [50] Speed: 612.51 samples/sec Train-accuracy=0.793594
2016-05-02 12:16:43,532 Node[0] Epoch[7] Batch [100] Speed: 614.68 samples/sec Train-accuracy=0.793281
2016-05-02 12:16:53,935 Node[0] Epoch[7] Batch [150] Speed: 615.18 samples/sec Train-accuracy=0.804219
2016-05-02 12:17:04,343 Node[0] Epoch[7] Batch [200] Speed: 614.94 samples/sec Train-accuracy=0.800469
2016-05-02 12:17:14,756 Node[0] Epoch[7] Batch [250] Speed: 614.65 samples/sec Train-accuracy=0.800156
2016-05-02 12:17:25,184 Node[0] Epoch[7] Batch [300] Speed: 613.76 samples/sec Train-accuracy=0.811562
2016-05-02 12:17:35,563 Node[0] Epoch[7] Batch [350] Speed: 616.64 samples/sec Train-accuracy=0.809219
2016-05-02 12:17:43,864 Node[0] Epoch[7] Resetting Data Iterator
2016-05-02 12:17:43,864 Node[0] Epoch[7] Time cost=81.249
2016-05-02 12:17:44,027 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-02 12:17:45,944 Node[0] Epoch[7] Validation-accuracy=0.792268
2016-05-02 12:17:56,332 Node[0] Epoch[8] Batch [50] Speed: 619.38 samples/sec Train-accuracy=0.803750
2016-05-02 12:18:06,670 Node[0] Epoch[8] Batch [100] Speed: 619.10 samples/sec Train-accuracy=0.809219
2016-05-02 12:18:17,028 Node[0] Epoch[8] Batch [150] Speed: 617.91 samples/sec Train-accuracy=0.822031
2016-05-02 12:18:27,428 Node[0] Epoch[8] Batch [200] Speed: 615.40 samples/sec Train-accuracy=0.811875
2016-05-02 12:18:37,823 Node[0] Epoch[8] Batch [250] Speed: 615.67 samples/sec Train-accuracy=0.812187
2016-05-02 12:18:48,227 Node[0] Epoch[8] Batch [300] Speed: 615.16 samples/sec Train-accuracy=0.822656
2016-05-02 12:18:58,657 Node[0] Epoch[8] Batch [350] Speed: 613.64 samples/sec Train-accuracy=0.818906
2016-05-02 12:19:07,163 Node[0] Epoch[8] Resetting Data Iterator
2016-05-02 12:19:07,163 Node[0] Epoch[8] Time cost=81.219
2016-05-02 12:19:07,328 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-02 12:19:09,407 Node[0] Epoch[8] Validation-accuracy=0.805775
2016-05-02 12:19:19,792 Node[0] Epoch[9] Batch [50] Speed: 619.64 samples/sec Train-accuracy=0.817500
2016-05-02 12:19:30,182 Node[0] Epoch[9] Batch [100] Speed: 615.99 samples/sec Train-accuracy=0.823594
2016-05-02 12:19:40,610 Node[0] Epoch[9] Batch [150] Speed: 613.77 samples/sec Train-accuracy=0.824063
2016-05-02 12:19:51,048 Node[0] Epoch[9] Batch [200] Speed: 613.12 samples/sec Train-accuracy=0.816719
2016-05-02 12:20:01,418 Node[0] Epoch[9] Batch [250] Speed: 617.23 samples/sec Train-accuracy=0.820469
2016-05-02 12:20:11,799 Node[0] Epoch[9] Batch [300] Speed: 616.51 samples/sec Train-accuracy=0.833906
2016-05-02 12:20:22,194 Node[0] Epoch[9] Batch [350] Speed: 615.68 samples/sec Train-accuracy=0.829063
2016-05-02 12:20:30,715 Node[0] Epoch[9] Resetting Data Iterator
2016-05-02 12:20:30,715 Node[0] Epoch[9] Time cost=81.308
2016-05-02 12:20:30,875 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-02 12:20:32,800 Node[0] Epoch[9] Validation-accuracy=0.788462
2016-05-02 12:20:43,266 Node[0] Epoch[10] Batch [50] Speed: 614.73 samples/sec Train-accuracy=0.830937
2016-05-02 12:20:53,666 Node[0] Epoch[10] Batch [100] Speed: 615.41 samples/sec Train-accuracy=0.835156
2016-05-02 12:21:04,020 Node[0] Epoch[10] Batch [150] Speed: 618.14 samples/sec Train-accuracy=0.836094
2016-05-02 12:21:14,426 Node[0] Epoch[10] Batch [200] Speed: 615.05 samples/sec Train-accuracy=0.833906
2016-05-02 12:21:24,810 Node[0] Epoch[10] Batch [250] Speed: 616.37 samples/sec Train-accuracy=0.847969
2016-05-02 12:21:35,215 Node[0] Epoch[10] Batch [300] Speed: 615.08 samples/sec Train-accuracy=0.844219
2016-05-02 12:21:45,593 Node[0] Epoch[10] Batch [350] Speed: 616.68 samples/sec Train-accuracy=0.841719
2016-05-02 12:21:53,881 Node[0] Epoch[10] Resetting Data Iterator
2016-05-02 12:21:53,881 Node[0] Epoch[10] Time cost=81.081
2016-05-02 12:21:54,044 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-02 12:21:55,949 Node[0] Epoch[10] Validation-accuracy=0.821114
2016-05-02 12:22:06,338 Node[0] Epoch[11] Batch [50] Speed: 619.15 samples/sec Train-accuracy=0.834219
2016-05-02 12:22:16,689 Node[0] Epoch[11] Batch [100] Speed: 618.37 samples/sec Train-accuracy=0.847031
2016-05-02 12:22:27,054 Node[0] Epoch[11] Batch [150] Speed: 617.44 samples/sec Train-accuracy=0.844688
2016-05-02 12:22:37,462 Node[0] Epoch[11] Batch [200] Speed: 614.96 samples/sec Train-accuracy=0.838750
2016-05-02 12:22:47,822 Node[0] Epoch[11] Batch [250] Speed: 617.77 samples/sec Train-accuracy=0.847500
2016-05-02 12:22:58,221 Node[0] Epoch[11] Batch [300] Speed: 615.47 samples/sec Train-accuracy=0.847344
2016-05-02 12:23:08,630 Node[0] Epoch[11] Batch [350] Speed: 614.84 samples/sec Train-accuracy=0.840313
2016-05-02 12:23:17,152 Node[0] Epoch[11] Resetting Data Iterator
2016-05-02 12:23:17,152 Node[0] Epoch[11] Time cost=81.203
2016-05-02 12:23:17,321 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-02 12:23:19,219 Node[0] Epoch[11] Validation-accuracy=0.812400
2016-05-02 12:23:29,611 Node[0] Epoch[12] Batch [50] Speed: 619.09 samples/sec Train-accuracy=0.839688
2016-05-02 12:23:39,991 Node[0] Epoch[12] Batch [100] Speed: 616.56 samples/sec Train-accuracy=0.848750
2016-05-02 12:23:50,421 Node[0] Epoch[12] Batch [150] Speed: 613.63 samples/sec Train-accuracy=0.855313
2016-05-02 12:24:00,842 Node[0] Epoch[12] Batch [200] Speed: 614.15 samples/sec Train-accuracy=0.847344
2016-05-02 12:24:11,217 Node[0] Epoch[12] Batch [250] Speed: 616.87 samples/sec Train-accuracy=0.849844
2016-05-02 12:24:21,553 Node[0] Epoch[12] Batch [300] Speed: 619.24 samples/sec Train-accuracy=0.862031
2016-05-02 12:24:31,906 Node[0] Epoch[12] Batch [350] Speed: 618.18 samples/sec Train-accuracy=0.848906
2016-05-02 12:24:40,413 Node[0] Epoch[12] Resetting Data Iterator
2016-05-02 12:24:40,413 Node[0] Epoch[12] Time cost=81.195
2016-05-02 12:24:40,577 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-02 12:24:42,493 Node[0] Epoch[12] Validation-accuracy=0.805489
2016-05-02 12:24:52,820 Node[0] Epoch[13] Batch [50] Speed: 623.10 samples/sec Train-accuracy=0.856406
2016-05-02 12:25:03,185 Node[0] Epoch[13] Batch [100] Speed: 617.45 samples/sec Train-accuracy=0.856250
2016-05-02 12:25:13,594 Node[0] Epoch[13] Batch [150] Speed: 614.90 samples/sec Train-accuracy=0.861875
2016-05-02 12:25:23,932 Node[0] Epoch[13] Batch [200] Speed: 619.06 samples/sec Train-accuracy=0.857344
2016-05-02 12:25:34,323 Node[0] Epoch[13] Batch [250] Speed: 615.95 samples/sec Train-accuracy=0.856719
2016-05-02 12:25:44,725 Node[0] Epoch[13] Batch [300] Speed: 615.28 samples/sec Train-accuracy=0.860781
2016-05-02 12:25:55,121 Node[0] Epoch[13] Batch [350] Speed: 615.69 samples/sec Train-accuracy=0.854844
2016-05-02 12:26:03,380 Node[0] Epoch[13] Resetting Data Iterator
2016-05-02 12:26:03,380 Node[0] Epoch[13] Time cost=80.887
2016-05-02 12:26:03,539 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-02 12:26:05,433 Node[0] Epoch[13] Validation-accuracy=0.795172
2016-05-02 12:26:15,816 Node[0] Epoch[14] Batch [50] Speed: 619.67 samples/sec Train-accuracy=0.857656
2016-05-02 12:26:26,181 Node[0] Epoch[14] Batch [100] Speed: 617.47 samples/sec Train-accuracy=0.855625
2016-05-02 12:26:36,518 Node[0] Epoch[14] Batch [150] Speed: 619.14 samples/sec Train-accuracy=0.866094
2016-05-02 12:26:46,869 Node[0] Epoch[14] Batch [200] Speed: 618.31 samples/sec Train-accuracy=0.864375
2016-05-02 12:26:57,271 Node[0] Epoch[14] Batch [250] Speed: 615.29 samples/sec Train-accuracy=0.863125
2016-05-02 12:27:07,666 Node[0] Epoch[14] Batch [300] Speed: 615.71 samples/sec Train-accuracy=0.867812
2016-05-02 12:27:18,075 Node[0] Epoch[14] Batch [350] Speed: 614.85 samples/sec Train-accuracy=0.860313
2016-05-02 12:27:26,558 Node[0] Epoch[14] Resetting Data Iterator
2016-05-02 12:27:26,559 Node[0] Epoch[14] Time cost=81.126
2016-05-02 12:27:26,722 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-02 12:27:28,643 Node[0] Epoch[14] Validation-accuracy=0.831631
2016-05-02 12:27:38,995 Node[0] Epoch[15] Batch [50] Speed: 621.50 samples/sec Train-accuracy=0.866563
2016-05-02 12:27:49,347 Node[0] Epoch[15] Batch [100] Speed: 618.28 samples/sec Train-accuracy=0.867344
2016-05-02 12:27:59,667 Node[0] Epoch[15] Batch [150] Speed: 620.18 samples/sec Train-accuracy=0.865313
2016-05-02 12:28:10,008 Node[0] Epoch[15] Batch [200] Speed: 618.89 samples/sec Train-accuracy=0.870938
2016-05-02 12:28:20,344 Node[0] Epoch[15] Batch [250] Speed: 619.21 samples/sec Train-accuracy=0.874375
2016-05-02 12:28:30,718 Node[0] Epoch[15] Batch [300] Speed: 616.92 samples/sec Train-accuracy=0.879062
2016-05-02 12:28:41,040 Node[0] Epoch[15] Batch [350] Speed: 620.08 samples/sec Train-accuracy=0.870625
2016-05-02 12:28:49,354 Node[0] Epoch[15] Resetting Data Iterator
2016-05-02 12:28:49,354 Node[0] Epoch[15] Time cost=80.710
2016-05-02 12:28:49,520 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-02 12:28:51,434 Node[0] Epoch[15] Validation-accuracy=0.844251
2016-05-02 12:29:01,798 Node[0] Epoch[16] Batch [50] Speed: 620.78 samples/sec Train-accuracy=0.875313
2016-05-02 12:29:12,171 Node[0] Epoch[16] Batch [100] Speed: 616.99 samples/sec Train-accuracy=0.870313
2016-05-02 12:29:22,531 Node[0] Epoch[16] Batch [150] Speed: 617.81 samples/sec Train-accuracy=0.869687
2016-05-02 12:29:32,899 Node[0] Epoch[16] Batch [200] Speed: 617.24 samples/sec Train-accuracy=0.879687
2016-05-02 12:29:43,246 Node[0] Epoch[16] Batch [250] Speed: 618.57 samples/sec Train-accuracy=0.872969
2016-05-02 12:29:53,620 Node[0] Epoch[16] Batch [300] Speed: 616.96 samples/sec Train-accuracy=0.872656
2016-05-02 12:30:03,983 Node[0] Epoch[16] Batch [350] Speed: 617.61 samples/sec Train-accuracy=0.864531
2016-05-02 12:30:12,472 Node[0] Epoch[16] Resetting Data Iterator
2016-05-02 12:30:12,472 Node[0] Epoch[16] Time cost=81.038
2016-05-02 12:30:12,631 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-02 12:30:14,711 Node[0] Epoch[16] Validation-accuracy=0.839003
2016-05-02 12:30:25,075 Node[0] Epoch[17] Batch [50] Speed: 620.88 samples/sec Train-accuracy=0.875000
2016-05-02 12:30:35,460 Node[0] Epoch[17] Batch [100] Speed: 616.27 samples/sec Train-accuracy=0.879062
2016-05-02 12:30:45,825 Node[0] Epoch[17] Batch [150] Speed: 617.45 samples/sec Train-accuracy=0.879844
2016-05-02 12:30:56,192 Node[0] Epoch[17] Batch [200] Speed: 617.41 samples/sec Train-accuracy=0.884844
2016-05-02 12:31:06,539 Node[0] Epoch[17] Batch [250] Speed: 618.53 samples/sec Train-accuracy=0.878125
2016-05-02 12:31:16,878 Node[0] Epoch[17] Batch [300] Speed: 619.02 samples/sec Train-accuracy=0.878594
2016-05-02 12:31:27,231 Node[0] Epoch[17] Batch [350] Speed: 618.21 samples/sec Train-accuracy=0.874062
2016-05-02 12:31:35,715 Node[0] Epoch[17] Resetting Data Iterator
2016-05-02 12:31:35,715 Node[0] Epoch[17] Time cost=81.004
2016-05-02 12:31:35,877 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-02 12:31:37,756 Node[0] Epoch[17] Validation-accuracy=0.849659
2016-05-02 12:31:48,133 Node[0] Epoch[18] Batch [50] Speed: 620.04 samples/sec Train-accuracy=0.878437
2016-05-02 12:31:58,528 Node[0] Epoch[18] Batch [100] Speed: 615.71 samples/sec Train-accuracy=0.874844
2016-05-02 12:32:08,907 Node[0] Epoch[18] Batch [150] Speed: 616.63 samples/sec Train-accuracy=0.884844
2016-05-02 12:32:19,284 Node[0] Epoch[18] Batch [200] Speed: 616.73 samples/sec Train-accuracy=0.881094
2016-05-02 12:32:29,661 Node[0] Epoch[18] Batch [250] Speed: 616.80 samples/sec Train-accuracy=0.887344
2016-05-02 12:32:39,996 Node[0] Epoch[18] Batch [300] Speed: 619.29 samples/sec Train-accuracy=0.886563
2016-05-02 12:32:50,335 Node[0] Epoch[18] Batch [350] Speed: 618.98 samples/sec Train-accuracy=0.880313
2016-05-02 12:32:58,610 Node[0] Epoch[18] Resetting Data Iterator
2016-05-02 12:32:58,610 Node[0] Epoch[18] Time cost=80.853
2016-05-02 12:32:58,775 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-02 12:33:00,689 Node[0] Epoch[18] Validation-accuracy=0.843550
2016-05-02 12:33:11,073 Node[0] Epoch[19] Batch [50] Speed: 619.62 samples/sec Train-accuracy=0.880313
2016-05-02 12:33:21,456 Node[0] Epoch[19] Batch [100] Speed: 616.45 samples/sec Train-accuracy=0.887969
2016-05-02 12:33:31,810 Node[0] Epoch[19] Batch [150] Speed: 618.10 samples/sec Train-accuracy=0.886094
2016-05-02 12:33:42,160 Node[0] Epoch[19] Batch [200] Speed: 618.38 samples/sec Train-accuracy=0.887188
2016-05-02 12:33:52,553 Node[0] Epoch[19] Batch [250] Speed: 615.81 samples/sec Train-accuracy=0.884062
2016-05-02 12:34:02,921 Node[0] Epoch[19] Batch [300] Speed: 617.27 samples/sec Train-accuracy=0.890469
2016-05-02 12:34:13,298 Node[0] Epoch[19] Batch [350] Speed: 616.80 samples/sec Train-accuracy=0.883437
2016-05-02 12:34:21,779 Node[0] Epoch[19] Resetting Data Iterator
2016-05-02 12:34:21,780 Node[0] Epoch[19] Time cost=81.090
2016-05-02 12:34:21,941 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-02 12:34:23,843 Node[0] Epoch[19] Validation-accuracy=0.845252
2016-05-02 12:34:34,289 Node[0] Epoch[20] Batch [50] Speed: 615.94 samples/sec Train-accuracy=0.887188
2016-05-02 12:34:44,676 Node[0] Epoch[20] Batch [100] Speed: 616.16 samples/sec Train-accuracy=0.886719
2016-05-02 12:34:55,034 Node[0] Epoch[20] Batch [150] Speed: 617.90 samples/sec Train-accuracy=0.891406
2016-05-02 12:35:05,410 Node[0] Epoch[20] Batch [200] Speed: 616.82 samples/sec Train-accuracy=0.888750
2016-05-02 12:35:15,772 Node[0] Epoch[20] Batch [250] Speed: 617.69 samples/sec Train-accuracy=0.890938
2016-05-02 12:35:26,150 Node[0] Epoch[20] Batch [300] Speed: 616.68 samples/sec Train-accuracy=0.896563
2016-05-02 12:35:36,543 Node[0] Epoch[20] Batch [350] Speed: 615.84 samples/sec Train-accuracy=0.887031
2016-05-02 12:35:45,040 Node[0] Epoch[20] Resetting Data Iterator
2016-05-02 12:35:45,041 Node[0] Epoch[20] Time cost=81.197
2016-05-02 12:35:45,202 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-02 12:35:47,130 Node[0] Epoch[20] Validation-accuracy=0.815405
2016-05-02 12:35:57,595 Node[0] Epoch[21] Batch [50] Speed: 614.85 samples/sec Train-accuracy=0.878125
2016-05-02 12:36:07,968 Node[0] Epoch[21] Batch [100] Speed: 616.97 samples/sec Train-accuracy=0.888437
2016-05-02 12:36:18,313 Node[0] Epoch[21] Batch [150] Speed: 618.68 samples/sec Train-accuracy=0.891406
2016-05-02 12:36:28,681 Node[0] Epoch[21] Batch [200] Speed: 617.32 samples/sec Train-accuracy=0.895625
2016-05-02 12:36:39,006 Node[0] Epoch[21] Batch [250] Speed: 619.84 samples/sec Train-accuracy=0.893437
2016-05-02 12:36:49,375 Node[0] Epoch[21] Batch [300] Speed: 617.24 samples/sec Train-accuracy=0.893125
2016-05-02 12:36:59,735 Node[0] Epoch[21] Batch [350] Speed: 617.78 samples/sec Train-accuracy=0.892031
2016-05-02 12:37:07,997 Node[0] Epoch[21] Resetting Data Iterator
2016-05-02 12:37:07,998 Node[0] Epoch[21] Time cost=80.868
2016-05-02 12:37:08,157 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-02 12:37:10,096 Node[0] Epoch[21] Validation-accuracy=0.824920
2016-05-02 12:37:20,539 Node[0] Epoch[22] Batch [50] Speed: 616.18 samples/sec Train-accuracy=0.890000
2016-05-02 12:37:30,912 Node[0] Epoch[22] Batch [100] Speed: 617.04 samples/sec Train-accuracy=0.901563
2016-05-02 12:37:41,304 Node[0] Epoch[22] Batch [150] Speed: 615.83 samples/sec Train-accuracy=0.888437
2016-05-02 12:37:51,685 Node[0] Epoch[22] Batch [200] Speed: 616.58 samples/sec Train-accuracy=0.886094
2016-05-02 12:38:02,060 Node[0] Epoch[22] Batch [250] Speed: 616.85 samples/sec Train-accuracy=0.897813
2016-05-02 12:38:12,397 Node[0] Epoch[22] Batch [300] Speed: 619.19 samples/sec Train-accuracy=0.902188
2016-05-02 12:38:22,752 Node[0] Epoch[22] Batch [350] Speed: 618.02 samples/sec Train-accuracy=0.891563
2016-05-02 12:38:31,238 Node[0] Epoch[22] Resetting Data Iterator
2016-05-02 12:38:31,239 Node[0] Epoch[22] Time cost=81.142
2016-05-02 12:38:31,402 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-02 12:38:33,320 Node[0] Epoch[22] Validation-accuracy=0.850260
2016-05-02 12:38:43,770 Node[0] Epoch[23] Batch [50] Speed: 615.81 samples/sec Train-accuracy=0.901094
2016-05-02 12:38:54,155 Node[0] Epoch[23] Batch [100] Speed: 616.27 samples/sec Train-accuracy=0.897188
2016-05-02 12:39:04,553 Node[0] Epoch[23] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.894844
2016-05-02 12:39:14,891 Node[0] Epoch[23] Batch [200] Speed: 619.09 samples/sec Train-accuracy=0.897344
2016-05-02 12:39:25,206 Node[0] Epoch[23] Batch [250] Speed: 620.47 samples/sec Train-accuracy=0.899219
2016-05-02 12:39:35,588 Node[0] Epoch[23] Batch [300] Speed: 616.48 samples/sec Train-accuracy=0.905312
2016-05-02 12:39:45,976 Node[0] Epoch[23] Batch [350] Speed: 616.13 samples/sec Train-accuracy=0.893750
2016-05-02 12:39:54,225 Node[0] Epoch[23] Resetting Data Iterator
2016-05-02 12:39:54,225 Node[0] Epoch[23] Time cost=80.905
2016-05-02 12:39:54,388 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-02 12:39:56,332 Node[0] Epoch[23] Validation-accuracy=0.844952
2016-05-02 12:40:06,778 Node[0] Epoch[24] Batch [50] Speed: 615.98 samples/sec Train-accuracy=0.893281
2016-05-02 12:40:17,209 Node[0] Epoch[24] Batch [100] Speed: 613.54 samples/sec Train-accuracy=0.907969
2016-05-02 12:40:27,614 Node[0] Epoch[24] Batch [150] Speed: 615.14 samples/sec Train-accuracy=0.900469
2016-05-02 12:40:37,987 Node[0] Epoch[24] Batch [200] Speed: 616.99 samples/sec Train-accuracy=0.896875
2016-05-02 12:40:48,375 Node[0] Epoch[24] Batch [250] Speed: 616.12 samples/sec Train-accuracy=0.897344
2016-05-02 12:40:58,751 Node[0] Epoch[24] Batch [300] Speed: 616.84 samples/sec Train-accuracy=0.907500
2016-05-02 12:41:09,162 Node[0] Epoch[24] Batch [350] Speed: 614.71 samples/sec Train-accuracy=0.899062
2016-05-02 12:41:17,712 Node[0] Epoch[24] Resetting Data Iterator
2016-05-02 12:41:17,712 Node[0] Epoch[24] Time cost=81.380
2016-05-02 12:41:17,876 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-02 12:41:19,980 Node[0] Epoch[24] Validation-accuracy=0.861551
2016-05-02 12:41:30,333 Node[0] Epoch[25] Batch [50] Speed: 621.39 samples/sec Train-accuracy=0.896563
2016-05-02 12:41:40,743 Node[0] Epoch[25] Batch [100] Speed: 614.83 samples/sec Train-accuracy=0.896094
2016-05-02 12:41:51,133 Node[0] Epoch[25] Batch [150] Speed: 616.00 samples/sec Train-accuracy=0.904062
2016-05-02 12:42:01,526 Node[0] Epoch[25] Batch [200] Speed: 615.81 samples/sec Train-accuracy=0.904219
2016-05-02 12:42:11,915 Node[0] Epoch[25] Batch [250] Speed: 616.06 samples/sec Train-accuracy=0.902031
2016-05-02 12:42:22,323 Node[0] Epoch[25] Batch [300] Speed: 614.93 samples/sec Train-accuracy=0.901563
2016-05-02 12:42:32,773 Node[0] Epoch[25] Batch [350] Speed: 612.47 samples/sec Train-accuracy=0.895781
2016-05-02 12:42:41,315 Node[0] Epoch[25] Resetting Data Iterator
2016-05-02 12:42:41,316 Node[0] Epoch[25] Time cost=81.336
2016-05-02 12:42:41,485 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-02 12:42:43,387 Node[0] Epoch[25] Validation-accuracy=0.843550
2016-05-02 12:42:53,807 Node[0] Epoch[26] Batch [50] Speed: 617.51 samples/sec Train-accuracy=0.906719
2016-05-02 12:43:04,176 Node[0] Epoch[26] Batch [100] Speed: 617.24 samples/sec Train-accuracy=0.908281
2016-05-02 12:43:14,560 Node[0] Epoch[26] Batch [150] Speed: 616.35 samples/sec Train-accuracy=0.902813
2016-05-02 12:43:24,944 Node[0] Epoch[26] Batch [200] Speed: 616.38 samples/sec Train-accuracy=0.899219
2016-05-02 12:43:35,308 Node[0] Epoch[26] Batch [250] Speed: 617.51 samples/sec Train-accuracy=0.907500
2016-05-02 12:43:45,684 Node[0] Epoch[26] Batch [300] Speed: 616.80 samples/sec Train-accuracy=0.908906
2016-05-02 12:43:56,045 Node[0] Epoch[26] Batch [350] Speed: 617.76 samples/sec Train-accuracy=0.900156
2016-05-02 12:44:04,375 Node[0] Epoch[26] Resetting Data Iterator
2016-05-02 12:44:04,375 Node[0] Epoch[26] Time cost=80.987
2016-05-02 12:44:04,544 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-02 12:44:06,455 Node[0] Epoch[26] Validation-accuracy=0.862079
2016-05-02 12:44:16,888 Node[0] Epoch[27] Batch [50] Speed: 616.67 samples/sec Train-accuracy=0.905781
2016-05-02 12:44:27,280 Node[0] Epoch[27] Batch [100] Speed: 615.90 samples/sec Train-accuracy=0.907031
2016-05-02 12:44:37,655 Node[0] Epoch[27] Batch [150] Speed: 616.85 samples/sec Train-accuracy=0.904844
2016-05-02 12:44:48,003 Node[0] Epoch[27] Batch [200] Speed: 618.53 samples/sec Train-accuracy=0.912813
2016-05-02 12:44:58,427 Node[0] Epoch[27] Batch [250] Speed: 613.99 samples/sec Train-accuracy=0.909219
2016-05-02 12:45:08,828 Node[0] Epoch[27] Batch [300] Speed: 615.32 samples/sec Train-accuracy=0.909219
2016-05-02 12:45:19,239 Node[0] Epoch[27] Batch [350] Speed: 614.76 samples/sec Train-accuracy=0.904062
2016-05-02 12:45:27,737 Node[0] Epoch[27] Resetting Data Iterator
2016-05-02 12:45:27,737 Node[0] Epoch[27] Time cost=81.282
2016-05-02 12:45:27,901 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-02 12:45:29,805 Node[0] Epoch[27] Validation-accuracy=0.846054
2016-05-02 12:45:40,204 Node[0] Epoch[28] Batch [50] Speed: 618.67 samples/sec Train-accuracy=0.906719
2016-05-02 12:45:50,614 Node[0] Epoch[28] Batch [100] Speed: 614.83 samples/sec Train-accuracy=0.903594
2016-05-02 12:46:00,955 Node[0] Epoch[28] Batch [150] Speed: 618.94 samples/sec Train-accuracy=0.909687
2016-05-02 12:46:11,286 Node[0] Epoch[28] Batch [200] Speed: 619.49 samples/sec Train-accuracy=0.903125
2016-05-02 12:46:21,632 Node[0] Epoch[28] Batch [250] Speed: 618.63 samples/sec Train-accuracy=0.913594
2016-05-02 12:46:32,017 Node[0] Epoch[28] Batch [300] Speed: 616.30 samples/sec Train-accuracy=0.915937
2016-05-02 12:46:42,413 Node[0] Epoch[28] Batch [350] Speed: 615.60 samples/sec Train-accuracy=0.908750
2016-05-02 12:46:50,942 Node[0] Epoch[28] Resetting Data Iterator
2016-05-02 12:46:50,943 Node[0] Epoch[28] Time cost=81.138
2016-05-02 12:46:51,105 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-02 12:46:53,045 Node[0] Epoch[28] Validation-accuracy=0.844351
2016-05-02 12:47:03,457 Node[0] Epoch[29] Batch [50] Speed: 617.97 samples/sec Train-accuracy=0.913906
2016-05-02 12:47:13,767 Node[0] Epoch[29] Batch [100] Speed: 620.80 samples/sec Train-accuracy=0.911719
2016-05-02 12:47:24,156 Node[0] Epoch[29] Batch [150] Speed: 616.02 samples/sec Train-accuracy=0.909219
2016-05-02 12:47:34,476 Node[0] Epoch[29] Batch [200] Speed: 620.19 samples/sec Train-accuracy=0.908281
2016-05-02 12:47:44,891 Node[0] Epoch[29] Batch [250] Speed: 614.50 samples/sec Train-accuracy=0.911719
2016-05-02 12:47:55,307 Node[0] Epoch[29] Batch [300] Speed: 614.48 samples/sec Train-accuracy=0.915156
2016-05-02 12:48:05,706 Node[0] Epoch[29] Batch [350] Speed: 615.43 samples/sec Train-accuracy=0.908281
2016-05-02 12:48:14,045 Node[0] Epoch[29] Resetting Data Iterator
2016-05-02 12:48:14,045 Node[0] Epoch[29] Time cost=81.000
2016-05-02 12:48:14,211 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-02 12:48:16,128 Node[0] Epoch[29] Validation-accuracy=0.858173
2016-05-02 12:48:26,477 Node[0] Epoch[30] Batch [50] Speed: 621.72 samples/sec Train-accuracy=0.915469
2016-05-02 12:48:36,848 Node[0] Epoch[30] Batch [100] Speed: 617.14 samples/sec Train-accuracy=0.913594
2016-05-02 12:48:47,254 Node[0] Epoch[30] Batch [150] Speed: 615.05 samples/sec Train-accuracy=0.911250
2016-05-02 12:48:57,635 Node[0] Epoch[30] Batch [200] Speed: 616.53 samples/sec Train-accuracy=0.911406
2016-05-02 12:49:07,971 Node[0] Epoch[30] Batch [250] Speed: 619.19 samples/sec Train-accuracy=0.914219
2016-05-02 12:49:18,358 Node[0] Epoch[30] Batch [300] Speed: 616.17 samples/sec Train-accuracy=0.914531
2016-05-02 12:49:28,741 Node[0] Epoch[30] Batch [350] Speed: 616.43 samples/sec Train-accuracy=0.906563
2016-05-02 12:49:37,220 Node[0] Epoch[30] Resetting Data Iterator
2016-05-02 12:49:37,221 Node[0] Epoch[30] Time cost=81.092
2016-05-02 12:49:37,387 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-02 12:49:39,272 Node[0] Epoch[30] Validation-accuracy=0.829427
2016-05-02 12:49:49,767 Node[0] Epoch[31] Batch [50] Speed: 612.98 samples/sec Train-accuracy=0.915312
2016-05-02 12:50:00,186 Node[0] Epoch[31] Batch [100] Speed: 614.24 samples/sec Train-accuracy=0.919844
2016-05-02 12:50:10,540 Node[0] Epoch[31] Batch [150] Speed: 618.19 samples/sec Train-accuracy=0.914687
2016-05-02 12:50:20,871 Node[0] Epoch[31] Batch [200] Speed: 619.50 samples/sec Train-accuracy=0.912500
2016-05-02 12:50:31,248 Node[0] Epoch[31] Batch [250] Speed: 616.77 samples/sec Train-accuracy=0.906563
2016-05-02 12:50:41,664 Node[0] Epoch[31] Batch [300] Speed: 614.43 samples/sec Train-accuracy=0.917031
2016-05-02 12:50:52,031 Node[0] Epoch[31] Batch [350] Speed: 617.37 samples/sec Train-accuracy=0.915625
2016-05-02 12:51:00,354 Node[0] Epoch[31] Resetting Data Iterator
2016-05-02 12:51:00,354 Node[0] Epoch[31] Time cost=81.083
2016-05-02 12:51:00,516 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-02 12:51:02,404 Node[0] Epoch[31] Validation-accuracy=0.852163
2016-05-02 12:51:12,799 Node[0] Epoch[32] Batch [50] Speed: 618.94 samples/sec Train-accuracy=0.914219
2016-05-02 12:51:23,183 Node[0] Epoch[32] Batch [100] Speed: 616.34 samples/sec Train-accuracy=0.918906
2016-05-02 12:51:33,602 Node[0] Epoch[32] Batch [150] Speed: 614.30 samples/sec Train-accuracy=0.914531
2016-05-02 12:51:44,095 Node[0] Epoch[32] Batch [200] Speed: 609.90 samples/sec Train-accuracy=0.916094
2016-05-02 12:51:54,502 Node[0] Epoch[32] Batch [250] Speed: 615.02 samples/sec Train-accuracy=0.917969
2016-05-02 12:52:04,826 Node[0] Epoch[32] Batch [300] Speed: 619.93 samples/sec Train-accuracy=0.916406
2016-05-02 12:52:15,208 Node[0] Epoch[32] Batch [350] Speed: 616.48 samples/sec Train-accuracy=0.906875
2016-05-02 12:52:23,692 Node[0] Epoch[32] Resetting Data Iterator
2016-05-02 12:52:23,693 Node[0] Epoch[32] Time cost=81.289
2016-05-02 12:52:23,856 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-02 12:52:25,987 Node[0] Epoch[32] Validation-accuracy=0.861551
2016-05-02 12:52:36,454 Node[0] Epoch[33] Batch [50] Speed: 614.64 samples/sec Train-accuracy=0.920000
2016-05-02 12:52:46,805 Node[0] Epoch[33] Batch [100] Speed: 618.29 samples/sec Train-accuracy=0.921875
2016-05-02 12:52:57,170 Node[0] Epoch[33] Batch [150] Speed: 617.49 samples/sec Train-accuracy=0.914219
2016-05-02 12:53:07,481 Node[0] Epoch[33] Batch [200] Speed: 620.71 samples/sec Train-accuracy=0.915937
2016-05-02 12:53:17,835 Node[0] Epoch[33] Batch [250] Speed: 618.17 samples/sec Train-accuracy=0.913906
2016-05-02 12:53:28,230 Node[0] Epoch[33] Batch [300] Speed: 615.64 samples/sec Train-accuracy=0.922188
2016-05-02 12:53:38,618 Node[0] Epoch[33] Batch [350] Speed: 616.11 samples/sec Train-accuracy=0.921406
2016-05-02 12:53:47,162 Node[0] Epoch[33] Resetting Data Iterator
2016-05-02 12:53:47,163 Node[0] Epoch[33] Time cost=81.176
2016-05-02 12:53:47,327 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-02 12:53:49,249 Node[0] Epoch[33] Validation-accuracy=0.850561
2016-05-02 12:53:59,523 Node[0] Epoch[34] Batch [50] Speed: 626.22 samples/sec Train-accuracy=0.917813
2016-05-02 12:54:09,913 Node[0] Epoch[34] Batch [100] Speed: 615.98 samples/sec Train-accuracy=0.911875
2016-05-02 12:54:20,274 Node[0] Epoch[34] Batch [150] Speed: 617.74 samples/sec Train-accuracy=0.916406
2016-05-02 12:54:30,663 Node[0] Epoch[34] Batch [200] Speed: 616.07 samples/sec Train-accuracy=0.913438
2016-05-02 12:54:41,000 Node[0] Epoch[34] Batch [250] Speed: 619.12 samples/sec Train-accuracy=0.919063
2016-05-02 12:54:51,353 Node[0] Epoch[34] Batch [300] Speed: 618.19 samples/sec Train-accuracy=0.922031
2016-05-02 12:55:01,742 Node[0] Epoch[34] Batch [350] Speed: 616.08 samples/sec Train-accuracy=0.922500
2016-05-02 12:55:10,047 Node[0] Epoch[34] Resetting Data Iterator
2016-05-02 12:55:10,047 Node[0] Epoch[34] Time cost=80.798
2016-05-02 12:55:10,210 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-02 12:55:12,107 Node[0] Epoch[34] Validation-accuracy=0.863381
2016-05-02 12:55:22,425 Node[0] Epoch[35] Batch [50] Speed: 623.55 samples/sec Train-accuracy=0.915156
2016-05-02 12:55:32,760 Node[0] Epoch[35] Batch [100] Speed: 619.27 samples/sec Train-accuracy=0.925312
2016-05-02 12:55:43,144 Node[0] Epoch[35] Batch [150] Speed: 616.33 samples/sec Train-accuracy=0.924844
2016-05-02 12:55:53,494 Node[0] Epoch[35] Batch [200] Speed: 618.39 samples/sec Train-accuracy=0.918594
2016-05-02 12:56:03,914 Node[0] Epoch[35] Batch [250] Speed: 614.19 samples/sec Train-accuracy=0.915469
2016-05-02 12:56:14,299 Node[0] Epoch[35] Batch [300] Speed: 616.33 samples/sec Train-accuracy=0.929531
2016-05-02 12:56:24,646 Node[0] Epoch[35] Batch [350] Speed: 618.53 samples/sec Train-accuracy=0.920469
2016-05-02 12:56:33,172 Node[0] Epoch[35] Resetting Data Iterator
2016-05-02 12:56:33,172 Node[0] Epoch[35] Time cost=81.065
2016-05-02 12:56:33,335 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-02 12:56:35,227 Node[0] Epoch[35] Validation-accuracy=0.853365
2016-05-02 12:56:45,548 Node[0] Epoch[36] Batch [50] Speed: 623.36 samples/sec Train-accuracy=0.921562
2016-05-02 12:56:55,906 Node[0] Epoch[36] Batch [100] Speed: 617.92 samples/sec Train-accuracy=0.924844
2016-05-02 12:57:06,284 Node[0] Epoch[36] Batch [150] Speed: 616.65 samples/sec Train-accuracy=0.920312
2016-05-02 12:57:16,663 Node[0] Epoch[36] Batch [200] Speed: 616.66 samples/sec Train-accuracy=0.920781
2016-05-02 12:57:27,032 Node[0] Epoch[36] Batch [250] Speed: 617.26 samples/sec Train-accuracy=0.921562
2016-05-02 12:57:37,403 Node[0] Epoch[36] Batch [300] Speed: 617.15 samples/sec Train-accuracy=0.923281
2016-05-02 12:57:47,792 Node[0] Epoch[36] Batch [350] Speed: 616.01 samples/sec Train-accuracy=0.917188
2016-05-02 12:57:56,288 Node[0] Epoch[36] Resetting Data Iterator
2016-05-02 12:57:56,288 Node[0] Epoch[36] Time cost=81.062
2016-05-02 12:57:56,450 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-02 12:57:58,396 Node[0] Epoch[36] Validation-accuracy=0.867188
2016-05-02 12:58:08,736 Node[0] Epoch[37] Batch [50] Speed: 622.22 samples/sec Train-accuracy=0.925000
2016-05-02 12:58:19,127 Node[0] Epoch[37] Batch [100] Speed: 615.96 samples/sec Train-accuracy=0.925000
2016-05-02 12:58:29,476 Node[0] Epoch[37] Batch [150] Speed: 618.40 samples/sec Train-accuracy=0.918125
2016-05-02 12:58:39,802 Node[0] Epoch[37] Batch [200] Speed: 619.84 samples/sec Train-accuracy=0.919687
2016-05-02 12:58:50,152 Node[0] Epoch[37] Batch [250] Speed: 618.35 samples/sec Train-accuracy=0.922969
2016-05-02 12:59:00,555 Node[0] Epoch[37] Batch [300] Speed: 615.22 samples/sec Train-accuracy=0.928281
2016-05-02 12:59:11,033 Node[0] Epoch[37] Batch [350] Speed: 610.81 samples/sec Train-accuracy=0.923594
2016-05-02 12:59:19,335 Node[0] Epoch[37] Resetting Data Iterator
2016-05-02 12:59:19,336 Node[0] Epoch[37] Time cost=80.940
2016-05-02 12:59:19,499 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-02 12:59:21,386 Node[0] Epoch[37] Validation-accuracy=0.861478
2016-05-02 12:59:31,790 Node[0] Epoch[38] Batch [50] Speed: 618.36 samples/sec Train-accuracy=0.918906
2016-05-02 12:59:42,147 Node[0] Epoch[38] Batch [100] Speed: 617.95 samples/sec Train-accuracy=0.930312
2016-05-02 12:59:52,539 Node[0] Epoch[38] Batch [150] Speed: 615.89 samples/sec Train-accuracy=0.923125
2016-05-02 13:00:02,955 Node[0] Epoch[38] Batch [200] Speed: 614.47 samples/sec Train-accuracy=0.923594
2016-05-02 13:00:13,388 Node[0] Epoch[38] Batch [250] Speed: 613.42 samples/sec Train-accuracy=0.922656
2016-05-02 13:00:23,787 Node[0] Epoch[38] Batch [300] Speed: 615.50 samples/sec Train-accuracy=0.920937
2016-05-02 13:00:34,227 Node[0] Epoch[38] Batch [350] Speed: 613.01 samples/sec Train-accuracy=0.917344
2016-05-02 13:00:42,735 Node[0] Epoch[38] Resetting Data Iterator
2016-05-02 13:00:42,735 Node[0] Epoch[38] Time cost=81.349
2016-05-02 13:00:42,901 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-02 13:00:44,803 Node[0] Epoch[38] Validation-accuracy=0.865885
2016-05-02 13:00:55,203 Node[0] Epoch[39] Batch [50] Speed: 618.75 samples/sec Train-accuracy=0.925156
2016-05-02 13:01:05,541 Node[0] Epoch[39] Batch [100] Speed: 619.11 samples/sec Train-accuracy=0.929844
2016-05-02 13:01:15,938 Node[0] Epoch[39] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.927813
2016-05-02 13:01:26,312 Node[0] Epoch[39] Batch [200] Speed: 616.95 samples/sec Train-accuracy=0.920312
2016-05-02 13:01:36,660 Node[0] Epoch[39] Batch [250] Speed: 618.54 samples/sec Train-accuracy=0.919375
2016-05-02 13:01:47,044 Node[0] Epoch[39] Batch [300] Speed: 616.32 samples/sec Train-accuracy=0.931094
2016-05-02 13:01:57,454 Node[0] Epoch[39] Batch [350] Speed: 614.85 samples/sec Train-accuracy=0.925469
2016-05-02 13:02:05,764 Node[0] Epoch[39] Resetting Data Iterator
2016-05-02 13:02:05,764 Node[0] Epoch[39] Time cost=80.961
2016-05-02 13:02:05,926 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-02 13:02:07,830 Node[0] Epoch[39] Validation-accuracy=0.856470
2016-05-02 13:02:18,296 Node[0] Epoch[40] Batch [50] Speed: 614.78 samples/sec Train-accuracy=0.918125
2016-05-02 13:02:28,672 Node[0] Epoch[40] Batch [100] Speed: 616.80 samples/sec Train-accuracy=0.925000
2016-05-02 13:02:39,063 Node[0] Epoch[40] Batch [150] Speed: 615.95 samples/sec Train-accuracy=0.922813
2016-05-02 13:02:49,470 Node[0] Epoch[40] Batch [200] Speed: 615.01 samples/sec Train-accuracy=0.925625
2016-05-02 13:02:59,855 Node[0] Epoch[40] Batch [250] Speed: 616.29 samples/sec Train-accuracy=0.929531
2016-05-02 13:03:10,289 Node[0] Epoch[40] Batch [300] Speed: 613.38 samples/sec Train-accuracy=0.932656
2016-05-02 13:03:20,675 Node[0] Epoch[40] Batch [350] Speed: 616.22 samples/sec Train-accuracy=0.927656
2016-05-02 13:03:29,182 Node[0] Epoch[40] Resetting Data Iterator
2016-05-02 13:03:29,183 Node[0] Epoch[40] Time cost=81.352
2016-05-02 13:03:29,347 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-02 13:03:31,421 Node[0] Epoch[40] Validation-accuracy=0.864913
2016-05-02 13:03:41,868 Node[0] Epoch[41] Batch [50] Speed: 615.84 samples/sec Train-accuracy=0.927656
2016-05-02 13:03:52,314 Node[0] Epoch[41] Batch [100] Speed: 612.73 samples/sec Train-accuracy=0.932813
2016-05-02 13:04:02,697 Node[0] Epoch[41] Batch [150] Speed: 616.40 samples/sec Train-accuracy=0.928281
2016-05-02 13:04:13,099 Node[0] Epoch[41] Batch [200] Speed: 615.26 samples/sec Train-accuracy=0.930000
2016-05-02 13:04:23,497 Node[0] Epoch[41] Batch [250] Speed: 615.52 samples/sec Train-accuracy=0.925469
2016-05-02 13:04:33,895 Node[0] Epoch[41] Batch [300] Speed: 615.53 samples/sec Train-accuracy=0.930312
2016-05-02 13:04:44,284 Node[0] Epoch[41] Batch [350] Speed: 616.04 samples/sec Train-accuracy=0.933594
2016-05-02 13:04:52,813 Node[0] Epoch[41] Resetting Data Iterator
2016-05-02 13:04:52,813 Node[0] Epoch[41] Time cost=81.392
2016-05-02 13:04:52,977 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-02 13:04:54,917 Node[0] Epoch[41] Validation-accuracy=0.842748
2016-05-02 13:05:05,463 Node[0] Epoch[42] Batch [50] Speed: 610.05 samples/sec Train-accuracy=0.925000
2016-05-02 13:05:15,935 Node[0] Epoch[42] Batch [100] Speed: 611.22 samples/sec Train-accuracy=0.927969
2016-05-02 13:05:26,322 Node[0] Epoch[42] Batch [150] Speed: 616.12 samples/sec Train-accuracy=0.927500
2016-05-02 13:05:36,741 Node[0] Epoch[42] Batch [200] Speed: 614.31 samples/sec Train-accuracy=0.925156
2016-05-02 13:05:47,142 Node[0] Epoch[42] Batch [250] Speed: 615.34 samples/sec Train-accuracy=0.920937
2016-05-02 13:05:57,571 Node[0] Epoch[42] Batch [300] Speed: 613.67 samples/sec Train-accuracy=0.930312
2016-05-02 13:06:07,985 Node[0] Epoch[42] Batch [350] Speed: 614.62 samples/sec Train-accuracy=0.927969
2016-05-02 13:06:16,291 Node[0] Epoch[42] Resetting Data Iterator
2016-05-02 13:06:16,292 Node[0] Epoch[42] Time cost=81.375
2016-05-02 13:06:16,454 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-02 13:06:18,376 Node[0] Epoch[42] Validation-accuracy=0.861579
2016-05-02 13:06:28,837 Node[0] Epoch[43] Batch [50] Speed: 615.02 samples/sec Train-accuracy=0.925156
2016-05-02 13:06:39,243 Node[0] Epoch[43] Batch [100] Speed: 615.05 samples/sec Train-accuracy=0.924844
2016-05-02 13:06:49,630 Node[0] Epoch[43] Batch [150] Speed: 616.20 samples/sec Train-accuracy=0.930625
2016-05-02 13:07:00,009 Node[0] Epoch[43] Batch [200] Speed: 616.65 samples/sec Train-accuracy=0.929531
2016-05-02 13:07:10,432 Node[0] Epoch[43] Batch [250] Speed: 614.02 samples/sec Train-accuracy=0.930937
2016-05-02 13:07:20,778 Node[0] Epoch[43] Batch [300] Speed: 618.64 samples/sec Train-accuracy=0.931094
2016-05-02 13:07:31,161 Node[0] Epoch[43] Batch [350] Speed: 616.40 samples/sec Train-accuracy=0.934219
2016-05-02 13:07:39,646 Node[0] Epoch[43] Resetting Data Iterator
2016-05-02 13:07:39,646 Node[0] Epoch[43] Time cost=81.270
2016-05-02 13:07:39,812 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-02 13:07:41,740 Node[0] Epoch[43] Validation-accuracy=0.859175
2016-05-02 13:07:52,264 Node[0] Epoch[44] Batch [50] Speed: 611.45 samples/sec Train-accuracy=0.935625
2016-05-02 13:08:02,676 Node[0] Epoch[44] Batch [100] Speed: 614.71 samples/sec Train-accuracy=0.926875
2016-05-02 13:08:13,105 Node[0] Epoch[44] Batch [150] Speed: 613.67 samples/sec Train-accuracy=0.929063
2016-05-02 13:08:23,525 Node[0] Epoch[44] Batch [200] Speed: 614.22 samples/sec Train-accuracy=0.932031
2016-05-02 13:08:33,915 Node[0] Epoch[44] Batch [250] Speed: 616.03 samples/sec Train-accuracy=0.932969
2016-05-02 13:08:44,465 Node[0] Epoch[44] Batch [300] Speed: 606.61 samples/sec Train-accuracy=0.931250
2016-05-02 13:08:54,868 Node[0] Epoch[44] Batch [350] Speed: 615.22 samples/sec Train-accuracy=0.932969
2016-05-02 13:09:03,364 Node[0] Epoch[44] Resetting Data Iterator
2016-05-02 13:09:03,365 Node[0] Epoch[44] Time cost=81.624
2016-05-02 13:09:03,527 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-02 13:09:05,446 Node[0] Epoch[44] Validation-accuracy=0.858373
2016-05-02 13:09:16,039 Node[0] Epoch[45] Batch [50] Speed: 607.42 samples/sec Train-accuracy=0.929531
2016-05-02 13:09:26,493 Node[0] Epoch[45] Batch [100] Speed: 612.23 samples/sec Train-accuracy=0.932969
2016-05-02 13:09:36,879 Node[0] Epoch[45] Batch [150] Speed: 616.22 samples/sec Train-accuracy=0.928906
2016-05-02 13:09:47,261 Node[0] Epoch[45] Batch [200] Speed: 616.43 samples/sec Train-accuracy=0.926719
2016-05-02 13:09:57,651 Node[0] Epoch[45] Batch [250] Speed: 615.99 samples/sec Train-accuracy=0.924687
2016-05-02 13:10:08,073 Node[0] Epoch[45] Batch [300] Speed: 614.13 samples/sec Train-accuracy=0.926875
2016-05-02 13:10:18,520 Node[0] Epoch[45] Batch [350] Speed: 612.63 samples/sec Train-accuracy=0.929531
2016-05-02 13:10:26,828 Node[0] Epoch[45] Resetting Data Iterator
2016-05-02 13:10:26,829 Node[0] Epoch[45] Time cost=81.382
2016-05-02 13:10:26,994 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-02 13:10:28,892 Node[0] Epoch[45] Validation-accuracy=0.862480
2016-05-02 13:10:39,428 Node[0] Epoch[46] Batch [50] Speed: 610.75 samples/sec Train-accuracy=0.925937
2016-05-02 13:10:49,797 Node[0] Epoch[46] Batch [100] Speed: 617.21 samples/sec Train-accuracy=0.930312
2016-05-02 13:11:00,186 Node[0] Epoch[46] Batch [150] Speed: 616.04 samples/sec Train-accuracy=0.928125
2016-05-02 13:11:10,567 Node[0] Epoch[46] Batch [200] Speed: 616.58 samples/sec Train-accuracy=0.932500
2016-05-02 13:11:21,019 Node[0] Epoch[46] Batch [250] Speed: 612.29 samples/sec Train-accuracy=0.932344
2016-05-02 13:11:31,557 Node[0] Epoch[46] Batch [300] Speed: 607.34 samples/sec Train-accuracy=0.938750
2016-05-02 13:11:42,044 Node[0] Epoch[46] Batch [350] Speed: 610.31 samples/sec Train-accuracy=0.930469
2016-05-02 13:11:50,583 Node[0] Epoch[46] Resetting Data Iterator
2016-05-02 13:11:50,584 Node[0] Epoch[46] Time cost=81.691
2016-05-02 13:11:50,746 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-02 13:11:52,688 Node[0] Epoch[46] Validation-accuracy=0.863582
2016-05-02 13:12:03,097 Node[0] Epoch[47] Batch [50] Speed: 618.07 samples/sec Train-accuracy=0.930781
2016-05-02 13:12:13,447 Node[0] Epoch[47] Batch [100] Speed: 618.34 samples/sec Train-accuracy=0.930937
2016-05-02 13:12:23,807 Node[0] Epoch[47] Batch [150] Speed: 617.81 samples/sec Train-accuracy=0.935469
2016-05-02 13:12:34,234 Node[0] Epoch[47] Batch [200] Speed: 613.82 samples/sec Train-accuracy=0.929375
2016-05-02 13:12:44,642 Node[0] Epoch[47] Batch [250] Speed: 614.92 samples/sec Train-accuracy=0.933125
2016-05-02 13:12:55,061 Node[0] Epoch[47] Batch [300] Speed: 614.28 samples/sec Train-accuracy=0.930937
2016-05-02 13:13:05,481 Node[0] Epoch[47] Batch [350] Speed: 614.20 samples/sec Train-accuracy=0.932969
2016-05-02 13:13:13,757 Node[0] Epoch[47] Resetting Data Iterator
2016-05-02 13:13:13,757 Node[0] Epoch[47] Time cost=81.069
2016-05-02 13:13:13,922 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-02 13:13:15,872 Node[0] Epoch[47] Validation-accuracy=0.873698
2016-05-02 13:13:26,358 Node[0] Epoch[48] Batch [50] Speed: 613.64 samples/sec Train-accuracy=0.935937
2016-05-02 13:13:36,734 Node[0] Epoch[48] Batch [100] Speed: 616.86 samples/sec Train-accuracy=0.935469
2016-05-02 13:13:47,399 Node[0] Epoch[48] Batch [150] Speed: 600.11 samples/sec Train-accuracy=0.931562
2016-05-02 13:13:58,032 Node[0] Epoch[48] Batch [200] Speed: 601.91 samples/sec Train-accuracy=0.931719
2016-05-02 13:14:08,477 Node[0] Epoch[48] Batch [250] Speed: 612.77 samples/sec Train-accuracy=0.934531
2016-05-02 13:14:18,899 Node[0] Epoch[48] Batch [300] Speed: 614.06 samples/sec Train-accuracy=0.931719
2016-05-02 13:14:29,324 Node[0] Epoch[48] Batch [350] Speed: 613.94 samples/sec Train-accuracy=0.931562
2016-05-02 13:14:37,889 Node[0] Epoch[48] Resetting Data Iterator
2016-05-02 13:14:37,889 Node[0] Epoch[48] Time cost=82.017
2016-05-02 13:14:38,054 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-02 13:14:40,165 Node[0] Epoch[48] Validation-accuracy=0.852749
2016-05-02 13:14:50,688 Node[0] Epoch[49] Batch [50] Speed: 611.40 samples/sec Train-accuracy=0.934688
2016-05-02 13:15:01,170 Node[0] Epoch[49] Batch [100] Speed: 610.56 samples/sec Train-accuracy=0.943906
2016-05-02 13:15:11,631 Node[0] Epoch[49] Batch [150] Speed: 611.87 samples/sec Train-accuracy=0.936562
2016-05-02 13:15:22,036 Node[0] Epoch[49] Batch [200] Speed: 615.09 samples/sec Train-accuracy=0.931250
2016-05-02 13:15:32,455 Node[0] Epoch[49] Batch [250] Speed: 614.29 samples/sec Train-accuracy=0.931562
2016-05-02 13:15:42,899 Node[0] Epoch[49] Batch [300] Speed: 612.80 samples/sec Train-accuracy=0.932500
2016-05-02 13:15:53,342 Node[0] Epoch[49] Batch [350] Speed: 612.88 samples/sec Train-accuracy=0.934531
2016-05-02 13:16:01,860 Node[0] Epoch[49] Resetting Data Iterator
2016-05-02 13:16:01,860 Node[0] Epoch[49] Time cost=81.695
2016-05-02 13:16:02,023 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-02 13:16:03,931 Node[0] Epoch[49] Validation-accuracy=0.867889
2016-05-02 13:16:14,432 Node[0] Epoch[50] Batch [50] Speed: 612.68 samples/sec Train-accuracy=0.939844
2016-05-02 13:16:24,863 Node[0] Epoch[50] Batch [100] Speed: 613.58 samples/sec Train-accuracy=0.929375
2016-05-02 13:16:35,273 Node[0] Epoch[50] Batch [150] Speed: 614.84 samples/sec Train-accuracy=0.932500
2016-05-02 13:16:45,657 Node[0] Epoch[50] Batch [200] Speed: 616.30 samples/sec Train-accuracy=0.933750
2016-05-02 13:16:56,019 Node[0] Epoch[50] Batch [250] Speed: 617.65 samples/sec Train-accuracy=0.939063
2016-05-02 13:17:06,448 Node[0] Epoch[50] Batch [300] Speed: 613.74 samples/sec Train-accuracy=0.933906
2016-05-02 13:17:16,888 Node[0] Epoch[50] Batch [350] Speed: 613.04 samples/sec Train-accuracy=0.932500
2016-05-02 13:17:25,212 Node[0] Epoch[50] Resetting Data Iterator
2016-05-02 13:17:25,212 Node[0] Epoch[50] Time cost=81.281
2016-05-02 13:17:25,377 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-02 13:17:27,307 Node[0] Epoch[50] Validation-accuracy=0.833233
2016-05-02 13:17:37,916 Node[0] Epoch[51] Batch [50] Speed: 606.52 samples/sec Train-accuracy=0.937187
2016-05-02 13:17:48,311 Node[0] Epoch[51] Batch [100] Speed: 615.67 samples/sec Train-accuracy=0.941562
2016-05-02 13:17:58,684 Node[0] Epoch[51] Batch [150] Speed: 617.04 samples/sec Train-accuracy=0.933906
2016-05-02 13:18:09,110 Node[0] Epoch[51] Batch [200] Speed: 613.83 samples/sec Train-accuracy=0.937813
2016-05-02 13:18:19,573 Node[0] Epoch[51] Batch [250] Speed: 611.71 samples/sec Train-accuracy=0.930000
2016-05-02 13:18:29,965 Node[0] Epoch[51] Batch [300] Speed: 615.89 samples/sec Train-accuracy=0.942656
2016-05-02 13:18:40,392 Node[0] Epoch[51] Batch [350] Speed: 613.81 samples/sec Train-accuracy=0.933438
2016-05-02 13:18:48,928 Node[0] Epoch[51] Resetting Data Iterator
2016-05-02 13:18:48,928 Node[0] Epoch[51] Time cost=81.621
2016-05-02 13:18:49,089 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-02 13:18:50,986 Node[0] Epoch[51] Validation-accuracy=0.866887
2016-05-02 13:19:01,431 Node[0] Epoch[52] Batch [50] Speed: 616.04 samples/sec Train-accuracy=0.940625
2016-05-02 13:19:11,868 Node[0] Epoch[52] Batch [100] Speed: 613.17 samples/sec Train-accuracy=0.932500
2016-05-02 13:19:22,257 Node[0] Epoch[52] Batch [150] Speed: 616.07 samples/sec Train-accuracy=0.942344
2016-05-02 13:19:32,679 Node[0] Epoch[52] Batch [200] Speed: 614.13 samples/sec Train-accuracy=0.940937
2016-05-02 13:19:43,087 Node[0] Epoch[52] Batch [250] Speed: 614.93 samples/sec Train-accuracy=0.933750
2016-05-02 13:19:53,487 Node[0] Epoch[52] Batch [300] Speed: 615.36 samples/sec Train-accuracy=0.940937
2016-05-02 13:20:03,910 Node[0] Epoch[52] Batch [350] Speed: 614.05 samples/sec Train-accuracy=0.940000
2016-05-02 13:20:12,483 Node[0] Epoch[52] Resetting Data Iterator
2016-05-02 13:20:12,483 Node[0] Epoch[52] Time cost=81.497
2016-05-02 13:20:12,645 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-02 13:20:14,601 Node[0] Epoch[52] Validation-accuracy=0.875501
2016-05-02 13:20:25,078 Node[0] Epoch[53] Batch [50] Speed: 614.07 samples/sec Train-accuracy=0.937031
2016-05-02 13:20:35,487 Node[0] Epoch[53] Batch [100] Speed: 614.87 samples/sec Train-accuracy=0.939375
2016-05-02 13:20:45,889 Node[0] Epoch[53] Batch [150] Speed: 615.24 samples/sec Train-accuracy=0.935625
2016-05-02 13:20:56,267 Node[0] Epoch[53] Batch [200] Speed: 616.72 samples/sec Train-accuracy=0.941094
2016-05-02 13:21:06,682 Node[0] Epoch[53] Batch [250] Speed: 614.51 samples/sec Train-accuracy=0.936406
2016-05-02 13:21:17,099 Node[0] Epoch[53] Batch [300] Speed: 614.46 samples/sec Train-accuracy=0.941875
2016-05-02 13:21:27,513 Node[0] Epoch[53] Batch [350] Speed: 614.57 samples/sec Train-accuracy=0.937031
2016-05-02 13:21:35,854 Node[0] Epoch[53] Resetting Data Iterator
2016-05-02 13:21:35,854 Node[0] Epoch[53] Time cost=81.253
2016-05-02 13:21:36,014 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-02 13:21:37,913 Node[0] Epoch[53] Validation-accuracy=0.863181
2016-05-02 13:21:48,430 Node[0] Epoch[54] Batch [50] Speed: 611.74 samples/sec Train-accuracy=0.934688
2016-05-02 13:21:58,858 Node[0] Epoch[54] Batch [100] Speed: 613.73 samples/sec Train-accuracy=0.936719
2016-05-02 13:22:09,264 Node[0] Epoch[54] Batch [150] Speed: 615.02 samples/sec Train-accuracy=0.935000
2016-05-02 13:22:19,643 Node[0] Epoch[54] Batch [200] Speed: 616.67 samples/sec Train-accuracy=0.935937
2016-05-02 13:22:30,064 Node[0] Epoch[54] Batch [250] Speed: 614.18 samples/sec Train-accuracy=0.939219
2016-05-02 13:22:40,465 Node[0] Epoch[54] Batch [300] Speed: 615.35 samples/sec Train-accuracy=0.942500
2016-05-02 13:22:50,853 Node[0] Epoch[54] Batch [350] Speed: 616.11 samples/sec Train-accuracy=0.940937
2016-05-02 13:22:59,377 Node[0] Epoch[54] Resetting Data Iterator
2016-05-02 13:22:59,378 Node[0] Epoch[54] Time cost=81.465
2016-05-02 13:22:59,540 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-02 13:23:01,465 Node[0] Epoch[54] Validation-accuracy=0.873998
2016-05-02 13:23:12,015 Node[0] Epoch[55] Batch [50] Speed: 609.95 samples/sec Train-accuracy=0.937656
2016-05-02 13:23:22,462 Node[0] Epoch[55] Batch [100] Speed: 612.66 samples/sec Train-accuracy=0.940781
2016-05-02 13:23:32,824 Node[0] Epoch[55] Batch [150] Speed: 617.62 samples/sec Train-accuracy=0.936562
2016-05-02 13:23:43,276 Node[0] Epoch[55] Batch [200] Speed: 612.33 samples/sec Train-accuracy=0.938906
2016-05-02 13:23:53,765 Node[0] Epoch[55] Batch [250] Speed: 610.21 samples/sec Train-accuracy=0.939375
2016-05-02 13:24:04,232 Node[0] Epoch[55] Batch [300] Speed: 611.45 samples/sec Train-accuracy=0.939219
2016-05-02 13:24:14,680 Node[0] Epoch[55] Batch [350] Speed: 612.57 samples/sec Train-accuracy=0.931094
2016-05-02 13:24:23,013 Node[0] Epoch[55] Resetting Data Iterator
2016-05-02 13:24:23,013 Node[0] Epoch[55] Time cost=81.548
2016-05-02 13:24:23,171 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-02 13:24:25,114 Node[0] Epoch[55] Validation-accuracy=0.865485
2016-05-02 13:24:35,548 Node[0] Epoch[56] Batch [50] Speed: 616.57 samples/sec Train-accuracy=0.942656
2016-05-02 13:24:45,950 Node[0] Epoch[56] Batch [100] Speed: 615.26 samples/sec Train-accuracy=0.940469
2016-05-02 13:24:56,371 Node[0] Epoch[56] Batch [150] Speed: 614.16 samples/sec Train-accuracy=0.939688
2016-05-02 13:25:06,766 Node[0] Epoch[56] Batch [200] Speed: 615.71 samples/sec Train-accuracy=0.936562
2016-05-02 13:25:17,155 Node[0] Epoch[56] Batch [250] Speed: 616.05 samples/sec Train-accuracy=0.936875
2016-05-02 13:25:27,583 Node[0] Epoch[56] Batch [300] Speed: 613.73 samples/sec Train-accuracy=0.941719
2016-05-02 13:25:38,024 Node[0] Epoch[56] Batch [350] Speed: 613.04 samples/sec Train-accuracy=0.939688
2016-05-02 13:25:46,549 Node[0] Epoch[56] Resetting Data Iterator
2016-05-02 13:25:46,549 Node[0] Epoch[56] Time cost=81.435
2016-05-02 13:25:46,714 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-02 13:25:48,848 Node[0] Epoch[56] Validation-accuracy=0.870352
2016-05-02 13:25:59,318 Node[0] Epoch[57] Batch [50] Speed: 614.41 samples/sec Train-accuracy=0.939219
2016-05-02 13:26:09,686 Node[0] Epoch[57] Batch [100] Speed: 617.33 samples/sec Train-accuracy=0.942031
2016-05-02 13:26:20,080 Node[0] Epoch[57] Batch [150] Speed: 615.74 samples/sec Train-accuracy=0.943750
2016-05-02 13:26:30,540 Node[0] Epoch[57] Batch [200] Speed: 611.86 samples/sec Train-accuracy=0.940156
2016-05-02 13:26:40,974 Node[0] Epoch[57] Batch [250] Speed: 613.40 samples/sec Train-accuracy=0.933125
2016-05-02 13:26:51,378 Node[0] Epoch[57] Batch [300] Speed: 615.20 samples/sec Train-accuracy=0.940312
2016-05-02 13:27:01,777 Node[0] Epoch[57] Batch [350] Speed: 615.42 samples/sec Train-accuracy=0.938906
2016-05-02 13:27:10,269 Node[0] Epoch[57] Resetting Data Iterator
2016-05-02 13:27:10,270 Node[0] Epoch[57] Time cost=81.422
2016-05-02 13:27:10,435 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-02 13:27:12,361 Node[0] Epoch[57] Validation-accuracy=0.877404
2016-05-02 13:27:22,895 Node[0] Epoch[58] Batch [50] Speed: 610.82 samples/sec Train-accuracy=0.942031
2016-05-02 13:27:33,323 Node[0] Epoch[58] Batch [100] Speed: 613.71 samples/sec Train-accuracy=0.944375
2016-05-02 13:27:43,675 Node[0] Epoch[58] Batch [150] Speed: 618.26 samples/sec Train-accuracy=0.944375
2016-05-02 13:27:54,046 Node[0] Epoch[58] Batch [200] Speed: 617.10 samples/sec Train-accuracy=0.944063
2016-05-02 13:28:04,769 Node[0] Epoch[58] Batch [250] Speed: 596.89 samples/sec Train-accuracy=0.941250
2016-05-02 13:28:15,343 Node[0] Epoch[58] Batch [300] Speed: 605.26 samples/sec Train-accuracy=0.938594
2016-05-02 13:28:25,767 Node[0] Epoch[58] Batch [350] Speed: 613.98 samples/sec Train-accuracy=0.945937
2016-05-02 13:28:34,062 Node[0] Epoch[58] Resetting Data Iterator
2016-05-02 13:28:34,062 Node[0] Epoch[58] Time cost=81.701
2016-05-02 13:28:34,223 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-02 13:28:36,152 Node[0] Epoch[58] Validation-accuracy=0.876603
2016-05-02 13:28:46,691 Node[0] Epoch[59] Batch [50] Speed: 610.51 samples/sec Train-accuracy=0.939219
2016-05-02 13:28:57,096 Node[0] Epoch[59] Batch [100] Speed: 615.09 samples/sec Train-accuracy=0.934688
2016-05-02 13:29:07,481 Node[0] Epoch[59] Batch [150] Speed: 616.30 samples/sec Train-accuracy=0.942813
2016-05-02 13:29:17,878 Node[0] Epoch[59] Batch [200] Speed: 615.59 samples/sec Train-accuracy=0.941875
2016-05-02 13:29:28,289 Node[0] Epoch[59] Batch [250] Speed: 614.76 samples/sec Train-accuracy=0.940156
2016-05-02 13:29:38,692 Node[0] Epoch[59] Batch [300] Speed: 615.23 samples/sec Train-accuracy=0.939219
2016-05-02 13:29:49,081 Node[0] Epoch[59] Batch [350] Speed: 616.06 samples/sec Train-accuracy=0.943750
2016-05-02 13:29:57,578 Node[0] Epoch[59] Resetting Data Iterator
2016-05-02 13:29:57,579 Node[0] Epoch[59] Time cost=81.426
2016-05-02 13:29:57,746 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-02 13:29:59,685 Node[0] Epoch[59] Validation-accuracy=0.841546
2016-05-02 13:30:10,217 Node[0] Epoch[60] Batch [50] Speed: 610.98 samples/sec Train-accuracy=0.937187
2016-05-02 13:30:20,646 Node[0] Epoch[60] Batch [100] Speed: 613.67 samples/sec Train-accuracy=0.941719
2016-05-02 13:30:31,025 Node[0] Epoch[60] Batch [150] Speed: 616.63 samples/sec Train-accuracy=0.938125
2016-05-02 13:30:41,419 Node[0] Epoch[60] Batch [200] Speed: 615.76 samples/sec Train-accuracy=0.944219
2016-05-02 13:30:51,785 Node[0] Epoch[60] Batch [250] Speed: 617.45 samples/sec Train-accuracy=0.944688
2016-05-02 13:31:02,207 Node[0] Epoch[60] Batch [300] Speed: 614.07 samples/sec Train-accuracy=0.942813
2016-05-02 13:31:12,601 Node[0] Epoch[60] Batch [350] Speed: 615.76 samples/sec Train-accuracy=0.932813
2016-05-02 13:31:21,123 Node[0] Epoch[60] Resetting Data Iterator
2016-05-02 13:31:21,124 Node[0] Epoch[60] Time cost=81.438
2016-05-02 13:31:21,285 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-02 13:31:23,214 Node[0] Epoch[60] Validation-accuracy=0.867588
2016-05-02 13:31:33,737 Node[0] Epoch[61] Batch [50] Speed: 611.46 samples/sec Train-accuracy=0.939375
2016-05-02 13:31:44,086 Node[0] Epoch[61] Batch [100] Speed: 618.43 samples/sec Train-accuracy=0.937500
2016-05-02 13:31:54,474 Node[0] Epoch[61] Batch [150] Speed: 616.11 samples/sec Train-accuracy=0.942344
2016-05-02 13:32:04,870 Node[0] Epoch[61] Batch [200] Speed: 615.63 samples/sec Train-accuracy=0.938438
2016-05-02 13:32:15,356 Node[0] Epoch[61] Batch [250] Speed: 610.35 samples/sec Train-accuracy=0.937031
2016-05-02 13:32:25,824 Node[0] Epoch[61] Batch [300] Speed: 611.42 samples/sec Train-accuracy=0.945937
2016-05-02 13:32:36,275 Node[0] Epoch[61] Batch [350] Speed: 612.43 samples/sec Train-accuracy=0.946875
2016-05-02 13:32:44,612 Node[0] Epoch[61] Resetting Data Iterator
2016-05-02 13:32:44,613 Node[0] Epoch[61] Time cost=81.398
2016-05-02 13:32:44,776 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-02 13:32:46,687 Node[0] Epoch[61] Validation-accuracy=0.881811
2016-05-02 13:32:57,120 Node[0] Epoch[62] Batch [50] Speed: 616.78 samples/sec Train-accuracy=0.944844
2016-05-02 13:33:07,479 Node[0] Epoch[62] Batch [100] Speed: 617.80 samples/sec Train-accuracy=0.941250
2016-05-02 13:33:17,855 Node[0] Epoch[62] Batch [150] Speed: 616.81 samples/sec Train-accuracy=0.938594
2016-05-02 13:33:28,250 Node[0] Epoch[62] Batch [200] Speed: 615.72 samples/sec Train-accuracy=0.941250
2016-05-02 13:33:38,677 Node[0] Epoch[62] Batch [250] Speed: 613.83 samples/sec Train-accuracy=0.942031
2016-05-02 13:33:49,075 Node[0] Epoch[62] Batch [300] Speed: 615.50 samples/sec Train-accuracy=0.947187
2016-05-02 13:33:59,491 Node[0] Epoch[62] Batch [350] Speed: 614.45 samples/sec Train-accuracy=0.936562
2016-05-02 13:34:08,097 Node[0] Epoch[62] Resetting Data Iterator
2016-05-02 13:34:08,098 Node[0] Epoch[62] Time cost=81.411
2016-05-02 13:34:08,265 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-02 13:34:10,170 Node[0] Epoch[62] Validation-accuracy=0.864984
2016-05-02 13:34:20,613 Node[0] Epoch[63] Batch [50] Speed: 616.13 samples/sec Train-accuracy=0.938906
2016-05-02 13:34:31,065 Node[0] Epoch[63] Batch [100] Speed: 612.30 samples/sec Train-accuracy=0.944531
2016-05-02 13:34:41,506 Node[0] Epoch[63] Batch [150] Speed: 612.97 samples/sec Train-accuracy=0.945781
2016-05-02 13:34:51,905 Node[0] Epoch[63] Batch [200] Speed: 615.50 samples/sec Train-accuracy=0.947031
2016-05-02 13:35:02,260 Node[0] Epoch[63] Batch [250] Speed: 618.06 samples/sec Train-accuracy=0.939688
2016-05-02 13:35:12,689 Node[0] Epoch[63] Batch [300] Speed: 613.71 samples/sec Train-accuracy=0.945156
2016-05-02 13:35:23,116 Node[0] Epoch[63] Batch [350] Speed: 613.78 samples/sec Train-accuracy=0.945625
2016-05-02 13:35:31,417 Node[0] Epoch[63] Resetting Data Iterator
2016-05-02 13:35:31,417 Node[0] Epoch[63] Time cost=81.247
2016-05-02 13:35:31,584 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-02 13:35:33,518 Node[0] Epoch[63] Validation-accuracy=0.863982
2016-05-02 13:35:44,101 Node[0] Epoch[64] Batch [50] Speed: 607.98 samples/sec Train-accuracy=0.943281
2016-05-02 13:35:54,491 Node[0] Epoch[64] Batch [100] Speed: 615.98 samples/sec Train-accuracy=0.942500
2016-05-02 13:36:04,889 Node[0] Epoch[64] Batch [150] Speed: 615.51 samples/sec Train-accuracy=0.939688
2016-05-02 13:36:15,259 Node[0] Epoch[64] Batch [200] Speed: 617.19 samples/sec Train-accuracy=0.940781
2016-05-02 13:36:25,630 Node[0] Epoch[64] Batch [250] Speed: 617.12 samples/sec Train-accuracy=0.933594
2016-05-02 13:36:36,018 Node[0] Epoch[64] Batch [300] Speed: 616.15 samples/sec Train-accuracy=0.946562
2016-05-02 13:36:46,389 Node[0] Epoch[64] Batch [350] Speed: 617.09 samples/sec Train-accuracy=0.945937
2016-05-02 13:36:54,904 Node[0] Epoch[64] Resetting Data Iterator
2016-05-02 13:36:54,905 Node[0] Epoch[64] Time cost=81.387
2016-05-02 13:36:55,071 Node[0] Saved checkpoint to "cifar10/resnet-0065.params"
2016-05-02 13:36:57,159 Node[0] Epoch[64] Validation-accuracy=0.869858
2016-05-02 13:37:07,691 Node[0] Epoch[65] Batch [50] Speed: 611.00 samples/sec Train-accuracy=0.946406
2016-05-02 13:37:18,110 Node[0] Epoch[65] Batch [100] Speed: 614.31 samples/sec Train-accuracy=0.948438
2016-05-02 13:37:28,509 Node[0] Epoch[65] Batch [150] Speed: 615.47 samples/sec Train-accuracy=0.940625
2016-05-02 13:37:38,935 Node[0] Epoch[65] Batch [200] Speed: 613.82 samples/sec Train-accuracy=0.936875
2016-05-02 13:37:49,310 Node[0] Epoch[65] Batch [250] Speed: 616.91 samples/sec Train-accuracy=0.944531
2016-05-02 13:37:59,763 Node[0] Epoch[65] Batch [300] Speed: 612.28 samples/sec Train-accuracy=0.951875
2016-05-02 13:38:10,240 Node[0] Epoch[65] Batch [350] Speed: 610.89 samples/sec Train-accuracy=0.945469
2016-05-02 13:38:18,825 Node[0] Epoch[65] Resetting Data Iterator
2016-05-02 13:38:18,825 Node[0] Epoch[65] Time cost=81.666
2016-05-02 13:38:18,990 Node[0] Saved checkpoint to "cifar10/resnet-0066.params"
2016-05-02 13:38:20,918 Node[0] Epoch[65] Validation-accuracy=0.874299
2016-05-02 13:38:31,338 Node[0] Epoch[66] Batch [50] Speed: 617.52 samples/sec Train-accuracy=0.941562
2016-05-02 13:38:41,697 Node[0] Epoch[66] Batch [100] Speed: 617.83 samples/sec Train-accuracy=0.943750
2016-05-02 13:38:52,115 Node[0] Epoch[66] Batch [150] Speed: 614.34 samples/sec Train-accuracy=0.951250
2016-05-02 13:39:02,523 Node[0] Epoch[66] Batch [200] Speed: 614.92 samples/sec Train-accuracy=0.942813
2016-05-02 13:39:12,980 Node[0] Epoch[66] Batch [250] Speed: 612.03 samples/sec Train-accuracy=0.942344
2016-05-02 13:39:23,485 Node[0] Epoch[66] Batch [300] Speed: 609.27 samples/sec Train-accuracy=0.941875
2016-05-02 13:39:33,949 Node[0] Epoch[66] Batch [350] Speed: 611.64 samples/sec Train-accuracy=0.945469
2016-05-02 13:39:42,255 Node[0] Epoch[66] Resetting Data Iterator
2016-05-02 13:39:42,256 Node[0] Epoch[66] Time cost=81.338
2016-05-02 13:39:42,417 Node[0] Saved checkpoint to "cifar10/resnet-0067.params"
2016-05-02 13:39:44,338 Node[0] Epoch[66] Validation-accuracy=0.866887
2016-05-02 13:39:54,830 Node[0] Epoch[67] Batch [50] Speed: 613.19 samples/sec Train-accuracy=0.942656
2016-05-02 13:40:05,267 Node[0] Epoch[67] Batch [100] Speed: 613.24 samples/sec Train-accuracy=0.945156
2016-05-02 13:40:15,644 Node[0] Epoch[67] Batch [150] Speed: 616.77 samples/sec Train-accuracy=0.940625
2016-05-02 13:40:26,056 Node[0] Epoch[67] Batch [200] Speed: 614.70 samples/sec Train-accuracy=0.944375
2016-05-02 13:40:36,485 Node[0] Epoch[67] Batch [250] Speed: 613.69 samples/sec Train-accuracy=0.947812
2016-05-02 13:40:46,998 Node[0] Epoch[67] Batch [300] Speed: 608.76 samples/sec Train-accuracy=0.944063
2016-05-02 13:40:57,470 Node[0] Epoch[67] Batch [350] Speed: 611.15 samples/sec Train-accuracy=0.942656
2016-05-02 13:41:06,048 Node[0] Epoch[67] Resetting Data Iterator
2016-05-02 13:41:06,048 Node[0] Epoch[67] Time cost=81.709
2016-05-02 13:41:06,218 Node[0] Saved checkpoint to "cifar10/resnet-0068.params"
2016-05-02 13:41:08,089 Node[0] Epoch[67] Validation-accuracy=0.880509
2016-05-02 13:41:18,513 Node[0] Epoch[68] Batch [50] Speed: 617.21 samples/sec Train-accuracy=0.940469
2016-05-02 13:41:28,980 Node[0] Epoch[68] Batch [100] Speed: 611.48 samples/sec Train-accuracy=0.945312
2016-05-02 13:41:39,380 Node[0] Epoch[68] Batch [150] Speed: 615.39 samples/sec Train-accuracy=0.940781
2016-05-02 13:41:49,774 Node[0] Epoch[68] Batch [200] Speed: 615.75 samples/sec Train-accuracy=0.948281
2016-05-02 13:42:00,203 Node[0] Epoch[68] Batch [250] Speed: 613.69 samples/sec Train-accuracy=0.945156
2016-05-02 13:42:10,688 Node[0] Epoch[68] Batch [300] Speed: 610.45 samples/sec Train-accuracy=0.949063
2016-05-02 13:42:21,261 Node[0] Epoch[68] Batch [350] Speed: 605.30 samples/sec Train-accuracy=0.945000
2016-05-02 13:42:29,870 Node[0] Epoch[68] Resetting Data Iterator
2016-05-02 13:42:29,870 Node[0] Epoch[68] Time cost=81.781
2016-05-02 13:42:30,032 Node[0] Saved checkpoint to "cifar10/resnet-0069.params"
2016-05-02 13:42:31,920 Node[0] Epoch[68] Validation-accuracy=0.871394
2016-05-02 13:42:42,365 Node[0] Epoch[69] Batch [50] Speed: 616.00 samples/sec Train-accuracy=0.940312
2016-05-02 13:42:52,784 Node[0] Epoch[69] Batch [100] Speed: 614.27 samples/sec Train-accuracy=0.942344
2016-05-02 13:43:03,145 Node[0] Epoch[69] Batch [150] Speed: 617.72 samples/sec Train-accuracy=0.944531
2016-05-02 13:43:13,519 Node[0] Epoch[69] Batch [200] Speed: 616.96 samples/sec Train-accuracy=0.943906
2016-05-02 13:43:23,922 Node[0] Epoch[69] Batch [250] Speed: 615.22 samples/sec Train-accuracy=0.947344
2016-05-02 13:43:34,427 Node[0] Epoch[69] Batch [300] Speed: 609.23 samples/sec Train-accuracy=0.946719
2016-05-02 13:43:44,903 Node[0] Epoch[69] Batch [350] Speed: 610.94 samples/sec Train-accuracy=0.947344
2016-05-02 13:43:53,286 Node[0] Epoch[69] Resetting Data Iterator
2016-05-02 13:43:53,286 Node[0] Epoch[69] Time cost=81.365
2016-05-02 13:43:53,449 Node[0] Saved checkpoint to "cifar10/resnet-0070.params"
2016-05-02 13:43:55,346 Node[0] Epoch[69] Validation-accuracy=0.874900
2016-05-02 13:44:05,810 Node[0] Epoch[70] Batch [50] Speed: 614.84 samples/sec Train-accuracy=0.945469
2016-05-02 13:44:16,293 Node[0] Epoch[70] Batch [100] Speed: 610.55 samples/sec Train-accuracy=0.944844
2016-05-02 13:44:26,682 Node[0] Epoch[70] Batch [150] Speed: 616.06 samples/sec Train-accuracy=0.942969
2016-05-02 13:44:37,055 Node[0] Epoch[70] Batch [200] Speed: 617.00 samples/sec Train-accuracy=0.951250
2016-05-02 13:44:47,419 Node[0] Epoch[70] Batch [250] Speed: 617.55 samples/sec Train-accuracy=0.948594
2016-05-02 13:44:57,859 Node[0] Epoch[70] Batch [300] Speed: 613.02 samples/sec Train-accuracy=0.945625
2016-05-02 13:45:08,317 Node[0] Epoch[70] Batch [350] Speed: 612.02 samples/sec Train-accuracy=0.945781
2016-05-02 13:45:16,882 Node[0] Epoch[70] Resetting Data Iterator
2016-05-02 13:45:16,883 Node[0] Epoch[70] Time cost=81.536
2016-05-02 13:45:17,046 Node[0] Saved checkpoint to "cifar10/resnet-0071.params"
2016-05-02 13:45:18,991 Node[0] Epoch[70] Validation-accuracy=0.869692
2016-05-02 13:45:29,404 Node[0] Epoch[71] Batch [50] Speed: 617.90 samples/sec Train-accuracy=0.950000
2016-05-02 13:45:39,822 Node[0] Epoch[71] Batch [100] Speed: 614.38 samples/sec Train-accuracy=0.944844
2016-05-02 13:45:50,248 Node[0] Epoch[71] Batch [150] Speed: 613.86 samples/sec Train-accuracy=0.943750
2016-05-02 13:46:00,681 Node[0] Epoch[71] Batch [200] Speed: 613.46 samples/sec Train-accuracy=0.948438
2016-05-02 13:46:11,163 Node[0] Epoch[71] Batch [250] Speed: 610.59 samples/sec Train-accuracy=0.943438
2016-05-02 13:46:21,677 Node[0] Epoch[71] Batch [300] Speed: 608.74 samples/sec Train-accuracy=0.948125
2016-05-02 13:46:32,162 Node[0] Epoch[71] Batch [350] Speed: 610.38 samples/sec Train-accuracy=0.946250
2016-05-02 13:46:40,507 Node[0] Epoch[71] Resetting Data Iterator
2016-05-02 13:46:40,507 Node[0] Epoch[71] Time cost=81.516
2016-05-02 13:46:40,669 Node[0] Saved checkpoint to "cifar10/resnet-0072.params"
2016-05-02 13:46:42,569 Node[0] Epoch[71] Validation-accuracy=0.894030
2016-05-02 13:46:52,939 Node[0] Epoch[72] Batch [50] Speed: 620.47 samples/sec Train-accuracy=0.948281
2016-05-02 13:47:03,327 Node[0] Epoch[72] Batch [100] Speed: 616.10 samples/sec Train-accuracy=0.943125
2016-05-02 13:47:13,675 Node[0] Epoch[72] Batch [150] Speed: 618.46 samples/sec Train-accuracy=0.936719
2016-05-02 13:47:24,162 Node[0] Epoch[72] Batch [200] Speed: 610.29 samples/sec Train-accuracy=0.940156
2016-05-02 13:47:34,628 Node[0] Epoch[72] Batch [250] Speed: 611.53 samples/sec Train-accuracy=0.944063
2016-05-02 13:47:45,101 Node[0] Epoch[72] Batch [300] Speed: 611.13 samples/sec Train-accuracy=0.948281
2016-05-02 13:47:55,569 Node[0] Epoch[72] Batch [350] Speed: 611.38 samples/sec Train-accuracy=0.943125
2016-05-02 13:48:04,144 Node[0] Epoch[72] Resetting Data Iterator
2016-05-02 13:48:04,145 Node[0] Epoch[72] Time cost=81.576
2016-05-02 13:48:04,311 Node[0] Saved checkpoint to "cifar10/resnet-0073.params"
2016-05-02 13:48:06,420 Node[0] Epoch[72] Validation-accuracy=0.875791
2016-05-02 13:48:16,853 Node[0] Epoch[73] Batch [50] Speed: 616.64 samples/sec Train-accuracy=0.947969
2016-05-02 13:48:27,333 Node[0] Epoch[73] Batch [100] Speed: 610.68 samples/sec Train-accuracy=0.949219
2016-05-02 13:48:37,717 Node[0] Epoch[73] Batch [150] Speed: 616.37 samples/sec Train-accuracy=0.946250
2016-05-02 13:48:48,139 Node[0] Epoch[73] Batch [200] Speed: 614.09 samples/sec Train-accuracy=0.944063
2016-05-02 13:48:58,550 Node[0] Epoch[73] Batch [250] Speed: 614.76 samples/sec Train-accuracy=0.944688
2016-05-02 13:49:09,019 Node[0] Epoch[73] Batch [300] Speed: 611.30 samples/sec Train-accuracy=0.949219
2016-05-02 13:49:19,448 Node[0] Epoch[73] Batch [350] Speed: 613.73 samples/sec Train-accuracy=0.944375
2016-05-02 13:49:28,001 Node[0] Epoch[73] Resetting Data Iterator
2016-05-02 13:49:28,001 Node[0] Epoch[73] Time cost=81.581
2016-05-02 13:49:28,164 Node[0] Saved checkpoint to "cifar10/resnet-0074.params"
2016-05-02 13:49:30,060 Node[0] Epoch[73] Validation-accuracy=0.883213
2016-05-02 13:49:40,616 Node[0] Epoch[74] Batch [50] Speed: 609.46 samples/sec Train-accuracy=0.943125
2016-05-02 13:49:50,970 Node[0] Epoch[74] Batch [100] Speed: 618.16 samples/sec Train-accuracy=0.945781
2016-05-02 13:50:01,353 Node[0] Epoch[74] Batch [150] Speed: 616.39 samples/sec Train-accuracy=0.943281
2016-05-02 13:50:11,812 Node[0] Epoch[74] Batch [200] Speed: 611.94 samples/sec Train-accuracy=0.946562
2016-05-02 13:50:22,317 Node[0] Epoch[74] Batch [250] Speed: 609.27 samples/sec Train-accuracy=0.938125
2016-05-02 13:50:32,818 Node[0] Epoch[74] Batch [300] Speed: 609.45 samples/sec Train-accuracy=0.945000
2016-05-02 13:50:43,284 Node[0] Epoch[74] Batch [350] Speed: 611.56 samples/sec Train-accuracy=0.942031
2016-05-02 13:50:51,683 Node[0] Epoch[74] Resetting Data Iterator
2016-05-02 13:50:51,684 Node[0] Epoch[74] Time cost=81.623
2016-05-02 13:50:51,846 Node[0] Saved checkpoint to "cifar10/resnet-0075.params"
2016-05-02 13:50:53,742 Node[0] Epoch[74] Validation-accuracy=0.878305
2016-05-02 13:51:04,215 Node[0] Epoch[75] Batch [50] Speed: 614.25 samples/sec Train-accuracy=0.945000
2016-05-02 13:51:14,675 Node[0] Epoch[75] Batch [100] Speed: 611.87 samples/sec Train-accuracy=0.940937
2016-05-02 13:51:25,064 Node[0] Epoch[75] Batch [150] Speed: 616.04 samples/sec Train-accuracy=0.947969
2016-05-02 13:51:35,469 Node[0] Epoch[75] Batch [200] Speed: 615.09 samples/sec Train-accuracy=0.950156
2016-05-02 13:51:45,955 Node[0] Epoch[75] Batch [250] Speed: 610.40 samples/sec Train-accuracy=0.949531
2016-05-02 13:51:56,470 Node[0] Epoch[75] Batch [300] Speed: 608.67 samples/sec Train-accuracy=0.951406
2016-05-02 13:52:06,954 Node[0] Epoch[75] Batch [350] Speed: 610.47 samples/sec Train-accuracy=0.942969
2016-05-02 13:52:15,528 Node[0] Epoch[75] Resetting Data Iterator
2016-05-02 13:52:15,528 Node[0] Epoch[75] Time cost=81.786
2016-05-02 13:52:15,696 Node[0] Saved checkpoint to "cifar10/resnet-0076.params"
2016-05-02 13:52:17,615 Node[0] Epoch[75] Validation-accuracy=0.876002
2016-05-02 13:52:28,132 Node[0] Epoch[76] Batch [50] Speed: 611.68 samples/sec Train-accuracy=0.942187
2016-05-02 13:52:38,566 Node[0] Epoch[76] Batch [100] Speed: 613.40 samples/sec Train-accuracy=0.946250
2016-05-02 13:52:49,001 Node[0] Epoch[76] Batch [150] Speed: 613.32 samples/sec Train-accuracy=0.942500
2016-05-02 13:52:59,440 Node[0] Epoch[76] Batch [200] Speed: 613.09 samples/sec Train-accuracy=0.950000
2016-05-02 13:53:09,940 Node[0] Epoch[76] Batch [250] Speed: 609.58 samples/sec Train-accuracy=0.944375
2016-05-02 13:53:20,406 Node[0] Epoch[76] Batch [300] Speed: 611.52 samples/sec Train-accuracy=0.945312
2016-05-02 13:53:30,886 Node[0] Epoch[76] Batch [350] Speed: 610.72 samples/sec Train-accuracy=0.940937
2016-05-02 13:53:39,531 Node[0] Epoch[76] Resetting Data Iterator
2016-05-02 13:53:39,531 Node[0] Epoch[76] Time cost=81.916
2016-05-02 13:53:39,695 Node[0] Saved checkpoint to "cifar10/resnet-0077.params"
2016-05-02 13:53:41,598 Node[0] Epoch[76] Validation-accuracy=0.854367
2016-05-02 13:53:52,025 Node[0] Epoch[77] Batch [50] Speed: 617.06 samples/sec Train-accuracy=0.947500
2016-05-02 13:54:02,441 Node[0] Epoch[77] Batch [100] Speed: 614.42 samples/sec Train-accuracy=0.949688
2016-05-02 13:54:12,783 Node[0] Epoch[77] Batch [150] Speed: 618.87 samples/sec Train-accuracy=0.944063
2016-05-02 13:54:23,127 Node[0] Epoch[77] Batch [200] Speed: 618.76 samples/sec Train-accuracy=0.947500
2016-05-02 13:54:33,586 Node[0] Epoch[77] Batch [250] Speed: 611.89 samples/sec Train-accuracy=0.947969
2016-05-02 13:54:44,051 Node[0] Epoch[77] Batch [300] Speed: 611.57 samples/sec Train-accuracy=0.950313
2016-05-02 13:54:54,541 Node[0] Epoch[77] Batch [350] Speed: 610.16 samples/sec Train-accuracy=0.943281
2016-05-02 13:55:02,894 Node[0] Epoch[77] Resetting Data Iterator
2016-05-02 13:55:02,894 Node[0] Epoch[77] Time cost=81.297
2016-05-02 13:55:03,060 Node[0] Saved checkpoint to "cifar10/resnet-0078.params"
2016-05-02 13:55:04,971 Node[0] Epoch[77] Validation-accuracy=0.869892
2016-05-02 13:55:15,381 Node[0] Epoch[78] Batch [50] Speed: 617.95 samples/sec Train-accuracy=0.947031
2016-05-02 13:55:25,853 Node[0] Epoch[78] Batch [100] Speed: 611.21 samples/sec Train-accuracy=0.948750
2016-05-02 13:55:36,225 Node[0] Epoch[78] Batch [150] Speed: 617.04 samples/sec Train-accuracy=0.943750
2016-05-02 13:55:46,624 Node[0] Epoch[78] Batch [200] Speed: 615.43 samples/sec Train-accuracy=0.946406
2016-05-02 13:55:57,048 Node[0] Epoch[78] Batch [250] Speed: 614.01 samples/sec Train-accuracy=0.949375
2016-05-02 13:56:07,444 Node[0] Epoch[78] Batch [300] Speed: 615.64 samples/sec Train-accuracy=0.947187
2016-05-02 13:56:17,956 Node[0] Epoch[78] Batch [350] Speed: 608.84 samples/sec Train-accuracy=0.947656
2016-05-02 13:56:26,529 Node[0] Epoch[78] Resetting Data Iterator
2016-05-02 13:56:26,529 Node[0] Epoch[78] Time cost=81.558
2016-05-02 13:56:26,692 Node[0] Saved checkpoint to "cifar10/resnet-0079.params"
2016-05-02 13:56:28,594 Node[0] Epoch[78] Validation-accuracy=0.860377
2016-05-02 13:56:39,007 Node[0] Epoch[79] Batch [50] Speed: 617.81 samples/sec Train-accuracy=0.949219
2016-05-02 13:56:49,411 Node[0] Epoch[79] Batch [100] Speed: 615.19 samples/sec Train-accuracy=0.947187
2016-05-02 13:56:59,768 Node[0] Epoch[79] Batch [150] Speed: 617.95 samples/sec Train-accuracy=0.945000
2016-05-02 13:57:10,127 Node[0] Epoch[79] Batch [200] Speed: 617.86 samples/sec Train-accuracy=0.950625
2016-05-02 13:57:20,500 Node[0] Epoch[79] Batch [250] Speed: 616.98 samples/sec Train-accuracy=0.947031
2016-05-02 13:57:30,917 Node[0] Epoch[79] Batch [300] Speed: 614.41 samples/sec Train-accuracy=0.950313
2016-05-02 13:57:39,226 Node[0] Update[31201]: Change learning rate to 1.00000e-02
2016-05-02 13:57:41,303 Node[0] Epoch[79] Batch [350] Speed: 616.21 samples/sec Train-accuracy=0.950469
2016-05-02 13:57:49,635 Node[0] Epoch[79] Resetting Data Iterator
2016-05-02 13:57:49,635 Node[0] Epoch[79] Time cost=81.042
2016-05-02 13:57:49,795 Node[0] Saved checkpoint to "cifar10/resnet-0080.params"
2016-05-02 13:57:51,727 Node[0] Epoch[79] Validation-accuracy=0.893830
2016-05-02 13:58:02,323 Node[0] Epoch[80] Batch [50] Speed: 607.25 samples/sec Train-accuracy=0.951719
2016-05-02 13:58:12,733 Node[0] Epoch[80] Batch [100] Speed: 614.81 samples/sec Train-accuracy=0.967812
2016-05-02 13:58:23,144 Node[0] Epoch[80] Batch [150] Speed: 614.77 samples/sec Train-accuracy=0.968906
2016-05-02 13:58:33,539 Node[0] Epoch[80] Batch [200] Speed: 615.67 samples/sec Train-accuracy=0.973750
2016-05-02 13:58:43,951 Node[0] Epoch[80] Batch [250] Speed: 614.71 samples/sec Train-accuracy=0.974688
2016-05-02 13:58:54,330 Node[0] Epoch[80] Batch [300] Speed: 616.61 samples/sec Train-accuracy=0.977187
2016-05-02 13:59:04,792 Node[0] Epoch[80] Batch [350] Speed: 611.76 samples/sec Train-accuracy=0.979531
2016-05-02 13:59:13,394 Node[0] Epoch[80] Resetting Data Iterator
2016-05-02 13:59:13,394 Node[0] Epoch[80] Time cost=81.667
2016-05-02 13:59:13,556 Node[0] Saved checkpoint to "cifar10/resnet-0081.params"
2016-05-02 13:59:15,670 Node[0] Epoch[80] Validation-accuracy=0.912579
2016-05-02 13:59:26,154 Node[0] Epoch[81] Batch [50] Speed: 613.70 samples/sec Train-accuracy=0.977187
2016-05-02 13:59:36,534 Node[0] Epoch[81] Batch [100] Speed: 616.57 samples/sec Train-accuracy=0.976875
2016-05-02 13:59:46,940 Node[0] Epoch[81] Batch [150] Speed: 615.08 samples/sec Train-accuracy=0.980781
2016-05-02 13:59:57,301 Node[0] Epoch[81] Batch [200] Speed: 617.69 samples/sec Train-accuracy=0.978125
2016-05-02 14:00:07,695 Node[0] Epoch[81] Batch [250] Speed: 615.75 samples/sec Train-accuracy=0.982812
2016-05-02 14:00:18,144 Node[0] Epoch[81] Batch [300] Speed: 612.55 samples/sec Train-accuracy=0.984531
2016-05-02 14:00:28,622 Node[0] Epoch[81] Batch [350] Speed: 610.81 samples/sec Train-accuracy=0.986875
2016-05-02 14:00:37,184 Node[0] Epoch[81] Resetting Data Iterator
2016-05-02 14:00:37,184 Node[0] Epoch[81] Time cost=81.514
2016-05-02 14:00:37,353 Node[0] Saved checkpoint to "cifar10/resnet-0082.params"
2016-05-02 14:00:39,259 Node[0] Epoch[81] Validation-accuracy=0.917468
2016-05-02 14:00:49,681 Node[0] Epoch[82] Batch [50] Speed: 617.35 samples/sec Train-accuracy=0.980625
2016-05-02 14:01:00,175 Node[0] Epoch[82] Batch [100] Speed: 609.88 samples/sec Train-accuracy=0.985156
2016-05-02 14:01:10,577 Node[0] Epoch[82] Batch [150] Speed: 615.29 samples/sec Train-accuracy=0.980781
2016-05-02 14:01:21,029 Node[0] Epoch[82] Batch [200] Speed: 612.34 samples/sec Train-accuracy=0.982031
2016-05-02 14:01:31,414 Node[0] Epoch[82] Batch [250] Speed: 616.30 samples/sec Train-accuracy=0.982500
2016-05-02 14:01:41,786 Node[0] Epoch[82] Batch [300] Speed: 617.07 samples/sec Train-accuracy=0.986094
2016-05-02 14:01:52,237 Node[0] Epoch[82] Batch [350] Speed: 612.36 samples/sec Train-accuracy=0.987187
2016-05-02 14:02:00,631 Node[0] Epoch[82] Resetting Data Iterator
2016-05-02 14:02:00,632 Node[0] Epoch[82] Time cost=81.373
2016-05-02 14:02:00,799 Node[0] Saved checkpoint to "cifar10/resnet-0083.params"
2016-05-02 14:02:02,713 Node[0] Epoch[82] Validation-accuracy=0.919872
2016-05-02 14:02:13,129 Node[0] Epoch[83] Batch [50] Speed: 617.80 samples/sec Train-accuracy=0.984062
2016-05-02 14:02:23,465 Node[0] Epoch[83] Batch [100] Speed: 619.22 samples/sec Train-accuracy=0.985313
2016-05-02 14:02:33,875 Node[0] Epoch[83] Batch [150] Speed: 614.82 samples/sec Train-accuracy=0.985469
2016-05-02 14:02:44,348 Node[0] Epoch[83] Batch [200] Speed: 611.10 samples/sec Train-accuracy=0.985156
2016-05-02 14:02:54,829 Node[0] Epoch[83] Batch [250] Speed: 610.62 samples/sec Train-accuracy=0.986563
2016-05-02 14:03:05,259 Node[0] Epoch[83] Batch [300] Speed: 613.64 samples/sec Train-accuracy=0.990000
2016-05-02 14:03:15,604 Node[0] Epoch[83] Batch [350] Speed: 618.67 samples/sec Train-accuracy=0.987344
2016-05-02 14:03:24,127 Node[0] Epoch[83] Resetting Data Iterator
2016-05-02 14:03:24,127 Node[0] Epoch[83] Time cost=81.414
2016-05-02 14:03:24,297 Node[0] Saved checkpoint to "cifar10/resnet-0084.params"
2016-05-02 14:03:26,228 Node[0] Epoch[83] Validation-accuracy=0.917869
2016-05-02 14:03:36,655 Node[0] Epoch[84] Batch [50] Speed: 617.08 samples/sec Train-accuracy=0.987656
2016-05-02 14:03:47,027 Node[0] Epoch[84] Batch [100] Speed: 617.02 samples/sec Train-accuracy=0.986406
2016-05-02 14:03:57,406 Node[0] Epoch[84] Batch [150] Speed: 616.68 samples/sec Train-accuracy=0.987344
2016-05-02 14:04:07,795 Node[0] Epoch[84] Batch [200] Speed: 616.01 samples/sec Train-accuracy=0.987969
2016-05-02 14:04:18,215 Node[0] Epoch[84] Batch [250] Speed: 614.23 samples/sec Train-accuracy=0.989219
2016-05-02 14:04:28,607 Node[0] Epoch[84] Batch [300] Speed: 615.91 samples/sec Train-accuracy=0.987812
2016-05-02 14:04:38,992 Node[0] Epoch[84] Batch [350] Speed: 616.26 samples/sec Train-accuracy=0.991563
2016-05-02 14:04:47,521 Node[0] Epoch[84] Resetting Data Iterator
2016-05-02 14:04:47,521 Node[0] Epoch[84] Time cost=81.293
2016-05-02 14:04:47,688 Node[0] Saved checkpoint to "cifar10/resnet-0085.params"
2016-05-02 14:04:49,654 Node[0] Epoch[84] Validation-accuracy=0.919671
2016-05-02 14:05:00,049 Node[0] Epoch[85] Batch [50] Speed: 618.98 samples/sec Train-accuracy=0.987656
2016-05-02 14:05:10,410 Node[0] Epoch[85] Batch [100] Speed: 617.75 samples/sec Train-accuracy=0.988594
2016-05-02 14:05:20,798 Node[0] Epoch[85] Batch [150] Speed: 616.13 samples/sec Train-accuracy=0.989062
2016-05-02 14:05:31,220 Node[0] Epoch[85] Batch [200] Speed: 614.07 samples/sec Train-accuracy=0.989375
2016-05-02 14:05:41,585 Node[0] Epoch[85] Batch [250] Speed: 617.50 samples/sec Train-accuracy=0.987969
2016-05-02 14:05:51,970 Node[0] Epoch[85] Batch [300] Speed: 616.27 samples/sec Train-accuracy=0.990625
2016-05-02 14:06:02,373 Node[0] Epoch[85] Batch [350] Speed: 615.22 samples/sec Train-accuracy=0.990000
2016-05-02 14:06:10,691 Node[0] Epoch[85] Resetting Data Iterator
2016-05-02 14:06:10,691 Node[0] Epoch[85] Time cost=81.036
2016-05-02 14:06:10,853 Node[0] Saved checkpoint to "cifar10/resnet-0086.params"
2016-05-02 14:06:12,772 Node[0] Epoch[85] Validation-accuracy=0.920573
2016-05-02 14:06:23,165 Node[0] Epoch[86] Batch [50] Speed: 619.02 samples/sec Train-accuracy=0.987812
2016-05-02 14:06:33,504 Node[0] Epoch[86] Batch [100] Speed: 619.04 samples/sec Train-accuracy=0.988594
2016-05-02 14:06:43,875 Node[0] Epoch[86] Batch [150] Speed: 617.12 samples/sec Train-accuracy=0.989219
2016-05-02 14:06:54,345 Node[0] Epoch[86] Batch [200] Speed: 611.26 samples/sec Train-accuracy=0.989844
2016-05-02 14:07:04,749 Node[0] Epoch[86] Batch [250] Speed: 615.19 samples/sec Train-accuracy=0.989375
2016-05-02 14:07:15,187 Node[0] Epoch[86] Batch [300] Speed: 613.14 samples/sec Train-accuracy=0.993281
2016-05-02 14:07:25,683 Node[0] Epoch[86] Batch [350] Speed: 609.75 samples/sec Train-accuracy=0.991563
2016-05-02 14:07:34,282 Node[0] Epoch[86] Resetting Data Iterator
2016-05-02 14:07:34,283 Node[0] Epoch[86] Time cost=81.511
2016-05-02 14:07:34,444 Node[0] Saved checkpoint to "cifar10/resnet-0087.params"
2016-05-02 14:07:36,355 Node[0] Epoch[86] Validation-accuracy=0.922276
2016-05-02 14:07:46,788 Node[0] Epoch[87] Batch [50] Speed: 616.63 samples/sec Train-accuracy=0.991875
2016-05-02 14:07:57,227 Node[0] Epoch[87] Batch [100] Speed: 613.13 samples/sec Train-accuracy=0.993281
2016-05-02 14:08:07,615 Node[0] Epoch[87] Batch [150] Speed: 616.12 samples/sec Train-accuracy=0.990469
2016-05-02 14:08:18,006 Node[0] Epoch[87] Batch [200] Speed: 615.92 samples/sec Train-accuracy=0.989375
2016-05-02 14:08:28,380 Node[0] Epoch[87] Batch [250] Speed: 616.92 samples/sec Train-accuracy=0.992812
2016-05-02 14:08:38,725 Node[0] Epoch[87] Batch [300] Speed: 618.73 samples/sec Train-accuracy=0.992812
2016-05-02 14:08:49,095 Node[0] Epoch[87] Batch [350] Speed: 617.15 samples/sec Train-accuracy=0.993281
2016-05-02 14:08:57,452 Node[0] Epoch[87] Resetting Data Iterator
2016-05-02 14:08:57,453 Node[0] Epoch[87] Time cost=81.097
2016-05-02 14:08:57,618 Node[0] Saved checkpoint to "cifar10/resnet-0088.params"
2016-05-02 14:08:59,528 Node[0] Epoch[87] Validation-accuracy=0.921374
2016-05-02 14:09:10,070 Node[0] Epoch[88] Batch [50] Speed: 610.30 samples/sec Train-accuracy=0.990469
2016-05-02 14:09:20,485 Node[0] Epoch[88] Batch [100] Speed: 614.48 samples/sec Train-accuracy=0.991563
2016-05-02 14:09:30,919 Node[0] Epoch[88] Batch [150] Speed: 613.42 samples/sec Train-accuracy=0.993125
2016-05-02 14:09:41,317 Node[0] Epoch[88] Batch [200] Speed: 615.55 samples/sec Train-accuracy=0.991875
2016-05-02 14:09:51,670 Node[0] Epoch[88] Batch [250] Speed: 618.16 samples/sec Train-accuracy=0.991406
2016-05-02 14:10:02,013 Node[0] Epoch[88] Batch [300] Speed: 618.79 samples/sec Train-accuracy=0.992500
2016-05-02 14:10:12,427 Node[0] Epoch[88] Batch [350] Speed: 614.61 samples/sec Train-accuracy=0.992500
2016-05-02 14:10:20,971 Node[0] Epoch[88] Resetting Data Iterator
2016-05-02 14:10:20,971 Node[0] Epoch[88] Time cost=81.442
2016-05-02 14:10:21,140 Node[0] Saved checkpoint to "cifar10/resnet-0089.params"
2016-05-02 14:10:23,268 Node[0] Epoch[88] Validation-accuracy=0.920688
2016-05-02 14:10:33,808 Node[0] Epoch[89] Batch [50] Speed: 610.38 samples/sec Train-accuracy=0.991563
2016-05-02 14:10:44,282 Node[0] Epoch[89] Batch [100] Speed: 611.03 samples/sec Train-accuracy=0.991719
2016-05-02 14:10:54,628 Node[0] Epoch[89] Batch [150] Speed: 618.61 samples/sec Train-accuracy=0.992656
2016-05-02 14:11:05,016 Node[0] Epoch[89] Batch [200] Speed: 616.11 samples/sec Train-accuracy=0.990625
2016-05-02 14:11:15,432 Node[0] Epoch[89] Batch [250] Speed: 614.46 samples/sec Train-accuracy=0.993594
2016-05-02 14:11:25,851 Node[0] Epoch[89] Batch [300] Speed: 614.25 samples/sec Train-accuracy=0.992812
2016-05-02 14:11:36,272 Node[0] Epoch[89] Batch [350] Speed: 614.18 samples/sec Train-accuracy=0.994062
2016-05-02 14:11:44,787 Node[0] Epoch[89] Resetting Data Iterator
2016-05-02 14:11:44,788 Node[0] Epoch[89] Time cost=81.519
2016-05-02 14:11:44,951 Node[0] Saved checkpoint to "cifar10/resnet-0090.params"
2016-05-02 14:11:46,854 Node[0] Epoch[89] Validation-accuracy=0.921575
2016-05-02 14:11:57,405 Node[0] Epoch[90] Batch [50] Speed: 609.76 samples/sec Train-accuracy=0.992031
2016-05-02 14:12:07,797 Node[0] Epoch[90] Batch [100] Speed: 615.86 samples/sec Train-accuracy=0.992188
2016-05-02 14:12:18,184 Node[0] Epoch[90] Batch [150] Speed: 616.21 samples/sec Train-accuracy=0.993281
2016-05-02 14:12:28,564 Node[0] Epoch[90] Batch [200] Speed: 616.58 samples/sec Train-accuracy=0.995625
2016-05-02 14:12:38,978 Node[0] Epoch[90] Batch [250] Speed: 614.59 samples/sec Train-accuracy=0.992031
2016-05-02 14:12:49,377 Node[0] Epoch[90] Batch [300] Speed: 615.46 samples/sec Train-accuracy=0.995313
2016-05-02 14:12:59,872 Node[0] Epoch[90] Batch [350] Speed: 609.78 samples/sec Train-accuracy=0.994062
2016-05-02 14:13:08,272 Node[0] Epoch[90] Resetting Data Iterator
2016-05-02 14:13:08,273 Node[0] Epoch[90] Time cost=81.419
2016-05-02 14:13:08,434 Node[0] Saved checkpoint to "cifar10/resnet-0091.params"
2016-05-02 14:13:10,350 Node[0] Epoch[90] Validation-accuracy=0.921474
2016-05-02 14:13:20,765 Node[0] Epoch[91] Batch [50] Speed: 617.71 samples/sec Train-accuracy=0.993437
2016-05-02 14:13:31,200 Node[0] Epoch[91] Batch [100] Speed: 613.30 samples/sec Train-accuracy=0.993125
2016-05-02 14:13:41,575 Node[0] Epoch[91] Batch [150] Speed: 616.92 samples/sec Train-accuracy=0.995156
2016-05-02 14:13:51,914 Node[0] Epoch[91] Batch [200] Speed: 618.99 samples/sec Train-accuracy=0.993125
2016-05-02 14:14:02,299 Node[0] Epoch[91] Batch [250] Speed: 616.29 samples/sec Train-accuracy=0.994219
2016-05-02 14:14:12,717 Node[0] Epoch[91] Batch [300] Speed: 614.37 samples/sec Train-accuracy=0.994062
2016-05-02 14:14:23,180 Node[0] Epoch[91] Batch [350] Speed: 611.67 samples/sec Train-accuracy=0.993906
2016-05-02 14:14:31,741 Node[0] Epoch[91] Resetting Data Iterator
2016-05-02 14:14:31,741 Node[0] Epoch[91] Time cost=81.391
2016-05-02 14:14:31,905 Node[0] Saved checkpoint to "cifar10/resnet-0092.params"
2016-05-02 14:14:33,816 Node[0] Epoch[91] Validation-accuracy=0.919772
2016-05-02 14:14:44,187 Node[0] Epoch[92] Batch [50] Speed: 620.40 samples/sec Train-accuracy=0.992656
2016-05-02 14:14:54,575 Node[0] Epoch[92] Batch [100] Speed: 616.09 samples/sec Train-accuracy=0.993281
2016-05-02 14:15:04,992 Node[0] Epoch[92] Batch [150] Speed: 614.44 samples/sec Train-accuracy=0.995000
2016-05-02 14:15:15,413 Node[0] Epoch[92] Batch [200] Speed: 614.11 samples/sec Train-accuracy=0.993437
2016-05-02 14:15:25,809 Node[0] Epoch[92] Batch [250] Speed: 615.66 samples/sec Train-accuracy=0.994062
2016-05-02 14:15:36,205 Node[0] Epoch[92] Batch [300] Speed: 615.65 samples/sec Train-accuracy=0.996563
2016-05-02 14:15:46,626 Node[0] Epoch[92] Batch [350] Speed: 614.14 samples/sec Train-accuracy=0.994687
2016-05-02 14:15:55,152 Node[0] Epoch[92] Resetting Data Iterator
2016-05-02 14:15:55,153 Node[0] Epoch[92] Time cost=81.336
2016-05-02 14:15:55,313 Node[0] Saved checkpoint to "cifar10/resnet-0093.params"
2016-05-02 14:15:57,216 Node[0] Epoch[92] Validation-accuracy=0.923177
2016-05-02 14:16:07,762 Node[0] Epoch[93] Batch [50] Speed: 610.08 samples/sec Train-accuracy=0.994531
2016-05-02 14:16:18,256 Node[0] Epoch[93] Batch [100] Speed: 609.85 samples/sec Train-accuracy=0.995625
2016-05-02 14:16:28,655 Node[0] Epoch[93] Batch [150] Speed: 615.50 samples/sec Train-accuracy=0.995625
2016-05-02 14:16:39,051 Node[0] Epoch[93] Batch [200] Speed: 615.60 samples/sec Train-accuracy=0.996094
2016-05-02 14:16:49,440 Node[0] Epoch[93] Batch [250] Speed: 616.09 samples/sec Train-accuracy=0.994844
2016-05-02 14:16:59,836 Node[0] Epoch[93] Batch [300] Speed: 615.64 samples/sec Train-accuracy=0.995469
2016-05-02 14:17:10,272 Node[0] Epoch[93] Batch [350] Speed: 613.27 samples/sec Train-accuracy=0.995469
2016-05-02 14:17:18,586 Node[0] Epoch[93] Resetting Data Iterator
2016-05-02 14:17:18,586 Node[0] Epoch[93] Time cost=81.369
2016-05-02 14:17:18,752 Node[0] Saved checkpoint to "cifar10/resnet-0094.params"
2016-05-02 14:17:20,670 Node[0] Epoch[93] Validation-accuracy=0.921274
2016-05-02 14:17:31,186 Node[0] Epoch[94] Batch [50] Speed: 611.80 samples/sec Train-accuracy=0.994844
2016-05-02 14:17:41,683 Node[0] Epoch[94] Batch [100] Speed: 609.72 samples/sec Train-accuracy=0.996406
2016-05-02 14:17:52,177 Node[0] Epoch[94] Batch [150] Speed: 609.85 samples/sec Train-accuracy=0.995000
2016-05-02 14:18:02,615 Node[0] Epoch[94] Batch [200] Speed: 613.17 samples/sec Train-accuracy=0.995781
2016-05-02 14:18:13,001 Node[0] Epoch[94] Batch [250] Speed: 616.23 samples/sec Train-accuracy=0.994375
2016-05-02 14:18:23,390 Node[0] Epoch[94] Batch [300] Speed: 616.07 samples/sec Train-accuracy=0.996563
2016-05-02 14:18:33,819 Node[0] Epoch[94] Batch [350] Speed: 613.70 samples/sec Train-accuracy=0.996094
2016-05-02 14:18:42,425 Node[0] Epoch[94] Resetting Data Iterator
2016-05-02 14:18:42,426 Node[0] Epoch[94] Time cost=81.756
2016-05-02 14:18:42,588 Node[0] Saved checkpoint to "cifar10/resnet-0095.params"
2016-05-02 14:18:44,516 Node[0] Epoch[94] Validation-accuracy=0.921374
2016-05-02 14:18:54,951 Node[0] Epoch[95] Batch [50] Speed: 616.55 samples/sec Train-accuracy=0.995469
2016-05-02 14:19:05,402 Node[0] Epoch[95] Batch [100] Speed: 612.42 samples/sec Train-accuracy=0.996563
2016-05-02 14:19:15,826 Node[0] Epoch[95] Batch [150] Speed: 613.97 samples/sec Train-accuracy=0.995781
2016-05-02 14:19:26,213 Node[0] Epoch[95] Batch [200] Speed: 616.17 samples/sec Train-accuracy=0.994531
2016-05-02 14:19:36,686 Node[0] Epoch[95] Batch [250] Speed: 611.11 samples/sec Train-accuracy=0.995781
2016-05-02 14:19:47,155 Node[0] Epoch[95] Batch [300] Speed: 611.33 samples/sec Train-accuracy=0.995469
2016-05-02 14:19:57,625 Node[0] Epoch[95] Batch [350] Speed: 611.31 samples/sec Train-accuracy=0.994375
2016-05-02 14:20:06,020 Node[0] Epoch[95] Resetting Data Iterator
2016-05-02 14:20:06,020 Node[0] Epoch[95] Time cost=81.504
2016-05-02 14:20:06,190 Node[0] Saved checkpoint to "cifar10/resnet-0096.params"
2016-05-02 14:20:08,109 Node[0] Epoch[95] Validation-accuracy=0.921975
2016-05-02 14:20:18,591 Node[0] Epoch[96] Batch [50] Speed: 613.79 samples/sec Train-accuracy=0.994844
2016-05-02 14:20:29,018 Node[0] Epoch[96] Batch [100] Speed: 613.84 samples/sec Train-accuracy=0.997031
2016-05-02 14:20:39,417 Node[0] Epoch[96] Batch [150] Speed: 615.43 samples/sec Train-accuracy=0.996094
2016-05-02 14:20:49,867 Node[0] Epoch[96] Batch [200] Speed: 612.48 samples/sec Train-accuracy=0.995156
2016-05-02 14:21:00,328 Node[0] Epoch[96] Batch [250] Speed: 611.82 samples/sec Train-accuracy=0.995938
2016-05-02 14:21:10,810 Node[0] Epoch[96] Batch [300] Speed: 610.57 samples/sec Train-accuracy=0.996250
2016-05-02 14:21:21,284 Node[0] Epoch[96] Batch [350] Speed: 611.09 samples/sec Train-accuracy=0.995000
2016-05-02 14:21:29,877 Node[0] Epoch[96] Resetting Data Iterator
2016-05-02 14:21:29,877 Node[0] Epoch[96] Time cost=81.769
2016-05-02 14:21:30,041 Node[0] Saved checkpoint to "cifar10/resnet-0097.params"
2016-05-02 14:21:32,136 Node[0] Epoch[96] Validation-accuracy=0.921578
2016-05-02 14:21:42,554 Node[0] Epoch[97] Batch [50] Speed: 617.61 samples/sec Train-accuracy=0.995625
2016-05-02 14:21:52,930 Node[0] Epoch[97] Batch [100] Speed: 616.83 samples/sec Train-accuracy=0.996094
2016-05-02 14:22:03,351 Node[0] Epoch[97] Batch [150] Speed: 614.12 samples/sec Train-accuracy=0.996563
2016-05-02 14:22:13,715 Node[0] Epoch[97] Batch [200] Speed: 617.54 samples/sec Train-accuracy=0.995625
2016-05-02 14:22:24,192 Node[0] Epoch[97] Batch [250] Speed: 610.90 samples/sec Train-accuracy=0.996875
2016-05-02 14:22:34,687 Node[0] Epoch[97] Batch [300] Speed: 609.82 samples/sec Train-accuracy=0.993906
2016-05-02 14:22:45,148 Node[0] Epoch[97] Batch [350] Speed: 611.86 samples/sec Train-accuracy=0.995000
2016-05-02 14:22:53,699 Node[0] Epoch[97] Resetting Data Iterator
2016-05-02 14:22:53,699 Node[0] Epoch[97] Time cost=81.563
2016-05-02 14:22:53,863 Node[0] Saved checkpoint to "cifar10/resnet-0098.params"
2016-05-02 14:22:55,805 Node[0] Epoch[97] Validation-accuracy=0.921374
2016-05-02 14:23:06,287 Node[0] Epoch[98] Batch [50] Speed: 613.84 samples/sec Train-accuracy=0.995469
2016-05-02 14:23:16,673 Node[0] Epoch[98] Batch [100] Speed: 616.20 samples/sec Train-accuracy=0.995156
2016-05-02 14:23:27,086 Node[0] Epoch[98] Batch [150] Speed: 614.66 samples/sec Train-accuracy=0.995625
2016-05-02 14:23:37,532 Node[0] Epoch[98] Batch [200] Speed: 612.72 samples/sec Train-accuracy=0.996250
2016-05-02 14:23:47,996 Node[0] Epoch[98] Batch [250] Speed: 611.60 samples/sec Train-accuracy=0.995469
2016-05-02 14:23:58,463 Node[0] Epoch[98] Batch [300] Speed: 611.46 samples/sec Train-accuracy=0.996875
2016-05-02 14:24:08,931 Node[0] Epoch[98] Batch [350] Speed: 611.43 samples/sec Train-accuracy=0.996094
2016-05-02 14:24:17,295 Node[0] Epoch[98] Resetting Data Iterator
2016-05-02 14:24:17,295 Node[0] Epoch[98] Time cost=81.490
2016-05-02 14:24:17,458 Node[0] Saved checkpoint to "cifar10/resnet-0099.params"
2016-05-02 14:24:19,365 Node[0] Epoch[98] Validation-accuracy=0.922276
2016-05-02 14:24:29,816 Node[0] Epoch[99] Batch [50] Speed: 615.62 samples/sec Train-accuracy=0.996719
2016-05-02 14:24:40,320 Node[0] Epoch[99] Batch [100] Speed: 609.30 samples/sec Train-accuracy=0.997031
2016-05-02 14:24:50,776 Node[0] Epoch[99] Batch [150] Speed: 612.12 samples/sec Train-accuracy=0.996563
2016-05-02 14:25:01,131 Node[0] Epoch[99] Batch [200] Speed: 618.08 samples/sec Train-accuracy=0.995938
2016-05-02 14:25:11,502 Node[0] Epoch[99] Batch [250] Speed: 617.09 samples/sec Train-accuracy=0.997656
2016-05-02 14:25:22,006 Node[0] Epoch[99] Batch [300] Speed: 609.30 samples/sec Train-accuracy=0.997344
2016-05-02 14:25:32,579 Node[0] Epoch[99] Batch [350] Speed: 605.35 samples/sec Train-accuracy=0.996250
2016-05-02 14:25:41,183 Node[0] Epoch[99] Resetting Data Iterator
2016-05-02 14:25:41,184 Node[0] Epoch[99] Time cost=81.818
2016-05-02 14:25:41,347 Node[0] Saved checkpoint to "cifar10/resnet-0100.params"
2016-05-02 14:25:43,271 Node[0] Epoch[99] Validation-accuracy=0.921975
2016-05-02 14:25:53,741 Node[0] Epoch[100] Batch [50] Speed: 614.36 samples/sec Train-accuracy=0.997500
2016-05-02 14:26:04,271 Node[0] Epoch[100] Batch [100] Speed: 607.84 samples/sec Train-accuracy=0.996719
2016-05-02 14:26:14,777 Node[0] Epoch[100] Batch [150] Speed: 609.20 samples/sec Train-accuracy=0.995938
2016-05-02 14:26:25,158 Node[0] Epoch[100] Batch [200] Speed: 616.50 samples/sec Train-accuracy=0.996563
2016-05-02 14:26:35,533 Node[0] Epoch[100] Batch [250] Speed: 616.88 samples/sec Train-accuracy=0.995781
2016-05-02 14:26:45,993 Node[0] Epoch[100] Batch [300] Speed: 611.91 samples/sec Train-accuracy=0.997344
2016-05-02 14:26:56,434 Node[0] Epoch[100] Batch [350] Speed: 612.97 samples/sec Train-accuracy=0.997344
2016-05-02 14:27:04,990 Node[0] Epoch[100] Resetting Data Iterator
2016-05-02 14:27:04,990 Node[0] Epoch[100] Time cost=81.719
2016-05-02 14:27:05,152 Node[0] Saved checkpoint to "cifar10/resnet-0101.params"
2016-05-02 14:27:07,097 Node[0] Epoch[100] Validation-accuracy=0.923678
2016-05-02 14:27:17,631 Node[0] Epoch[101] Batch [50] Speed: 610.82 samples/sec Train-accuracy=0.997812
2016-05-02 14:27:28,161 Node[0] Epoch[101] Batch [100] Speed: 607.84 samples/sec Train-accuracy=0.997344
2016-05-02 14:27:38,566 Node[0] Epoch[101] Batch [150] Speed: 615.11 samples/sec Train-accuracy=0.996406
2016-05-02 14:27:48,968 Node[0] Epoch[101] Batch [200] Speed: 615.30 samples/sec Train-accuracy=0.997031
2016-05-02 14:27:59,414 Node[0] Epoch[101] Batch [250] Speed: 612.67 samples/sec Train-accuracy=0.997500
2016-05-02 14:28:09,867 Node[0] Epoch[101] Batch [300] Speed: 612.28 samples/sec Train-accuracy=0.997969
2016-05-02 14:28:20,376 Node[0] Epoch[101] Batch [350] Speed: 609.02 samples/sec Train-accuracy=0.997500
2016-05-02 14:28:28,764 Node[0] Epoch[101] Resetting Data Iterator
2016-05-02 14:28:28,764 Node[0] Epoch[101] Time cost=81.667
2016-05-02 14:28:28,928 Node[0] Saved checkpoint to "cifar10/resnet-0102.params"
2016-05-02 14:28:30,832 Node[0] Epoch[101] Validation-accuracy=0.921274
2016-05-02 14:28:41,346 Node[0] Epoch[102] Batch [50] Speed: 611.97 samples/sec Train-accuracy=0.996563
2016-05-02 14:28:51,747 Node[0] Epoch[102] Batch [100] Speed: 615.31 samples/sec Train-accuracy=0.996875
2016-05-02 14:29:02,134 Node[0] Epoch[102] Batch [150] Speed: 616.21 samples/sec Train-accuracy=0.997031
2016-05-02 14:29:12,486 Node[0] Epoch[102] Batch [200] Speed: 618.22 samples/sec Train-accuracy=0.997500
2016-05-02 14:29:22,915 Node[0] Epoch[102] Batch [250] Speed: 613.68 samples/sec Train-accuracy=0.997031
2016-05-02 14:29:33,501 Node[0] Epoch[102] Batch [300] Speed: 604.60 samples/sec Train-accuracy=0.996563
2016-05-02 14:29:44,013 Node[0] Epoch[102] Batch [350] Speed: 608.84 samples/sec Train-accuracy=0.997812
2016-05-02 14:29:52,437 Node[0] Epoch[102] Resetting Data Iterator
2016-05-02 14:29:52,437 Node[0] Epoch[102] Time cost=81.604
2016-05-02 14:29:52,596 Node[0] Saved checkpoint to "cifar10/resnet-0103.params"
2016-05-02 14:29:54,497 Node[0] Epoch[102] Validation-accuracy=0.923277
2016-05-02 14:30:05,016 Node[0] Epoch[103] Batch [50] Speed: 611.63 samples/sec Train-accuracy=0.997344
2016-05-02 14:30:15,525 Node[0] Epoch[103] Batch [100] Speed: 609.06 samples/sec Train-accuracy=0.997188
2016-05-02 14:30:25,924 Node[0] Epoch[103] Batch [150] Speed: 615.43 samples/sec Train-accuracy=0.996406
2016-05-02 14:30:36,290 Node[0] Epoch[103] Batch [200] Speed: 617.42 samples/sec Train-accuracy=0.997344
2016-05-02 14:30:46,692 Node[0] Epoch[103] Batch [250] Speed: 615.31 samples/sec Train-accuracy=0.996094
2016-05-02 14:30:57,180 Node[0] Epoch[103] Batch [300] Speed: 610.25 samples/sec Train-accuracy=0.998594
2016-05-02 14:31:07,615 Node[0] Epoch[103] Batch [350] Speed: 613.30 samples/sec Train-accuracy=0.997188
2016-05-02 14:31:15,974 Node[0] Epoch[103] Resetting Data Iterator
2016-05-02 14:31:15,974 Node[0] Epoch[103] Time cost=81.477
2016-05-02 14:31:16,135 Node[0] Saved checkpoint to "cifar10/resnet-0104.params"
2016-05-02 14:31:18,026 Node[0] Epoch[103] Validation-accuracy=0.922075
2016-05-02 14:31:28,526 Node[0] Epoch[104] Batch [50] Speed: 612.73 samples/sec Train-accuracy=0.996719
2016-05-02 14:31:39,032 Node[0] Epoch[104] Batch [100] Speed: 609.23 samples/sec Train-accuracy=0.997031
2016-05-02 14:31:49,432 Node[0] Epoch[104] Batch [150] Speed: 615.37 samples/sec Train-accuracy=0.997031
2016-05-02 14:31:59,813 Node[0] Epoch[104] Batch [200] Speed: 616.52 samples/sec Train-accuracy=0.997500
2016-05-02 14:32:10,205 Node[0] Epoch[104] Batch [250] Speed: 615.92 samples/sec Train-accuracy=0.996563
2016-05-02 14:32:20,689 Node[0] Epoch[104] Batch [300] Speed: 610.44 samples/sec Train-accuracy=0.997969
2016-05-02 14:32:31,144 Node[0] Epoch[104] Batch [350] Speed: 612.18 samples/sec Train-accuracy=0.997031
2016-05-02 14:32:39,696 Node[0] Epoch[104] Resetting Data Iterator
2016-05-02 14:32:39,697 Node[0] Epoch[104] Time cost=81.670
2016-05-02 14:32:39,862 Node[0] Saved checkpoint to "cifar10/resnet-0105.params"
2016-05-02 14:32:42,019 Node[0] Epoch[104] Validation-accuracy=0.921875
2016-05-02 14:32:52,482 Node[0] Epoch[105] Batch [50] Speed: 614.85 samples/sec Train-accuracy=0.996875
2016-05-02 14:33:02,878 Node[0] Epoch[105] Batch [100] Speed: 615.68 samples/sec Train-accuracy=0.996719
2016-05-02 14:33:13,253 Node[0] Epoch[105] Batch [150] Speed: 616.87 samples/sec Train-accuracy=0.997344
2016-05-02 14:33:23,733 Node[0] Epoch[105] Batch [200] Speed: 610.71 samples/sec Train-accuracy=0.997344
2016-05-02 14:33:34,192 Node[0] Epoch[105] Batch [250] Speed: 611.91 samples/sec Train-accuracy=0.996250
2016-05-02 14:33:44,688 Node[0] Epoch[105] Batch [300] Speed: 609.78 samples/sec Train-accuracy=0.997500
2016-05-02 14:33:55,181 Node[0] Epoch[105] Batch [350] Speed: 609.96 samples/sec Train-accuracy=0.997812
2016-05-02 14:34:03,758 Node[0] Epoch[105] Resetting Data Iterator
2016-05-02 14:34:03,758 Node[0] Epoch[105] Time cost=81.739
2016-05-02 14:34:03,927 Node[0] Saved checkpoint to "cifar10/resnet-0106.params"
2016-05-02 14:34:05,839 Node[0] Epoch[105] Validation-accuracy=0.921675
2016-05-02 14:34:16,320 Node[0] Epoch[106] Batch [50] Speed: 613.75 samples/sec Train-accuracy=0.996719
2016-05-02 14:34:26,839 Node[0] Epoch[106] Batch [100] Speed: 608.44 samples/sec Train-accuracy=0.997812
2016-05-02 14:34:37,356 Node[0] Epoch[106] Batch [150] Speed: 608.55 samples/sec Train-accuracy=0.997969
2016-05-02 14:34:47,825 Node[0] Epoch[106] Batch [200] Speed: 611.39 samples/sec Train-accuracy=0.997500
2016-05-02 14:34:58,174 Node[0] Epoch[106] Batch [250] Speed: 618.40 samples/sec Train-accuracy=0.997344
2016-05-02 14:35:08,582 Node[0] Epoch[106] Batch [300] Speed: 614.91 samples/sec Train-accuracy=0.999062
2016-05-02 14:35:19,159 Node[0] Epoch[106] Batch [350] Speed: 605.13 samples/sec Train-accuracy=0.998281
2016-05-02 14:35:27,620 Node[0] Epoch[106] Resetting Data Iterator
2016-05-02 14:35:27,620 Node[0] Epoch[106] Time cost=81.781
2016-05-02 14:35:27,785 Node[0] Saved checkpoint to "cifar10/resnet-0107.params"
2016-05-02 14:35:29,699 Node[0] Epoch[106] Validation-accuracy=0.922776
2016-05-02 14:35:40,116 Node[0] Epoch[107] Batch [50] Speed: 617.54 samples/sec Train-accuracy=0.997812
2016-05-02 14:35:50,574 Node[0] Epoch[107] Batch [100] Speed: 612.02 samples/sec Train-accuracy=0.997656
2016-05-02 14:36:01,057 Node[0] Epoch[107] Batch [150] Speed: 610.50 samples/sec Train-accuracy=0.998437
2016-05-02 14:36:11,448 Node[0] Epoch[107] Batch [200] Speed: 615.95 samples/sec Train-accuracy=0.997969
2016-05-02 14:36:21,831 Node[0] Epoch[107] Batch [250] Speed: 616.41 samples/sec Train-accuracy=0.997656
2016-05-02 14:36:32,281 Node[0] Epoch[107] Batch [300] Speed: 612.48 samples/sec Train-accuracy=0.997812
2016-05-02 14:36:42,732 Node[0] Epoch[107] Batch [350] Speed: 612.40 samples/sec Train-accuracy=0.997969
2016-05-02 14:36:51,332 Node[0] Epoch[107] Resetting Data Iterator
2016-05-02 14:36:51,332 Node[0] Epoch[107] Time cost=81.633
2016-05-02 14:36:51,501 Node[0] Saved checkpoint to "cifar10/resnet-0108.params"
2016-05-02 14:36:53,405 Node[0] Epoch[107] Validation-accuracy=0.921374
2016-05-02 14:37:03,893 Node[0] Epoch[108] Batch [50] Speed: 613.48 samples/sec Train-accuracy=0.998594
2016-05-02 14:37:14,400 Node[0] Epoch[108] Batch [100] Speed: 609.12 samples/sec Train-accuracy=0.998281
2016-05-02 14:37:24,915 Node[0] Epoch[108] Batch [150] Speed: 608.68 samples/sec Train-accuracy=0.997031
2016-05-02 14:37:35,389 Node[0] Epoch[108] Batch [200] Speed: 611.08 samples/sec Train-accuracy=0.997969
2016-05-02 14:37:45,755 Node[0] Epoch[108] Batch [250] Speed: 617.39 samples/sec Train-accuracy=0.998125
2016-05-02 14:37:56,191 Node[0] Epoch[108] Batch [300] Speed: 613.28 samples/sec Train-accuracy=0.997656
2016-05-02 14:38:06,683 Node[0] Epoch[108] Batch [350] Speed: 609.98 samples/sec Train-accuracy=0.997656
2016-05-02 14:38:15,285 Node[0] Epoch[108] Resetting Data Iterator
2016-05-02 14:38:15,285 Node[0] Epoch[108] Time cost=81.880
2016-05-02 14:38:15,451 Node[0] Saved checkpoint to "cifar10/resnet-0109.params"
2016-05-02 14:38:17,379 Node[0] Epoch[108] Validation-accuracy=0.922576
2016-05-02 14:38:27,972 Node[0] Epoch[109] Batch [50] Speed: 607.41 samples/sec Train-accuracy=0.996875
2016-05-02 14:38:38,468 Node[0] Epoch[109] Batch [100] Speed: 609.74 samples/sec Train-accuracy=0.997969
2016-05-02 14:38:48,872 Node[0] Epoch[109] Batch [150] Speed: 615.21 samples/sec Train-accuracy=0.998906
2016-05-02 14:38:59,265 Node[0] Epoch[109] Batch [200] Speed: 615.77 samples/sec Train-accuracy=0.997344
2016-05-02 14:39:09,677 Node[0] Epoch[109] Batch [250] Speed: 614.68 samples/sec Train-accuracy=0.998125
2016-05-02 14:39:20,151 Node[0] Epoch[109] Batch [300] Speed: 611.09 samples/sec Train-accuracy=0.997656
2016-05-02 14:39:30,634 Node[0] Epoch[109] Batch [350] Speed: 610.53 samples/sec Train-accuracy=0.997969
2016-05-02 14:39:39,000 Node[0] Epoch[109] Resetting Data Iterator
2016-05-02 14:39:39,000 Node[0] Epoch[109] Time cost=81.622
2016-05-02 14:39:39,164 Node[0] Saved checkpoint to "cifar10/resnet-0110.params"
2016-05-02 14:39:41,093 Node[0] Epoch[109] Validation-accuracy=0.921074
2016-05-02 14:39:51,628 Node[0] Epoch[110] Batch [50] Speed: 610.63 samples/sec Train-accuracy=0.997031
2016-05-02 14:40:02,111 Node[0] Epoch[110] Batch [100] Speed: 610.57 samples/sec Train-accuracy=0.997344
2016-05-02 14:40:12,494 Node[0] Epoch[110] Batch [150] Speed: 616.37 samples/sec Train-accuracy=0.996719
2016-05-02 14:40:22,865 Node[0] Epoch[110] Batch [200] Speed: 617.15 samples/sec Train-accuracy=0.997344
2016-05-02 14:40:33,268 Node[0] Epoch[110] Batch [250] Speed: 615.20 samples/sec Train-accuracy=0.997969
2016-05-02 14:40:43,751 Node[0] Epoch[110] Batch [300] Speed: 610.55 samples/sec Train-accuracy=0.997812
2016-05-02 14:40:54,259 Node[0] Epoch[110] Batch [350] Speed: 609.06 samples/sec Train-accuracy=0.997344
2016-05-02 14:41:02,837 Node[0] Epoch[110] Resetting Data Iterator
2016-05-02 14:41:02,837 Node[0] Epoch[110] Time cost=81.744
2016-05-02 14:41:03,000 Node[0] Saved checkpoint to "cifar10/resnet-0111.params"
2016-05-02 14:41:04,921 Node[0] Epoch[110] Validation-accuracy=0.922476
2016-05-02 14:41:15,436 Node[0] Epoch[111] Batch [50] Speed: 611.89 samples/sec Train-accuracy=0.997812
2016-05-02 14:41:25,832 Node[0] Epoch[111] Batch [100] Speed: 615.64 samples/sec Train-accuracy=0.998125
2016-05-02 14:41:36,247 Node[0] Epoch[111] Batch [150] Speed: 614.50 samples/sec Train-accuracy=0.998750
2016-05-02 14:41:46,608 Node[0] Epoch[111] Batch [200] Speed: 617.73 samples/sec Train-accuracy=0.998594
2016-05-02 14:41:57,030 Node[0] Epoch[111] Batch [250] Speed: 614.12 samples/sec Train-accuracy=0.997344
2016-05-02 14:42:07,520 Node[0] Epoch[111] Batch [300] Speed: 610.08 samples/sec Train-accuracy=0.997031
2016-05-02 14:42:18,004 Node[0] Epoch[111] Batch [350] Speed: 610.49 samples/sec Train-accuracy=0.999062
2016-05-02 14:42:26,375 Node[0] Epoch[111] Resetting Data Iterator
2016-05-02 14:42:26,375 Node[0] Epoch[111] Time cost=81.455
2016-05-02 14:42:26,538 Node[0] Saved checkpoint to "cifar10/resnet-0112.params"
2016-05-02 14:42:28,435 Node[0] Epoch[111] Validation-accuracy=0.920873
2016-05-02 14:42:38,888 Node[0] Epoch[112] Batch [50] Speed: 615.57 samples/sec Train-accuracy=0.998594
2016-05-02 14:42:49,379 Node[0] Epoch[112] Batch [100] Speed: 610.05 samples/sec Train-accuracy=0.998750
2016-05-02 14:42:59,759 Node[0] Epoch[112] Batch [150] Speed: 616.61 samples/sec Train-accuracy=0.998437
2016-05-02 14:43:10,109 Node[0] Epoch[112] Batch [200] Speed: 618.37 samples/sec Train-accuracy=0.996719
2016-05-02 14:43:20,525 Node[0] Epoch[112] Batch [250] Speed: 614.45 samples/sec Train-accuracy=0.998437
2016-05-02 14:43:30,957 Node[0] Epoch[112] Batch [300] Speed: 613.48 samples/sec Train-accuracy=0.997812
2016-05-02 14:43:41,466 Node[0] Epoch[112] Batch [350] Speed: 609.05 samples/sec Train-accuracy=0.997969
2016-05-02 14:43:50,048 Node[0] Epoch[112] Resetting Data Iterator
2016-05-02 14:43:50,048 Node[0] Epoch[112] Time cost=81.613
2016-05-02 14:43:50,218 Node[0] Saved checkpoint to "cifar10/resnet-0113.params"
2016-05-02 14:43:52,326 Node[0] Epoch[112] Validation-accuracy=0.922468
2016-05-02 14:44:02,777 Node[0] Epoch[113] Batch [50] Speed: 615.56 samples/sec Train-accuracy=0.997812
2016-05-02 14:44:13,230 Node[0] Epoch[113] Batch [100] Speed: 612.27 samples/sec Train-accuracy=0.998750
2016-05-02 14:44:23,661 Node[0] Epoch[113] Batch [150] Speed: 613.57 samples/sec Train-accuracy=0.998906
2016-05-02 14:44:34,031 Node[0] Epoch[113] Batch [200] Speed: 617.20 samples/sec Train-accuracy=0.998125
2016-05-02 14:44:44,453 Node[0] Epoch[113] Batch [250] Speed: 614.06 samples/sec Train-accuracy=0.997344
2016-05-02 14:44:54,845 Node[0] Epoch[113] Batch [300] Speed: 615.92 samples/sec Train-accuracy=0.998594
2016-05-02 14:45:05,317 Node[0] Epoch[113] Batch [350] Speed: 611.17 samples/sec Train-accuracy=0.998594
2016-05-02 14:45:13,870 Node[0] Epoch[113] Resetting Data Iterator
2016-05-02 14:45:13,871 Node[0] Epoch[113] Time cost=81.545
2016-05-02 14:45:14,033 Node[0] Saved checkpoint to "cifar10/resnet-0114.params"
2016-05-02 14:45:15,938 Node[0] Epoch[113] Validation-accuracy=0.922075
2016-05-02 14:45:26,400 Node[0] Epoch[114] Batch [50] Speed: 614.93 samples/sec Train-accuracy=0.998125
2016-05-02 14:45:36,832 Node[0] Epoch[114] Batch [100] Speed: 613.48 samples/sec Train-accuracy=0.996875
2016-05-02 14:45:47,221 Node[0] Epoch[114] Batch [150] Speed: 616.06 samples/sec Train-accuracy=0.997812
2016-05-02 14:45:57,570 Node[0] Epoch[114] Batch [200] Speed: 618.45 samples/sec Train-accuracy=0.998125
2016-05-02 14:46:08,035 Node[0] Epoch[114] Batch [250] Speed: 611.56 samples/sec Train-accuracy=0.997969
2016-05-02 14:46:18,501 Node[0] Epoch[114] Batch [300] Speed: 611.52 samples/sec Train-accuracy=0.998750
2016-05-02 14:46:28,968 Node[0] Epoch[114] Batch [350] Speed: 611.45 samples/sec Train-accuracy=0.998594
2016-05-02 14:46:37,341 Node[0] Epoch[114] Resetting Data Iterator
2016-05-02 14:46:37,341 Node[0] Epoch[114] Time cost=81.404
2016-05-02 14:46:37,504 Node[0] Saved checkpoint to "cifar10/resnet-0115.params"
2016-05-02 14:46:39,387 Node[0] Epoch[114] Validation-accuracy=0.922075
2016-05-02 14:46:49,831 Node[0] Epoch[115] Batch [50] Speed: 615.99 samples/sec Train-accuracy=0.998281
2016-05-02 14:47:00,234 Node[0] Epoch[115] Batch [100] Speed: 615.24 samples/sec Train-accuracy=0.997969
2016-05-02 14:47:10,660 Node[0] Epoch[115] Batch [150] Speed: 613.89 samples/sec Train-accuracy=0.998437
2016-05-02 14:47:21,023 Node[0] Epoch[115] Batch [200] Speed: 617.58 samples/sec Train-accuracy=0.998125
2016-05-02 14:47:31,442 Node[0] Epoch[115] Batch [250] Speed: 614.25 samples/sec Train-accuracy=0.998281
2016-05-02 14:47:41,914 Node[0] Epoch[115] Batch [300] Speed: 611.16 samples/sec Train-accuracy=0.998750
2016-05-02 14:47:52,381 Node[0] Epoch[115] Batch [350] Speed: 611.49 samples/sec Train-accuracy=0.998125
2016-05-02 14:48:00,972 Node[0] Epoch[115] Resetting Data Iterator
2016-05-02 14:48:00,972 Node[0] Epoch[115] Time cost=81.585
2016-05-02 14:48:01,138 Node[0] Saved checkpoint to "cifar10/resnet-0116.params"
2016-05-02 14:48:03,038 Node[0] Epoch[115] Validation-accuracy=0.922676
2016-05-02 14:48:13,486 Node[0] Epoch[116] Batch [50] Speed: 615.72 samples/sec Train-accuracy=0.998437
2016-05-02 14:48:23,848 Node[0] Epoch[116] Batch [100] Speed: 617.63 samples/sec Train-accuracy=0.997969
2016-05-02 14:48:34,229 Node[0] Epoch[116] Batch [150] Speed: 616.53 samples/sec Train-accuracy=0.998281
2016-05-02 14:48:44,616 Node[0] Epoch[116] Batch [200] Speed: 616.19 samples/sec Train-accuracy=0.998437
2016-05-02 14:48:55,053 Node[0] Epoch[116] Batch [250] Speed: 613.18 samples/sec Train-accuracy=0.998594
2016-05-02 14:49:05,577 Node[0] Epoch[116] Batch [300] Speed: 608.15 samples/sec Train-accuracy=0.999531
2016-05-02 14:49:16,084 Node[0] Epoch[116] Batch [350] Speed: 609.13 samples/sec Train-accuracy=0.998906
2016-05-02 14:49:24,683 Node[0] Epoch[116] Resetting Data Iterator
2016-05-02 14:49:24,684 Node[0] Epoch[116] Time cost=81.646
2016-05-02 14:49:24,848 Node[0] Saved checkpoint to "cifar10/resnet-0117.params"
2016-05-02 14:49:26,772 Node[0] Epoch[116] Validation-accuracy=0.921775
2016-05-02 14:49:37,234 Node[0] Epoch[117] Batch [50] Speed: 614.93 samples/sec Train-accuracy=0.998594
2016-05-02 14:49:47,598 Node[0] Epoch[117] Batch [100] Speed: 617.51 samples/sec Train-accuracy=0.999062
2016-05-02 14:49:58,006 Node[0] Epoch[117] Batch [150] Speed: 614.93 samples/sec Train-accuracy=0.999687
2016-05-02 14:50:08,404 Node[0] Epoch[117] Batch [200] Speed: 615.52 samples/sec Train-accuracy=0.999062
2016-05-02 14:50:18,804 Node[0] Epoch[117] Batch [250] Speed: 615.43 samples/sec Train-accuracy=0.998437
2016-05-02 14:50:29,206 Node[0] Epoch[117] Batch [300] Speed: 615.27 samples/sec Train-accuracy=0.998594
2016-05-02 14:50:39,720 Node[0] Epoch[117] Batch [350] Speed: 608.73 samples/sec Train-accuracy=0.998594
2016-05-02 14:50:48,122 Node[0] Epoch[117] Resetting Data Iterator
2016-05-02 14:50:48,122 Node[0] Epoch[117] Time cost=81.349
2016-05-02 14:50:48,291 Node[0] Saved checkpoint to "cifar10/resnet-0118.params"
2016-05-02 14:50:50,182 Node[0] Epoch[117] Validation-accuracy=0.921975
2016-05-02 14:51:00,556 Node[0] Epoch[118] Batch [50] Speed: 620.12 samples/sec Train-accuracy=0.998750
2016-05-02 14:51:11,014 Node[0] Epoch[118] Batch [100] Speed: 611.97 samples/sec Train-accuracy=0.998125
2016-05-02 14:51:21,406 Node[0] Epoch[118] Batch [150] Speed: 615.88 samples/sec Train-accuracy=0.998437
2016-05-02 14:51:31,798 Node[0] Epoch[118] Batch [200] Speed: 615.85 samples/sec Train-accuracy=0.998281
2016-05-02 14:51:42,144 Node[0] Epoch[118] Batch [250] Speed: 618.67 samples/sec Train-accuracy=0.999375
2016-05-02 14:51:52,497 Node[0] Epoch[118] Batch [300] Speed: 618.16 samples/sec Train-accuracy=0.998750
2016-05-02 14:52:02,927 Node[0] Epoch[118] Batch [350] Speed: 613.65 samples/sec Train-accuracy=0.999531
2016-05-02 14:52:11,486 Node[0] Epoch[118] Resetting Data Iterator
2016-05-02 14:52:11,486 Node[0] Epoch[118] Time cost=81.305
2016-05-02 14:52:11,651 Node[0] Saved checkpoint to "cifar10/resnet-0119.params"
2016-05-02 14:52:13,555 Node[0] Epoch[118] Validation-accuracy=0.922376
2016-05-02 14:52:23,998 Node[0] Epoch[119] Batch [50] Speed: 616.06 samples/sec Train-accuracy=0.998125
2016-05-02 14:52:34,376 Node[0] Epoch[119] Batch [100] Speed: 616.72 samples/sec Train-accuracy=0.997500
2016-05-02 14:52:44,771 Node[0] Epoch[119] Batch [150] Speed: 615.68 samples/sec Train-accuracy=0.998906
2016-05-02 14:52:55,194 Node[0] Epoch[119] Batch [200] Speed: 614.08 samples/sec Train-accuracy=0.999062
2016-05-02 14:53:05,607 Node[0] Epoch[119] Batch [250] Speed: 614.60 samples/sec Train-accuracy=0.998125
2016-05-02 14:53:15,974 Node[0] Epoch[119] Batch [300] Speed: 617.40 samples/sec Train-accuracy=0.998437
2016-05-02 14:53:26,399 Node[0] Epoch[119] Batch [350] Speed: 613.91 samples/sec Train-accuracy=0.999062
2016-05-02 14:53:34,773 Node[0] Epoch[119] Resetting Data Iterator
2016-05-02 14:53:34,773 Node[0] Epoch[119] Time cost=81.218
2016-05-02 14:53:34,941 Node[0] Saved checkpoint to "cifar10/resnet-0120.params"
2016-05-02 14:53:36,834 Node[0] Epoch[119] Validation-accuracy=0.923177
2016-05-02 14:53:47,354 Node[0] Epoch[120] Batch [50] Speed: 611.58 samples/sec Train-accuracy=0.998281
2016-05-02 14:53:57,752 Node[0] Epoch[120] Batch [100] Speed: 615.52 samples/sec Train-accuracy=0.998594
2016-05-02 14:54:08,133 Node[0] Epoch[120] Batch [150] Speed: 616.51 samples/sec Train-accuracy=0.998281
2016-05-02 14:54:18,553 Node[0] Epoch[120] Batch [200] Speed: 614.22 samples/sec Train-accuracy=0.998906
2016-05-02 14:54:28,996 Node[0] Epoch[120] Batch [250] Speed: 612.88 samples/sec Train-accuracy=0.998281
2016-05-02 14:54:39,453 Node[0] Epoch[120] Batch [300] Speed: 612.02 samples/sec Train-accuracy=0.998125
2016-05-02 14:54:49,957 Node[0] Epoch[120] Batch [350] Speed: 609.30 samples/sec Train-accuracy=0.998906
2016-05-02 14:54:58,453 Node[0] Epoch[120] Resetting Data Iterator
2016-05-02 14:54:58,454 Node[0] Epoch[120] Time cost=81.620
2016-05-02 14:54:58,619 Node[0] Saved checkpoint to "cifar10/resnet-0121.params"
2016-05-02 14:55:00,717 Node[0] Epoch[120] Validation-accuracy=0.922567
2016-05-02 14:55:11,146 Node[0] Epoch[121] Batch [50] Speed: 616.92 samples/sec Train-accuracy=0.998281
2016-05-02 14:55:21,523 Node[0] Epoch[121] Batch [100] Speed: 616.76 samples/sec Train-accuracy=0.999375
2016-05-02 14:55:31,883 Node[0] Epoch[121] Batch [150] Speed: 617.79 samples/sec Train-accuracy=0.998281
2016-05-02 14:55:42,346 Node[0] Epoch[121] Batch [200] Speed: 611.70 samples/sec Train-accuracy=0.999375
2016-05-02 14:55:52,860 Node[0] Epoch[121] Batch [250] Speed: 608.73 samples/sec Train-accuracy=0.999531
2016-05-02 14:56:03,364 Node[0] Epoch[121] Batch [300] Speed: 609.31 samples/sec Train-accuracy=0.998906
2016-05-02 14:56:13,791 Node[0] Epoch[121] Batch [350] Speed: 613.83 samples/sec Train-accuracy=0.998437
2016-05-02 14:56:22,331 Node[0] Epoch[121] Resetting Data Iterator
2016-05-02 14:56:22,331 Node[0] Epoch[121] Time cost=81.614
2016-05-02 14:56:22,494 Node[0] Saved checkpoint to "cifar10/resnet-0122.params"
2016-05-02 14:56:24,401 Node[0] Epoch[121] Validation-accuracy=0.921875
2016-05-02 14:56:34,886 Node[0] Epoch[122] Batch [50] Speed: 613.57 samples/sec Train-accuracy=0.999062
2016-05-02 14:56:45,308 Node[0] Epoch[122] Batch [100] Speed: 614.12 samples/sec Train-accuracy=0.998281
2016-05-02 14:56:55,672 Node[0] Epoch[122] Batch [150] Speed: 617.56 samples/sec Train-accuracy=0.998906
2016-05-02 14:57:06,102 Node[0] Epoch[122] Batch [200] Speed: 613.59 samples/sec Train-accuracy=0.998281
2016-05-02 14:57:16,629 Node[0] Epoch[122] Batch [250] Speed: 608.01 samples/sec Train-accuracy=0.998594
2016-05-02 14:57:27,089 Node[0] Epoch[122] Batch [300] Speed: 611.86 samples/sec Train-accuracy=0.998594
2016-05-02 14:57:37,584 Node[0] Epoch[122] Batch [350] Speed: 609.82 samples/sec Train-accuracy=0.997656
2016-05-02 14:57:45,946 Node[0] Epoch[122] Resetting Data Iterator
2016-05-02 14:57:45,946 Node[0] Epoch[122] Time cost=81.545
2016-05-02 14:57:46,112 Node[0] Saved checkpoint to "cifar10/resnet-0123.params"
2016-05-02 14:57:48,042 Node[0] Epoch[122] Validation-accuracy=0.921474
2016-05-02 14:57:58,501 Node[0] Epoch[123] Batch [50] Speed: 615.19 samples/sec Train-accuracy=0.998594
2016-05-02 14:58:08,957 Node[0] Epoch[123] Batch [100] Speed: 612.07 samples/sec Train-accuracy=0.998125
2016-05-02 14:58:19,449 Node[0] Epoch[123] Batch [150] Speed: 610.01 samples/sec Train-accuracy=0.998906
2016-05-02 14:58:29,904 Node[0] Epoch[123] Batch [200] Speed: 612.15 samples/sec Train-accuracy=0.998750
2016-05-02 14:58:40,308 Node[0] Epoch[123] Batch [250] Speed: 615.18 samples/sec Train-accuracy=0.999062
2016-05-02 14:58:50,754 Node[0] Epoch[123] Batch [300] Speed: 612.69 samples/sec Train-accuracy=0.997812
2016-05-02 14:59:01,241 Node[0] Epoch[123] Batch [350] Speed: 610.27 samples/sec Train-accuracy=0.998125
2016-05-02 14:59:09,795 Node[0] Epoch[123] Resetting Data Iterator
2016-05-02 14:59:09,795 Node[0] Epoch[123] Time cost=81.753
2016-05-02 14:59:09,958 Node[0] Saved checkpoint to "cifar10/resnet-0124.params"
2016-05-02 14:59:11,882 Node[0] Epoch[123] Validation-accuracy=0.919972
2016-05-02 14:59:22,445 Node[0] Epoch[124] Batch [50] Speed: 609.04 samples/sec Train-accuracy=0.999687
2016-05-02 14:59:32,960 Node[0] Epoch[124] Batch [100] Speed: 608.68 samples/sec Train-accuracy=0.999219
2016-05-02 14:59:43,348 Node[0] Epoch[124] Batch [150] Speed: 616.13 samples/sec Train-accuracy=0.998906
2016-05-02 14:59:53,780 Node[0] Epoch[124] Batch [200] Speed: 613.50 samples/sec Train-accuracy=0.998750
2016-05-02 15:00:04,255 Node[0] Epoch[124] Batch [250] Speed: 610.99 samples/sec Train-accuracy=0.998750
2016-05-02 15:00:14,721 Node[0] Epoch[124] Batch [300] Speed: 611.53 samples/sec Train-accuracy=0.999844
2016-05-02 15:00:25,184 Node[0] Epoch[124] Batch [350] Speed: 611.70 samples/sec Train-accuracy=0.999375
2016-05-02 15:00:33,787 Node[0] Epoch[124] Resetting Data Iterator
2016-05-02 15:00:33,788 Node[0] Epoch[124] Time cost=81.905
2016-05-02 15:00:33,954 Node[0] Saved checkpoint to "cifar10/resnet-0125.params"
2016-05-02 15:00:35,943 Node[0] Epoch[124] Validation-accuracy=0.921775
2016-05-02 15:00:46,472 Node[0] Epoch[125] Batch [50] Speed: 611.06 samples/sec Train-accuracy=0.998906
2016-05-02 15:00:56,985 Node[0] Epoch[125] Batch [100] Speed: 608.73 samples/sec Train-accuracy=0.999062
2016-05-02 15:01:07,368 Node[0] Epoch[125] Batch [150] Speed: 616.43 samples/sec Train-accuracy=0.998906
2016-05-02 15:01:17,756 Node[0] Epoch[125] Batch [200] Speed: 616.13 samples/sec Train-accuracy=0.998906
2016-05-02 15:01:28,177 Node[0] Epoch[125] Batch [250] Speed: 614.15 samples/sec Train-accuracy=0.998906
2016-05-02 15:01:38,592 Node[0] Epoch[125] Batch [300] Speed: 614.50 samples/sec Train-accuracy=0.998125
2016-05-02 15:01:49,049 Node[0] Epoch[125] Batch [350] Speed: 612.09 samples/sec Train-accuracy=0.998906
2016-05-02 15:01:57,406 Node[0] Epoch[125] Resetting Data Iterator
2016-05-02 15:01:57,406 Node[0] Epoch[125] Time cost=81.464
2016-05-02 15:01:57,574 Node[0] Saved checkpoint to "cifar10/resnet-0126.params"
2016-05-02 15:01:59,485 Node[0] Epoch[125] Validation-accuracy=0.922676
2016-05-02 15:02:10,005 Node[0] Epoch[126] Batch [50] Speed: 611.62 samples/sec Train-accuracy=0.998750
2016-05-02 15:02:20,455 Node[0] Epoch[126] Batch [100] Speed: 612.49 samples/sec Train-accuracy=0.999062
2016-05-02 15:02:30,833 Node[0] Epoch[126] Batch [150] Speed: 616.68 samples/sec Train-accuracy=0.999219
2016-05-02 15:02:41,214 Node[0] Epoch[126] Batch [200] Speed: 616.57 samples/sec Train-accuracy=0.998750
2016-05-02 15:02:51,608 Node[0] Epoch[126] Batch [250] Speed: 615.72 samples/sec Train-accuracy=0.999375
2016-05-02 15:03:02,081 Node[0] Epoch[126] Batch [300] Speed: 611.12 samples/sec Train-accuracy=0.998594
2016-05-02 15:03:12,559 Node[0] Epoch[126] Batch [350] Speed: 610.81 samples/sec Train-accuracy=0.998906
2016-05-02 15:03:21,145 Node[0] Epoch[126] Resetting Data Iterator
2016-05-02 15:03:21,145 Node[0] Epoch[126] Time cost=81.660
2016-05-02 15:03:21,310 Node[0] Saved checkpoint to "cifar10/resnet-0127.params"
2016-05-02 15:03:23,210 Node[0] Epoch[126] Validation-accuracy=0.919772
2016-05-02 15:03:33,690 Node[0] Epoch[127] Batch [50] Speed: 614.34 samples/sec Train-accuracy=0.998594
2016-05-02 15:03:44,138 Node[0] Epoch[127] Batch [100] Speed: 612.62 samples/sec Train-accuracy=0.998594
2016-05-02 15:03:54,533 Node[0] Epoch[127] Batch [150] Speed: 615.67 samples/sec Train-accuracy=0.999531
2016-05-02 15:04:04,933 Node[0] Epoch[127] Batch [200] Speed: 615.39 samples/sec Train-accuracy=0.999687
2016-05-02 15:04:15,307 Node[0] Epoch[127] Batch [250] Speed: 616.95 samples/sec Train-accuracy=0.998906
2016-05-02 15:04:25,785 Node[0] Epoch[127] Batch [300] Speed: 610.84 samples/sec Train-accuracy=0.998906
2016-05-02 15:04:36,215 Node[0] Epoch[127] Batch [350] Speed: 613.65 samples/sec Train-accuracy=0.999375
2016-05-02 15:04:44,567 Node[0] Epoch[127] Resetting Data Iterator
2016-05-02 15:04:44,567 Node[0] Epoch[127] Time cost=81.357
2016-05-02 15:04:44,731 Node[0] Saved checkpoint to "cifar10/resnet-0128.params"
2016-05-02 15:04:46,648 Node[0] Epoch[127] Validation-accuracy=0.921074
2016-05-02 15:04:57,123 Node[0] Epoch[128] Batch [50] Speed: 614.23 samples/sec Train-accuracy=0.998594
2016-05-02 15:05:07,601 Node[0] Epoch[128] Batch [100] Speed: 610.85 samples/sec Train-accuracy=0.999375
2016-05-02 15:05:17,941 Node[0] Epoch[128] Batch [150] Speed: 618.96 samples/sec Train-accuracy=0.998594
2016-05-02 15:05:28,361 Node[0] Epoch[128] Batch [200] Speed: 614.19 samples/sec Train-accuracy=0.999219
2016-05-02 15:05:38,774 Node[0] Epoch[128] Batch [250] Speed: 614.64 samples/sec Train-accuracy=0.999375
2016-05-02 15:05:49,211 Node[0] Epoch[128] Batch [300] Speed: 613.21 samples/sec Train-accuracy=0.999062
2016-05-02 15:05:59,692 Node[0] Epoch[128] Batch [350] Speed: 610.63 samples/sec Train-accuracy=0.998750
2016-05-02 15:06:08,260 Node[0] Epoch[128] Resetting Data Iterator
2016-05-02 15:06:08,261 Node[0] Epoch[128] Time cost=81.612
2016-05-02 15:06:08,421 Node[0] Saved checkpoint to "cifar10/resnet-0129.params"
2016-05-02 15:06:10,510 Node[0] Epoch[128] Validation-accuracy=0.921875
2016-05-02 15:06:20,997 Node[0] Epoch[129] Batch [50] Speed: 613.52 samples/sec Train-accuracy=0.998906
2016-05-02 15:06:31,413 Node[0] Epoch[129] Batch [100] Speed: 614.46 samples/sec Train-accuracy=0.999062
2016-05-02 15:06:41,837 Node[0] Epoch[129] Batch [150] Speed: 613.94 samples/sec Train-accuracy=0.999062
2016-05-02 15:06:52,233 Node[0] Epoch[129] Batch [200] Speed: 615.63 samples/sec Train-accuracy=0.998594
2016-05-02 15:07:02,706 Node[0] Epoch[129] Batch [250] Speed: 611.12 samples/sec Train-accuracy=0.999219
2016-05-02 15:07:13,158 Node[0] Epoch[129] Batch [300] Speed: 612.34 samples/sec Train-accuracy=0.999062
2016-05-02 15:07:23,643 Node[0] Epoch[129] Batch [350] Speed: 610.44 samples/sec Train-accuracy=0.999219
2016-05-02 15:07:32,217 Node[0] Epoch[129] Resetting Data Iterator
2016-05-02 15:07:32,217 Node[0] Epoch[129] Time cost=81.708
2016-05-02 15:07:32,383 Node[0] Saved checkpoint to "cifar10/resnet-0130.params"
2016-05-02 15:07:34,296 Node[0] Epoch[129] Validation-accuracy=0.921074
2016-05-02 15:07:44,815 Node[0] Epoch[130] Batch [50] Speed: 611.59 samples/sec Train-accuracy=0.999844
2016-05-02 15:07:55,245 Node[0] Epoch[130] Batch [100] Speed: 613.65 samples/sec Train-accuracy=0.998594
2016-05-02 15:08:05,657 Node[0] Epoch[130] Batch [150] Speed: 614.70 samples/sec Train-accuracy=0.998750
2016-05-02 15:08:16,045 Node[0] Epoch[130] Batch [200] Speed: 616.08 samples/sec Train-accuracy=0.998906
2016-05-02 15:08:26,482 Node[0] Epoch[130] Batch [250] Speed: 613.23 samples/sec Train-accuracy=0.999062
2016-05-02 15:08:36,982 Node[0] Epoch[130] Batch [300] Speed: 609.51 samples/sec Train-accuracy=0.999219
2016-05-02 15:08:47,423 Node[0] Epoch[130] Batch [350] Speed: 612.99 samples/sec Train-accuracy=0.999062
2016-05-02 15:08:55,809 Node[0] Epoch[130] Resetting Data Iterator
2016-05-02 15:08:55,809 Node[0] Epoch[130] Time cost=81.513
2016-05-02 15:08:55,973 Node[0] Saved checkpoint to "cifar10/resnet-0131.params"
2016-05-02 15:08:57,870 Node[0] Epoch[130] Validation-accuracy=0.922075
2016-05-02 15:09:08,358 Node[0] Epoch[131] Batch [50] Speed: 613.42 samples/sec Train-accuracy=0.999687
2016-05-02 15:09:18,763 Node[0] Epoch[131] Batch [100] Speed: 615.13 samples/sec Train-accuracy=0.999531
2016-05-02 15:09:29,151 Node[0] Epoch[131] Batch [150] Speed: 616.10 samples/sec Train-accuracy=0.999375
2016-05-02 15:09:39,535 Node[0] Epoch[131] Batch [200] Speed: 616.34 samples/sec Train-accuracy=0.997656
2016-05-02 15:09:50,011 Node[0] Epoch[131] Batch [250] Speed: 610.96 samples/sec Train-accuracy=0.999219
2016-05-02 15:10:00,513 Node[0] Epoch[131] Batch [300] Speed: 609.41 samples/sec Train-accuracy=0.999531
2016-05-02 15:10:10,942 Node[0] Epoch[131] Batch [350] Speed: 613.71 samples/sec Train-accuracy=0.998906
2016-05-02 15:10:19,505 Node[0] Epoch[131] Resetting Data Iterator
2016-05-02 15:10:19,505 Node[0] Epoch[131] Time cost=81.635
2016-05-02 15:10:19,670 Node[0] Saved checkpoint to "cifar10/resnet-0132.params"
2016-05-02 15:10:21,573 Node[0] Epoch[131] Validation-accuracy=0.922075
2016-05-02 15:10:32,041 Node[0] Epoch[132] Batch [50] Speed: 614.57 samples/sec Train-accuracy=0.999375
2016-05-02 15:10:42,438 Node[0] Epoch[132] Batch [100] Speed: 615.59 samples/sec Train-accuracy=0.999687
2016-05-02 15:10:52,814 Node[0] Epoch[132] Batch [150] Speed: 616.81 samples/sec Train-accuracy=0.998281
2016-05-02 15:11:03,198 Node[0] Epoch[132] Batch [200] Speed: 616.37 samples/sec Train-accuracy=0.998750
2016-05-02 15:11:13,588 Node[0] Epoch[132] Batch [250] Speed: 615.97 samples/sec Train-accuracy=0.999531
2016-05-02 15:11:24,105 Node[0] Epoch[132] Batch [300] Speed: 608.59 samples/sec Train-accuracy=0.999062
2016-05-02 15:11:34,549 Node[0] Epoch[132] Batch [350] Speed: 612.79 samples/sec Train-accuracy=0.997969
2016-05-02 15:11:43,125 Node[0] Epoch[132] Resetting Data Iterator
2016-05-02 15:11:43,125 Node[0] Epoch[132] Time cost=81.552
2016-05-02 15:11:43,287 Node[0] Saved checkpoint to "cifar10/resnet-0133.params"
2016-05-02 15:11:45,154 Node[0] Epoch[132] Validation-accuracy=0.922776
2016-05-02 15:11:55,609 Node[0] Epoch[133] Batch [50] Speed: 615.38 samples/sec Train-accuracy=0.998906
2016-05-02 15:12:05,992 Node[0] Epoch[133] Batch [100] Speed: 616.41 samples/sec Train-accuracy=0.998906
2016-05-02 15:12:16,413 Node[0] Epoch[133] Batch [150] Speed: 614.18 samples/sec Train-accuracy=0.998594
2016-05-02 15:12:26,821 Node[0] Epoch[133] Batch [200] Speed: 614.93 samples/sec Train-accuracy=0.999062
2016-05-02 15:12:37,265 Node[0] Epoch[133] Batch [250] Speed: 612.77 samples/sec Train-accuracy=0.999375
2016-05-02 15:12:47,785 Node[0] Epoch[133] Batch [300] Speed: 608.39 samples/sec Train-accuracy=0.999844
2016-05-02 15:12:58,244 Node[0] Epoch[133] Batch [350] Speed: 611.93 samples/sec Train-accuracy=0.998437
2016-05-02 15:13:06,618 Node[0] Epoch[133] Resetting Data Iterator
2016-05-02 15:13:06,618 Node[0] Epoch[133] Time cost=81.463
2016-05-02 15:13:06,781 Node[0] Saved checkpoint to "cifar10/resnet-0134.params"
2016-05-02 15:13:08,645 Node[0] Epoch[133] Validation-accuracy=0.923277
2016-05-02 15:13:19,029 Node[0] Epoch[134] Batch [50] Speed: 619.60 samples/sec Train-accuracy=0.999375
2016-05-02 15:13:29,444 Node[0] Epoch[134] Batch [100] Speed: 614.49 samples/sec Train-accuracy=0.999219
2016-05-02 15:13:39,818 Node[0] Epoch[134] Batch [150] Speed: 616.98 samples/sec Train-accuracy=0.998281
2016-05-02 15:13:50,181 Node[0] Epoch[134] Batch [200] Speed: 617.55 samples/sec Train-accuracy=0.999375
2016-05-02 15:14:00,644 Node[0] Epoch[134] Batch [250] Speed: 611.72 samples/sec Train-accuracy=0.998125
2016-05-02 15:14:11,119 Node[0] Epoch[134] Batch [300] Speed: 611.02 samples/sec Train-accuracy=0.999531
2016-05-02 15:14:21,549 Node[0] Epoch[134] Batch [350] Speed: 613.59 samples/sec Train-accuracy=0.999531
2016-05-02 15:14:30,115 Node[0] Epoch[134] Resetting Data Iterator
2016-05-02 15:14:30,115 Node[0] Epoch[134] Time cost=81.470
2016-05-02 15:14:30,281 Node[0] Saved checkpoint to "cifar10/resnet-0135.params"
2016-05-02 15:14:32,158 Node[0] Epoch[134] Validation-accuracy=0.921875
2016-05-02 15:14:42,607 Node[0] Epoch[135] Batch [50] Speed: 615.74 samples/sec Train-accuracy=0.998750
2016-05-02 15:14:53,021 Node[0] Epoch[135] Batch [100] Speed: 614.56 samples/sec Train-accuracy=0.998906
2016-05-02 15:15:03,381 Node[0] Epoch[135] Batch [150] Speed: 617.76 samples/sec Train-accuracy=0.999219
2016-05-02 15:15:13,735 Node[0] Epoch[135] Batch [200] Speed: 618.15 samples/sec Train-accuracy=0.998594
2016-05-02 15:15:24,199 Node[0] Epoch[135] Batch [250] Speed: 611.61 samples/sec Train-accuracy=0.998594
2016-05-02 15:15:34,703 Node[0] Epoch[135] Batch [300] Speed: 609.35 samples/sec Train-accuracy=0.999219
2016-05-02 15:15:45,179 Node[0] Epoch[135] Batch [350] Speed: 610.91 samples/sec Train-accuracy=0.999219
2016-05-02 15:15:53,486 Node[0] Epoch[135] Resetting Data Iterator
2016-05-02 15:15:53,487 Node[0] Epoch[135] Time cost=81.329
2016-05-02 15:15:53,648 Node[0] Saved checkpoint to "cifar10/resnet-0136.params"
2016-05-02 15:15:55,564 Node[0] Epoch[135] Validation-accuracy=0.922075
2016-05-02 15:16:06,022 Node[0] Epoch[136] Batch [50] Speed: 615.17 samples/sec Train-accuracy=0.998906
2016-05-02 15:16:16,551 Node[0] Epoch[136] Batch [100] Speed: 607.85 samples/sec Train-accuracy=0.999375
2016-05-02 15:16:26,953 Node[0] Epoch[136] Batch [150] Speed: 615.28 samples/sec Train-accuracy=0.999687
2016-05-02 15:16:37,398 Node[0] Epoch[136] Batch [200] Speed: 612.80 samples/sec Train-accuracy=0.998906
2016-05-02 15:16:47,798 Node[0] Epoch[136] Batch [250] Speed: 615.39 samples/sec Train-accuracy=0.999531
2016-05-02 15:16:58,180 Node[0] Epoch[136] Batch [300] Speed: 616.45 samples/sec Train-accuracy=0.998906
2016-05-02 15:17:08,660 Node[0] Epoch[136] Batch [350] Speed: 610.73 samples/sec Train-accuracy=0.999062
2016-05-02 15:17:17,301 Node[0] Epoch[136] Resetting Data Iterator
2016-05-02 15:17:17,301 Node[0] Epoch[136] Time cost=81.737
2016-05-02 15:17:17,468 Node[0] Saved checkpoint to "cifar10/resnet-0137.params"
2016-05-02 15:17:19,598 Node[0] Epoch[136] Validation-accuracy=0.921578
2016-05-02 15:17:30,049 Node[0] Epoch[137] Batch [50] Speed: 615.60 samples/sec Train-accuracy=0.999062
2016-05-02 15:17:40,472 Node[0] Epoch[137] Batch [100] Speed: 614.04 samples/sec Train-accuracy=0.999531
2016-05-02 15:17:50,836 Node[0] Epoch[137] Batch [150] Speed: 617.55 samples/sec Train-accuracy=0.999531
2016-05-02 15:18:01,200 Node[0] Epoch[137] Batch [200] Speed: 617.56 samples/sec Train-accuracy=0.998750
2016-05-02 15:18:11,570 Node[0] Epoch[137] Batch [250] Speed: 617.17 samples/sec Train-accuracy=0.999375
2016-05-02 15:18:21,970 Node[0] Epoch[137] Batch [300] Speed: 615.41 samples/sec Train-accuracy=0.998594
2016-05-02 15:18:32,424 Node[0] Epoch[137] Batch [350] Speed: 612.21 samples/sec Train-accuracy=0.998594
2016-05-02 15:18:41,087 Node[0] Epoch[137] Resetting Data Iterator
2016-05-02 15:18:41,087 Node[0] Epoch[137] Time cost=81.489
2016-05-02 15:18:41,252 Node[0] Saved checkpoint to "cifar10/resnet-0138.params"
2016-05-02 15:18:43,150 Node[0] Epoch[137] Validation-accuracy=0.920974
2016-05-02 15:18:53,540 Node[0] Epoch[138] Batch [50] Speed: 619.26 samples/sec Train-accuracy=0.998750
2016-05-02 15:19:03,924 Node[0] Epoch[138] Batch [100] Speed: 616.35 samples/sec Train-accuracy=0.999219
2016-05-02 15:19:14,324 Node[0] Epoch[138] Batch [150] Speed: 615.40 samples/sec Train-accuracy=0.999062
2016-05-02 15:19:24,721 Node[0] Epoch[138] Batch [200] Speed: 615.57 samples/sec Train-accuracy=0.998594
2016-05-02 15:19:35,154 Node[0] Epoch[138] Batch [250] Speed: 613.48 samples/sec Train-accuracy=0.998906
2016-05-02 15:19:45,655 Node[0] Epoch[138] Batch [300] Speed: 609.45 samples/sec Train-accuracy=0.999531
2016-05-02 15:19:56,123 Node[0] Epoch[138] Batch [350] Speed: 611.44 samples/sec Train-accuracy=0.999062
2016-05-02 15:20:04,424 Node[0] Epoch[138] Resetting Data Iterator
2016-05-02 15:20:04,424 Node[0] Epoch[138] Time cost=81.274
2016-05-02 15:20:04,587 Node[0] Saved checkpoint to "cifar10/resnet-0139.params"
2016-05-02 15:20:06,517 Node[0] Epoch[138] Validation-accuracy=0.919371
2016-05-02 15:20:17,019 Node[0] Epoch[139] Batch [50] Speed: 612.57 samples/sec Train-accuracy=0.998750
2016-05-02 15:20:27,456 Node[0] Epoch[139] Batch [100] Speed: 613.22 samples/sec Train-accuracy=0.999375
2016-05-02 15:20:37,844 Node[0] Epoch[139] Batch [150] Speed: 616.13 samples/sec Train-accuracy=0.999687
2016-05-02 15:20:48,232 Node[0] Epoch[139] Batch [200] Speed: 616.07 samples/sec Train-accuracy=0.998750
2016-05-02 15:20:58,691 Node[0] Epoch[139] Batch [250] Speed: 611.93 samples/sec Train-accuracy=0.999687
2016-05-02 15:21:09,175 Node[0] Epoch[139] Batch [300] Speed: 610.47 samples/sec Train-accuracy=0.999375
2016-05-02 15:21:19,653 Node[0] Epoch[139] Batch [350] Speed: 610.83 samples/sec Train-accuracy=0.999687
2016-05-02 15:21:28,235 Node[0] Epoch[139] Resetting Data Iterator
2016-05-02 15:21:28,235 Node[0] Epoch[139] Time cost=81.718
2016-05-02 15:21:28,403 Node[0] Saved checkpoint to "cifar10/resnet-0140.params"
2016-05-02 15:21:30,317 Node[0] Epoch[139] Validation-accuracy=0.922075
2016-05-02 15:21:40,767 Node[0] Epoch[140] Batch [50] Speed: 615.64 samples/sec Train-accuracy=0.998906
2016-05-02 15:21:51,169 Node[0] Epoch[140] Batch [100] Speed: 615.27 samples/sec Train-accuracy=0.999219
2016-05-02 15:22:01,594 Node[0] Epoch[140] Batch [150] Speed: 613.98 samples/sec Train-accuracy=0.999687
2016-05-02 15:22:11,974 Node[0] Epoch[140] Batch [200] Speed: 616.53 samples/sec Train-accuracy=0.998906
2016-05-02 15:22:22,345 Node[0] Epoch[140] Batch [250] Speed: 617.15 samples/sec Train-accuracy=0.999219
2016-05-02 15:22:32,693 Node[0] Epoch[140] Batch [300] Speed: 618.49 samples/sec Train-accuracy=0.999375
2016-05-02 15:22:43,056 Node[0] Epoch[140] Batch [350] Speed: 617.60 samples/sec Train-accuracy=0.999531
2016-05-02 15:22:51,615 Node[0] Epoch[140] Resetting Data Iterator
2016-05-02 15:22:51,616 Node[0] Epoch[140] Time cost=81.298
2016-05-02 15:22:51,780 Node[0] Saved checkpoint to "cifar10/resnet-0141.params"
2016-05-02 15:22:53,748 Node[0] Epoch[140] Validation-accuracy=0.923678
2016-05-02 15:23:04,320 Node[0] Epoch[141] Batch [50] Speed: 608.59 samples/sec Train-accuracy=0.999375
2016-05-02 15:23:14,700 Node[0] Epoch[141] Batch [100] Speed: 616.58 samples/sec Train-accuracy=0.999375
2016-05-02 15:23:25,152 Node[0] Epoch[141] Batch [150] Speed: 612.39 samples/sec Train-accuracy=0.999531
2016-05-02 15:23:35,538 Node[0] Epoch[141] Batch [200] Speed: 616.21 samples/sec Train-accuracy=0.999219
2016-05-02 15:23:45,968 Node[0] Epoch[141] Batch [250] Speed: 613.65 samples/sec Train-accuracy=0.999062
2016-05-02 15:23:56,408 Node[0] Epoch[141] Batch [300] Speed: 613.00 samples/sec Train-accuracy=0.998750
2016-05-02 15:24:06,754 Node[0] Epoch[141] Batch [350] Speed: 618.64 samples/sec Train-accuracy=0.999219
2016-05-02 15:24:15,041 Node[0] Epoch[141] Resetting Data Iterator
2016-05-02 15:24:15,041 Node[0] Epoch[141] Time cost=81.293
2016-05-02 15:24:15,205 Node[0] Saved checkpoint to "cifar10/resnet-0142.params"
2016-05-02 15:24:17,155 Node[0] Epoch[141] Validation-accuracy=0.922676
2016-05-02 15:24:27,664 Node[0] Epoch[142] Batch [50] Speed: 612.23 samples/sec Train-accuracy=0.999062
2016-05-02 15:24:38,021 Node[0] Epoch[142] Batch [100] Speed: 617.95 samples/sec Train-accuracy=0.999687
2016-05-02 15:24:48,381 Node[0] Epoch[142] Batch [150] Speed: 617.75 samples/sec Train-accuracy=0.998281
2016-05-02 15:24:58,788 Node[0] Epoch[142] Batch [200] Speed: 615.00 samples/sec Train-accuracy=0.999375
2016-05-02 15:25:09,140 Node[0] Epoch[142] Batch [250] Speed: 618.24 samples/sec Train-accuracy=0.999219
2016-05-02 15:25:19,567 Node[0] Epoch[142] Batch [300] Speed: 613.79 samples/sec Train-accuracy=0.999375
2016-05-02 15:25:30,050 Node[0] Epoch[142] Batch [350] Speed: 610.56 samples/sec Train-accuracy=0.999062
2016-05-02 15:25:38,632 Node[0] Epoch[142] Resetting Data Iterator
2016-05-02 15:25:38,632 Node[0] Epoch[142] Time cost=81.477
2016-05-02 15:25:38,795 Node[0] Saved checkpoint to "cifar10/resnet-0143.params"
2016-05-02 15:25:40,697 Node[0] Epoch[142] Validation-accuracy=0.921174
2016-05-02 15:25:51,087 Node[0] Epoch[143] Batch [50] Speed: 619.28 samples/sec Train-accuracy=0.999531
2016-05-02 15:26:01,486 Node[0] Epoch[143] Batch [100] Speed: 615.44 samples/sec Train-accuracy=0.998750
2016-05-02 15:26:11,873 Node[0] Epoch[143] Batch [150] Speed: 616.21 samples/sec Train-accuracy=0.999687
2016-05-02 15:26:22,241 Node[0] Epoch[143] Batch [200] Speed: 617.30 samples/sec Train-accuracy=0.999687
2016-05-02 15:26:32,630 Node[0] Epoch[143] Batch [250] Speed: 616.01 samples/sec Train-accuracy=0.999375
2016-05-02 15:26:43,015 Node[0] Epoch[143] Batch [300] Speed: 616.34 samples/sec Train-accuracy=0.998906
2016-05-02 15:26:53,485 Node[0] Epoch[143] Batch [350] Speed: 611.26 samples/sec Train-accuracy=0.999844
2016-05-02 15:27:01,845 Node[0] Epoch[143] Resetting Data Iterator
2016-05-02 15:27:01,846 Node[0] Epoch[143] Time cost=81.148
2016-05-02 15:27:02,012 Node[0] Saved checkpoint to "cifar10/resnet-0144.params"
2016-05-02 15:27:03,935 Node[0] Epoch[143] Validation-accuracy=0.921074
2016-05-02 15:27:14,412 Node[0] Epoch[144] Batch [50] Speed: 614.13 samples/sec Train-accuracy=0.999219
2016-05-02 15:27:24,844 Node[0] Epoch[144] Batch [100] Speed: 613.50 samples/sec Train-accuracy=0.999062
2016-05-02 15:27:35,252 Node[0] Epoch[144] Batch [150] Speed: 614.94 samples/sec Train-accuracy=0.999219
2016-05-02 15:27:45,661 Node[0] Epoch[144] Batch [200] Speed: 614.87 samples/sec Train-accuracy=0.999375
2016-05-02 15:27:56,084 Node[0] Epoch[144] Batch [250] Speed: 614.02 samples/sec Train-accuracy=0.999375
2016-05-02 15:28:06,532 Node[0] Epoch[144] Batch [300] Speed: 612.59 samples/sec Train-accuracy=0.999062
2016-05-02 15:28:16,983 Node[0] Epoch[144] Batch [350] Speed: 612.38 samples/sec Train-accuracy=0.999531
2016-05-02 15:28:25,510 Node[0] Epoch[144] Resetting Data Iterator
2016-05-02 15:28:25,511 Node[0] Epoch[144] Time cost=81.576
2016-05-02 15:28:25,676 Node[0] Saved checkpoint to "cifar10/resnet-0145.params"
2016-05-02 15:28:27,730 Node[0] Epoch[144] Validation-accuracy=0.921084
2016-05-02 15:28:38,166 Node[0] Epoch[145] Batch [50] Speed: 616.43 samples/sec Train-accuracy=0.999531
2016-05-02 15:28:48,573 Node[0] Epoch[145] Batch [100] Speed: 614.99 samples/sec Train-accuracy=0.998594
2016-05-02 15:28:58,961 Node[0] Epoch[145] Batch [150] Speed: 616.12 samples/sec Train-accuracy=0.999375
2016-05-02 15:29:09,334 Node[0] Epoch[145] Batch [200] Speed: 616.99 samples/sec Train-accuracy=0.999062
2016-05-02 15:29:19,713 Node[0] Epoch[145] Batch [250] Speed: 616.69 samples/sec Train-accuracy=0.999375
2016-05-02 15:29:30,175 Node[0] Epoch[145] Batch [300] Speed: 611.70 samples/sec Train-accuracy=0.999687
2016-05-02 15:29:40,676 Node[0] Epoch[145] Batch [350] Speed: 609.50 samples/sec Train-accuracy=0.999531
2016-05-02 15:29:49,247 Node[0] Epoch[145] Resetting Data Iterator
2016-05-02 15:29:49,247 Node[0] Epoch[145] Time cost=81.517
2016-05-02 15:29:49,414 Node[0] Saved checkpoint to "cifar10/resnet-0146.params"
2016-05-02 15:29:51,332 Node[0] Epoch[145] Validation-accuracy=0.921575
2016-05-02 15:30:01,750 Node[0] Epoch[146] Batch [50] Speed: 617.54 samples/sec Train-accuracy=0.999375
2016-05-02 15:30:12,199 Node[0] Epoch[146] Batch [100] Speed: 612.56 samples/sec Train-accuracy=0.999687
2016-05-02 15:30:22,531 Node[0] Epoch[146] Batch [150] Speed: 619.43 samples/sec Train-accuracy=0.999219
2016-05-02 15:30:32,946 Node[0] Epoch[146] Batch [200] Speed: 614.54 samples/sec Train-accuracy=0.999844
2016-05-02 15:30:43,372 Node[0] Epoch[146] Batch [250] Speed: 613.85 samples/sec Train-accuracy=0.999062
2016-05-02 15:30:53,830 Node[0] Epoch[146] Batch [300] Speed: 611.97 samples/sec Train-accuracy=0.999219
2016-05-02 15:31:04,290 Node[0] Epoch[146] Batch [350] Speed: 611.86 samples/sec Train-accuracy=0.999531
2016-05-02 15:31:12,650 Node[0] Epoch[146] Resetting Data Iterator
2016-05-02 15:31:12,651 Node[0] Epoch[146] Time cost=81.318
2016-05-02 15:31:12,814 Node[0] Saved checkpoint to "cifar10/resnet-0147.params"
2016-05-02 15:31:14,727 Node[0] Epoch[146] Validation-accuracy=0.924279
2016-05-02 15:31:25,117 Node[0] Epoch[147] Batch [50] Speed: 619.15 samples/sec Train-accuracy=0.999219
2016-05-02 15:31:35,456 Node[0] Epoch[147] Batch [100] Speed: 619.01 samples/sec Train-accuracy=0.999687
2016-05-02 15:31:45,879 Node[0] Epoch[147] Batch [150] Speed: 614.09 samples/sec Train-accuracy=0.999531
2016-05-02 15:31:56,223 Node[0] Epoch[147] Batch [200] Speed: 618.69 samples/sec Train-accuracy=0.999687
2016-05-02 15:32:06,633 Node[0] Epoch[147] Batch [250] Speed: 614.82 samples/sec Train-accuracy=0.999375
2016-05-02 15:32:17,129 Node[0] Epoch[147] Batch [300] Speed: 609.79 samples/sec Train-accuracy=0.999219
2016-05-02 15:32:27,582 Node[0] Epoch[147] Batch [350] Speed: 612.23 samples/sec Train-accuracy=0.999531
2016-05-02 15:32:36,189 Node[0] Epoch[147] Resetting Data Iterator
2016-05-02 15:32:36,189 Node[0] Epoch[147] Time cost=81.462
2016-05-02 15:32:36,353 Node[0] Saved checkpoint to "cifar10/resnet-0148.params"
2016-05-02 15:32:38,257 Node[0] Epoch[147] Validation-accuracy=0.921975
2016-05-02 15:32:48,621 Node[0] Epoch[148] Batch [50] Speed: 620.74 samples/sec Train-accuracy=0.999375
2016-05-02 15:32:59,065 Node[0] Epoch[148] Batch [100] Speed: 612.81 samples/sec Train-accuracy=0.998437
2016-05-02 15:33:09,481 Node[0] Epoch[148] Batch [150] Speed: 614.44 samples/sec Train-accuracy=0.999844
2016-05-02 15:33:19,877 Node[0] Epoch[148] Batch [200] Speed: 615.63 samples/sec Train-accuracy=0.999062
2016-05-02 15:33:30,289 Node[0] Epoch[148] Batch [250] Speed: 614.71 samples/sec Train-accuracy=0.999844
2016-05-02 15:33:40,652 Node[0] Epoch[148] Batch [300] Speed: 617.61 samples/sec Train-accuracy=0.999687
2016-05-02 15:33:51,050 Node[0] Epoch[148] Batch [350] Speed: 615.50 samples/sec Train-accuracy=0.999531
2016-05-02 15:33:59,594 Node[0] Epoch[148] Resetting Data Iterator
2016-05-02 15:33:59,594 Node[0] Epoch[148] Time cost=81.337
2016-05-02 15:33:59,760 Node[0] Saved checkpoint to "cifar10/resnet-0149.params"
2016-05-02 15:34:01,687 Node[0] Epoch[148] Validation-accuracy=0.920673
2016-05-02 15:34:12,189 Node[0] Epoch[149] Batch [50] Speed: 612.60 samples/sec Train-accuracy=0.999062
2016-05-02 15:34:22,596 Node[0] Epoch[149] Batch [100] Speed: 615.00 samples/sec Train-accuracy=0.999219
2016-05-02 15:34:32,981 Node[0] Epoch[149] Batch [150] Speed: 616.28 samples/sec Train-accuracy=0.999531
2016-05-02 15:34:43,387 Node[0] Epoch[149] Batch [200] Speed: 615.06 samples/sec Train-accuracy=0.999531
2016-05-02 15:34:53,803 Node[0] Epoch[149] Batch [250] Speed: 614.40 samples/sec Train-accuracy=0.999687
2016-05-02 15:35:04,238 Node[0] Epoch[149] Batch [300] Speed: 613.34 samples/sec Train-accuracy=0.999375
2016-05-02 15:35:14,630 Node[0] Epoch[149] Batch [350] Speed: 615.91 samples/sec Train-accuracy=0.999375
2016-05-02 15:35:22,963 Node[0] Epoch[149] Resetting Data Iterator
2016-05-02 15:35:22,964 Node[0] Epoch[149] Time cost=81.276
2016-05-02 15:35:23,129 Node[0] Saved checkpoint to "cifar10/resnet-0150.params"
2016-05-02 15:35:25,026 Node[0] Epoch[149] Validation-accuracy=0.919571
2016-05-02 15:35:35,484 Node[0] Epoch[150] Batch [50] Speed: 615.20 samples/sec Train-accuracy=0.999062
2016-05-02 15:35:45,807 Node[0] Epoch[150] Batch [100] Speed: 619.98 samples/sec Train-accuracy=0.999219
2016-05-02 15:35:56,161 Node[0] Epoch[150] Batch [150] Speed: 618.14 samples/sec Train-accuracy=0.999219
2016-05-02 15:36:06,515 Node[0] Epoch[150] Batch [200] Speed: 618.15 samples/sec Train-accuracy=0.999062
2016-05-02 15:36:16,868 Node[0] Epoch[150] Batch [250] Speed: 618.20 samples/sec Train-accuracy=0.999062
2016-05-02 15:36:27,259 Node[0] Epoch[150] Batch [300] Speed: 615.92 samples/sec Train-accuracy=0.999531
2016-05-02 15:36:37,725 Node[0] Epoch[150] Batch [350] Speed: 611.50 samples/sec Train-accuracy=0.999375
2016-05-02 15:36:46,315 Node[0] Epoch[150] Resetting Data Iterator
2016-05-02 15:36:46,315 Node[0] Epoch[150] Time cost=81.289
2016-05-02 15:36:46,480 Node[0] Saved checkpoint to "cifar10/resnet-0151.params"
2016-05-02 15:36:48,408 Node[0] Epoch[150] Validation-accuracy=0.920773
2016-05-02 15:36:58,829 Node[0] Epoch[151] Batch [50] Speed: 617.42 samples/sec Train-accuracy=0.999219
2016-05-02 15:37:09,253 Node[0] Epoch[151] Batch [100] Speed: 613.97 samples/sec Train-accuracy=1.000000
2016-05-02 15:37:19,593 Node[0] Epoch[151] Batch [150] Speed: 618.98 samples/sec Train-accuracy=0.999375
2016-05-02 15:37:29,961 Node[0] Epoch[151] Batch [200] Speed: 617.28 samples/sec Train-accuracy=0.999219
2016-05-02 15:37:40,326 Node[0] Epoch[151] Batch [250] Speed: 617.48 samples/sec Train-accuracy=0.999375
2016-05-02 15:37:50,714 Node[0] Epoch[151] Batch [300] Speed: 616.10 samples/sec Train-accuracy=0.999844
2016-05-02 15:38:01,133 Node[0] Epoch[151] Batch [350] Speed: 614.30 samples/sec Train-accuracy=0.999375
2016-05-02 15:38:09,454 Node[0] Epoch[151] Resetting Data Iterator
2016-05-02 15:38:09,455 Node[0] Epoch[151] Time cost=81.046
2016-05-02 15:38:09,615 Node[0] Saved checkpoint to "cifar10/resnet-0152.params"
2016-05-02 15:38:11,497 Node[0] Epoch[151] Validation-accuracy=0.922175
2016-05-02 15:38:21,882 Node[0] Epoch[152] Batch [50] Speed: 619.56 samples/sec Train-accuracy=0.999531
2016-05-02 15:38:32,238 Node[0] Epoch[152] Batch [100] Speed: 618.02 samples/sec Train-accuracy=0.999687
2016-05-02 15:38:42,598 Node[0] Epoch[152] Batch [150] Speed: 617.76 samples/sec Train-accuracy=0.999844
2016-05-02 15:38:52,937 Node[0] Epoch[152] Batch [200] Speed: 619.03 samples/sec Train-accuracy=0.999375
2016-05-02 15:39:03,304 Node[0] Epoch[152] Batch [250] Speed: 617.41 samples/sec Train-accuracy=0.998750
2016-05-02 15:39:13,655 Node[0] Epoch[152] Batch [300] Speed: 618.28 samples/sec Train-accuracy=0.999531
2016-05-02 15:39:24,083 Node[0] Epoch[152] Batch [350] Speed: 613.78 samples/sec Train-accuracy=0.999531
2016-05-02 15:39:32,590 Node[0] Epoch[152] Resetting Data Iterator
2016-05-02 15:39:32,590 Node[0] Epoch[152] Time cost=81.093
2016-05-02 15:39:32,753 Node[0] Saved checkpoint to "cifar10/resnet-0153.params"
2016-05-02 15:39:34,834 Node[0] Epoch[152] Validation-accuracy=0.921875
2016-05-02 15:39:45,377 Node[0] Epoch[153] Batch [50] Speed: 610.21 samples/sec Train-accuracy=0.999531
2016-05-02 15:39:55,788 Node[0] Epoch[153] Batch [100] Speed: 614.76 samples/sec Train-accuracy=0.999375
2016-05-02 15:40:06,219 Node[0] Epoch[153] Batch [150] Speed: 613.53 samples/sec Train-accuracy=0.999375
2016-05-02 15:40:16,621 Node[0] Epoch[153] Batch [200] Speed: 615.31 samples/sec Train-accuracy=0.999375
2016-05-02 15:40:27,028 Node[0] Epoch[153] Batch [250] Speed: 615.01 samples/sec Train-accuracy=0.999531
2016-05-02 15:40:37,440 Node[0] Epoch[153] Batch [300] Speed: 614.66 samples/sec Train-accuracy=0.999531
2016-05-02 15:40:47,820 Node[0] Epoch[153] Batch [350] Speed: 616.58 samples/sec Train-accuracy=0.999062
2016-05-02 15:40:56,328 Node[0] Epoch[153] Resetting Data Iterator
2016-05-02 15:40:56,328 Node[0] Epoch[153] Time cost=81.494
2016-05-02 15:40:56,486 Node[0] Saved checkpoint to "cifar10/resnet-0154.params"
2016-05-02 15:40:58,375 Node[0] Epoch[153] Validation-accuracy=0.922376
2016-05-02 15:41:08,832 Node[0] Epoch[154] Batch [50] Speed: 615.26 samples/sec Train-accuracy=0.999219
2016-05-02 15:41:19,241 Node[0] Epoch[154] Batch [100] Speed: 614.85 samples/sec Train-accuracy=0.999062
2016-05-02 15:41:29,665 Node[0] Epoch[154] Batch [150] Speed: 613.98 samples/sec Train-accuracy=0.999062
2016-05-02 15:41:40,054 Node[0] Epoch[154] Batch [200] Speed: 616.07 samples/sec Train-accuracy=0.999531
2016-05-02 15:41:50,471 Node[0] Epoch[154] Batch [250] Speed: 614.38 samples/sec Train-accuracy=0.999375
2016-05-02 15:42:00,880 Node[0] Epoch[154] Batch [300] Speed: 614.86 samples/sec Train-accuracy=0.998906
2016-05-02 15:42:11,261 Node[0] Epoch[154] Batch [350] Speed: 616.53 samples/sec Train-accuracy=0.999531
2016-05-02 15:42:19,539 Node[0] Epoch[154] Resetting Data Iterator
2016-05-02 15:42:19,540 Node[0] Epoch[154] Time cost=81.164
2016-05-02 15:42:19,700 Node[0] Saved checkpoint to "cifar10/resnet-0155.params"
2016-05-02 15:42:21,641 Node[0] Epoch[154] Validation-accuracy=0.921474
2016-05-02 15:42:32,167 Node[0] Epoch[155] Batch [50] Speed: 611.22 samples/sec Train-accuracy=0.999531
2016-05-02 15:42:42,647 Node[0] Epoch[155] Batch [100] Speed: 610.66 samples/sec Train-accuracy=0.999219
2016-05-02 15:42:53,042 Node[0] Epoch[155] Batch [150] Speed: 615.72 samples/sec Train-accuracy=0.999531
2016-05-02 15:43:03,461 Node[0] Epoch[155] Batch [200] Speed: 614.26 samples/sec Train-accuracy=0.999687
2016-05-02 15:43:13,836 Node[0] Epoch[155] Batch [250] Speed: 616.89 samples/sec Train-accuracy=0.999375
2016-05-02 15:43:24,226 Node[0] Epoch[155] Batch [300] Speed: 615.98 samples/sec Train-accuracy=0.999531
2016-05-02 15:43:34,578 Node[0] Epoch[155] Batch [350] Speed: 618.25 samples/sec Train-accuracy=0.999531
2016-05-02 15:43:43,063 Node[0] Epoch[155] Resetting Data Iterator
2016-05-02 15:43:43,063 Node[0] Epoch[155] Time cost=81.421
2016-05-02 15:43:43,225 Node[0] Saved checkpoint to "cifar10/resnet-0156.params"
2016-05-02 15:43:45,182 Node[0] Epoch[155] Validation-accuracy=0.921975
2016-05-02 15:43:55,661 Node[0] Epoch[156] Batch [50] Speed: 613.95 samples/sec Train-accuracy=0.999219
2016-05-02 15:44:06,012 Node[0] Epoch[156] Batch [100] Speed: 618.30 samples/sec Train-accuracy=0.999844
2016-05-02 15:44:16,364 Node[0] Epoch[156] Batch [150] Speed: 618.29 samples/sec Train-accuracy=0.999687
2016-05-02 15:44:26,722 Node[0] Epoch[156] Batch [200] Speed: 617.88 samples/sec Train-accuracy=0.999687
2016-05-02 15:44:37,112 Node[0] Epoch[156] Batch [250] Speed: 615.99 samples/sec Train-accuracy=0.998906
2016-05-02 15:44:47,523 Node[0] Epoch[156] Batch [300] Speed: 614.73 samples/sec Train-accuracy=0.999844
2016-05-02 15:44:57,898 Node[0] Epoch[156] Batch [350] Speed: 616.93 samples/sec Train-accuracy=0.999375
2016-05-02 15:45:06,438 Node[0] Epoch[156] Resetting Data Iterator
2016-05-02 15:45:06,438 Node[0] Epoch[156] Time cost=81.256
2016-05-02 15:45:06,603 Node[0] Saved checkpoint to "cifar10/resnet-0157.params"
2016-05-02 15:45:08,549 Node[0] Epoch[156] Validation-accuracy=0.922276
2016-05-02 15:45:18,965 Node[0] Epoch[157] Batch [50] Speed: 617.60 samples/sec Train-accuracy=0.999375
2016-05-02 15:45:29,396 Node[0] Epoch[157] Batch [100] Speed: 613.61 samples/sec Train-accuracy=0.999531
2016-05-02 15:45:39,808 Node[0] Epoch[157] Batch [150] Speed: 614.71 samples/sec Train-accuracy=0.999375
2016-05-02 15:45:50,175 Node[0] Epoch[157] Batch [200] Speed: 617.35 samples/sec Train-accuracy=0.999687
2016-05-02 15:46:00,530 Node[0] Epoch[157] Batch [250] Speed: 618.06 samples/sec Train-accuracy=0.999375
2016-05-02 15:46:10,898 Node[0] Epoch[157] Batch [300] Speed: 617.31 samples/sec Train-accuracy=0.999687
2016-05-02 15:46:21,257 Node[0] Epoch[157] Batch [350] Speed: 617.78 samples/sec Train-accuracy=0.999219
2016-05-02 15:46:29,599 Node[0] Epoch[157] Resetting Data Iterator
2016-05-02 15:46:29,599 Node[0] Epoch[157] Time cost=81.050
2016-05-02 15:46:29,766 Node[0] Saved checkpoint to "cifar10/resnet-0158.params"
2016-05-02 15:46:31,689 Node[0] Epoch[157] Validation-accuracy=0.922175
2016-05-02 15:46:42,137 Node[0] Epoch[158] Batch [50] Speed: 615.78 samples/sec Train-accuracy=0.999219
2016-05-02 15:46:52,500 Node[0] Epoch[158] Batch [100] Speed: 617.59 samples/sec Train-accuracy=0.999531
2016-05-02 15:47:02,861 Node[0] Epoch[158] Batch [150] Speed: 617.70 samples/sec Train-accuracy=0.998750
2016-05-02 15:47:13,254 Node[0] Epoch[158] Batch [200] Speed: 615.81 samples/sec Train-accuracy=0.998906
2016-05-02 15:47:23,605 Node[0] Epoch[158] Batch [250] Speed: 618.35 samples/sec Train-accuracy=0.998594
2016-05-02 15:47:33,945 Node[0] Epoch[158] Batch [300] Speed: 618.94 samples/sec Train-accuracy=0.999375
2016-05-02 15:47:44,300 Node[0] Epoch[158] Batch [350] Speed: 618.11 samples/sec Train-accuracy=0.999219
2016-05-02 15:47:52,809 Node[0] Epoch[158] Resetting Data Iterator
2016-05-02 15:47:52,810 Node[0] Epoch[158] Time cost=81.121
2016-05-02 15:47:52,970 Node[0] Saved checkpoint to "cifar10/resnet-0159.params"
2016-05-02 15:47:54,873 Node[0] Epoch[158] Validation-accuracy=0.922776
2016-05-02 15:48:05,352 Node[0] Epoch[159] Batch [50] Speed: 613.98 samples/sec Train-accuracy=0.999687
2016-05-02 15:48:15,692 Node[0] Epoch[159] Batch [100] Speed: 618.97 samples/sec Train-accuracy=0.999844
2016-05-02 15:48:26,085 Node[0] Epoch[159] Batch [150] Speed: 615.80 samples/sec Train-accuracy=0.999531
2016-05-02 15:48:36,428 Node[0] Epoch[159] Batch [200] Speed: 618.80 samples/sec Train-accuracy=0.999687
2016-05-02 15:48:46,852 Node[0] Epoch[159] Batch [250] Speed: 613.96 samples/sec Train-accuracy=0.999375
2016-05-02 15:48:55,174 Node[0] Update[62401]: Change learning rate to 1.00000e-03
2016-05-02 15:48:57,254 Node[0] Epoch[159] Batch [300] Speed: 615.28 samples/sec Train-accuracy=0.999219
2016-05-02 15:49:07,658 Node[0] Epoch[159] Batch [350] Speed: 615.18 samples/sec Train-accuracy=0.999844
2016-05-02 15:49:15,964 Node[0] Epoch[159] Resetting Data Iterator
2016-05-02 15:49:15,964 Node[0] Epoch[159] Time cost=81.091
2016-05-02 15:49:16,124 Node[0] Saved checkpoint to "cifar10/resnet-0160.params"
2016-05-02 15:49:18,037 Node[0] Epoch[159] Validation-accuracy=0.921775
2016-05-02 15:49:28,494 Node[0] Epoch[160] Batch [50] Speed: 615.25 samples/sec Train-accuracy=0.999531
2016-05-02 15:49:38,879 Node[0] Epoch[160] Batch [100] Speed: 616.25 samples/sec Train-accuracy=0.999531
2016-05-02 15:49:49,272 Node[0] Epoch[160] Batch [150] Speed: 615.83 samples/sec Train-accuracy=0.999531
2016-05-02 15:49:59,690 Node[0] Epoch[160] Batch [200] Speed: 614.35 samples/sec Train-accuracy=0.999844
2016-05-02 15:50:10,044 Node[0] Epoch[160] Batch [250] Speed: 618.14 samples/sec Train-accuracy=0.999375
2016-05-02 15:50:20,402 Node[0] Epoch[160] Batch [300] Speed: 617.90 samples/sec Train-accuracy=0.999687
2016-05-02 15:50:30,826 Node[0] Epoch[160] Batch [350] Speed: 613.96 samples/sec Train-accuracy=0.999531
2016-05-02 15:50:39,329 Node[0] Epoch[160] Resetting Data Iterator
2016-05-02 15:50:39,329 Node[0] Epoch[160] Time cost=81.292
2016-05-02 15:50:39,498 Node[0] Saved checkpoint to "cifar10/resnet-0161.params"
2016-05-02 15:50:41,608 Node[0] Epoch[160] Validation-accuracy=0.922172
2016-05-02 15:50:52,000 Node[0] Epoch[161] Batch [50] Speed: 619.11 samples/sec Train-accuracy=0.999062
2016-05-02 15:51:02,386 Node[0] Epoch[161] Batch [100] Speed: 616.21 samples/sec Train-accuracy=1.000000
2016-05-02 15:51:12,784 Node[0] Epoch[161] Batch [150] Speed: 615.51 samples/sec Train-accuracy=0.999687
2016-05-02 15:51:23,192 Node[0] Epoch[161] Batch [200] Speed: 614.94 samples/sec Train-accuracy=0.999531
2016-05-02 15:51:33,577 Node[0] Epoch[161] Batch [250] Speed: 616.27 samples/sec Train-accuracy=0.999687
2016-05-02 15:51:43,978 Node[0] Epoch[161] Batch [300] Speed: 615.36 samples/sec Train-accuracy=0.999687
2016-05-02 15:51:54,362 Node[0] Epoch[161] Batch [350] Speed: 616.31 samples/sec Train-accuracy=0.999375
2016-05-02 15:52:02,869 Node[0] Epoch[161] Resetting Data Iterator
2016-05-02 15:52:02,869 Node[0] Epoch[161] Time cost=81.261
2016-05-02 15:52:03,033 Node[0] Saved checkpoint to "cifar10/resnet-0162.params"
2016-05-02 15:52:04,944 Node[0] Epoch[161] Validation-accuracy=0.921274
2016-05-02 15:52:15,281 Node[0] Epoch[162] Batch [50] Speed: 622.44 samples/sec Train-accuracy=0.999687
2016-05-02 15:52:25,625 Node[0] Epoch[162] Batch [100] Speed: 618.71 samples/sec Train-accuracy=0.999531
2016-05-02 15:52:36,023 Node[0] Epoch[162] Batch [150] Speed: 615.53 samples/sec Train-accuracy=0.999375
2016-05-02 15:52:46,420 Node[0] Epoch[162] Batch [200] Speed: 615.59 samples/sec Train-accuracy=0.999062
2016-05-02 15:52:56,840 Node[0] Epoch[162] Batch [250] Speed: 614.20 samples/sec Train-accuracy=0.999531
2016-05-02 15:53:07,237 Node[0] Epoch[162] Batch [300] Speed: 615.59 samples/sec Train-accuracy=0.999531
2016-05-02 15:53:17,653 Node[0] Epoch[162] Batch [350] Speed: 614.46 samples/sec Train-accuracy=0.999844
2016-05-02 15:53:25,949 Node[0] Epoch[162] Resetting Data Iterator
2016-05-02 15:53:25,950 Node[0] Epoch[162] Time cost=81.005
2016-05-02 15:53:26,113 Node[0] Saved checkpoint to "cifar10/resnet-0163.params"
2016-05-02 15:53:28,010 Node[0] Epoch[162] Validation-accuracy=0.920974
2016-05-02 15:53:38,368 Node[0] Epoch[163] Batch [50] Speed: 621.18 samples/sec Train-accuracy=0.999219
2016-05-02 15:53:48,739 Node[0] Epoch[163] Batch [100] Speed: 617.13 samples/sec Train-accuracy=0.999687
2016-05-02 15:53:59,163 Node[0] Epoch[163] Batch [150] Speed: 613.97 samples/sec Train-accuracy=1.000000
2016-05-02 15:54:09,562 Node[0] Epoch[163] Batch [200] Speed: 615.47 samples/sec Train-accuracy=0.999687
2016-05-02 15:54:19,955 Node[0] Epoch[163] Batch [250] Speed: 615.81 samples/sec Train-accuracy=0.999687
2016-05-02 15:54:30,353 Node[0] Epoch[163] Batch [300] Speed: 615.51 samples/sec Train-accuracy=0.999844
2016-05-02 15:54:40,740 Node[0] Epoch[163] Batch [350] Speed: 616.20 samples/sec Train-accuracy=0.999531
2016-05-02 15:54:49,236 Node[0] Epoch[163] Resetting Data Iterator
2016-05-02 15:54:49,237 Node[0] Epoch[163] Time cost=81.226
2016-05-02 15:54:49,400 Node[0] Saved checkpoint to "cifar10/resnet-0164.params"
2016-05-02 15:54:51,318 Node[0] Epoch[163] Validation-accuracy=0.921775
2016-05-02 15:55:01,693 Node[0] Epoch[164] Batch [50] Speed: 620.08 samples/sec Train-accuracy=0.999531
2016-05-02 15:55:12,070 Node[0] Epoch[164] Batch [100] Speed: 616.76 samples/sec Train-accuracy=0.999844
2016-05-02 15:55:22,426 Node[0] Epoch[164] Batch [150] Speed: 618.02 samples/sec Train-accuracy=0.999687
2016-05-02 15:55:32,780 Node[0] Epoch[164] Batch [200] Speed: 618.13 samples/sec Train-accuracy=0.999687
2016-05-02 15:55:43,155 Node[0] Epoch[164] Batch [250] Speed: 616.88 samples/sec Train-accuracy=1.000000
2016-05-02 15:55:53,506 Node[0] Epoch[164] Batch [300] Speed: 618.28 samples/sec Train-accuracy=0.999687
2016-05-02 15:56:03,906 Node[0] Epoch[164] Batch [350] Speed: 615.43 samples/sec Train-accuracy=0.999375
2016-05-02 15:56:12,448 Node[0] Epoch[164] Resetting Data Iterator
2016-05-02 15:56:12,448 Node[0] Epoch[164] Time cost=81.130
2016-05-02 15:56:12,609 Node[0] Saved checkpoint to "cifar10/resnet-0165.params"
2016-05-02 15:56:14,498 Node[0] Epoch[164] Validation-accuracy=0.922175
2016-05-02 15:56:24,880 Node[0] Epoch[165] Batch [50] Speed: 619.73 samples/sec Train-accuracy=0.999844
2016-05-02 15:56:35,256 Node[0] Epoch[165] Batch [100] Speed: 616.78 samples/sec Train-accuracy=0.999687
2016-05-02 15:56:45,616 Node[0] Epoch[165] Batch [150] Speed: 617.77 samples/sec Train-accuracy=0.999844
2016-05-02 15:56:56,042 Node[0] Epoch[165] Batch [200] Speed: 613.92 samples/sec Train-accuracy=0.999844
2016-05-02 15:57:06,440 Node[0] Epoch[165] Batch [250] Speed: 615.51 samples/sec Train-accuracy=0.999687
2016-05-02 15:57:16,849 Node[0] Epoch[165] Batch [300] Speed: 614.84 samples/sec Train-accuracy=0.999687
2016-05-02 15:57:27,209 Node[0] Epoch[165] Batch [350] Speed: 617.80 samples/sec Train-accuracy=0.999844
2016-05-02 15:57:35,534 Node[0] Epoch[165] Resetting Data Iterator
2016-05-02 15:57:35,534 Node[0] Epoch[165] Time cost=81.036
2016-05-02 15:57:35,700 Node[0] Saved checkpoint to "cifar10/resnet-0166.params"
2016-05-02 15:57:37,629 Node[0] Epoch[165] Validation-accuracy=0.921975
2016-05-02 15:57:48,053 Node[0] Epoch[166] Batch [50] Speed: 617.16 samples/sec Train-accuracy=0.999844
2016-05-02 15:57:58,413 Node[0] Epoch[166] Batch [100] Speed: 617.80 samples/sec Train-accuracy=0.999219
2016-05-02 15:58:08,857 Node[0] Epoch[166] Batch [150] Speed: 612.81 samples/sec Train-accuracy=0.999375
2016-05-02 15:58:19,217 Node[0] Epoch[166] Batch [200] Speed: 617.76 samples/sec Train-accuracy=0.999531
2016-05-02 15:58:29,583 Node[0] Epoch[166] Batch [250] Speed: 617.45 samples/sec Train-accuracy=0.999844
2016-05-02 15:58:39,970 Node[0] Epoch[166] Batch [300] Speed: 616.14 samples/sec Train-accuracy=0.999844
2016-05-02 15:58:50,345 Node[0] Epoch[166] Batch [350] Speed: 616.94 samples/sec Train-accuracy=0.999687
2016-05-02 15:58:58,920 Node[0] Epoch[166] Resetting Data Iterator
2016-05-02 15:58:58,921 Node[0] Epoch[166] Time cost=81.292
2016-05-02 15:58:59,084 Node[0] Saved checkpoint to "cifar10/resnet-0167.params"
2016-05-02 15:59:01,003 Node[0] Epoch[166] Validation-accuracy=0.920873
2016-05-02 15:59:11,389 Node[0] Epoch[167] Batch [50] Speed: 619.51 samples/sec Train-accuracy=0.999687
2016-05-02 15:59:21,772 Node[0] Epoch[167] Batch [100] Speed: 616.43 samples/sec Train-accuracy=0.999844
2016-05-02 15:59:32,130 Node[0] Epoch[167] Batch [150] Speed: 617.89 samples/sec Train-accuracy=0.999531
2016-05-02 15:59:42,476 Node[0] Epoch[167] Batch [200] Speed: 618.62 samples/sec Train-accuracy=0.999687
2016-05-02 15:59:52,836 Node[0] Epoch[167] Batch [250] Speed: 617.74 samples/sec Train-accuracy=0.999687
2016-05-02 16:00:03,244 Node[0] Epoch[167] Batch [300] Speed: 614.94 samples/sec Train-accuracy=0.999687
2016-05-02 16:00:13,649 Node[0] Epoch[167] Batch [350] Speed: 615.14 samples/sec Train-accuracy=0.999531
2016-05-02 16:00:21,950 Node[0] Epoch[167] Resetting Data Iterator
2016-05-02 16:00:21,950 Node[0] Epoch[167] Time cost=80.947
2016-05-02 16:00:22,110 Node[0] Saved checkpoint to "cifar10/resnet-0168.params"
2016-05-02 16:00:23,998 Node[0] Epoch[167] Validation-accuracy=0.921274
2016-05-02 16:00:34,581 Node[0] Epoch[168] Batch [50] Speed: 607.97 samples/sec Train-accuracy=0.999219
2016-05-02 16:00:45,007 Node[0] Epoch[168] Batch [100] Speed: 613.90 samples/sec Train-accuracy=0.999844
2016-05-02 16:00:55,449 Node[0] Epoch[168] Batch [150] Speed: 612.91 samples/sec Train-accuracy=0.999687
2016-05-02 16:01:05,829 Node[0] Epoch[168] Batch [200] Speed: 616.59 samples/sec Train-accuracy=0.999062
2016-05-02 16:01:16,228 Node[0] Epoch[168] Batch [250] Speed: 615.46 samples/sec Train-accuracy=0.999687
2016-05-02 16:01:26,628 Node[0] Epoch[168] Batch [300] Speed: 615.41 samples/sec Train-accuracy=0.999687
2016-05-02 16:01:36,984 Node[0] Epoch[168] Batch [350] Speed: 618.01 samples/sec Train-accuracy=0.999531
2016-05-02 16:01:45,485 Node[0] Epoch[168] Resetting Data Iterator
2016-05-02 16:01:45,485 Node[0] Epoch[168] Time cost=81.486
2016-05-02 16:01:45,654 Node[0] Saved checkpoint to "cifar10/resnet-0169.params"
2016-05-02 16:01:47,775 Node[0] Epoch[168] Validation-accuracy=0.921084
2016-05-02 16:01:58,285 Node[0] Epoch[169] Batch [50] Speed: 612.05 samples/sec Train-accuracy=1.000000
2016-05-02 16:02:08,642 Node[0] Epoch[169] Batch [100] Speed: 617.99 samples/sec Train-accuracy=0.999844
2016-05-02 16:02:19,049 Node[0] Epoch[169] Batch [150] Speed: 614.99 samples/sec Train-accuracy=0.999531
2016-05-02 16:02:29,464 Node[0] Epoch[169] Batch [200] Speed: 614.50 samples/sec Train-accuracy=0.999687
2016-05-02 16:02:39,866 Node[0] Epoch[169] Batch [250] Speed: 615.27 samples/sec Train-accuracy=0.999531
2016-05-02 16:02:50,233 Node[0] Epoch[169] Batch [300] Speed: 617.36 samples/sec Train-accuracy=0.999375
2016-05-02 16:03:00,612 Node[0] Epoch[169] Batch [350] Speed: 616.63 samples/sec Train-accuracy=0.999687
2016-05-02 16:03:09,149 Node[0] Epoch[169] Resetting Data Iterator
2016-05-02 16:03:09,149 Node[0] Epoch[169] Time cost=81.375
2016-05-02 16:03:09,310 Node[0] Saved checkpoint to "cifar10/resnet-0170.params"
2016-05-02 16:03:11,245 Node[0] Epoch[169] Validation-accuracy=0.921575
2016-05-02 16:03:21,741 Node[0] Epoch[170] Batch [50] Speed: 612.98 samples/sec Train-accuracy=0.999687
2016-05-02 16:03:32,186 Node[0] Epoch[170] Batch [100] Speed: 612.74 samples/sec Train-accuracy=0.999531
2016-05-02 16:03:42,572 Node[0] Epoch[170] Batch [150] Speed: 616.24 samples/sec Train-accuracy=1.000000
2016-05-02 16:03:52,924 Node[0] Epoch[170] Batch [200] Speed: 618.27 samples/sec Train-accuracy=0.999844
2016-05-02 16:04:05,304 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-02 16:04:05,700 Node[0] Start training with [gpu(0)]
2016-05-02 16:04:26,673 Node[0] Epoch[0] Batch [50] Speed: 641.83 samples/sec Train-accuracy=0.127344
2016-05-02 16:04:36,857 Node[0] Epoch[0] Batch [100] Speed: 628.47 samples/sec Train-accuracy=0.200313
2016-05-02 16:04:47,080 Node[0] Epoch[0] Batch [150] Speed: 626.04 samples/sec Train-accuracy=0.273906
2016-05-02 16:04:57,708 Node[0] Epoch[0] Batch [200] Speed: 602.21 samples/sec Train-accuracy=0.320000
2016-05-02 16:05:08,757 Node[0] Epoch[0] Batch [250] Speed: 579.23 samples/sec Train-accuracy=0.356250
2016-05-02 16:05:19,863 Node[0] Epoch[0] Batch [300] Speed: 576.28 samples/sec Train-accuracy=0.369375
2016-05-02 16:05:30,965 Node[0] Epoch[0] Batch [350] Speed: 576.49 samples/sec Train-accuracy=0.397031
2016-05-02 16:05:39,926 Node[0] Epoch[0] Resetting Data Iterator
2016-05-02 16:05:39,926 Node[0] Epoch[0] Time cost=83.483
2016-05-02 16:05:40,099 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-02 16:05:42,246 Node[0] Epoch[0] Validation-accuracy=0.425930
2016-05-02 16:05:53,163 Node[0] Epoch[1] Batch [50] Speed: 589.22 samples/sec Train-accuracy=0.440937
2016-05-02 16:06:03,982 Node[0] Epoch[1] Batch [100] Speed: 591.56 samples/sec Train-accuracy=0.471094
2016-05-02 16:06:14,780 Node[0] Epoch[1] Batch [150] Speed: 592.75 samples/sec Train-accuracy=0.483906
2016-05-02 16:06:25,560 Node[0] Epoch[1] Batch [200] Speed: 593.70 samples/sec Train-accuracy=0.484687
2016-05-02 16:06:36,349 Node[0] Epoch[1] Batch [250] Speed: 593.23 samples/sec Train-accuracy=0.507500
2016-05-02 16:06:47,109 Node[0] Epoch[1] Batch [300] Speed: 594.80 samples/sec Train-accuracy=0.510312
2016-05-02 16:06:57,945 Node[0] Epoch[1] Batch [350] Speed: 590.62 samples/sec Train-accuracy=0.536563
2016-05-02 16:07:06,780 Node[0] Epoch[1] Resetting Data Iterator
2016-05-02 16:07:06,781 Node[0] Epoch[1] Time cost=84.535
2016-05-02 16:07:06,952 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-02 16:07:08,925 Node[0] Epoch[1] Validation-accuracy=0.531250
2016-05-02 16:07:19,654 Node[0] Epoch[2] Batch [50] Speed: 599.62 samples/sec Train-accuracy=0.551719
2016-05-02 16:07:30,315 Node[0] Epoch[2] Batch [100] Speed: 600.35 samples/sec Train-accuracy=0.576719
2016-05-02 16:07:40,982 Node[0] Epoch[2] Batch [150] Speed: 600.01 samples/sec Train-accuracy=0.582656
2016-05-02 16:07:51,675 Node[0] Epoch[2] Batch [200] Speed: 598.50 samples/sec Train-accuracy=0.590781
2016-05-02 16:08:02,342 Node[0] Epoch[2] Batch [250] Speed: 600.03 samples/sec Train-accuracy=0.612500
2016-05-02 16:08:13,021 Node[0] Epoch[2] Batch [300] Speed: 599.30 samples/sec Train-accuracy=0.613750
2016-05-02 16:08:23,690 Node[0] Epoch[2] Batch [350] Speed: 599.90 samples/sec Train-accuracy=0.619062
2016-05-02 16:08:32,251 Node[0] Epoch[2] Resetting Data Iterator
2016-05-02 16:08:32,251 Node[0] Epoch[2] Time cost=83.326
2016-05-02 16:08:32,418 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-02 16:08:34,352 Node[0] Epoch[2] Validation-accuracy=0.607973
2016-05-02 16:08:45,012 Node[0] Epoch[3] Batch [50] Speed: 603.52 samples/sec Train-accuracy=0.634531
2016-05-02 16:08:55,669 Node[0] Epoch[3] Batch [100] Speed: 600.59 samples/sec Train-accuracy=0.646563
2016-05-02 16:09:06,350 Node[0] Epoch[3] Batch [150] Speed: 599.20 samples/sec Train-accuracy=0.660625
2016-05-02 16:09:17,024 Node[0] Epoch[3] Batch [200] Speed: 599.58 samples/sec Train-accuracy=0.669375
2016-05-02 16:09:27,710 Node[0] Epoch[3] Batch [250] Speed: 598.93 samples/sec Train-accuracy=0.671250
2016-05-02 16:09:38,400 Node[0] Epoch[3] Batch [300] Speed: 598.72 samples/sec Train-accuracy=0.678125
2016-05-02 16:09:48,978 Node[0] Epoch[3] Batch [350] Speed: 605.07 samples/sec Train-accuracy=0.679063
2016-05-02 16:09:57,607 Node[0] Epoch[3] Resetting Data Iterator
2016-05-02 16:09:57,607 Node[0] Epoch[3] Time cost=83.254
2016-05-02 16:09:57,773 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-02 16:09:59,736 Node[0] Epoch[3] Validation-accuracy=0.687500
2016-05-02 16:10:10,462 Node[0] Epoch[4] Batch [50] Speed: 599.80 samples/sec Train-accuracy=0.678906
2016-05-02 16:10:21,050 Node[0] Epoch[4] Batch [100] Speed: 604.48 samples/sec Train-accuracy=0.696094
2016-05-02 16:10:31,581 Node[0] Epoch[4] Batch [150] Speed: 607.70 samples/sec Train-accuracy=0.717656
2016-05-02 16:10:42,149 Node[0] Epoch[4] Batch [200] Speed: 605.63 samples/sec Train-accuracy=0.711875
2016-05-02 16:10:52,721 Node[0] Epoch[4] Batch [250] Speed: 605.42 samples/sec Train-accuracy=0.716562
2016-05-02 16:11:03,243 Node[0] Epoch[4] Batch [300] Speed: 608.26 samples/sec Train-accuracy=0.724531
2016-05-02 16:11:13,925 Node[0] Epoch[4] Batch [350] Speed: 599.15 samples/sec Train-accuracy=0.730313
2016-05-02 16:11:22,619 Node[0] Epoch[4] Resetting Data Iterator
2016-05-02 16:11:22,619 Node[0] Epoch[4] Time cost=82.883
2016-05-02 16:11:22,788 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-02 16:11:24,735 Node[0] Epoch[4] Validation-accuracy=0.737981
2016-05-02 16:11:35,366 Node[0] Epoch[5] Batch [50] Speed: 605.18 samples/sec Train-accuracy=0.729688
2016-05-02 16:11:45,786 Node[0] Epoch[5] Batch [100] Speed: 614.20 samples/sec Train-accuracy=0.739219
2016-05-02 16:11:56,238 Node[0] Epoch[5] Batch [150] Speed: 612.34 samples/sec Train-accuracy=0.757188
2016-05-02 16:12:06,780 Node[0] Epoch[5] Batch [200] Speed: 607.09 samples/sec Train-accuracy=0.745156
2016-05-02 16:12:17,263 Node[0] Epoch[5] Batch [250] Speed: 610.52 samples/sec Train-accuracy=0.750625
2016-05-02 16:12:27,802 Node[0] Epoch[5] Batch [300] Speed: 607.32 samples/sec Train-accuracy=0.750469
2016-05-02 16:12:38,355 Node[0] Epoch[5] Batch [350] Speed: 606.49 samples/sec Train-accuracy=0.760781
2016-05-02 16:12:46,726 Node[0] Epoch[5] Resetting Data Iterator
2016-05-02 16:12:46,726 Node[0] Epoch[5] Time cost=81.991
2016-05-02 16:12:46,892 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-02 16:12:48,825 Node[0] Epoch[5] Validation-accuracy=0.755909
2016-05-02 16:12:59,435 Node[0] Epoch[6] Batch [50] Speed: 606.43 samples/sec Train-accuracy=0.765781
2016-05-02 16:13:09,937 Node[0] Epoch[6] Batch [100] Speed: 609.47 samples/sec Train-accuracy=0.760469
2016-05-02 16:13:20,400 Node[0] Epoch[6] Batch [150] Speed: 611.67 samples/sec Train-accuracy=0.782969
2016-05-02 16:13:30,821 Node[0] Epoch[6] Batch [200] Speed: 614.17 samples/sec Train-accuracy=0.774687
2016-05-02 16:13:41,299 Node[0] Epoch[6] Batch [250] Speed: 610.78 samples/sec Train-accuracy=0.773750
2016-05-02 16:13:51,825 Node[0] Epoch[6] Batch [300] Speed: 608.07 samples/sec Train-accuracy=0.782500
2016-05-02 16:14:02,343 Node[0] Epoch[6] Batch [350] Speed: 608.51 samples/sec Train-accuracy=0.782969
2016-05-02 16:14:10,947 Node[0] Epoch[6] Resetting Data Iterator
2016-05-02 16:14:10,947 Node[0] Epoch[6] Time cost=82.122
2016-05-02 16:14:11,111 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-02 16:14:13,039 Node[0] Epoch[6] Validation-accuracy=0.741386
2016-05-02 16:14:23,515 Node[0] Epoch[7] Batch [50] Speed: 614.21 samples/sec Train-accuracy=0.782656
2016-05-02 16:14:34,051 Node[0] Epoch[7] Batch [100] Speed: 607.41 samples/sec Train-accuracy=0.783594
2016-05-02 16:14:44,556 Node[0] Epoch[7] Batch [150] Speed: 609.27 samples/sec Train-accuracy=0.803125
2016-05-02 16:14:55,038 Node[0] Epoch[7] Batch [200] Speed: 610.56 samples/sec Train-accuracy=0.795781
2016-05-02 16:15:05,528 Node[0] Epoch[7] Batch [250] Speed: 610.12 samples/sec Train-accuracy=0.789219
2016-05-02 16:15:15,919 Node[0] Epoch[7] Batch [300] Speed: 615.97 samples/sec Train-accuracy=0.797500
2016-05-02 16:15:26,361 Node[0] Epoch[7] Batch [350] Speed: 612.91 samples/sec Train-accuracy=0.801406
2016-05-02 16:15:34,656 Node[0] Epoch[7] Resetting Data Iterator
2016-05-02 16:15:34,656 Node[0] Epoch[7] Time cost=81.617
2016-05-02 16:15:34,820 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-02 16:15:36,730 Node[0] Epoch[7] Validation-accuracy=0.773938
2016-05-02 16:15:47,370 Node[0] Epoch[8] Batch [50] Speed: 604.73 samples/sec Train-accuracy=0.803906
2016-05-02 16:15:57,810 Node[0] Epoch[8] Batch [100] Speed: 613.00 samples/sec Train-accuracy=0.807969
2016-05-02 16:16:08,250 Node[0] Epoch[8] Batch [150] Speed: 613.07 samples/sec Train-accuracy=0.823281
2016-05-02 16:16:18,721 Node[0] Epoch[8] Batch [200] Speed: 611.18 samples/sec Train-accuracy=0.812031
2016-05-02 16:16:29,223 Node[0] Epoch[8] Batch [250] Speed: 609.44 samples/sec Train-accuracy=0.815000
2016-05-02 16:16:39,718 Node[0] Epoch[8] Batch [300] Speed: 609.82 samples/sec Train-accuracy=0.816719
2016-05-02 16:16:50,197 Node[0] Epoch[8] Batch [350] Speed: 610.76 samples/sec Train-accuracy=0.817656
2016-05-02 16:16:58,806 Node[0] Epoch[8] Resetting Data Iterator
2016-05-02 16:16:58,806 Node[0] Epoch[8] Time cost=82.075
2016-05-02 16:16:58,976 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-02 16:17:01,033 Node[0] Epoch[8] Validation-accuracy=0.779866
2016-05-02 16:17:11,536 Node[0] Epoch[9] Batch [50] Speed: 612.51 samples/sec Train-accuracy=0.814688
2016-05-02 16:17:22,011 Node[0] Epoch[9] Batch [100] Speed: 611.03 samples/sec Train-accuracy=0.820000
2016-05-02 16:17:32,415 Node[0] Epoch[9] Batch [150] Speed: 615.12 samples/sec Train-accuracy=0.830781
2016-05-02 16:17:42,847 Node[0] Epoch[9] Batch [200] Speed: 613.54 samples/sec Train-accuracy=0.821875
2016-05-02 16:17:53,360 Node[0] Epoch[9] Batch [250] Speed: 608.76 samples/sec Train-accuracy=0.820937
2016-05-02 16:18:03,836 Node[0] Epoch[9] Batch [300] Speed: 610.99 samples/sec Train-accuracy=0.822031
2016-05-02 16:18:14,328 Node[0] Epoch[9] Batch [350] Speed: 609.96 samples/sec Train-accuracy=0.830469
2016-05-02 16:18:22,924 Node[0] Epoch[9] Resetting Data Iterator
2016-05-02 16:18:22,925 Node[0] Epoch[9] Time cost=81.892
2016-05-02 16:18:23,094 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-02 16:18:25,010 Node[0] Epoch[9] Validation-accuracy=0.780449
2016-05-02 16:18:35,499 Node[0] Epoch[10] Batch [50] Speed: 613.30 samples/sec Train-accuracy=0.823281
2016-05-02 16:18:45,874 Node[0] Epoch[10] Batch [100] Speed: 616.91 samples/sec Train-accuracy=0.828125
2016-05-02 16:18:56,306 Node[0] Epoch[10] Batch [150] Speed: 613.50 samples/sec Train-accuracy=0.840156
2016-05-02 16:19:06,715 Node[0] Epoch[10] Batch [200] Speed: 614.89 samples/sec Train-accuracy=0.827969
2016-05-02 16:19:17,139 Node[0] Epoch[10] Batch [250] Speed: 613.97 samples/sec Train-accuracy=0.837031
2016-05-02 16:19:27,606 Node[0] Epoch[10] Batch [300] Speed: 611.45 samples/sec Train-accuracy=0.843125
2016-05-02 16:19:38,080 Node[0] Epoch[10] Batch [350] Speed: 611.08 samples/sec Train-accuracy=0.832500
2016-05-02 16:19:46,475 Node[0] Epoch[10] Resetting Data Iterator
2016-05-02 16:19:46,475 Node[0] Epoch[10] Time cost=81.466
2016-05-02 16:19:46,642 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-02 16:19:48,582 Node[0] Epoch[10] Validation-accuracy=0.819311
2016-05-02 16:19:59,048 Node[0] Epoch[11] Batch [50] Speed: 614.76 samples/sec Train-accuracy=0.840781
2016-05-02 16:20:09,492 Node[0] Epoch[11] Batch [100] Speed: 612.78 samples/sec Train-accuracy=0.845938
2016-05-02 16:20:19,930 Node[0] Epoch[11] Batch [150] Speed: 613.21 samples/sec Train-accuracy=0.852500
2016-05-02 16:20:30,348 Node[0] Epoch[11] Batch [200] Speed: 614.34 samples/sec Train-accuracy=0.841719
2016-05-02 16:20:40,819 Node[0] Epoch[11] Batch [250] Speed: 611.21 samples/sec Train-accuracy=0.847031
2016-05-02 16:20:51,331 Node[0] Epoch[11] Batch [300] Speed: 608.82 samples/sec Train-accuracy=0.851250
2016-05-02 16:21:01,834 Node[0] Epoch[11] Batch [350] Speed: 609.41 samples/sec Train-accuracy=0.847656
2016-05-02 16:21:10,361 Node[0] Epoch[11] Resetting Data Iterator
2016-05-02 16:21:10,361 Node[0] Epoch[11] Time cost=81.779
2016-05-02 16:21:10,525 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-02 16:21:12,424 Node[0] Epoch[11] Validation-accuracy=0.813401
2016-05-02 16:21:22,906 Node[0] Epoch[12] Batch [50] Speed: 613.77 samples/sec Train-accuracy=0.842500
2016-05-02 16:21:33,409 Node[0] Epoch[12] Batch [100] Speed: 609.36 samples/sec Train-accuracy=0.853750
2016-05-02 16:21:43,846 Node[0] Epoch[12] Batch [150] Speed: 613.25 samples/sec Train-accuracy=0.856563
2016-05-02 16:21:54,234 Node[0] Epoch[12] Batch [200] Speed: 616.13 samples/sec Train-accuracy=0.851875
2016-05-02 16:22:04,674 Node[0] Epoch[12] Batch [250] Speed: 612.99 samples/sec Train-accuracy=0.852031
2016-05-02 16:22:15,064 Node[0] Epoch[12] Batch [300] Speed: 615.99 samples/sec Train-accuracy=0.858125
2016-05-02 16:22:25,561 Node[0] Epoch[12] Batch [350] Speed: 609.74 samples/sec Train-accuracy=0.852812
2016-05-02 16:22:34,171 Node[0] Epoch[12] Resetting Data Iterator
2016-05-02 16:22:34,171 Node[0] Epoch[12] Time cost=81.747
2016-05-02 16:22:34,341 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-02 16:22:36,291 Node[0] Epoch[12] Validation-accuracy=0.821314
2016-05-02 16:22:46,747 Node[0] Epoch[13] Batch [50] Speed: 615.41 samples/sec Train-accuracy=0.858281
2016-05-02 16:22:57,148 Node[0] Epoch[13] Batch [100] Speed: 615.36 samples/sec Train-accuracy=0.858281
2016-05-02 16:23:07,569 Node[0] Epoch[13] Batch [150] Speed: 614.10 samples/sec Train-accuracy=0.863594
2016-05-02 16:23:17,980 Node[0] Epoch[13] Batch [200] Speed: 614.78 samples/sec Train-accuracy=0.855156
2016-05-02 16:23:28,476 Node[0] Epoch[13] Batch [250] Speed: 609.75 samples/sec Train-accuracy=0.859844
2016-05-02 16:23:38,971 Node[0] Epoch[13] Batch [300] Speed: 609.85 samples/sec Train-accuracy=0.861250
2016-05-02 16:23:49,499 Node[0] Epoch[13] Batch [350] Speed: 607.90 samples/sec Train-accuracy=0.860469
2016-05-02 16:23:57,885 Node[0] Epoch[13] Resetting Data Iterator
2016-05-02 16:23:57,886 Node[0] Epoch[13] Time cost=81.594
2016-05-02 16:23:58,053 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-02 16:23:59,941 Node[0] Epoch[13] Validation-accuracy=0.824319
2016-05-02 16:24:10,360 Node[0] Epoch[14] Batch [50] Speed: 617.47 samples/sec Train-accuracy=0.860938
2016-05-02 16:24:20,845 Node[0] Epoch[14] Batch [100] Speed: 610.45 samples/sec Train-accuracy=0.862812
2016-05-02 16:24:31,253 Node[0] Epoch[14] Batch [150] Speed: 614.91 samples/sec Train-accuracy=0.874219
2016-05-02 16:24:41,663 Node[0] Epoch[14] Batch [200] Speed: 614.77 samples/sec Train-accuracy=0.863594
2016-05-02 16:24:52,069 Node[0] Epoch[14] Batch [250] Speed: 615.10 samples/sec Train-accuracy=0.865469
2016-05-02 16:25:02,490 Node[0] Epoch[14] Batch [300] Speed: 614.17 samples/sec Train-accuracy=0.866250
2016-05-02 16:25:12,920 Node[0] Epoch[14] Batch [350] Speed: 613.61 samples/sec Train-accuracy=0.869062
2016-05-02 16:25:21,534 Node[0] Epoch[14] Resetting Data Iterator
2016-05-02 16:25:21,534 Node[0] Epoch[14] Time cost=81.592
2016-05-02 16:25:21,703 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-02 16:25:23,634 Node[0] Epoch[14] Validation-accuracy=0.840645
2016-05-02 16:26:04,552 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-02 16:26:04,892 Node[0] Start training with [gpu(0)]
2016-05-02 16:26:26,041 Node[0] Epoch[0] Batch [50] Speed: 641.47 samples/sec Train-accuracy=0.112969
2016-05-02 16:26:36,184 Node[0] Epoch[0] Batch [100] Speed: 630.98 samples/sec Train-accuracy=0.188750
2016-05-02 16:26:46,340 Node[0] Epoch[0] Batch [150] Speed: 630.20 samples/sec Train-accuracy=0.252812
2016-05-02 16:26:56,644 Node[0] Epoch[0] Batch [200] Speed: 621.09 samples/sec Train-accuracy=0.259062
2016-05-02 16:27:07,666 Node[0] Epoch[0] Batch [250] Speed: 580.70 samples/sec Train-accuracy=0.310469
2016-05-02 16:27:18,711 Node[0] Epoch[0] Batch [300] Speed: 579.46 samples/sec Train-accuracy=0.319063
2016-05-02 16:27:29,730 Node[0] Epoch[0] Batch [350] Speed: 580.79 samples/sec Train-accuracy=0.338125
2016-05-02 16:27:38,469 Node[0] Update[391]: Change learning rate to 1.00000e-02
2016-05-02 16:27:38,686 Node[0] Epoch[0] Resetting Data Iterator
2016-05-02 16:27:38,686 Node[0] Epoch[0] Time cost=82.887
2016-05-02 16:27:38,856 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-02 16:27:41,033 Node[0] Epoch[0] Validation-accuracy=0.331092
2016-05-02 16:27:51,975 Node[0] Epoch[1] Batch [50] Speed: 587.91 samples/sec Train-accuracy=0.386875
2016-05-02 16:32:42,991 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-02 16:32:43,353 Node[0] Start training with [gpu(0)]
2016-05-02 16:33:04,417 Node[0] Epoch[0] Batch [50] Speed: 648.23 samples/sec Train-accuracy=0.149219
2016-05-02 16:33:14,561 Node[0] Epoch[0] Batch [100] Speed: 630.96 samples/sec Train-accuracy=0.256719
2016-05-02 16:33:24,752 Node[0] Epoch[0] Batch [150] Speed: 628.02 samples/sec Train-accuracy=0.328437
2016-05-02 16:33:34,934 Node[0] Epoch[0] Batch [200] Speed: 628.54 samples/sec Train-accuracy=0.363438
2016-05-02 16:33:45,067 Node[0] Epoch[0] Batch [250] Speed: 631.64 samples/sec Train-accuracy=0.403281
2016-05-02 16:33:55,192 Node[0] Epoch[0] Batch [300] Speed: 632.13 samples/sec Train-accuracy=0.424687
2016-05-02 16:34:05,549 Node[0] Epoch[0] Batch [350] Speed: 617.95 samples/sec Train-accuracy=0.454062
2016-05-02 16:34:14,358 Node[0] Epoch[0] Resetting Data Iterator
2016-05-02 16:34:14,358 Node[0] Epoch[0] Time cost=80.078
2016-05-02 16:34:14,528 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-02 16:34:16,675 Node[0] Epoch[0] Validation-accuracy=0.459553
2016-05-02 16:34:27,414 Node[0] Epoch[1] Batch [50] Speed: 599.13 samples/sec Train-accuracy=0.481406
2016-05-02 16:34:38,066 Node[0] Epoch[1] Batch [100] Speed: 600.83 samples/sec Train-accuracy=0.510000
2016-05-02 16:34:48,702 Node[0] Epoch[1] Batch [150] Speed: 601.73 samples/sec Train-accuracy=0.537031
2016-05-02 16:34:59,395 Node[0] Epoch[1] Batch [200] Speed: 598.55 samples/sec Train-accuracy=0.540625
2016-05-02 16:35:09,925 Node[0] Epoch[1] Batch [250] Speed: 607.82 samples/sec Train-accuracy=0.573438
2016-05-02 16:35:20,447 Node[0] Epoch[1] Batch [300] Speed: 608.27 samples/sec Train-accuracy=0.583906
2016-05-02 16:35:30,968 Node[0] Epoch[1] Batch [350] Speed: 608.33 samples/sec Train-accuracy=0.580937
2016-05-02 16:35:39,671 Node[0] Epoch[1] Resetting Data Iterator
2016-05-02 16:35:39,672 Node[0] Epoch[1] Time cost=82.996
2016-05-02 16:35:39,840 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-02 16:35:41,773 Node[0] Epoch[1] Validation-accuracy=0.575020
2016-05-02 16:35:52,514 Node[0] Epoch[2] Batch [50] Speed: 599.00 samples/sec Train-accuracy=0.608125
2016-05-02 16:36:03,183 Node[0] Epoch[2] Batch [100] Speed: 599.83 samples/sec Train-accuracy=0.626406
2016-05-02 16:36:13,752 Node[0] Epoch[2] Batch [150] Speed: 605.57 samples/sec Train-accuracy=0.645000
2016-05-02 16:36:24,263 Node[0] Epoch[2] Batch [200] Speed: 608.93 samples/sec Train-accuracy=0.647500
2016-05-02 16:36:34,802 Node[0] Epoch[2] Batch [250] Speed: 607.28 samples/sec Train-accuracy=0.656094
2016-05-02 16:36:45,433 Node[0] Epoch[2] Batch [300] Speed: 602.04 samples/sec Train-accuracy=0.661250
2016-05-02 16:36:56,046 Node[0] Epoch[2] Batch [350] Speed: 603.00 samples/sec Train-accuracy=0.677188
2016-05-02 16:37:04,552 Node[0] Epoch[2] Resetting Data Iterator
2016-05-02 16:37:04,552 Node[0] Epoch[2] Time cost=82.779
2016-05-02 16:37:04,718 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-02 16:37:06,654 Node[0] Epoch[2] Validation-accuracy=0.625100
2016-05-02 16:37:17,219 Node[0] Epoch[3] Batch [50] Speed: 608.98 samples/sec Train-accuracy=0.681719
2016-05-02 16:37:27,784 Node[0] Epoch[3] Batch [100] Speed: 605.79 samples/sec Train-accuracy=0.700000
2016-05-02 16:37:38,306 Node[0] Epoch[3] Batch [150] Speed: 608.32 samples/sec Train-accuracy=0.713906
2016-05-02 16:37:48,790 Node[0] Epoch[3] Batch [200] Speed: 610.47 samples/sec Train-accuracy=0.710781
2016-05-02 16:37:59,312 Node[0] Epoch[3] Batch [250] Speed: 608.25 samples/sec Train-accuracy=0.716406
2016-05-02 16:38:09,864 Node[0] Epoch[3] Batch [300] Speed: 606.51 samples/sec Train-accuracy=0.724531
2016-05-02 16:38:20,377 Node[0] Epoch[3] Batch [350] Speed: 608.79 samples/sec Train-accuracy=0.736719
2016-05-02 16:38:28,974 Node[0] Epoch[3] Resetting Data Iterator
2016-05-02 16:38:28,975 Node[0] Epoch[3] Time cost=82.321
2016-05-02 16:38:29,139 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-02 16:38:31,048 Node[0] Epoch[3] Validation-accuracy=0.670172
2016-05-02 16:38:41,658 Node[0] Epoch[4] Batch [50] Speed: 606.43 samples/sec Train-accuracy=0.745313
2016-05-02 16:38:52,183 Node[0] Epoch[4] Batch [100] Speed: 608.09 samples/sec Train-accuracy=0.747969
2016-05-02 16:39:02,710 Node[0] Epoch[4] Batch [150] Speed: 607.95 samples/sec Train-accuracy=0.757188
2016-05-02 16:39:13,200 Node[0] Epoch[4] Batch [200] Speed: 610.13 samples/sec Train-accuracy=0.753594
2016-05-02 16:39:23,706 Node[0] Epoch[4] Batch [250] Speed: 609.20 samples/sec Train-accuracy=0.759375
2016-05-02 16:39:34,222 Node[0] Epoch[4] Batch [300] Speed: 608.63 samples/sec Train-accuracy=0.762500
2016-05-02 16:39:44,722 Node[0] Epoch[4] Batch [350] Speed: 609.53 samples/sec Train-accuracy=0.763437
2016-05-02 16:39:53,286 Node[0] Epoch[4] Resetting Data Iterator
2016-05-02 16:39:53,286 Node[0] Epoch[4] Time cost=82.238
2016-05-02 16:39:53,452 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-02 16:39:55,380 Node[0] Epoch[4] Validation-accuracy=0.755809
2016-05-02 16:40:05,846 Node[0] Epoch[5] Batch [50] Speed: 614.71 samples/sec Train-accuracy=0.767031
2016-05-02 16:40:16,348 Node[0] Epoch[5] Batch [100] Speed: 609.44 samples/sec Train-accuracy=0.770625
2016-05-02 16:40:26,827 Node[0] Epoch[5] Batch [150] Speed: 610.76 samples/sec Train-accuracy=0.790937
2016-05-02 16:40:37,336 Node[0] Epoch[5] Batch [200] Speed: 609.03 samples/sec Train-accuracy=0.776719
2016-05-02 16:40:47,793 Node[0] Epoch[5] Batch [250] Speed: 612.04 samples/sec Train-accuracy=0.781875
2016-05-02 16:40:58,165 Node[0] Epoch[5] Batch [300] Speed: 617.06 samples/sec Train-accuracy=0.785156
2016-05-02 16:41:08,979 Node[0] Epoch[5] Batch [350] Speed: 591.83 samples/sec Train-accuracy=0.787500
2016-05-02 16:41:17,474 Node[0] Epoch[5] Resetting Data Iterator
2016-05-02 16:41:17,474 Node[0] Epoch[5] Time cost=82.094
2016-05-02 16:41:17,638 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-02 16:41:19,584 Node[0] Epoch[5] Validation-accuracy=0.759716
2016-05-02 16:41:30,097 Node[0] Epoch[6] Batch [50] Speed: 612.04 samples/sec Train-accuracy=0.785625
2016-05-02 16:41:40,616 Node[0] Epoch[6] Batch [100] Speed: 608.44 samples/sec Train-accuracy=0.792188
2016-05-02 16:41:51,004 Node[0] Epoch[6] Batch [150] Speed: 616.09 samples/sec Train-accuracy=0.805781
2016-05-02 16:42:01,424 Node[0] Epoch[6] Batch [200] Speed: 614.25 samples/sec Train-accuracy=0.797344
2016-05-02 16:42:11,812 Node[0] Epoch[6] Batch [250] Speed: 616.10 samples/sec Train-accuracy=0.797969
2016-05-02 16:42:22,231 Node[0] Epoch[6] Batch [300] Speed: 614.27 samples/sec Train-accuracy=0.808906
2016-05-02 16:42:32,633 Node[0] Epoch[6] Batch [350] Speed: 615.28 samples/sec Train-accuracy=0.812656
2016-05-02 16:42:41,145 Node[0] Epoch[6] Resetting Data Iterator
2016-05-02 16:42:41,145 Node[0] Epoch[6] Time cost=81.561
2016-05-02 16:42:41,306 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-02 16:42:43,221 Node[0] Epoch[6] Validation-accuracy=0.758614
2016-05-02 16:42:53,718 Node[0] Epoch[7] Batch [50] Speed: 612.90 samples/sec Train-accuracy=0.811562
2016-05-02 16:43:04,154 Node[0] Epoch[7] Batch [100] Speed: 613.29 samples/sec Train-accuracy=0.813750
2016-05-02 16:43:14,506 Node[0] Epoch[7] Batch [150] Speed: 618.21 samples/sec Train-accuracy=0.823906
2016-05-02 16:43:24,948 Node[0] Epoch[7] Batch [200] Speed: 612.96 samples/sec Train-accuracy=0.811406
2016-05-02 16:43:35,357 Node[0] Epoch[7] Batch [250] Speed: 614.89 samples/sec Train-accuracy=0.817344
2016-05-02 16:43:45,804 Node[0] Epoch[7] Batch [300] Speed: 612.60 samples/sec Train-accuracy=0.819063
2016-05-02 16:43:56,216 Node[0] Epoch[7] Batch [350] Speed: 614.67 samples/sec Train-accuracy=0.820000
2016-05-02 16:44:04,520 Node[0] Epoch[7] Resetting Data Iterator
2016-05-02 16:44:04,520 Node[0] Epoch[7] Time cost=81.299
2016-05-02 16:44:04,680 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-02 16:44:06,583 Node[0] Epoch[7] Validation-accuracy=0.781550
2016-05-02 16:44:16,989 Node[0] Epoch[8] Batch [50] Speed: 618.24 samples/sec Train-accuracy=0.828594
2016-05-02 16:44:27,402 Node[0] Epoch[8] Batch [100] Speed: 614.64 samples/sec Train-accuracy=0.820000
2016-05-02 16:44:37,806 Node[0] Epoch[8] Batch [150] Speed: 615.19 samples/sec Train-accuracy=0.837969
2016-05-02 16:44:48,278 Node[0] Epoch[8] Batch [200] Speed: 611.16 samples/sec Train-accuracy=0.826250
2016-05-02 16:44:58,725 Node[0] Epoch[8] Batch [250] Speed: 612.61 samples/sec Train-accuracy=0.832969
2016-05-02 16:45:09,098 Node[0] Epoch[8] Batch [300] Speed: 617.05 samples/sec Train-accuracy=0.839688
2016-05-02 16:45:19,511 Node[0] Epoch[8] Batch [350] Speed: 614.61 samples/sec Train-accuracy=0.830156
2016-05-02 16:45:28,052 Node[0] Epoch[8] Resetting Data Iterator
2016-05-02 16:45:28,052 Node[0] Epoch[8] Time cost=81.469
2016-05-02 16:45:28,214 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-02 16:45:30,347 Node[0] Epoch[8] Validation-accuracy=0.792128
2016-05-02 16:45:40,775 Node[0] Epoch[9] Batch [50] Speed: 616.90 samples/sec Train-accuracy=0.827969
2016-05-02 16:45:51,219 Node[0] Epoch[9] Batch [100] Speed: 612.84 samples/sec Train-accuracy=0.839844
2016-05-02 16:46:01,686 Node[0] Epoch[9] Batch [150] Speed: 611.47 samples/sec Train-accuracy=0.844375
2016-05-02 16:46:12,074 Node[0] Epoch[9] Batch [200] Speed: 616.10 samples/sec Train-accuracy=0.837656
2016-05-02 16:46:22,468 Node[0] Epoch[9] Batch [250] Speed: 615.74 samples/sec Train-accuracy=0.836406
2016-05-02 16:46:32,894 Node[0] Epoch[9] Batch [300] Speed: 613.89 samples/sec Train-accuracy=0.846094
2016-05-02 16:46:43,302 Node[0] Epoch[9] Batch [350] Speed: 614.94 samples/sec Train-accuracy=0.836094
2016-05-02 16:46:51,850 Node[0] Epoch[9] Resetting Data Iterator
2016-05-02 16:46:51,850 Node[0] Epoch[9] Time cost=81.503
2016-05-02 16:46:52,013 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-02 16:46:53,906 Node[0] Epoch[9] Validation-accuracy=0.780349
2016-05-02 16:47:04,343 Node[0] Epoch[10] Batch [50] Speed: 616.40 samples/sec Train-accuracy=0.842344
2016-05-02 16:47:14,722 Node[0] Epoch[10] Batch [100] Speed: 616.66 samples/sec Train-accuracy=0.844688
2016-05-02 16:47:25,053 Node[0] Epoch[10] Batch [150] Speed: 619.52 samples/sec Train-accuracy=0.856563
2016-05-02 16:47:35,435 Node[0] Epoch[10] Batch [200] Speed: 616.47 samples/sec Train-accuracy=0.842969
2016-05-02 16:47:45,848 Node[0] Epoch[10] Batch [250] Speed: 614.60 samples/sec Train-accuracy=0.849219
2016-05-02 16:47:56,299 Node[0] Epoch[10] Batch [300] Speed: 612.43 samples/sec Train-accuracy=0.849531
2016-05-02 16:48:06,686 Node[0] Epoch[10] Batch [350] Speed: 616.18 samples/sec Train-accuracy=0.839844
2016-05-02 16:48:14,988 Node[0] Epoch[10] Resetting Data Iterator
2016-05-02 16:48:14,988 Node[0] Epoch[10] Time cost=81.082
2016-05-02 16:48:15,157 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-02 16:48:17,065 Node[0] Epoch[10] Validation-accuracy=0.820012
2016-05-02 16:48:27,484 Node[0] Epoch[11] Batch [50] Speed: 617.45 samples/sec Train-accuracy=0.850625
2016-05-02 16:48:37,841 Node[0] Epoch[11] Batch [100] Speed: 617.95 samples/sec Train-accuracy=0.852344
2016-05-02 16:48:48,200 Node[0] Epoch[11] Batch [150] Speed: 617.84 samples/sec Train-accuracy=0.857344
2016-05-02 16:48:58,595 Node[0] Epoch[11] Batch [200] Speed: 615.72 samples/sec Train-accuracy=0.856563
2016-05-02 16:49:08,993 Node[0] Epoch[11] Batch [250] Speed: 615.51 samples/sec Train-accuracy=0.853281
2016-05-02 16:49:19,339 Node[0] Epoch[11] Batch [300] Speed: 618.59 samples/sec Train-accuracy=0.857344
2016-05-02 16:49:29,690 Node[0] Epoch[11] Batch [350] Speed: 618.33 samples/sec Train-accuracy=0.856719
2016-05-02 16:49:38,235 Node[0] Epoch[11] Resetting Data Iterator
2016-05-02 16:49:38,235 Node[0] Epoch[11] Time cost=81.170
2016-05-02 16:49:38,401 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-02 16:49:40,290 Node[0] Epoch[11] Validation-accuracy=0.820513
2016-05-02 16:49:50,686 Node[0] Epoch[12] Batch [50] Speed: 618.88 samples/sec Train-accuracy=0.860625
2016-05-02 16:50:01,034 Node[0] Epoch[12] Batch [100] Speed: 618.49 samples/sec Train-accuracy=0.860469
2016-05-02 16:50:11,418 Node[0] Epoch[12] Batch [150] Speed: 616.31 samples/sec Train-accuracy=0.865938
2016-05-02 16:50:21,766 Node[0] Epoch[12] Batch [200] Speed: 618.48 samples/sec Train-accuracy=0.858281
2016-05-02 16:50:32,168 Node[0] Epoch[12] Batch [250] Speed: 615.31 samples/sec Train-accuracy=0.860000
2016-05-02 16:50:42,570 Node[0] Epoch[12] Batch [300] Speed: 615.27 samples/sec Train-accuracy=0.863906
2016-05-02 16:50:52,991 Node[0] Epoch[12] Batch [350] Speed: 614.20 samples/sec Train-accuracy=0.860000
2016-05-02 16:51:01,505 Node[0] Epoch[12] Resetting Data Iterator
2016-05-02 16:51:01,505 Node[0] Epoch[12] Time cost=81.214
2016-05-02 16:51:01,670 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-02 16:51:03,556 Node[0] Epoch[12] Validation-accuracy=0.815805
2016-05-02 16:51:13,937 Node[0] Epoch[13] Batch [50] Speed: 619.77 samples/sec Train-accuracy=0.865156
2016-05-02 16:51:24,330 Node[0] Epoch[13] Batch [100] Speed: 615.80 samples/sec Train-accuracy=0.871875
2016-05-02 16:51:34,688 Node[0] Epoch[13] Batch [150] Speed: 617.88 samples/sec Train-accuracy=0.873281
2016-05-02 16:51:45,024 Node[0] Epoch[13] Batch [200] Speed: 619.23 samples/sec Train-accuracy=0.864062
2016-05-02 16:51:55,395 Node[0] Epoch[13] Batch [250] Speed: 617.12 samples/sec Train-accuracy=0.870625
2016-05-02 16:52:05,776 Node[0] Epoch[13] Batch [300] Speed: 616.50 samples/sec Train-accuracy=0.867344
2016-05-02 16:52:16,152 Node[0] Epoch[13] Batch [350] Speed: 616.86 samples/sec Train-accuracy=0.865625
2016-05-02 16:52:24,446 Node[0] Epoch[13] Resetting Data Iterator
2016-05-02 16:52:24,446 Node[0] Epoch[13] Time cost=80.890
2016-05-02 16:52:24,610 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-02 16:52:26,516 Node[0] Epoch[13] Validation-accuracy=0.821514
2016-05-02 16:52:36,823 Node[0] Epoch[14] Batch [50] Speed: 624.17 samples/sec Train-accuracy=0.869687
2016-05-02 16:52:47,194 Node[0] Epoch[14] Batch [100] Speed: 617.16 samples/sec Train-accuracy=0.872812
2016-05-02 16:52:57,569 Node[0] Epoch[14] Batch [150] Speed: 616.83 samples/sec Train-accuracy=0.878125
2016-05-02 16:53:07,912 Node[0] Epoch[14] Batch [200] Speed: 618.80 samples/sec Train-accuracy=0.869062
2016-05-02 16:53:18,263 Node[0] Epoch[14] Batch [250] Speed: 618.35 samples/sec Train-accuracy=0.872188
2016-05-02 16:53:28,612 Node[0] Epoch[14] Batch [300] Speed: 618.44 samples/sec Train-accuracy=0.867500
2016-05-02 16:53:38,985 Node[0] Epoch[14] Batch [350] Speed: 616.96 samples/sec Train-accuracy=0.867188
2016-05-02 16:53:47,489 Node[0] Epoch[14] Resetting Data Iterator
2016-05-02 16:53:47,490 Node[0] Epoch[14] Time cost=80.973
2016-05-02 16:53:47,653 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-02 16:53:49,550 Node[0] Epoch[14] Validation-accuracy=0.832732
2016-05-02 16:53:59,961 Node[0] Epoch[15] Batch [50] Speed: 618.07 samples/sec Train-accuracy=0.874531
2016-05-02 16:54:10,365 Node[0] Epoch[15] Batch [100] Speed: 615.17 samples/sec Train-accuracy=0.878125
2016-05-02 16:54:20,690 Node[0] Epoch[15] Batch [150] Speed: 619.88 samples/sec Train-accuracy=0.879375
2016-05-02 16:54:31,065 Node[0] Epoch[15] Batch [200] Speed: 616.86 samples/sec Train-accuracy=0.876875
2016-05-02 16:54:41,413 Node[0] Epoch[15] Batch [250] Speed: 618.48 samples/sec Train-accuracy=0.882031
2016-05-02 16:54:51,791 Node[0] Epoch[15] Batch [300] Speed: 616.72 samples/sec Train-accuracy=0.881406
2016-05-02 16:55:02,116 Node[0] Epoch[15] Batch [350] Speed: 619.86 samples/sec Train-accuracy=0.879687
2016-05-02 16:55:10,425 Node[0] Epoch[15] Resetting Data Iterator
2016-05-02 16:55:10,426 Node[0] Epoch[15] Time cost=80.875
2016-05-02 16:55:10,584 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-02 16:55:12,477 Node[0] Epoch[15] Validation-accuracy=0.840345
2016-05-02 16:55:22,875 Node[0] Epoch[16] Batch [50] Speed: 618.84 samples/sec Train-accuracy=0.878594
2016-05-02 16:55:33,214 Node[0] Epoch[16] Batch [100] Speed: 619.01 samples/sec Train-accuracy=0.884531
2016-05-02 16:55:43,594 Node[0] Epoch[16] Batch [150] Speed: 616.60 samples/sec Train-accuracy=0.887969
2016-05-02 16:55:53,962 Node[0] Epoch[16] Batch [200] Speed: 617.32 samples/sec Train-accuracy=0.882344
2016-05-02 16:56:04,392 Node[0] Epoch[16] Batch [250] Speed: 613.62 samples/sec Train-accuracy=0.880625
2016-05-02 16:56:14,799 Node[0] Epoch[16] Batch [300] Speed: 614.99 samples/sec Train-accuracy=0.885625
2016-05-02 16:56:25,157 Node[0] Epoch[16] Batch [350] Speed: 617.85 samples/sec Train-accuracy=0.880313
2016-05-02 16:56:33,645 Node[0] Epoch[16] Resetting Data Iterator
2016-05-02 16:56:33,646 Node[0] Epoch[16] Time cost=81.169
2016-05-02 16:56:33,812 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-02 16:56:35,935 Node[0] Epoch[16] Validation-accuracy=0.836135
2016-05-02 16:56:46,280 Node[0] Epoch[17] Batch [50] Speed: 621.93 samples/sec Train-accuracy=0.880313
2016-05-02 16:56:56,625 Node[0] Epoch[17] Batch [100] Speed: 618.64 samples/sec Train-accuracy=0.882656
2016-05-02 16:57:06,910 Node[0] Epoch[17] Batch [150] Speed: 622.33 samples/sec Train-accuracy=0.885312
2016-05-02 16:57:17,216 Node[0] Epoch[17] Batch [200] Speed: 621.01 samples/sec Train-accuracy=0.886250
2016-05-02 16:57:27,599 Node[0] Epoch[17] Batch [250] Speed: 616.39 samples/sec Train-accuracy=0.884219
2016-05-02 16:57:37,972 Node[0] Epoch[17] Batch [300] Speed: 617.00 samples/sec Train-accuracy=0.888437
2016-05-02 16:57:48,343 Node[0] Epoch[17] Batch [350] Speed: 617.11 samples/sec Train-accuracy=0.885938
2016-05-02 16:57:56,801 Node[0] Epoch[17] Resetting Data Iterator
2016-05-02 16:57:56,801 Node[0] Epoch[17] Time cost=80.867
2016-05-02 16:57:56,963 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-02 16:57:58,891 Node[0] Epoch[17] Validation-accuracy=0.842047
2016-05-02 16:58:09,211 Node[0] Epoch[18] Batch [50] Speed: 623.40 samples/sec Train-accuracy=0.884844
2016-05-02 16:58:19,563 Node[0] Epoch[18] Batch [100] Speed: 618.27 samples/sec Train-accuracy=0.888281
2016-05-02 16:58:29,909 Node[0] Epoch[18] Batch [150] Speed: 618.61 samples/sec Train-accuracy=0.892344
2016-05-02 16:58:40,280 Node[0] Epoch[18] Batch [200] Speed: 617.13 samples/sec Train-accuracy=0.885156
2016-05-02 16:58:50,660 Node[0] Epoch[18] Batch [250] Speed: 616.60 samples/sec Train-accuracy=0.893125
2016-05-02 16:59:01,015 Node[0] Epoch[18] Batch [300] Speed: 618.10 samples/sec Train-accuracy=0.895000
2016-05-02 16:59:11,361 Node[0] Epoch[18] Batch [350] Speed: 618.58 samples/sec Train-accuracy=0.889219
2016-05-02 16:59:19,657 Node[0] Epoch[18] Resetting Data Iterator
2016-05-02 16:59:19,657 Node[0] Epoch[18] Time cost=80.766
2016-05-02 16:59:19,821 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-02 16:59:21,695 Node[0] Epoch[18] Validation-accuracy=0.842248
2016-05-02 16:59:32,106 Node[0] Epoch[19] Batch [50] Speed: 617.97 samples/sec Train-accuracy=0.889375
2016-05-02 16:59:42,510 Node[0] Epoch[19] Batch [100] Speed: 615.14 samples/sec Train-accuracy=0.895781
2016-05-02 16:59:52,883 Node[0] Epoch[19] Batch [150] Speed: 617.00 samples/sec Train-accuracy=0.883437
2016-05-02 17:00:03,266 Node[0] Epoch[19] Batch [200] Speed: 616.44 samples/sec Train-accuracy=0.877188
2016-05-02 17:00:13,638 Node[0] Epoch[19] Batch [250] Speed: 617.08 samples/sec Train-accuracy=0.889375
2016-05-02 17:00:24,021 Node[0] Epoch[19] Batch [300] Speed: 616.39 samples/sec Train-accuracy=0.897500
2016-05-02 17:00:34,410 Node[0] Epoch[19] Batch [350] Speed: 616.03 samples/sec Train-accuracy=0.892031
2016-05-02 17:00:42,911 Node[0] Epoch[19] Resetting Data Iterator
2016-05-02 17:00:42,911 Node[0] Epoch[19] Time cost=81.216
2016-05-02 17:00:43,075 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-02 17:00:44,979 Node[0] Epoch[19] Validation-accuracy=0.853165
2016-05-02 17:00:55,328 Node[0] Epoch[20] Batch [50] Speed: 621.71 samples/sec Train-accuracy=0.889531
2016-05-02 17:01:05,722 Node[0] Epoch[20] Batch [100] Speed: 615.73 samples/sec Train-accuracy=0.895312
2016-05-02 17:01:16,086 Node[0] Epoch[20] Batch [150] Speed: 617.57 samples/sec Train-accuracy=0.897188
2016-05-02 17:01:26,468 Node[0] Epoch[20] Batch [200] Speed: 616.42 samples/sec Train-accuracy=0.895781
2016-05-02 17:01:36,845 Node[0] Epoch[20] Batch [250] Speed: 616.79 samples/sec Train-accuracy=0.892344
2016-05-02 17:01:47,223 Node[0] Epoch[20] Batch [300] Speed: 616.72 samples/sec Train-accuracy=0.901875
2016-05-02 17:01:57,585 Node[0] Epoch[20] Batch [350] Speed: 617.65 samples/sec Train-accuracy=0.896094
2016-05-02 17:02:06,054 Node[0] Epoch[20] Resetting Data Iterator
2016-05-02 17:02:06,054 Node[0] Epoch[20] Time cost=81.075
2016-05-02 17:02:06,216 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-02 17:02:08,146 Node[0] Epoch[20] Validation-accuracy=0.834736
2016-05-02 17:02:18,594 Node[0] Epoch[21] Batch [50] Speed: 615.85 samples/sec Train-accuracy=0.889375
2016-05-02 17:02:28,963 Node[0] Epoch[21] Batch [100] Speed: 617.25 samples/sec Train-accuracy=0.897188
2016-05-02 17:02:39,340 Node[0] Epoch[21] Batch [150] Speed: 616.79 samples/sec Train-accuracy=0.899844
2016-05-02 17:02:49,695 Node[0] Epoch[21] Batch [200] Speed: 618.07 samples/sec Train-accuracy=0.888750
2016-05-02 17:03:00,044 Node[0] Epoch[21] Batch [250] Speed: 618.39 samples/sec Train-accuracy=0.902031
2016-05-02 17:03:10,401 Node[0] Epoch[21] Batch [300] Speed: 617.99 samples/sec Train-accuracy=0.900156
2016-05-02 17:03:20,774 Node[0] Epoch[21] Batch [350] Speed: 617.00 samples/sec Train-accuracy=0.895469
2016-05-02 17:03:29,057 Node[0] Epoch[21] Resetting Data Iterator
2016-05-02 17:03:29,057 Node[0] Epoch[21] Time cost=80.911
2016-05-02 17:03:29,216 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-02 17:03:31,122 Node[0] Epoch[21] Validation-accuracy=0.857071
2016-05-02 17:03:41,644 Node[0] Epoch[22] Batch [50] Speed: 611.41 samples/sec Train-accuracy=0.900469
2016-05-02 17:03:51,995 Node[0] Epoch[22] Batch [100] Speed: 618.31 samples/sec Train-accuracy=0.901875
2016-05-02 17:04:02,243 Node[0] Epoch[22] Batch [150] Speed: 624.53 samples/sec Train-accuracy=0.900312
2016-05-02 17:04:12,630 Node[0] Epoch[22] Batch [200] Speed: 616.17 samples/sec Train-accuracy=0.894531
2016-05-02 17:04:23,045 Node[0] Epoch[22] Batch [250] Speed: 614.50 samples/sec Train-accuracy=0.901875
2016-05-02 17:04:33,486 Node[0] Epoch[22] Batch [300] Speed: 613.01 samples/sec Train-accuracy=0.904687
2016-05-02 17:04:43,884 Node[0] Epoch[22] Batch [350] Speed: 615.49 samples/sec Train-accuracy=0.902969
2016-05-02 17:04:52,368 Node[0] Epoch[22] Resetting Data Iterator
2016-05-02 17:04:52,368 Node[0] Epoch[22] Time cost=81.246
2016-05-02 17:04:52,533 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-02 17:04:54,418 Node[0] Epoch[22] Validation-accuracy=0.854367
2016-05-02 17:05:04,909 Node[0] Epoch[23] Batch [50] Speed: 613.31 samples/sec Train-accuracy=0.906094
2016-05-02 17:05:15,364 Node[0] Epoch[23] Batch [100] Speed: 612.16 samples/sec Train-accuracy=0.901875
2016-05-02 17:05:25,677 Node[0] Epoch[23] Batch [150] Speed: 620.61 samples/sec Train-accuracy=0.907500
2016-05-02 17:05:36,030 Node[0] Epoch[23] Batch [200] Speed: 618.17 samples/sec Train-accuracy=0.900781
2016-05-02 17:05:46,396 Node[0] Epoch[23] Batch [250] Speed: 617.42 samples/sec Train-accuracy=0.900781
2016-05-02 17:05:56,721 Node[0] Epoch[23] Batch [300] Speed: 619.91 samples/sec Train-accuracy=0.909062
2016-05-02 17:06:07,077 Node[0] Epoch[23] Batch [350] Speed: 617.99 samples/sec Train-accuracy=0.902031
2016-05-02 17:06:15,329 Node[0] Epoch[23] Resetting Data Iterator
2016-05-02 17:06:15,329 Node[0] Epoch[23] Time cost=80.911
2016-05-02 17:06:15,488 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-02 17:06:17,375 Node[0] Epoch[23] Validation-accuracy=0.847656
2016-05-02 17:06:27,725 Node[0] Epoch[24] Batch [50] Speed: 621.68 samples/sec Train-accuracy=0.900312
2016-05-02 17:06:38,066 Node[0] Epoch[24] Batch [100] Speed: 618.94 samples/sec Train-accuracy=0.907344
2016-05-02 17:06:48,457 Node[0] Epoch[24] Batch [150] Speed: 615.89 samples/sec Train-accuracy=0.910937
2016-05-02 17:06:58,838 Node[0] Epoch[24] Batch [200] Speed: 616.54 samples/sec Train-accuracy=0.903594
2016-05-02 17:07:09,189 Node[0] Epoch[24] Batch [250] Speed: 618.34 samples/sec Train-accuracy=0.907500
2016-05-02 17:07:19,566 Node[0] Epoch[24] Batch [300] Speed: 616.74 samples/sec Train-accuracy=0.911719
2016-05-02 17:07:29,962 Node[0] Epoch[24] Batch [350] Speed: 615.64 samples/sec Train-accuracy=0.910781
2016-05-02 17:07:38,439 Node[0] Epoch[24] Resetting Data Iterator
2016-05-02 17:07:38,440 Node[0] Epoch[24] Time cost=81.064
2016-05-02 17:07:38,604 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-02 17:07:40,745 Node[0] Epoch[24] Validation-accuracy=0.853738
2016-05-02 17:07:51,106 Node[0] Epoch[25] Batch [50] Speed: 620.98 samples/sec Train-accuracy=0.905312
2016-05-02 17:08:01,535 Node[0] Epoch[25] Batch [100] Speed: 613.71 samples/sec Train-accuracy=0.907656
2016-05-02 17:08:11,905 Node[0] Epoch[25] Batch [150] Speed: 617.20 samples/sec Train-accuracy=0.909531
2016-05-02 17:08:22,308 Node[0] Epoch[25] Batch [200] Speed: 615.17 samples/sec Train-accuracy=0.903281
2016-05-02 17:08:32,676 Node[0] Epoch[25] Batch [250] Speed: 617.33 samples/sec Train-accuracy=0.903125
2016-05-02 17:08:43,029 Node[0] Epoch[25] Batch [300] Speed: 618.22 samples/sec Train-accuracy=0.909062
2016-05-02 17:08:53,395 Node[0] Epoch[25] Batch [350] Speed: 617.40 samples/sec Train-accuracy=0.912344
2016-05-02 17:09:01,920 Node[0] Epoch[25] Resetting Data Iterator
2016-05-02 17:09:01,920 Node[0] Epoch[25] Time cost=81.175
2016-05-02 17:09:02,089 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-02 17:09:03,987 Node[0] Epoch[25] Validation-accuracy=0.847356
2016-05-02 17:09:14,351 Node[0] Epoch[26] Batch [50] Speed: 620.74 samples/sec Train-accuracy=0.908906
2016-05-02 17:09:24,748 Node[0] Epoch[26] Batch [100] Speed: 615.61 samples/sec Train-accuracy=0.907031
2016-05-02 17:09:35,060 Node[0] Epoch[26] Batch [150] Speed: 620.62 samples/sec Train-accuracy=0.914062
2016-05-02 17:09:45,402 Node[0] Epoch[26] Batch [200] Speed: 618.86 samples/sec Train-accuracy=0.910781
2016-05-02 17:09:55,765 Node[0] Epoch[26] Batch [250] Speed: 617.62 samples/sec Train-accuracy=0.909844
2016-05-02 17:10:06,121 Node[0] Epoch[26] Batch [300] Speed: 618.03 samples/sec Train-accuracy=0.913750
2016-05-02 17:10:16,513 Node[0] Epoch[26] Batch [350] Speed: 615.84 samples/sec Train-accuracy=0.906094
2016-05-02 17:10:24,793 Node[0] Epoch[26] Resetting Data Iterator
2016-05-02 17:10:24,793 Node[0] Epoch[26] Time cost=80.807
2016-05-02 17:10:24,953 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-02 17:10:26,851 Node[0] Epoch[26] Validation-accuracy=0.842448
2016-05-02 17:10:37,239 Node[0] Epoch[27] Batch [50] Speed: 619.34 samples/sec Train-accuracy=0.907969
2016-05-02 17:10:47,650 Node[0] Epoch[27] Batch [100] Speed: 614.71 samples/sec Train-accuracy=0.910156
2016-05-02 17:10:58,004 Node[0] Epoch[27] Batch [150] Speed: 618.15 samples/sec Train-accuracy=0.914375
2016-05-02 17:11:08,364 Node[0] Epoch[27] Batch [200] Speed: 617.80 samples/sec Train-accuracy=0.913125
2016-05-02 17:11:18,726 Node[0] Epoch[27] Batch [250] Speed: 617.63 samples/sec Train-accuracy=0.918594
2016-05-02 17:11:29,162 Node[0] Epoch[27] Batch [300] Speed: 613.27 samples/sec Train-accuracy=0.912031
2016-05-02 17:11:39,565 Node[0] Epoch[27] Batch [350] Speed: 615.24 samples/sec Train-accuracy=0.917813
2016-05-02 17:11:48,098 Node[0] Epoch[27] Resetting Data Iterator
2016-05-02 17:11:48,098 Node[0] Epoch[27] Time cost=81.248
2016-05-02 17:11:48,265 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-02 17:11:50,169 Node[0] Epoch[27] Validation-accuracy=0.819111
2016-05-02 17:12:00,543 Node[0] Epoch[28] Batch [50] Speed: 620.15 samples/sec Train-accuracy=0.915000
2016-05-02 17:12:10,931 Node[0] Epoch[28] Batch [100] Speed: 616.12 samples/sec Train-accuracy=0.919375
2016-05-02 17:12:21,270 Node[0] Epoch[28] Batch [150] Speed: 618.97 samples/sec Train-accuracy=0.918281
2016-05-02 17:12:31,665 Node[0] Epoch[28] Batch [200] Speed: 615.72 samples/sec Train-accuracy=0.914844
2016-05-02 17:12:42,053 Node[0] Epoch[28] Batch [250] Speed: 616.14 samples/sec Train-accuracy=0.913594
2016-05-02 17:12:52,416 Node[0] Epoch[28] Batch [300] Speed: 617.56 samples/sec Train-accuracy=0.915312
2016-05-02 17:13:02,774 Node[0] Epoch[28] Batch [350] Speed: 617.90 samples/sec Train-accuracy=0.913750
2016-05-02 17:13:11,265 Node[0] Epoch[28] Resetting Data Iterator
2016-05-02 17:13:11,266 Node[0] Epoch[28] Time cost=81.096
2016-05-02 17:13:11,428 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-02 17:13:13,320 Node[0] Epoch[28] Validation-accuracy=0.868990
2016-05-02 17:13:23,675 Node[0] Epoch[29] Batch [50] Speed: 621.34 samples/sec Train-accuracy=0.914219
2016-05-02 17:13:34,039 Node[0] Epoch[29] Batch [100] Speed: 617.55 samples/sec Train-accuracy=0.920312
2016-05-02 17:13:44,392 Node[0] Epoch[29] Batch [150] Speed: 618.17 samples/sec Train-accuracy=0.916719
2016-05-02 17:13:54,820 Node[0] Epoch[29] Batch [200] Speed: 613.75 samples/sec Train-accuracy=0.915781
2016-05-02 17:14:05,191 Node[0] Epoch[29] Batch [250] Speed: 617.14 samples/sec Train-accuracy=0.920469
2016-05-02 17:14:15,544 Node[0] Epoch[29] Batch [300] Speed: 618.20 samples/sec Train-accuracy=0.918594
2016-05-02 17:14:25,896 Node[0] Epoch[29] Batch [350] Speed: 618.21 samples/sec Train-accuracy=0.916094
2016-05-02 17:14:34,177 Node[0] Epoch[29] Resetting Data Iterator
2016-05-02 17:14:34,177 Node[0] Epoch[29] Time cost=80.857
2016-05-02 17:14:34,347 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-02 17:14:36,254 Node[0] Epoch[29] Validation-accuracy=0.836639
2016-05-02 17:14:46,653 Node[0] Epoch[30] Batch [50] Speed: 618.73 samples/sec Train-accuracy=0.916250
2016-05-02 17:14:57,034 Node[0] Epoch[30] Batch [100] Speed: 616.55 samples/sec Train-accuracy=0.919375
2016-05-02 17:15:07,397 Node[0] Epoch[30] Batch [150] Speed: 617.61 samples/sec Train-accuracy=0.923125
2016-05-02 17:15:17,738 Node[0] Epoch[30] Batch [200] Speed: 618.88 samples/sec Train-accuracy=0.915312
2016-05-02 17:15:28,118 Node[0] Epoch[30] Batch [250] Speed: 616.61 samples/sec Train-accuracy=0.914531
2016-05-02 17:15:38,451 Node[0] Epoch[30] Batch [300] Speed: 619.36 samples/sec Train-accuracy=0.920156
2016-05-02 17:15:48,794 Node[0] Epoch[30] Batch [350] Speed: 618.81 samples/sec Train-accuracy=0.917031
2016-05-02 17:15:57,300 Node[0] Epoch[30] Resetting Data Iterator
2016-05-02 17:15:57,300 Node[0] Epoch[30] Time cost=81.046
2016-05-02 17:15:57,466 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-02 17:15:59,364 Node[0] Epoch[30] Validation-accuracy=0.856270
2016-05-02 17:16:09,741 Node[0] Epoch[31] Batch [50] Speed: 619.98 samples/sec Train-accuracy=0.916250
2016-05-02 17:16:20,127 Node[0] Epoch[31] Batch [100] Speed: 616.23 samples/sec Train-accuracy=0.922188
2016-05-02 17:16:30,514 Node[0] Epoch[31] Batch [150] Speed: 616.19 samples/sec Train-accuracy=0.920156
2016-05-02 17:16:40,883 Node[0] Epoch[31] Batch [200] Speed: 617.21 samples/sec Train-accuracy=0.916094
2016-05-02 17:16:51,293 Node[0] Epoch[31] Batch [250] Speed: 614.83 samples/sec Train-accuracy=0.922500
2016-05-02 17:17:01,677 Node[0] Epoch[31] Batch [300] Speed: 616.37 samples/sec Train-accuracy=0.926719
2016-05-02 17:17:11,989 Node[0] Epoch[31] Batch [350] Speed: 620.61 samples/sec Train-accuracy=0.919219
2016-05-02 17:17:20,296 Node[0] Epoch[31] Resetting Data Iterator
2016-05-02 17:17:20,297 Node[0] Epoch[31] Time cost=80.933
2016-05-02 17:17:20,454 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-02 17:17:22,362 Node[0] Epoch[31] Validation-accuracy=0.856971
2016-05-02 17:17:32,707 Node[0] Epoch[32] Batch [50] Speed: 622.00 samples/sec Train-accuracy=0.916562
2016-05-02 17:17:43,115 Node[0] Epoch[32] Batch [100] Speed: 614.89 samples/sec Train-accuracy=0.916719
2016-05-02 17:17:53,588 Node[0] Epoch[32] Batch [150] Speed: 611.16 samples/sec Train-accuracy=0.914687
2016-05-02 17:18:03,953 Node[0] Epoch[32] Batch [200] Speed: 617.45 samples/sec Train-accuracy=0.920000
2016-05-02 17:18:14,315 Node[0] Epoch[32] Batch [250] Speed: 617.67 samples/sec Train-accuracy=0.920781
2016-05-02 17:18:24,696 Node[0] Epoch[32] Batch [300] Speed: 616.54 samples/sec Train-accuracy=0.923594
2016-05-02 17:18:35,084 Node[0] Epoch[32] Batch [350] Speed: 616.09 samples/sec Train-accuracy=0.923750
2016-05-02 17:18:43,595 Node[0] Epoch[32] Resetting Data Iterator
2016-05-02 17:18:43,596 Node[0] Epoch[32] Time cost=81.234
2016-05-02 17:18:43,759 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-02 17:18:45,938 Node[0] Epoch[32] Validation-accuracy=0.861452
2016-05-02 17:18:56,284 Node[0] Epoch[33] Batch [50] Speed: 621.79 samples/sec Train-accuracy=0.915000
2016-05-02 17:19:06,673 Node[0] Epoch[33] Batch [100] Speed: 616.04 samples/sec Train-accuracy=0.926094
2016-05-02 17:19:17,046 Node[0] Epoch[33] Batch [150] Speed: 617.01 samples/sec Train-accuracy=0.928750
2016-05-02 17:19:27,379 Node[0] Epoch[33] Batch [200] Speed: 619.40 samples/sec Train-accuracy=0.920156
2016-05-02 17:19:37,774 Node[0] Epoch[33] Batch [250] Speed: 615.72 samples/sec Train-accuracy=0.915156
2016-05-02 17:19:48,208 Node[0] Epoch[33] Batch [300] Speed: 613.41 samples/sec Train-accuracy=0.925000
2016-05-02 17:19:58,593 Node[0] Epoch[33] Batch [350] Speed: 616.27 samples/sec Train-accuracy=0.926406
2016-05-02 17:20:07,088 Node[0] Epoch[33] Resetting Data Iterator
2016-05-02 17:20:07,088 Node[0] Epoch[33] Time cost=81.150
2016-05-02 17:20:07,251 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-02 17:20:09,143 Node[0] Epoch[33] Validation-accuracy=0.839844
2016-05-02 17:20:19,458 Node[0] Epoch[34] Batch [50] Speed: 623.70 samples/sec Train-accuracy=0.923594
2016-05-02 17:20:29,811 Node[0] Epoch[34] Batch [100] Speed: 618.21 samples/sec Train-accuracy=0.919531
2016-05-02 17:20:40,191 Node[0] Epoch[34] Batch [150] Speed: 616.54 samples/sec Train-accuracy=0.924375
2016-05-02 17:20:50,542 Node[0] Epoch[34] Batch [200] Speed: 618.31 samples/sec Train-accuracy=0.925469
2016-05-02 17:21:00,895 Node[0] Epoch[34] Batch [250] Speed: 618.22 samples/sec Train-accuracy=0.928281
2016-05-02 17:21:11,296 Node[0] Epoch[34] Batch [300] Speed: 615.36 samples/sec Train-accuracy=0.928906
2016-05-02 17:21:21,750 Node[0] Epoch[34] Batch [350] Speed: 612.19 samples/sec Train-accuracy=0.918125
2016-05-02 17:21:30,078 Node[0] Epoch[34] Resetting Data Iterator
2016-05-02 17:21:30,078 Node[0] Epoch[34] Time cost=80.935
2016-05-02 17:21:30,238 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-02 17:21:32,145 Node[0] Epoch[34] Validation-accuracy=0.857672
2016-05-02 17:21:42,563 Node[0] Epoch[35] Batch [50] Speed: 617.55 samples/sec Train-accuracy=0.923750
2016-05-02 17:21:52,926 Node[0] Epoch[35] Batch [100] Speed: 617.61 samples/sec Train-accuracy=0.922969
2016-05-02 17:22:03,299 Node[0] Epoch[35] Batch [150] Speed: 616.96 samples/sec Train-accuracy=0.924531
2016-05-02 17:22:13,666 Node[0] Epoch[35] Batch [200] Speed: 617.37 samples/sec Train-accuracy=0.923438
2016-05-02 17:22:24,013 Node[0] Epoch[35] Batch [250] Speed: 618.54 samples/sec Train-accuracy=0.929063
2016-05-02 17:22:34,342 Node[0] Epoch[35] Batch [300] Speed: 619.63 samples/sec Train-accuracy=0.931250
2016-05-02 17:22:44,760 Node[0] Epoch[35] Batch [350] Speed: 614.33 samples/sec Train-accuracy=0.927031
2016-05-02 17:22:53,257 Node[0] Epoch[35] Resetting Data Iterator
2016-05-02 17:22:53,257 Node[0] Epoch[35] Time cost=81.112
2016-05-02 17:22:53,420 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-02 17:22:55,318 Node[0] Epoch[35] Validation-accuracy=0.862480
2016-05-02 17:23:05,667 Node[0] Epoch[36] Batch [50] Speed: 621.66 samples/sec Train-accuracy=0.925312
2016-05-02 17:23:16,049 Node[0] Epoch[36] Batch [100] Speed: 616.43 samples/sec Train-accuracy=0.922969
2016-05-02 17:23:26,399 Node[0] Epoch[36] Batch [150] Speed: 618.40 samples/sec Train-accuracy=0.925000
2016-05-02 17:23:36,793 Node[0] Epoch[36] Batch [200] Speed: 615.74 samples/sec Train-accuracy=0.922344
2016-05-02 17:23:47,150 Node[0] Epoch[36] Batch [250] Speed: 617.95 samples/sec Train-accuracy=0.931250
2016-05-02 17:23:57,585 Node[0] Epoch[36] Batch [300] Speed: 613.31 samples/sec Train-accuracy=0.928906
2016-05-02 17:24:07,987 Node[0] Epoch[36] Batch [350] Speed: 615.31 samples/sec Train-accuracy=0.925312
2016-05-02 17:24:16,516 Node[0] Epoch[36] Resetting Data Iterator
2016-05-02 17:24:16,516 Node[0] Epoch[36] Time cost=81.198
2016-05-02 17:24:16,686 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-02 17:24:18,610 Node[0] Epoch[36] Validation-accuracy=0.859575
2016-05-02 17:24:28,982 Node[0] Epoch[37] Batch [50] Speed: 620.26 samples/sec Train-accuracy=0.922031
2016-05-02 17:24:39,330 Node[0] Epoch[37] Batch [100] Speed: 618.53 samples/sec Train-accuracy=0.934063
2016-05-02 17:24:49,717 Node[0] Epoch[37] Batch [150] Speed: 616.14 samples/sec Train-accuracy=0.927188
2016-05-02 17:25:00,072 Node[0] Epoch[37] Batch [200] Speed: 618.08 samples/sec Train-accuracy=0.922500
2016-05-02 17:25:10,442 Node[0] Epoch[37] Batch [250] Speed: 617.19 samples/sec Train-accuracy=0.927031
2016-05-02 17:25:20,780 Node[0] Epoch[37] Batch [300] Speed: 619.09 samples/sec Train-accuracy=0.929688
2016-05-02 17:25:31,199 Node[0] Epoch[37] Batch [350] Speed: 614.28 samples/sec Train-accuracy=0.921875
2016-05-02 17:25:39,496 Node[0] Epoch[37] Resetting Data Iterator
2016-05-02 17:25:39,497 Node[0] Epoch[37] Time cost=80.887
2016-05-02 17:25:39,657 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-02 17:25:41,549 Node[0] Epoch[37] Validation-accuracy=0.869792
2016-05-02 17:25:51,957 Node[0] Epoch[38] Batch [50] Speed: 618.10 samples/sec Train-accuracy=0.925625
2016-05-02 17:26:02,210 Node[0] Epoch[38] Batch [100] Speed: 624.20 samples/sec Train-accuracy=0.930000
2016-05-02 17:26:12,527 Node[0] Epoch[38] Batch [150] Speed: 620.34 samples/sec Train-accuracy=0.934688
2016-05-02 17:26:22,913 Node[0] Epoch[38] Batch [200] Speed: 616.25 samples/sec Train-accuracy=0.925937
2016-05-02 17:26:33,310 Node[0] Epoch[38] Batch [250] Speed: 615.61 samples/sec Train-accuracy=0.928594
2016-05-02 17:26:43,704 Node[0] Epoch[38] Batch [300] Speed: 615.71 samples/sec Train-accuracy=0.930312
2016-05-02 17:26:54,078 Node[0] Epoch[38] Batch [350] Speed: 616.94 samples/sec Train-accuracy=0.931406
2016-05-02 17:27:02,549 Node[0] Epoch[38] Resetting Data Iterator
2016-05-02 17:27:02,549 Node[0] Epoch[38] Time cost=81.000
2016-05-02 17:27:02,711 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-02 17:27:04,597 Node[0] Epoch[38] Validation-accuracy=0.861579
2016-05-02 17:27:14,929 Node[0] Epoch[39] Batch [50] Speed: 622.75 samples/sec Train-accuracy=0.929219
2016-05-02 17:27:25,246 Node[0] Epoch[39] Batch [100] Speed: 620.36 samples/sec Train-accuracy=0.935781
2016-05-02 17:27:35,615 Node[0] Epoch[39] Batch [150] Speed: 617.25 samples/sec Train-accuracy=0.942344
2016-05-02 17:27:45,992 Node[0] Epoch[39] Batch [200] Speed: 616.77 samples/sec Train-accuracy=0.926094
2016-05-02 17:27:56,344 Node[0] Epoch[39] Batch [250] Speed: 618.23 samples/sec Train-accuracy=0.925000
2016-05-02 17:28:06,717 Node[0] Epoch[39] Batch [300] Speed: 617.01 samples/sec Train-accuracy=0.928906
2016-05-02 17:28:17,085 Node[0] Epoch[39] Batch [350] Speed: 617.33 samples/sec Train-accuracy=0.926562
2016-05-02 17:28:25,375 Node[0] Epoch[39] Resetting Data Iterator
2016-05-02 17:28:25,376 Node[0] Epoch[39] Time cost=80.778
2016-05-02 17:28:25,537 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-02 17:28:27,411 Node[0] Epoch[39] Validation-accuracy=0.870393
2016-05-02 17:28:37,764 Node[0] Epoch[40] Batch [50] Speed: 621.46 samples/sec Train-accuracy=0.927813
2016-05-02 17:28:48,127 Node[0] Epoch[40] Batch [100] Speed: 617.59 samples/sec Train-accuracy=0.930312
2016-05-02 17:28:58,534 Node[0] Epoch[40] Batch [150] Speed: 614.99 samples/sec Train-accuracy=0.930000
2016-05-02 17:29:08,862 Node[0] Epoch[40] Batch [200] Speed: 619.68 samples/sec Train-accuracy=0.926094
2016-05-02 17:29:19,223 Node[0] Epoch[40] Batch [250] Speed: 617.70 samples/sec Train-accuracy=0.931094
2016-05-02 17:29:29,598 Node[0] Epoch[40] Batch [300] Speed: 616.88 samples/sec Train-accuracy=0.932344
2016-05-02 17:29:39,991 Node[0] Epoch[40] Batch [350] Speed: 615.87 samples/sec Train-accuracy=0.927031
2016-05-02 17:29:48,497 Node[0] Epoch[40] Resetting Data Iterator
2016-05-02 17:29:48,497 Node[0] Epoch[40] Time cost=81.086
2016-05-02 17:29:48,664 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-02 17:29:50,783 Node[0] Epoch[40] Validation-accuracy=0.862737
2016-05-02 17:30:01,219 Node[0] Epoch[41] Batch [50] Speed: 616.54 samples/sec Train-accuracy=0.929375
2016-05-02 17:30:11,559 Node[0] Epoch[41] Batch [100] Speed: 618.92 samples/sec Train-accuracy=0.936094
2016-05-02 17:30:21,920 Node[0] Epoch[41] Batch [150] Speed: 617.74 samples/sec Train-accuracy=0.937813
2016-05-02 17:30:32,286 Node[0] Epoch[41] Batch [200] Speed: 617.44 samples/sec Train-accuracy=0.928594
2016-05-02 17:30:42,596 Node[0] Epoch[41] Batch [250] Speed: 620.73 samples/sec Train-accuracy=0.930937
2016-05-02 17:30:52,914 Node[0] Epoch[41] Batch [300] Speed: 620.32 samples/sec Train-accuracy=0.939063
2016-05-02 17:31:03,304 Node[0] Epoch[41] Batch [350] Speed: 615.99 samples/sec Train-accuracy=0.933750
2016-05-02 17:31:11,827 Node[0] Epoch[41] Resetting Data Iterator
2016-05-02 17:31:11,828 Node[0] Epoch[41] Time cost=81.044
2016-05-02 17:31:11,990 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-02 17:31:13,885 Node[0] Epoch[41] Validation-accuracy=0.854067
2016-05-02 17:31:24,230 Node[0] Epoch[42] Batch [50] Speed: 621.94 samples/sec Train-accuracy=0.935312
2016-05-02 17:31:34,598 Node[0] Epoch[42] Batch [100] Speed: 617.27 samples/sec Train-accuracy=0.933281
2016-05-02 17:31:44,942 Node[0] Epoch[42] Batch [150] Speed: 618.75 samples/sec Train-accuracy=0.935469
2016-05-02 17:31:55,313 Node[0] Epoch[42] Batch [200] Speed: 617.10 samples/sec Train-accuracy=0.926094
2016-05-02 17:32:05,625 Node[0] Epoch[42] Batch [250] Speed: 620.69 samples/sec Train-accuracy=0.925937
2016-05-02 17:32:16,044 Node[0] Epoch[42] Batch [300] Speed: 614.22 samples/sec Train-accuracy=0.937813
2016-05-02 17:32:26,406 Node[0] Epoch[42] Batch [350] Speed: 617.66 samples/sec Train-accuracy=0.930937
2016-05-02 17:32:34,740 Node[0] Epoch[42] Resetting Data Iterator
2016-05-02 17:32:34,740 Node[0] Epoch[42] Time cost=80.855
2016-05-02 17:32:34,906 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-02 17:32:36,830 Node[0] Epoch[42] Validation-accuracy=0.860176
2016-05-02 17:32:47,180 Node[0] Epoch[43] Batch [50] Speed: 621.58 samples/sec Train-accuracy=0.928750
2016-05-02 17:32:57,560 Node[0] Epoch[43] Batch [100] Speed: 616.60 samples/sec Train-accuracy=0.936719
2016-05-02 17:33:07,950 Node[0] Epoch[43] Batch [150] Speed: 615.98 samples/sec Train-accuracy=0.935156
2016-05-02 17:33:18,327 Node[0] Epoch[43] Batch [200] Speed: 616.81 samples/sec Train-accuracy=0.933750
2016-05-02 17:33:28,699 Node[0] Epoch[43] Batch [250] Speed: 617.02 samples/sec Train-accuracy=0.933281
2016-05-02 17:33:39,066 Node[0] Epoch[43] Batch [300] Speed: 617.37 samples/sec Train-accuracy=0.940625
2016-05-02 17:33:49,441 Node[0] Epoch[43] Batch [350] Speed: 616.88 samples/sec Train-accuracy=0.939063
2016-05-02 17:33:57,942 Node[0] Epoch[43] Resetting Data Iterator
2016-05-02 17:33:57,942 Node[0] Epoch[43] Time cost=81.112
2016-05-02 17:33:58,102 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-02 17:33:59,978 Node[0] Epoch[43] Validation-accuracy=0.858474
2016-05-02 17:34:10,374 Node[0] Epoch[44] Batch [50] Speed: 618.81 samples/sec Train-accuracy=0.928281
2016-05-02 17:34:20,749 Node[0] Epoch[44] Batch [100] Speed: 616.90 samples/sec Train-accuracy=0.932500
2016-05-02 17:34:31,091 Node[0] Epoch[44] Batch [150] Speed: 618.86 samples/sec Train-accuracy=0.934688
2016-05-02 17:34:41,452 Node[0] Epoch[44] Batch [200] Speed: 617.75 samples/sec Train-accuracy=0.935312
2016-05-02 17:34:51,794 Node[0] Epoch[44] Batch [250] Speed: 618.83 samples/sec Train-accuracy=0.935937
2016-05-02 17:35:02,102 Node[0] Epoch[44] Batch [300] Speed: 620.89 samples/sec Train-accuracy=0.936875
2016-05-02 17:35:12,480 Node[0] Epoch[44] Batch [350] Speed: 616.74 samples/sec Train-accuracy=0.938594
2016-05-02 17:35:20,958 Node[0] Epoch[44] Resetting Data Iterator
2016-05-02 17:35:20,958 Node[0] Epoch[44] Time cost=80.980
2016-05-02 17:35:21,122 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-02 17:35:23,040 Node[0] Epoch[44] Validation-accuracy=0.880909
2016-05-02 17:35:33,471 Node[0] Epoch[45] Batch [50] Speed: 616.86 samples/sec Train-accuracy=0.940937
2016-05-02 17:35:43,832 Node[0] Epoch[45] Batch [100] Speed: 617.74 samples/sec Train-accuracy=0.932969
2016-05-02 17:35:54,200 Node[0] Epoch[45] Batch [150] Speed: 617.29 samples/sec Train-accuracy=0.937969
2016-05-02 17:36:04,570 Node[0] Epoch[45] Batch [200] Speed: 617.19 samples/sec Train-accuracy=0.930937
2016-05-02 17:36:14,900 Node[0] Epoch[45] Batch [250] Speed: 619.59 samples/sec Train-accuracy=0.931562
2016-05-02 17:36:25,221 Node[0] Epoch[45] Batch [300] Speed: 620.11 samples/sec Train-accuracy=0.936406
2016-05-02 17:36:35,572 Node[0] Epoch[45] Batch [350] Speed: 618.32 samples/sec Train-accuracy=0.936406
2016-05-02 17:36:43,818 Node[0] Epoch[45] Resetting Data Iterator
2016-05-02 17:36:43,818 Node[0] Epoch[45] Time cost=80.778
2016-05-02 17:36:43,980 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-02 17:36:45,893 Node[0] Epoch[45] Validation-accuracy=0.877504
2016-05-02 17:36:56,334 Node[0] Epoch[46] Batch [50] Speed: 616.25 samples/sec Train-accuracy=0.931406
2016-05-02 17:37:06,661 Node[0] Epoch[46] Batch [100] Speed: 619.71 samples/sec Train-accuracy=0.936875
2016-05-02 17:37:17,009 Node[0] Epoch[46] Batch [150] Speed: 618.53 samples/sec Train-accuracy=0.934375
2016-05-02 17:37:27,379 Node[0] Epoch[46] Batch [200] Speed: 617.17 samples/sec Train-accuracy=0.936562
2016-05-02 17:37:37,720 Node[0] Epoch[46] Batch [250] Speed: 618.93 samples/sec Train-accuracy=0.930312
2016-05-02 17:37:48,065 Node[0] Epoch[46] Batch [300] Speed: 618.65 samples/sec Train-accuracy=0.945156
2016-05-02 17:37:58,448 Node[0] Epoch[46] Batch [350] Speed: 616.40 samples/sec Train-accuracy=0.937813
2016-05-02 17:38:06,929 Node[0] Epoch[46] Resetting Data Iterator
2016-05-02 17:38:06,929 Node[0] Epoch[46] Time cost=81.036
2016-05-02 17:38:07,093 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-02 17:38:09,009 Node[0] Epoch[46] Validation-accuracy=0.872897
2016-05-02 17:38:19,475 Node[0] Epoch[47] Batch [50] Speed: 614.86 samples/sec Train-accuracy=0.933438
2016-05-02 17:38:29,788 Node[0] Epoch[47] Batch [100] Speed: 620.64 samples/sec Train-accuracy=0.935781
2016-05-02 17:38:40,147 Node[0] Epoch[47] Batch [150] Speed: 617.82 samples/sec Train-accuracy=0.946406
2016-05-02 17:38:50,549 Node[0] Epoch[47] Batch [200] Speed: 615.26 samples/sec Train-accuracy=0.937500
2016-05-02 17:39:00,970 Node[0] Epoch[47] Batch [250] Speed: 614.19 samples/sec Train-accuracy=0.935000
2016-05-02 17:39:11,373 Node[0] Epoch[47] Batch [300] Speed: 615.23 samples/sec Train-accuracy=0.935469
2016-05-02 17:39:21,764 Node[0] Epoch[47] Batch [350] Speed: 615.90 samples/sec Train-accuracy=0.938594
2016-05-02 17:39:30,045 Node[0] Epoch[47] Resetting Data Iterator
2016-05-02 17:39:30,045 Node[0] Epoch[47] Time cost=81.036
2016-05-02 17:39:30,207 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-02 17:39:32,084 Node[0] Epoch[47] Validation-accuracy=0.888922
2016-05-02 17:39:42,365 Node[0] Epoch[48] Batch [50] Speed: 625.76 samples/sec Train-accuracy=0.939688
2016-05-02 17:39:52,740 Node[0] Epoch[48] Batch [100] Speed: 616.92 samples/sec Train-accuracy=0.936094
2016-05-02 17:40:03,076 Node[0] Epoch[48] Batch [150] Speed: 619.23 samples/sec Train-accuracy=0.935469
2016-05-02 17:40:13,384 Node[0] Epoch[48] Batch [200] Speed: 620.87 samples/sec Train-accuracy=0.933125
2016-05-02 17:40:23,710 Node[0] Epoch[48] Batch [250] Speed: 619.79 samples/sec Train-accuracy=0.928906
2016-05-02 17:40:34,055 Node[0] Epoch[48] Batch [300] Speed: 618.66 samples/sec Train-accuracy=0.936406
2016-05-02 17:40:44,422 Node[0] Epoch[48] Batch [350] Speed: 617.36 samples/sec Train-accuracy=0.939375
2016-05-02 17:40:52,910 Node[0] Epoch[48] Resetting Data Iterator
2016-05-02 17:40:52,910 Node[0] Epoch[48] Time cost=80.826
2016-05-02 17:40:53,069 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-02 17:40:55,176 Node[0] Epoch[48] Validation-accuracy=0.864814
2016-05-02 17:41:05,534 Node[0] Epoch[49] Batch [50] Speed: 621.07 samples/sec Train-accuracy=0.935937
2016-05-02 17:41:15,930 Node[0] Epoch[49] Batch [100] Speed: 615.64 samples/sec Train-accuracy=0.938281
2016-05-02 17:41:26,330 Node[0] Epoch[49] Batch [150] Speed: 615.42 samples/sec Train-accuracy=0.941406
2016-05-02 17:41:36,704 Node[0] Epoch[49] Batch [200] Speed: 616.92 samples/sec Train-accuracy=0.936875
2016-05-02 17:41:47,032 Node[0] Epoch[49] Batch [250] Speed: 619.67 samples/sec Train-accuracy=0.935000
2016-05-02 17:41:57,401 Node[0] Epoch[49] Batch [300] Speed: 617.26 samples/sec Train-accuracy=0.937344
2016-05-02 17:42:07,833 Node[0] Epoch[49] Batch [350] Speed: 613.49 samples/sec Train-accuracy=0.936562
2016-05-02 17:42:16,350 Node[0] Epoch[49] Resetting Data Iterator
2016-05-02 17:42:16,351 Node[0] Epoch[49] Time cost=81.175
2016-05-02 17:42:16,512 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-02 17:42:18,383 Node[0] Epoch[49] Validation-accuracy=0.868289
2016-05-02 17:42:28,686 Node[0] Epoch[50] Batch [50] Speed: 624.47 samples/sec Train-accuracy=0.937344
2016-05-02 17:42:39,109 Node[0] Epoch[50] Batch [100] Speed: 614.03 samples/sec Train-accuracy=0.941562
2016-05-02 17:42:49,461 Node[0] Epoch[50] Batch [150] Speed: 618.27 samples/sec Train-accuracy=0.943125
2016-05-02 17:42:59,787 Node[0] Epoch[50] Batch [200] Speed: 619.80 samples/sec Train-accuracy=0.940000
2016-05-02 17:43:10,138 Node[0] Epoch[50] Batch [250] Speed: 618.32 samples/sec Train-accuracy=0.935937
2016-05-02 17:43:20,479 Node[0] Epoch[50] Batch [300] Speed: 618.95 samples/sec Train-accuracy=0.939063
2016-05-02 17:43:30,889 Node[0] Epoch[50] Batch [350] Speed: 614.79 samples/sec Train-accuracy=0.938594
2016-05-02 17:43:39,134 Node[0] Epoch[50] Resetting Data Iterator
2016-05-02 17:43:39,134 Node[0] Epoch[50] Time cost=80.751
2016-05-02 17:43:39,298 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-02 17:43:41,237 Node[0] Epoch[50] Validation-accuracy=0.872095
2016-05-02 17:43:51,693 Node[0] Epoch[51] Batch [50] Speed: 615.29 samples/sec Train-accuracy=0.937344
2016-05-02 17:44:01,979 Node[0] Epoch[51] Batch [100] Speed: 622.23 samples/sec Train-accuracy=0.938750
2016-05-02 17:44:12,236 Node[0] Epoch[51] Batch [150] Speed: 624.00 samples/sec Train-accuracy=0.942813
2016-05-02 17:44:22,641 Node[0] Epoch[51] Batch [200] Speed: 615.06 samples/sec Train-accuracy=0.944063
2016-05-02 17:44:33,003 Node[0] Epoch[51] Batch [250] Speed: 617.69 samples/sec Train-accuracy=0.934844
2016-05-02 17:44:43,339 Node[0] Epoch[51] Batch [300] Speed: 619.20 samples/sec Train-accuracy=0.941719
2016-05-02 17:44:53,673 Node[0] Epoch[51] Batch [350] Speed: 619.37 samples/sec Train-accuracy=0.940000
2016-05-02 17:45:02,139 Node[0] Epoch[51] Resetting Data Iterator
2016-05-02 17:45:02,139 Node[0] Epoch[51] Time cost=80.902
2016-05-02 17:45:02,302 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-02 17:45:04,179 Node[0] Epoch[51] Validation-accuracy=0.878205
2016-05-02 17:45:14,520 Node[0] Epoch[52] Batch [50] Speed: 622.12 samples/sec Train-accuracy=0.936875
2016-05-02 17:45:24,901 Node[0] Epoch[52] Batch [100] Speed: 616.54 samples/sec Train-accuracy=0.937969
2016-05-02 17:45:35,255 Node[0] Epoch[52] Batch [150] Speed: 618.11 samples/sec Train-accuracy=0.938750
2016-05-02 17:45:45,644 Node[0] Epoch[52] Batch [200] Speed: 616.02 samples/sec Train-accuracy=0.942500
2016-05-02 17:45:55,975 Node[0] Epoch[52] Batch [250] Speed: 619.54 samples/sec Train-accuracy=0.942344
2016-05-02 17:46:06,385 Node[0] Epoch[52] Batch [300] Speed: 614.79 samples/sec Train-accuracy=0.943594
2016-05-02 17:46:16,719 Node[0] Epoch[52] Batch [350] Speed: 619.35 samples/sec Train-accuracy=0.939531
2016-05-02 17:46:25,228 Node[0] Epoch[52] Resetting Data Iterator
2016-05-02 17:46:25,228 Node[0] Epoch[52] Time cost=81.049
2016-05-02 17:46:25,390 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-02 17:46:27,301 Node[0] Epoch[52] Validation-accuracy=0.872095
2016-05-02 17:46:37,696 Node[0] Epoch[53] Batch [50] Speed: 618.90 samples/sec Train-accuracy=0.938906
2016-05-02 17:46:48,047 Node[0] Epoch[53] Batch [100] Speed: 618.33 samples/sec Train-accuracy=0.939688
2016-05-02 17:46:58,449 Node[0] Epoch[53] Batch [150] Speed: 615.28 samples/sec Train-accuracy=0.941094
2016-05-02 17:47:08,786 Node[0] Epoch[53] Batch [200] Speed: 619.14 samples/sec Train-accuracy=0.940469
2016-05-02 17:47:19,168 Node[0] Epoch[53] Batch [250] Speed: 616.46 samples/sec Train-accuracy=0.934375
2016-05-02 17:47:29,548 Node[0] Epoch[53] Batch [300] Speed: 616.60 samples/sec Train-accuracy=0.941250
2016-05-02 17:47:39,905 Node[0] Epoch[53] Batch [350] Speed: 617.99 samples/sec Train-accuracy=0.939375
2016-05-02 17:47:48,157 Node[0] Epoch[53] Resetting Data Iterator
2016-05-02 17:47:48,157 Node[0] Epoch[53] Time cost=80.856
2016-05-02 17:47:48,320 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-02 17:47:50,229 Node[0] Epoch[53] Validation-accuracy=0.871595
2016-05-02 17:48:00,586 Node[0] Epoch[54] Batch [50] Speed: 621.19 samples/sec Train-accuracy=0.935937
2016-05-02 17:48:10,932 Node[0] Epoch[54] Batch [100] Speed: 618.61 samples/sec Train-accuracy=0.942500
2016-05-02 17:48:21,284 Node[0] Epoch[54] Batch [150] Speed: 618.27 samples/sec Train-accuracy=0.944688
2016-05-02 17:48:31,626 Node[0] Epoch[54] Batch [200] Speed: 618.86 samples/sec Train-accuracy=0.935937
2016-05-02 17:48:41,968 Node[0] Epoch[54] Batch [250] Speed: 618.86 samples/sec Train-accuracy=0.934844
2016-05-02 17:48:52,307 Node[0] Epoch[54] Batch [300] Speed: 619.04 samples/sec Train-accuracy=0.946719
2016-05-02 17:49:02,643 Node[0] Epoch[54] Batch [350] Speed: 619.16 samples/sec Train-accuracy=0.944063
2016-05-02 17:49:11,123 Node[0] Epoch[54] Resetting Data Iterator
2016-05-02 17:49:11,123 Node[0] Epoch[54] Time cost=80.894
2016-05-02 17:49:11,286 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-02 17:49:13,217 Node[0] Epoch[54] Validation-accuracy=0.878906
2016-05-02 17:49:23,657 Node[0] Epoch[55] Batch [50] Speed: 616.25 samples/sec Train-accuracy=0.940781
2016-05-02 17:49:33,943 Node[0] Epoch[55] Batch [100] Speed: 622.25 samples/sec Train-accuracy=0.941406
2016-05-02 17:49:44,278 Node[0] Epoch[55] Batch [150] Speed: 619.27 samples/sec Train-accuracy=0.948906
2016-05-02 17:49:54,643 Node[0] Epoch[55] Batch [200] Speed: 617.46 samples/sec Train-accuracy=0.937500
2016-05-02 17:50:04,961 Node[0] Epoch[55] Batch [250] Speed: 620.31 samples/sec Train-accuracy=0.938125
2016-05-02 17:50:15,313 Node[0] Epoch[55] Batch [300] Speed: 618.26 samples/sec Train-accuracy=0.945469
2016-05-02 17:50:25,649 Node[0] Epoch[55] Batch [350] Speed: 619.22 samples/sec Train-accuracy=0.945312
2016-05-02 17:50:33,909 Node[0] Epoch[55] Resetting Data Iterator
2016-05-02 17:50:33,909 Node[0] Epoch[55] Time cost=80.692
2016-05-02 17:50:34,071 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-02 17:50:35,945 Node[0] Epoch[55] Validation-accuracy=0.878405
2016-05-02 17:50:46,319 Node[0] Epoch[56] Batch [50] Speed: 620.28 samples/sec Train-accuracy=0.942187
2016-05-02 17:50:56,677 Node[0] Epoch[56] Batch [100] Speed: 617.90 samples/sec Train-accuracy=0.944063
2016-05-02 17:51:06,939 Node[0] Epoch[56] Batch [150] Speed: 623.69 samples/sec Train-accuracy=0.940156
2016-05-02 17:51:17,297 Node[0] Epoch[56] Batch [200] Speed: 617.90 samples/sec Train-accuracy=0.942187
2016-05-02 17:51:27,633 Node[0] Epoch[56] Batch [250] Speed: 619.21 samples/sec Train-accuracy=0.940469
2016-05-02 17:51:37,994 Node[0] Epoch[56] Batch [300] Speed: 617.67 samples/sec Train-accuracy=0.945156
2016-05-02 17:51:48,392 Node[0] Epoch[56] Batch [350] Speed: 615.53 samples/sec Train-accuracy=0.942500
2016-05-02 17:51:56,895 Node[0] Epoch[56] Resetting Data Iterator
2016-05-02 17:51:56,895 Node[0] Epoch[56] Time cost=80.950
2016-05-02 17:51:57,056 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-02 17:51:59,127 Node[0] Epoch[56] Validation-accuracy=0.882219
2016-05-02 17:52:09,446 Node[0] Epoch[57] Batch [50] Speed: 623.51 samples/sec Train-accuracy=0.938906
2016-05-02 17:52:19,789 Node[0] Epoch[57] Batch [100] Speed: 618.81 samples/sec Train-accuracy=0.943125
2016-05-02 17:52:30,145 Node[0] Epoch[57] Batch [150] Speed: 617.99 samples/sec Train-accuracy=0.941719
2016-05-02 17:52:40,490 Node[0] Epoch[57] Batch [200] Speed: 618.66 samples/sec Train-accuracy=0.946094
2016-05-02 17:52:50,808 Node[0] Epoch[57] Batch [250] Speed: 620.31 samples/sec Train-accuracy=0.938750
2016-05-02 17:53:01,187 Node[0] Epoch[57] Batch [300] Speed: 616.61 samples/sec Train-accuracy=0.947031
2016-05-02 17:53:11,519 Node[0] Epoch[57] Batch [350] Speed: 619.48 samples/sec Train-accuracy=0.937969
2016-05-02 17:53:20,033 Node[0] Epoch[57] Resetting Data Iterator
2016-05-02 17:53:20,033 Node[0] Epoch[57] Time cost=80.906
2016-05-02 17:53:20,198 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-02 17:53:22,110 Node[0] Epoch[57] Validation-accuracy=0.876803
2016-05-02 17:53:32,557 Node[0] Epoch[58] Batch [50] Speed: 615.83 samples/sec Train-accuracy=0.945312
2016-05-02 17:53:42,919 Node[0] Epoch[58] Batch [100] Speed: 617.66 samples/sec Train-accuracy=0.947187
2016-05-02 17:53:53,302 Node[0] Epoch[58] Batch [150] Speed: 616.37 samples/sec Train-accuracy=0.938281
2016-05-02 17:54:03,656 Node[0] Epoch[58] Batch [200] Speed: 618.13 samples/sec Train-accuracy=0.942656
2016-05-02 17:54:13,999 Node[0] Epoch[58] Batch [250] Speed: 618.79 samples/sec Train-accuracy=0.940000
2016-05-02 17:54:24,324 Node[0] Epoch[58] Batch [300] Speed: 619.89 samples/sec Train-accuracy=0.943594
2016-05-02 17:54:34,719 Node[0] Epoch[58] Batch [350] Speed: 615.72 samples/sec Train-accuracy=0.946406
2016-05-02 17:54:42,984 Node[0] Epoch[58] Resetting Data Iterator
2016-05-02 17:54:42,984 Node[0] Epoch[58] Time cost=80.874
2016-05-02 17:54:43,146 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-02 17:54:45,030 Node[0] Epoch[58] Validation-accuracy=0.860978
2016-05-02 17:54:55,426 Node[0] Epoch[59] Batch [50] Speed: 618.96 samples/sec Train-accuracy=0.942813
2016-05-02 17:55:05,801 Node[0] Epoch[59] Batch [100] Speed: 616.90 samples/sec Train-accuracy=0.946875
2016-05-02 17:55:16,187 Node[0] Epoch[59] Batch [150] Speed: 616.25 samples/sec Train-accuracy=0.946406
2016-05-02 17:55:26,554 Node[0] Epoch[59] Batch [200] Speed: 617.33 samples/sec Train-accuracy=0.942813
2016-05-02 17:55:36,971 Node[0] Epoch[59] Batch [250] Speed: 614.38 samples/sec Train-accuracy=0.937969
2016-05-02 17:55:47,327 Node[0] Epoch[59] Batch [300] Speed: 618.01 samples/sec Train-accuracy=0.942969
2016-05-02 17:55:57,653 Node[0] Epoch[59] Batch [350] Speed: 619.81 samples/sec Train-accuracy=0.950000
2016-05-02 17:56:06,151 Node[0] Epoch[59] Resetting Data Iterator
2016-05-02 17:56:06,151 Node[0] Epoch[59] Time cost=81.120
2016-05-02 17:56:06,311 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-02 17:56:08,202 Node[0] Epoch[59] Validation-accuracy=0.874299
2016-05-02 17:56:18,670 Node[0] Epoch[60] Batch [50] Speed: 614.59 samples/sec Train-accuracy=0.942031
2016-05-02 17:56:29,015 Node[0] Epoch[60] Batch [100] Speed: 618.68 samples/sec Train-accuracy=0.946875
2016-05-02 17:56:39,397 Node[0] Epoch[60] Batch [150] Speed: 616.48 samples/sec Train-accuracy=0.942813
2016-05-02 17:56:49,777 Node[0] Epoch[60] Batch [200] Speed: 616.57 samples/sec Train-accuracy=0.936094
2016-05-02 17:57:00,119 Node[0] Epoch[60] Batch [250] Speed: 618.85 samples/sec Train-accuracy=0.944219
2016-05-02 17:57:10,497 Node[0] Epoch[60] Batch [300] Speed: 616.71 samples/sec Train-accuracy=0.947500
2016-05-02 17:57:20,906 Node[0] Epoch[60] Batch [350] Speed: 614.83 samples/sec Train-accuracy=0.939531
2016-05-02 17:57:29,398 Node[0] Epoch[60] Resetting Data Iterator
2016-05-02 17:57:29,398 Node[0] Epoch[60] Time cost=81.195
2016-05-02 17:57:29,561 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-02 17:57:31,435 Node[0] Epoch[60] Validation-accuracy=0.863281
2016-05-02 17:57:41,823 Node[0] Epoch[61] Batch [50] Speed: 619.26 samples/sec Train-accuracy=0.940937
2016-05-02 17:57:52,241 Node[0] Epoch[61] Batch [100] Speed: 614.34 samples/sec Train-accuracy=0.942500
2016-05-02 17:58:02,608 Node[0] Epoch[61] Batch [150] Speed: 617.36 samples/sec Train-accuracy=0.943750
2016-05-02 17:58:12,994 Node[0] Epoch[61] Batch [200] Speed: 616.23 samples/sec Train-accuracy=0.942969
2016-05-02 17:58:23,369 Node[0] Epoch[61] Batch [250] Speed: 616.88 samples/sec Train-accuracy=0.938438
2016-05-02 17:58:33,723 Node[0] Epoch[61] Batch [300] Speed: 618.14 samples/sec Train-accuracy=0.942656
2016-05-02 17:58:44,284 Node[0] Epoch[61] Batch [350] Speed: 606.04 samples/sec Train-accuracy=0.944375
2016-05-02 17:58:52,585 Node[0] Epoch[61] Resetting Data Iterator
2016-05-02 17:58:52,585 Node[0] Epoch[61] Time cost=81.150
2016-05-02 17:58:52,749 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-02 17:58:54,663 Node[0] Epoch[61] Validation-accuracy=0.883213
2016-05-02 17:59:04,980 Node[0] Epoch[62] Batch [50] Speed: 623.59 samples/sec Train-accuracy=0.941562
2016-05-02 17:59:15,340 Node[0] Epoch[62] Batch [100] Speed: 617.75 samples/sec Train-accuracy=0.948281
2016-05-02 17:59:25,739 Node[0] Epoch[62] Batch [150] Speed: 615.44 samples/sec Train-accuracy=0.943594
2016-05-02 17:59:36,200 Node[0] Epoch[62] Batch [200] Speed: 611.82 samples/sec Train-accuracy=0.945312
2016-05-02 17:59:46,595 Node[0] Epoch[62] Batch [250] Speed: 615.71 samples/sec Train-accuracy=0.944688
2016-05-02 17:59:56,969 Node[0] Epoch[62] Batch [300] Speed: 616.95 samples/sec Train-accuracy=0.949375
2016-05-02 18:00:07,402 Node[0] Epoch[62] Batch [350] Speed: 613.43 samples/sec Train-accuracy=0.949375
2016-05-02 18:00:15,922 Node[0] Epoch[62] Resetting Data Iterator
2016-05-02 18:00:15,922 Node[0] Epoch[62] Time cost=81.259
2016-05-02 18:00:16,085 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-02 18:00:17,956 Node[0] Epoch[62] Validation-accuracy=0.869191
2016-05-02 18:00:28,288 Node[0] Epoch[63] Batch [50] Speed: 622.80 samples/sec Train-accuracy=0.941719
2016-05-02 18:00:38,637 Node[0] Epoch[63] Batch [100] Speed: 618.43 samples/sec Train-accuracy=0.949844
2016-05-02 18:00:49,055 Node[0] Epoch[63] Batch [150] Speed: 614.31 samples/sec Train-accuracy=0.945469
2016-05-02 18:00:59,442 Node[0] Epoch[63] Batch [200] Speed: 616.20 samples/sec Train-accuracy=0.945625
2016-05-02 18:01:09,890 Node[0] Epoch[63] Batch [250] Speed: 612.54 samples/sec Train-accuracy=0.951250
2016-05-02 18:01:20,303 Node[0] Epoch[63] Batch [300] Speed: 614.63 samples/sec Train-accuracy=0.949688
2016-05-02 18:01:30,729 Node[0] Epoch[63] Batch [350] Speed: 613.86 samples/sec Train-accuracy=0.954219
2016-05-02 18:01:39,066 Node[0] Epoch[63] Resetting Data Iterator
2016-05-02 18:01:39,067 Node[0] Epoch[63] Time cost=81.110
2016-05-02 18:01:39,233 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-02 18:01:41,133 Node[0] Epoch[63] Validation-accuracy=0.869692
2016-05-02 18:01:51,491 Node[0] Epoch[64] Batch [50] Speed: 621.21 samples/sec Train-accuracy=0.941406
2016-05-02 18:02:01,833 Node[0] Epoch[64] Batch [100] Speed: 618.87 samples/sec Train-accuracy=0.947500
2016-05-02 18:02:12,213 Node[0] Epoch[64] Batch [150] Speed: 616.58 samples/sec Train-accuracy=0.947812
2016-05-02 18:02:22,579 Node[0] Epoch[64] Batch [200] Speed: 617.43 samples/sec Train-accuracy=0.946094
2016-05-02 18:02:33,007 Node[0] Epoch[64] Batch [250] Speed: 613.75 samples/sec Train-accuracy=0.941719
2016-05-02 18:02:43,358 Node[0] Epoch[64] Batch [300] Speed: 618.27 samples/sec Train-accuracy=0.943281
2016-05-02 18:02:53,730 Node[0] Epoch[64] Batch [350] Speed: 617.12 samples/sec Train-accuracy=0.945312
2016-05-02 18:03:02,247 Node[0] Epoch[64] Resetting Data Iterator
2016-05-02 18:03:02,248 Node[0] Epoch[64] Time cost=81.114
2016-05-02 18:03:02,411 Node[0] Saved checkpoint to "cifar10/resnet-0065.params"
2016-05-02 18:03:04,541 Node[0] Epoch[64] Validation-accuracy=0.885186
2016-05-02 18:03:15,046 Node[0] Epoch[65] Batch [50] Speed: 612.42 samples/sec Train-accuracy=0.945000
2016-05-02 18:03:25,361 Node[0] Epoch[65] Batch [100] Speed: 620.48 samples/sec Train-accuracy=0.949688
2016-05-02 18:03:35,736 Node[0] Epoch[65] Batch [150] Speed: 616.89 samples/sec Train-accuracy=0.949531
2016-05-02 18:03:46,079 Node[0] Epoch[65] Batch [200] Speed: 618.78 samples/sec Train-accuracy=0.942969
2016-05-02 18:03:56,429 Node[0] Epoch[65] Batch [250] Speed: 618.36 samples/sec Train-accuracy=0.945625
2016-05-02 18:04:06,805 Node[0] Epoch[65] Batch [300] Speed: 616.83 samples/sec Train-accuracy=0.946406
2016-05-02 18:04:17,232 Node[0] Epoch[65] Batch [350] Speed: 613.84 samples/sec Train-accuracy=0.946250
2016-05-02 18:04:25,718 Node[0] Epoch[65] Resetting Data Iterator
2016-05-02 18:04:25,718 Node[0] Epoch[65] Time cost=81.177
2016-05-02 18:04:25,882 Node[0] Saved checkpoint to "cifar10/resnet-0066.params"
2016-05-02 18:04:27,784 Node[0] Epoch[65] Validation-accuracy=0.854267
2016-05-02 18:04:38,155 Node[0] Epoch[66] Batch [50] Speed: 620.32 samples/sec Train-accuracy=0.942813
2016-05-02 18:04:48,519 Node[0] Epoch[66] Batch [100] Speed: 617.50 samples/sec Train-accuracy=0.945469
2016-05-02 18:04:58,844 Node[0] Epoch[66] Batch [150] Speed: 619.88 samples/sec Train-accuracy=0.946406
2016-05-02 18:05:09,185 Node[0] Epoch[66] Batch [200] Speed: 618.91 samples/sec Train-accuracy=0.942969
2016-05-02 18:05:19,552 Node[0] Epoch[66] Batch [250] Speed: 617.39 samples/sec Train-accuracy=0.948281
2016-05-02 18:05:29,921 Node[0] Epoch[66] Batch [300] Speed: 617.26 samples/sec Train-accuracy=0.949844
2016-05-02 18:05:40,315 Node[0] Epoch[66] Batch [350] Speed: 615.71 samples/sec Train-accuracy=0.948906
2016-05-02 18:05:48,617 Node[0] Epoch[66] Resetting Data Iterator
2016-05-02 18:05:48,618 Node[0] Epoch[66] Time cost=80.833
2016-05-02 18:05:48,782 Node[0] Saved checkpoint to "cifar10/resnet-0067.params"
2016-05-02 18:05:50,669 Node[0] Epoch[66] Validation-accuracy=0.878806
2016-05-02 18:06:01,015 Node[0] Epoch[67] Batch [50] Speed: 621.87 samples/sec Train-accuracy=0.944219
2016-05-02 18:06:11,380 Node[0] Epoch[67] Batch [100] Speed: 617.48 samples/sec Train-accuracy=0.944531
2016-05-02 18:06:21,746 Node[0] Epoch[67] Batch [150] Speed: 617.43 samples/sec Train-accuracy=0.950156
2016-05-02 18:06:32,134 Node[0] Epoch[67] Batch [200] Speed: 616.07 samples/sec Train-accuracy=0.944688
2016-05-02 18:06:42,521 Node[0] Epoch[67] Batch [250] Speed: 616.20 samples/sec Train-accuracy=0.945625
2016-05-02 18:06:52,879 Node[0] Epoch[67] Batch [300] Speed: 617.88 samples/sec Train-accuracy=0.950000
2016-05-02 18:07:03,235 Node[0] Epoch[67] Batch [350] Speed: 618.01 samples/sec Train-accuracy=0.947500
2016-05-02 18:07:11,733 Node[0] Epoch[67] Resetting Data Iterator
2016-05-02 18:07:11,733 Node[0] Epoch[67] Time cost=81.064
2016-05-02 18:07:11,895 Node[0] Saved checkpoint to "cifar10/resnet-0068.params"
2016-05-02 18:07:13,802 Node[0] Epoch[67] Validation-accuracy=0.883213
2016-05-02 18:07:24,248 Node[0] Epoch[68] Batch [50] Speed: 615.85 samples/sec Train-accuracy=0.945781
2016-05-02 18:07:34,641 Node[0] Epoch[68] Batch [100] Speed: 615.84 samples/sec Train-accuracy=0.947812
2016-05-02 18:07:44,986 Node[0] Epoch[68] Batch [150] Speed: 618.61 samples/sec Train-accuracy=0.951406
2016-05-02 18:07:55,381 Node[0] Epoch[68] Batch [200] Speed: 615.75 samples/sec Train-accuracy=0.946719
2016-05-02 18:08:05,712 Node[0] Epoch[68] Batch [250] Speed: 619.49 samples/sec Train-accuracy=0.947969
2016-05-02 18:08:16,074 Node[0] Epoch[68] Batch [300] Speed: 617.65 samples/sec Train-accuracy=0.942344
2016-05-02 18:08:26,487 Node[0] Epoch[68] Batch [350] Speed: 614.62 samples/sec Train-accuracy=0.942813
2016-05-02 18:08:34,979 Node[0] Epoch[68] Resetting Data Iterator
2016-05-02 18:08:34,980 Node[0] Epoch[68] Time cost=81.178
2016-05-02 18:08:35,148 Node[0] Saved checkpoint to "cifar10/resnet-0069.params"
2016-05-02 18:08:37,011 Node[0] Epoch[68] Validation-accuracy=0.881210
2016-05-02 18:08:47,371 Node[0] Epoch[69] Batch [50] Speed: 621.02 samples/sec Train-accuracy=0.946719
2016-05-02 18:08:57,802 Node[0] Epoch[69] Batch [100] Speed: 613.56 samples/sec Train-accuracy=0.948281
2016-05-02 18:09:08,188 Node[0] Epoch[69] Batch [150] Speed: 616.27 samples/sec Train-accuracy=0.948906
2016-05-02 18:09:18,572 Node[0] Epoch[69] Batch [200] Speed: 616.34 samples/sec Train-accuracy=0.950469
2016-05-02 18:09:28,971 Node[0] Epoch[69] Batch [250] Speed: 615.43 samples/sec Train-accuracy=0.945937
2016-05-02 18:09:39,334 Node[0] Epoch[69] Batch [300] Speed: 617.61 samples/sec Train-accuracy=0.954531
2016-05-02 18:09:49,712 Node[0] Epoch[69] Batch [350] Speed: 616.70 samples/sec Train-accuracy=0.950000
2016-05-02 18:09:57,974 Node[0] Epoch[69] Resetting Data Iterator
2016-05-02 18:09:57,974 Node[0] Epoch[69] Time cost=80.963
2016-05-02 18:09:58,135 Node[0] Saved checkpoint to "cifar10/resnet-0070.params"
2016-05-02 18:10:00,031 Node[0] Epoch[69] Validation-accuracy=0.870593
2016-05-02 18:10:10,487 Node[0] Epoch[70] Batch [50] Speed: 615.32 samples/sec Train-accuracy=0.948125
2016-05-02 18:10:20,885 Node[0] Epoch[70] Batch [100] Speed: 615.56 samples/sec Train-accuracy=0.952500
2016-05-02 18:10:31,236 Node[0] Epoch[70] Batch [150] Speed: 618.29 samples/sec Train-accuracy=0.948750
2016-05-02 18:10:41,584 Node[0] Epoch[70] Batch [200] Speed: 618.48 samples/sec Train-accuracy=0.942969
2016-05-02 18:10:51,913 Node[0] Epoch[70] Batch [250] Speed: 619.62 samples/sec Train-accuracy=0.944219
2016-05-02 18:11:02,322 Node[0] Epoch[70] Batch [300] Speed: 614.90 samples/sec Train-accuracy=0.946875
2016-05-02 18:11:12,709 Node[0] Epoch[70] Batch [350] Speed: 616.18 samples/sec Train-accuracy=0.946406
2016-05-02 18:11:21,217 Node[0] Epoch[70] Resetting Data Iterator
2016-05-02 18:11:21,217 Node[0] Epoch[70] Time cost=81.186
2016-05-02 18:11:21,379 Node[0] Saved checkpoint to "cifar10/resnet-0071.params"
2016-05-02 18:11:23,292 Node[0] Epoch[70] Validation-accuracy=0.887320
2016-05-02 18:11:33,668 Node[0] Epoch[71] Batch [50] Speed: 620.05 samples/sec Train-accuracy=0.954844
2016-05-02 18:11:44,069 Node[0] Epoch[71] Batch [100] Speed: 615.37 samples/sec Train-accuracy=0.949531
2016-05-02 18:11:54,394 Node[0] Epoch[71] Batch [150] Speed: 619.85 samples/sec Train-accuracy=0.953438
2016-05-02 18:12:04,779 Node[0] Epoch[71] Batch [200] Speed: 616.30 samples/sec Train-accuracy=0.946875
2016-05-02 18:12:15,158 Node[0] Epoch[71] Batch [250] Speed: 616.62 samples/sec Train-accuracy=0.948438
2016-05-02 18:12:25,563 Node[0] Epoch[71] Batch [300] Speed: 615.09 samples/sec Train-accuracy=0.950469
2016-05-02 18:12:36,043 Node[0] Epoch[71] Batch [350] Speed: 610.71 samples/sec Train-accuracy=0.950781
2016-05-02 18:12:44,360 Node[0] Epoch[71] Resetting Data Iterator
2016-05-02 18:12:44,361 Node[0] Epoch[71] Time cost=81.068
2016-05-02 18:12:44,525 Node[0] Saved checkpoint to "cifar10/resnet-0072.params"
2016-05-02 18:12:46,409 Node[0] Epoch[71] Validation-accuracy=0.863982
2016-05-02 18:12:56,838 Node[0] Epoch[72] Batch [50] Speed: 616.89 samples/sec Train-accuracy=0.949375
2016-05-02 18:13:07,299 Node[0] Epoch[72] Batch [100] Speed: 611.82 samples/sec Train-accuracy=0.948438
2016-05-02 18:13:17,661 Node[0] Epoch[72] Batch [150] Speed: 617.63 samples/sec Train-accuracy=0.952656
2016-05-02 18:13:27,998 Node[0] Epoch[72] Batch [200] Speed: 619.16 samples/sec Train-accuracy=0.949844
2016-05-02 18:13:38,391 Node[0] Epoch[72] Batch [250] Speed: 615.80 samples/sec Train-accuracy=0.948125
2016-05-02 18:13:48,869 Node[0] Epoch[72] Batch [300] Speed: 610.84 samples/sec Train-accuracy=0.947344
2016-05-02 18:13:59,279 Node[0] Epoch[72] Batch [350] Speed: 614.82 samples/sec Train-accuracy=0.947500
2016-05-02 18:14:07,784 Node[0] Epoch[72] Resetting Data Iterator
2016-05-02 18:14:07,784 Node[0] Epoch[72] Time cost=81.376
2016-05-02 18:14:07,949 Node[0] Saved checkpoint to "cifar10/resnet-0073.params"
2016-05-02 18:14:10,034 Node[0] Epoch[72] Validation-accuracy=0.874901
2016-05-02 18:14:20,358 Node[0] Epoch[73] Batch [50] Speed: 623.10 samples/sec Train-accuracy=0.951562
2016-05-02 18:14:30,793 Node[0] Epoch[73] Batch [100] Speed: 613.37 samples/sec Train-accuracy=0.950625
2016-05-02 18:14:41,175 Node[0] Epoch[73] Batch [150] Speed: 616.46 samples/sec Train-accuracy=0.951250
2016-05-02 18:14:51,549 Node[0] Epoch[73] Batch [200] Speed: 616.94 samples/sec Train-accuracy=0.947500
2016-05-02 18:15:01,866 Node[0] Epoch[73] Batch [250] Speed: 620.35 samples/sec Train-accuracy=0.945156
2016-05-02 18:15:12,264 Node[0] Epoch[73] Batch [300] Speed: 615.56 samples/sec Train-accuracy=0.952344
2016-05-02 18:15:22,617 Node[0] Epoch[73] Batch [350] Speed: 618.14 samples/sec Train-accuracy=0.956406
2016-05-02 18:15:31,104 Node[0] Epoch[73] Resetting Data Iterator
2016-05-02 18:15:31,104 Node[0] Epoch[73] Time cost=81.070
2016-05-02 18:15:31,265 Node[0] Saved checkpoint to "cifar10/resnet-0074.params"
2016-05-02 18:15:33,171 Node[0] Epoch[73] Validation-accuracy=0.880509
2016-05-02 18:15:43,585 Node[0] Epoch[74] Batch [50] Speed: 617.80 samples/sec Train-accuracy=0.948281
2016-05-02 18:15:54,000 Node[0] Epoch[74] Batch [100] Speed: 614.52 samples/sec Train-accuracy=0.952969
2016-05-02 18:16:04,363 Node[0] Epoch[74] Batch [150] Speed: 617.57 samples/sec Train-accuracy=0.957344
2016-05-02 18:16:14,741 Node[0] Epoch[74] Batch [200] Speed: 616.73 samples/sec Train-accuracy=0.953438
2016-05-02 18:16:25,077 Node[0] Epoch[74] Batch [250] Speed: 619.19 samples/sec Train-accuracy=0.940625
2016-05-02 18:16:35,450 Node[0] Epoch[74] Batch [300] Speed: 617.02 samples/sec Train-accuracy=0.948125
2016-05-02 18:16:45,883 Node[0] Epoch[74] Batch [350] Speed: 613.43 samples/sec Train-accuracy=0.947187
2016-05-02 18:16:54,204 Node[0] Epoch[74] Resetting Data Iterator
2016-05-02 18:16:54,204 Node[0] Epoch[74] Time cost=81.033
2016-05-02 18:16:54,367 Node[0] Saved checkpoint to "cifar10/resnet-0075.params"
2016-05-02 18:16:56,297 Node[0] Epoch[74] Validation-accuracy=0.872596
2016-05-02 18:17:06,688 Node[0] Epoch[75] Batch [50] Speed: 619.14 samples/sec Train-accuracy=0.948906
2016-05-02 18:17:17,089 Node[0] Epoch[75] Batch [100] Speed: 615.35 samples/sec Train-accuracy=0.947031
2016-05-02 18:17:27,459 Node[0] Epoch[75] Batch [150] Speed: 617.20 samples/sec Train-accuracy=0.947187
2016-05-02 18:17:37,771 Node[0] Epoch[75] Batch [200] Speed: 620.61 samples/sec Train-accuracy=0.946875
2016-05-02 18:17:48,241 Node[0] Epoch[75] Batch [250] Speed: 611.30 samples/sec Train-accuracy=0.946875
2016-05-02 18:17:58,660 Node[0] Epoch[75] Batch [300] Speed: 614.31 samples/sec Train-accuracy=0.952031
2016-05-02 18:18:09,066 Node[0] Epoch[75] Batch [350] Speed: 615.04 samples/sec Train-accuracy=0.948750
2016-05-02 18:18:17,578 Node[0] Epoch[75] Resetting Data Iterator
2016-05-02 18:18:17,578 Node[0] Epoch[75] Time cost=81.281
2016-05-02 18:18:17,737 Node[0] Saved checkpoint to "cifar10/resnet-0076.params"
2016-05-02 18:18:19,626 Node[0] Epoch[75] Validation-accuracy=0.883614
2016-05-02 18:18:29,983 Node[0] Epoch[76] Batch [50] Speed: 621.15 samples/sec Train-accuracy=0.946719
2016-05-02 18:18:40,331 Node[0] Epoch[76] Batch [100] Speed: 618.47 samples/sec Train-accuracy=0.950469
2016-05-02 18:18:50,598 Node[0] Epoch[76] Batch [150] Speed: 623.36 samples/sec Train-accuracy=0.950313
2016-05-02 18:19:00,965 Node[0] Epoch[76] Batch [200] Speed: 617.33 samples/sec Train-accuracy=0.950469
2016-05-02 18:19:11,349 Node[0] Epoch[76] Batch [250] Speed: 616.35 samples/sec Train-accuracy=0.946094
2016-05-02 18:19:21,704 Node[0] Epoch[76] Batch [300] Speed: 618.08 samples/sec Train-accuracy=0.950625
2016-05-02 18:19:32,127 Node[0] Epoch[76] Batch [350] Speed: 614.07 samples/sec Train-accuracy=0.953594
2016-05-02 18:19:40,651 Node[0] Epoch[76] Resetting Data Iterator
2016-05-02 18:19:40,652 Node[0] Epoch[76] Time cost=81.025
2016-05-02 18:19:40,817 Node[0] Saved checkpoint to "cifar10/resnet-0077.params"
2016-05-02 18:19:42,725 Node[0] Epoch[76] Validation-accuracy=0.889423
2016-05-02 18:19:53,091 Node[0] Epoch[77] Batch [50] Speed: 620.58 samples/sec Train-accuracy=0.951406
2016-05-02 18:20:03,479 Node[0] Epoch[77] Batch [100] Speed: 616.13 samples/sec Train-accuracy=0.947500
2016-05-02 18:20:13,865 Node[0] Epoch[77] Batch [150] Speed: 616.22 samples/sec Train-accuracy=0.948906
2016-05-02 18:20:24,260 Node[0] Epoch[77] Batch [200] Speed: 615.69 samples/sec Train-accuracy=0.947031
2016-05-02 18:20:34,624 Node[0] Epoch[77] Batch [250] Speed: 617.55 samples/sec Train-accuracy=0.951875
2016-05-02 18:20:45,018 Node[0] Epoch[77] Batch [300] Speed: 615.77 samples/sec Train-accuracy=0.951875
2016-05-02 18:20:55,402 Node[0] Epoch[77] Batch [350] Speed: 616.33 samples/sec Train-accuracy=0.946094
2016-05-02 18:21:03,698 Node[0] Epoch[77] Resetting Data Iterator
2016-05-02 18:21:03,699 Node[0] Epoch[77] Time cost=80.974
2016-05-02 18:21:03,863 Node[0] Saved checkpoint to "cifar10/resnet-0078.params"
2016-05-02 18:21:05,750 Node[0] Epoch[77] Validation-accuracy=0.869892
2016-05-02 18:21:16,091 Node[0] Epoch[78] Batch [50] Speed: 622.28 samples/sec Train-accuracy=0.947500
2016-05-02 18:21:26,519 Node[0] Epoch[78] Batch [100] Speed: 613.75 samples/sec Train-accuracy=0.946719
2016-05-02 18:21:36,922 Node[0] Epoch[78] Batch [150] Speed: 615.22 samples/sec Train-accuracy=0.950000
2016-05-02 18:21:47,274 Node[0] Epoch[78] Batch [200] Speed: 618.26 samples/sec Train-accuracy=0.947969
2016-05-02 18:21:57,668 Node[0] Epoch[78] Batch [250] Speed: 615.72 samples/sec Train-accuracy=0.950000
2016-05-02 18:22:08,059 Node[0] Epoch[78] Batch [300] Speed: 615.92 samples/sec Train-accuracy=0.952969
2016-05-02 18:22:18,476 Node[0] Epoch[78] Batch [350] Speed: 614.40 samples/sec Train-accuracy=0.950781
2016-05-02 18:22:27,004 Node[0] Epoch[78] Resetting Data Iterator
2016-05-02 18:22:27,004 Node[0] Epoch[78] Time cost=81.254
2016-05-02 18:22:27,166 Node[0] Saved checkpoint to "cifar10/resnet-0079.params"
2016-05-02 18:22:29,092 Node[0] Epoch[78] Validation-accuracy=0.884916
2016-05-02 18:22:39,541 Node[0] Epoch[79] Batch [50] Speed: 615.66 samples/sec Train-accuracy=0.947187
2016-05-02 18:22:49,921 Node[0] Epoch[79] Batch [100] Speed: 616.60 samples/sec Train-accuracy=0.954688
2016-05-02 18:23:00,294 Node[0] Epoch[79] Batch [150] Speed: 617.00 samples/sec Train-accuracy=0.955781
2016-05-02 18:23:10,671 Node[0] Epoch[79] Batch [200] Speed: 616.77 samples/sec Train-accuracy=0.953906
2016-05-02 18:23:20,997 Node[0] Epoch[79] Batch [250] Speed: 619.78 samples/sec Train-accuracy=0.948750
2016-05-02 18:23:31,372 Node[0] Epoch[79] Batch [300] Speed: 616.91 samples/sec Train-accuracy=0.950313
2016-05-02 18:23:41,766 Node[0] Epoch[79] Batch [350] Speed: 615.72 samples/sec Train-accuracy=0.951875
2016-05-02 18:23:50,032 Node[0] Epoch[79] Resetting Data Iterator
2016-05-02 18:23:50,032 Node[0] Epoch[79] Time cost=80.940
2016-05-02 18:23:50,194 Node[0] Saved checkpoint to "cifar10/resnet-0080.params"
2016-05-02 18:23:52,086 Node[0] Epoch[79] Validation-accuracy=0.875200
2016-05-02 18:23:52,086 Node[0] Update[31251]: Change learning rate to 1.00000e-02
2016-05-02 18:24:02,398 Node[0] Epoch[80] Batch [50] Speed: 623.90 samples/sec Train-accuracy=0.951875
2016-05-02 18:24:12,802 Node[0] Epoch[80] Batch [100] Speed: 615.19 samples/sec Train-accuracy=0.964063
2016-05-02 18:24:23,195 Node[0] Epoch[80] Batch [150] Speed: 615.82 samples/sec Train-accuracy=0.966719
2016-05-02 18:24:33,519 Node[0] Epoch[80] Batch [200] Speed: 619.90 samples/sec Train-accuracy=0.970156
2016-05-02 18:24:43,867 Node[0] Epoch[80] Batch [250] Speed: 618.52 samples/sec Train-accuracy=0.975156
2016-05-02 18:24:54,225 Node[0] Epoch[80] Batch [300] Speed: 617.88 samples/sec Train-accuracy=0.979375
2016-05-02 18:25:04,655 Node[0] Epoch[80] Batch [350] Speed: 613.62 samples/sec Train-accuracy=0.982031
2016-05-02 18:25:13,209 Node[0] Epoch[80] Resetting Data Iterator
2016-05-02 18:25:13,209 Node[0] Epoch[80] Time cost=81.123
2016-05-02 18:25:13,370 Node[0] Saved checkpoint to "cifar10/resnet-0081.params"
2016-05-02 18:25:15,495 Node[0] Epoch[80] Validation-accuracy=0.913766
2016-05-02 18:25:25,882 Node[0] Epoch[81] Batch [50] Speed: 619.39 samples/sec Train-accuracy=0.977969
2016-05-02 18:25:36,236 Node[0] Epoch[81] Batch [100] Speed: 618.10 samples/sec Train-accuracy=0.981875
2016-05-02 18:25:46,594 Node[0] Epoch[81] Batch [150] Speed: 617.91 samples/sec Train-accuracy=0.980313
2016-05-02 18:25:56,942 Node[0] Epoch[81] Batch [200] Speed: 618.49 samples/sec Train-accuracy=0.979844
2016-05-02 18:26:07,305 Node[0] Epoch[81] Batch [250] Speed: 617.59 samples/sec Train-accuracy=0.980625
2016-05-02 18:26:17,679 Node[0] Epoch[81] Batch [300] Speed: 616.95 samples/sec Train-accuracy=0.984062
2016-05-02 18:26:28,105 Node[0] Epoch[81] Batch [350] Speed: 613.87 samples/sec Train-accuracy=0.985781
2016-05-02 18:26:36,623 Node[0] Epoch[81] Resetting Data Iterator
2016-05-02 18:26:36,624 Node[0] Epoch[81] Time cost=81.128
2016-05-02 18:26:36,788 Node[0] Saved checkpoint to "cifar10/resnet-0082.params"
2016-05-02 18:26:38,671 Node[0] Epoch[81] Validation-accuracy=0.915765
2016-05-02 18:26:49,004 Node[0] Epoch[82] Batch [50] Speed: 622.62 samples/sec Train-accuracy=0.981719
2016-05-02 18:26:59,378 Node[0] Epoch[82] Batch [100] Speed: 616.92 samples/sec Train-accuracy=0.984688
2016-05-02 18:27:09,724 Node[0] Epoch[82] Batch [150] Speed: 618.63 samples/sec Train-accuracy=0.985938
2016-05-02 18:27:20,085 Node[0] Epoch[82] Batch [200] Speed: 617.68 samples/sec Train-accuracy=0.986250
2016-05-02 18:27:30,465 Node[0] Epoch[82] Batch [250] Speed: 616.62 samples/sec Train-accuracy=0.983437
2016-05-02 18:27:40,820 Node[0] Epoch[82] Batch [300] Speed: 618.08 samples/sec Train-accuracy=0.985469
2016-05-02 18:27:51,158 Node[0] Epoch[82] Batch [350] Speed: 619.04 samples/sec Train-accuracy=0.989375
2016-05-02 18:27:59,437 Node[0] Epoch[82] Resetting Data Iterator
2016-05-02 18:27:59,438 Node[0] Epoch[82] Time cost=80.767
2016-05-02 18:27:59,600 Node[0] Saved checkpoint to "cifar10/resnet-0083.params"
2016-05-02 18:28:01,490 Node[0] Epoch[82] Validation-accuracy=0.915865
2016-05-02 18:28:11,862 Node[0] Epoch[83] Batch [50] Speed: 620.28 samples/sec Train-accuracy=0.983125
2016-05-02 18:28:22,243 Node[0] Epoch[83] Batch [100] Speed: 616.55 samples/sec Train-accuracy=0.987031
2016-05-02 18:28:32,623 Node[0] Epoch[83] Batch [150] Speed: 616.56 samples/sec Train-accuracy=0.987187
2016-05-02 18:28:43,018 Node[0] Epoch[83] Batch [200] Speed: 615.70 samples/sec Train-accuracy=0.983906
2016-05-02 18:28:53,345 Node[0] Epoch[83] Batch [250] Speed: 619.78 samples/sec Train-accuracy=0.986094
2016-05-02 18:29:03,713 Node[0] Epoch[83] Batch [300] Speed: 617.27 samples/sec Train-accuracy=0.990781
2016-05-02 18:29:14,086 Node[0] Epoch[83] Batch [350] Speed: 616.99 samples/sec Train-accuracy=0.988281
2016-05-02 18:29:22,596 Node[0] Epoch[83] Resetting Data Iterator
2016-05-02 18:29:22,597 Node[0] Epoch[83] Time cost=81.106
2016-05-02 18:29:22,759 Node[0] Saved checkpoint to "cifar10/resnet-0084.params"
2016-05-02 18:29:24,666 Node[0] Epoch[83] Validation-accuracy=0.918970
2016-05-02 18:29:35,078 Node[0] Epoch[84] Batch [50] Speed: 617.88 samples/sec Train-accuracy=0.987812
2016-05-02 18:29:45,377 Node[0] Epoch[84] Batch [100] Speed: 621.46 samples/sec Train-accuracy=0.990156
2016-05-02 18:29:55,732 Node[0] Epoch[84] Batch [150] Speed: 618.06 samples/sec Train-accuracy=0.989531
2016-05-02 18:30:06,109 Node[0] Epoch[84] Batch [200] Speed: 616.79 samples/sec Train-accuracy=0.990469
2016-05-02 18:30:16,468 Node[0] Epoch[84] Batch [250] Speed: 617.83 samples/sec Train-accuracy=0.986719
2016-05-02 18:30:26,788 Node[0] Epoch[84] Batch [300] Speed: 620.18 samples/sec Train-accuracy=0.991563
2016-05-02 18:30:37,131 Node[0] Epoch[84] Batch [350] Speed: 618.78 samples/sec Train-accuracy=0.992969
2016-05-02 18:30:45,607 Node[0] Epoch[84] Resetting Data Iterator
2016-05-02 18:30:45,607 Node[0] Epoch[84] Time cost=80.941
2016-05-02 18:30:45,769 Node[0] Saved checkpoint to "cifar10/resnet-0085.params"
2016-05-02 18:30:47,689 Node[0] Epoch[84] Validation-accuracy=0.921675
2016-05-02 18:30:58,106 Node[0] Epoch[85] Batch [50] Speed: 617.60 samples/sec Train-accuracy=0.990938
2016-05-02 18:31:08,487 Node[0] Epoch[85] Batch [100] Speed: 616.52 samples/sec Train-accuracy=0.989375
2016-05-02 18:31:18,832 Node[0] Epoch[85] Batch [150] Speed: 618.69 samples/sec Train-accuracy=0.991406
2016-05-02 18:31:29,197 Node[0] Epoch[85] Batch [200] Speed: 617.44 samples/sec Train-accuracy=0.990313
2016-05-02 18:31:39,533 Node[0] Epoch[85] Batch [250] Speed: 619.22 samples/sec Train-accuracy=0.989375
2016-05-02 18:31:49,878 Node[0] Epoch[85] Batch [300] Speed: 618.70 samples/sec Train-accuracy=0.992812
2016-05-02 18:32:00,273 Node[0] Epoch[85] Batch [350] Speed: 615.68 samples/sec Train-accuracy=0.993594
2016-05-02 18:32:08,538 Node[0] Epoch[85] Resetting Data Iterator
2016-05-02 18:32:08,539 Node[0] Epoch[85] Time cost=80.849
2016-05-02 18:32:08,704 Node[0] Saved checkpoint to "cifar10/resnet-0086.params"
2016-05-02 18:32:10,654 Node[0] Epoch[85] Validation-accuracy=0.920473
2016-05-02 18:32:21,058 Node[0] Epoch[86] Batch [50] Speed: 618.41 samples/sec Train-accuracy=0.990000
2016-05-02 18:32:31,407 Node[0] Epoch[86] Batch [100] Speed: 618.46 samples/sec Train-accuracy=0.990938
2016-05-02 18:32:41,760 Node[0] Epoch[86] Batch [150] Speed: 618.18 samples/sec Train-accuracy=0.990938
2016-05-02 18:32:52,114 Node[0] Epoch[86] Batch [200] Speed: 618.13 samples/sec Train-accuracy=0.990469
2016-05-02 18:33:02,442 Node[0] Epoch[86] Batch [250] Speed: 619.70 samples/sec Train-accuracy=0.991719
2016-05-02 18:33:12,779 Node[0] Epoch[86] Batch [300] Speed: 619.13 samples/sec Train-accuracy=0.994219
2016-05-02 18:33:23,158 Node[0] Epoch[86] Batch [350] Speed: 616.67 samples/sec Train-accuracy=0.991563
2016-05-02 18:33:31,633 Node[0] Epoch[86] Resetting Data Iterator
2016-05-02 18:33:31,634 Node[0] Epoch[86] Time cost=80.980
2016-05-02 18:33:31,794 Node[0] Saved checkpoint to "cifar10/resnet-0087.params"
2016-05-02 18:33:33,691 Node[0] Epoch[86] Validation-accuracy=0.921575
2016-05-02 18:33:44,055 Node[0] Epoch[87] Batch [50] Speed: 620.76 samples/sec Train-accuracy=0.992188
2016-05-02 18:33:54,427 Node[0] Epoch[87] Batch [100] Speed: 617.06 samples/sec Train-accuracy=0.993437
2016-05-02 18:34:04,769 Node[0] Epoch[87] Batch [150] Speed: 618.84 samples/sec Train-accuracy=0.993437
2016-05-02 18:34:15,117 Node[0] Epoch[87] Batch [200] Speed: 618.54 samples/sec Train-accuracy=0.992656
2016-05-02 18:34:25,461 Node[0] Epoch[87] Batch [250] Speed: 618.68 samples/sec Train-accuracy=0.991250
2016-05-02 18:34:35,887 Node[0] Epoch[87] Batch [300] Speed: 613.89 samples/sec Train-accuracy=0.992344
2016-05-02 18:34:46,258 Node[0] Epoch[87] Batch [350] Speed: 617.10 samples/sec Train-accuracy=0.994531
2016-05-02 18:34:54,526 Node[0] Epoch[87] Resetting Data Iterator
2016-05-02 18:34:54,526 Node[0] Epoch[87] Time cost=80.835
2016-05-02 18:34:54,695 Node[0] Saved checkpoint to "cifar10/resnet-0088.params"
2016-05-02 18:34:56,588 Node[0] Epoch[87] Validation-accuracy=0.920773
2016-05-02 18:35:06,974 Node[0] Epoch[88] Batch [50] Speed: 619.49 samples/sec Train-accuracy=0.992812
2016-05-02 18:35:17,355 Node[0] Epoch[88] Batch [100] Speed: 616.53 samples/sec Train-accuracy=0.994062
2016-05-02 18:35:27,685 Node[0] Epoch[88] Batch [150] Speed: 619.62 samples/sec Train-accuracy=0.990625
2016-05-02 18:35:38,054 Node[0] Epoch[88] Batch [200] Speed: 617.24 samples/sec Train-accuracy=0.993125
2016-05-02 18:35:48,415 Node[0] Epoch[88] Batch [250] Speed: 617.71 samples/sec Train-accuracy=0.992188
2016-05-02 18:35:58,773 Node[0] Epoch[88] Batch [300] Speed: 617.90 samples/sec Train-accuracy=0.993750
2016-05-02 18:36:09,145 Node[0] Epoch[88] Batch [350] Speed: 617.05 samples/sec Train-accuracy=0.994062
2016-05-02 18:36:17,642 Node[0] Epoch[88] Resetting Data Iterator
2016-05-02 18:36:17,642 Node[0] Epoch[88] Time cost=81.054
2016-05-02 18:36:17,804 Node[0] Saved checkpoint to "cifar10/resnet-0089.params"
2016-05-02 18:36:19,910 Node[0] Epoch[88] Validation-accuracy=0.921776
2016-05-02 18:36:30,273 Node[0] Epoch[89] Batch [50] Speed: 620.85 samples/sec Train-accuracy=0.993594
2016-05-02 18:36:40,616 Node[0] Epoch[89] Batch [100] Speed: 618.79 samples/sec Train-accuracy=0.994531
2016-05-02 18:36:51,026 Node[0] Epoch[89] Batch [150] Speed: 614.81 samples/sec Train-accuracy=0.994219
2016-05-02 18:37:01,400 Node[0] Epoch[89] Batch [200] Speed: 616.93 samples/sec Train-accuracy=0.991875
2016-05-02 18:37:11,757 Node[0] Epoch[89] Batch [250] Speed: 617.93 samples/sec Train-accuracy=0.993437
2016-05-02 18:37:22,157 Node[0] Epoch[89] Batch [300] Speed: 615.40 samples/sec Train-accuracy=0.996563
2016-05-02 18:37:32,566 Node[0] Epoch[89] Batch [350] Speed: 614.90 samples/sec Train-accuracy=0.995625
2016-05-02 18:37:41,074 Node[0] Epoch[89] Resetting Data Iterator
2016-05-02 18:37:41,074 Node[0] Epoch[89] Time cost=81.164
2016-05-02 18:37:41,237 Node[0] Saved checkpoint to "cifar10/resnet-0090.params"
2016-05-02 18:37:43,141 Node[0] Epoch[89] Validation-accuracy=0.921975
2016-05-02 18:37:53,573 Node[0] Epoch[90] Batch [50] Speed: 616.76 samples/sec Train-accuracy=0.993437
2016-05-02 18:38:03,862 Node[0] Epoch[90] Batch [100] Speed: 622.04 samples/sec Train-accuracy=0.994687
2016-05-02 18:38:14,135 Node[0] Epoch[90] Batch [150] Speed: 622.97 samples/sec Train-accuracy=0.994062
2016-05-02 18:38:24,505 Node[0] Epoch[90] Batch [200] Speed: 617.23 samples/sec Train-accuracy=0.995469
2016-05-02 18:38:34,879 Node[0] Epoch[90] Batch [250] Speed: 616.95 samples/sec Train-accuracy=0.995000
2016-05-02 18:38:45,274 Node[0] Epoch[90] Batch [300] Speed: 615.69 samples/sec Train-accuracy=0.994375
2016-05-02 18:38:55,644 Node[0] Epoch[90] Batch [350] Speed: 617.17 samples/sec Train-accuracy=0.995781
2016-05-02 18:39:03,847 Node[0] Epoch[90] Resetting Data Iterator
2016-05-02 18:39:03,847 Node[0] Epoch[90] Time cost=80.706
2016-05-02 18:39:04,008 Node[0] Saved checkpoint to "cifar10/resnet-0091.params"
2016-05-02 18:39:05,896 Node[0] Epoch[90] Validation-accuracy=0.921575
2016-05-02 18:39:16,295 Node[0] Epoch[91] Batch [50] Speed: 618.67 samples/sec Train-accuracy=0.995313
2016-05-02 18:39:26,654 Node[0] Epoch[91] Batch [100] Speed: 617.86 samples/sec Train-accuracy=0.994687
2016-05-02 18:39:37,024 Node[0] Epoch[91] Batch [150] Speed: 617.19 samples/sec Train-accuracy=0.994219
2016-05-02 18:39:47,376 Node[0] Epoch[91] Batch [200] Speed: 618.25 samples/sec Train-accuracy=0.993281
2016-05-02 18:39:57,744 Node[0] Epoch[91] Batch [250] Speed: 617.26 samples/sec Train-accuracy=0.994062
2016-05-02 18:40:08,073 Node[0] Epoch[91] Batch [300] Speed: 619.68 samples/sec Train-accuracy=0.995313
2016-05-02 18:40:18,453 Node[0] Epoch[91] Batch [350] Speed: 616.55 samples/sec Train-accuracy=0.995156
2016-05-02 18:40:26,904 Node[0] Epoch[91] Resetting Data Iterator
2016-05-02 18:40:26,904 Node[0] Epoch[91] Time cost=81.008
2016-05-02 18:40:27,066 Node[0] Saved checkpoint to "cifar10/resnet-0092.params"
2016-05-02 18:40:29,004 Node[0] Epoch[91] Validation-accuracy=0.922276
2016-05-02 18:40:39,428 Node[0] Epoch[92] Batch [50] Speed: 617.23 samples/sec Train-accuracy=0.992969
2016-05-02 18:40:49,799 Node[0] Epoch[92] Batch [100] Speed: 617.15 samples/sec Train-accuracy=0.994687
2016-05-02 18:41:00,166 Node[0] Epoch[92] Batch [150] Speed: 617.36 samples/sec Train-accuracy=0.996406
2016-05-02 18:41:10,532 Node[0] Epoch[92] Batch [200] Speed: 617.42 samples/sec Train-accuracy=0.995156
2016-05-02 18:41:20,900 Node[0] Epoch[92] Batch [250] Speed: 617.29 samples/sec Train-accuracy=0.996094
2016-05-02 18:41:31,279 Node[0] Epoch[92] Batch [300] Speed: 616.66 samples/sec Train-accuracy=0.995781
2016-05-02 18:41:41,667 Node[0] Epoch[92] Batch [350] Speed: 616.11 samples/sec Train-accuracy=0.995781
2016-05-02 18:41:50,199 Node[0] Epoch[92] Resetting Data Iterator
2016-05-02 18:41:50,200 Node[0] Epoch[92] Time cost=81.195
2016-05-02 18:41:50,361 Node[0] Saved checkpoint to "cifar10/resnet-0093.params"
2016-05-02 18:41:52,287 Node[0] Epoch[92] Validation-accuracy=0.922476
2016-05-02 18:42:02,687 Node[0] Epoch[93] Batch [50] Speed: 618.62 samples/sec Train-accuracy=0.995156
2016-05-02 18:42:13,023 Node[0] Epoch[93] Batch [100] Speed: 619.20 samples/sec Train-accuracy=0.994375
2016-05-02 18:42:23,346 Node[0] Epoch[93] Batch [150] Speed: 620.00 samples/sec Train-accuracy=0.993906
2016-05-02 18:42:33,660 Node[0] Epoch[93] Batch [200] Speed: 620.51 samples/sec Train-accuracy=0.995313
2016-05-02 18:42:44,038 Node[0] Epoch[93] Batch [250] Speed: 616.71 samples/sec Train-accuracy=0.995469
2016-05-02 18:42:54,461 Node[0] Epoch[93] Batch [300] Speed: 614.06 samples/sec Train-accuracy=0.995156
2016-05-02 18:43:04,901 Node[0] Epoch[93] Batch [350] Speed: 613.04 samples/sec Train-accuracy=0.996719
2016-05-02 18:43:13,163 Node[0] Epoch[93] Resetting Data Iterator
2016-05-02 18:43:13,163 Node[0] Epoch[93] Time cost=80.875
2016-05-02 18:43:13,328 Node[0] Saved checkpoint to "cifar10/resnet-0094.params"
2016-05-02 18:43:15,227 Node[0] Epoch[93] Validation-accuracy=0.922576
2016-05-02 18:43:25,591 Node[0] Epoch[94] Batch [50] Speed: 620.78 samples/sec Train-accuracy=0.993750
2016-05-02 18:43:35,999 Node[0] Epoch[94] Batch [100] Speed: 614.94 samples/sec Train-accuracy=0.994687
2016-05-02 18:43:46,393 Node[0] Epoch[94] Batch [150] Speed: 615.74 samples/sec Train-accuracy=0.995781
2016-05-02 18:43:56,757 Node[0] Epoch[94] Batch [200] Speed: 617.56 samples/sec Train-accuracy=0.995781
2016-05-02 18:44:07,143 Node[0] Epoch[94] Batch [250] Speed: 616.26 samples/sec Train-accuracy=0.995625
2016-05-02 18:44:17,520 Node[0] Epoch[94] Batch [300] Speed: 616.73 samples/sec Train-accuracy=0.996406
2016-05-02 18:44:27,835 Node[0] Epoch[94] Batch [350] Speed: 620.50 samples/sec Train-accuracy=0.997188
2016-05-02 18:44:36,331 Node[0] Epoch[94] Resetting Data Iterator
2016-05-02 18:44:36,331 Node[0] Epoch[94] Time cost=81.104
2016-05-02 18:44:36,496 Node[0] Saved checkpoint to "cifar10/resnet-0095.params"
2016-05-02 18:44:38,394 Node[0] Epoch[94] Validation-accuracy=0.921875
2016-05-02 18:44:48,809 Node[0] Epoch[95] Batch [50] Speed: 617.82 samples/sec Train-accuracy=0.995938
2016-05-02 18:44:59,188 Node[0] Epoch[95] Batch [100] Speed: 616.62 samples/sec Train-accuracy=0.996406
2016-05-02 18:45:09,481 Node[0] Epoch[95] Batch [150] Speed: 621.78 samples/sec Train-accuracy=0.996250
2016-05-02 18:45:19,822 Node[0] Epoch[95] Batch [200] Speed: 618.94 samples/sec Train-accuracy=0.995938
2016-05-02 18:45:30,183 Node[0] Epoch[95] Batch [250] Speed: 617.69 samples/sec Train-accuracy=0.996250
2016-05-02 18:45:40,566 Node[0] Epoch[95] Batch [300] Speed: 616.44 samples/sec Train-accuracy=0.996406
2016-05-02 18:45:50,991 Node[0] Epoch[95] Batch [350] Speed: 613.93 samples/sec Train-accuracy=0.997656
2016-05-02 18:45:59,274 Node[0] Epoch[95] Resetting Data Iterator
2016-05-02 18:45:59,275 Node[0] Epoch[95] Time cost=80.881
2016-05-02 18:45:59,442 Node[0] Saved checkpoint to "cifar10/resnet-0096.params"
2016-05-02 18:46:01,321 Node[0] Epoch[95] Validation-accuracy=0.920873
2016-05-02 18:46:11,662 Node[0] Epoch[96] Batch [50] Speed: 622.15 samples/sec Train-accuracy=0.995781
2016-05-02 18:46:22,004 Node[0] Epoch[96] Batch [100] Speed: 618.87 samples/sec Train-accuracy=0.996250
2016-05-02 18:46:32,342 Node[0] Epoch[96] Batch [150] Speed: 619.12 samples/sec Train-accuracy=0.995938
2016-05-02 18:46:42,657 Node[0] Epoch[96] Batch [200] Speed: 620.41 samples/sec Train-accuracy=0.995156
2016-05-02 18:46:53,042 Node[0] Epoch[96] Batch [250] Speed: 616.32 samples/sec Train-accuracy=0.996875
2016-05-02 18:47:03,439 Node[0] Epoch[96] Batch [300] Speed: 615.54 samples/sec Train-accuracy=0.996250
2016-05-02 18:47:13,809 Node[0] Epoch[96] Batch [350] Speed: 617.21 samples/sec Train-accuracy=0.997031
2016-05-02 18:47:22,313 Node[0] Epoch[96] Resetting Data Iterator
2016-05-02 18:47:22,313 Node[0] Epoch[96] Time cost=80.992
2016-05-02 18:47:22,473 Node[0] Saved checkpoint to "cifar10/resnet-0097.params"
2016-05-02 18:47:24,525 Node[0] Epoch[96] Validation-accuracy=0.922172
2016-05-02 18:47:34,884 Node[0] Epoch[97] Batch [50] Speed: 621.10 samples/sec Train-accuracy=0.996875
2016-05-02 18:47:45,207 Node[0] Epoch[97] Batch [100] Speed: 620.01 samples/sec Train-accuracy=0.997188
2016-05-02 18:47:55,579 Node[0] Epoch[97] Batch [150] Speed: 617.07 samples/sec Train-accuracy=0.995938
2016-05-02 18:48:05,951 Node[0] Epoch[97] Batch [200] Speed: 617.06 samples/sec Train-accuracy=0.994687
2016-05-02 18:48:16,307 Node[0] Epoch[97] Batch [250] Speed: 617.98 samples/sec Train-accuracy=0.996563
2016-05-02 18:48:26,658 Node[0] Epoch[97] Batch [300] Speed: 618.36 samples/sec Train-accuracy=0.997812
2016-05-02 18:48:37,031 Node[0] Epoch[97] Batch [350] Speed: 617.00 samples/sec Train-accuracy=0.997031
2016-05-02 18:48:45,519 Node[0] Epoch[97] Resetting Data Iterator
2016-05-02 18:48:45,519 Node[0] Epoch[97] Time cost=80.994
2016-05-02 18:48:45,684 Node[0] Saved checkpoint to "cifar10/resnet-0098.params"
2016-05-02 18:48:47,591 Node[0] Epoch[97] Validation-accuracy=0.922175
2016-05-02 18:48:57,992 Node[0] Epoch[98] Batch [50] Speed: 618.59 samples/sec Train-accuracy=0.997656
2016-05-02 18:49:08,380 Node[0] Epoch[98] Batch [100] Speed: 616.08 samples/sec Train-accuracy=0.996875
2016-05-02 18:49:18,719 Node[0] Epoch[98] Batch [150] Speed: 619.04 samples/sec Train-accuracy=0.995625
2016-05-02 18:49:29,064 Node[0] Epoch[98] Batch [200] Speed: 618.69 samples/sec Train-accuracy=0.997500
2016-05-02 18:49:39,394 Node[0] Epoch[98] Batch [250] Speed: 619.53 samples/sec Train-accuracy=0.995469
2016-05-02 18:49:49,651 Node[0] Epoch[98] Batch [300] Speed: 623.96 samples/sec Train-accuracy=0.997188
2016-05-02 18:49:59,949 Node[0] Epoch[98] Batch [350] Speed: 621.53 samples/sec Train-accuracy=0.997500
2016-05-02 18:50:08,208 Node[0] Epoch[98] Resetting Data Iterator
2016-05-02 18:50:08,208 Node[0] Epoch[98] Time cost=80.617
2016-05-02 18:50:08,371 Node[0] Saved checkpoint to "cifar10/resnet-0099.params"
2016-05-02 18:50:10,290 Node[0] Epoch[98] Validation-accuracy=0.920172
2016-05-02 18:50:20,633 Node[0] Epoch[99] Batch [50] Speed: 622.05 samples/sec Train-accuracy=0.995938
2016-05-02 18:50:30,983 Node[0] Epoch[99] Batch [100] Speed: 618.36 samples/sec Train-accuracy=0.998281
2016-05-02 18:50:41,383 Node[0] Epoch[99] Batch [150] Speed: 615.43 samples/sec Train-accuracy=0.997500
2016-05-02 18:50:51,770 Node[0] Epoch[99] Batch [200] Speed: 616.18 samples/sec Train-accuracy=0.997344
2016-05-02 18:51:02,086 Node[0] Epoch[99] Batch [250] Speed: 620.43 samples/sec Train-accuracy=0.995938
2016-05-02 18:51:12,396 Node[0] Epoch[99] Batch [300] Speed: 620.77 samples/sec Train-accuracy=0.997500
2016-05-02 18:51:22,757 Node[0] Epoch[99] Batch [350] Speed: 617.69 samples/sec Train-accuracy=0.996563
2016-05-02 18:51:31,242 Node[0] Epoch[99] Resetting Data Iterator
2016-05-02 18:51:31,242 Node[0] Epoch[99] Time cost=80.951
2016-05-02 18:51:31,404 Node[0] Saved checkpoint to "cifar10/resnet-0100.params"
2016-05-02 18:51:33,328 Node[0] Epoch[99] Validation-accuracy=0.922175
2016-05-02 18:51:43,714 Node[0] Epoch[100] Batch [50] Speed: 619.43 samples/sec Train-accuracy=0.996875
2016-05-02 18:51:54,010 Node[0] Epoch[100] Batch [100] Speed: 621.62 samples/sec Train-accuracy=0.996875
2016-05-02 18:52:04,372 Node[0] Epoch[100] Batch [150] Speed: 617.62 samples/sec Train-accuracy=0.995781
2016-05-02 18:52:14,682 Node[0] Epoch[100] Batch [200] Speed: 620.77 samples/sec Train-accuracy=0.997500
2016-05-02 18:52:25,023 Node[0] Epoch[100] Batch [250] Speed: 618.93 samples/sec Train-accuracy=0.996563
2016-05-02 18:52:35,355 Node[0] Epoch[100] Batch [300] Speed: 619.47 samples/sec Train-accuracy=0.997812
2016-05-02 18:52:45,650 Node[0] Epoch[100] Batch [350] Speed: 621.67 samples/sec Train-accuracy=0.997812
2016-05-02 18:52:54,137 Node[0] Epoch[100] Resetting Data Iterator
2016-05-02 18:52:54,137 Node[0] Epoch[100] Time cost=80.809
2016-05-02 18:52:54,299 Node[0] Saved checkpoint to "cifar10/resnet-0101.params"
2016-05-02 18:52:56,178 Node[0] Epoch[100] Validation-accuracy=0.922476
2016-05-02 18:53:06,469 Node[0] Epoch[101] Batch [50] Speed: 625.13 samples/sec Train-accuracy=0.996563
2016-05-02 18:53:16,826 Node[0] Epoch[101] Batch [100] Speed: 618.00 samples/sec Train-accuracy=0.997500
2016-05-02 18:53:27,188 Node[0] Epoch[101] Batch [150] Speed: 617.65 samples/sec Train-accuracy=0.997500
2016-05-02 18:53:37,534 Node[0] Epoch[101] Batch [200] Speed: 618.61 samples/sec Train-accuracy=0.996875
2016-05-02 18:53:47,874 Node[0] Epoch[101] Batch [250] Speed: 619.00 samples/sec Train-accuracy=0.997188
2016-05-02 18:53:58,288 Node[0] Epoch[101] Batch [300] Speed: 614.53 samples/sec Train-accuracy=0.998125
2016-05-02 18:54:08,666 Node[0] Epoch[101] Batch [350] Speed: 616.74 samples/sec Train-accuracy=0.997969
2016-05-02 18:54:16,996 Node[0] Epoch[101] Resetting Data Iterator
2016-05-02 18:54:16,996 Node[0] Epoch[101] Time cost=80.818
2016-05-02 18:54:17,158 Node[0] Saved checkpoint to "cifar10/resnet-0102.params"
2016-05-02 18:54:19,049 Node[0] Epoch[101] Validation-accuracy=0.922376
2016-05-02 18:54:29,350 Node[0] Epoch[102] Batch [50] Speed: 624.56 samples/sec Train-accuracy=0.995938
2016-05-02 18:54:39,715 Node[0] Epoch[102] Batch [100] Speed: 617.43 samples/sec Train-accuracy=0.997969
2016-05-02 18:54:50,052 Node[0] Epoch[102] Batch [150] Speed: 619.21 samples/sec Train-accuracy=0.998437
2016-05-02 18:55:00,438 Node[0] Epoch[102] Batch [200] Speed: 616.24 samples/sec Train-accuracy=0.996719
2016-05-02 18:55:10,770 Node[0] Epoch[102] Batch [250] Speed: 619.43 samples/sec Train-accuracy=0.996719
2016-05-02 18:55:21,104 Node[0] Epoch[102] Batch [300] Speed: 619.31 samples/sec Train-accuracy=0.998125
2016-05-02 18:55:31,440 Node[0] Epoch[102] Batch [350] Speed: 619.20 samples/sec Train-accuracy=0.998437
2016-05-02 18:55:39,858 Node[0] Epoch[102] Resetting Data Iterator
2016-05-02 18:55:39,859 Node[0] Epoch[102] Time cost=80.809
2016-05-02 18:55:40,023 Node[0] Saved checkpoint to "cifar10/resnet-0103.params"
2016-05-02 18:55:41,923 Node[0] Epoch[102] Validation-accuracy=0.923177
2016-05-02 18:55:52,309 Node[0] Epoch[103] Batch [50] Speed: 619.56 samples/sec Train-accuracy=0.997812
2016-05-02 18:56:02,671 Node[0] Epoch[103] Batch [100] Speed: 617.64 samples/sec Train-accuracy=0.997656
2016-05-02 18:56:13,059 Node[0] Epoch[103] Batch [150] Speed: 616.10 samples/sec Train-accuracy=0.997500
2016-05-02 18:56:23,430 Node[0] Epoch[103] Batch [200] Speed: 617.11 samples/sec Train-accuracy=0.997656
2016-05-02 18:56:33,783 Node[0] Epoch[103] Batch [250] Speed: 618.19 samples/sec Train-accuracy=0.997344
2016-05-02 18:56:44,106 Node[0] Epoch[103] Batch [300] Speed: 620.01 samples/sec Train-accuracy=0.998125
2016-05-02 18:56:54,476 Node[0] Epoch[103] Batch [350] Speed: 617.20 samples/sec Train-accuracy=0.997500
2016-05-02 18:57:02,739 Node[0] Epoch[103] Resetting Data Iterator
2016-05-02 18:57:02,739 Node[0] Epoch[103] Time cost=80.816
2016-05-02 18:57:02,896 Node[0] Saved checkpoint to "cifar10/resnet-0104.params"
2016-05-02 18:57:04,815 Node[0] Epoch[103] Validation-accuracy=0.920573
2016-05-02 18:57:15,161 Node[0] Epoch[104] Batch [50] Speed: 621.82 samples/sec Train-accuracy=0.997656
2016-05-02 18:57:25,534 Node[0] Epoch[104] Batch [100] Speed: 617.01 samples/sec Train-accuracy=0.997344
2016-05-02 18:57:35,869 Node[0] Epoch[104] Batch [150] Speed: 619.28 samples/sec Train-accuracy=0.996563
2016-05-02 18:57:46,243 Node[0] Epoch[104] Batch [200] Speed: 616.90 samples/sec Train-accuracy=0.997969
2016-05-02 18:57:56,586 Node[0] Epoch[104] Batch [250] Speed: 618.82 samples/sec Train-accuracy=0.997031
2016-05-02 18:58:06,945 Node[0] Epoch[104] Batch [300] Speed: 617.79 samples/sec Train-accuracy=0.997969
2016-05-02 18:58:17,253 Node[0] Epoch[104] Batch [350] Speed: 620.94 samples/sec Train-accuracy=0.998125
2016-05-02 18:58:25,751 Node[0] Epoch[104] Resetting Data Iterator
2016-05-02 18:58:25,752 Node[0] Epoch[104] Time cost=80.936
2016-05-02 18:58:25,914 Node[0] Saved checkpoint to "cifar10/resnet-0105.params"
2016-05-02 18:58:27,971 Node[0] Epoch[104] Validation-accuracy=0.920985
2016-05-02 18:58:38,394 Node[0] Epoch[105] Batch [50] Speed: 617.20 samples/sec Train-accuracy=0.997656
2016-05-02 18:58:48,663 Node[0] Epoch[105] Batch [100] Speed: 623.27 samples/sec Train-accuracy=0.997344
2016-05-02 18:58:58,961 Node[0] Epoch[105] Batch [150] Speed: 621.47 samples/sec Train-accuracy=0.997812
2016-05-02 18:59:09,283 Node[0] Epoch[105] Batch [200] Speed: 620.08 samples/sec Train-accuracy=0.997344
2016-05-02 18:59:19,585 Node[0] Epoch[105] Batch [250] Speed: 621.27 samples/sec Train-accuracy=0.997969
2016-05-02 18:59:29,879 Node[0] Epoch[105] Batch [300] Speed: 621.69 samples/sec Train-accuracy=0.997969
2016-05-02 18:59:40,271 Node[0] Epoch[105] Batch [350] Speed: 615.87 samples/sec Train-accuracy=0.998125
2016-05-02 18:59:48,817 Node[0] Epoch[105] Resetting Data Iterator
2016-05-02 18:59:48,817 Node[0] Epoch[105] Time cost=80.846
2016-05-02 18:59:48,985 Node[0] Saved checkpoint to "cifar10/resnet-0106.params"
2016-05-02 18:59:50,860 Node[0] Epoch[105] Validation-accuracy=0.923578
2016-05-02 19:00:01,185 Node[0] Epoch[106] Batch [50] Speed: 623.04 samples/sec Train-accuracy=0.996719
2016-05-02 19:00:11,522 Node[0] Epoch[106] Batch [100] Speed: 619.15 samples/sec Train-accuracy=0.997969
2016-05-02 19:00:21,851 Node[0] Epoch[106] Batch [150] Speed: 619.62 samples/sec Train-accuracy=0.998125
2016-05-02 19:00:32,206 Node[0] Epoch[106] Batch [200] Speed: 618.09 samples/sec Train-accuracy=0.997188
2016-05-02 19:00:42,533 Node[0] Epoch[106] Batch [250] Speed: 619.77 samples/sec Train-accuracy=0.997812
2016-05-02 19:00:52,903 Node[0] Epoch[106] Batch [300] Speed: 617.16 samples/sec Train-accuracy=0.998125
2016-05-02 19:01:03,301 Node[0] Epoch[106] Batch [350] Speed: 615.53 samples/sec Train-accuracy=0.998125
2016-05-02 19:01:11,610 Node[0] Epoch[106] Resetting Data Iterator
2016-05-02 19:01:11,610 Node[0] Epoch[106] Time cost=80.750
2016-05-02 19:01:11,773 Node[0] Saved checkpoint to "cifar10/resnet-0107.params"
2016-05-02 19:01:13,656 Node[0] Epoch[106] Validation-accuracy=0.921474
2016-05-02 19:01:24,011 Node[0] Epoch[107] Batch [50] Speed: 621.29 samples/sec Train-accuracy=0.998281
2016-05-02 19:01:34,389 Node[0] Epoch[107] Batch [100] Speed: 616.74 samples/sec Train-accuracy=0.998437
2016-05-02 19:01:44,763 Node[0] Epoch[107] Batch [150] Speed: 616.94 samples/sec Train-accuracy=0.997500
2016-05-02 19:01:55,087 Node[0] Epoch[107] Batch [200] Speed: 619.93 samples/sec Train-accuracy=0.998125
2016-05-02 19:02:05,441 Node[0] Epoch[107] Batch [250] Speed: 618.10 samples/sec Train-accuracy=0.997656
2016-05-02 19:02:15,862 Node[0] Epoch[107] Batch [300] Speed: 614.19 samples/sec Train-accuracy=0.998906
2016-05-02 19:02:26,201 Node[0] Epoch[107] Batch [350] Speed: 619.05 samples/sec Train-accuracy=0.998437
2016-05-02 19:02:34,726 Node[0] Epoch[107] Resetting Data Iterator
2016-05-02 19:02:34,726 Node[0] Epoch[107] Time cost=81.070
2016-05-02 19:02:34,886 Node[0] Saved checkpoint to "cifar10/resnet-0108.params"
2016-05-02 19:02:36,791 Node[0] Epoch[107] Validation-accuracy=0.921875
2016-05-02 19:02:47,129 Node[0] Epoch[108] Batch [50] Speed: 622.36 samples/sec Train-accuracy=0.997656
2016-05-02 19:02:57,522 Node[0] Epoch[108] Batch [100] Speed: 615.80 samples/sec Train-accuracy=0.998906
2016-05-02 19:03:07,878 Node[0] Epoch[108] Batch [150] Speed: 617.98 samples/sec Train-accuracy=0.997812
2016-05-02 19:03:18,239 Node[0] Epoch[108] Batch [200] Speed: 617.73 samples/sec Train-accuracy=0.998281
2016-05-02 19:03:28,577 Node[0] Epoch[108] Batch [250] Speed: 619.08 samples/sec Train-accuracy=0.998750
2016-05-02 19:03:38,907 Node[0] Epoch[108] Batch [300] Speed: 619.62 samples/sec Train-accuracy=0.997656
2016-05-02 19:03:49,259 Node[0] Epoch[108] Batch [350] Speed: 618.23 samples/sec Train-accuracy=0.999219
2016-05-02 19:03:57,712 Node[0] Epoch[108] Resetting Data Iterator
2016-05-02 19:03:57,712 Node[0] Epoch[108] Time cost=80.921
2016-05-02 19:03:57,871 Node[0] Saved checkpoint to "cifar10/resnet-0109.params"
2016-05-02 19:03:59,773 Node[0] Epoch[108] Validation-accuracy=0.923578
2016-05-02 19:04:10,241 Node[0] Epoch[109] Batch [50] Speed: 614.59 samples/sec Train-accuracy=0.998281
2016-05-02 19:04:20,619 Node[0] Epoch[109] Batch [100] Speed: 616.72 samples/sec Train-accuracy=0.997969
2016-05-02 19:04:30,866 Node[0] Epoch[109] Batch [150] Speed: 624.62 samples/sec Train-accuracy=0.997969
2016-05-02 19:04:41,172 Node[0] Epoch[109] Batch [200] Speed: 621.01 samples/sec Train-accuracy=0.998125
2016-05-02 19:04:51,565 Node[0] Epoch[109] Batch [250] Speed: 615.76 samples/sec Train-accuracy=0.996875
2016-05-02 19:05:01,959 Node[0] Epoch[109] Batch [300] Speed: 615.76 samples/sec Train-accuracy=0.998906
2016-05-02 19:05:12,306 Node[0] Epoch[109] Batch [350] Speed: 618.58 samples/sec Train-accuracy=0.997969
2016-05-02 19:05:20,552 Node[0] Epoch[109] Resetting Data Iterator
2016-05-02 19:05:20,552 Node[0] Epoch[109] Time cost=80.778
2016-05-02 19:05:20,714 Node[0] Saved checkpoint to "cifar10/resnet-0110.params"
2016-05-02 19:05:22,604 Node[0] Epoch[109] Validation-accuracy=0.922576
2016-05-02 19:05:32,926 Node[0] Epoch[110] Batch [50] Speed: 623.25 samples/sec Train-accuracy=0.997656
2016-05-02 19:05:43,198 Node[0] Epoch[110] Batch [100] Speed: 623.07 samples/sec Train-accuracy=0.998281
2016-05-02 19:05:53,517 Node[0] Epoch[110] Batch [150] Speed: 620.22 samples/sec Train-accuracy=0.998125
2016-05-02 19:06:03,899 Node[0] Epoch[110] Batch [200] Speed: 616.52 samples/sec Train-accuracy=0.997812
2016-05-02 19:06:14,277 Node[0] Epoch[110] Batch [250] Speed: 616.69 samples/sec Train-accuracy=0.997031
2016-05-02 19:06:24,651 Node[0] Epoch[110] Batch [300] Speed: 616.95 samples/sec Train-accuracy=0.998281
2016-05-02 19:06:34,988 Node[0] Epoch[110] Batch [350] Speed: 619.16 samples/sec Train-accuracy=0.999219
2016-05-02 19:06:43,436 Node[0] Epoch[110] Resetting Data Iterator
2016-05-02 19:06:43,436 Node[0] Epoch[110] Time cost=80.831
2016-05-02 19:06:43,599 Node[0] Saved checkpoint to "cifar10/resnet-0111.params"
2016-05-02 19:06:45,524 Node[0] Epoch[110] Validation-accuracy=0.921374
2016-05-02 19:06:55,871 Node[0] Epoch[111] Batch [50] Speed: 621.83 samples/sec Train-accuracy=0.998437
2016-05-02 19:07:06,223 Node[0] Epoch[111] Batch [100] Speed: 618.25 samples/sec Train-accuracy=0.998281
2016-05-02 19:07:16,610 Node[0] Epoch[111] Batch [150] Speed: 616.18 samples/sec Train-accuracy=0.998125
2016-05-02 19:07:26,957 Node[0] Epoch[111] Batch [200] Speed: 618.56 samples/sec Train-accuracy=0.998125
2016-05-02 19:07:37,308 Node[0] Epoch[111] Batch [250] Speed: 618.27 samples/sec Train-accuracy=0.997656
2016-05-02 19:07:47,677 Node[0] Epoch[111] Batch [300] Speed: 617.25 samples/sec Train-accuracy=0.999062
2016-05-02 19:07:58,047 Node[0] Epoch[111] Batch [350] Speed: 617.17 samples/sec Train-accuracy=0.997656
2016-05-02 19:08:06,362 Node[0] Epoch[111] Resetting Data Iterator
2016-05-02 19:08:06,362 Node[0] Epoch[111] Time cost=80.838
2016-05-02 19:08:06,520 Node[0] Saved checkpoint to "cifar10/resnet-0112.params"
2016-05-02 19:08:08,397 Node[0] Epoch[111] Validation-accuracy=0.923778
2016-05-02 19:08:18,775 Node[0] Epoch[112] Batch [50] Speed: 619.88 samples/sec Train-accuracy=0.997656
2016-05-02 19:08:29,068 Node[0] Epoch[112] Batch [100] Speed: 621.83 samples/sec Train-accuracy=0.998750
2016-05-02 19:08:39,350 Node[0] Epoch[112] Batch [150] Speed: 622.47 samples/sec Train-accuracy=0.998125
2016-05-02 19:08:49,708 Node[0] Epoch[112] Batch [200] Speed: 617.87 samples/sec Train-accuracy=0.997812
2016-05-02 19:09:00,071 Node[0] Epoch[112] Batch [250] Speed: 617.61 samples/sec Train-accuracy=0.997969
2016-05-02 19:09:10,476 Node[0] Epoch[112] Batch [300] Speed: 615.06 samples/sec Train-accuracy=0.998437
2016-05-02 19:09:20,860 Node[0] Epoch[112] Batch [350] Speed: 616.40 samples/sec Train-accuracy=0.998906
2016-05-02 19:09:29,258 Node[0] Epoch[112] Resetting Data Iterator
2016-05-02 19:09:29,258 Node[0] Epoch[112] Time cost=80.861
2016-05-02 19:09:29,418 Node[0] Saved checkpoint to "cifar10/resnet-0113.params"
2016-05-02 19:09:31,570 Node[0] Epoch[112] Validation-accuracy=0.922271
2016-05-02 19:09:41,880 Node[0] Epoch[113] Batch [50] Speed: 623.96 samples/sec Train-accuracy=0.999062
2016-05-02 19:09:52,242 Node[0] Epoch[113] Batch [100] Speed: 617.66 samples/sec Train-accuracy=0.998281
2016-05-02 19:10:02,529 Node[0] Epoch[113] Batch [150] Speed: 622.20 samples/sec Train-accuracy=0.999062
2016-05-02 19:10:12,852 Node[0] Epoch[113] Batch [200] Speed: 619.96 samples/sec Train-accuracy=0.999062
2016-05-02 19:10:23,172 Node[0] Epoch[113] Batch [250] Speed: 620.15 samples/sec Train-accuracy=0.998437
2016-05-02 19:10:33,545 Node[0] Epoch[113] Batch [300] Speed: 617.01 samples/sec Train-accuracy=0.998437
2016-05-02 19:10:43,924 Node[0] Epoch[113] Batch [350] Speed: 616.64 samples/sec Train-accuracy=0.997969
2016-05-02 19:10:52,436 Node[0] Epoch[113] Resetting Data Iterator
2016-05-02 19:10:52,436 Node[0] Epoch[113] Time cost=80.866
2016-05-02 19:10:52,595 Node[0] Saved checkpoint to "cifar10/resnet-0114.params"
2016-05-02 19:10:54,496 Node[0] Epoch[113] Validation-accuracy=0.922776
2016-05-02 19:11:04,768 Node[0] Epoch[114] Batch [50] Speed: 626.34 samples/sec Train-accuracy=0.998906
2016-05-02 19:11:15,160 Node[0] Epoch[114] Batch [100] Speed: 615.88 samples/sec Train-accuracy=0.998594
2016-05-02 19:11:25,493 Node[0] Epoch[114] Batch [150] Speed: 619.33 samples/sec Train-accuracy=0.998906
2016-05-02 19:11:35,830 Node[0] Epoch[114] Batch [200] Speed: 619.18 samples/sec Train-accuracy=0.999062
2016-05-02 19:11:46,160 Node[0] Epoch[114] Batch [250] Speed: 619.57 samples/sec Train-accuracy=0.997656
2016-05-02 19:11:56,506 Node[0] Epoch[114] Batch [300] Speed: 618.61 samples/sec Train-accuracy=0.999062
2016-05-02 19:12:06,893 Node[0] Epoch[114] Batch [350] Speed: 616.17 samples/sec Train-accuracy=0.998125
2016-05-02 19:12:15,146 Node[0] Epoch[114] Resetting Data Iterator
2016-05-02 19:12:15,146 Node[0] Epoch[114] Time cost=80.651
2016-05-02 19:12:15,309 Node[0] Saved checkpoint to "cifar10/resnet-0115.params"
2016-05-02 19:12:17,191 Node[0] Epoch[114] Validation-accuracy=0.924179
2016-05-02 19:12:27,477 Node[0] Epoch[115] Batch [50] Speed: 625.50 samples/sec Train-accuracy=0.998125
2016-05-02 19:12:37,830 Node[0] Epoch[115] Batch [100] Speed: 618.19 samples/sec Train-accuracy=0.997969
2016-05-02 19:12:48,164 Node[0] Epoch[115] Batch [150] Speed: 619.39 samples/sec Train-accuracy=0.998281
2016-05-02 19:12:58,521 Node[0] Epoch[115] Batch [200] Speed: 617.92 samples/sec Train-accuracy=0.997969
2016-05-02 19:13:08,886 Node[0] Epoch[115] Batch [250] Speed: 617.47 samples/sec Train-accuracy=0.999219
2016-05-02 19:13:19,263 Node[0] Epoch[115] Batch [300] Speed: 616.81 samples/sec Train-accuracy=0.998750
2016-05-02 19:13:29,548 Node[0] Epoch[115] Batch [350] Speed: 622.24 samples/sec Train-accuracy=0.999219
2016-05-02 19:13:37,971 Node[0] Epoch[115] Resetting Data Iterator
2016-05-02 19:13:37,971 Node[0] Epoch[115] Time cost=80.780
2016-05-02 19:13:38,133 Node[0] Saved checkpoint to "cifar10/resnet-0116.params"
2016-05-02 19:13:40,023 Node[0] Epoch[115] Validation-accuracy=0.924780
2016-05-02 19:13:50,459 Node[0] Epoch[116] Batch [50] Speed: 616.54 samples/sec Train-accuracy=0.998437
2016-05-02 19:14:00,820 Node[0] Epoch[116] Batch [100] Speed: 617.67 samples/sec Train-accuracy=0.998594
2016-05-02 19:14:11,167 Node[0] Epoch[116] Batch [150] Speed: 618.57 samples/sec Train-accuracy=0.998437
2016-05-02 19:14:21,554 Node[0] Epoch[116] Batch [200] Speed: 616.18 samples/sec Train-accuracy=0.998125
2016-05-02 19:14:31,916 Node[0] Epoch[116] Batch [250] Speed: 617.64 samples/sec Train-accuracy=0.998281
2016-05-02 19:14:42,262 Node[0] Epoch[116] Batch [300] Speed: 618.60 samples/sec Train-accuracy=0.998281
2016-05-02 19:14:52,605 Node[0] Epoch[116] Batch [350] Speed: 618.81 samples/sec Train-accuracy=0.997344
2016-05-02 19:15:01,051 Node[0] Epoch[116] Resetting Data Iterator
2016-05-02 19:15:01,052 Node[0] Epoch[116] Time cost=81.029
2016-05-02 19:15:01,214 Node[0] Saved checkpoint to "cifar10/resnet-0117.params"
2016-05-02 19:15:03,098 Node[0] Epoch[116] Validation-accuracy=0.924179
2016-05-02 19:15:13,419 Node[0] Epoch[117] Batch [50] Speed: 623.45 samples/sec Train-accuracy=0.997656
2016-05-02 19:15:23,757 Node[0] Epoch[117] Batch [100] Speed: 619.09 samples/sec Train-accuracy=0.998437
2016-05-02 19:15:34,133 Node[0] Epoch[117] Batch [150] Speed: 616.79 samples/sec Train-accuracy=0.999062
2016-05-02 19:15:44,419 Node[0] Epoch[117] Batch [200] Speed: 622.24 samples/sec Train-accuracy=0.999219
2016-05-02 19:15:54,685 Node[0] Epoch[117] Batch [250] Speed: 623.43 samples/sec Train-accuracy=0.999219
2016-05-02 19:16:04,966 Node[0] Epoch[117] Batch [300] Speed: 622.51 samples/sec Train-accuracy=0.998281
2016-05-02 19:16:15,306 Node[0] Epoch[117] Batch [350] Speed: 618.97 samples/sec Train-accuracy=0.998750
2016-05-02 19:16:23,544 Node[0] Epoch[117] Resetting Data Iterator
2016-05-02 19:16:23,544 Node[0] Epoch[117] Time cost=80.446
2016-05-02 19:16:23,707 Node[0] Saved checkpoint to "cifar10/resnet-0118.params"
2016-05-02 19:16:25,602 Node[0] Epoch[117] Validation-accuracy=0.923077
2016-05-02 19:16:35,950 Node[0] Epoch[118] Batch [50] Speed: 621.70 samples/sec Train-accuracy=0.998750
2016-05-02 19:16:46,260 Node[0] Epoch[118] Batch [100] Speed: 620.76 samples/sec Train-accuracy=0.999062
2016-05-02 19:16:56,546 Node[0] Epoch[118] Batch [150] Speed: 622.24 samples/sec Train-accuracy=0.999062
2016-05-02 19:17:06,833 Node[0] Epoch[118] Batch [200] Speed: 622.14 samples/sec Train-accuracy=0.998594
2016-05-02 19:17:17,193 Node[0] Epoch[118] Batch [250] Speed: 617.77 samples/sec Train-accuracy=0.998594
2016-05-02 19:17:27,536 Node[0] Epoch[118] Batch [300] Speed: 618.81 samples/sec Train-accuracy=0.999375
2016-05-02 19:17:37,841 Node[0] Epoch[118] Batch [350] Speed: 621.05 samples/sec Train-accuracy=0.999219
2016-05-02 19:17:46,285 Node[0] Epoch[118] Resetting Data Iterator
2016-05-02 19:17:46,286 Node[0] Epoch[118] Time cost=80.684
2016-05-02 19:17:46,446 Node[0] Saved checkpoint to "cifar10/resnet-0119.params"
2016-05-02 19:17:48,333 Node[0] Epoch[118] Validation-accuracy=0.922877
2016-05-02 19:17:58,731 Node[0] Epoch[119] Batch [50] Speed: 618.74 samples/sec Train-accuracy=0.998594
2016-05-02 19:18:09,084 Node[0] Epoch[119] Batch [100] Speed: 618.20 samples/sec Train-accuracy=0.998437
2016-05-02 19:18:19,456 Node[0] Epoch[119] Batch [150] Speed: 617.06 samples/sec Train-accuracy=0.999219
2016-05-02 19:18:29,739 Node[0] Epoch[119] Batch [200] Speed: 622.44 samples/sec Train-accuracy=0.998594
2016-05-02 19:18:40,107 Node[0] Epoch[119] Batch [250] Speed: 617.26 samples/sec Train-accuracy=0.997656
2016-05-02 19:18:50,507 Node[0] Epoch[119] Batch [300] Speed: 615.43 samples/sec Train-accuracy=0.998594
2016-05-02 19:19:00,874 Node[0] Epoch[119] Batch [350] Speed: 617.32 samples/sec Train-accuracy=0.998281
2016-05-02 19:19:09,115 Node[0] Epoch[119] Resetting Data Iterator
2016-05-02 19:19:09,116 Node[0] Epoch[119] Time cost=80.782
2016-05-02 19:19:09,276 Node[0] Saved checkpoint to "cifar10/resnet-0120.params"
2016-05-02 19:19:11,155 Node[0] Epoch[119] Validation-accuracy=0.921775
2016-05-02 19:19:21,532 Node[0] Epoch[120] Batch [50] Speed: 620.03 samples/sec Train-accuracy=0.998750
2016-05-02 19:19:31,812 Node[0] Epoch[120] Batch [100] Speed: 622.61 samples/sec Train-accuracy=0.998125
2016-05-02 19:19:42,110 Node[0] Epoch[120] Batch [150] Speed: 621.50 samples/sec Train-accuracy=0.999219
2016-05-02 19:19:52,424 Node[0] Epoch[120] Batch [200] Speed: 620.51 samples/sec Train-accuracy=0.998437
2016-05-02 19:20:02,813 Node[0] Epoch[120] Batch [250] Speed: 616.08 samples/sec Train-accuracy=0.999219
2016-05-02 19:20:13,137 Node[0] Epoch[120] Batch [300] Speed: 619.90 samples/sec Train-accuracy=0.998594
2016-05-02 19:20:23,498 Node[0] Epoch[120] Batch [350] Speed: 617.74 samples/sec Train-accuracy=0.998281
2016-05-02 19:20:31,974 Node[0] Epoch[120] Resetting Data Iterator
2016-05-02 19:20:31,974 Node[0] Epoch[120] Time cost=80.819
2016-05-02 19:20:32,139 Node[0] Saved checkpoint to "cifar10/resnet-0121.params"
2016-05-02 19:20:34,232 Node[0] Epoch[120] Validation-accuracy=0.921084
2016-05-02 19:20:44,532 Node[0] Epoch[121] Batch [50] Speed: 624.61 samples/sec Train-accuracy=0.997969
2016-05-02 19:20:54,907 Node[0] Epoch[121] Batch [100] Speed: 616.88 samples/sec Train-accuracy=0.998750
2016-05-02 19:21:05,193 Node[0] Epoch[121] Batch [150] Speed: 622.21 samples/sec Train-accuracy=0.998437
2016-05-02 19:21:15,500 Node[0] Epoch[121] Batch [200] Speed: 620.95 samples/sec Train-accuracy=0.998125
2016-05-02 19:21:25,829 Node[0] Epoch[121] Batch [250] Speed: 619.64 samples/sec Train-accuracy=0.999375
2016-05-02 19:21:36,195 Node[0] Epoch[121] Batch [300] Speed: 617.41 samples/sec Train-accuracy=0.998437
2016-05-02 19:21:46,536 Node[0] Epoch[121] Batch [350] Speed: 618.92 samples/sec Train-accuracy=0.998594
2016-05-02 19:21:55,002 Node[0] Epoch[121] Resetting Data Iterator
2016-05-02 19:21:55,002 Node[0] Epoch[121] Time cost=80.770
2016-05-02 19:21:55,163 Node[0] Saved checkpoint to "cifar10/resnet-0122.params"
2016-05-02 19:21:57,038 Node[0] Epoch[121] Validation-accuracy=0.922676
2016-05-02 19:22:07,307 Node[0] Epoch[122] Batch [50] Speed: 626.49 samples/sec Train-accuracy=0.998594
2016-05-02 19:22:17,670 Node[0] Epoch[122] Batch [100] Speed: 617.59 samples/sec Train-accuracy=0.998594
2016-05-02 19:22:28,012 Node[0] Epoch[122] Batch [150] Speed: 618.89 samples/sec Train-accuracy=0.999062
2016-05-02 19:22:38,346 Node[0] Epoch[122] Batch [200] Speed: 619.33 samples/sec Train-accuracy=0.998906
2016-05-02 19:22:48,653 Node[0] Epoch[122] Batch [250] Speed: 620.95 samples/sec Train-accuracy=0.998750
2016-05-02 19:22:59,024 Node[0] Epoch[122] Batch [300] Speed: 617.15 samples/sec Train-accuracy=0.999375
2016-05-02 19:23:09,360 Node[0] Epoch[122] Batch [350] Speed: 619.18 samples/sec Train-accuracy=0.999844
2016-05-02 19:23:17,658 Node[0] Epoch[122] Resetting Data Iterator
2016-05-02 19:23:17,658 Node[0] Epoch[122] Time cost=80.620
2016-05-02 19:23:17,822 Node[0] Saved checkpoint to "cifar10/resnet-0123.params"
2016-05-02 19:23:19,713 Node[0] Epoch[122] Validation-accuracy=0.923377
2016-05-02 19:23:30,058 Node[0] Epoch[123] Batch [50] Speed: 621.95 samples/sec Train-accuracy=0.998437
2016-05-02 19:23:40,379 Node[0] Epoch[123] Batch [100] Speed: 620.09 samples/sec Train-accuracy=0.998437
2016-05-02 19:23:50,683 Node[0] Epoch[123] Batch [150] Speed: 621.12 samples/sec Train-accuracy=0.998594
2016-05-02 19:24:00,975 Node[0] Epoch[123] Batch [200] Speed: 621.88 samples/sec Train-accuracy=0.998906
2016-05-02 19:24:11,301 Node[0] Epoch[123] Batch [250] Speed: 619.78 samples/sec Train-accuracy=0.999219
2016-05-02 19:24:21,641 Node[0] Epoch[123] Batch [300] Speed: 618.99 samples/sec Train-accuracy=0.998437
2016-05-02 19:24:32,004 Node[0] Epoch[123] Batch [350] Speed: 617.56 samples/sec Train-accuracy=0.998594
2016-05-02 19:24:40,492 Node[0] Epoch[123] Resetting Data Iterator
2016-05-02 19:24:40,492 Node[0] Epoch[123] Time cost=80.779
2016-05-02 19:24:40,654 Node[0] Saved checkpoint to "cifar10/resnet-0124.params"
2016-05-02 19:24:42,549 Node[0] Epoch[123] Validation-accuracy=0.922376
2016-05-02 19:24:52,749 Node[0] Epoch[124] Batch [50] Speed: 630.72 samples/sec Train-accuracy=0.998906
2016-05-02 19:25:03,074 Node[0] Epoch[124] Batch [100] Speed: 619.88 samples/sec Train-accuracy=0.998594
2016-05-02 19:25:13,427 Node[0] Epoch[124] Batch [150] Speed: 618.20 samples/sec Train-accuracy=0.999062
2016-05-02 19:25:23,782 Node[0] Epoch[124] Batch [200] Speed: 618.08 samples/sec Train-accuracy=0.999531
2016-05-02 19:25:34,100 Node[0] Epoch[124] Batch [250] Speed: 620.30 samples/sec Train-accuracy=0.997812
2016-05-02 19:25:44,501 Node[0] Epoch[124] Batch [300] Speed: 615.37 samples/sec Train-accuracy=0.998437
2016-05-02 19:25:54,820 Node[0] Epoch[124] Batch [350] Speed: 620.25 samples/sec Train-accuracy=0.998437
2016-05-02 19:26:03,209 Node[0] Epoch[124] Resetting Data Iterator
2016-05-02 19:26:03,209 Node[0] Epoch[124] Time cost=80.660
2016-05-02 19:26:03,369 Node[0] Saved checkpoint to "cifar10/resnet-0125.params"
2016-05-02 19:26:05,265 Node[0] Epoch[124] Validation-accuracy=0.922175
2016-05-02 19:26:15,601 Node[0] Epoch[125] Batch [50] Speed: 622.43 samples/sec Train-accuracy=0.998437
2016-05-02 19:26:25,896 Node[0] Epoch[125] Batch [100] Speed: 621.65 samples/sec Train-accuracy=0.999219
2016-05-02 19:26:36,201 Node[0] Epoch[125] Batch [150] Speed: 621.10 samples/sec Train-accuracy=0.998750
2016-05-02 19:26:46,498 Node[0] Epoch[125] Batch [200] Speed: 621.55 samples/sec Train-accuracy=0.998906
2016-05-02 19:26:56,836 Node[0] Epoch[125] Batch [250] Speed: 619.09 samples/sec Train-accuracy=0.998437
2016-05-02 19:27:07,193 Node[0] Epoch[125] Batch [300] Speed: 617.98 samples/sec Train-accuracy=0.998437
2016-05-02 19:27:17,527 Node[0] Epoch[125] Batch [350] Speed: 619.33 samples/sec Train-accuracy=0.999687
2016-05-02 19:27:25,780 Node[0] Epoch[125] Resetting Data Iterator
2016-05-02 19:27:25,780 Node[0] Epoch[125] Time cost=80.515
2016-05-02 19:27:25,943 Node[0] Saved checkpoint to "cifar10/resnet-0126.params"
2016-05-02 19:27:27,820 Node[0] Epoch[125] Validation-accuracy=0.922776
2016-05-02 19:27:38,141 Node[0] Epoch[126] Batch [50] Speed: 623.40 samples/sec Train-accuracy=0.998750
2016-05-02 19:27:48,406 Node[0] Epoch[126] Batch [100] Speed: 623.54 samples/sec Train-accuracy=0.999219
2016-05-02 19:27:58,678 Node[0] Epoch[126] Batch [150] Speed: 623.08 samples/sec Train-accuracy=0.998750
2016-05-02 19:28:08,975 Node[0] Epoch[126] Batch [200] Speed: 621.53 samples/sec Train-accuracy=0.998594
2016-05-02 19:28:19,334 Node[0] Epoch[126] Batch [250] Speed: 617.83 samples/sec Train-accuracy=0.999375
2016-05-02 19:28:29,633 Node[0] Epoch[126] Batch [300] Speed: 621.43 samples/sec Train-accuracy=0.998594
2016-05-02 19:28:39,952 Node[0] Epoch[126] Batch [350] Speed: 620.24 samples/sec Train-accuracy=0.999062
2016-05-02 19:28:48,443 Node[0] Epoch[126] Resetting Data Iterator
2016-05-02 19:28:48,443 Node[0] Epoch[126] Time cost=80.622
2016-05-02 19:28:48,613 Node[0] Saved checkpoint to "cifar10/resnet-0127.params"
2016-05-02 19:28:50,498 Node[0] Epoch[126] Validation-accuracy=0.922276
2016-05-02 19:29:00,821 Node[0] Epoch[127] Batch [50] Speed: 623.15 samples/sec Train-accuracy=0.999062
2016-05-02 19:29:11,131 Node[0] Epoch[127] Batch [100] Speed: 620.79 samples/sec Train-accuracy=0.999219
2016-05-02 19:29:21,437 Node[0] Epoch[127] Batch [150] Speed: 621.03 samples/sec Train-accuracy=0.999219
2016-05-02 19:29:31,826 Node[0] Epoch[127] Batch [200] Speed: 616.01 samples/sec Train-accuracy=0.999062
2016-05-02 19:29:42,196 Node[0] Epoch[127] Batch [250] Speed: 617.18 samples/sec Train-accuracy=0.998906
2016-05-02 19:29:52,570 Node[0] Epoch[127] Batch [300] Speed: 616.96 samples/sec Train-accuracy=0.999375
2016-05-02 19:30:02,921 Node[0] Epoch[127] Batch [350] Speed: 618.31 samples/sec Train-accuracy=0.999062
2016-05-02 19:30:11,130 Node[0] Epoch[127] Resetting Data Iterator
2016-05-02 19:30:11,130 Node[0] Epoch[127] Time cost=80.632
2016-05-02 19:30:11,294 Node[0] Saved checkpoint to "cifar10/resnet-0128.params"
2016-05-02 19:30:13,155 Node[0] Epoch[127] Validation-accuracy=0.922576
2016-05-02 19:30:23,470 Node[0] Epoch[128] Batch [50] Speed: 623.73 samples/sec Train-accuracy=0.998906
2016-05-02 19:30:33,718 Node[0] Epoch[128] Batch [100] Speed: 624.53 samples/sec Train-accuracy=0.998906
2016-05-02 19:30:44,031 Node[0] Epoch[128] Batch [150] Speed: 620.64 samples/sec Train-accuracy=0.999062
2016-05-02 19:30:54,338 Node[0] Epoch[128] Batch [200] Speed: 620.92 samples/sec Train-accuracy=0.998437
2016-05-02 19:31:04,670 Node[0] Epoch[128] Batch [250] Speed: 619.48 samples/sec Train-accuracy=0.999062
2016-05-02 19:31:14,969 Node[0] Epoch[128] Batch [300] Speed: 621.42 samples/sec Train-accuracy=0.998594
2016-05-02 19:31:25,322 Node[0] Epoch[128] Batch [350] Speed: 618.20 samples/sec Train-accuracy=0.998750
2016-05-02 19:31:33,775 Node[0] Epoch[128] Resetting Data Iterator
2016-05-02 19:31:33,775 Node[0] Epoch[128] Time cost=80.621
2016-05-02 19:31:33,938 Node[0] Saved checkpoint to "cifar10/resnet-0129.params"
2016-05-02 19:31:36,021 Node[0] Epoch[128] Validation-accuracy=0.922073
2016-05-02 19:31:46,266 Node[0] Epoch[129] Batch [50] Speed: 627.97 samples/sec Train-accuracy=0.998906
2016-05-02 19:31:56,620 Node[0] Epoch[129] Batch [100] Speed: 618.10 samples/sec Train-accuracy=0.998281
2016-05-02 19:32:06,892 Node[0] Epoch[129] Batch [150] Speed: 623.10 samples/sec Train-accuracy=0.999531
2016-05-02 19:32:17,190 Node[0] Epoch[129] Batch [200] Speed: 621.43 samples/sec Train-accuracy=0.998906
2016-05-02 19:32:27,512 Node[0] Epoch[129] Batch [250] Speed: 620.10 samples/sec Train-accuracy=0.998906
2016-05-02 19:32:37,836 Node[0] Epoch[129] Batch [300] Speed: 619.92 samples/sec Train-accuracy=0.999375
2016-05-02 19:32:48,136 Node[0] Epoch[129] Batch [350] Speed: 621.34 samples/sec Train-accuracy=0.998437
2016-05-02 19:32:56,592 Node[0] Epoch[129] Resetting Data Iterator
2016-05-02 19:32:56,592 Node[0] Epoch[129] Time cost=80.571
2016-05-02 19:32:56,757 Node[0] Saved checkpoint to "cifar10/resnet-0130.params"
2016-05-02 19:32:58,654 Node[0] Epoch[129] Validation-accuracy=0.924079
2016-05-02 19:33:09,020 Node[0] Epoch[130] Batch [50] Speed: 620.65 samples/sec Train-accuracy=0.999219
2016-05-02 19:33:19,328 Node[0] Epoch[130] Batch [100] Speed: 620.85 samples/sec Train-accuracy=0.998125
2016-05-02 19:33:29,561 Node[0] Epoch[130] Batch [150] Speed: 625.49 samples/sec Train-accuracy=0.998437
2016-05-02 19:33:39,898 Node[0] Epoch[130] Batch [200] Speed: 619.12 samples/sec Train-accuracy=0.998906
2016-05-02 19:33:50,203 Node[0] Epoch[130] Batch [250] Speed: 621.09 samples/sec Train-accuracy=0.999219
2016-05-02 19:34:00,517 Node[0] Epoch[130] Batch [300] Speed: 620.56 samples/sec Train-accuracy=0.999531
2016-05-02 19:34:10,838 Node[0] Epoch[130] Batch [350] Speed: 620.07 samples/sec Train-accuracy=0.998594
2016-05-02 19:34:19,093 Node[0] Epoch[130] Resetting Data Iterator
2016-05-02 19:34:19,094 Node[0] Epoch[130] Time cost=80.439
2016-05-02 19:34:19,256 Node[0] Saved checkpoint to "cifar10/resnet-0131.params"
2016-05-02 19:34:21,122 Node[0] Epoch[130] Validation-accuracy=0.922877
2016-05-02 19:34:31,396 Node[0] Epoch[131] Batch [50] Speed: 626.11 samples/sec Train-accuracy=0.999687
2016-05-02 19:34:41,722 Node[0] Epoch[131] Batch [100] Speed: 619.83 samples/sec Train-accuracy=0.998906
2016-05-02 19:34:52,044 Node[0] Epoch[131] Batch [150] Speed: 620.05 samples/sec Train-accuracy=0.999531
2016-05-02 19:35:02,425 Node[0] Epoch[131] Batch [200] Speed: 616.51 samples/sec Train-accuracy=0.998125
2016-05-02 19:35:12,681 Node[0] Epoch[131] Batch [250] Speed: 624.05 samples/sec Train-accuracy=0.999687
2016-05-02 19:35:22,924 Node[0] Epoch[131] Batch [300] Speed: 624.82 samples/sec Train-accuracy=0.999531
2016-05-02 19:35:33,218 Node[0] Epoch[131] Batch [350] Speed: 621.77 samples/sec Train-accuracy=0.998906
2016-05-02 19:35:41,744 Node[0] Epoch[131] Resetting Data Iterator
2016-05-02 19:35:41,745 Node[0] Epoch[131] Time cost=80.623
2016-05-02 19:35:41,910 Node[0] Saved checkpoint to "cifar10/resnet-0132.params"
2016-05-02 19:35:43,800 Node[0] Epoch[131] Validation-accuracy=0.922075
2016-05-02 19:35:54,144 Node[0] Epoch[132] Batch [50] Speed: 621.90 samples/sec Train-accuracy=0.999531
2016-05-02 19:36:04,531 Node[0] Epoch[132] Batch [100] Speed: 616.15 samples/sec Train-accuracy=0.999219
2016-05-02 19:36:14,894 Node[0] Epoch[132] Batch [150] Speed: 617.62 samples/sec Train-accuracy=0.999531
2016-05-02 19:36:25,170 Node[0] Epoch[132] Batch [200] Speed: 622.81 samples/sec Train-accuracy=0.999531
2016-05-02 19:36:35,475 Node[0] Epoch[132] Batch [250] Speed: 621.06 samples/sec Train-accuracy=0.998906
2016-05-02 19:36:45,832 Node[0] Epoch[132] Batch [300] Speed: 617.95 samples/sec Train-accuracy=0.998750
2016-05-02 19:36:56,158 Node[0] Epoch[132] Batch [350] Speed: 619.82 samples/sec Train-accuracy=0.998750
2016-05-02 19:37:04,646 Node[0] Epoch[132] Resetting Data Iterator
2016-05-02 19:37:04,647 Node[0] Epoch[132] Time cost=80.847
2016-05-02 19:37:04,808 Node[0] Saved checkpoint to "cifar10/resnet-0133.params"
2016-05-02 19:37:06,680 Node[0] Epoch[132] Validation-accuracy=0.922276
2016-05-02 19:37:17,064 Node[0] Epoch[133] Batch [50] Speed: 619.56 samples/sec Train-accuracy=0.998125
2016-05-02 19:37:27,390 Node[0] Epoch[133] Batch [100] Speed: 619.81 samples/sec Train-accuracy=0.998594
2016-05-02 19:37:37,665 Node[0] Epoch[133] Batch [150] Speed: 622.89 samples/sec Train-accuracy=0.998594
2016-05-02 19:37:47,908 Node[0] Epoch[133] Batch [200] Speed: 624.84 samples/sec Train-accuracy=0.998750
2016-05-02 19:37:58,228 Node[0] Epoch[133] Batch [250] Speed: 620.16 samples/sec Train-accuracy=0.999219
2016-05-02 19:38:08,532 Node[0] Epoch[133] Batch [300] Speed: 621.14 samples/sec Train-accuracy=0.999687
2016-05-02 19:38:18,843 Node[0] Epoch[133] Batch [350] Speed: 620.69 samples/sec Train-accuracy=0.998750
2016-05-02 19:38:27,124 Node[0] Epoch[133] Resetting Data Iterator
2016-05-02 19:38:27,124 Node[0] Epoch[133] Time cost=80.444
2016-05-02 19:38:27,288 Node[0] Saved checkpoint to "cifar10/resnet-0134.params"
2016-05-02 19:38:29,144 Node[0] Epoch[133] Validation-accuracy=0.922175
2016-05-02 19:38:39,481 Node[0] Epoch[134] Batch [50] Speed: 622.37 samples/sec Train-accuracy=0.998906
2016-05-02 19:38:49,804 Node[0] Epoch[134] Batch [100] Speed: 620.03 samples/sec Train-accuracy=0.998750
2016-05-02 19:39:00,177 Node[0] Epoch[134] Batch [150] Speed: 616.98 samples/sec Train-accuracy=0.998750
2016-05-02 19:39:10,570 Node[0] Epoch[134] Batch [200] Speed: 615.82 samples/sec Train-accuracy=0.998125
2016-05-02 19:39:20,930 Node[0] Epoch[134] Batch [250] Speed: 617.78 samples/sec Train-accuracy=0.999687
2016-05-02 19:39:31,270 Node[0] Epoch[134] Batch [300] Speed: 618.99 samples/sec Train-accuracy=0.999219
2016-05-02 19:39:41,588 Node[0] Epoch[134] Batch [350] Speed: 620.30 samples/sec Train-accuracy=0.998906
2016-05-02 19:39:50,066 Node[0] Epoch[134] Resetting Data Iterator
2016-05-02 19:39:50,067 Node[0] Epoch[134] Time cost=80.922
2016-05-02 19:39:50,226 Node[0] Saved checkpoint to "cifar10/resnet-0135.params"
2016-05-02 19:39:52,116 Node[0] Epoch[134] Validation-accuracy=0.922376
2016-05-02 19:40:02,472 Node[0] Epoch[135] Batch [50] Speed: 621.28 samples/sec Train-accuracy=0.999531
2016-05-02 19:40:12,893 Node[0] Epoch[135] Batch [100] Speed: 614.16 samples/sec Train-accuracy=0.999531
2016-05-02 19:40:23,239 Node[0] Epoch[135] Batch [150] Speed: 618.64 samples/sec Train-accuracy=0.999375
2016-05-02 19:40:33,637 Node[0] Epoch[135] Batch [200] Speed: 615.49 samples/sec Train-accuracy=0.999062
2016-05-02 19:40:43,947 Node[0] Epoch[135] Batch [250] Speed: 620.78 samples/sec Train-accuracy=0.998437
2016-05-02 19:40:54,285 Node[0] Epoch[135] Batch [300] Speed: 619.13 samples/sec Train-accuracy=0.999375
2016-05-02 19:41:04,686 Node[0] Epoch[135] Batch [350] Speed: 615.32 samples/sec Train-accuracy=0.999375
2016-05-02 19:41:12,998 Node[0] Epoch[135] Resetting Data Iterator
2016-05-02 19:41:12,999 Node[0] Epoch[135] Time cost=80.882
2016-05-02 19:41:13,163 Node[0] Saved checkpoint to "cifar10/resnet-0136.params"
2016-05-02 19:41:15,022 Node[0] Epoch[135] Validation-accuracy=0.922175
2016-05-02 19:41:25,372 Node[0] Epoch[136] Batch [50] Speed: 621.66 samples/sec Train-accuracy=0.998750
2016-05-02 19:41:35,619 Node[0] Epoch[136] Batch [100] Speed: 624.57 samples/sec Train-accuracy=0.999062
2016-05-02 19:41:45,929 Node[0] Epoch[136] Batch [150] Speed: 620.76 samples/sec Train-accuracy=0.998281
2016-05-02 19:41:56,277 Node[0] Epoch[136] Batch [200] Speed: 618.52 samples/sec Train-accuracy=0.998125
2016-05-02 19:42:06,586 Node[0] Epoch[136] Batch [250] Speed: 620.82 samples/sec Train-accuracy=0.999375
2016-05-02 19:42:16,966 Node[0] Epoch[136] Batch [300] Speed: 616.59 samples/sec Train-accuracy=0.999062
2016-05-02 19:42:27,309 Node[0] Epoch[136] Batch [350] Speed: 618.81 samples/sec Train-accuracy=0.999375
2016-05-02 19:42:35,800 Node[0] Epoch[136] Resetting Data Iterator
2016-05-02 19:42:35,800 Node[0] Epoch[136] Time cost=80.777
2016-05-02 19:42:35,965 Node[0] Saved checkpoint to "cifar10/resnet-0137.params"
2016-05-02 19:42:38,077 Node[0] Epoch[136] Validation-accuracy=0.924150
2016-05-02 19:42:48,444 Node[0] Epoch[137] Batch [50] Speed: 620.59 samples/sec Train-accuracy=0.998906
2016-05-02 19:42:58,810 Node[0] Epoch[137] Batch [100] Speed: 617.47 samples/sec Train-accuracy=0.999062
2016-05-02 19:43:09,167 Node[0] Epoch[137] Batch [150] Speed: 617.91 samples/sec Train-accuracy=0.999219
2016-05-02 19:43:19,428 Node[0] Epoch[137] Batch [200] Speed: 623.77 samples/sec Train-accuracy=0.999219
2016-05-02 19:43:29,738 Node[0] Epoch[137] Batch [250] Speed: 620.73 samples/sec Train-accuracy=0.998906
2016-05-02 19:43:40,045 Node[0] Epoch[137] Batch [300] Speed: 620.95 samples/sec Train-accuracy=0.999219
2016-05-02 19:43:50,367 Node[0] Epoch[137] Batch [350] Speed: 620.08 samples/sec Train-accuracy=0.999687
2016-05-02 19:43:58,823 Node[0] Epoch[137] Resetting Data Iterator
2016-05-02 19:43:58,824 Node[0] Epoch[137] Time cost=80.747
2016-05-02 19:43:58,987 Node[0] Saved checkpoint to "cifar10/resnet-0138.params"
2016-05-02 19:44:00,875 Node[0] Epoch[137] Validation-accuracy=0.924479
2016-05-02 19:44:11,217 Node[0] Epoch[138] Batch [50] Speed: 622.09 samples/sec Train-accuracy=0.999062
2016-05-02 19:44:21,568 Node[0] Epoch[138] Batch [100] Speed: 618.34 samples/sec Train-accuracy=0.998750
2016-05-02 19:44:31,883 Node[0] Epoch[138] Batch [150] Speed: 620.43 samples/sec Train-accuracy=0.999062
2016-05-02 19:44:42,229 Node[0] Epoch[138] Batch [200] Speed: 618.66 samples/sec Train-accuracy=0.998906
2016-05-02 19:44:52,506 Node[0] Epoch[138] Batch [250] Speed: 622.77 samples/sec Train-accuracy=0.999219
2016-05-02 19:45:02,832 Node[0] Epoch[138] Batch [300] Speed: 619.77 samples/sec Train-accuracy=0.999531
2016-05-02 19:45:13,141 Node[0] Epoch[138] Batch [350] Speed: 620.83 samples/sec Train-accuracy=0.999219
2016-05-02 19:45:21,416 Node[0] Epoch[138] Resetting Data Iterator
2016-05-02 19:45:21,416 Node[0] Epoch[138] Time cost=80.541
2016-05-02 19:45:21,580 Node[0] Saved checkpoint to "cifar10/resnet-0139.params"
2016-05-02 19:45:23,463 Node[0] Epoch[138] Validation-accuracy=0.923277
2016-05-02 19:45:33,800 Node[0] Epoch[139] Batch [50] Speed: 622.33 samples/sec Train-accuracy=0.999687
2016-05-02 19:45:44,037 Node[0] Epoch[139] Batch [100] Speed: 625.20 samples/sec Train-accuracy=0.999844
2016-05-02 19:45:54,271 Node[0] Epoch[139] Batch [150] Speed: 625.38 samples/sec Train-accuracy=0.999531
2016-05-02 19:46:04,505 Node[0] Epoch[139] Batch [200] Speed: 625.39 samples/sec Train-accuracy=0.999531
2016-05-02 19:46:14,840 Node[0] Epoch[139] Batch [250] Speed: 619.27 samples/sec Train-accuracy=0.999375
2016-05-02 19:46:25,191 Node[0] Epoch[139] Batch [300] Speed: 618.33 samples/sec Train-accuracy=0.999531
2016-05-02 19:46:35,570 Node[0] Epoch[139] Batch [350] Speed: 616.62 samples/sec Train-accuracy=0.999062
2016-05-02 19:46:44,061 Node[0] Epoch[139] Resetting Data Iterator
2016-05-02 19:46:44,061 Node[0] Epoch[139] Time cost=80.598
2016-05-02 19:46:44,225 Node[0] Saved checkpoint to "cifar10/resnet-0140.params"
2016-05-02 19:46:46,142 Node[0] Epoch[139] Validation-accuracy=0.920873
2016-05-02 19:46:56,503 Node[0] Epoch[140] Batch [50] Speed: 620.98 samples/sec Train-accuracy=0.999062
2016-05-02 19:47:06,781 Node[0] Epoch[140] Batch [100] Speed: 622.71 samples/sec Train-accuracy=0.999687
2016-05-02 19:47:17,054 Node[0] Epoch[140] Batch [150] Speed: 622.97 samples/sec Train-accuracy=0.999375
2016-05-02 19:47:27,310 Node[0] Epoch[140] Batch [200] Speed: 624.04 samples/sec Train-accuracy=0.998750
2016-05-02 19:47:37,648 Node[0] Epoch[140] Batch [250] Speed: 619.14 samples/sec Train-accuracy=0.999375
2016-05-02 19:47:48,005 Node[0] Epoch[140] Batch [300] Speed: 617.95 samples/sec Train-accuracy=0.999687
2016-05-02 19:47:58,339 Node[0] Epoch[140] Batch [350] Speed: 619.33 samples/sec Train-accuracy=0.999375
2016-05-02 19:48:06,800 Node[0] Epoch[140] Resetting Data Iterator
2016-05-02 19:48:06,800 Node[0] Epoch[140] Time cost=80.658
2016-05-02 19:48:06,963 Node[0] Saved checkpoint to "cifar10/resnet-0141.params"
2016-05-02 19:48:08,856 Node[0] Epoch[140] Validation-accuracy=0.923978
2016-05-02 19:48:19,179 Node[0] Epoch[141] Batch [50] Speed: 623.22 samples/sec Train-accuracy=0.999531
2016-05-02 19:48:29,520 Node[0] Epoch[141] Batch [100] Speed: 618.90 samples/sec Train-accuracy=0.999219
2016-05-02 19:48:39,825 Node[0] Epoch[141] Batch [150] Speed: 621.06 samples/sec Train-accuracy=0.999375
2016-05-02 19:48:50,154 Node[0] Epoch[141] Batch [200] Speed: 619.61 samples/sec Train-accuracy=0.999531
2016-05-02 19:49:00,519 Node[0] Epoch[141] Batch [250] Speed: 617.48 samples/sec Train-accuracy=0.999375
2016-05-02 19:49:10,849 Node[0] Epoch[141] Batch [300] Speed: 619.59 samples/sec Train-accuracy=0.999219
2016-05-02 19:49:21,219 Node[0] Epoch[141] Batch [350] Speed: 617.20 samples/sec Train-accuracy=0.999531
2016-05-02 19:49:29,465 Node[0] Epoch[141] Resetting Data Iterator
2016-05-02 19:49:29,465 Node[0] Epoch[141] Time cost=80.609
2016-05-02 19:49:29,626 Node[0] Saved checkpoint to "cifar10/resnet-0142.params"
2016-05-02 19:49:31,552 Node[0] Epoch[141] Validation-accuracy=0.924880
2016-05-02 19:49:41,812 Node[0] Epoch[142] Batch [50] Speed: 627.13 samples/sec Train-accuracy=0.999375
2016-05-02 19:49:52,095 Node[0] Epoch[142] Batch [100] Speed: 622.36 samples/sec Train-accuracy=0.999844
2016-05-02 19:50:02,386 Node[0] Epoch[142] Batch [150] Speed: 621.96 samples/sec Train-accuracy=0.999219
2016-05-02 19:50:12,743 Node[0] Epoch[142] Batch [200] Speed: 617.94 samples/sec Train-accuracy=0.999062
2016-05-02 19:50:23,042 Node[0] Epoch[142] Batch [250] Speed: 621.42 samples/sec Train-accuracy=0.999375
2016-05-02 19:50:33,393 Node[0] Epoch[142] Batch [300] Speed: 618.34 samples/sec Train-accuracy=0.999219
2016-05-02 19:50:43,715 Node[0] Epoch[142] Batch [350] Speed: 620.02 samples/sec Train-accuracy=0.998750
2016-05-02 19:50:52,177 Node[0] Epoch[142] Resetting Data Iterator
2016-05-02 19:50:52,177 Node[0] Epoch[142] Time cost=80.625
2016-05-02 19:50:52,342 Node[0] Saved checkpoint to "cifar10/resnet-0143.params"
2016-05-02 19:50:54,220 Node[0] Epoch[142] Validation-accuracy=0.924579
2016-05-02 19:51:04,513 Node[0] Epoch[143] Batch [50] Speed: 624.94 samples/sec Train-accuracy=0.999062
2016-05-02 19:51:14,822 Node[0] Epoch[143] Batch [100] Speed: 620.87 samples/sec Train-accuracy=0.999062
2016-05-02 19:51:25,099 Node[0] Epoch[143] Batch [150] Speed: 622.72 samples/sec Train-accuracy=0.999844
2016-05-02 19:51:35,384 Node[0] Epoch[143] Batch [200] Speed: 622.33 samples/sec Train-accuracy=0.999062
2016-05-02 19:51:45,775 Node[0] Epoch[143] Batch [250] Speed: 615.91 samples/sec Train-accuracy=0.999219
2016-05-02 19:51:56,151 Node[0] Epoch[143] Batch [300] Speed: 616.83 samples/sec Train-accuracy=0.999375
2016-05-02 19:52:06,372 Node[0] Epoch[143] Batch [350] Speed: 626.17 samples/sec Train-accuracy=0.999062
2016-05-02 19:52:14,590 Node[0] Epoch[143] Resetting Data Iterator
2016-05-02 19:52:14,590 Node[0] Epoch[143] Time cost=80.370
2016-05-02 19:52:14,755 Node[0] Saved checkpoint to "cifar10/resnet-0144.params"
2016-05-02 19:52:16,650 Node[0] Epoch[143] Validation-accuracy=0.926683
2016-05-02 19:52:27,110 Node[0] Epoch[144] Batch [50] Speed: 615.14 samples/sec Train-accuracy=0.999844
2016-05-02 19:52:37,489 Node[0] Epoch[144] Batch [100] Speed: 616.60 samples/sec Train-accuracy=0.999375
2016-05-02 19:52:47,786 Node[0] Epoch[144] Batch [150] Speed: 621.60 samples/sec Train-accuracy=0.998750
2016-05-02 19:52:58,117 Node[0] Epoch[144] Batch [200] Speed: 619.48 samples/sec Train-accuracy=0.999687
2016-05-02 19:53:08,456 Node[0] Epoch[144] Batch [250] Speed: 619.04 samples/sec Train-accuracy=0.999687
2016-05-02 19:53:18,807 Node[0] Epoch[144] Batch [300] Speed: 618.34 samples/sec Train-accuracy=0.998594
2016-05-02 19:53:29,100 Node[0] Epoch[144] Batch [350] Speed: 621.75 samples/sec Train-accuracy=0.999062
2016-05-02 19:53:37,587 Node[0] Epoch[144] Resetting Data Iterator
2016-05-02 19:53:37,587 Node[0] Epoch[144] Time cost=80.936
2016-05-02 19:53:37,748 Node[0] Saved checkpoint to "cifar10/resnet-0145.params"
2016-05-02 19:53:39,893 Node[0] Epoch[144] Validation-accuracy=0.924842
2016-05-02 19:53:50,202 Node[0] Epoch[145] Batch [50] Speed: 624.04 samples/sec Train-accuracy=0.999531
2016-05-02 19:54:00,561 Node[0] Epoch[145] Batch [100] Speed: 617.83 samples/sec Train-accuracy=0.999219
2016-05-02 19:54:10,923 Node[0] Epoch[145] Batch [150] Speed: 617.68 samples/sec Train-accuracy=0.999687
2016-05-02 19:54:21,159 Node[0] Epoch[145] Batch [200] Speed: 625.27 samples/sec Train-accuracy=0.998906
2016-05-02 19:54:31,421 Node[0] Epoch[145] Batch [250] Speed: 623.66 samples/sec Train-accuracy=0.999531
2016-05-02 19:54:41,761 Node[0] Epoch[145] Batch [300] Speed: 618.97 samples/sec Train-accuracy=0.999687
2016-05-02 19:54:52,113 Node[0] Epoch[145] Batch [350] Speed: 618.29 samples/sec Train-accuracy=0.999531
2016-05-02 19:55:00,632 Node[0] Epoch[145] Resetting Data Iterator
2016-05-02 19:55:00,633 Node[0] Epoch[145] Time cost=80.739
2016-05-02 19:55:00,794 Node[0] Saved checkpoint to "cifar10/resnet-0146.params"
2016-05-02 19:55:02,663 Node[0] Epoch[145] Validation-accuracy=0.923377
2016-05-02 19:55:12,963 Node[0] Epoch[146] Batch [50] Speed: 624.59 samples/sec Train-accuracy=0.999687
2016-05-02 19:55:23,203 Node[0] Epoch[146] Batch [100] Speed: 625.03 samples/sec Train-accuracy=0.998750
2016-05-02 19:55:33,501 Node[0] Epoch[146] Batch [150] Speed: 621.50 samples/sec Train-accuracy=0.999219
2016-05-02 19:55:43,839 Node[0] Epoch[146] Batch [200] Speed: 619.06 samples/sec Train-accuracy=0.999219
2016-05-02 19:55:54,156 Node[0] Epoch[146] Batch [250] Speed: 620.39 samples/sec Train-accuracy=0.998281
2016-05-02 19:56:04,483 Node[0] Epoch[146] Batch [300] Speed: 619.76 samples/sec Train-accuracy=0.999531
2016-05-02 19:56:14,834 Node[0] Epoch[146] Batch [350] Speed: 618.28 samples/sec Train-accuracy=0.998906
2016-05-02 19:56:23,086 Node[0] Epoch[146] Resetting Data Iterator
2016-05-02 19:56:23,086 Node[0] Epoch[146] Time cost=80.423
2016-05-02 19:56:23,253 Node[0] Saved checkpoint to "cifar10/resnet-0147.params"
2016-05-02 19:56:25,166 Node[0] Epoch[146] Validation-accuracy=0.925982
2016-05-02 19:56:35,476 Node[0] Epoch[147] Batch [50] Speed: 624.07 samples/sec Train-accuracy=0.999687
2016-05-02 19:56:45,869 Node[0] Epoch[147] Batch [100] Speed: 615.82 samples/sec Train-accuracy=0.999687
2016-05-02 19:56:56,215 Node[0] Epoch[147] Batch [150] Speed: 618.61 samples/sec Train-accuracy=0.999375
2016-05-02 19:57:06,446 Node[0] Epoch[147] Batch [200] Speed: 625.58 samples/sec Train-accuracy=0.999219
2016-05-02 19:57:16,691 Node[0] Epoch[147] Batch [250] Speed: 624.73 samples/sec Train-accuracy=0.999687
2016-05-02 19:57:26,996 Node[0] Epoch[147] Batch [300] Speed: 621.05 samples/sec Train-accuracy=0.999687
2016-05-02 19:57:37,342 Node[0] Epoch[147] Batch [350] Speed: 618.63 samples/sec Train-accuracy=0.999687
2016-05-02 19:57:45,800 Node[0] Epoch[147] Resetting Data Iterator
2016-05-02 19:57:45,800 Node[0] Epoch[147] Time cost=80.634
2016-05-02 19:57:45,963 Node[0] Saved checkpoint to "cifar10/resnet-0148.params"
2016-05-02 19:57:47,858 Node[0] Epoch[147] Validation-accuracy=0.924279
2016-05-02 19:57:58,161 Node[0] Epoch[148] Batch [50] Speed: 624.44 samples/sec Train-accuracy=0.999531
2016-05-02 19:58:08,551 Node[0] Epoch[148] Batch [100] Speed: 616.03 samples/sec Train-accuracy=0.999375
2016-05-02 19:58:18,898 Node[0] Epoch[148] Batch [150] Speed: 618.55 samples/sec Train-accuracy=0.999375
2016-05-02 19:58:29,199 Node[0] Epoch[148] Batch [200] Speed: 621.31 samples/sec Train-accuracy=0.999219
2016-05-02 19:58:39,483 Node[0] Epoch[148] Batch [250] Speed: 622.34 samples/sec Train-accuracy=0.999375
2016-05-02 19:58:49,780 Node[0] Epoch[148] Batch [300] Speed: 621.54 samples/sec Train-accuracy=0.999219
2016-05-02 19:59:00,027 Node[0] Epoch[148] Batch [350] Speed: 624.58 samples/sec Train-accuracy=0.999687
2016-05-02 19:59:08,499 Node[0] Epoch[148] Resetting Data Iterator
2016-05-02 19:59:08,499 Node[0] Epoch[148] Time cost=80.641
2016-05-02 19:59:08,665 Node[0] Saved checkpoint to "cifar10/resnet-0149.params"
2016-05-02 19:59:10,603 Node[0] Epoch[148] Validation-accuracy=0.923778
2016-05-02 19:59:20,944 Node[0] Epoch[149] Batch [50] Speed: 622.11 samples/sec Train-accuracy=0.999687
2016-05-02 19:59:31,280 Node[0] Epoch[149] Batch [100] Speed: 619.22 samples/sec Train-accuracy=0.999687
2016-05-02 19:59:41,556 Node[0] Epoch[149] Batch [150] Speed: 622.83 samples/sec Train-accuracy=0.999687
2016-05-02 19:59:51,818 Node[0] Epoch[149] Batch [200] Speed: 623.68 samples/sec Train-accuracy=0.999219
2016-05-02 20:00:02,163 Node[0] Epoch[149] Batch [250] Speed: 618.67 samples/sec Train-accuracy=0.999375
2016-05-02 20:00:12,508 Node[0] Epoch[149] Batch [300] Speed: 618.66 samples/sec Train-accuracy=0.999219
2016-05-02 20:00:22,855 Node[0] Epoch[149] Batch [350] Speed: 618.58 samples/sec Train-accuracy=0.999375
2016-05-02 20:00:31,109 Node[0] Epoch[149] Resetting Data Iterator
2016-05-02 20:00:31,109 Node[0] Epoch[149] Time cost=80.505
2016-05-02 20:00:31,273 Node[0] Saved checkpoint to "cifar10/resnet-0150.params"
2016-05-02 20:00:33,155 Node[0] Epoch[149] Validation-accuracy=0.925681
2016-05-02 20:00:43,505 Node[0] Epoch[150] Batch [50] Speed: 621.56 samples/sec Train-accuracy=0.999375
2016-05-02 20:00:53,782 Node[0] Epoch[150] Batch [100] Speed: 622.77 samples/sec Train-accuracy=0.999687
2016-05-02 20:01:04,047 Node[0] Epoch[150] Batch [150] Speed: 623.52 samples/sec Train-accuracy=0.999844
2016-05-02 20:01:14,366 Node[0] Epoch[150] Batch [200] Speed: 620.23 samples/sec Train-accuracy=0.999219
2016-05-02 20:01:24,685 Node[0] Epoch[150] Batch [250] Speed: 620.25 samples/sec Train-accuracy=0.999531
2016-05-02 20:01:35,050 Node[0] Epoch[150] Batch [300] Speed: 617.47 samples/sec Train-accuracy=0.999375
2016-05-02 20:01:45,432 Node[0] Epoch[150] Batch [350] Speed: 616.47 samples/sec Train-accuracy=0.999375
2016-05-02 20:01:53,911 Node[0] Epoch[150] Resetting Data Iterator
2016-05-02 20:01:53,912 Node[0] Epoch[150] Time cost=80.756
2016-05-02 20:01:54,074 Node[0] Saved checkpoint to "cifar10/resnet-0151.params"
2016-05-02 20:01:55,943 Node[0] Epoch[150] Validation-accuracy=0.923778
2016-05-02 20:02:06,185 Node[0] Epoch[151] Batch [50] Speed: 628.18 samples/sec Train-accuracy=0.999062
2016-05-02 20:02:16,496 Node[0] Epoch[151] Batch [100] Speed: 620.74 samples/sec Train-accuracy=0.999531
2016-05-02 20:02:26,861 Node[0] Epoch[151] Batch [150] Speed: 617.49 samples/sec Train-accuracy=0.999219
2016-05-02 20:02:37,199 Node[0] Epoch[151] Batch [200] Speed: 619.04 samples/sec Train-accuracy=0.999375
2016-05-02 20:02:47,450 Node[0] Epoch[151] Batch [250] Speed: 624.38 samples/sec Train-accuracy=0.999687
2016-05-02 20:02:57,734 Node[0] Epoch[151] Batch [300] Speed: 622.31 samples/sec Train-accuracy=0.999219
2016-05-02 20:03:08,030 Node[0] Epoch[151] Batch [350] Speed: 621.64 samples/sec Train-accuracy=0.999531
2016-05-02 20:03:16,285 Node[0] Epoch[151] Resetting Data Iterator
2016-05-02 20:03:16,286 Node[0] Epoch[151] Time cost=80.342
2016-05-02 20:03:16,453 Node[0] Saved checkpoint to "cifar10/resnet-0152.params"
2016-05-02 20:03:18,355 Node[0] Epoch[151] Validation-accuracy=0.924379
2016-05-02 20:03:28,728 Node[0] Epoch[152] Batch [50] Speed: 620.26 samples/sec Train-accuracy=0.999531
2016-05-02 20:03:39,065 Node[0] Epoch[152] Batch [100] Speed: 619.13 samples/sec Train-accuracy=0.999062
2016-05-02 20:03:49,334 Node[0] Epoch[152] Batch [150] Speed: 623.26 samples/sec Train-accuracy=0.999844
2016-05-02 20:03:59,633 Node[0] Epoch[152] Batch [200] Speed: 621.43 samples/sec Train-accuracy=0.999531
2016-05-02 20:04:09,889 Node[0] Epoch[152] Batch [250] Speed: 624.07 samples/sec Train-accuracy=0.999219
2016-05-02 20:04:20,207 Node[0] Epoch[152] Batch [300] Speed: 620.28 samples/sec Train-accuracy=0.999687
2016-05-02 20:04:30,556 Node[0] Epoch[152] Batch [350] Speed: 618.40 samples/sec Train-accuracy=0.999375
2016-05-02 20:04:39,046 Node[0] Epoch[152] Resetting Data Iterator
2016-05-02 20:04:39,046 Node[0] Epoch[152] Time cost=80.691
2016-05-02 20:04:39,213 Node[0] Saved checkpoint to "cifar10/resnet-0153.params"
2016-05-02 20:04:41,257 Node[0] Epoch[152] Validation-accuracy=0.923655
2016-05-02 20:04:51,565 Node[0] Epoch[153] Batch [50] Speed: 624.20 samples/sec Train-accuracy=0.999375
2016-05-02 20:05:01,807 Node[0] Epoch[153] Batch [100] Speed: 624.90 samples/sec Train-accuracy=0.999844
2016-05-02 20:05:12,102 Node[0] Epoch[153] Batch [150] Speed: 621.66 samples/sec Train-accuracy=0.999687
2016-05-02 20:05:22,400 Node[0] Epoch[153] Batch [200] Speed: 621.51 samples/sec Train-accuracy=0.999687
2016-05-02 20:05:32,698 Node[0] Epoch[153] Batch [250] Speed: 621.49 samples/sec Train-accuracy=0.999219
2016-05-02 20:05:43,006 Node[0] Epoch[153] Batch [300] Speed: 620.90 samples/sec Train-accuracy=0.999687
2016-05-02 20:05:53,356 Node[0] Epoch[153] Batch [350] Speed: 618.37 samples/sec Train-accuracy=1.000000
2016-05-02 20:06:01,816 Node[0] Epoch[153] Resetting Data Iterator
2016-05-02 20:06:01,817 Node[0] Epoch[153] Time cost=80.559
2016-05-02 20:06:01,978 Node[0] Saved checkpoint to "cifar10/resnet-0154.params"
2016-05-02 20:06:03,836 Node[0] Epoch[153] Validation-accuracy=0.923978
2016-05-02 20:06:14,119 Node[0] Epoch[154] Batch [50] Speed: 625.63 samples/sec Train-accuracy=0.999531
2016-05-02 20:06:24,417 Node[0] Epoch[154] Batch [100] Speed: 621.48 samples/sec Train-accuracy=0.999062
2016-05-02 20:06:34,696 Node[0] Epoch[154] Batch [150] Speed: 622.66 samples/sec Train-accuracy=0.998437
2016-05-02 20:06:45,047 Node[0] Epoch[154] Batch [200] Speed: 618.31 samples/sec Train-accuracy=0.999375
2016-05-02 20:06:55,408 Node[0] Epoch[154] Batch [250] Speed: 617.69 samples/sec Train-accuracy=0.998125
2016-05-02 20:07:05,781 Node[0] Epoch[154] Batch [300] Speed: 617.03 samples/sec Train-accuracy=0.999531
2016-05-02 20:07:16,083 Node[0] Epoch[154] Batch [350] Speed: 621.22 samples/sec Train-accuracy=0.999062
2016-05-02 20:07:24,336 Node[0] Epoch[154] Resetting Data Iterator
2016-05-02 20:07:24,336 Node[0] Epoch[154] Time cost=80.500
2016-05-02 20:07:24,495 Node[0] Saved checkpoint to "cifar10/resnet-0155.params"
2016-05-02 20:07:26,374 Node[0] Epoch[154] Validation-accuracy=0.924079
2016-05-02 20:07:36,694 Node[0] Epoch[155] Batch [50] Speed: 623.36 samples/sec Train-accuracy=0.998750
2016-05-02 20:07:47,072 Node[0] Epoch[155] Batch [100] Speed: 616.68 samples/sec Train-accuracy=0.999375
2016-05-02 20:07:57,448 Node[0] Epoch[155] Batch [150] Speed: 616.82 samples/sec Train-accuracy=0.999531
2016-05-02 20:08:07,803 Node[0] Epoch[155] Batch [200] Speed: 618.12 samples/sec Train-accuracy=0.999375
2016-05-02 20:08:18,166 Node[0] Epoch[155] Batch [250] Speed: 617.59 samples/sec Train-accuracy=0.999531
2016-05-02 20:08:28,465 Node[0] Epoch[155] Batch [300] Speed: 621.43 samples/sec Train-accuracy=0.999375
2016-05-02 20:08:38,713 Node[0] Epoch[155] Batch [350] Speed: 624.54 samples/sec Train-accuracy=0.999375
2016-05-02 20:08:47,136 Node[0] Epoch[155] Resetting Data Iterator
2016-05-02 20:08:47,136 Node[0] Epoch[155] Time cost=80.762
2016-05-02 20:08:47,297 Node[0] Saved checkpoint to "cifar10/resnet-0156.params"
2016-05-02 20:08:49,212 Node[0] Epoch[155] Validation-accuracy=0.921675
2016-05-02 20:08:59,608 Node[0] Epoch[156] Batch [50] Speed: 618.84 samples/sec Train-accuracy=0.999844
2016-05-02 20:09:09,921 Node[0] Epoch[156] Batch [100] Speed: 620.60 samples/sec Train-accuracy=0.999844
2016-05-02 20:09:20,248 Node[0] Epoch[156] Batch [150] Speed: 619.76 samples/sec Train-accuracy=0.999687
2016-05-02 20:09:30,597 Node[0] Epoch[156] Batch [200] Speed: 618.42 samples/sec Train-accuracy=0.999687
2016-05-02 20:09:40,950 Node[0] Epoch[156] Batch [250] Speed: 618.23 samples/sec Train-accuracy=0.999844
2016-05-02 20:09:51,221 Node[0] Epoch[156] Batch [300] Speed: 623.14 samples/sec Train-accuracy=0.999375
2016-05-02 20:10:01,522 Node[0] Epoch[156] Batch [350] Speed: 621.29 samples/sec Train-accuracy=1.000000
2016-05-02 20:10:09,964 Node[0] Epoch[156] Resetting Data Iterator
2016-05-02 20:10:09,964 Node[0] Epoch[156] Time cost=80.752
2016-05-02 20:10:10,129 Node[0] Saved checkpoint to "cifar10/resnet-0157.params"
2016-05-02 20:10:12,039 Node[0] Epoch[156] Validation-accuracy=0.923377
2016-05-02 20:10:22,357 Node[0] Epoch[157] Batch [50] Speed: 623.55 samples/sec Train-accuracy=0.999531
2016-05-02 20:10:32,676 Node[0] Epoch[157] Batch [100] Speed: 620.22 samples/sec Train-accuracy=0.999687
2016-05-02 20:10:43,006 Node[0] Epoch[157] Batch [150] Speed: 619.56 samples/sec Train-accuracy=0.999687
2016-05-02 20:10:53,318 Node[0] Epoch[157] Batch [200] Speed: 620.62 samples/sec Train-accuracy=0.999062
2016-05-02 20:11:03,555 Node[0] Epoch[157] Batch [250] Speed: 625.21 samples/sec Train-accuracy=0.999687
2016-05-02 20:11:13,843 Node[0] Epoch[157] Batch [300] Speed: 622.10 samples/sec Train-accuracy=0.999531
2016-05-02 20:11:24,156 Node[0] Epoch[157] Batch [350] Speed: 620.59 samples/sec Train-accuracy=0.999375
2016-05-02 20:11:32,407 Node[0] Epoch[157] Resetting Data Iterator
2016-05-02 20:11:32,407 Node[0] Epoch[157] Time cost=80.368
2016-05-02 20:11:32,571 Node[0] Saved checkpoint to "cifar10/resnet-0158.params"
2016-05-02 20:11:34,475 Node[0] Epoch[157] Validation-accuracy=0.922075
2016-05-02 20:11:44,722 Node[0] Epoch[158] Batch [50] Speed: 627.83 samples/sec Train-accuracy=0.999687
2016-05-02 20:11:55,076 Node[0] Epoch[158] Batch [100] Speed: 618.14 samples/sec Train-accuracy=0.999687
2016-05-02 20:12:05,352 Node[0] Epoch[158] Batch [150] Speed: 622.83 samples/sec Train-accuracy=0.999062
2016-05-02 20:12:15,639 Node[0] Epoch[158] Batch [200] Speed: 622.17 samples/sec Train-accuracy=0.999219
2016-05-02 20:12:25,968 Node[0] Epoch[158] Batch [250] Speed: 619.63 samples/sec Train-accuracy=0.999219
2016-05-02 20:12:36,303 Node[0] Epoch[158] Batch [300] Speed: 619.30 samples/sec Train-accuracy=0.999062
2016-05-02 20:12:46,598 Node[0] Epoch[158] Batch [350] Speed: 621.64 samples/sec Train-accuracy=0.999375
2016-05-02 20:12:55,060 Node[0] Epoch[158] Resetting Data Iterator
2016-05-02 20:12:55,061 Node[0] Epoch[158] Time cost=80.585
2016-05-02 20:12:55,221 Node[0] Saved checkpoint to "cifar10/resnet-0159.params"
2016-05-02 20:12:57,115 Node[0] Epoch[158] Validation-accuracy=0.922877
2016-05-02 20:13:07,432 Node[0] Epoch[159] Batch [50] Speed: 623.55 samples/sec Train-accuracy=0.999375
2016-05-02 20:13:17,816 Node[0] Epoch[159] Batch [100] Speed: 616.35 samples/sec Train-accuracy=0.999219
2016-05-02 20:13:28,134 Node[0] Epoch[159] Batch [150] Speed: 620.31 samples/sec Train-accuracy=0.999844
2016-05-02 20:13:38,438 Node[0] Epoch[159] Batch [200] Speed: 621.13 samples/sec Train-accuracy=0.999375
2016-05-02 20:13:48,738 Node[0] Epoch[159] Batch [250] Speed: 621.33 samples/sec Train-accuracy=0.999844
2016-05-02 20:13:59,065 Node[0] Epoch[159] Batch [300] Speed: 619.80 samples/sec Train-accuracy=0.999375
2016-05-02 20:14:09,378 Node[0] Epoch[159] Batch [350] Speed: 620.56 samples/sec Train-accuracy=0.999219
2016-05-02 20:14:17,665 Node[0] Epoch[159] Resetting Data Iterator
2016-05-02 20:14:17,665 Node[0] Epoch[159] Time cost=80.550
2016-05-02 20:14:17,831 Node[0] Saved checkpoint to "cifar10/resnet-0160.params"
2016-05-02 20:14:19,727 Node[0] Epoch[159] Validation-accuracy=0.925681
2016-05-02 20:14:19,728 Node[0] Update[62501]: Change learning rate to 1.00000e-03
2016-05-02 20:14:30,010 Node[0] Epoch[160] Batch [50] Speed: 625.70 samples/sec Train-accuracy=0.998906
2016-05-02 20:14:40,376 Node[0] Epoch[160] Batch [100] Speed: 617.40 samples/sec Train-accuracy=0.999844
2016-05-02 20:14:50,744 Node[0] Epoch[160] Batch [150] Speed: 617.31 samples/sec Train-accuracy=0.999687
2016-05-02 20:15:01,092 Node[0] Epoch[160] Batch [200] Speed: 618.48 samples/sec Train-accuracy=0.999375
2016-05-02 20:15:11,386 Node[0] Epoch[160] Batch [250] Speed: 621.74 samples/sec Train-accuracy=0.999687
2016-05-02 20:15:21,683 Node[0] Epoch[160] Batch [300] Speed: 621.58 samples/sec Train-accuracy=0.999219
2016-05-02 20:15:31,978 Node[0] Epoch[160] Batch [350] Speed: 621.67 samples/sec Train-accuracy=0.999687
2016-05-02 20:15:40,422 Node[0] Epoch[160] Resetting Data Iterator
2016-05-02 20:15:40,422 Node[0] Epoch[160] Time cost=80.695
2016-05-02 20:15:40,581 Node[0] Saved checkpoint to "cifar10/resnet-0161.params"
2016-05-02 20:15:42,636 Node[0] Epoch[160] Validation-accuracy=0.924347
2016-05-02 20:15:52,888 Node[0] Epoch[161] Batch [50] Speed: 627.56 samples/sec Train-accuracy=0.999375
2016-05-02 20:16:03,185 Node[0] Epoch[161] Batch [100] Speed: 621.58 samples/sec Train-accuracy=0.999687
2016-05-02 20:16:13,433 Node[0] Epoch[161] Batch [150] Speed: 624.53 samples/sec Train-accuracy=0.999844
2016-05-02 20:16:23,784 Node[0] Epoch[161] Batch [200] Speed: 618.31 samples/sec Train-accuracy=0.999687
2016-05-02 20:16:34,146 Node[0] Epoch[161] Batch [250] Speed: 617.68 samples/sec Train-accuracy=0.999844
2016-05-02 20:16:44,489 Node[0] Epoch[161] Batch [300] Speed: 618.75 samples/sec Train-accuracy=0.999531
2016-05-02 20:16:54,810 Node[0] Epoch[161] Batch [350] Speed: 620.10 samples/sec Train-accuracy=0.999687
2016-05-02 20:17:03,249 Node[0] Epoch[161] Resetting Data Iterator
2016-05-02 20:17:03,249 Node[0] Epoch[161] Time cost=80.612
2016-05-02 20:17:03,408 Node[0] Saved checkpoint to "cifar10/resnet-0162.params"
2016-05-02 20:17:05,297 Node[0] Epoch[161] Validation-accuracy=0.924079
2016-05-02 20:17:15,622 Node[0] Epoch[162] Batch [50] Speed: 623.09 samples/sec Train-accuracy=0.999531
2016-05-02 20:17:25,919 Node[0] Epoch[162] Batch [100] Speed: 621.54 samples/sec Train-accuracy=0.999375
2016-05-02 20:17:36,217 Node[0] Epoch[162] Batch [150] Speed: 621.53 samples/sec Train-accuracy=0.999844
2016-05-02 20:17:46,454 Node[0] Epoch[162] Batch [200] Speed: 625.17 samples/sec Train-accuracy=0.999687
2016-05-02 20:17:56,733 Node[0] Epoch[162] Batch [250] Speed: 622.64 samples/sec Train-accuracy=0.999375
2016-05-02 20:18:07,064 Node[0] Epoch[162] Batch [300] Speed: 619.51 samples/sec Train-accuracy=0.999531
2016-05-02 20:18:17,423 Node[0] Epoch[162] Batch [350] Speed: 617.83 samples/sec Train-accuracy=0.999531
2016-05-02 20:18:25,627 Node[0] Epoch[162] Resetting Data Iterator
2016-05-02 20:18:25,628 Node[0] Epoch[162] Time cost=80.330
2016-05-02 20:18:25,789 Node[0] Saved checkpoint to "cifar10/resnet-0163.params"
2016-05-02 20:18:27,677 Node[0] Epoch[162] Validation-accuracy=0.924379
2016-05-02 20:18:38,050 Node[0] Epoch[163] Batch [50] Speed: 620.36 samples/sec Train-accuracy=0.999219
2016-05-02 20:18:48,407 Node[0] Epoch[163] Batch [100] Speed: 617.94 samples/sec Train-accuracy=0.999844
2016-05-02 20:18:58,677 Node[0] Epoch[163] Batch [150] Speed: 623.17 samples/sec Train-accuracy=0.999844
2016-05-02 20:19:08,967 Node[0] Epoch[163] Batch [200] Speed: 621.97 samples/sec Train-accuracy=0.999687
2016-05-02 20:19:19,253 Node[0] Epoch[163] Batch [250] Speed: 622.23 samples/sec Train-accuracy=0.999375
2016-05-02 20:19:29,575 Node[0] Epoch[163] Batch [300] Speed: 620.03 samples/sec Train-accuracy=0.999531
2016-05-02 20:19:39,875 Node[0] Epoch[163] Batch [350] Speed: 621.42 samples/sec Train-accuracy=0.999844
2016-05-02 20:19:48,320 Node[0] Epoch[163] Resetting Data Iterator
2016-05-02 20:19:48,321 Node[0] Epoch[163] Time cost=80.643
2016-05-02 20:19:48,485 Node[0] Saved checkpoint to "cifar10/resnet-0164.params"
2016-05-02 20:19:50,366 Node[0] Epoch[163] Validation-accuracy=0.924679
2016-05-02 20:20:00,585 Node[0] Epoch[164] Batch [50] Speed: 629.54 samples/sec Train-accuracy=0.999844
2016-05-02 20:20:10,914 Node[0] Epoch[164] Batch [100] Speed: 619.62 samples/sec Train-accuracy=0.999531
2016-05-02 20:20:21,162 Node[0] Epoch[164] Batch [150] Speed: 624.57 samples/sec Train-accuracy=0.999687
2016-05-02 20:20:31,458 Node[0] Epoch[164] Batch [200] Speed: 621.58 samples/sec Train-accuracy=0.999844
2016-05-02 20:20:41,762 Node[0] Epoch[164] Batch [250] Speed: 621.17 samples/sec Train-accuracy=0.999844
2016-05-02 20:20:52,121 Node[0] Epoch[164] Batch [300] Speed: 617.79 samples/sec Train-accuracy=0.999375
2016-05-02 20:21:02,448 Node[0] Epoch[164] Batch [350] Speed: 619.80 samples/sec Train-accuracy=0.999375
2016-05-02 20:21:10,949 Node[0] Epoch[164] Resetting Data Iterator
2016-05-02 20:21:10,949 Node[0] Epoch[164] Time cost=80.583
2016-05-02 20:21:11,113 Node[0] Saved checkpoint to "cifar10/resnet-0165.params"
2016-05-02 20:21:13,028 Node[0] Epoch[164] Validation-accuracy=0.924679
2016-05-02 20:21:23,282 Node[0] Epoch[165] Batch [50] Speed: 627.41 samples/sec Train-accuracy=0.999219
2016-05-02 20:21:33,643 Node[0] Epoch[165] Batch [100] Speed: 617.74 samples/sec Train-accuracy=0.999844
2016-05-02 20:21:43,965 Node[0] Epoch[165] Batch [150] Speed: 620.02 samples/sec Train-accuracy=1.000000
2016-05-02 20:21:54,211 Node[0] Epoch[165] Batch [200] Speed: 624.65 samples/sec Train-accuracy=0.999687
2016-05-02 20:22:04,465 Node[0] Epoch[165] Batch [250] Speed: 624.16 samples/sec Train-accuracy=0.999531
2016-05-02 20:22:14,736 Node[0] Epoch[165] Batch [300] Speed: 623.15 samples/sec Train-accuracy=0.999844
2016-05-02 20:22:25,108 Node[0] Epoch[165] Batch [350] Speed: 617.09 samples/sec Train-accuracy=0.999687
2016-05-02 20:22:33,448 Node[0] Epoch[165] Resetting Data Iterator
2016-05-02 20:22:33,448 Node[0] Epoch[165] Time cost=80.420
2016-05-02 20:22:33,608 Node[0] Saved checkpoint to "cifar10/resnet-0166.params"
2016-05-02 20:22:35,499 Node[0] Epoch[165] Validation-accuracy=0.925381
2016-05-02 20:22:45,741 Node[0] Epoch[166] Batch [50] Speed: 628.09 samples/sec Train-accuracy=0.999687
2016-05-02 20:22:56,056 Node[0] Epoch[166] Batch [100] Speed: 620.47 samples/sec Train-accuracy=0.999844
2016-05-02 20:23:06,336 Node[0] Epoch[166] Batch [150] Speed: 622.58 samples/sec Train-accuracy=0.999844
2016-05-02 20:23:16,604 Node[0] Epoch[166] Batch [200] Speed: 623.33 samples/sec Train-accuracy=0.999687
2016-05-02 20:23:26,899 Node[0] Epoch[166] Batch [250] Speed: 621.69 samples/sec Train-accuracy=1.000000
2016-05-02 20:23:37,237 Node[0] Epoch[166] Batch [300] Speed: 619.10 samples/sec Train-accuracy=0.999375
2016-05-02 20:23:47,588 Node[0] Epoch[166] Batch [350] Speed: 618.30 samples/sec Train-accuracy=0.999375
2016-05-02 20:23:56,063 Node[0] Epoch[166] Resetting Data Iterator
2016-05-02 20:23:56,063 Node[0] Epoch[166] Time cost=80.564
2016-05-02 20:23:56,226 Node[0] Saved checkpoint to "cifar10/resnet-0167.params"
2016-05-02 20:23:58,112 Node[0] Epoch[166] Validation-accuracy=0.924880
2016-05-02 20:24:08,460 Node[0] Epoch[167] Batch [50] Speed: 621.71 samples/sec Train-accuracy=0.999844
2016-05-02 20:24:18,804 Node[0] Epoch[167] Batch [100] Speed: 618.78 samples/sec Train-accuracy=0.999844
2016-05-02 20:24:29,166 Node[0] Epoch[167] Batch [150] Speed: 617.66 samples/sec Train-accuracy=0.999687
2016-05-02 20:24:39,428 Node[0] Epoch[167] Batch [200] Speed: 623.65 samples/sec Train-accuracy=0.999844
2016-05-02 20:24:49,703 Node[0] Epoch[167] Batch [250] Speed: 622.90 samples/sec Train-accuracy=0.999844
2016-05-02 20:25:00,079 Node[0] Epoch[167] Batch [300] Speed: 616.82 samples/sec Train-accuracy=1.000000
2016-05-02 20:25:10,414 Node[0] Epoch[167] Batch [350] Speed: 619.30 samples/sec Train-accuracy=0.999844
2016-05-02 20:25:18,677 Node[0] Epoch[167] Resetting Data Iterator
2016-05-02 20:25:18,678 Node[0] Epoch[167] Time cost=80.565
2016-05-02 20:25:18,837 Node[0] Saved checkpoint to "cifar10/resnet-0168.params"
2016-05-02 20:25:20,708 Node[0] Epoch[167] Validation-accuracy=0.925280
2016-05-02 20:25:31,057 Node[0] Epoch[168] Batch [50] Speed: 621.72 samples/sec Train-accuracy=0.999687
2016-05-02 20:25:41,438 Node[0] Epoch[168] Batch [100] Speed: 616.50 samples/sec Train-accuracy=0.999844
2016-05-02 20:25:51,735 Node[0] Epoch[168] Batch [150] Speed: 621.57 samples/sec Train-accuracy=0.999687
2016-05-02 20:26:02,043 Node[0] Epoch[168] Batch [200] Speed: 620.87 samples/sec Train-accuracy=0.999375
2016-05-02 20:26:12,394 Node[0] Epoch[168] Batch [250] Speed: 618.31 samples/sec Train-accuracy=0.999687
2016-05-02 20:26:22,719 Node[0] Epoch[168] Batch [300] Speed: 619.92 samples/sec Train-accuracy=0.999531
2016-05-02 20:26:33,034 Node[0] Epoch[168] Batch [350] Speed: 620.47 samples/sec Train-accuracy=0.999844
2016-05-02 20:26:41,480 Node[0] Epoch[168] Resetting Data Iterator
2016-05-02 20:26:41,481 Node[0] Epoch[168] Time cost=80.773
2016-05-02 20:26:41,643 Node[0] Saved checkpoint to "cifar10/resnet-0169.params"
2016-05-02 20:26:43,752 Node[0] Epoch[168] Validation-accuracy=0.924743
2016-05-02 20:26:54,037 Node[0] Epoch[169] Batch [50] Speed: 625.57 samples/sec Train-accuracy=0.999844
2016-05-02 20:27:04,370 Node[0] Epoch[169] Batch [100] Speed: 619.38 samples/sec Train-accuracy=0.999531
2016-05-02 20:27:14,709 Node[0] Epoch[169] Batch [150] Speed: 619.06 samples/sec Train-accuracy=0.999844
2016-05-02 20:27:25,044 Node[0] Epoch[169] Batch [200] Speed: 619.25 samples/sec Train-accuracy=0.999531
2016-05-02 20:27:35,394 Node[0] Epoch[169] Batch [250] Speed: 618.43 samples/sec Train-accuracy=0.999062
2016-05-02 20:27:45,731 Node[0] Epoch[169] Batch [300] Speed: 619.15 samples/sec Train-accuracy=0.999531
2016-05-02 20:27:56,086 Node[0] Epoch[169] Batch [350] Speed: 618.05 samples/sec Train-accuracy=1.000000
2016-05-02 20:28:04,575 Node[0] Epoch[169] Resetting Data Iterator
2016-05-02 20:28:04,575 Node[0] Epoch[169] Time cost=80.823
2016-05-02 20:28:04,739 Node[0] Saved checkpoint to "cifar10/resnet-0170.params"
2016-05-02 20:28:06,675 Node[0] Epoch[169] Validation-accuracy=0.925180
2016-05-02 20:28:16,967 Node[0] Epoch[170] Batch [50] Speed: 625.06 samples/sec Train-accuracy=0.999844
2016-05-02 20:28:27,306 Node[0] Epoch[170] Batch [100] Speed: 619.06 samples/sec Train-accuracy=1.000000
2016-05-02 20:28:37,691 Node[0] Epoch[170] Batch [150] Speed: 616.28 samples/sec Train-accuracy=1.000000
2016-05-02 20:28:48,057 Node[0] Epoch[170] Batch [200] Speed: 617.41 samples/sec Train-accuracy=0.999687
2016-05-02 20:28:58,400 Node[0] Epoch[170] Batch [250] Speed: 618.77 samples/sec Train-accuracy=0.999531
2016-05-02 20:29:08,784 Node[0] Epoch[170] Batch [300] Speed: 616.38 samples/sec Train-accuracy=0.999531
2016-05-02 20:29:19,134 Node[0] Epoch[170] Batch [350] Speed: 618.39 samples/sec Train-accuracy=0.999844
2016-05-02 20:29:27,419 Node[0] Epoch[170] Resetting Data Iterator
2016-05-02 20:29:27,419 Node[0] Epoch[170] Time cost=80.744
2016-05-02 20:29:27,587 Node[0] Saved checkpoint to "cifar10/resnet-0171.params"
2016-05-02 20:29:29,477 Node[0] Epoch[170] Validation-accuracy=0.925080
2016-05-02 20:29:39,818 Node[0] Epoch[171] Batch [50] Speed: 622.10 samples/sec Train-accuracy=0.999844
2016-05-02 20:29:50,171 Node[0] Epoch[171] Batch [100] Speed: 618.16 samples/sec Train-accuracy=0.999687
2016-05-02 20:30:00,468 Node[0] Epoch[171] Batch [150] Speed: 621.54 samples/sec Train-accuracy=1.000000
2016-05-02 20:30:10,719 Node[0] Epoch[171] Batch [200] Speed: 624.35 samples/sec Train-accuracy=0.999531
2016-05-02 20:30:21,069 Node[0] Epoch[171] Batch [250] Speed: 618.41 samples/sec Train-accuracy=0.999375
2016-05-02 20:30:31,386 Node[0] Epoch[171] Batch [300] Speed: 620.32 samples/sec Train-accuracy=0.999844
2016-05-02 20:30:41,688 Node[0] Epoch[171] Batch [350] Speed: 621.25 samples/sec Train-accuracy=0.999375
2016-05-02 20:30:50,161 Node[0] Epoch[171] Resetting Data Iterator
2016-05-02 20:30:50,161 Node[0] Epoch[171] Time cost=80.684
2016-05-02 20:30:50,329 Node[0] Saved checkpoint to "cifar10/resnet-0172.params"
2016-05-02 20:30:52,220 Node[0] Epoch[171] Validation-accuracy=0.924980
2016-05-02 20:31:02,535 Node[0] Epoch[172] Batch [50] Speed: 623.71 samples/sec Train-accuracy=1.000000
2016-05-02 20:31:12,802 Node[0] Epoch[172] Batch [100] Speed: 623.36 samples/sec Train-accuracy=1.000000
2016-05-02 20:31:23,073 Node[0] Epoch[172] Batch [150] Speed: 623.13 samples/sec Train-accuracy=0.999531
2016-05-02 20:31:33,420 Node[0] Epoch[172] Batch [200] Speed: 618.56 samples/sec Train-accuracy=0.999375
2016-05-02 20:31:43,867 Node[0] Epoch[172] Batch [250] Speed: 612.64 samples/sec Train-accuracy=0.999375
2016-05-02 20:31:54,184 Node[0] Epoch[172] Batch [300] Speed: 620.32 samples/sec Train-accuracy=0.999687
2016-05-02 20:32:04,460 Node[0] Epoch[172] Batch [350] Speed: 622.84 samples/sec Train-accuracy=1.000000
2016-05-02 20:32:12,876 Node[0] Epoch[172] Resetting Data Iterator
2016-05-02 20:32:12,876 Node[0] Epoch[172] Time cost=80.656
2016-05-02 20:32:13,044 Node[0] Saved checkpoint to "cifar10/resnet-0173.params"
2016-05-02 20:32:14,952 Node[0] Epoch[172] Validation-accuracy=0.925180
2016-05-02 20:32:25,337 Node[0] Epoch[173] Batch [50] Speed: 619.58 samples/sec Train-accuracy=0.999531
2016-05-02 20:32:35,663 Node[0] Epoch[173] Batch [100] Speed: 619.85 samples/sec Train-accuracy=0.999687
2016-05-02 20:32:45,972 Node[0] Epoch[173] Batch [150] Speed: 620.79 samples/sec Train-accuracy=0.999687
2016-05-02 20:32:56,216 Node[0] Epoch[173] Batch [200] Speed: 624.80 samples/sec Train-accuracy=0.999844
2016-05-02 20:33:06,491 Node[0] Epoch[173] Batch [250] Speed: 622.91 samples/sec Train-accuracy=0.999844
2016-05-02 20:33:16,794 Node[0] Epoch[173] Batch [300] Speed: 621.16 samples/sec Train-accuracy=0.999687
2016-05-02 20:33:27,125 Node[0] Epoch[173] Batch [350] Speed: 619.52 samples/sec Train-accuracy=1.000000
2016-05-02 20:33:35,402 Node[0] Epoch[173] Resetting Data Iterator
2016-05-02 20:33:35,402 Node[0] Epoch[173] Time cost=80.451
2016-05-02 20:33:35,562 Node[0] Saved checkpoint to "cifar10/resnet-0174.params"
2016-05-02 20:33:37,442 Node[0] Epoch[173] Validation-accuracy=0.924780
2016-05-02 20:33:47,714 Node[0] Epoch[174] Batch [50] Speed: 626.27 samples/sec Train-accuracy=0.999844
2016-05-02 20:33:58,020 Node[0] Epoch[174] Batch [100] Speed: 621.01 samples/sec Train-accuracy=0.999844
2016-05-02 20:34:08,289 Node[0] Epoch[174] Batch [150] Speed: 623.28 samples/sec Train-accuracy=0.999687
2016-05-02 20:34:18,555 Node[0] Epoch[174] Batch [200] Speed: 623.44 samples/sec Train-accuracy=1.000000
2016-05-02 20:34:28,822 Node[0] Epoch[174] Batch [250] Speed: 623.39 samples/sec Train-accuracy=0.999687
2016-05-02 20:34:39,123 Node[0] Epoch[174] Batch [300] Speed: 621.29 samples/sec Train-accuracy=1.000000
2016-05-02 20:34:49,452 Node[0] Epoch[174] Batch [350] Speed: 619.67 samples/sec Train-accuracy=0.999687
2016-05-02 20:34:57,926 Node[0] Epoch[174] Resetting Data Iterator
2016-05-02 20:34:57,926 Node[0] Epoch[174] Time cost=80.485
2016-05-02 20:34:58,087 Node[0] Saved checkpoint to "cifar10/resnet-0175.params"
2016-05-02 20:34:59,976 Node[0] Epoch[174] Validation-accuracy=0.924679
2016-05-02 20:35:10,334 Node[0] Epoch[175] Batch [50] Speed: 621.10 samples/sec Train-accuracy=0.999844
2016-05-02 20:35:20,556 Node[0] Epoch[175] Batch [100] Speed: 626.13 samples/sec Train-accuracy=0.999687
2016-05-02 20:35:30,831 Node[0] Epoch[175] Batch [150] Speed: 622.89 samples/sec Train-accuracy=0.999844
2016-05-02 20:35:41,124 Node[0] Epoch[175] Batch [200] Speed: 621.77 samples/sec Train-accuracy=0.999687
2016-05-02 20:35:51,410 Node[0] Epoch[175] Batch [250] Speed: 622.25 samples/sec Train-accuracy=0.999844
2016-05-02 20:36:01,729 Node[0] Epoch[175] Batch [300] Speed: 620.23 samples/sec Train-accuracy=1.000000
2016-05-02 20:36:12,013 Node[0] Epoch[175] Batch [350] Speed: 622.33 samples/sec Train-accuracy=0.999844
2016-05-02 20:36:20,270 Node[0] Epoch[175] Resetting Data Iterator
2016-05-02 20:36:20,270 Node[0] Epoch[175] Time cost=80.295
2016-05-02 20:36:20,434 Node[0] Saved checkpoint to "cifar10/resnet-0176.params"
2016-05-02 20:36:22,298 Node[0] Epoch[175] Validation-accuracy=0.925381
2016-05-02 20:36:32,504 Node[0] Epoch[176] Batch [50] Speed: 630.35 samples/sec Train-accuracy=0.999844
2016-05-02 20:36:42,817 Node[0] Epoch[176] Batch [100] Speed: 620.59 samples/sec Train-accuracy=1.000000
2016-05-02 20:36:53,076 Node[0] Epoch[176] Batch [150] Speed: 623.85 samples/sec Train-accuracy=0.999687
2016-05-02 20:37:03,339 Node[0] Epoch[176] Batch [200] Speed: 623.63 samples/sec Train-accuracy=0.999844
2016-05-02 20:37:13,647 Node[0] Epoch[176] Batch [250] Speed: 620.87 samples/sec Train-accuracy=0.999844
2016-05-02 20:37:23,998 Node[0] Epoch[176] Batch [300] Speed: 618.35 samples/sec Train-accuracy=0.999844
2016-05-02 20:37:34,324 Node[0] Epoch[176] Batch [350] Speed: 619.79 samples/sec Train-accuracy=0.999844
2016-05-02 20:37:42,748 Node[0] Epoch[176] Resetting Data Iterator
2016-05-02 20:37:42,748 Node[0] Epoch[176] Time cost=80.450
2016-05-02 20:37:42,913 Node[0] Saved checkpoint to "cifar10/resnet-0177.params"
2016-05-02 20:37:44,971 Node[0] Epoch[176] Validation-accuracy=0.924941
2016-05-02 20:37:55,300 Node[0] Epoch[177] Batch [50] Speed: 622.79 samples/sec Train-accuracy=0.999844
2016-05-02 20:38:05,664 Node[0] Epoch[177] Batch [100] Speed: 617.53 samples/sec Train-accuracy=0.999687
2016-05-02 20:38:15,933 Node[0] Epoch[177] Batch [150] Speed: 623.24 samples/sec Train-accuracy=0.999844
2016-05-02 20:38:26,199 Node[0] Epoch[177] Batch [200] Speed: 623.48 samples/sec Train-accuracy=0.999687
2016-05-02 20:38:36,510 Node[0] Epoch[177] Batch [250] Speed: 620.66 samples/sec Train-accuracy=1.000000
2016-05-02 20:38:46,814 Node[0] Epoch[177] Batch [300] Speed: 621.18 samples/sec Train-accuracy=0.999844
2016-05-02 20:38:57,182 Node[0] Epoch[177] Batch [350] Speed: 617.30 samples/sec Train-accuracy=0.999844
2016-05-02 20:39:05,653 Node[0] Epoch[177] Resetting Data Iterator
2016-05-02 20:39:05,653 Node[0] Epoch[177] Time cost=80.682
2016-05-02 20:39:05,814 Node[0] Saved checkpoint to "cifar10/resnet-0178.params"
2016-05-02 20:39:07,698 Node[0] Epoch[177] Validation-accuracy=0.925581
2016-05-02 20:39:18,005 Node[0] Epoch[178] Batch [50] Speed: 624.20 samples/sec Train-accuracy=1.000000
2016-05-02 20:39:28,373 Node[0] Epoch[178] Batch [100] Speed: 617.30 samples/sec Train-accuracy=1.000000
2016-05-02 20:39:38,646 Node[0] Epoch[178] Batch [150] Speed: 622.98 samples/sec Train-accuracy=1.000000
2016-05-02 20:39:48,931 Node[0] Epoch[178] Batch [200] Speed: 622.27 samples/sec Train-accuracy=0.999531
2016-05-02 20:39:59,192 Node[0] Epoch[178] Batch [250] Speed: 623.76 samples/sec Train-accuracy=0.999687
2016-05-02 20:40:09,529 Node[0] Epoch[178] Batch [300] Speed: 619.17 samples/sec Train-accuracy=0.999844
2016-05-02 20:40:19,901 Node[0] Epoch[178] Batch [350] Speed: 617.03 samples/sec Train-accuracy=0.999844
2016-05-02 20:40:28,149 Node[0] Epoch[178] Resetting Data Iterator
2016-05-02 20:40:28,149 Node[0] Epoch[178] Time cost=80.451
2016-05-02 20:40:28,311 Node[0] Saved checkpoint to "cifar10/resnet-0179.params"
2016-05-02 20:40:30,208 Node[0] Epoch[178] Validation-accuracy=0.925280
2016-05-02 20:40:40,501 Node[0] Epoch[179] Batch [50] Speed: 625.08 samples/sec Train-accuracy=0.999844
2016-05-02 20:40:50,777 Node[0] Epoch[179] Batch [100] Speed: 622.84 samples/sec Train-accuracy=0.999844
2016-05-02 20:41:01,067 Node[0] Epoch[179] Batch [150] Speed: 621.98 samples/sec Train-accuracy=0.999687
2016-05-02 20:41:11,429 Node[0] Epoch[179] Batch [200] Speed: 617.70 samples/sec Train-accuracy=1.000000
2016-05-02 20:41:21,763 Node[0] Epoch[179] Batch [250] Speed: 619.33 samples/sec Train-accuracy=0.999844
2016-05-02 20:41:32,078 Node[0] Epoch[179] Batch [300] Speed: 620.46 samples/sec Train-accuracy=0.999844
2016-05-02 20:41:42,423 Node[0] Epoch[179] Batch [350] Speed: 618.68 samples/sec Train-accuracy=0.999844
2016-05-02 20:41:50,899 Node[0] Epoch[179] Resetting Data Iterator
2016-05-02 20:41:50,900 Node[0] Epoch[179] Time cost=80.692
2016-05-02 20:41:51,061 Node[0] Saved checkpoint to "cifar10/resnet-0180.params"
2016-05-02 20:41:52,934 Node[0] Epoch[179] Validation-accuracy=0.925781
2016-05-02 20:42:03,259 Node[0] Epoch[180] Batch [50] Speed: 623.07 samples/sec Train-accuracy=0.999375
2016-05-02 20:42:13,527 Node[0] Epoch[180] Batch [100] Speed: 623.29 samples/sec Train-accuracy=1.000000
2016-05-02 20:42:23,858 Node[0] Epoch[180] Batch [150] Speed: 619.55 samples/sec Train-accuracy=1.000000
2016-05-02 20:42:34,190 Node[0] Epoch[180] Batch [200] Speed: 619.41 samples/sec Train-accuracy=0.999844
2016-05-02 20:42:44,520 Node[0] Epoch[180] Batch [250] Speed: 619.62 samples/sec Train-accuracy=0.999687
2016-05-02 20:42:54,834 Node[0] Epoch[180] Batch [300] Speed: 620.52 samples/sec Train-accuracy=0.999687
2016-05-02 20:43:05,203 Node[0] Epoch[180] Batch [350] Speed: 617.20 samples/sec Train-accuracy=1.000000
2016-05-02 20:43:13,672 Node[0] Epoch[180] Resetting Data Iterator
2016-05-02 20:43:13,672 Node[0] Epoch[180] Time cost=80.738
2016-05-02 20:43:13,833 Node[0] Saved checkpoint to "cifar10/resnet-0181.params"
2016-05-02 20:43:15,732 Node[0] Epoch[180] Validation-accuracy=0.926482
2016-05-02 20:43:26,011 Node[0] Epoch[181] Batch [50] Speed: 625.80 samples/sec Train-accuracy=0.999531
2016-05-02 20:43:36,338 Node[0] Epoch[181] Batch [100] Speed: 619.76 samples/sec Train-accuracy=0.999844
2016-05-02 20:43:46,682 Node[0] Epoch[181] Batch [150] Speed: 618.74 samples/sec Train-accuracy=0.999844
2016-05-02 20:43:56,918 Node[0] Epoch[181] Batch [200] Speed: 625.26 samples/sec Train-accuracy=0.999844
2016-05-02 20:44:07,212 Node[0] Epoch[181] Batch [250] Speed: 621.76 samples/sec Train-accuracy=0.999687
2016-05-02 20:44:17,476 Node[0] Epoch[181] Batch [300] Speed: 623.55 samples/sec Train-accuracy=0.999375
2016-05-02 20:44:27,820 Node[0] Epoch[181] Batch [350] Speed: 618.74 samples/sec Train-accuracy=0.999844
2016-05-02 20:44:36,062 Node[0] Epoch[181] Resetting Data Iterator
2016-05-02 20:44:36,062 Node[0] Epoch[181] Time cost=80.330
2016-05-02 20:44:36,223 Node[0] Saved checkpoint to "cifar10/resnet-0182.params"
2016-05-02 20:44:38,109 Node[0] Epoch[181] Validation-accuracy=0.925581
2016-05-02 20:44:48,428 Node[0] Epoch[182] Batch [50] Speed: 623.48 samples/sec Train-accuracy=0.999844
2016-05-02 20:44:58,751 Node[0] Epoch[182] Batch [100] Speed: 620.04 samples/sec Train-accuracy=0.999844
2016-05-02 20:45:09,038 Node[0] Epoch[182] Batch [150] Speed: 622.14 samples/sec Train-accuracy=0.999687
2016-05-02 20:45:19,323 Node[0] Epoch[182] Batch [200] Speed: 622.27 samples/sec Train-accuracy=0.999531
2016-05-02 20:45:29,700 Node[0] Epoch[182] Batch [250] Speed: 616.75 samples/sec Train-accuracy=1.000000
2016-05-02 20:45:40,040 Node[0] Epoch[182] Batch [300] Speed: 618.98 samples/sec Train-accuracy=1.000000
2016-05-02 20:45:50,404 Node[0] Epoch[182] Batch [350] Speed: 617.55 samples/sec Train-accuracy=0.999687
2016-05-02 20:45:58,906 Node[0] Epoch[182] Resetting Data Iterator
2016-05-02 20:45:58,906 Node[0] Epoch[182] Time cost=80.797
2016-05-02 20:45:59,067 Node[0] Saved checkpoint to "cifar10/resnet-0183.params"
2016-05-02 20:46:00,973 Node[0] Epoch[182] Validation-accuracy=0.925481
2016-05-02 20:46:11,300 Node[0] Epoch[183] Batch [50] Speed: 623.04 samples/sec Train-accuracy=0.999844
2016-05-02 20:46:21,693 Node[0] Epoch[183] Batch [100] Speed: 615.81 samples/sec Train-accuracy=0.999844
2016-05-02 20:46:32,065 Node[0] Epoch[183] Batch [150] Speed: 617.11 samples/sec Train-accuracy=1.000000
2016-05-02 20:46:42,416 Node[0] Epoch[183] Batch [200] Speed: 618.29 samples/sec Train-accuracy=1.000000
2016-05-02 20:46:52,773 Node[0] Epoch[183] Batch [250] Speed: 617.93 samples/sec Train-accuracy=0.999687
2016-05-02 20:47:03,189 Node[0] Epoch[183] Batch [300] Speed: 614.48 samples/sec Train-accuracy=1.000000
2016-05-02 20:47:13,552 Node[0] Epoch[183] Batch [350] Speed: 617.63 samples/sec Train-accuracy=0.999844
2016-05-02 20:47:21,844 Node[0] Epoch[183] Resetting Data Iterator
2016-05-02 20:47:21,844 Node[0] Epoch[183] Time cost=80.871
2016-05-02 20:47:22,014 Node[0] Saved checkpoint to "cifar10/resnet-0184.params"
2016-05-02 20:47:23,893 Node[0] Epoch[183] Validation-accuracy=0.925381
2016-05-02 20:47:34,240 Node[0] Epoch[184] Batch [50] Speed: 621.78 samples/sec Train-accuracy=1.000000
2016-05-02 20:47:44,585 Node[0] Epoch[184] Batch [100] Speed: 618.69 samples/sec Train-accuracy=0.999844
2016-05-02 20:47:54,955 Node[0] Epoch[184] Batch [150] Speed: 617.17 samples/sec Train-accuracy=0.999844
2016-05-02 20:48:05,323 Node[0] Epoch[184] Batch [200] Speed: 617.31 samples/sec Train-accuracy=0.999844
2016-05-02 20:48:15,700 Node[0] Epoch[184] Batch [250] Speed: 616.79 samples/sec Train-accuracy=0.999844
2016-05-02 20:48:26,093 Node[0] Epoch[184] Batch [300] Speed: 615.81 samples/sec Train-accuracy=1.000000
2016-05-02 20:48:36,484 Node[0] Epoch[184] Batch [350] Speed: 615.92 samples/sec Train-accuracy=0.999687
2016-05-02 20:48:44,946 Node[0] Epoch[184] Resetting Data Iterator
2016-05-02 20:48:44,947 Node[0] Epoch[184] Time cost=81.053
2016-05-02 20:48:45,108 Node[0] Saved checkpoint to "cifar10/resnet-0185.params"
2016-05-02 20:48:47,185 Node[0] Epoch[184] Validation-accuracy=0.925633
2016-05-02 20:48:57,491 Node[0] Epoch[185] Batch [50] Speed: 624.30 samples/sec Train-accuracy=0.999687
2016-05-02 20:49:07,830 Node[0] Epoch[185] Batch [100] Speed: 619.06 samples/sec Train-accuracy=0.999687
2016-05-02 20:49:18,158 Node[0] Epoch[185] Batch [150] Speed: 619.67 samples/sec Train-accuracy=0.999687
2016-05-02 20:49:28,516 Node[0] Epoch[185] Batch [200] Speed: 617.91 samples/sec Train-accuracy=0.999531
2016-05-02 20:49:38,829 Node[0] Epoch[185] Batch [250] Speed: 620.60 samples/sec Train-accuracy=1.000000
2016-05-02 20:49:49,138 Node[0] Epoch[185] Batch [300] Speed: 620.84 samples/sec Train-accuracy=1.000000
2016-05-02 20:49:59,456 Node[0] Epoch[185] Batch [350] Speed: 620.28 samples/sec Train-accuracy=0.999687
2016-05-02 20:50:07,910 Node[0] Epoch[185] Resetting Data Iterator
2016-05-02 20:50:07,910 Node[0] Epoch[185] Time cost=80.725
2016-05-02 20:50:08,074 Node[0] Saved checkpoint to "cifar10/resnet-0186.params"
2016-05-02 20:50:09,976 Node[0] Epoch[185] Validation-accuracy=0.924880
2016-05-02 20:50:20,342 Node[0] Epoch[186] Batch [50] Speed: 620.66 samples/sec Train-accuracy=0.999844
2016-05-02 20:50:30,668 Node[0] Epoch[186] Batch [100] Speed: 619.85 samples/sec Train-accuracy=1.000000
2016-05-02 20:50:40,995 Node[0] Epoch[186] Batch [150] Speed: 619.74 samples/sec Train-accuracy=0.999531
2016-05-02 20:50:51,429 Node[0] Epoch[186] Batch [200] Speed: 613.39 samples/sec Train-accuracy=0.999844
2016-05-02 20:51:01,780 Node[0] Epoch[186] Batch [250] Speed: 618.31 samples/sec Train-accuracy=1.000000
2016-05-02 20:51:12,113 Node[0] Epoch[186] Batch [300] Speed: 619.43 samples/sec Train-accuracy=0.999687
2016-05-02 20:51:22,483 Node[0] Epoch[186] Batch [350] Speed: 617.15 samples/sec Train-accuracy=0.999687
2016-05-02 20:51:30,752 Node[0] Epoch[186] Resetting Data Iterator
2016-05-02 20:51:30,752 Node[0] Epoch[186] Time cost=80.776
2016-05-02 20:51:30,910 Node[0] Saved checkpoint to "cifar10/resnet-0187.params"
2016-05-02 20:51:32,812 Node[0] Epoch[186] Validation-accuracy=0.924980
2016-05-02 20:51:43,141 Node[0] Epoch[187] Batch [50] Speed: 622.81 samples/sec Train-accuracy=0.999531
2016-05-02 20:51:53,497 Node[0] Epoch[187] Batch [100] Speed: 618.06 samples/sec Train-accuracy=0.999687
2016-05-02 20:52:03,839 Node[0] Epoch[187] Batch [150] Speed: 618.85 samples/sec Train-accuracy=0.999844
2016-05-02 20:52:14,205 Node[0] Epoch[187] Batch [200] Speed: 617.41 samples/sec Train-accuracy=1.000000
2016-05-02 20:52:24,534 Node[0] Epoch[187] Batch [250] Speed: 619.63 samples/sec Train-accuracy=0.999375
2016-05-02 20:52:34,889 Node[0] Epoch[187] Batch [300] Speed: 618.07 samples/sec Train-accuracy=1.000000
2016-05-02 20:52:45,228 Node[0] Epoch[187] Batch [350] Speed: 619.01 samples/sec Train-accuracy=1.000000
2016-05-02 20:52:53,705 Node[0] Epoch[187] Resetting Data Iterator
2016-05-02 20:52:53,705 Node[0] Epoch[187] Time cost=80.893
2016-05-02 20:52:53,870 Node[0] Saved checkpoint to "cifar10/resnet-0188.params"
2016-05-02 20:52:55,757 Node[0] Epoch[187] Validation-accuracy=0.924780
2016-05-02 20:53:06,086 Node[0] Epoch[188] Batch [50] Speed: 623.00 samples/sec Train-accuracy=1.000000
2016-05-02 20:53:16,436 Node[0] Epoch[188] Batch [100] Speed: 618.37 samples/sec Train-accuracy=0.999531
2016-05-02 20:53:26,733 Node[0] Epoch[188] Batch [150] Speed: 621.59 samples/sec Train-accuracy=1.000000
2016-05-02 20:53:37,061 Node[0] Epoch[188] Batch [200] Speed: 619.68 samples/sec Train-accuracy=1.000000
2016-05-02 20:53:47,416 Node[0] Epoch[188] Batch [250] Speed: 618.06 samples/sec Train-accuracy=1.000000
2016-05-02 20:53:57,752 Node[0] Epoch[188] Batch [300] Speed: 619.25 samples/sec Train-accuracy=0.999531
2016-05-02 20:54:08,128 Node[0] Epoch[188] Batch [350] Speed: 616.78 samples/sec Train-accuracy=0.999687
2016-05-02 20:54:16,594 Node[0] Epoch[188] Resetting Data Iterator
2016-05-02 20:54:16,595 Node[0] Epoch[188] Time cost=80.837
2016-05-02 20:54:16,756 Node[0] Saved checkpoint to "cifar10/resnet-0189.params"
2016-05-02 20:54:18,613 Node[0] Epoch[188] Validation-accuracy=0.925280
2016-05-02 20:54:29,001 Node[0] Epoch[189] Batch [50] Speed: 619.34 samples/sec Train-accuracy=0.999844
2016-05-02 20:54:39,355 Node[0] Epoch[189] Batch [100] Speed: 618.13 samples/sec Train-accuracy=0.999219
2016-05-02 20:54:49,691 Node[0] Epoch[189] Batch [150] Speed: 619.24 samples/sec Train-accuracy=0.999844
2016-05-02 20:55:00,052 Node[0] Epoch[189] Batch [200] Speed: 617.68 samples/sec Train-accuracy=0.999375
2016-05-02 20:55:10,418 Node[0] Epoch[189] Batch [250] Speed: 617.46 samples/sec Train-accuracy=1.000000
2016-05-02 20:55:20,770 Node[0] Epoch[189] Batch [300] Speed: 618.24 samples/sec Train-accuracy=0.999844
2016-05-02 20:55:31,018 Node[0] Epoch[189] Batch [350] Speed: 624.55 samples/sec Train-accuracy=1.000000
2016-05-02 20:55:39,226 Node[0] Epoch[189] Resetting Data Iterator
2016-05-02 20:55:39,226 Node[0] Epoch[189] Time cost=80.613
2016-05-02 20:55:39,387 Node[0] Saved checkpoint to "cifar10/resnet-0190.params"
2016-05-02 20:55:41,287 Node[0] Epoch[189] Validation-accuracy=0.925681
2016-05-02 20:55:51,659 Node[0] Epoch[190] Batch [50] Speed: 620.29 samples/sec Train-accuracy=0.999687
2016-05-02 20:56:01,927 Node[0] Epoch[190] Batch [100] Speed: 623.29 samples/sec Train-accuracy=0.999844
2016-05-02 20:56:12,154 Node[0] Epoch[190] Batch [150] Speed: 625.80 samples/sec Train-accuracy=0.999844
2016-05-02 20:56:22,495 Node[0] Epoch[190] Batch [200] Speed: 618.93 samples/sec Train-accuracy=0.999844
2016-05-02 20:56:32,808 Node[0] Epoch[190] Batch [250] Speed: 620.60 samples/sec Train-accuracy=1.000000
2016-05-02 20:56:43,154 Node[0] Epoch[190] Batch [300] Speed: 618.64 samples/sec Train-accuracy=0.999844
2016-05-02 20:56:53,505 Node[0] Epoch[190] Batch [350] Speed: 618.26 samples/sec Train-accuracy=1.000000
2016-05-02 20:57:01,969 Node[0] Epoch[190] Resetting Data Iterator
2016-05-02 20:57:01,969 Node[0] Epoch[190] Time cost=80.681
2016-05-02 20:57:02,133 Node[0] Saved checkpoint to "cifar10/resnet-0191.params"
2016-05-02 20:57:04,016 Node[0] Epoch[190] Validation-accuracy=0.925481
2016-05-02 20:57:14,199 Node[0] Epoch[191] Batch [50] Speed: 631.75 samples/sec Train-accuracy=0.999531
2016-05-02 20:57:24,473 Node[0] Epoch[191] Batch [100] Speed: 622.99 samples/sec Train-accuracy=0.999531
2016-05-02 20:57:34,736 Node[0] Epoch[191] Batch [150] Speed: 623.59 samples/sec Train-accuracy=0.999687
2016-05-02 20:57:45,056 Node[0] Epoch[191] Batch [200] Speed: 620.19 samples/sec Train-accuracy=0.999844
2016-05-02 20:57:55,387 Node[0] Epoch[191] Batch [250] Speed: 619.48 samples/sec Train-accuracy=1.000000
2016-05-02 20:58:05,699 Node[0] Epoch[191] Batch [300] Speed: 620.69 samples/sec Train-accuracy=0.999687
2016-05-02 20:58:15,996 Node[0] Epoch[191] Batch [350] Speed: 621.54 samples/sec Train-accuracy=0.999687
2016-05-02 20:58:24,230 Node[0] Epoch[191] Resetting Data Iterator
2016-05-02 20:58:24,231 Node[0] Epoch[191] Time cost=80.215
2016-05-02 20:58:24,395 Node[0] Saved checkpoint to "cifar10/resnet-0192.params"
2016-05-02 20:58:26,256 Node[0] Epoch[191] Validation-accuracy=0.924780
2016-05-02 20:58:36,505 Node[0] Epoch[192] Batch [50] Speed: 627.68 samples/sec Train-accuracy=0.999531
2016-05-02 20:58:46,782 Node[0] Epoch[192] Batch [100] Speed: 622.81 samples/sec Train-accuracy=1.000000
2016-05-02 20:58:56,979 Node[0] Epoch[192] Batch [150] Speed: 627.61 samples/sec Train-accuracy=0.999531
2016-05-02 20:59:07,257 Node[0] Epoch[192] Batch [200] Speed: 622.71 samples/sec Train-accuracy=0.999844
2016-05-02 20:59:17,626 Node[0] Epoch[192] Batch [250] Speed: 617.25 samples/sec Train-accuracy=0.999844
2016-05-02 20:59:27,944 Node[0] Epoch[192] Batch [300] Speed: 620.28 samples/sec Train-accuracy=1.000000
2016-05-02 20:59:38,223 Node[0] Epoch[192] Batch [350] Speed: 622.69 samples/sec Train-accuracy=1.000000
2016-05-02 20:59:46,672 Node[0] Epoch[192] Resetting Data Iterator
2016-05-02 20:59:46,672 Node[0] Epoch[192] Time cost=80.415
2016-05-02 20:59:46,832 Node[0] Saved checkpoint to "cifar10/resnet-0193.params"
2016-05-02 20:59:48,886 Node[0] Epoch[192] Validation-accuracy=0.926226
2016-05-02 20:59:59,141 Node[0] Epoch[193] Batch [50] Speed: 627.36 samples/sec Train-accuracy=1.000000
2016-05-02 21:00:09,489 Node[0] Epoch[193] Batch [100] Speed: 618.54 samples/sec Train-accuracy=1.000000
2016-05-02 21:00:19,752 Node[0] Epoch[193] Batch [150] Speed: 623.60 samples/sec Train-accuracy=0.999687
2016-05-02 21:00:30,049 Node[0] Epoch[193] Batch [200] Speed: 621.56 samples/sec Train-accuracy=1.000000
2016-05-02 21:00:40,349 Node[0] Epoch[193] Batch [250] Speed: 621.35 samples/sec Train-accuracy=0.999687
2016-05-02 21:00:50,665 Node[0] Epoch[193] Batch [300] Speed: 620.44 samples/sec Train-accuracy=0.999687
2016-05-02 21:01:00,923 Node[0] Epoch[193] Batch [350] Speed: 623.89 samples/sec Train-accuracy=0.999687
2016-05-02 21:01:09,335 Node[0] Epoch[193] Resetting Data Iterator
2016-05-02 21:01:09,335 Node[0] Epoch[193] Time cost=80.449
2016-05-02 21:01:09,496 Node[0] Saved checkpoint to "cifar10/resnet-0194.params"
2016-05-02 21:01:11,435 Node[0] Epoch[193] Validation-accuracy=0.925881
2016-05-02 21:01:21,801 Node[0] Epoch[194] Batch [50] Speed: 620.63 samples/sec Train-accuracy=0.999531
2016-05-02 21:01:32,061 Node[0] Epoch[194] Batch [100] Speed: 623.85 samples/sec Train-accuracy=0.999844
2016-05-02 21:01:42,311 Node[0] Epoch[194] Batch [150] Speed: 624.41 samples/sec Train-accuracy=0.999531
2016-05-02 21:01:52,620 Node[0] Epoch[194] Batch [200] Speed: 620.82 samples/sec Train-accuracy=1.000000
2016-05-02 21:02:02,893 Node[0] Epoch[194] Batch [250] Speed: 623.00 samples/sec Train-accuracy=0.999844
2016-05-02 21:02:13,231 Node[0] Epoch[194] Batch [300] Speed: 619.08 samples/sec Train-accuracy=1.000000
2016-05-02 21:02:23,535 Node[0] Epoch[194] Batch [350] Speed: 621.17 samples/sec Train-accuracy=0.999844
2016-05-02 21:02:31,795 Node[0] Epoch[194] Resetting Data Iterator
2016-05-02 21:02:31,796 Node[0] Epoch[194] Time cost=80.361
2016-05-02 21:02:31,953 Node[0] Saved checkpoint to "cifar10/resnet-0195.params"
2016-05-02 21:02:33,828 Node[0] Epoch[194] Validation-accuracy=0.925381
2016-05-02 21:02:44,068 Node[0] Epoch[195] Batch [50] Speed: 628.24 samples/sec Train-accuracy=1.000000
2016-05-02 21:02:54,397 Node[0] Epoch[195] Batch [100] Speed: 619.64 samples/sec Train-accuracy=1.000000
2016-05-02 21:03:04,662 Node[0] Epoch[195] Batch [150] Speed: 623.49 samples/sec Train-accuracy=0.999375
2016-05-02 21:03:14,945 Node[0] Epoch[195] Batch [200] Speed: 622.42 samples/sec Train-accuracy=0.999531
2016-05-02 21:03:25,174 Node[0] Epoch[195] Batch [250] Speed: 625.69 samples/sec Train-accuracy=1.000000
2016-05-02 21:03:35,401 Node[0] Epoch[195] Batch [300] Speed: 625.78 samples/sec Train-accuracy=0.999844
2016-05-02 21:03:45,713 Node[0] Epoch[195] Batch [350] Speed: 620.69 samples/sec Train-accuracy=0.999844
2016-05-02 21:03:54,164 Node[0] Epoch[195] Resetting Data Iterator
2016-05-02 21:03:54,164 Node[0] Epoch[195] Time cost=80.337
2016-05-02 21:03:54,332 Node[0] Saved checkpoint to "cifar10/resnet-0196.params"
2016-05-02 21:03:56,249 Node[0] Epoch[195] Validation-accuracy=0.925982
2016-05-02 21:04:06,562 Node[0] Epoch[196] Batch [50] Speed: 623.96 samples/sec Train-accuracy=0.999531
2016-05-02 21:04:16,914 Node[0] Epoch[196] Batch [100] Speed: 618.25 samples/sec Train-accuracy=1.000000
2016-05-02 21:04:27,167 Node[0] Epoch[196] Batch [150] Speed: 624.20 samples/sec Train-accuracy=0.999844
2016-05-02 21:04:37,449 Node[0] Epoch[196] Batch [200] Speed: 622.49 samples/sec Train-accuracy=0.999375
2016-05-02 21:04:47,724 Node[0] Epoch[196] Batch [250] Speed: 622.85 samples/sec Train-accuracy=1.000000
2016-05-02 21:04:58,034 Node[0] Epoch[196] Batch [300] Speed: 620.75 samples/sec Train-accuracy=0.999844
2016-05-02 21:05:08,352 Node[0] Epoch[196] Batch [350] Speed: 620.33 samples/sec Train-accuracy=0.999375
2016-05-02 21:05:16,765 Node[0] Epoch[196] Resetting Data Iterator
2016-05-02 21:05:16,765 Node[0] Epoch[196] Time cost=80.516
2016-05-02 21:05:16,931 Node[0] Saved checkpoint to "cifar10/resnet-0197.params"
2016-05-02 21:05:18,796 Node[0] Epoch[196] Validation-accuracy=0.926382
2016-05-02 21:05:29,131 Node[0] Epoch[197] Batch [50] Speed: 622.51 samples/sec Train-accuracy=1.000000
2016-05-02 21:05:39,534 Node[0] Epoch[197] Batch [100] Speed: 615.23 samples/sec Train-accuracy=1.000000
2016-05-02 21:05:49,806 Node[0] Epoch[197] Batch [150] Speed: 623.09 samples/sec Train-accuracy=1.000000
2016-05-02 21:06:00,109 Node[0] Epoch[197] Batch [200] Speed: 621.19 samples/sec Train-accuracy=0.999844
2016-05-02 21:06:10,380 Node[0] Epoch[197] Batch [250] Speed: 623.12 samples/sec Train-accuracy=0.999687
2016-05-02 21:06:20,654 Node[0] Epoch[197] Batch [300] Speed: 622.94 samples/sec Train-accuracy=1.000000
2016-05-02 21:06:30,923 Node[0] Epoch[197] Batch [350] Speed: 623.25 samples/sec Train-accuracy=0.999687
2016-05-02 21:06:39,128 Node[0] Epoch[197] Resetting Data Iterator
2016-05-02 21:06:39,128 Node[0] Epoch[197] Time cost=80.332
2016-05-02 21:06:39,294 Node[0] Saved checkpoint to "cifar10/resnet-0198.params"
2016-05-02 21:06:41,213 Node[0] Epoch[197] Validation-accuracy=0.925982
2016-05-02 21:06:51,558 Node[0] Epoch[198] Batch [50] Speed: 621.94 samples/sec Train-accuracy=0.999844
2016-05-02 21:07:01,792 Node[0] Epoch[198] Batch [100] Speed: 625.42 samples/sec Train-accuracy=1.000000
2016-05-02 21:07:12,054 Node[0] Epoch[198] Batch [150] Speed: 623.64 samples/sec Train-accuracy=0.999687
2016-05-02 21:07:22,369 Node[0] Epoch[198] Batch [200] Speed: 620.46 samples/sec Train-accuracy=1.000000
2016-05-02 21:07:32,640 Node[0] Epoch[198] Batch [250] Speed: 623.15 samples/sec Train-accuracy=1.000000
2016-05-02 21:07:42,965 Node[0] Epoch[198] Batch [300] Speed: 619.88 samples/sec Train-accuracy=0.999844
2016-05-02 21:07:53,209 Node[0] Epoch[198] Batch [350] Speed: 624.75 samples/sec Train-accuracy=0.999844
2016-05-02 21:08:01,624 Node[0] Epoch[198] Resetting Data Iterator
2016-05-02 21:08:01,624 Node[0] Epoch[198] Time cost=80.410
2016-05-02 21:08:01,781 Node[0] Saved checkpoint to "cifar10/resnet-0199.params"
2016-05-02 21:08:03,687 Node[0] Epoch[198] Validation-accuracy=0.925982
2016-05-02 21:08:14,071 Node[0] Epoch[199] Batch [50] Speed: 619.61 samples/sec Train-accuracy=0.999844
2016-05-02 21:08:24,321 Node[0] Epoch[199] Batch [100] Speed: 624.42 samples/sec Train-accuracy=0.999844
2016-05-02 21:08:34,617 Node[0] Epoch[199] Batch [150] Speed: 621.60 samples/sec Train-accuracy=0.999844
2016-05-02 21:08:44,868 Node[0] Epoch[199] Batch [200] Speed: 624.32 samples/sec Train-accuracy=0.999687
2016-05-02 21:08:55,156 Node[0] Epoch[199] Batch [250] Speed: 622.13 samples/sec Train-accuracy=0.999844
2016-05-02 21:09:05,485 Node[0] Epoch[199] Batch [300] Speed: 619.59 samples/sec Train-accuracy=0.999844
2016-05-02 21:09:15,792 Node[0] Epoch[199] Batch [350] Speed: 620.97 samples/sec Train-accuracy=0.999844
2016-05-02 21:09:24,084 Node[0] Epoch[199] Resetting Data Iterator
2016-05-02 21:09:24,084 Node[0] Epoch[199] Time cost=80.397
2016-05-02 21:09:24,245 Node[0] Saved checkpoint to "cifar10/resnet-0200.params"
2016-05-02 21:09:26,091 Node[0] Epoch[199] Validation-accuracy=0.925581
2016-05-03 03:12:07,964 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:14:03,632 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:14:41,001 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:14:41,385 Node[0] Start training with [gpu(0)]
2016-05-03 03:15:02,247 Node[0] Epoch[0] Batch [50] Speed: 651.27 samples/sec Train-accuracy=0.109531
2016-05-03 03:15:12,380 Node[0] Epoch[0] Batch [100] Speed: 631.65 samples/sec Train-accuracy=0.135625
2016-05-03 03:15:22,459 Node[0] Epoch[0] Batch [150] Speed: 635.00 samples/sec Train-accuracy=0.164687
2016-05-03 03:15:32,595 Node[0] Epoch[0] Batch [200] Speed: 631.40 samples/sec Train-accuracy=0.212344
2016-05-03 03:15:42,796 Node[0] Epoch[0] Batch [250] Speed: 627.42 samples/sec Train-accuracy=0.251094
2016-05-03 03:15:52,943 Node[0] Epoch[0] Batch [300] Speed: 630.77 samples/sec Train-accuracy=0.280938
2016-05-03 03:17:02,539 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:17:28,686 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:19:01,678 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:19:11,536 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 03:19:11,911 Node[0] Start training with [gpu(0)]
2016-05-03 03:19:32,962 Node[0] Epoch[0] Batch [50] Speed: 646.82 samples/sec Train-accuracy=0.118906
2016-05-03 03:19:43,067 Node[0] Epoch[0] Batch [100] Speed: 633.33 samples/sec Train-accuracy=0.150781
2016-05-03 03:19:53,174 Node[0] Epoch[0] Batch [150] Speed: 633.27 samples/sec Train-accuracy=0.208750
2016-05-03 03:20:03,286 Node[0] Epoch[0] Batch [200] Speed: 632.92 samples/sec Train-accuracy=0.232813
2016-05-03 03:20:13,428 Node[0] Epoch[0] Batch [250] Speed: 631.08 samples/sec Train-accuracy=0.272031
2016-05-03 03:20:23,584 Node[0] Epoch[0] Batch [300] Speed: 630.15 samples/sec Train-accuracy=0.302344
2016-05-03 03:20:33,741 Node[0] Epoch[0] Batch [350] Speed: 630.12 samples/sec Train-accuracy=0.322813
2016-05-03 03:20:42,120 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 03:20:42,121 Node[0] Epoch[0] Time cost=79.376
2016-05-03 03:20:42,282 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 03:20:44,281 Node[0] Epoch[0] Validation-accuracy=0.356210
2016-05-03 03:20:54,873 Node[0] Epoch[1] Batch [50] Speed: 607.14 samples/sec Train-accuracy=0.362969
2016-05-03 03:21:05,356 Node[0] Epoch[1] Batch [100] Speed: 610.51 samples/sec Train-accuracy=0.391094
2016-05-03 03:21:15,741 Node[0] Epoch[1] Batch [150] Speed: 616.30 samples/sec Train-accuracy=0.412187
2016-05-03 03:21:26,107 Node[0] Epoch[1] Batch [200] Speed: 617.42 samples/sec Train-accuracy=0.409687
2016-05-03 03:21:36,487 Node[0] Epoch[1] Batch [250] Speed: 616.60 samples/sec Train-accuracy=0.433594
2016-05-03 03:21:46,946 Node[0] Epoch[1] Batch [300] Speed: 611.93 samples/sec Train-accuracy=0.440469
2016-05-03 03:21:57,457 Node[0] Epoch[1] Batch [350] Speed: 608.89 samples/sec Train-accuracy=0.466719
2016-05-03 03:22:06,005 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 03:22:06,005 Node[0] Epoch[1] Time cost=81.724
2016-05-03 03:22:06,169 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 03:22:08,052 Node[0] Epoch[1] Validation-accuracy=0.463442
2016-05-03 03:22:18,427 Node[0] Epoch[2] Batch [50] Speed: 620.03 samples/sec Train-accuracy=0.482187
2016-05-03 03:22:28,823 Node[0] Epoch[2] Batch [100] Speed: 615.64 samples/sec Train-accuracy=0.507812
2016-05-03 03:22:39,251 Node[0] Epoch[2] Batch [150] Speed: 613.75 samples/sec Train-accuracy=0.504219
2016-05-03 03:22:49,629 Node[0] Epoch[2] Batch [200] Speed: 616.71 samples/sec Train-accuracy=0.530469
2016-05-03 03:23:00,020 Node[0] Epoch[2] Batch [250] Speed: 615.93 samples/sec Train-accuracy=0.545156
2016-05-03 03:23:10,422 Node[0] Epoch[2] Batch [300] Speed: 615.27 samples/sec Train-accuracy=0.541250
2016-05-03 03:23:20,833 Node[0] Epoch[2] Batch [350] Speed: 614.76 samples/sec Train-accuracy=0.559063
2016-05-03 03:23:29,151 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 03:23:29,151 Node[0] Epoch[2] Time cost=81.099
2016-05-03 03:23:29,312 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 03:23:31,228 Node[0] Epoch[2] Validation-accuracy=0.551482
2016-05-03 03:23:41,723 Node[0] Epoch[3] Batch [50] Speed: 613.05 samples/sec Train-accuracy=0.594531
2016-05-03 03:23:52,132 Node[0] Epoch[3] Batch [100] Speed: 614.86 samples/sec Train-accuracy=0.592969
2016-05-03 03:24:02,549 Node[0] Epoch[3] Batch [150] Speed: 614.43 samples/sec Train-accuracy=0.615156
2016-05-03 03:24:12,943 Node[0] Epoch[3] Batch [200] Speed: 615.75 samples/sec Train-accuracy=0.612969
2016-05-03 03:24:23,388 Node[0] Epoch[3] Batch [250] Speed: 612.72 samples/sec Train-accuracy=0.626406
2016-05-03 03:24:33,783 Node[0] Epoch[3] Batch [300] Speed: 615.70 samples/sec Train-accuracy=0.636875
2016-05-03 03:24:44,187 Node[0] Epoch[3] Batch [350] Speed: 615.18 samples/sec Train-accuracy=0.645781
2016-05-03 03:24:52,709 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 03:24:52,709 Node[0] Epoch[3] Time cost=81.481
2016-05-03 03:24:52,872 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 03:24:54,806 Node[0] Epoch[3] Validation-accuracy=0.616587
2016-05-03 03:25:05,249 Node[0] Epoch[4] Batch [50] Speed: 616.04 samples/sec Train-accuracy=0.656250
2016-05-03 03:25:15,704 Node[0] Epoch[4] Batch [100] Speed: 612.24 samples/sec Train-accuracy=0.661875
2016-05-03 03:25:26,195 Node[0] Epoch[4] Batch [150] Speed: 610.05 samples/sec Train-accuracy=0.678281
2016-05-03 03:25:36,636 Node[0] Epoch[4] Batch [200] Speed: 612.96 samples/sec Train-accuracy=0.688906
2016-05-03 03:25:47,005 Node[0] Epoch[4] Batch [250] Speed: 617.27 samples/sec Train-accuracy=0.689063
2016-05-03 03:25:57,374 Node[0] Epoch[4] Batch [300] Speed: 617.19 samples/sec Train-accuracy=0.689688
2016-05-03 03:26:07,780 Node[0] Epoch[4] Batch [350] Speed: 615.07 samples/sec Train-accuracy=0.697656
2016-05-03 03:26:16,283 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 03:26:16,283 Node[0] Epoch[4] Time cost=81.477
2016-05-03 03:26:16,449 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 03:26:18,326 Node[0] Epoch[4] Validation-accuracy=0.685096
2016-05-03 03:26:28,791 Node[0] Epoch[5] Batch [50] Speed: 614.88 samples/sec Train-accuracy=0.713281
2016-05-03 03:26:39,176 Node[0] Epoch[5] Batch [100] Speed: 616.29 samples/sec Train-accuracy=0.717656
2016-05-03 03:26:49,573 Node[0] Epoch[5] Batch [150] Speed: 615.52 samples/sec Train-accuracy=0.732656
2016-05-03 03:26:59,964 Node[0] Epoch[5] Batch [200] Speed: 615.99 samples/sec Train-accuracy=0.735469
2016-05-03 03:27:10,365 Node[0] Epoch[5] Batch [250] Speed: 615.31 samples/sec Train-accuracy=0.733125
2016-05-03 03:27:20,800 Node[0] Epoch[5] Batch [300] Speed: 613.34 samples/sec Train-accuracy=0.741719
2016-05-03 03:27:31,275 Node[0] Epoch[5] Batch [350] Speed: 611.00 samples/sec Train-accuracy=0.743906
2016-05-03 03:27:39,608 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 03:27:39,608 Node[0] Epoch[5] Time cost=81.283
2016-05-03 03:27:39,776 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 03:27:41,679 Node[0] Epoch[5] Validation-accuracy=0.730369
2016-05-03 03:27:52,059 Node[0] Epoch[6] Batch [50] Speed: 619.84 samples/sec Train-accuracy=0.749844
2016-05-03 03:28:02,505 Node[0] Epoch[6] Batch [100] Speed: 612.68 samples/sec Train-accuracy=0.757656
2016-05-03 03:28:12,876 Node[0] Epoch[6] Batch [150] Speed: 617.12 samples/sec Train-accuracy=0.770312
2016-05-03 03:28:23,284 Node[0] Epoch[6] Batch [200] Speed: 614.91 samples/sec Train-accuracy=0.768437
2016-05-03 03:28:33,694 Node[0] Epoch[6] Batch [250] Speed: 614.84 samples/sec Train-accuracy=0.767344
2016-05-03 03:28:44,090 Node[0] Epoch[6] Batch [300] Speed: 615.63 samples/sec Train-accuracy=0.776875
2016-05-03 03:28:54,465 Node[0] Epoch[6] Batch [350] Speed: 616.91 samples/sec Train-accuracy=0.784531
2016-05-03 03:29:03,006 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 03:29:03,007 Node[0] Epoch[6] Time cost=81.327
2016-05-03 03:29:03,174 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 03:29:05,074 Node[0] Epoch[6] Validation-accuracy=0.755709
2016-05-03 03:29:15,479 Node[0] Epoch[7] Batch [50] Speed: 618.35 samples/sec Train-accuracy=0.776250
2016-05-03 03:29:25,886 Node[0] Epoch[7] Batch [100] Speed: 614.93 samples/sec Train-accuracy=0.785781
2016-05-03 03:29:36,323 Node[0] Epoch[7] Batch [150] Speed: 613.27 samples/sec Train-accuracy=0.801250
2016-05-03 03:29:46,724 Node[0] Epoch[7] Batch [200] Speed: 615.34 samples/sec Train-accuracy=0.800469
2016-05-03 03:29:57,119 Node[0] Epoch[7] Batch [250] Speed: 615.67 samples/sec Train-accuracy=0.797969
2016-05-03 03:30:07,562 Node[0] Epoch[7] Batch [300] Speed: 612.86 samples/sec Train-accuracy=0.795781
2016-05-03 03:30:17,962 Node[0] Epoch[7] Batch [350] Speed: 615.43 samples/sec Train-accuracy=0.804063
2016-05-03 03:30:26,260 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 03:30:26,260 Node[0] Epoch[7] Time cost=81.186
2016-05-03 03:30:26,435 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 03:30:28,352 Node[0] Epoch[7] Validation-accuracy=0.758313
2016-05-03 03:30:38,790 Node[0] Epoch[8] Batch [50] Speed: 616.51 samples/sec Train-accuracy=0.803750
2016-05-03 03:30:49,223 Node[0] Epoch[8] Batch [100] Speed: 613.47 samples/sec Train-accuracy=0.810469
2016-05-03 03:30:59,646 Node[0] Epoch[8] Batch [150] Speed: 614.02 samples/sec Train-accuracy=0.816719
2016-05-03 03:31:10,034 Node[0] Epoch[8] Batch [200] Speed: 616.09 samples/sec Train-accuracy=0.817344
2016-05-03 03:31:20,469 Node[0] Epoch[8] Batch [250] Speed: 613.36 samples/sec Train-accuracy=0.808906
2016-05-03 03:31:30,877 Node[0] Epoch[8] Batch [300] Speed: 614.91 samples/sec Train-accuracy=0.816875
2016-05-03 03:31:41,287 Node[0] Epoch[8] Batch [350] Speed: 614.82 samples/sec Train-accuracy=0.809844
2016-05-03 03:31:49,791 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 03:31:49,792 Node[0] Epoch[8] Time cost=81.439
2016-05-03 03:31:49,955 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 03:31:52,107 Node[0] Epoch[8] Validation-accuracy=0.792919
2016-05-03 03:32:02,565 Node[0] Epoch[9] Batch [50] Speed: 615.20 samples/sec Train-accuracy=0.817344
2016-05-03 03:32:12,965 Node[0] Epoch[9] Batch [100] Speed: 615.39 samples/sec Train-accuracy=0.820000
2016-05-03 03:32:23,382 Node[0] Epoch[9] Batch [150] Speed: 614.40 samples/sec Train-accuracy=0.832187
2016-05-03 03:32:33,778 Node[0] Epoch[9] Batch [200] Speed: 615.65 samples/sec Train-accuracy=0.822812
2016-05-03 03:32:44,171 Node[0] Epoch[9] Batch [250] Speed: 615.78 samples/sec Train-accuracy=0.816250
2016-05-03 03:32:54,627 Node[0] Epoch[9] Batch [300] Speed: 612.11 samples/sec Train-accuracy=0.830937
2016-05-03 03:33:05,046 Node[0] Epoch[9] Batch [350] Speed: 614.31 samples/sec Train-accuracy=0.830625
2016-05-03 03:33:13,580 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 03:33:13,580 Node[0] Epoch[9] Time cost=81.473
2016-05-03 03:33:13,750 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 03:33:15,643 Node[0] Epoch[9] Validation-accuracy=0.797576
2016-05-03 03:33:26,096 Node[0] Epoch[10] Batch [50] Speed: 615.49 samples/sec Train-accuracy=0.831406
2016-05-03 03:33:36,497 Node[0] Epoch[10] Batch [100] Speed: 615.34 samples/sec Train-accuracy=0.831719
2016-05-03 03:33:46,871 Node[0] Epoch[10] Batch [150] Speed: 616.96 samples/sec Train-accuracy=0.835781
2016-05-03 03:33:57,235 Node[0] Epoch[10] Batch [200] Speed: 617.53 samples/sec Train-accuracy=0.835313
2016-05-03 03:34:07,627 Node[0] Epoch[10] Batch [250] Speed: 615.91 samples/sec Train-accuracy=0.830625
2016-05-03 03:34:18,051 Node[0] Epoch[10] Batch [300] Speed: 613.97 samples/sec Train-accuracy=0.842812
2016-05-03 03:34:28,452 Node[0] Epoch[10] Batch [350] Speed: 615.33 samples/sec Train-accuracy=0.831875
2016-05-03 03:34:36,777 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 03:34:36,778 Node[0] Epoch[10] Time cost=81.134
2016-05-03 03:34:36,939 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 03:34:38,861 Node[0] Epoch[10] Validation-accuracy=0.807893
2016-05-03 03:34:49,347 Node[0] Epoch[11] Batch [50] Speed: 613.56 samples/sec Train-accuracy=0.842969
2016-05-03 03:34:59,738 Node[0] Epoch[11] Batch [100] Speed: 615.94 samples/sec Train-accuracy=0.836250
2016-05-03 03:35:10,123 Node[0] Epoch[11] Batch [150] Speed: 616.29 samples/sec Train-accuracy=0.849844
2016-05-03 03:35:20,524 Node[0] Epoch[11] Batch [200] Speed: 615.33 samples/sec Train-accuracy=0.847500
2016-05-03 03:35:30,938 Node[0] Epoch[11] Batch [250] Speed: 614.60 samples/sec Train-accuracy=0.839844
2016-05-03 03:35:41,312 Node[0] Epoch[11] Batch [300] Speed: 616.92 samples/sec Train-accuracy=0.848437
2016-05-03 03:35:51,693 Node[0] Epoch[11] Batch [350] Speed: 616.56 samples/sec Train-accuracy=0.848281
2016-05-03 03:36:00,234 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 03:36:00,234 Node[0] Epoch[11] Time cost=81.373
2016-05-03 03:36:00,399 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 03:36:02,363 Node[0] Epoch[11] Validation-accuracy=0.805088
2016-05-03 03:36:12,814 Node[0] Epoch[12] Batch [50] Speed: 615.62 samples/sec Train-accuracy=0.854531
2016-05-03 03:36:23,242 Node[0] Epoch[12] Batch [100] Speed: 613.75 samples/sec Train-accuracy=0.855938
2016-05-03 03:36:33,648 Node[0] Epoch[12] Batch [150] Speed: 615.07 samples/sec Train-accuracy=0.857656
2016-05-03 03:36:44,092 Node[0] Epoch[12] Batch [200] Speed: 612.80 samples/sec Train-accuracy=0.851406
2016-05-03 03:36:54,476 Node[0] Epoch[12] Batch [250] Speed: 616.32 samples/sec Train-accuracy=0.856875
2016-05-03 03:37:04,929 Node[0] Epoch[12] Batch [300] Speed: 612.32 samples/sec Train-accuracy=0.858594
2016-05-03 03:37:15,375 Node[0] Epoch[12] Batch [350] Speed: 612.64 samples/sec Train-accuracy=0.857656
2016-05-03 03:37:23,914 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 03:37:23,914 Node[0] Epoch[12] Time cost=81.551
2016-05-03 03:37:24,075 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 03:37:25,998 Node[0] Epoch[12] Validation-accuracy=0.800280
2016-05-03 03:37:36,495 Node[0] Epoch[13] Batch [50] Speed: 612.86 samples/sec Train-accuracy=0.853125
2016-05-03 03:37:46,962 Node[0] Epoch[13] Batch [100] Speed: 611.48 samples/sec Train-accuracy=0.856094
2016-05-03 03:37:57,360 Node[0] Epoch[13] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.867656
2016-05-03 03:38:07,771 Node[0] Epoch[13] Batch [200] Speed: 614.75 samples/sec Train-accuracy=0.858125
2016-05-03 03:38:18,183 Node[0] Epoch[13] Batch [250] Speed: 614.67 samples/sec Train-accuracy=0.866250
2016-05-03 03:38:28,615 Node[0] Epoch[13] Batch [300] Speed: 613.50 samples/sec Train-accuracy=0.868906
2016-05-03 03:38:39,082 Node[0] Epoch[13] Batch [350] Speed: 611.48 samples/sec Train-accuracy=0.863594
2016-05-03 03:38:47,402 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 03:38:47,402 Node[0] Epoch[13] Time cost=81.404
2016-05-03 03:38:47,567 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 03:38:49,447 Node[0] Epoch[13] Validation-accuracy=0.826322
2016-05-03 03:38:59,987 Node[0] Epoch[14] Batch [50] Speed: 610.40 samples/sec Train-accuracy=0.863750
2016-05-03 03:39:10,440 Node[0] Epoch[14] Batch [100] Speed: 612.32 samples/sec Train-accuracy=0.866094
2016-05-03 03:39:20,862 Node[0] Epoch[14] Batch [150] Speed: 614.10 samples/sec Train-accuracy=0.865313
2016-05-03 03:39:31,231 Node[0] Epoch[14] Batch [200] Speed: 617.19 samples/sec Train-accuracy=0.866563
2016-05-03 03:39:41,616 Node[0] Epoch[14] Batch [250] Speed: 616.29 samples/sec Train-accuracy=0.867500
2016-05-03 03:39:52,025 Node[0] Epoch[14] Batch [300] Speed: 614.90 samples/sec Train-accuracy=0.862656
2016-05-03 03:40:02,453 Node[0] Epoch[14] Batch [350] Speed: 613.72 samples/sec Train-accuracy=0.864688
2016-05-03 03:40:10,969 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 03:40:10,970 Node[0] Epoch[14] Time cost=81.522
2016-05-03 03:40:11,133 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 03:40:13,111 Node[0] Epoch[14] Validation-accuracy=0.832031
2016-05-03 03:40:23,605 Node[0] Epoch[15] Batch [50] Speed: 613.10 samples/sec Train-accuracy=0.867656
2016-05-03 03:40:34,026 Node[0] Epoch[15] Batch [100] Speed: 614.14 samples/sec Train-accuracy=0.877969
2016-05-03 03:40:44,443 Node[0] Epoch[15] Batch [150] Speed: 614.38 samples/sec Train-accuracy=0.874531
2016-05-03 03:40:54,893 Node[0] Epoch[15] Batch [200] Speed: 612.46 samples/sec Train-accuracy=0.875000
2016-05-03 03:41:05,324 Node[0] Epoch[15] Batch [250] Speed: 613.61 samples/sec Train-accuracy=0.872656
2016-05-03 03:41:15,735 Node[0] Epoch[15] Batch [300] Speed: 614.69 samples/sec Train-accuracy=0.876250
2016-05-03 03:41:26,156 Node[0] Epoch[15] Batch [350] Speed: 614.21 samples/sec Train-accuracy=0.873281
2016-05-03 03:41:34,468 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 03:41:34,468 Node[0] Epoch[15] Time cost=81.357
2016-05-03 03:41:34,635 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 03:41:36,528 Node[0] Epoch[15] Validation-accuracy=0.834235
2016-05-03 03:41:47,096 Node[0] Epoch[16] Batch [50] Speed: 608.83 samples/sec Train-accuracy=0.875625
2016-05-03 03:41:57,556 Node[0] Epoch[16] Batch [100] Speed: 611.84 samples/sec Train-accuracy=0.873750
2016-05-03 03:42:07,968 Node[0] Epoch[16] Batch [150] Speed: 614.74 samples/sec Train-accuracy=0.872344
2016-05-03 03:42:18,392 Node[0] Epoch[16] Batch [200] Speed: 613.99 samples/sec Train-accuracy=0.870156
2016-05-03 03:42:28,836 Node[0] Epoch[16] Batch [250] Speed: 612.76 samples/sec Train-accuracy=0.875469
2016-05-03 03:42:39,247 Node[0] Epoch[16] Batch [300] Speed: 614.77 samples/sec Train-accuracy=0.877188
2016-05-03 03:42:49,620 Node[0] Epoch[16] Batch [350] Speed: 617.02 samples/sec Train-accuracy=0.874375
2016-05-03 03:42:58,128 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 03:42:58,129 Node[0] Epoch[16] Time cost=81.600
2016-05-03 03:42:58,291 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 03:43:00,414 Node[0] Epoch[16] Validation-accuracy=0.830696
2016-05-03 03:43:10,948 Node[0] Epoch[17] Batch [50] Speed: 610.76 samples/sec Train-accuracy=0.877812
2016-05-03 03:43:21,448 Node[0] Epoch[17] Batch [100] Speed: 609.56 samples/sec Train-accuracy=0.882656
2016-05-03 03:43:31,879 Node[0] Epoch[17] Batch [150] Speed: 613.56 samples/sec Train-accuracy=0.887188
2016-05-03 03:43:42,272 Node[0] Epoch[17] Batch [200] Speed: 615.80 samples/sec Train-accuracy=0.885938
2016-05-03 03:43:52,610 Node[0] Epoch[17] Batch [250] Speed: 619.10 samples/sec Train-accuracy=0.880938
2016-05-03 03:44:03,102 Node[0] Epoch[17] Batch [300] Speed: 609.99 samples/sec Train-accuracy=0.879375
2016-05-03 03:44:13,550 Node[0] Epoch[17] Batch [350] Speed: 612.59 samples/sec Train-accuracy=0.878750
2016-05-03 03:44:22,113 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 03:44:22,113 Node[0] Epoch[17] Time cost=81.700
2016-05-03 03:44:22,276 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 03:44:24,201 Node[0] Epoch[17] Validation-accuracy=0.834736
2016-05-03 03:44:34,600 Node[0] Epoch[18] Batch [50] Speed: 618.63 samples/sec Train-accuracy=0.881875
2016-05-03 03:44:44,975 Node[0] Epoch[18] Batch [100] Speed: 616.91 samples/sec Train-accuracy=0.888281
2016-05-03 03:44:55,365 Node[0] Epoch[18] Batch [150] Speed: 615.97 samples/sec Train-accuracy=0.884531
2016-05-03 03:45:05,784 Node[0] Epoch[18] Batch [200] Speed: 614.33 samples/sec Train-accuracy=0.884687
2016-05-03 03:45:16,190 Node[0] Epoch[18] Batch [250] Speed: 615.04 samples/sec Train-accuracy=0.883906
2016-05-03 03:45:26,620 Node[0] Epoch[18] Batch [300] Speed: 613.64 samples/sec Train-accuracy=0.890312
2016-05-03 03:45:37,019 Node[0] Epoch[18] Batch [350] Speed: 615.42 samples/sec Train-accuracy=0.887188
2016-05-03 03:45:45,348 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 03:45:45,349 Node[0] Epoch[18] Time cost=81.148
2016-05-03 03:45:45,516 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 03:45:47,415 Node[0] Epoch[18] Validation-accuracy=0.847857
2016-05-03 03:45:57,925 Node[0] Epoch[19] Batch [50] Speed: 612.29 samples/sec Train-accuracy=0.891563
2016-05-03 03:46:08,327 Node[0] Epoch[19] Batch [100] Speed: 615.30 samples/sec Train-accuracy=0.901406
2016-05-03 03:46:18,728 Node[0] Epoch[19] Batch [150] Speed: 615.35 samples/sec Train-accuracy=0.890000
2016-05-03 03:46:29,086 Node[0] Epoch[19] Batch [200] Speed: 617.88 samples/sec Train-accuracy=0.887188
2016-05-03 03:46:39,464 Node[0] Epoch[19] Batch [250] Speed: 616.73 samples/sec Train-accuracy=0.891563
2016-05-03 03:46:49,879 Node[0] Epoch[19] Batch [300] Speed: 614.54 samples/sec Train-accuracy=0.889687
2016-05-03 03:47:00,278 Node[0] Epoch[19] Batch [350] Speed: 615.42 samples/sec Train-accuracy=0.887031
2016-05-03 03:47:08,805 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 03:47:08,805 Node[0] Epoch[19] Time cost=81.390
2016-05-03 03:47:08,965 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 03:47:10,860 Node[0] Epoch[19] Validation-accuracy=0.856270
2016-05-03 03:47:21,389 Node[0] Epoch[20] Batch [50] Speed: 611.05 samples/sec Train-accuracy=0.893594
2016-05-03 03:47:31,754 Node[0] Epoch[20] Batch [100] Speed: 617.48 samples/sec Train-accuracy=0.895469
2016-05-03 03:47:42,128 Node[0] Epoch[20] Batch [150] Speed: 616.93 samples/sec Train-accuracy=0.900625
2016-05-03 03:47:52,545 Node[0] Epoch[20] Batch [200] Speed: 614.37 samples/sec Train-accuracy=0.890000
2016-05-03 03:48:02,949 Node[0] Epoch[20] Batch [250] Speed: 615.18 samples/sec Train-accuracy=0.896719
2016-05-03 03:48:13,337 Node[0] Epoch[20] Batch [300] Speed: 616.10 samples/sec Train-accuracy=0.896406
2016-05-03 03:48:23,748 Node[0] Epoch[20] Batch [350] Speed: 614.78 samples/sec Train-accuracy=0.892813
2016-05-03 03:48:32,339 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 03:48:32,339 Node[0] Epoch[20] Time cost=81.479
2016-05-03 03:48:32,499 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 03:48:34,402 Node[0] Epoch[20] Validation-accuracy=0.855369
2016-05-03 03:48:44,884 Node[0] Epoch[21] Batch [50] Speed: 613.79 samples/sec Train-accuracy=0.894531
2016-05-03 03:48:55,276 Node[0] Epoch[21] Batch [100] Speed: 615.88 samples/sec Train-accuracy=0.896719
2016-05-03 03:49:05,693 Node[0] Epoch[21] Batch [150] Speed: 614.41 samples/sec Train-accuracy=0.903281
2016-05-03 03:49:16,056 Node[0] Epoch[21] Batch [200] Speed: 617.58 samples/sec Train-accuracy=0.897656
2016-05-03 03:49:26,523 Node[0] Epoch[21] Batch [250] Speed: 611.47 samples/sec Train-accuracy=0.897031
2016-05-03 03:49:36,970 Node[0] Epoch[21] Batch [300] Speed: 612.62 samples/sec Train-accuracy=0.900312
2016-05-03 03:49:47,362 Node[0] Epoch[21] Batch [350] Speed: 615.91 samples/sec Train-accuracy=0.898281
2016-05-03 03:49:55,702 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 03:49:55,703 Node[0] Epoch[21] Time cost=81.300
2016-05-03 03:49:55,866 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 03:49:57,790 Node[0] Epoch[21] Validation-accuracy=0.855970
2016-05-03 03:50:08,289 Node[0] Epoch[22] Batch [50] Speed: 612.77 samples/sec Train-accuracy=0.901875
2016-05-03 03:50:18,713 Node[0] Epoch[22] Batch [100] Speed: 614.00 samples/sec Train-accuracy=0.905312
2016-05-03 03:50:29,083 Node[0] Epoch[22] Batch [150] Speed: 617.17 samples/sec Train-accuracy=0.897500
2016-05-03 03:50:39,470 Node[0] Epoch[22] Batch [200] Speed: 616.13 samples/sec Train-accuracy=0.900156
2016-05-03 03:50:49,854 Node[0] Epoch[22] Batch [250] Speed: 616.35 samples/sec Train-accuracy=0.897031
2016-05-03 03:51:00,282 Node[0] Epoch[22] Batch [300] Speed: 613.77 samples/sec Train-accuracy=0.900156
2016-05-03 03:51:10,673 Node[0] Epoch[22] Batch [350] Speed: 615.96 samples/sec Train-accuracy=0.901406
2016-05-03 03:51:19,181 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 03:51:19,181 Node[0] Epoch[22] Time cost=81.391
2016-05-03 03:51:19,349 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 03:51:21,270 Node[0] Epoch[22] Validation-accuracy=0.837139
2016-05-03 03:51:31,793 Node[0] Epoch[23] Batch [50] Speed: 611.37 samples/sec Train-accuracy=0.902031
2016-05-03 03:51:42,193 Node[0] Epoch[23] Batch [100] Speed: 615.44 samples/sec Train-accuracy=0.899687
2016-05-03 03:51:52,572 Node[0] Epoch[23] Batch [150] Speed: 616.60 samples/sec Train-accuracy=0.905000
2016-05-03 03:52:02,965 Node[0] Epoch[23] Batch [200] Speed: 615.84 samples/sec Train-accuracy=0.901563
2016-05-03 03:52:13,345 Node[0] Epoch[23] Batch [250] Speed: 616.55 samples/sec Train-accuracy=0.896406
2016-05-03 03:52:23,766 Node[0] Epoch[23] Batch [300] Speed: 614.22 samples/sec Train-accuracy=0.911094
2016-05-03 03:52:34,186 Node[0] Epoch[23] Batch [350] Speed: 614.21 samples/sec Train-accuracy=0.896719
2016-05-03 03:52:42,518 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 03:52:42,518 Node[0] Epoch[23] Time cost=81.248
2016-05-03 03:52:42,686 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 03:52:44,592 Node[0] Epoch[23] Validation-accuracy=0.857372
2016-05-03 03:52:55,130 Node[0] Epoch[24] Batch [50] Speed: 610.57 samples/sec Train-accuracy=0.901094
2016-05-03 03:53:05,580 Node[0] Epoch[24] Batch [100] Speed: 612.44 samples/sec Train-accuracy=0.905312
2016-05-03 03:53:15,982 Node[0] Epoch[24] Batch [150] Speed: 615.29 samples/sec Train-accuracy=0.905469
2016-05-03 03:53:26,396 Node[0] Epoch[24] Batch [200] Speed: 614.54 samples/sec Train-accuracy=0.907813
2016-05-03 03:53:36,814 Node[0] Epoch[24] Batch [250] Speed: 614.34 samples/sec Train-accuracy=0.901563
2016-05-03 03:53:47,203 Node[0] Epoch[24] Batch [300] Speed: 616.04 samples/sec Train-accuracy=0.916562
2016-05-03 03:53:57,557 Node[0] Epoch[24] Batch [350] Speed: 618.16 samples/sec Train-accuracy=0.900156
2016-05-03 03:54:06,063 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 03:54:06,063 Node[0] Epoch[24] Time cost=81.470
2016-05-03 03:54:06,225 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 03:54:08,324 Node[0] Epoch[24] Validation-accuracy=0.862540
2016-05-03 03:54:18,822 Node[0] Epoch[25] Batch [50] Speed: 612.89 samples/sec Train-accuracy=0.896875
2016-05-03 03:54:29,305 Node[0] Epoch[25] Batch [100] Speed: 610.49 samples/sec Train-accuracy=0.904687
2016-05-03 03:54:39,681 Node[0] Epoch[25] Batch [150] Speed: 616.88 samples/sec Train-accuracy=0.907656
2016-05-03 03:54:50,053 Node[0] Epoch[25] Batch [200] Speed: 617.04 samples/sec Train-accuracy=0.908906
2016-05-03 03:55:00,486 Node[0] Epoch[25] Batch [250] Speed: 613.47 samples/sec Train-accuracy=0.907188
2016-05-03 03:55:10,900 Node[0] Epoch[25] Batch [300] Speed: 614.58 samples/sec Train-accuracy=0.913906
2016-05-03 03:55:21,268 Node[0] Epoch[25] Batch [350] Speed: 617.29 samples/sec Train-accuracy=0.907500
2016-05-03 03:55:29,759 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 03:55:29,760 Node[0] Epoch[25] Time cost=81.436
2016-05-03 03:55:29,927 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 03:55:31,850 Node[0] Epoch[25] Validation-accuracy=0.860076
2016-05-03 03:55:42,347 Node[0] Epoch[26] Batch [50] Speed: 612.83 samples/sec Train-accuracy=0.910000
2016-05-03 03:55:52,761 Node[0] Epoch[26] Batch [100] Speed: 614.61 samples/sec Train-accuracy=0.902031
2016-05-03 03:56:03,142 Node[0] Epoch[26] Batch [150] Speed: 616.53 samples/sec Train-accuracy=0.907656
2016-05-03 03:56:13,525 Node[0] Epoch[26] Batch [200] Speed: 616.41 samples/sec Train-accuracy=0.910781
2016-05-03 03:56:23,994 Node[0] Epoch[26] Batch [250] Speed: 611.33 samples/sec Train-accuracy=0.912813
2016-05-03 03:56:34,437 Node[0] Epoch[26] Batch [300] Speed: 612.86 samples/sec Train-accuracy=0.912031
2016-05-03 03:56:44,980 Node[0] Epoch[26] Batch [350] Speed: 607.04 samples/sec Train-accuracy=0.909375
2016-05-03 03:56:53,319 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 03:56:53,319 Node[0] Epoch[26] Time cost=81.469
2016-05-03 03:56:53,482 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 03:56:55,364 Node[0] Epoch[26] Validation-accuracy=0.858273
2016-05-03 03:57:05,784 Node[0] Epoch[27] Batch [50] Speed: 617.41 samples/sec Train-accuracy=0.902188
2016-05-03 03:57:16,208 Node[0] Epoch[27] Batch [100] Speed: 614.00 samples/sec Train-accuracy=0.909219
2016-05-03 03:57:26,604 Node[0] Epoch[27] Batch [150] Speed: 615.66 samples/sec Train-accuracy=0.915312
2016-05-03 03:57:37,008 Node[0] Epoch[27] Batch [200] Speed: 615.11 samples/sec Train-accuracy=0.919375
2016-05-03 03:57:47,422 Node[0] Epoch[27] Batch [250] Speed: 614.61 samples/sec Train-accuracy=0.915469
2016-05-03 03:57:57,817 Node[0] Epoch[27] Batch [300] Speed: 615.68 samples/sec Train-accuracy=0.906719
2016-05-03 03:58:08,221 Node[0] Epoch[27] Batch [350] Speed: 615.18 samples/sec Train-accuracy=0.912344
2016-05-03 03:58:16,781 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 03:58:16,782 Node[0] Epoch[27] Time cost=81.417
2016-05-03 03:58:16,945 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 03:58:18,875 Node[0] Epoch[27] Validation-accuracy=0.857071
2016-05-03 03:58:29,357 Node[0] Epoch[28] Batch [50] Speed: 613.76 samples/sec Train-accuracy=0.915625
2016-05-03 03:58:39,786 Node[0] Epoch[28] Batch [100] Speed: 613.70 samples/sec Train-accuracy=0.908594
2016-05-03 03:58:50,171 Node[0] Epoch[28] Batch [150] Speed: 616.31 samples/sec Train-accuracy=0.910000
2016-05-03 03:59:00,587 Node[0] Epoch[28] Batch [200] Speed: 614.42 samples/sec Train-accuracy=0.910156
2016-05-03 03:59:11,006 Node[0] Epoch[28] Batch [250] Speed: 614.28 samples/sec Train-accuracy=0.917031
2016-05-03 03:59:21,397 Node[0] Epoch[28] Batch [300] Speed: 615.95 samples/sec Train-accuracy=0.918750
2016-05-03 03:59:31,869 Node[0] Epoch[28] Batch [350] Speed: 611.19 samples/sec Train-accuracy=0.916719
2016-05-03 03:59:40,447 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 03:59:40,448 Node[0] Epoch[28] Time cost=81.572
2016-05-03 03:59:40,609 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 03:59:42,556 Node[0] Epoch[28] Validation-accuracy=0.849860
2016-05-03 03:59:53,055 Node[0] Epoch[29] Batch [50] Speed: 612.71 samples/sec Train-accuracy=0.918750
2016-05-03 04:00:03,480 Node[0] Epoch[29] Batch [100] Speed: 613.95 samples/sec Train-accuracy=0.918750
2016-05-03 04:00:13,835 Node[0] Epoch[29] Batch [150] Speed: 618.09 samples/sec Train-accuracy=0.918750
2016-05-03 04:00:24,243 Node[0] Epoch[29] Batch [200] Speed: 614.93 samples/sec Train-accuracy=0.915937
2016-05-03 04:00:34,658 Node[0] Epoch[29] Batch [250] Speed: 614.47 samples/sec Train-accuracy=0.920312
2016-05-03 04:00:45,029 Node[0] Epoch[29] Batch [300] Speed: 617.17 samples/sec Train-accuracy=0.914062
2016-05-03 04:00:55,451 Node[0] Epoch[29] Batch [350] Speed: 614.05 samples/sec Train-accuracy=0.915156
2016-05-03 04:01:03,734 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 04:01:03,734 Node[0] Epoch[29] Time cost=81.179
2016-05-03 04:01:03,895 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 04:01:05,829 Node[0] Epoch[29] Validation-accuracy=0.867087
2016-05-03 04:01:16,359 Node[0] Epoch[30] Batch [50] Speed: 611.00 samples/sec Train-accuracy=0.915156
2016-05-03 04:01:26,820 Node[0] Epoch[30] Batch [100] Speed: 611.77 samples/sec Train-accuracy=0.916406
2016-05-03 04:01:37,218 Node[0] Epoch[30] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.922344
2016-05-03 04:01:47,623 Node[0] Epoch[30] Batch [200] Speed: 615.10 samples/sec Train-accuracy=0.921875
2016-05-03 04:01:58,059 Node[0] Epoch[30] Batch [250] Speed: 613.25 samples/sec Train-accuracy=0.922500
2016-05-03 04:02:08,467 Node[0] Epoch[30] Batch [300] Speed: 614.97 samples/sec Train-accuracy=0.921875
2016-05-03 04:02:18,822 Node[0] Epoch[30] Batch [350] Speed: 618.07 samples/sec Train-accuracy=0.908281
2016-05-03 04:02:27,354 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 04:02:27,354 Node[0] Epoch[30] Time cost=81.525
2016-05-03 04:02:27,518 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 04:02:29,453 Node[0] Epoch[30] Validation-accuracy=0.851863
2016-05-03 04:02:39,949 Node[0] Epoch[31] Batch [50] Speed: 612.96 samples/sec Train-accuracy=0.918594
2016-05-03 04:02:50,377 Node[0] Epoch[31] Batch [100] Speed: 613.77 samples/sec Train-accuracy=0.917500
2016-05-03 04:03:00,744 Node[0] Epoch[31] Batch [150] Speed: 617.37 samples/sec Train-accuracy=0.916562
2016-05-03 04:03:11,117 Node[0] Epoch[31] Batch [200] Speed: 616.96 samples/sec Train-accuracy=0.919531
2016-05-03 04:03:21,512 Node[0] Epoch[31] Batch [250] Speed: 615.74 samples/sec Train-accuracy=0.917031
2016-05-03 04:03:31,975 Node[0] Epoch[31] Batch [300] Speed: 611.65 samples/sec Train-accuracy=0.931406
2016-05-03 04:03:42,397 Node[0] Epoch[31] Batch [350] Speed: 614.14 samples/sec Train-accuracy=0.911094
2016-05-03 04:03:50,717 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 04:03:50,718 Node[0] Epoch[31] Time cost=81.264
2016-05-03 04:03:50,885 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 04:03:52,797 Node[0] Epoch[31] Validation-accuracy=0.868890
2016-05-03 04:04:03,273 Node[0] Epoch[32] Batch [50] Speed: 614.23 samples/sec Train-accuracy=0.915781
2016-05-03 04:04:13,660 Node[0] Epoch[32] Batch [100] Speed: 616.21 samples/sec Train-accuracy=0.914062
2016-05-03 04:04:24,027 Node[0] Epoch[32] Batch [150] Speed: 617.37 samples/sec Train-accuracy=0.916562
2016-05-03 04:04:34,423 Node[0] Epoch[32] Batch [200] Speed: 615.62 samples/sec Train-accuracy=0.921250
2016-05-03 04:04:44,783 Node[0] Epoch[32] Batch [250] Speed: 617.76 samples/sec Train-accuracy=0.920156
2016-05-03 04:04:55,189 Node[0] Epoch[32] Batch [300] Speed: 615.05 samples/sec Train-accuracy=0.925000
2016-05-03 04:05:05,558 Node[0] Epoch[32] Batch [350] Speed: 617.24 samples/sec Train-accuracy=0.918594
2016-05-03 04:05:14,159 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 04:05:14,159 Node[0] Epoch[32] Time cost=81.362
2016-05-03 04:05:14,325 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 04:05:16,405 Node[0] Epoch[32] Validation-accuracy=0.864616
2016-05-03 04:05:26,838 Node[0] Epoch[33] Batch [50] Speed: 616.59 samples/sec Train-accuracy=0.925625
2016-05-03 04:05:37,244 Node[0] Epoch[33] Batch [100] Speed: 615.08 samples/sec Train-accuracy=0.920781
2016-05-03 04:05:47,647 Node[0] Epoch[33] Batch [150] Speed: 615.23 samples/sec Train-accuracy=0.922969
2016-05-03 04:05:58,087 Node[0] Epoch[33] Batch [200] Speed: 613.05 samples/sec Train-accuracy=0.916250
2016-05-03 04:06:08,508 Node[0] Epoch[33] Batch [250] Speed: 614.12 samples/sec Train-accuracy=0.918906
2016-05-03 04:06:18,902 Node[0] Epoch[33] Batch [300] Speed: 615.80 samples/sec Train-accuracy=0.923594
2016-05-03 04:06:29,290 Node[0] Epoch[33] Batch [350] Speed: 616.08 samples/sec Train-accuracy=0.923438
2016-05-03 04:06:37,782 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 04:06:37,782 Node[0] Epoch[33] Time cost=81.377
2016-05-03 04:06:37,944 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 04:06:39,892 Node[0] Epoch[33] Validation-accuracy=0.872796
2016-05-03 04:06:50,439 Node[0] Epoch[34] Batch [50] Speed: 610.03 samples/sec Train-accuracy=0.927969
2016-05-03 04:07:00,876 Node[0] Epoch[34] Batch [100] Speed: 613.19 samples/sec Train-accuracy=0.925156
2016-05-03 04:07:11,267 Node[0] Epoch[34] Batch [150] Speed: 615.96 samples/sec Train-accuracy=0.927656
2016-05-03 04:07:21,683 Node[0] Epoch[34] Batch [200] Speed: 614.46 samples/sec Train-accuracy=0.923750
2016-05-03 04:07:32,096 Node[0] Epoch[34] Batch [250] Speed: 614.62 samples/sec Train-accuracy=0.924063
2016-05-03 04:07:42,532 Node[0] Epoch[34] Batch [300] Speed: 613.27 samples/sec Train-accuracy=0.929375
2016-05-03 04:07:52,914 Node[0] Epoch[34] Batch [350] Speed: 616.47 samples/sec Train-accuracy=0.919687
2016-05-03 04:08:01,231 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 04:08:01,231 Node[0] Epoch[34] Time cost=81.339
2016-05-03 04:08:01,392 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 04:08:03,319 Node[0] Epoch[34] Validation-accuracy=0.871294
2016-05-03 04:08:13,899 Node[0] Epoch[35] Batch [50] Speed: 608.12 samples/sec Train-accuracy=0.920625
2016-05-03 04:08:24,346 Node[0] Epoch[35] Batch [100] Speed: 612.66 samples/sec Train-accuracy=0.916094
2016-05-03 04:08:34,734 Node[0] Epoch[35] Batch [150] Speed: 616.07 samples/sec Train-accuracy=0.920781
2016-05-03 04:08:45,118 Node[0] Epoch[35] Batch [200] Speed: 616.36 samples/sec Train-accuracy=0.923281
2016-05-03 04:08:55,482 Node[0] Epoch[35] Batch [250] Speed: 617.54 samples/sec Train-accuracy=0.920312
2016-05-03 04:09:05,874 Node[0] Epoch[35] Batch [300] Speed: 615.88 samples/sec Train-accuracy=0.930625
2016-05-03 04:09:16,290 Node[0] Epoch[35] Batch [350] Speed: 614.45 samples/sec Train-accuracy=0.922031
2016-05-03 04:09:24,794 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 04:09:24,794 Node[0] Epoch[35] Time cost=81.475
2016-05-03 04:09:24,956 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 04:09:26,900 Node[0] Epoch[35] Validation-accuracy=0.862780
2016-05-03 04:09:37,466 Node[0] Epoch[36] Batch [50] Speed: 608.84 samples/sec Train-accuracy=0.929531
2016-05-03 04:09:47,833 Node[0] Epoch[36] Batch [100] Speed: 617.34 samples/sec Train-accuracy=0.928594
2016-05-03 04:09:58,235 Node[0] Epoch[36] Batch [150] Speed: 615.29 samples/sec Train-accuracy=0.927656
2016-05-03 04:10:08,644 Node[0] Epoch[36] Batch [200] Speed: 614.86 samples/sec Train-accuracy=0.926094
2016-05-03 04:10:19,016 Node[0] Epoch[36] Batch [250] Speed: 617.06 samples/sec Train-accuracy=0.927188
2016-05-03 04:10:29,378 Node[0] Epoch[36] Batch [300] Speed: 617.71 samples/sec Train-accuracy=0.925625
2016-05-03 04:10:39,844 Node[0] Epoch[36] Batch [350] Speed: 611.53 samples/sec Train-accuracy=0.922500
2016-05-03 04:10:48,437 Node[0] Epoch[36] Resetting Data Iterator
2016-05-03 04:10:48,437 Node[0] Epoch[36] Time cost=81.537
2016-05-03 04:10:48,599 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-03 04:10:50,507 Node[0] Epoch[36] Validation-accuracy=0.867288
2016-05-03 04:11:00,994 Node[0] Epoch[37] Batch [50] Speed: 613.47 samples/sec Train-accuracy=0.928438
2016-05-03 04:11:11,434 Node[0] Epoch[37] Batch [100] Speed: 613.05 samples/sec Train-accuracy=0.927031
2016-05-03 04:11:21,807 Node[0] Epoch[37] Batch [150] Speed: 617.03 samples/sec Train-accuracy=0.922656
2016-05-03 04:11:32,202 Node[0] Epoch[37] Batch [200] Speed: 615.65 samples/sec Train-accuracy=0.931406
2016-05-03 04:11:42,627 Node[0] Epoch[37] Batch [250] Speed: 613.95 samples/sec Train-accuracy=0.928125
2016-05-03 04:11:53,000 Node[0] Epoch[37] Batch [300] Speed: 617.02 samples/sec Train-accuracy=0.930937
2016-05-03 04:12:03,407 Node[0] Epoch[37] Batch [350] Speed: 614.95 samples/sec Train-accuracy=0.924531
2016-05-03 04:12:11,758 Node[0] Epoch[37] Resetting Data Iterator
2016-05-03 04:12:11,758 Node[0] Epoch[37] Time cost=81.251
2016-05-03 04:12:11,926 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-03 04:12:13,840 Node[0] Epoch[37] Validation-accuracy=0.864083
2016-05-03 04:12:24,322 Node[0] Epoch[38] Batch [50] Speed: 613.76 samples/sec Train-accuracy=0.925156
2016-05-03 04:12:34,715 Node[0] Epoch[38] Batch [100] Speed: 615.83 samples/sec Train-accuracy=0.923125
2016-05-03 04:12:45,141 Node[0] Epoch[38] Batch [150] Speed: 613.86 samples/sec Train-accuracy=0.925469
2016-05-03 04:12:55,560 Node[0] Epoch[38] Batch [200] Speed: 614.29 samples/sec Train-accuracy=0.931875
2016-05-03 04:13:05,941 Node[0] Epoch[38] Batch [250] Speed: 616.51 samples/sec Train-accuracy=0.933906
2016-05-03 04:13:16,351 Node[0] Epoch[38] Batch [300] Speed: 614.81 samples/sec Train-accuracy=0.932031
2016-05-03 04:13:26,773 Node[0] Epoch[38] Batch [350] Speed: 614.10 samples/sec Train-accuracy=0.925156
2016-05-03 04:13:35,261 Node[0] Epoch[38] Resetting Data Iterator
2016-05-03 04:13:35,261 Node[0] Epoch[38] Time cost=81.421
2016-05-03 04:13:35,426 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-03 04:13:37,366 Node[0] Epoch[38] Validation-accuracy=0.869491
2016-05-03 04:13:47,925 Node[0] Epoch[39] Batch [50] Speed: 609.32 samples/sec Train-accuracy=0.928906
2016-05-03 04:13:58,314 Node[0] Epoch[39] Batch [100] Speed: 616.07 samples/sec Train-accuracy=0.932500
2016-05-03 04:14:08,714 Node[0] Epoch[39] Batch [150] Speed: 615.36 samples/sec Train-accuracy=0.931875
2016-05-03 04:14:19,106 Node[0] Epoch[39] Batch [200] Speed: 615.87 samples/sec Train-accuracy=0.931719
2016-05-03 04:14:29,528 Node[0] Epoch[39] Batch [250] Speed: 614.10 samples/sec Train-accuracy=0.920781
2016-05-03 04:14:39,969 Node[0] Epoch[39] Batch [300] Speed: 612.99 samples/sec Train-accuracy=0.933125
2016-05-03 04:14:50,370 Node[0] Epoch[39] Batch [350] Speed: 615.35 samples/sec Train-accuracy=0.931250
2016-05-03 04:14:58,752 Node[0] Epoch[39] Resetting Data Iterator
2016-05-03 04:14:58,753 Node[0] Epoch[39] Time cost=81.386
2016-05-03 04:14:58,918 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-03 04:15:00,818 Node[0] Epoch[39] Validation-accuracy=0.857472
2016-05-03 04:15:11,280 Node[0] Epoch[40] Batch [50] Speed: 615.06 samples/sec Train-accuracy=0.930469
2016-05-03 04:15:21,665 Node[0] Epoch[40] Batch [100] Speed: 616.28 samples/sec Train-accuracy=0.931562
2016-05-03 04:15:32,113 Node[0] Epoch[40] Batch [150] Speed: 612.59 samples/sec Train-accuracy=0.933750
2016-05-03 04:15:42,514 Node[0] Epoch[40] Batch [200] Speed: 615.31 samples/sec Train-accuracy=0.935937
2016-05-03 04:15:52,901 Node[0] Epoch[40] Batch [250] Speed: 616.20 samples/sec Train-accuracy=0.930156
2016-05-03 04:16:03,354 Node[0] Epoch[40] Batch [300] Speed: 612.24 samples/sec Train-accuracy=0.931094
2016-05-03 04:16:13,874 Node[0] Epoch[40] Batch [350] Speed: 608.42 samples/sec Train-accuracy=0.928281
2016-05-03 04:16:22,465 Node[0] Epoch[40] Resetting Data Iterator
2016-05-03 04:16:22,465 Node[0] Epoch[40] Time cost=81.647
2016-05-03 04:16:22,636 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-03 04:16:24,689 Node[0] Epoch[40] Validation-accuracy=0.870352
2016-05-03 04:16:35,097 Node[0] Epoch[41] Batch [50] Speed: 618.15 samples/sec Train-accuracy=0.933906
2016-05-03 04:16:45,489 Node[0] Epoch[41] Batch [100] Speed: 615.86 samples/sec Train-accuracy=0.932656
2016-05-03 04:16:55,886 Node[0] Epoch[41] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.937500
2016-05-03 04:17:06,341 Node[0] Epoch[41] Batch [200] Speed: 612.16 samples/sec Train-accuracy=0.935937
2016-05-03 04:17:16,837 Node[0] Epoch[41] Batch [250] Speed: 609.80 samples/sec Train-accuracy=0.933438
2016-05-03 04:17:27,315 Node[0] Epoch[41] Batch [300] Speed: 610.84 samples/sec Train-accuracy=0.931094
2016-05-03 04:17:37,790 Node[0] Epoch[41] Batch [350] Speed: 611.00 samples/sec Train-accuracy=0.930312
2016-05-03 04:17:46,303 Node[0] Epoch[41] Resetting Data Iterator
2016-05-03 04:17:46,304 Node[0] Epoch[41] Time cost=81.615
2016-05-03 04:17:46,469 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-03 04:17:48,356 Node[0] Epoch[41] Validation-accuracy=0.875300
2016-05-03 04:17:58,859 Node[0] Epoch[42] Batch [50] Speed: 612.54 samples/sec Train-accuracy=0.934688
2016-05-03 04:18:09,320 Node[0] Epoch[42] Batch [100] Speed: 611.82 samples/sec Train-accuracy=0.929688
2016-05-03 04:18:19,673 Node[0] Epoch[42] Batch [150] Speed: 618.20 samples/sec Train-accuracy=0.933906
2016-05-03 04:18:30,059 Node[0] Epoch[42] Batch [200] Speed: 616.20 samples/sec Train-accuracy=0.931875
2016-05-03 04:18:40,499 Node[0] Epoch[42] Batch [250] Speed: 613.07 samples/sec Train-accuracy=0.932656
2016-05-03 04:18:50,997 Node[0] Epoch[42] Batch [300] Speed: 609.66 samples/sec Train-accuracy=0.935312
2016-05-03 04:19:01,522 Node[0] Epoch[42] Batch [350] Speed: 608.08 samples/sec Train-accuracy=0.928125
2016-05-03 04:19:09,894 Node[0] Epoch[42] Resetting Data Iterator
2016-05-03 04:19:09,895 Node[0] Epoch[42] Time cost=81.539
2016-05-03 04:19:10,060 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-03 04:19:11,963 Node[0] Epoch[42] Validation-accuracy=0.870092
2016-05-03 04:19:22,408 Node[0] Epoch[43] Batch [50] Speed: 615.89 samples/sec Train-accuracy=0.930781
2016-05-03 04:19:32,875 Node[0] Epoch[43] Batch [100] Speed: 611.46 samples/sec Train-accuracy=0.932969
2016-05-03 04:19:43,283 Node[0] Epoch[43] Batch [150] Speed: 614.91 samples/sec Train-accuracy=0.937344
2016-05-03 04:19:53,671 Node[0] Epoch[43] Batch [200] Speed: 616.11 samples/sec Train-accuracy=0.931094
2016-05-03 04:20:04,081 Node[0] Epoch[43] Batch [250] Speed: 614.80 samples/sec Train-accuracy=0.938281
2016-05-03 04:20:14,540 Node[0] Epoch[43] Batch [300] Speed: 611.90 samples/sec Train-accuracy=0.937344
2016-05-03 04:20:25,000 Node[0] Epoch[43] Batch [350] Speed: 611.90 samples/sec Train-accuracy=0.938438
2016-05-03 04:20:33,620 Node[0] Epoch[43] Resetting Data Iterator
2016-05-03 04:20:33,620 Node[0] Epoch[43] Time cost=81.657
2016-05-03 04:20:33,786 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-03 04:20:35,713 Node[0] Epoch[43] Validation-accuracy=0.878105
2016-05-03 04:20:46,182 Node[0] Epoch[44] Batch [50] Speed: 614.52 samples/sec Train-accuracy=0.937031
2016-05-03 04:20:56,691 Node[0] Epoch[44] Batch [100] Speed: 609.01 samples/sec Train-accuracy=0.936250
2016-05-03 04:21:07,187 Node[0] Epoch[44] Batch [150] Speed: 609.77 samples/sec Train-accuracy=0.936562
2016-05-03 04:21:17,559 Node[0] Epoch[44] Batch [200] Speed: 617.06 samples/sec Train-accuracy=0.933281
2016-05-03 04:21:27,944 Node[0] Epoch[44] Batch [250] Speed: 616.28 samples/sec Train-accuracy=0.929531
2016-05-03 04:21:38,330 Node[0] Epoch[44] Batch [300] Speed: 616.26 samples/sec Train-accuracy=0.931562
2016-05-03 04:21:48,819 Node[0] Epoch[44] Batch [350] Speed: 610.20 samples/sec Train-accuracy=0.932187
2016-05-03 04:21:57,411 Node[0] Epoch[44] Resetting Data Iterator
2016-05-03 04:21:57,411 Node[0] Epoch[44] Time cost=81.698
2016-05-03 04:21:57,579 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-03 04:21:59,498 Node[0] Epoch[44] Validation-accuracy=0.860377
2016-05-03 04:22:10,038 Node[0] Epoch[45] Batch [50] Speed: 610.39 samples/sec Train-accuracy=0.940469
2016-05-03 04:22:20,447 Node[0] Epoch[45] Batch [100] Speed: 614.90 samples/sec Train-accuracy=0.934531
2016-05-03 04:22:30,882 Node[0] Epoch[45] Batch [150] Speed: 613.32 samples/sec Train-accuracy=0.936562
2016-05-03 04:22:41,274 Node[0] Epoch[45] Batch [200] Speed: 615.91 samples/sec Train-accuracy=0.932344
2016-05-03 04:22:51,680 Node[0] Epoch[45] Batch [250] Speed: 615.04 samples/sec Train-accuracy=0.933281
2016-05-03 04:23:02,100 Node[0] Epoch[45] Batch [300] Speed: 614.20 samples/sec Train-accuracy=0.938125
2016-05-03 04:23:12,593 Node[0] Epoch[45] Batch [350] Speed: 609.97 samples/sec Train-accuracy=0.930937
2016-05-03 04:23:20,945 Node[0] Epoch[45] Resetting Data Iterator
2016-05-03 04:23:20,945 Node[0] Epoch[45] Time cost=81.446
2016-05-03 04:23:21,108 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-03 04:23:23,033 Node[0] Epoch[45] Validation-accuracy=0.868890
2016-05-03 04:23:33,586 Node[0] Epoch[46] Batch [50] Speed: 609.68 samples/sec Train-accuracy=0.931562
2016-05-03 04:23:43,994 Node[0] Epoch[46] Batch [100] Speed: 614.94 samples/sec Train-accuracy=0.933125
2016-05-03 04:23:54,377 Node[0] Epoch[46] Batch [150] Speed: 616.44 samples/sec Train-accuracy=0.937344
2016-05-03 04:24:04,823 Node[0] Epoch[46] Batch [200] Speed: 612.66 samples/sec Train-accuracy=0.938594
2016-05-03 04:24:15,238 Node[0] Epoch[46] Batch [250] Speed: 614.52 samples/sec Train-accuracy=0.939219
2016-05-03 04:24:25,738 Node[0] Epoch[46] Batch [300] Speed: 609.55 samples/sec Train-accuracy=0.942187
2016-05-03 04:24:36,201 Node[0] Epoch[46] Batch [350] Speed: 611.68 samples/sec Train-accuracy=0.941875
2016-05-03 04:24:44,757 Node[0] Epoch[46] Resetting Data Iterator
2016-05-03 04:24:44,757 Node[0] Epoch[46] Time cost=81.724
2016-05-03 04:24:44,924 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-03 04:24:46,800 Node[0] Epoch[46] Validation-accuracy=0.867388
2016-05-03 04:24:57,241 Node[0] Epoch[47] Batch [50] Speed: 616.17 samples/sec Train-accuracy=0.935625
2016-05-03 04:25:07,754 Node[0] Epoch[47] Batch [100] Speed: 608.80 samples/sec Train-accuracy=0.936719
2016-05-03 04:25:18,165 Node[0] Epoch[47] Batch [150] Speed: 614.73 samples/sec Train-accuracy=0.935625
2016-05-03 04:25:28,538 Node[0] Epoch[47] Batch [200] Speed: 617.01 samples/sec Train-accuracy=0.940156
2016-05-03 04:25:38,942 Node[0] Epoch[47] Batch [250] Speed: 615.19 samples/sec Train-accuracy=0.940156
2016-05-03 04:25:49,342 Node[0] Epoch[47] Batch [300] Speed: 615.38 samples/sec Train-accuracy=0.937656
2016-05-03 04:25:59,823 Node[0] Epoch[47] Batch [350] Speed: 610.63 samples/sec Train-accuracy=0.937813
2016-05-03 04:26:08,218 Node[0] Epoch[47] Resetting Data Iterator
2016-05-03 04:26:08,219 Node[0] Epoch[47] Time cost=81.419
2016-05-03 04:26:08,381 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-03 04:26:10,295 Node[0] Epoch[47] Validation-accuracy=0.858674
2016-05-03 04:26:20,757 Node[0] Epoch[48] Batch [50] Speed: 614.94 samples/sec Train-accuracy=0.936094
2016-05-03 04:26:31,252 Node[0] Epoch[48] Batch [100] Speed: 609.81 samples/sec Train-accuracy=0.942344
2016-05-03 04:26:41,654 Node[0] Epoch[48] Batch [150] Speed: 615.26 samples/sec Train-accuracy=0.933906
2016-05-03 04:26:52,072 Node[0] Epoch[48] Batch [200] Speed: 614.34 samples/sec Train-accuracy=0.939219
2016-05-03 04:27:02,543 Node[0] Epoch[48] Batch [250] Speed: 611.21 samples/sec Train-accuracy=0.930312
2016-05-03 04:27:13,009 Node[0] Epoch[48] Batch [300] Speed: 611.55 samples/sec Train-accuracy=0.942344
2016-05-03 04:27:23,528 Node[0] Epoch[48] Batch [350] Speed: 608.45 samples/sec Train-accuracy=0.935469
2016-05-03 04:27:32,087 Node[0] Epoch[48] Resetting Data Iterator
2016-05-03 04:27:32,087 Node[0] Epoch[48] Time cost=81.792
2016-05-03 04:27:32,249 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-03 04:27:34,360 Node[0] Epoch[48] Validation-accuracy=0.876582
2016-05-03 04:27:44,834 Node[0] Epoch[49] Batch [50] Speed: 614.19 samples/sec Train-accuracy=0.939688
2016-05-03 04:27:55,225 Node[0] Epoch[49] Batch [100] Speed: 615.93 samples/sec Train-accuracy=0.947344
2016-05-03 04:28:05,591 Node[0] Epoch[49] Batch [150] Speed: 617.45 samples/sec Train-accuracy=0.943281
2016-05-03 04:28:16,013 Node[0] Epoch[49] Batch [200] Speed: 614.06 samples/sec Train-accuracy=0.935781
2016-05-03 04:28:26,454 Node[0] Epoch[49] Batch [250] Speed: 613.00 samples/sec Train-accuracy=0.937500
2016-05-03 04:28:36,948 Node[0] Epoch[49] Batch [300] Speed: 609.86 samples/sec Train-accuracy=0.935312
2016-05-03 04:28:47,415 Node[0] Epoch[49] Batch [350] Speed: 611.44 samples/sec Train-accuracy=0.941562
2016-05-03 04:28:56,026 Node[0] Epoch[49] Resetting Data Iterator
2016-05-03 04:28:56,027 Node[0] Epoch[49] Time cost=81.667
2016-05-03 04:28:56,191 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-03 04:28:58,102 Node[0] Epoch[49] Validation-accuracy=0.857973
2016-05-03 04:29:08,592 Node[0] Epoch[50] Batch [50] Speed: 613.31 samples/sec Train-accuracy=0.939063
2016-05-03 04:29:19,057 Node[0] Epoch[50] Batch [100] Speed: 611.56 samples/sec Train-accuracy=0.941719
2016-05-03 04:29:29,502 Node[0] Epoch[50] Batch [150] Speed: 612.78 samples/sec Train-accuracy=0.937813
2016-05-03 04:29:39,905 Node[0] Epoch[50] Batch [200] Speed: 615.22 samples/sec Train-accuracy=0.937187
2016-05-03 04:29:50,322 Node[0] Epoch[50] Batch [250] Speed: 614.37 samples/sec Train-accuracy=0.943906
2016-05-03 04:30:00,780 Node[0] Epoch[50] Batch [300] Speed: 612.00 samples/sec Train-accuracy=0.942187
2016-05-03 04:30:11,269 Node[0] Epoch[50] Batch [350] Speed: 610.19 samples/sec Train-accuracy=0.940469
2016-05-03 04:30:19,649 Node[0] Epoch[50] Resetting Data Iterator
2016-05-03 04:30:19,649 Node[0] Epoch[50] Time cost=81.546
2016-05-03 04:30:19,810 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-03 04:30:21,730 Node[0] Epoch[50] Validation-accuracy=0.870693
2016-05-03 04:30:32,193 Node[0] Epoch[51] Batch [50] Speed: 614.92 samples/sec Train-accuracy=0.933750
2016-05-03 04:30:42,659 Node[0] Epoch[51] Batch [100] Speed: 611.53 samples/sec Train-accuracy=0.940937
2016-05-03 04:30:53,082 Node[0] Epoch[51] Batch [150] Speed: 614.04 samples/sec Train-accuracy=0.940469
2016-05-03 04:31:03,462 Node[0] Epoch[51] Batch [200] Speed: 616.56 samples/sec Train-accuracy=0.937187
2016-05-03 04:31:13,907 Node[0] Epoch[51] Batch [250] Speed: 612.79 samples/sec Train-accuracy=0.938438
2016-05-03 04:31:24,407 Node[0] Epoch[51] Batch [300] Speed: 609.54 samples/sec Train-accuracy=0.941406
2016-05-03 04:31:34,882 Node[0] Epoch[51] Batch [350] Speed: 610.96 samples/sec Train-accuracy=0.946719
2016-05-03 04:31:43,473 Node[0] Epoch[51] Resetting Data Iterator
2016-05-03 04:31:43,473 Node[0] Epoch[51] Time cost=81.743
2016-05-03 04:31:43,640 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-03 04:31:45,540 Node[0] Epoch[51] Validation-accuracy=0.881611
2016-05-03 04:31:55,997 Node[0] Epoch[52] Batch [50] Speed: 615.19 samples/sec Train-accuracy=0.943594
2016-05-03 04:32:06,542 Node[0] Epoch[52] Batch [100] Speed: 606.97 samples/sec Train-accuracy=0.941562
2016-05-03 04:32:17,087 Node[0] Epoch[52] Batch [150] Speed: 606.91 samples/sec Train-accuracy=0.938438
2016-05-03 04:32:27,543 Node[0] Epoch[52] Batch [200] Speed: 612.11 samples/sec Train-accuracy=0.937500
2016-05-03 04:32:37,917 Node[0] Epoch[52] Batch [250] Speed: 616.96 samples/sec Train-accuracy=0.939375
2016-05-03 04:32:48,332 Node[0] Epoch[52] Batch [300] Speed: 614.54 samples/sec Train-accuracy=0.939844
2016-05-03 04:32:58,739 Node[0] Epoch[52] Batch [350] Speed: 614.96 samples/sec Train-accuracy=0.937656
2016-05-03 04:33:07,348 Node[0] Epoch[52] Resetting Data Iterator
2016-05-03 04:33:07,348 Node[0] Epoch[52] Time cost=81.808
2016-05-03 04:33:07,514 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-03 04:33:09,464 Node[0] Epoch[52] Validation-accuracy=0.882011
2016-05-03 04:33:19,983 Node[0] Epoch[53] Batch [50] Speed: 611.61 samples/sec Train-accuracy=0.945156
2016-05-03 04:33:30,498 Node[0] Epoch[53] Batch [100] Speed: 608.68 samples/sec Train-accuracy=0.935312
2016-05-03 04:33:40,974 Node[0] Epoch[53] Batch [150] Speed: 610.97 samples/sec Train-accuracy=0.939219
2016-05-03 04:33:51,458 Node[0] Epoch[53] Batch [200] Speed: 610.47 samples/sec Train-accuracy=0.945469
2016-05-03 04:34:01,975 Node[0] Epoch[53] Batch [250] Speed: 608.54 samples/sec Train-accuracy=0.939063
2016-05-03 04:34:12,414 Node[0] Epoch[53] Batch [300] Speed: 613.13 samples/sec Train-accuracy=0.941562
2016-05-03 04:34:22,824 Node[0] Epoch[53] Batch [350] Speed: 614.81 samples/sec Train-accuracy=0.939063
2016-05-03 04:34:31,161 Node[0] Epoch[53] Resetting Data Iterator
2016-05-03 04:34:31,162 Node[0] Epoch[53] Time cost=81.698
2016-05-03 04:34:31,326 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-03 04:34:33,221 Node[0] Epoch[53] Validation-accuracy=0.874199
2016-05-03 04:34:43,768 Node[0] Epoch[54] Batch [50] Speed: 609.99 samples/sec Train-accuracy=0.942500
2016-05-03 04:34:54,247 Node[0] Epoch[54] Batch [100] Speed: 610.79 samples/sec Train-accuracy=0.942344
2016-05-03 04:35:04,717 Node[0] Epoch[54] Batch [150] Speed: 611.27 samples/sec Train-accuracy=0.938438
2016-05-03 04:35:15,095 Node[0] Epoch[54] Batch [200] Speed: 616.70 samples/sec Train-accuracy=0.937187
2016-05-03 04:35:25,491 Node[0] Epoch[54] Batch [250] Speed: 615.65 samples/sec Train-accuracy=0.938438
2016-05-03 04:35:35,897 Node[0] Epoch[54] Batch [300] Speed: 615.08 samples/sec Train-accuracy=0.943906
2016-05-03 04:35:46,369 Node[0] Epoch[54] Batch [350] Speed: 611.15 samples/sec Train-accuracy=0.939219
2016-05-03 04:35:54,941 Node[0] Epoch[54] Resetting Data Iterator
2016-05-03 04:35:54,941 Node[0] Epoch[54] Time cost=81.719
2016-05-03 04:35:55,101 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-03 04:35:57,040 Node[0] Epoch[54] Validation-accuracy=0.876502
2016-05-03 04:36:07,541 Node[0] Epoch[55] Batch [50] Speed: 612.72 samples/sec Train-accuracy=0.942500
2016-05-03 04:36:18,057 Node[0] Epoch[55] Batch [100] Speed: 608.62 samples/sec Train-accuracy=0.943125
2016-05-03 04:36:28,465 Node[0] Epoch[55] Batch [150] Speed: 614.90 samples/sec Train-accuracy=0.945469
2016-05-03 04:36:38,903 Node[0] Epoch[55] Batch [200] Speed: 613.15 samples/sec Train-accuracy=0.939375
2016-05-03 04:36:49,417 Node[0] Epoch[55] Batch [250] Speed: 608.75 samples/sec Train-accuracy=0.940625
2016-05-03 04:36:59,899 Node[0] Epoch[55] Batch [300] Speed: 610.60 samples/sec Train-accuracy=0.942656
2016-05-03 04:37:10,431 Node[0] Epoch[55] Batch [350] Speed: 607.68 samples/sec Train-accuracy=0.942344
2016-05-03 04:37:18,807 Node[0] Epoch[55] Resetting Data Iterator
2016-05-03 04:37:18,807 Node[0] Epoch[55] Time cost=81.766
2016-05-03 04:37:18,969 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-03 04:37:20,848 Node[0] Epoch[55] Validation-accuracy=0.877204
2016-05-03 04:37:31,309 Node[0] Epoch[56] Batch [50] Speed: 615.09 samples/sec Train-accuracy=0.941094
2016-05-03 04:37:41,825 Node[0] Epoch[56] Batch [100] Speed: 608.58 samples/sec Train-accuracy=0.943125
2016-05-03 04:37:52,281 Node[0] Epoch[56] Batch [150] Speed: 612.13 samples/sec Train-accuracy=0.939688
2016-05-03 04:38:02,705 Node[0] Epoch[56] Batch [200] Speed: 613.96 samples/sec Train-accuracy=0.938438
2016-05-03 04:38:13,141 Node[0] Epoch[56] Batch [250] Speed: 613.29 samples/sec Train-accuracy=0.945781
2016-05-03 04:38:23,615 Node[0] Epoch[56] Batch [300] Speed: 611.07 samples/sec Train-accuracy=0.944375
2016-05-03 04:38:34,096 Node[0] Epoch[56] Batch [350] Speed: 610.64 samples/sec Train-accuracy=0.941406
2016-05-03 04:38:42,646 Node[0] Epoch[56] Resetting Data Iterator
2016-05-03 04:38:42,647 Node[0] Epoch[56] Time cost=81.799
2016-05-03 04:38:42,809 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-03 04:38:44,946 Node[0] Epoch[56] Validation-accuracy=0.880736
2016-05-03 04:38:55,496 Node[0] Epoch[57] Batch [50] Speed: 609.82 samples/sec Train-accuracy=0.938750
2016-05-03 04:39:05,890 Node[0] Epoch[57] Batch [100] Speed: 615.74 samples/sec Train-accuracy=0.942656
2016-05-03 04:39:16,270 Node[0] Epoch[57] Batch [150] Speed: 616.59 samples/sec Train-accuracy=0.946875
2016-05-03 04:39:26,737 Node[0] Epoch[57] Batch [200] Speed: 611.51 samples/sec Train-accuracy=0.942500
2016-05-03 04:39:37,214 Node[0] Epoch[57] Batch [250] Speed: 610.84 samples/sec Train-accuracy=0.939063
2016-05-03 04:39:47,704 Node[0] Epoch[57] Batch [300] Speed: 610.14 samples/sec Train-accuracy=0.941875
2016-05-03 04:39:58,206 Node[0] Epoch[57] Batch [350] Speed: 609.44 samples/sec Train-accuracy=0.945781
2016-05-03 04:40:06,794 Node[0] Epoch[57] Resetting Data Iterator
2016-05-03 04:40:06,794 Node[0] Epoch[57] Time cost=81.849
2016-05-03 04:40:06,957 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-03 04:40:08,864 Node[0] Epoch[57] Validation-accuracy=0.870593
2016-05-03 04:40:19,389 Node[0] Epoch[58] Batch [50] Speed: 611.31 samples/sec Train-accuracy=0.945000
2016-05-03 04:40:29,820 Node[0] Epoch[58] Batch [100] Speed: 613.54 samples/sec Train-accuracy=0.944375
2016-05-03 04:40:40,258 Node[0] Epoch[58] Batch [150] Speed: 613.16 samples/sec Train-accuracy=0.941094
2016-05-03 04:40:50,664 Node[0] Epoch[58] Batch [200] Speed: 615.05 samples/sec Train-accuracy=0.942656
2016-05-03 04:41:01,162 Node[0] Epoch[58] Batch [250] Speed: 609.70 samples/sec Train-accuracy=0.947500
2016-05-03 04:41:11,659 Node[0] Epoch[58] Batch [300] Speed: 609.67 samples/sec Train-accuracy=0.943281
2016-05-03 04:41:22,119 Node[0] Epoch[58] Batch [350] Speed: 611.88 samples/sec Train-accuracy=0.941250
2016-05-03 04:41:30,501 Node[0] Epoch[58] Resetting Data Iterator
2016-05-03 04:41:30,501 Node[0] Epoch[58] Time cost=81.637
2016-05-03 04:41:30,669 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-03 04:41:32,595 Node[0] Epoch[58] Validation-accuracy=0.870693
2016-05-03 04:41:43,070 Node[0] Epoch[59] Batch [50] Speed: 614.14 samples/sec Train-accuracy=0.941406
2016-05-03 04:41:53,483 Node[0] Epoch[59] Batch [100] Speed: 614.65 samples/sec Train-accuracy=0.946094
2016-05-03 04:42:03,911 Node[0] Epoch[59] Batch [150] Speed: 613.71 samples/sec Train-accuracy=0.945312
2016-05-03 04:42:14,335 Node[0] Epoch[59] Batch [200] Speed: 613.99 samples/sec Train-accuracy=0.946719
2016-05-03 04:42:24,854 Node[0] Epoch[59] Batch [250] Speed: 608.47 samples/sec Train-accuracy=0.937031
2016-05-03 04:42:35,341 Node[0] Epoch[59] Batch [300] Speed: 610.30 samples/sec Train-accuracy=0.942656
2016-05-03 04:42:45,783 Node[0] Epoch[59] Batch [350] Speed: 612.92 samples/sec Train-accuracy=0.945000
2016-05-03 04:42:54,359 Node[0] Epoch[59] Resetting Data Iterator
2016-05-03 04:42:54,359 Node[0] Epoch[59] Time cost=81.764
2016-05-03 04:42:54,526 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-03 04:42:56,437 Node[0] Epoch[59] Validation-accuracy=0.872796
2016-05-03 04:43:06,922 Node[0] Epoch[60] Batch [50] Speed: 613.62 samples/sec Train-accuracy=0.945937
2016-05-03 04:43:17,358 Node[0] Epoch[60] Batch [100] Speed: 613.29 samples/sec Train-accuracy=0.942656
2016-05-03 04:43:27,714 Node[0] Epoch[60] Batch [150] Speed: 617.99 samples/sec Train-accuracy=0.943281
2016-05-03 04:43:38,136 Node[0] Epoch[60] Batch [200] Speed: 614.13 samples/sec Train-accuracy=0.941562
2016-05-03 04:43:48,600 Node[0] Epoch[60] Batch [250] Speed: 611.62 samples/sec Train-accuracy=0.945312
2016-05-03 04:43:59,080 Node[0] Epoch[60] Batch [300] Speed: 610.69 samples/sec Train-accuracy=0.947500
2016-05-03 04:44:09,567 Node[0] Epoch[60] Batch [350] Speed: 610.31 samples/sec Train-accuracy=0.939375
2016-05-03 04:44:18,130 Node[0] Epoch[60] Resetting Data Iterator
2016-05-03 04:44:18,130 Node[0] Epoch[60] Time cost=81.693
2016-05-03 04:44:18,291 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-03 04:44:20,187 Node[0] Epoch[60] Validation-accuracy=0.878405
2016-05-03 04:44:30,651 Node[0] Epoch[61] Batch [50] Speed: 614.81 samples/sec Train-accuracy=0.946562
2016-05-03 04:44:41,094 Node[0] Epoch[61] Batch [100] Speed: 612.86 samples/sec Train-accuracy=0.940469
2016-05-03 04:44:51,508 Node[0] Epoch[61] Batch [150] Speed: 614.60 samples/sec Train-accuracy=0.945156
2016-05-03 04:45:01,947 Node[0] Epoch[61] Batch [200] Speed: 613.07 samples/sec Train-accuracy=0.946094
2016-05-03 04:45:12,403 Node[0] Epoch[61] Batch [250] Speed: 612.13 samples/sec Train-accuracy=0.942344
2016-05-03 04:45:22,865 Node[0] Epoch[61] Batch [300] Speed: 611.76 samples/sec Train-accuracy=0.947031
2016-05-03 04:45:33,336 Node[0] Epoch[61] Batch [350] Speed: 611.19 samples/sec Train-accuracy=0.947500
2016-05-03 04:45:41,699 Node[0] Epoch[61] Resetting Data Iterator
2016-05-03 04:45:41,699 Node[0] Epoch[61] Time cost=81.512
2016-05-03 04:45:41,864 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-03 04:45:43,791 Node[0] Epoch[61] Validation-accuracy=0.872296
2016-05-03 04:45:54,277 Node[0] Epoch[62] Batch [50] Speed: 613.46 samples/sec Train-accuracy=0.946719
2016-05-03 04:46:04,698 Node[0] Epoch[62] Batch [100] Speed: 614.16 samples/sec Train-accuracy=0.942656
2016-05-03 04:46:15,103 Node[0] Epoch[62] Batch [150] Speed: 615.15 samples/sec Train-accuracy=0.946250
2016-05-03 04:46:25,542 Node[0] Epoch[62] Batch [200] Speed: 613.07 samples/sec Train-accuracy=0.944688
2016-05-03 04:46:36,047 Node[0] Epoch[62] Batch [250] Speed: 609.25 samples/sec Train-accuracy=0.942656
2016-05-03 04:46:46,568 Node[0] Epoch[62] Batch [300] Speed: 608.34 samples/sec Train-accuracy=0.945625
2016-05-03 04:46:57,030 Node[0] Epoch[62] Batch [350] Speed: 611.76 samples/sec Train-accuracy=0.948750
2016-05-03 04:47:05,590 Node[0] Epoch[62] Resetting Data Iterator
2016-05-03 04:47:05,590 Node[0] Epoch[62] Time cost=81.799
2016-05-03 04:47:05,752 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-03 04:47:07,653 Node[0] Epoch[62] Validation-accuracy=0.869692
2016-05-03 04:47:18,120 Node[0] Epoch[63] Batch [50] Speed: 614.76 samples/sec Train-accuracy=0.936875
2016-05-03 04:47:28,500 Node[0] Epoch[63] Batch [100] Speed: 616.53 samples/sec Train-accuracy=0.943594
2016-05-03 04:47:38,911 Node[0] Epoch[63] Batch [150] Speed: 614.78 samples/sec Train-accuracy=0.947656
2016-05-03 04:47:49,381 Node[0] Epoch[63] Batch [200] Speed: 611.26 samples/sec Train-accuracy=0.945469
2016-05-03 04:47:59,859 Node[0] Epoch[63] Batch [250] Speed: 610.84 samples/sec Train-accuracy=0.945781
2016-05-03 04:48:10,303 Node[0] Epoch[63] Batch [300] Speed: 612.84 samples/sec Train-accuracy=0.952500
2016-05-03 04:48:20,750 Node[0] Epoch[63] Batch [350] Speed: 612.58 samples/sec Train-accuracy=0.951094
2016-05-03 04:48:29,152 Node[0] Epoch[63] Resetting Data Iterator
2016-05-03 04:48:29,153 Node[0] Epoch[63] Time cost=81.500
2016-05-03 04:48:29,318 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-03 04:48:31,216 Node[0] Epoch[63] Validation-accuracy=0.878005
2016-05-03 04:48:41,712 Node[0] Epoch[64] Batch [50] Speed: 612.98 samples/sec Train-accuracy=0.941875
2016-05-03 04:48:52,180 Node[0] Epoch[64] Batch [100] Speed: 611.40 samples/sec Train-accuracy=0.949688
2016-05-03 04:49:02,602 Node[0] Epoch[64] Batch [150] Speed: 614.12 samples/sec Train-accuracy=0.947656
2016-05-03 04:49:13,008 Node[0] Epoch[64] Batch [200] Speed: 615.05 samples/sec Train-accuracy=0.947500
2016-05-03 04:49:23,433 Node[0] Epoch[64] Batch [250] Speed: 613.93 samples/sec Train-accuracy=0.948750
2016-05-03 04:49:33,848 Node[0] Epoch[64] Batch [300] Speed: 614.50 samples/sec Train-accuracy=0.946094
2016-05-03 04:49:44,345 Node[0] Epoch[64] Batch [350] Speed: 609.70 samples/sec Train-accuracy=0.943438
2016-05-03 04:49:52,920 Node[0] Epoch[64] Resetting Data Iterator
2016-05-03 04:49:52,921 Node[0] Epoch[64] Time cost=81.704
2016-05-03 04:49:53,087 Node[0] Saved checkpoint to "cifar10/resnet-0065.params"
2016-05-03 04:49:55,242 Node[0] Epoch[64] Validation-accuracy=0.891218
2016-05-03 04:50:05,789 Node[0] Epoch[65] Batch [50] Speed: 609.95 samples/sec Train-accuracy=0.946094
2016-05-03 04:50:16,206 Node[0] Epoch[65] Batch [100] Speed: 614.38 samples/sec Train-accuracy=0.948594
2016-05-03 04:50:26,596 Node[0] Epoch[65] Batch [150] Speed: 615.99 samples/sec Train-accuracy=0.945312
2016-05-03 04:50:36,974 Node[0] Epoch[65] Batch [200] Speed: 616.74 samples/sec Train-accuracy=0.948281
2016-05-03 04:50:47,383 Node[0] Epoch[65] Batch [250] Speed: 614.86 samples/sec Train-accuracy=0.948438
2016-05-03 04:50:57,880 Node[0] Epoch[65] Batch [300] Speed: 609.70 samples/sec Train-accuracy=0.948750
2016-05-03 04:51:08,397 Node[0] Epoch[65] Batch [350] Speed: 608.59 samples/sec Train-accuracy=0.947500
2016-05-03 04:51:16,956 Node[0] Epoch[65] Resetting Data Iterator
2016-05-03 04:51:16,956 Node[0] Epoch[65] Time cost=81.714
2016-05-03 04:51:17,121 Node[0] Saved checkpoint to "cifar10/resnet-0066.params"
2016-05-03 04:51:19,044 Node[0] Epoch[65] Validation-accuracy=0.869291
2016-05-03 04:51:29,514 Node[0] Epoch[66] Batch [50] Speed: 614.43 samples/sec Train-accuracy=0.947031
2016-05-03 04:51:39,966 Node[0] Epoch[66] Batch [100] Speed: 612.33 samples/sec Train-accuracy=0.948438
2016-05-03 04:51:50,349 Node[0] Epoch[66] Batch [150] Speed: 616.44 samples/sec Train-accuracy=0.946406
2016-05-03 04:52:00,743 Node[0] Epoch[66] Batch [200] Speed: 615.77 samples/sec Train-accuracy=0.951250
2016-05-03 04:52:11,192 Node[0] Epoch[66] Batch [250] Speed: 612.47 samples/sec Train-accuracy=0.951719
2016-05-03 04:52:21,670 Node[0] Epoch[66] Batch [300] Speed: 610.81 samples/sec Train-accuracy=0.947344
2016-05-03 04:52:32,135 Node[0] Epoch[66] Batch [350] Speed: 611.63 samples/sec Train-accuracy=0.942969
2016-05-03 04:52:40,497 Node[0] Epoch[66] Resetting Data Iterator
2016-05-03 04:52:40,497 Node[0] Epoch[66] Time cost=81.453
2016-05-03 04:52:40,665 Node[0] Saved checkpoint to "cifar10/resnet-0067.params"
2016-05-03 04:52:42,595 Node[0] Epoch[66] Validation-accuracy=0.878305
2016-05-03 04:52:53,116 Node[0] Epoch[67] Batch [50] Speed: 611.51 samples/sec Train-accuracy=0.947344
2016-05-03 04:53:03,544 Node[0] Epoch[67] Batch [100] Speed: 613.72 samples/sec Train-accuracy=0.949688
2016-05-03 04:53:13,899 Node[0] Epoch[67] Batch [150] Speed: 618.11 samples/sec Train-accuracy=0.947969
2016-05-03 04:53:24,345 Node[0] Epoch[67] Batch [200] Speed: 612.68 samples/sec Train-accuracy=0.948906
2016-05-03 04:53:34,796 Node[0] Epoch[67] Batch [250] Speed: 612.36 samples/sec Train-accuracy=0.944375
2016-05-03 04:53:45,287 Node[0] Epoch[67] Batch [300] Speed: 610.11 samples/sec Train-accuracy=0.949375
2016-05-03 04:53:55,740 Node[0] Epoch[67] Batch [350] Speed: 612.27 samples/sec Train-accuracy=0.947187
2016-05-03 04:54:04,336 Node[0] Epoch[67] Resetting Data Iterator
2016-05-03 04:54:04,337 Node[0] Epoch[67] Time cost=81.741
2016-05-03 04:54:04,503 Node[0] Saved checkpoint to "cifar10/resnet-0068.params"
2016-05-03 04:54:06,449 Node[0] Epoch[67] Validation-accuracy=0.879307
2016-05-03 04:54:16,894 Node[0] Epoch[68] Batch [50] Speed: 615.98 samples/sec Train-accuracy=0.946250
2016-05-03 04:54:27,390 Node[0] Epoch[68] Batch [100] Speed: 609.77 samples/sec Train-accuracy=0.944375
2016-05-03 04:54:37,778 Node[0] Epoch[68] Batch [150] Speed: 616.11 samples/sec Train-accuracy=0.946094
2016-05-03 04:54:48,166 Node[0] Epoch[68] Batch [200] Speed: 616.14 samples/sec Train-accuracy=0.947969
2016-05-03 04:54:58,647 Node[0] Epoch[68] Batch [250] Speed: 610.65 samples/sec Train-accuracy=0.947500
2016-05-03 04:55:09,137 Node[0] Epoch[68] Batch [300] Speed: 610.09 samples/sec Train-accuracy=0.947500
2016-05-03 04:55:19,604 Node[0] Epoch[68] Batch [350] Speed: 611.48 samples/sec Train-accuracy=0.944844
2016-05-03 04:55:28,177 Node[0] Epoch[68] Resetting Data Iterator
2016-05-03 04:55:28,177 Node[0] Epoch[68] Time cost=81.727
2016-05-03 04:55:28,343 Node[0] Saved checkpoint to "cifar10/resnet-0069.params"
2016-05-03 04:55:30,262 Node[0] Epoch[68] Validation-accuracy=0.870393
2016-05-03 04:55:40,786 Node[0] Epoch[69] Batch [50] Speed: 611.42 samples/sec Train-accuracy=0.947031
2016-05-03 04:55:51,309 Node[0] Epoch[69] Batch [100] Speed: 608.19 samples/sec Train-accuracy=0.948281
2016-05-03 04:56:01,842 Node[0] Epoch[69] Batch [150] Speed: 607.66 samples/sec Train-accuracy=0.948594
2016-05-03 04:56:12,374 Node[0] Epoch[69] Batch [200] Speed: 607.68 samples/sec Train-accuracy=0.947656
2016-05-03 04:56:22,872 Node[0] Epoch[69] Batch [250] Speed: 609.64 samples/sec Train-accuracy=0.950937
2016-05-03 04:56:33,372 Node[0] Epoch[69] Batch [300] Speed: 609.58 samples/sec Train-accuracy=0.945000
2016-05-03 04:56:43,841 Node[0] Epoch[69] Batch [350] Speed: 611.30 samples/sec Train-accuracy=0.942969
2016-05-03 04:56:52,232 Node[0] Epoch[69] Resetting Data Iterator
2016-05-03 04:56:52,232 Node[0] Epoch[69] Time cost=81.970
2016-05-03 04:56:52,395 Node[0] Saved checkpoint to "cifar10/resnet-0070.params"
2016-05-03 04:56:54,308 Node[0] Epoch[69] Validation-accuracy=0.882412
2016-05-03 04:57:04,782 Node[0] Epoch[70] Batch [50] Speed: 614.23 samples/sec Train-accuracy=0.950000
2016-05-03 04:57:15,296 Node[0] Epoch[70] Batch [100] Speed: 608.72 samples/sec Train-accuracy=0.944844
2016-05-03 04:57:25,801 Node[0] Epoch[70] Batch [150] Speed: 609.29 samples/sec Train-accuracy=0.940312
2016-05-03 04:57:36,353 Node[0] Epoch[70] Batch [200] Speed: 606.50 samples/sec Train-accuracy=0.950000
2016-05-03 04:57:46,766 Node[0] Epoch[70] Batch [250] Speed: 614.62 samples/sec Train-accuracy=0.947344
2016-05-03 04:57:57,215 Node[0] Epoch[70] Batch [300] Speed: 612.52 samples/sec Train-accuracy=0.945625
2016-05-03 04:58:07,681 Node[0] Epoch[70] Batch [350] Speed: 611.54 samples/sec Train-accuracy=0.948281
2016-05-03 04:58:16,254 Node[0] Epoch[70] Resetting Data Iterator
2016-05-03 04:58:16,254 Node[0] Epoch[70] Time cost=81.946
2016-05-03 04:58:16,417 Node[0] Saved checkpoint to "cifar10/resnet-0071.params"
2016-05-03 04:58:18,349 Node[0] Epoch[70] Validation-accuracy=0.879908
2016-05-03 04:58:28,865 Node[0] Epoch[71] Batch [50] Speed: 611.81 samples/sec Train-accuracy=0.949844
2016-05-03 04:58:39,377 Node[0] Epoch[71] Batch [100] Speed: 608.82 samples/sec Train-accuracy=0.949375
2016-05-03 04:58:49,907 Node[0] Epoch[71] Batch [150] Speed: 607.84 samples/sec Train-accuracy=0.949531
2016-05-03 04:59:00,441 Node[0] Epoch[71] Batch [200] Speed: 607.53 samples/sec Train-accuracy=0.949375
2016-05-03 04:59:10,929 Node[0] Epoch[71] Batch [250] Speed: 610.25 samples/sec Train-accuracy=0.949688
2016-05-03 04:59:21,443 Node[0] Epoch[71] Batch [300] Speed: 608.72 samples/sec Train-accuracy=0.946875
2016-05-03 04:59:31,947 Node[0] Epoch[71] Batch [350] Speed: 609.31 samples/sec Train-accuracy=0.951250
2016-05-03 04:59:40,358 Node[0] Epoch[71] Resetting Data Iterator
2016-05-03 04:59:40,359 Node[0] Epoch[71] Time cost=82.009
2016-05-03 04:59:40,521 Node[0] Saved checkpoint to "cifar10/resnet-0072.params"
2016-05-03 04:59:42,415 Node[0] Epoch[71] Validation-accuracy=0.875000
2016-05-03 04:59:52,949 Node[0] Epoch[72] Batch [50] Speed: 610.74 samples/sec Train-accuracy=0.948125
2016-05-03 05:00:03,404 Node[0] Epoch[72] Batch [100] Speed: 612.17 samples/sec Train-accuracy=0.947812
2016-05-03 05:00:13,773 Node[0] Epoch[72] Batch [150] Speed: 617.23 samples/sec Train-accuracy=0.949375
2016-05-03 05:00:24,235 Node[0] Epoch[72] Batch [200] Speed: 611.77 samples/sec Train-accuracy=0.950313
2016-05-03 05:00:34,739 Node[0] Epoch[72] Batch [250] Speed: 609.27 samples/sec Train-accuracy=0.951250
2016-05-03 05:00:45,242 Node[0] Epoch[72] Batch [300] Speed: 609.40 samples/sec Train-accuracy=0.952500
2016-05-03 05:00:55,741 Node[0] Epoch[72] Batch [350] Speed: 609.56 samples/sec Train-accuracy=0.949531
2016-05-03 05:01:04,306 Node[0] Epoch[72] Resetting Data Iterator
2016-05-03 05:01:04,307 Node[0] Epoch[72] Time cost=81.892
2016-05-03 05:01:04,473 Node[0] Saved checkpoint to "cifar10/resnet-0073.params"
2016-05-03 05:01:06,589 Node[0] Epoch[72] Validation-accuracy=0.882911
2016-05-03 05:01:17,059 Node[0] Epoch[73] Batch [50] Speed: 614.49 samples/sec Train-accuracy=0.953594
2016-05-03 05:01:27,540 Node[0] Epoch[73] Batch [100] Speed: 610.61 samples/sec Train-accuracy=0.950313
2016-05-03 05:01:38,024 Node[0] Epoch[73] Batch [150] Speed: 610.51 samples/sec Train-accuracy=0.944219
2016-05-03 05:01:48,517 Node[0] Epoch[73] Batch [200] Speed: 609.94 samples/sec Train-accuracy=0.947344
2016-05-03 05:01:59,057 Node[0] Epoch[73] Batch [250] Speed: 607.21 samples/sec Train-accuracy=0.947187
2016-05-03 05:02:09,570 Node[0] Epoch[73] Batch [300] Speed: 608.76 samples/sec Train-accuracy=0.951719
2016-05-03 05:02:20,079 Node[0] Epoch[73] Batch [350] Speed: 609.05 samples/sec Train-accuracy=0.949375
2016-05-03 05:02:28,688 Node[0] Epoch[73] Resetting Data Iterator
2016-05-03 05:02:28,688 Node[0] Epoch[73] Time cost=82.099
2016-05-03 05:02:28,857 Node[0] Saved checkpoint to "cifar10/resnet-0074.params"
2016-05-03 05:02:30,784 Node[0] Epoch[73] Validation-accuracy=0.876502
2016-05-03 05:02:41,281 Node[0] Epoch[74] Batch [50] Speed: 612.90 samples/sec Train-accuracy=0.950937
2016-05-03 05:02:51,770 Node[0] Epoch[74] Batch [100] Speed: 610.14 samples/sec Train-accuracy=0.950781
2016-05-03 05:03:02,315 Node[0] Epoch[74] Batch [150] Speed: 606.96 samples/sec Train-accuracy=0.948594
2016-05-03 05:03:12,787 Node[0] Epoch[74] Batch [200] Speed: 611.14 samples/sec Train-accuracy=0.946094
2016-05-03 05:03:23,338 Node[0] Epoch[74] Batch [250] Speed: 606.60 samples/sec Train-accuracy=0.947344
2016-05-03 05:03:33,843 Node[0] Epoch[74] Batch [300] Speed: 609.25 samples/sec Train-accuracy=0.950000
2016-05-03 05:03:44,321 Node[0] Epoch[74] Batch [350] Speed: 610.82 samples/sec Train-accuracy=0.947187
2016-05-03 05:03:52,726 Node[0] Epoch[74] Resetting Data Iterator
2016-05-03 05:03:52,726 Node[0] Epoch[74] Time cost=81.943
2016-05-03 05:03:52,895 Node[0] Saved checkpoint to "cifar10/resnet-0075.params"
2016-05-03 05:03:54,797 Node[0] Epoch[74] Validation-accuracy=0.880709
2016-05-03 05:04:05,378 Node[0] Epoch[75] Batch [50] Speed: 607.93 samples/sec Train-accuracy=0.942969
2016-05-03 05:04:15,870 Node[0] Epoch[75] Batch [100] Speed: 609.99 samples/sec Train-accuracy=0.950781
2016-05-03 05:04:26,357 Node[0] Epoch[75] Batch [150] Speed: 610.28 samples/sec Train-accuracy=0.953125
2016-05-03 05:04:36,825 Node[0] Epoch[75] Batch [200] Speed: 611.46 samples/sec Train-accuracy=0.950469
2016-05-03 05:04:47,333 Node[0] Epoch[75] Batch [250] Speed: 609.03 samples/sec Train-accuracy=0.949531
2016-05-03 05:04:57,825 Node[0] Epoch[75] Batch [300] Speed: 610.02 samples/sec Train-accuracy=0.951562
2016-05-03 05:05:08,356 Node[0] Epoch[75] Batch [350] Speed: 607.74 samples/sec Train-accuracy=0.948750
2016-05-03 05:05:16,942 Node[0] Epoch[75] Resetting Data Iterator
2016-05-03 05:05:16,942 Node[0] Epoch[75] Time cost=82.145
2016-05-03 05:05:17,107 Node[0] Saved checkpoint to "cifar10/resnet-0076.params"
2016-05-03 05:05:19,045 Node[0] Epoch[75] Validation-accuracy=0.892228
2016-05-03 05:05:29,609 Node[0] Epoch[76] Batch [50] Speed: 609.02 samples/sec Train-accuracy=0.957656
2016-05-03 05:05:40,177 Node[0] Epoch[76] Batch [100] Speed: 605.61 samples/sec Train-accuracy=0.948125
2016-05-03 05:05:50,696 Node[0] Epoch[76] Batch [150] Speed: 608.45 samples/sec Train-accuracy=0.948281
2016-05-03 05:06:01,180 Node[0] Epoch[76] Batch [200] Speed: 610.42 samples/sec Train-accuracy=0.949219
2016-05-03 05:06:11,660 Node[0] Epoch[76] Batch [250] Speed: 610.73 samples/sec Train-accuracy=0.945937
2016-05-03 05:06:22,178 Node[0] Epoch[76] Batch [300] Speed: 608.52 samples/sec Train-accuracy=0.952187
2016-05-03 05:06:32,714 Node[0] Epoch[76] Batch [350] Speed: 607.41 samples/sec Train-accuracy=0.950781
2016-05-03 05:06:41,310 Node[0] Epoch[76] Resetting Data Iterator
2016-05-03 05:06:41,310 Node[0] Epoch[76] Time cost=82.265
2016-05-03 05:06:41,473 Node[0] Saved checkpoint to "cifar10/resnet-0077.params"
2016-05-03 05:06:43,406 Node[0] Epoch[76] Validation-accuracy=0.866186
2016-05-03 05:06:53,986 Node[0] Epoch[77] Batch [50] Speed: 608.14 samples/sec Train-accuracy=0.942656
2016-05-03 05:07:04,506 Node[0] Epoch[77] Batch [100] Speed: 608.38 samples/sec Train-accuracy=0.949688
2016-05-03 05:07:14,993 Node[0] Epoch[77] Batch [150] Speed: 610.24 samples/sec Train-accuracy=0.953125
2016-05-03 05:07:25,508 Node[0] Epoch[77] Batch [200] Speed: 608.67 samples/sec Train-accuracy=0.947500
2016-05-03 05:07:36,020 Node[0] Epoch[77] Batch [250] Speed: 608.89 samples/sec Train-accuracy=0.950625
2016-05-03 05:07:46,543 Node[0] Epoch[77] Batch [300] Speed: 608.21 samples/sec Train-accuracy=0.954688
2016-05-03 05:07:57,041 Node[0] Epoch[77] Batch [350] Speed: 609.63 samples/sec Train-accuracy=0.944844
2016-05-03 05:08:05,424 Node[0] Epoch[77] Resetting Data Iterator
2016-05-03 05:08:05,425 Node[0] Epoch[77] Time cost=82.018
2016-05-03 05:08:05,593 Node[0] Saved checkpoint to "cifar10/resnet-0078.params"
2016-05-03 05:08:07,541 Node[0] Epoch[77] Validation-accuracy=0.883413
2016-05-03 05:08:18,127 Node[0] Epoch[78] Batch [50] Speed: 607.83 samples/sec Train-accuracy=0.947031
2016-05-03 05:08:28,630 Node[0] Epoch[78] Batch [100] Speed: 609.38 samples/sec Train-accuracy=0.951562
2016-05-03 05:08:39,125 Node[0] Epoch[78] Batch [150] Speed: 609.78 samples/sec Train-accuracy=0.952187
2016-05-03 05:08:49,610 Node[0] Epoch[78] Batch [200] Speed: 610.42 samples/sec Train-accuracy=0.950625
2016-05-03 05:09:00,161 Node[0] Epoch[78] Batch [250] Speed: 606.63 samples/sec Train-accuracy=0.955000
2016-05-03 05:09:10,672 Node[0] Epoch[78] Batch [300] Speed: 608.90 samples/sec Train-accuracy=0.950313
2016-05-03 05:09:21,192 Node[0] Epoch[78] Batch [350] Speed: 608.36 samples/sec Train-accuracy=0.950156
2016-05-03 05:09:29,813 Node[0] Epoch[78] Resetting Data Iterator
2016-05-03 05:09:29,813 Node[0] Epoch[78] Time cost=82.272
2016-05-03 05:09:29,977 Node[0] Saved checkpoint to "cifar10/resnet-0079.params"
2016-05-03 05:09:31,901 Node[0] Epoch[78] Validation-accuracy=0.874399
2016-05-03 05:09:42,435 Node[0] Epoch[79] Batch [50] Speed: 610.75 samples/sec Train-accuracy=0.953125
2016-05-03 05:09:52,936 Node[0] Epoch[79] Batch [100] Speed: 609.50 samples/sec Train-accuracy=0.950313
2016-05-03 05:10:03,406 Node[0] Epoch[79] Batch [150] Speed: 611.29 samples/sec Train-accuracy=0.950781
2016-05-03 05:10:13,906 Node[0] Epoch[79] Batch [200] Speed: 609.53 samples/sec Train-accuracy=0.955000
2016-05-03 05:10:24,426 Node[0] Epoch[79] Batch [250] Speed: 608.38 samples/sec Train-accuracy=0.943438
2016-05-03 05:10:34,945 Node[0] Epoch[79] Batch [300] Speed: 608.42 samples/sec Train-accuracy=0.951094
2016-05-03 05:10:45,474 Node[0] Epoch[79] Batch [350] Speed: 607.89 samples/sec Train-accuracy=0.954688
2016-05-03 05:10:53,875 Node[0] Epoch[79] Resetting Data Iterator
2016-05-03 05:10:53,875 Node[0] Epoch[79] Time cost=81.974
2016-05-03 05:10:54,039 Node[0] Saved checkpoint to "cifar10/resnet-0080.params"
2016-05-03 05:10:55,943 Node[0] Epoch[79] Validation-accuracy=0.866186
2016-05-03 05:10:55,944 Node[0] Update[31251]: Change learning rate to 1.00000e-02
2016-05-03 05:11:06,502 Node[0] Epoch[80] Batch [50] Speed: 609.29 samples/sec Train-accuracy=0.954844
2016-05-03 05:11:17,066 Node[0] Epoch[80] Batch [100] Speed: 605.89 samples/sec Train-accuracy=0.966875
2016-05-03 05:11:27,606 Node[0] Epoch[80] Batch [150] Speed: 607.18 samples/sec Train-accuracy=0.970156
2016-05-03 05:11:38,149 Node[0] Epoch[80] Batch [200] Speed: 607.10 samples/sec Train-accuracy=0.971719
2016-05-03 05:11:48,695 Node[0] Epoch[80] Batch [250] Speed: 606.82 samples/sec Train-accuracy=0.974688
2016-05-03 05:11:59,172 Node[0] Epoch[80] Batch [300] Speed: 610.91 samples/sec Train-accuracy=0.978906
2016-05-03 05:12:09,643 Node[0] Epoch[80] Batch [350] Speed: 611.20 samples/sec Train-accuracy=0.979531
2016-05-03 05:12:18,251 Node[0] Epoch[80] Resetting Data Iterator
2016-05-03 05:12:18,251 Node[0] Epoch[80] Time cost=82.308
2016-05-03 05:12:18,414 Node[0] Saved checkpoint to "cifar10/resnet-0081.params"
2016-05-03 05:12:20,529 Node[0] Epoch[80] Validation-accuracy=0.914953
2016-05-03 05:12:31,082 Node[0] Epoch[81] Batch [50] Speed: 609.71 samples/sec Train-accuracy=0.979531
2016-05-03 05:12:41,561 Node[0] Epoch[81] Batch [100] Speed: 610.80 samples/sec Train-accuracy=0.978750
2016-05-03 05:12:51,959 Node[0] Epoch[81] Batch [150] Speed: 615.49 samples/sec Train-accuracy=0.978906
2016-05-03 05:13:02,323 Node[0] Epoch[81] Batch [200] Speed: 617.53 samples/sec Train-accuracy=0.981406
2016-05-03 05:13:12,855 Node[0] Epoch[81] Batch [250] Speed: 607.70 samples/sec Train-accuracy=0.981563
2016-05-03 05:13:23,482 Node[0] Epoch[81] Batch [300] Speed: 602.22 samples/sec Train-accuracy=0.985156
2016-05-03 05:13:34,074 Node[0] Epoch[81] Batch [350] Speed: 604.25 samples/sec Train-accuracy=0.985781
2016-05-03 05:13:42,689 Node[0] Epoch[81] Resetting Data Iterator
2016-05-03 05:13:42,690 Node[0] Epoch[81] Time cost=82.160
2016-05-03 05:13:42,854 Node[0] Saved checkpoint to "cifar10/resnet-0082.params"
2016-05-03 05:13:44,758 Node[0] Epoch[81] Validation-accuracy=0.917167
2016-05-03 05:13:55,216 Node[0] Epoch[82] Batch [50] Speed: 615.21 samples/sec Train-accuracy=0.984688
2016-05-03 05:14:05,737 Node[0] Epoch[82] Batch [100] Speed: 608.27 samples/sec Train-accuracy=0.986563
2016-05-03 05:14:16,217 Node[0] Epoch[82] Batch [150] Speed: 610.74 samples/sec Train-accuracy=0.985625
2016-05-03 05:14:26,787 Node[0] Epoch[82] Batch [200] Speed: 605.48 samples/sec Train-accuracy=0.985938
2016-05-03 05:14:37,267 Node[0] Epoch[82] Batch [250] Speed: 610.70 samples/sec Train-accuracy=0.988281
2016-05-03 05:14:47,731 Node[0] Epoch[82] Batch [300] Speed: 611.64 samples/sec Train-accuracy=0.987344
2016-05-03 05:14:58,241 Node[0] Epoch[82] Batch [350] Speed: 608.97 samples/sec Train-accuracy=0.987969
2016-05-03 05:15:06,625 Node[0] Epoch[82] Resetting Data Iterator
2016-05-03 05:15:06,625 Node[0] Epoch[82] Time cost=81.867
2016-05-03 05:15:06,789 Node[0] Saved checkpoint to "cifar10/resnet-0083.params"
2016-05-03 05:15:08,701 Node[0] Epoch[82] Validation-accuracy=0.918870
2016-05-03 05:15:19,233 Node[0] Epoch[83] Batch [50] Speed: 610.92 samples/sec Train-accuracy=0.986875
2016-05-03 05:15:29,725 Node[0] Epoch[83] Batch [100] Speed: 609.99 samples/sec Train-accuracy=0.983906
2016-05-03 05:15:40,242 Node[0] Epoch[83] Batch [150] Speed: 608.57 samples/sec Train-accuracy=0.986719
2016-05-03 05:15:50,748 Node[0] Epoch[83] Batch [200] Speed: 609.18 samples/sec Train-accuracy=0.989219
2016-05-03 05:16:01,271 Node[0] Epoch[83] Batch [250] Speed: 608.25 samples/sec Train-accuracy=0.989062
2016-05-03 05:16:11,752 Node[0] Epoch[83] Batch [300] Speed: 610.63 samples/sec Train-accuracy=0.990938
2016-05-03 05:16:22,270 Node[0] Epoch[83] Batch [350] Speed: 608.45 samples/sec Train-accuracy=0.988750
2016-05-03 05:16:30,884 Node[0] Epoch[83] Resetting Data Iterator
2016-05-03 05:16:30,885 Node[0] Epoch[83] Time cost=82.183
2016-05-03 05:16:31,051 Node[0] Saved checkpoint to "cifar10/resnet-0084.params"
2016-05-03 05:16:32,987 Node[0] Epoch[83] Validation-accuracy=0.917668
2016-05-03 05:16:43,567 Node[0] Epoch[84] Batch [50] Speed: 608.10 samples/sec Train-accuracy=0.988594
2016-05-03 05:16:54,121 Node[0] Epoch[84] Batch [100] Speed: 606.44 samples/sec Train-accuracy=0.988594
2016-05-03 05:17:04,507 Node[0] Epoch[84] Batch [150] Speed: 616.23 samples/sec Train-accuracy=0.988750
2016-05-03 05:17:14,934 Node[0] Epoch[84] Batch [200] Speed: 613.81 samples/sec Train-accuracy=0.988906
2016-05-03 05:17:25,433 Node[0] Epoch[84] Batch [250] Speed: 609.61 samples/sec Train-accuracy=0.992344
2016-05-03 05:17:35,919 Node[0] Epoch[84] Batch [300] Speed: 610.33 samples/sec Train-accuracy=0.991563
2016-05-03 05:17:46,436 Node[0] Epoch[84] Batch [350] Speed: 608.59 samples/sec Train-accuracy=0.992031
2016-05-03 05:17:55,020 Node[0] Epoch[84] Resetting Data Iterator
2016-05-03 05:17:55,020 Node[0] Epoch[84] Time cost=82.033
2016-05-03 05:17:55,185 Node[0] Saved checkpoint to "cifar10/resnet-0085.params"
2016-05-03 05:17:57,098 Node[0] Epoch[84] Validation-accuracy=0.920873
2016-05-03 05:18:07,681 Node[0] Epoch[85] Batch [50] Speed: 608.05 samples/sec Train-accuracy=0.990000
2016-05-03 05:18:18,276 Node[0] Epoch[85] Batch [100] Speed: 604.07 samples/sec Train-accuracy=0.990000
2016-05-03 05:18:28,764 Node[0] Epoch[85] Batch [150] Speed: 610.27 samples/sec Train-accuracy=0.989375
2016-05-03 05:18:39,255 Node[0] Epoch[85] Batch [200] Speed: 610.03 samples/sec Train-accuracy=0.989219
2016-05-03 05:18:49,807 Node[0] Epoch[85] Batch [250] Speed: 606.52 samples/sec Train-accuracy=0.990938
2016-05-03 05:19:00,303 Node[0] Epoch[85] Batch [300] Speed: 609.78 samples/sec Train-accuracy=0.991875
2016-05-03 05:19:10,721 Node[0] Epoch[85] Batch [350] Speed: 614.34 samples/sec Train-accuracy=0.992812
2016-05-03 05:19:19,110 Node[0] Epoch[85] Resetting Data Iterator
2016-05-03 05:19:19,110 Node[0] Epoch[85] Time cost=82.012
2016-05-03 05:19:19,272 Node[0] Saved checkpoint to "cifar10/resnet-0086.params"
2016-05-03 05:19:21,198 Node[0] Epoch[85] Validation-accuracy=0.920072
2016-05-03 05:19:31,826 Node[0] Epoch[86] Batch [50] Speed: 605.33 samples/sec Train-accuracy=0.990469
2016-05-03 05:19:42,370 Node[0] Epoch[86] Batch [100] Speed: 606.99 samples/sec Train-accuracy=0.990469
2016-05-03 05:19:52,852 Node[0] Epoch[86] Batch [150] Speed: 610.61 samples/sec Train-accuracy=0.992344
2016-05-03 05:20:03,360 Node[0] Epoch[86] Batch [200] Speed: 609.03 samples/sec Train-accuracy=0.989688
2016-05-03 05:20:13,864 Node[0] Epoch[86] Batch [250] Speed: 609.34 samples/sec Train-accuracy=0.992031
2016-05-03 05:20:24,351 Node[0] Epoch[86] Batch [300] Speed: 610.28 samples/sec Train-accuracy=0.993437
2016-05-03 05:20:34,815 Node[0] Epoch[86] Batch [350] Speed: 611.65 samples/sec Train-accuracy=0.995000
2016-05-03 05:20:43,418 Node[0] Epoch[86] Resetting Data Iterator
2016-05-03 05:20:43,418 Node[0] Epoch[86] Time cost=82.220
2016-05-03 05:20:43,584 Node[0] Saved checkpoint to "cifar10/resnet-0087.params"
2016-05-03 05:20:45,524 Node[0] Epoch[86] Validation-accuracy=0.920573
2016-05-03 05:20:56,072 Node[0] Epoch[87] Batch [50] Speed: 609.91 samples/sec Train-accuracy=0.992656
2016-05-03 05:21:06,582 Node[0] Epoch[87] Batch [100] Speed: 608.97 samples/sec Train-accuracy=0.992031
2016-05-03 05:21:17,108 Node[0] Epoch[87] Batch [150] Speed: 608.00 samples/sec Train-accuracy=0.991875
2016-05-03 05:21:27,613 Node[0] Epoch[87] Batch [200] Speed: 609.23 samples/sec Train-accuracy=0.989531
2016-05-03 05:21:38,078 Node[0] Epoch[87] Batch [250] Speed: 611.60 samples/sec Train-accuracy=0.994687
2016-05-03 05:21:48,576 Node[0] Epoch[87] Batch [300] Speed: 609.63 samples/sec Train-accuracy=0.993594
2016-05-03 05:21:59,097 Node[0] Epoch[87] Batch [350] Speed: 608.36 samples/sec Train-accuracy=0.995000
2016-05-03 05:22:07,494 Node[0] Epoch[87] Resetting Data Iterator
2016-05-03 05:22:07,495 Node[0] Epoch[87] Time cost=81.971
2016-05-03 05:22:07,656 Node[0] Saved checkpoint to "cifar10/resnet-0088.params"
2016-05-03 05:22:09,574 Node[0] Epoch[87] Validation-accuracy=0.920773
2016-05-03 05:22:20,188 Node[0] Epoch[88] Batch [50] Speed: 606.16 samples/sec Train-accuracy=0.991406
2016-05-03 05:22:30,703 Node[0] Epoch[88] Batch [100] Speed: 608.69 samples/sec Train-accuracy=0.992812
2016-05-03 05:22:41,187 Node[0] Epoch[88] Batch [150] Speed: 610.46 samples/sec Train-accuracy=0.993281
2016-05-03 05:22:51,650 Node[0] Epoch[88] Batch [200] Speed: 611.70 samples/sec Train-accuracy=0.994531
2016-05-03 05:23:02,181 Node[0] Epoch[88] Batch [250] Speed: 607.76 samples/sec Train-accuracy=0.994531
2016-05-03 05:23:12,716 Node[0] Epoch[88] Batch [300] Speed: 607.49 samples/sec Train-accuracy=0.992969
2016-05-03 05:23:23,234 Node[0] Epoch[88] Batch [350] Speed: 608.52 samples/sec Train-accuracy=0.994844
2016-05-03 05:23:31,814 Node[0] Epoch[88] Resetting Data Iterator
2016-05-03 05:23:31,814 Node[0] Epoch[88] Time cost=82.240
2016-05-03 05:23:31,976 Node[0] Saved checkpoint to "cifar10/resnet-0089.params"
2016-05-03 05:23:34,151 Node[0] Epoch[88] Validation-accuracy=0.921084
2016-05-03 05:23:44,717 Node[0] Epoch[89] Batch [50] Speed: 608.90 samples/sec Train-accuracy=0.992812
2016-05-03 05:23:55,255 Node[0] Epoch[89] Batch [100] Speed: 607.31 samples/sec Train-accuracy=0.994844
2016-05-03 05:24:05,719 Node[0] Epoch[89] Batch [150] Speed: 611.66 samples/sec Train-accuracy=0.993125
2016-05-03 05:24:16,224 Node[0] Epoch[89] Batch [200] Speed: 609.22 samples/sec Train-accuracy=0.993750
2016-05-03 05:24:26,704 Node[0] Epoch[89] Batch [250] Speed: 610.72 samples/sec Train-accuracy=0.993750
2016-05-03 05:24:37,196 Node[0] Epoch[89] Batch [300] Speed: 610.00 samples/sec Train-accuracy=0.995313
2016-05-03 05:24:47,721 Node[0] Epoch[89] Batch [350] Speed: 608.09 samples/sec Train-accuracy=0.994687
2016-05-03 05:24:56,331 Node[0] Epoch[89] Resetting Data Iterator
2016-05-03 05:24:56,331 Node[0] Epoch[89] Time cost=82.179
2016-05-03 05:24:56,501 Node[0] Saved checkpoint to "cifar10/resnet-0090.params"
2016-05-03 05:24:58,438 Node[0] Epoch[89] Validation-accuracy=0.920072
2016-05-03 05:25:08,992 Node[0] Epoch[90] Batch [50] Speed: 609.58 samples/sec Train-accuracy=0.993906
2016-05-03 05:25:19,550 Node[0] Epoch[90] Batch [100] Speed: 606.23 samples/sec Train-accuracy=0.992500
2016-05-03 05:25:30,069 Node[0] Epoch[90] Batch [150] Speed: 608.45 samples/sec Train-accuracy=0.995000
2016-05-03 05:25:40,567 Node[0] Epoch[90] Batch [200] Speed: 609.62 samples/sec Train-accuracy=0.993437
2016-05-03 05:25:51,071 Node[0] Epoch[90] Batch [250] Speed: 609.30 samples/sec Train-accuracy=0.994531
2016-05-03 05:26:01,598 Node[0] Epoch[90] Batch [300] Speed: 607.98 samples/sec Train-accuracy=0.995781
2016-05-03 05:26:12,120 Node[0] Epoch[90] Batch [350] Speed: 608.24 samples/sec Train-accuracy=0.994531
2016-05-03 05:26:20,496 Node[0] Epoch[90] Resetting Data Iterator
2016-05-03 05:26:20,496 Node[0] Epoch[90] Time cost=82.057
2016-05-03 05:26:20,661 Node[0] Saved checkpoint to "cifar10/resnet-0091.params"
2016-05-03 05:26:22,571 Node[0] Epoch[90] Validation-accuracy=0.919271
2016-05-03 05:26:33,202 Node[0] Epoch[91] Batch [50] Speed: 605.22 samples/sec Train-accuracy=0.996250
2016-05-03 05:26:43,665 Node[0] Epoch[91] Batch [100] Speed: 611.65 samples/sec Train-accuracy=0.994219
2016-05-03 05:26:54,034 Node[0] Epoch[91] Batch [150] Speed: 617.27 samples/sec Train-accuracy=0.995625
2016-05-03 05:27:04,554 Node[0] Epoch[91] Batch [200] Speed: 608.40 samples/sec Train-accuracy=0.995469
2016-05-03 05:27:15,026 Node[0] Epoch[91] Batch [250] Speed: 611.12 samples/sec Train-accuracy=0.995938
2016-05-03 05:27:25,507 Node[0] Epoch[91] Batch [300] Speed: 610.69 samples/sec Train-accuracy=0.994687
2016-05-03 05:27:35,952 Node[0] Epoch[91] Batch [350] Speed: 612.74 samples/sec Train-accuracy=0.996094
2016-05-03 05:27:44,550 Node[0] Epoch[91] Resetting Data Iterator
2016-05-03 05:27:44,550 Node[0] Epoch[91] Time cost=81.978
2016-05-03 05:27:44,717 Node[0] Saved checkpoint to "cifar10/resnet-0092.params"
2016-05-03 05:27:46,662 Node[0] Epoch[91] Validation-accuracy=0.919471
2016-05-03 05:27:57,237 Node[0] Epoch[92] Batch [50] Speed: 608.46 samples/sec Train-accuracy=0.995469
2016-05-03 05:28:07,711 Node[0] Epoch[92] Batch [100] Speed: 611.03 samples/sec Train-accuracy=0.994844
2016-05-03 05:28:18,089 Node[0] Epoch[92] Batch [150] Speed: 616.70 samples/sec Train-accuracy=0.994687
2016-05-03 05:28:28,530 Node[0] Epoch[92] Batch [200] Speed: 613.02 samples/sec Train-accuracy=0.994687
2016-05-03 05:28:39,020 Node[0] Epoch[92] Batch [250] Speed: 610.12 samples/sec Train-accuracy=0.994062
2016-05-03 05:28:49,496 Node[0] Epoch[92] Batch [300] Speed: 610.92 samples/sec Train-accuracy=0.996875
2016-05-03 05:29:00,024 Node[0] Epoch[92] Batch [350] Speed: 607.90 samples/sec Train-accuracy=0.995000
2016-05-03 05:29:08,621 Node[0] Epoch[92] Resetting Data Iterator
2016-05-03 05:29:08,622 Node[0] Epoch[92] Time cost=81.960
2016-05-03 05:29:08,784 Node[0] Saved checkpoint to "cifar10/resnet-0093.params"
2016-05-03 05:29:10,715 Node[0] Epoch[92] Validation-accuracy=0.920673
2016-05-03 05:29:21,246 Node[0] Epoch[93] Batch [50] Speed: 610.91 samples/sec Train-accuracy=0.994219
2016-05-03 05:29:31,765 Node[0] Epoch[93] Batch [100] Speed: 608.45 samples/sec Train-accuracy=0.996719
2016-05-03 05:29:42,266 Node[0] Epoch[93] Batch [150] Speed: 609.48 samples/sec Train-accuracy=0.995000
2016-05-03 05:29:52,800 Node[0] Epoch[93] Batch [200] Speed: 607.56 samples/sec Train-accuracy=0.995781
2016-05-03 05:30:03,319 Node[0] Epoch[93] Batch [250] Speed: 608.44 samples/sec Train-accuracy=0.995938
2016-05-03 05:30:13,820 Node[0] Epoch[93] Batch [300] Speed: 609.48 samples/sec Train-accuracy=0.996406
2016-05-03 05:30:24,318 Node[0] Epoch[93] Batch [350] Speed: 609.63 samples/sec Train-accuracy=0.997031
2016-05-03 05:30:32,704 Node[0] Epoch[93] Resetting Data Iterator
2016-05-03 05:30:32,704 Node[0] Epoch[93] Time cost=81.989
2016-05-03 05:30:32,870 Node[0] Saved checkpoint to "cifar10/resnet-0094.params"
2016-05-03 05:30:34,801 Node[0] Epoch[93] Validation-accuracy=0.920773
2016-05-03 05:30:45,348 Node[0] Epoch[94] Batch [50] Speed: 609.98 samples/sec Train-accuracy=0.993750
2016-05-03 05:30:55,777 Node[0] Epoch[94] Batch [100] Speed: 613.74 samples/sec Train-accuracy=0.995000
2016-05-03 05:31:06,174 Node[0] Epoch[94] Batch [150] Speed: 615.57 samples/sec Train-accuracy=0.997031
2016-05-03 05:31:16,620 Node[0] Epoch[94] Batch [200] Speed: 612.64 samples/sec Train-accuracy=0.995000
2016-05-03 05:31:27,223 Node[0] Epoch[94] Batch [250] Speed: 603.62 samples/sec Train-accuracy=0.994844
2016-05-03 05:31:37,847 Node[0] Epoch[94] Batch [300] Speed: 602.45 samples/sec Train-accuracy=0.996406
2016-05-03 05:31:48,367 Node[0] Epoch[94] Batch [350] Speed: 608.40 samples/sec Train-accuracy=0.996719
2016-05-03 05:31:56,928 Node[0] Epoch[94] Resetting Data Iterator
2016-05-03 05:31:56,928 Node[0] Epoch[94] Time cost=82.127
2016-05-03 05:31:57,090 Node[0] Saved checkpoint to "cifar10/resnet-0095.params"
2016-05-03 05:31:59,004 Node[0] Epoch[94] Validation-accuracy=0.919171
2016-05-03 05:32:09,606 Node[0] Epoch[95] Batch [50] Speed: 606.83 samples/sec Train-accuracy=0.996875
2016-05-03 05:32:20,047 Node[0] Epoch[95] Batch [100] Speed: 612.97 samples/sec Train-accuracy=0.996875
2016-05-03 05:32:30,454 Node[0] Epoch[95] Batch [150] Speed: 614.98 samples/sec Train-accuracy=0.996094
2016-05-03 05:32:40,965 Node[0] Epoch[95] Batch [200] Speed: 608.88 samples/sec Train-accuracy=0.995781
2016-05-03 05:32:51,566 Node[0] Epoch[95] Batch [250] Speed: 603.76 samples/sec Train-accuracy=0.995625
2016-05-03 05:33:02,100 Node[0] Epoch[95] Batch [300] Speed: 607.57 samples/sec Train-accuracy=0.996094
2016-05-03 05:33:12,601 Node[0] Epoch[95] Batch [350] Speed: 609.47 samples/sec Train-accuracy=0.996719
2016-05-03 05:33:20,989 Node[0] Epoch[95] Resetting Data Iterator
2016-05-03 05:33:20,990 Node[0] Epoch[95] Time cost=81.985
2016-05-03 05:33:21,156 Node[0] Saved checkpoint to "cifar10/resnet-0096.params"
2016-05-03 05:33:23,059 Node[0] Epoch[95] Validation-accuracy=0.922476
2016-05-03 05:33:33,593 Node[0] Epoch[96] Batch [50] Speed: 610.74 samples/sec Train-accuracy=0.996563
2016-05-03 05:33:44,065 Node[0] Epoch[96] Batch [100] Speed: 611.20 samples/sec Train-accuracy=0.997344
2016-05-03 05:33:54,530 Node[0] Epoch[96] Batch [150] Speed: 611.55 samples/sec Train-accuracy=0.995000
2016-05-03 05:34:05,085 Node[0] Epoch[96] Batch [200] Speed: 606.36 samples/sec Train-accuracy=0.997031
2016-05-03 05:34:15,591 Node[0] Epoch[96] Batch [250] Speed: 609.22 samples/sec Train-accuracy=0.996719
2016-05-03 05:34:26,118 Node[0] Epoch[96] Batch [300] Speed: 607.98 samples/sec Train-accuracy=0.996094
2016-05-03 05:34:36,617 Node[0] Epoch[96] Batch [350] Speed: 609.57 samples/sec Train-accuracy=0.996875
2016-05-03 05:34:45,222 Node[0] Epoch[96] Resetting Data Iterator
2016-05-03 05:34:45,222 Node[0] Epoch[96] Time cost=82.163
2016-05-03 05:34:45,387 Node[0] Saved checkpoint to "cifar10/resnet-0097.params"
2016-05-03 05:34:47,497 Node[0] Epoch[96] Validation-accuracy=0.922963
2016-05-03 05:34:58,052 Node[0] Epoch[97] Batch [50] Speed: 609.51 samples/sec Train-accuracy=0.994844
2016-05-03 05:35:08,577 Node[0] Epoch[97] Batch [100] Speed: 608.06 samples/sec Train-accuracy=0.995469
2016-05-03 05:35:19,057 Node[0] Epoch[97] Batch [150] Speed: 610.69 samples/sec Train-accuracy=0.995938
2016-05-03 05:35:29,608 Node[0] Epoch[97] Batch [200] Speed: 606.63 samples/sec Train-accuracy=0.996719
2016-05-03 05:35:40,091 Node[0] Epoch[97] Batch [250] Speed: 610.53 samples/sec Train-accuracy=0.996094
2016-05-03 05:35:50,621 Node[0] Epoch[97] Batch [300] Speed: 607.78 samples/sec Train-accuracy=0.997812
2016-05-03 05:36:01,163 Node[0] Epoch[97] Batch [350] Speed: 607.13 samples/sec Train-accuracy=0.997031
2016-05-03 05:36:09,774 Node[0] Epoch[97] Resetting Data Iterator
2016-05-03 05:36:09,774 Node[0] Epoch[97] Time cost=82.277
2016-05-03 05:36:09,938 Node[0] Saved checkpoint to "cifar10/resnet-0098.params"
2016-05-03 05:36:11,876 Node[0] Epoch[97] Validation-accuracy=0.921474
2016-05-03 05:36:22,496 Node[0] Epoch[98] Batch [50] Speed: 605.84 samples/sec Train-accuracy=0.995469
2016-05-03 05:36:32,888 Node[0] Epoch[98] Batch [100] Speed: 615.90 samples/sec Train-accuracy=0.997344
2016-05-03 05:36:43,342 Node[0] Epoch[98] Batch [150] Speed: 612.22 samples/sec Train-accuracy=0.995938
2016-05-03 05:36:53,905 Node[0] Epoch[98] Batch [200] Speed: 605.91 samples/sec Train-accuracy=0.996719
2016-05-03 05:37:04,441 Node[0] Epoch[98] Batch [250] Speed: 607.45 samples/sec Train-accuracy=0.997031
2016-05-03 05:37:14,956 Node[0] Epoch[98] Batch [300] Speed: 608.62 samples/sec Train-accuracy=0.997969
2016-05-03 05:37:25,518 Node[0] Epoch[98] Batch [350] Speed: 606.01 samples/sec Train-accuracy=0.996875
2016-05-03 05:37:33,948 Node[0] Epoch[98] Resetting Data Iterator
2016-05-03 05:37:33,949 Node[0] Epoch[98] Time cost=82.073
2016-05-03 05:37:34,117 Node[0] Saved checkpoint to "cifar10/resnet-0099.params"
2016-05-03 05:37:36,049 Node[0] Epoch[98] Validation-accuracy=0.921374
2016-05-03 05:37:46,544 Node[0] Epoch[99] Batch [50] Speed: 612.99 samples/sec Train-accuracy=0.998437
2016-05-03 05:37:57,062 Node[0] Epoch[99] Batch [100] Speed: 608.52 samples/sec Train-accuracy=0.996563
2016-05-03 05:38:07,545 Node[0] Epoch[99] Batch [150] Speed: 610.55 samples/sec Train-accuracy=0.997656
2016-05-03 05:38:18,067 Node[0] Epoch[99] Batch [200] Speed: 608.25 samples/sec Train-accuracy=0.998125
2016-05-03 05:38:28,620 Node[0] Epoch[99] Batch [250] Speed: 606.49 samples/sec Train-accuracy=0.997500
2016-05-03 05:38:39,146 Node[0] Epoch[99] Batch [300] Speed: 607.99 samples/sec Train-accuracy=0.997344
2016-05-03 05:38:49,641 Node[0] Epoch[99] Batch [350] Speed: 609.85 samples/sec Train-accuracy=0.996719
2016-05-03 05:38:58,231 Node[0] Epoch[99] Resetting Data Iterator
2016-05-03 05:38:58,232 Node[0] Epoch[99] Time cost=82.183
2016-05-03 05:38:58,393 Node[0] Saved checkpoint to "cifar10/resnet-0100.params"
2016-05-03 05:39:00,315 Node[0] Epoch[99] Validation-accuracy=0.921875
2016-05-03 05:39:10,858 Node[0] Epoch[100] Batch [50] Speed: 610.20 samples/sec Train-accuracy=0.997812
2016-05-03 05:39:21,352 Node[0] Epoch[100] Batch [100] Speed: 609.92 samples/sec Train-accuracy=0.997344
2016-05-03 05:39:31,910 Node[0] Epoch[100] Batch [150] Speed: 606.21 samples/sec Train-accuracy=0.997969
2016-05-03 05:39:42,411 Node[0] Epoch[100] Batch [200] Speed: 609.46 samples/sec Train-accuracy=0.997969
2016-05-03 05:39:52,896 Node[0] Epoch[100] Batch [250] Speed: 610.42 samples/sec Train-accuracy=0.996875
2016-05-03 05:40:03,404 Node[0] Epoch[100] Batch [300] Speed: 609.09 samples/sec Train-accuracy=0.996563
2016-05-03 05:40:13,890 Node[0] Epoch[100] Batch [350] Speed: 610.32 samples/sec Train-accuracy=0.997656
2016-05-03 05:40:22,481 Node[0] Epoch[100] Resetting Data Iterator
2016-05-03 05:40:22,482 Node[0] Epoch[100] Time cost=82.166
2016-05-03 05:40:22,643 Node[0] Saved checkpoint to "cifar10/resnet-0101.params"
2016-05-03 05:40:24,592 Node[0] Epoch[100] Validation-accuracy=0.921575
2016-05-03 05:40:35,125 Node[0] Epoch[101] Batch [50] Speed: 610.81 samples/sec Train-accuracy=0.997656
2016-05-03 05:40:45,635 Node[0] Epoch[101] Batch [100] Speed: 608.95 samples/sec Train-accuracy=0.996250
2016-05-03 05:40:56,153 Node[0] Epoch[101] Batch [150] Speed: 608.51 samples/sec Train-accuracy=0.996406
2016-05-03 05:41:06,666 Node[0] Epoch[101] Batch [200] Speed: 608.76 samples/sec Train-accuracy=0.997969
2016-05-03 05:41:17,156 Node[0] Epoch[101] Batch [250] Speed: 610.13 samples/sec Train-accuracy=0.997969
2016-05-03 05:41:27,697 Node[0] Epoch[101] Batch [300] Speed: 607.19 samples/sec Train-accuracy=0.997500
2016-05-03 05:41:38,228 Node[0] Epoch[101] Batch [350] Speed: 607.72 samples/sec Train-accuracy=0.996719
2016-05-03 05:41:46,627 Node[0] Epoch[101] Resetting Data Iterator
2016-05-03 05:41:46,627 Node[0] Epoch[101] Time cost=82.035
2016-05-03 05:41:46,798 Node[0] Saved checkpoint to "cifar10/resnet-0102.params"
2016-05-03 05:41:48,744 Node[0] Epoch[101] Validation-accuracy=0.922476
2016-05-03 05:41:59,332 Node[0] Epoch[102] Batch [50] Speed: 607.62 samples/sec Train-accuracy=0.997500
2016-05-03 05:42:09,869 Node[0] Epoch[102] Batch [100] Speed: 607.42 samples/sec Train-accuracy=0.998125
2016-05-03 05:42:20,271 Node[0] Epoch[102] Batch [150] Speed: 615.24 samples/sec Train-accuracy=0.997500
2016-05-03 05:42:30,750 Node[0] Epoch[102] Batch [200] Speed: 610.77 samples/sec Train-accuracy=0.997500
2016-05-03 05:42:41,331 Node[0] Epoch[102] Batch [250] Speed: 604.89 samples/sec Train-accuracy=0.996875
2016-05-03 05:42:51,929 Node[0] Epoch[102] Batch [300] Speed: 603.89 samples/sec Train-accuracy=0.997500
2016-05-03 05:43:02,461 Node[0] Epoch[102] Batch [350] Speed: 607.71 samples/sec Train-accuracy=0.996875
2016-05-03 05:43:11,079 Node[0] Epoch[102] Resetting Data Iterator
2016-05-03 05:43:11,079 Node[0] Epoch[102] Time cost=82.335
2016-05-03 05:43:11,244 Node[0] Saved checkpoint to "cifar10/resnet-0103.params"
2016-05-03 05:43:13,133 Node[0] Epoch[102] Validation-accuracy=0.921474
2016-05-03 05:43:23,659 Node[0] Epoch[103] Batch [50] Speed: 611.23 samples/sec Train-accuracy=0.997656
2016-05-03 05:43:34,160 Node[0] Epoch[103] Batch [100] Speed: 609.51 samples/sec Train-accuracy=0.997656
2016-05-03 05:43:44,675 Node[0] Epoch[103] Batch [150] Speed: 608.66 samples/sec Train-accuracy=0.997188
2016-05-03 05:43:55,228 Node[0] Epoch[103] Batch [200] Speed: 606.49 samples/sec Train-accuracy=0.997969
2016-05-03 05:44:05,715 Node[0] Epoch[103] Batch [250] Speed: 610.30 samples/sec Train-accuracy=0.997812
2016-05-03 05:44:16,255 Node[0] Epoch[103] Batch [300] Speed: 607.23 samples/sec Train-accuracy=0.997656
2016-05-03 05:44:26,783 Node[0] Epoch[103] Batch [350] Speed: 607.91 samples/sec Train-accuracy=0.998125
2016-05-03 05:44:35,171 Node[0] Epoch[103] Resetting Data Iterator
2016-05-03 05:44:35,172 Node[0] Epoch[103] Time cost=82.038
2016-05-03 05:44:35,332 Node[0] Saved checkpoint to "cifar10/resnet-0104.params"
2016-05-03 05:44:37,244 Node[0] Epoch[103] Validation-accuracy=0.922877
2016-05-03 05:44:47,862 Node[0] Epoch[104] Batch [50] Speed: 605.92 samples/sec Train-accuracy=0.996563
2016-05-03 05:45:05,914 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 05:45:06,319 Node[0] Start training with [gpu(0)]
2016-05-03 05:45:27,373 Node[0] Epoch[0] Batch [50] Speed: 646.04 samples/sec Train-accuracy=0.101094
2016-05-03 05:45:37,463 Node[0] Epoch[0] Batch [100] Speed: 634.28 samples/sec Train-accuracy=0.105469
2016-05-03 05:45:47,642 Node[0] Epoch[0] Batch [150] Speed: 628.76 samples/sec Train-accuracy=0.099062
2016-05-03 05:45:58,079 Node[0] Epoch[0] Batch [200] Speed: 613.20 samples/sec Train-accuracy=0.099219
2016-05-03 05:46:22,947 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 05:46:23,346 Node[0] Start training with [gpu(0)]
2016-05-03 05:46:44,712 Node[0] Epoch[0] Batch [50] Speed: 644.94 samples/sec Train-accuracy=0.102813
2016-05-03 05:47:38,606 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 05:48:53,921 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 05:49:00,024 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 05:49:00,371 Node[0] Start training with [gpu(0)]
2016-05-03 05:49:21,285 Node[0] Epoch[0] Batch [50] Speed: 652.82 samples/sec Train-accuracy=0.101406
2016-05-03 05:49:31,338 Node[0] Epoch[0] Batch [100] Speed: 636.63 samples/sec Train-accuracy=0.100781
2016-05-03 05:49:41,426 Node[0] Epoch[0] Batch [150] Speed: 634.43 samples/sec Train-accuracy=0.100781
2016-05-03 05:49:51,541 Node[0] Epoch[0] Batch [200] Speed: 632.76 samples/sec Train-accuracy=0.101250
2016-05-03 05:50:01,610 Node[0] Epoch[0] Batch [250] Speed: 635.61 samples/sec Train-accuracy=0.093594
2016-05-03 05:50:11,772 Node[0] Epoch[0] Batch [300] Speed: 629.83 samples/sec Train-accuracy=0.098281
2016-05-03 05:50:22,445 Node[0] Epoch[0] Batch [350] Speed: 599.64 samples/sec Train-accuracy=0.095625
2016-05-03 05:50:31,231 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 05:50:31,232 Node[0] Epoch[0] Time cost=80.014
2016-05-03 05:50:31,398 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 05:50:33,570 Node[0] Epoch[0] Validation-accuracy=0.100079
2016-05-03 05:50:44,306 Node[0] Epoch[1] Batch [50] Speed: 599.28 samples/sec Train-accuracy=0.097500
2016-05-03 05:50:54,905 Node[0] Epoch[1] Batch [100] Speed: 603.87 samples/sec Train-accuracy=0.100469
2016-05-03 05:51:05,447 Node[0] Epoch[1] Batch [150] Speed: 607.13 samples/sec Train-accuracy=0.096094
2016-05-03 05:51:15,963 Node[0] Epoch[1] Batch [200] Speed: 608.61 samples/sec Train-accuracy=0.100625
2016-05-03 05:51:26,524 Node[0] Epoch[1] Batch [250] Speed: 606.02 samples/sec Train-accuracy=0.102500
2016-05-03 05:51:37,083 Node[0] Epoch[1] Batch [300] Speed: 606.09 samples/sec Train-accuracy=0.096094
2016-05-03 05:51:47,627 Node[0] Epoch[1] Batch [350] Speed: 607.04 samples/sec Train-accuracy=0.097812
2016-05-03 05:51:56,232 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 05:51:56,232 Node[0] Epoch[1] Time cost=82.662
2016-05-03 05:51:56,399 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 05:51:58,311 Node[0] Epoch[1] Validation-accuracy=0.099960
2016-05-03 05:52:09,016 Node[0] Epoch[2] Batch [50] Speed: 601.12 samples/sec Train-accuracy=0.097969
2016-05-03 06:09:52,936 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 06:09:53,292 Node[0] Start training with [gpu(0)]
2016-05-03 06:10:14,456 Node[0] Epoch[0] Batch [50] Speed: 652.67 samples/sec Train-accuracy=0.103281
2016-05-03 06:10:24,410 Node[0] Epoch[0] Batch [100] Speed: 643.00 samples/sec Train-accuracy=0.099844
2016-05-03 06:10:34,458 Node[0] Epoch[0] Batch [150] Speed: 636.97 samples/sec Train-accuracy=0.096875
2016-05-03 06:10:44,612 Node[0] Epoch[0] Batch [200] Speed: 630.30 samples/sec Train-accuracy=0.100469
2016-05-03 06:10:54,721 Node[0] Epoch[0] Batch [250] Speed: 633.12 samples/sec Train-accuracy=0.095781
2016-05-03 06:11:04,794 Node[0] Epoch[0] Batch [300] Speed: 635.36 samples/sec Train-accuracy=0.099844
2016-05-03 06:11:14,881 Node[0] Epoch[0] Batch [350] Speed: 634.53 samples/sec Train-accuracy=0.095625
2016-05-03 06:11:23,174 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 06:11:23,175 Node[0] Epoch[0] Time cost=78.787
2016-05-03 06:11:23,339 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 06:11:25,358 Node[0] Epoch[0] Validation-accuracy=0.100079
2016-05-03 06:11:35,481 Node[0] Epoch[1] Batch [50] Speed: 635.49 samples/sec Train-accuracy=0.091719
2016-05-03 06:11:45,881 Node[0] Epoch[1] Batch [100] Speed: 615.40 samples/sec Train-accuracy=0.098750
2016-05-03 06:11:56,310 Node[0] Epoch[1] Batch [150] Speed: 613.68 samples/sec Train-accuracy=0.102969
2016-05-03 06:12:06,760 Node[0] Epoch[1] Batch [200] Speed: 612.47 samples/sec Train-accuracy=0.100312
2016-05-03 06:12:17,102 Node[0] Epoch[1] Batch [250] Speed: 618.85 samples/sec Train-accuracy=0.098906
2016-05-03 06:12:27,459 Node[0] Epoch[1] Batch [300] Speed: 617.96 samples/sec Train-accuracy=0.096562
2016-05-03 06:12:37,783 Node[0] Epoch[1] Batch [350] Speed: 619.91 samples/sec Train-accuracy=0.096875
2016-05-03 06:12:46,290 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 06:12:46,291 Node[0] Epoch[1] Time cost=80.933
2016-05-03 06:12:46,458 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 06:12:48,378 Node[0] Epoch[1] Validation-accuracy=0.100060
2016-05-03 06:12:58,950 Node[0] Epoch[2] Batch [50] Speed: 608.55 samples/sec Train-accuracy=0.097031
2016-05-03 06:13:09,305 Node[0] Epoch[2] Batch [100] Speed: 618.10 samples/sec Train-accuracy=0.106094
2016-05-03 06:13:19,624 Node[0] Epoch[2] Batch [150] Speed: 620.22 samples/sec Train-accuracy=0.101562
2016-05-03 06:13:47,008 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 06:13:47,451 Node[0] Start training with [gpu(0)]
2016-05-03 06:14:10,673 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 06:14:11,003 Node[0] Start training with [gpu(0)]
2016-05-03 06:14:32,152 Node[0] Epoch[0] Batch [50] Speed: 647.38 samples/sec Train-accuracy=0.097344
2016-05-03 06:14:42,230 Node[0] Epoch[0] Batch [100] Speed: 635.09 samples/sec Train-accuracy=0.105000
2016-05-03 06:14:52,317 Node[0] Epoch[0] Batch [150] Speed: 634.51 samples/sec Train-accuracy=0.103281
2016-05-03 06:15:02,702 Node[0] Epoch[0] Batch [200] Speed: 616.29 samples/sec Train-accuracy=0.118125
2016-05-03 06:15:13,598 Node[0] Epoch[0] Batch [250] Speed: 587.33 samples/sec Train-accuracy=0.111875
2016-05-03 06:15:24,526 Node[0] Epoch[0] Batch [300] Speed: 585.67 samples/sec Train-accuracy=0.133281
2016-05-03 06:15:35,351 Node[0] Epoch[0] Batch [350] Speed: 591.28 samples/sec Train-accuracy=0.173906
2016-05-03 06:15:44,099 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 06:15:44,100 Node[0] Epoch[0] Time cost=82.105
2016-05-03 06:15:44,269 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 06:15:46,523 Node[0] Epoch[0] Validation-accuracy=0.235265
2016-05-03 06:15:57,277 Node[0] Epoch[1] Batch [50] Speed: 598.25 samples/sec Train-accuracy=0.238594
2016-05-03 06:16:08,000 Node[0] Epoch[1] Batch [100] Speed: 596.88 samples/sec Train-accuracy=0.255937
2016-05-03 07:59:59,409 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:01:30,747 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:02:17,599 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:02:32,917 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:02:41,717 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:04:34,816 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 08:04:35,159 Node[0] Start training with [gpu(0)]
2016-05-03 08:04:56,058 Node[0] Epoch[0] Batch [50] Speed: 653.57 samples/sec Train-accuracy=0.110625
2016-05-03 08:05:06,037 Node[0] Epoch[0] Batch [100] Speed: 641.36 samples/sec Train-accuracy=0.118906
2016-05-03 08:05:16,040 Node[0] Epoch[0] Batch [150] Speed: 639.83 samples/sec Train-accuracy=0.126406
2016-05-03 08:05:26,085 Node[0] Epoch[0] Batch [200] Speed: 637.12 samples/sec Train-accuracy=0.182188
2016-05-03 08:05:36,179 Node[0] Epoch[0] Batch [250] Speed: 634.05 samples/sec Train-accuracy=0.229531
2016-05-03 08:05:46,302 Node[0] Epoch[0] Batch [300] Speed: 632.28 samples/sec Train-accuracy=0.263125
2016-05-03 08:05:56,389 Node[0] Epoch[0] Batch [350] Speed: 634.49 samples/sec Train-accuracy=0.278438
2016-05-03 08:06:04,652 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 08:06:04,652 Node[0] Epoch[0] Time cost=78.722
2016-05-03 08:06:04,812 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 08:06:06,859 Node[0] Epoch[0] Validation-accuracy=0.332278
2016-05-03 08:06:17,391 Node[0] Epoch[1] Batch [50] Speed: 610.59 samples/sec Train-accuracy=0.319219
2016-05-03 08:06:27,927 Node[0] Epoch[1] Batch [100] Speed: 607.47 samples/sec Train-accuracy=0.352812
2016-05-03 08:06:38,292 Node[0] Epoch[1] Batch [150] Speed: 617.50 samples/sec Train-accuracy=0.368125
2016-05-03 08:06:48,660 Node[0] Epoch[1] Batch [200] Speed: 617.29 samples/sec Train-accuracy=0.376250
2016-05-03 08:06:58,988 Node[0] Epoch[1] Batch [250] Speed: 619.68 samples/sec Train-accuracy=0.401875
2016-05-03 08:07:09,340 Node[0] Epoch[1] Batch [300] Speed: 618.23 samples/sec Train-accuracy=0.407500
2016-05-03 08:07:19,856 Node[0] Epoch[1] Batch [350] Speed: 608.64 samples/sec Train-accuracy=0.416875
2016-05-03 08:07:28,415 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 08:07:28,415 Node[0] Epoch[1] Time cost=81.556
2016-05-03 08:07:28,580 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 08:07:30,508 Node[0] Epoch[1] Validation-accuracy=0.438802
2016-05-03 08:07:41,054 Node[0] Epoch[2] Batch [50] Speed: 610.12 samples/sec Train-accuracy=0.440625
2016-05-03 08:07:51,470 Node[0] Epoch[2] Batch [100] Speed: 614.42 samples/sec Train-accuracy=0.466094
2016-05-03 08:08:01,809 Node[0] Epoch[2] Batch [150] Speed: 619.03 samples/sec Train-accuracy=0.472187
2016-05-03 08:08:12,157 Node[0] Epoch[2] Batch [200] Speed: 618.51 samples/sec Train-accuracy=0.484687
2016-05-03 08:08:22,606 Node[0] Epoch[2] Batch [250] Speed: 612.52 samples/sec Train-accuracy=0.497344
2016-05-03 08:08:33,007 Node[0] Epoch[2] Batch [300] Speed: 615.33 samples/sec Train-accuracy=0.511875
2016-05-03 08:08:43,436 Node[0] Epoch[2] Batch [350] Speed: 613.70 samples/sec Train-accuracy=0.514062
2016-05-03 08:08:51,762 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 08:08:51,762 Node[0] Epoch[2] Time cost=81.254
2016-05-03 08:08:51,928 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 08:08:53,905 Node[0] Epoch[2] Validation-accuracy=0.528145
2016-05-03 08:09:04,470 Node[0] Epoch[3] Batch [50] Speed: 608.99 samples/sec Train-accuracy=0.531094
2016-05-03 08:09:14,827 Node[0] Epoch[3] Batch [100] Speed: 617.96 samples/sec Train-accuracy=0.552500
2016-05-03 08:09:25,225 Node[0] Epoch[3] Batch [150] Speed: 615.54 samples/sec Train-accuracy=0.565156
2016-05-03 08:09:35,685 Node[0] Epoch[3] Batch [200] Speed: 611.83 samples/sec Train-accuracy=0.567656
2016-05-03 08:09:46,108 Node[0] Epoch[3] Batch [250] Speed: 614.06 samples/sec Train-accuracy=0.573906
2016-05-03 08:09:56,547 Node[0] Epoch[3] Batch [300] Speed: 613.12 samples/sec Train-accuracy=0.586719
2016-05-03 08:10:06,958 Node[0] Epoch[3] Batch [350] Speed: 614.73 samples/sec Train-accuracy=0.594063
2016-05-03 08:10:15,481 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 08:10:15,481 Node[0] Epoch[3] Time cost=81.576
2016-05-03 08:10:15,645 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 08:10:17,641 Node[0] Epoch[3] Validation-accuracy=0.573017
2016-05-03 08:10:28,169 Node[0] Epoch[4] Batch [50] Speed: 611.16 samples/sec Train-accuracy=0.604531
2016-05-03 08:10:38,636 Node[0] Epoch[4] Batch [100] Speed: 611.50 samples/sec Train-accuracy=0.622656
2016-05-03 08:10:49,065 Node[0] Epoch[4] Batch [150] Speed: 613.69 samples/sec Train-accuracy=0.626094
2016-05-03 08:10:59,519 Node[0] Epoch[4] Batch [200] Speed: 612.20 samples/sec Train-accuracy=0.624844
2016-05-03 08:11:09,981 Node[0] Epoch[4] Batch [250] Speed: 611.78 samples/sec Train-accuracy=0.629687
2016-05-03 08:11:20,404 Node[0] Epoch[4] Batch [300] Speed: 614.01 samples/sec Train-accuracy=0.636875
2016-05-03 08:11:30,813 Node[0] Epoch[4] Batch [350] Speed: 614.89 samples/sec Train-accuracy=0.643281
2016-05-03 08:11:39,375 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 08:11:39,376 Node[0] Epoch[4] Time cost=81.734
2016-05-03 08:11:39,540 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 08:11:41,499 Node[0] Epoch[4] Validation-accuracy=0.612380
2016-05-03 08:11:51,981 Node[0] Epoch[5] Batch [50] Speed: 613.92 samples/sec Train-accuracy=0.636875
2016-05-03 08:12:02,420 Node[0] Epoch[5] Batch [100] Speed: 613.08 samples/sec Train-accuracy=0.657188
2016-05-03 08:12:12,873 Node[0] Epoch[5] Batch [150] Speed: 612.30 samples/sec Train-accuracy=0.671250
2016-05-03 08:12:23,323 Node[0] Epoch[5] Batch [200] Speed: 612.43 samples/sec Train-accuracy=0.659687
2016-05-03 08:12:33,781 Node[0] Epoch[5] Batch [250] Speed: 611.99 samples/sec Train-accuracy=0.667656
2016-05-03 08:12:44,239 Node[0] Epoch[5] Batch [300] Speed: 612.01 samples/sec Train-accuracy=0.669531
2016-05-03 08:12:54,714 Node[0] Epoch[5] Batch [350] Speed: 611.00 samples/sec Train-accuracy=0.679063
2016-05-03 08:13:03,033 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 08:13:03,033 Node[0] Epoch[5] Time cost=81.534
2016-05-03 08:13:03,197 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 08:13:05,125 Node[0] Epoch[5] Validation-accuracy=0.660958
2016-05-03 08:13:15,665 Node[0] Epoch[6] Batch [50] Speed: 610.43 samples/sec Train-accuracy=0.683125
2016-05-03 08:13:26,105 Node[0] Epoch[6] Batch [100] Speed: 613.06 samples/sec Train-accuracy=0.682813
2016-05-03 08:13:36,545 Node[0] Epoch[6] Batch [150] Speed: 613.03 samples/sec Train-accuracy=0.700156
2016-05-03 08:13:46,978 Node[0] Epoch[6] Batch [200] Speed: 613.46 samples/sec Train-accuracy=0.694375
2016-05-03 08:13:57,500 Node[0] Epoch[6] Batch [250] Speed: 608.27 samples/sec Train-accuracy=0.697500
2016-05-03 08:14:07,959 Node[0] Epoch[6] Batch [300] Speed: 611.88 samples/sec Train-accuracy=0.701875
2016-05-03 08:14:18,437 Node[0] Epoch[6] Batch [350] Speed: 610.84 samples/sec Train-accuracy=0.715469
2016-05-03 08:14:27,022 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 08:14:27,022 Node[0] Epoch[6] Time cost=81.896
2016-05-03 08:14:27,185 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 08:14:29,145 Node[0] Epoch[6] Validation-accuracy=0.705529
2016-05-03 08:14:39,617 Node[0] Epoch[7] Batch [50] Speed: 614.37 samples/sec Train-accuracy=0.705781
2016-05-03 08:14:50,103 Node[0] Epoch[7] Batch [100] Speed: 610.38 samples/sec Train-accuracy=0.711250
2016-05-03 08:15:00,552 Node[0] Epoch[7] Batch [150] Speed: 612.49 samples/sec Train-accuracy=0.734062
2016-05-03 08:15:10,979 Node[0] Epoch[7] Batch [200] Speed: 613.83 samples/sec Train-accuracy=0.728281
2016-05-03 08:15:21,445 Node[0] Epoch[7] Batch [250] Speed: 611.49 samples/sec Train-accuracy=0.729531
2016-05-03 08:15:31,902 Node[0] Epoch[7] Batch [300] Speed: 612.03 samples/sec Train-accuracy=0.733125
2016-05-03 08:15:42,383 Node[0] Epoch[7] Batch [350] Speed: 610.69 samples/sec Train-accuracy=0.736094
2016-05-03 08:15:50,722 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 08:15:50,723 Node[0] Epoch[7] Time cost=81.578
2016-05-03 08:15:50,883 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 08:15:52,826 Node[0] Epoch[7] Validation-accuracy=0.728165
2016-05-03 08:16:03,344 Node[0] Epoch[8] Batch [50] Speed: 611.78 samples/sec Train-accuracy=0.732344
2016-05-03 08:16:13,827 Node[0] Epoch[8] Batch [100] Speed: 610.50 samples/sec Train-accuracy=0.741250
2016-05-03 08:16:24,278 Node[0] Epoch[8] Batch [150] Speed: 612.41 samples/sec Train-accuracy=0.757344
2016-05-03 08:16:34,724 Node[0] Epoch[8] Batch [200] Speed: 612.71 samples/sec Train-accuracy=0.749844
2016-05-03 08:16:45,175 Node[0] Epoch[8] Batch [250] Speed: 612.37 samples/sec Train-accuracy=0.745469
2016-05-03 08:16:55,652 Node[0] Epoch[8] Batch [300] Speed: 610.90 samples/sec Train-accuracy=0.749687
2016-05-03 08:17:06,104 Node[0] Epoch[8] Batch [350] Speed: 612.29 samples/sec Train-accuracy=0.752500
2016-05-03 08:17:14,725 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 08:17:14,726 Node[0] Epoch[8] Time cost=81.899
2016-05-03 08:17:14,891 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 08:17:17,042 Node[0] Epoch[8] Validation-accuracy=0.728936
2016-05-03 08:17:27,524 Node[0] Epoch[9] Batch [50] Speed: 613.85 samples/sec Train-accuracy=0.750313
2016-05-03 08:17:38,010 Node[0] Epoch[9] Batch [100] Speed: 610.34 samples/sec Train-accuracy=0.766094
2016-05-03 08:17:48,506 Node[0] Epoch[9] Batch [150] Speed: 609.77 samples/sec Train-accuracy=0.774375
2016-05-03 08:17:58,986 Node[0] Epoch[9] Batch [200] Speed: 610.69 samples/sec Train-accuracy=0.761875
2016-05-03 08:18:09,468 Node[0] Epoch[9] Batch [250] Speed: 610.61 samples/sec Train-accuracy=0.761875
2016-05-03 08:18:19,940 Node[0] Epoch[9] Batch [300] Speed: 611.15 samples/sec Train-accuracy=0.764219
2016-05-03 08:18:30,364 Node[0] Epoch[9] Batch [350] Speed: 613.97 samples/sec Train-accuracy=0.775625
2016-05-03 08:18:38,909 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 08:18:38,909 Node[0] Epoch[9] Time cost=81.868
2016-05-03 08:18:39,073 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 08:18:41,014 Node[0] Epoch[9] Validation-accuracy=0.748698
2016-05-03 08:18:51,568 Node[0] Epoch[10] Batch [50] Speed: 609.58 samples/sec Train-accuracy=0.769062
2016-05-03 08:19:02,020 Node[0] Epoch[10] Batch [100] Speed: 612.31 samples/sec Train-accuracy=0.778594
2016-05-03 08:19:12,367 Node[0] Epoch[10] Batch [150] Speed: 618.55 samples/sec Train-accuracy=0.786094
2016-05-03 08:19:22,752 Node[0] Epoch[10] Batch [200] Speed: 616.32 samples/sec Train-accuracy=0.781563
2016-05-03 08:19:33,202 Node[0] Epoch[10] Batch [250] Speed: 612.43 samples/sec Train-accuracy=0.776094
2016-05-03 08:19:43,651 Node[0] Epoch[10] Batch [300] Speed: 612.55 samples/sec Train-accuracy=0.784219
2016-05-03 08:19:54,094 Node[0] Epoch[10] Batch [350] Speed: 612.86 samples/sec Train-accuracy=0.782500
2016-05-03 08:20:02,416 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 08:20:02,416 Node[0] Epoch[10] Time cost=81.403
2016-05-03 08:20:02,578 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 08:20:04,548 Node[0] Epoch[10] Validation-accuracy=0.758313
2016-05-03 08:20:15,096 Node[0] Epoch[11] Batch [50] Speed: 609.90 samples/sec Train-accuracy=0.780625
2016-05-03 08:20:25,605 Node[0] Epoch[11] Batch [100] Speed: 609.05 samples/sec Train-accuracy=0.787656
2016-05-03 08:20:36,107 Node[0] Epoch[11] Batch [150] Speed: 609.40 samples/sec Train-accuracy=0.803281
2016-05-03 08:20:46,597 Node[0] Epoch[11] Batch [200] Speed: 610.15 samples/sec Train-accuracy=0.789844
2016-05-03 08:20:57,088 Node[0] Epoch[11] Batch [250] Speed: 610.06 samples/sec Train-accuracy=0.790156
2016-05-03 08:21:07,538 Node[0] Epoch[11] Batch [300] Speed: 612.47 samples/sec Train-accuracy=0.798438
2016-05-03 08:21:17,996 Node[0] Epoch[11] Batch [350] Speed: 611.98 samples/sec Train-accuracy=0.803438
2016-05-03 08:21:26,590 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 08:21:26,591 Node[0] Epoch[11] Time cost=82.043
2016-05-03 08:21:26,757 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 08:21:28,707 Node[0] Epoch[11] Validation-accuracy=0.778746
2016-05-03 08:21:39,238 Node[0] Epoch[12] Batch [50] Speed: 610.97 samples/sec Train-accuracy=0.805156
2016-05-03 08:21:49,670 Node[0] Epoch[12] Batch [100] Speed: 613.51 samples/sec Train-accuracy=0.807969
2016-05-03 08:22:00,118 Node[0] Epoch[12] Batch [150] Speed: 612.57 samples/sec Train-accuracy=0.811719
2016-05-03 08:22:10,583 Node[0] Epoch[12] Batch [200] Speed: 611.55 samples/sec Train-accuracy=0.807500
2016-05-03 08:22:21,031 Node[0] Epoch[12] Batch [250] Speed: 612.57 samples/sec Train-accuracy=0.795625
2016-05-03 08:22:31,462 Node[0] Epoch[12] Batch [300] Speed: 613.62 samples/sec Train-accuracy=0.806562
2016-05-03 08:22:41,938 Node[0] Epoch[12] Batch [350] Speed: 610.92 samples/sec Train-accuracy=0.805156
2016-05-03 08:22:50,500 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 08:22:50,501 Node[0] Epoch[12] Time cost=81.794
2016-05-03 08:22:50,664 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 08:22:52,579 Node[0] Epoch[12] Validation-accuracy=0.770333
2016-05-03 08:23:03,160 Node[0] Epoch[13] Batch [50] Speed: 608.17 samples/sec Train-accuracy=0.807500
2016-05-03 08:23:13,598 Node[0] Epoch[13] Batch [100] Speed: 613.18 samples/sec Train-accuracy=0.819375
2016-05-03 08:23:24,091 Node[0] Epoch[13] Batch [150] Speed: 609.93 samples/sec Train-accuracy=0.821094
2016-05-03 08:23:34,545 Node[0] Epoch[13] Batch [200] Speed: 612.24 samples/sec Train-accuracy=0.809219
2016-05-03 08:23:44,998 Node[0] Epoch[13] Batch [250] Speed: 612.28 samples/sec Train-accuracy=0.814063
2016-05-03 08:23:55,463 Node[0] Epoch[13] Batch [300] Speed: 611.58 samples/sec Train-accuracy=0.815781
2016-05-03 08:24:05,903 Node[0] Epoch[13] Batch [350] Speed: 613.03 samples/sec Train-accuracy=0.820625
2016-05-03 08:24:14,256 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 08:24:14,257 Node[0] Epoch[13] Time cost=81.678
2016-05-03 08:24:14,425 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 08:24:16,372 Node[0] Epoch[13] Validation-accuracy=0.793570
2016-05-03 08:24:26,979 Node[0] Epoch[14] Batch [50] Speed: 606.52 samples/sec Train-accuracy=0.812656
2016-05-03 08:24:37,492 Node[0] Epoch[14] Batch [100] Speed: 608.82 samples/sec Train-accuracy=0.823906
2016-05-03 08:24:47,928 Node[0] Epoch[14] Batch [150] Speed: 613.27 samples/sec Train-accuracy=0.829375
2016-05-03 08:24:58,406 Node[0] Epoch[14] Batch [200] Speed: 610.82 samples/sec Train-accuracy=0.818438
2016-05-03 08:25:08,866 Node[0] Epoch[14] Batch [250] Speed: 611.88 samples/sec Train-accuracy=0.817187
2016-05-03 08:25:19,295 Node[0] Epoch[14] Batch [300] Speed: 613.68 samples/sec Train-accuracy=0.821875
2016-05-03 08:25:29,780 Node[0] Epoch[14] Batch [350] Speed: 610.39 samples/sec Train-accuracy=0.827969
2016-05-03 08:25:38,353 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 08:25:38,353 Node[0] Epoch[14] Time cost=81.981
2016-05-03 08:25:38,516 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 08:25:40,434 Node[0] Epoch[14] Validation-accuracy=0.795373
2016-05-03 08:25:51,040 Node[0] Epoch[15] Batch [50] Speed: 606.66 samples/sec Train-accuracy=0.834219
2016-05-03 08:26:01,566 Node[0] Epoch[15] Batch [100] Speed: 608.03 samples/sec Train-accuracy=0.832812
2016-05-03 08:26:12,055 Node[0] Epoch[15] Batch [150] Speed: 610.22 samples/sec Train-accuracy=0.834531
2016-05-03 08:26:22,507 Node[0] Epoch[15] Batch [200] Speed: 612.35 samples/sec Train-accuracy=0.826875
2016-05-03 08:26:32,987 Node[0] Epoch[15] Batch [250] Speed: 610.71 samples/sec Train-accuracy=0.829375
2016-05-03 08:26:43,454 Node[0] Epoch[15] Batch [300] Speed: 611.41 samples/sec Train-accuracy=0.836562
2016-05-03 08:26:53,897 Node[0] Epoch[15] Batch [350] Speed: 612.86 samples/sec Train-accuracy=0.838281
2016-05-03 08:27:02,251 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 08:27:02,252 Node[0] Epoch[15] Time cost=81.818
2016-05-03 08:27:02,416 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 08:27:04,364 Node[0] Epoch[15] Validation-accuracy=0.792568
2016-05-03 08:27:15,022 Node[0] Epoch[16] Batch [50] Speed: 603.65 samples/sec Train-accuracy=0.836094
2016-05-03 08:27:25,489 Node[0] Epoch[16] Batch [100] Speed: 611.47 samples/sec Train-accuracy=0.836562
2016-05-03 08:27:35,920 Node[0] Epoch[16] Batch [150] Speed: 613.56 samples/sec Train-accuracy=0.846562
2016-05-03 08:27:46,346 Node[0] Epoch[16] Batch [200] Speed: 613.84 samples/sec Train-accuracy=0.832187
2016-05-03 08:27:56,758 Node[0] Epoch[16] Batch [250] Speed: 614.74 samples/sec Train-accuracy=0.831406
2016-05-03 08:28:07,192 Node[0] Epoch[16] Batch [300] Speed: 613.39 samples/sec Train-accuracy=0.843594
2016-05-03 08:28:17,650 Node[0] Epoch[16] Batch [350] Speed: 611.95 samples/sec Train-accuracy=0.839688
2016-05-03 08:28:26,311 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 08:28:26,311 Node[0] Epoch[16] Time cost=81.947
2016-05-03 08:28:26,477 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 08:28:28,656 Node[0] Epoch[16] Validation-accuracy=0.807358
2016-05-03 08:28:39,216 Node[0] Epoch[17] Batch [50] Speed: 609.22 samples/sec Train-accuracy=0.840469
2016-05-03 08:28:49,755 Node[0] Epoch[17] Batch [100] Speed: 607.32 samples/sec Train-accuracy=0.843750
2016-05-03 08:29:00,188 Node[0] Epoch[17] Batch [150] Speed: 613.45 samples/sec Train-accuracy=0.853437
2016-05-03 08:29:10,640 Node[0] Epoch[17] Batch [200] Speed: 612.33 samples/sec Train-accuracy=0.845000
2016-05-03 08:29:21,081 Node[0] Epoch[17] Batch [250] Speed: 612.96 samples/sec Train-accuracy=0.843906
2016-05-03 08:29:31,500 Node[0] Epoch[17] Batch [300] Speed: 614.30 samples/sec Train-accuracy=0.844688
2016-05-03 08:29:42,007 Node[0] Epoch[17] Batch [350] Speed: 609.14 samples/sec Train-accuracy=0.847969
2016-05-03 08:29:50,639 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 08:29:50,640 Node[0] Epoch[17] Time cost=81.983
2016-05-03 08:29:50,804 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 08:29:52,727 Node[0] Epoch[17] Validation-accuracy=0.812400
2016-05-03 08:30:03,285 Node[0] Epoch[18] Batch [50] Speed: 609.33 samples/sec Train-accuracy=0.847187
2016-05-03 08:30:13,779 Node[0] Epoch[18] Batch [100] Speed: 609.92 samples/sec Train-accuracy=0.849375
2016-05-03 08:30:24,255 Node[0] Epoch[18] Batch [150] Speed: 610.93 samples/sec Train-accuracy=0.855781
2016-05-03 08:30:34,738 Node[0] Epoch[18] Batch [200] Speed: 610.53 samples/sec Train-accuracy=0.843750
2016-05-03 08:30:45,201 Node[0] Epoch[18] Batch [250] Speed: 611.69 samples/sec Train-accuracy=0.843750
2016-05-03 08:30:55,692 Node[0] Epoch[18] Batch [300] Speed: 610.06 samples/sec Train-accuracy=0.851875
2016-05-03 08:31:06,115 Node[0] Epoch[18] Batch [350] Speed: 614.06 samples/sec Train-accuracy=0.857969
2016-05-03 08:31:14,474 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 08:31:14,474 Node[0] Epoch[18] Time cost=81.747
2016-05-03 08:31:14,637 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 08:31:16,585 Node[0] Epoch[18] Validation-accuracy=0.813201
2016-05-03 08:31:27,168 Node[0] Epoch[19] Batch [50] Speed: 607.97 samples/sec Train-accuracy=0.844219
2016-05-03 08:31:37,696 Node[0] Epoch[19] Batch [100] Speed: 607.94 samples/sec Train-accuracy=0.855000
2016-05-03 08:31:48,154 Node[0] Epoch[19] Batch [150] Speed: 611.98 samples/sec Train-accuracy=0.860781
2016-05-03 08:31:58,614 Node[0] Epoch[19] Batch [200] Speed: 611.86 samples/sec Train-accuracy=0.855938
2016-05-03 08:32:09,071 Node[0] Epoch[19] Batch [250] Speed: 612.05 samples/sec Train-accuracy=0.855313
2016-05-03 08:32:19,554 Node[0] Epoch[19] Batch [300] Speed: 610.53 samples/sec Train-accuracy=0.859219
2016-05-03 08:32:29,967 Node[0] Epoch[19] Batch [350] Speed: 614.63 samples/sec Train-accuracy=0.857812
2016-05-03 08:32:38,574 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 08:32:38,575 Node[0] Epoch[19] Time cost=81.989
2016-05-03 08:32:38,739 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 08:32:40,688 Node[0] Epoch[19] Validation-accuracy=0.802183
2016-05-03 08:32:51,349 Node[0] Epoch[20] Batch [50] Speed: 603.50 samples/sec Train-accuracy=0.857656
2016-05-03 08:33:01,808 Node[0] Epoch[20] Batch [100] Speed: 611.97 samples/sec Train-accuracy=0.859844
2016-05-03 08:33:12,245 Node[0] Epoch[20] Batch [150] Speed: 613.23 samples/sec Train-accuracy=0.865313
2016-05-03 08:33:22,693 Node[0] Epoch[20] Batch [200] Speed: 612.54 samples/sec Train-accuracy=0.859531
2016-05-03 08:33:33,089 Node[0] Epoch[20] Batch [250] Speed: 615.66 samples/sec Train-accuracy=0.861875
2016-05-03 08:33:43,637 Node[0] Epoch[20] Batch [300] Speed: 606.76 samples/sec Train-accuracy=0.862812
2016-05-03 08:33:54,178 Node[0] Epoch[20] Batch [350] Speed: 607.18 samples/sec Train-accuracy=0.864531
2016-05-03 08:34:02,833 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 08:34:02,834 Node[0] Epoch[20] Time cost=82.145
2016-05-03 08:34:03,000 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 08:34:04,952 Node[0] Epoch[20] Validation-accuracy=0.820613
2016-05-03 08:34:15,414 Node[0] Epoch[21] Batch [50] Speed: 614.88 samples/sec Train-accuracy=0.859219
2016-05-03 08:34:25,926 Node[0] Epoch[21] Batch [100] Speed: 608.81 samples/sec Train-accuracy=0.858750
2016-05-03 08:34:36,376 Node[0] Epoch[21] Batch [150] Speed: 612.48 samples/sec Train-accuracy=0.867500
2016-05-03 08:34:46,816 Node[0] Epoch[21] Batch [200] Speed: 613.05 samples/sec Train-accuracy=0.866250
2016-05-03 08:34:57,261 Node[0] Epoch[21] Batch [250] Speed: 612.74 samples/sec Train-accuracy=0.871719
2016-05-03 08:35:07,816 Node[0] Epoch[21] Batch [300] Speed: 606.36 samples/sec Train-accuracy=0.865938
2016-05-03 08:35:18,382 Node[0] Epoch[21] Batch [350] Speed: 605.71 samples/sec Train-accuracy=0.862500
2016-05-03 08:35:26,804 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 08:35:26,804 Node[0] Epoch[21] Time cost=81.853
2016-05-03 08:35:26,968 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 08:35:28,906 Node[0] Epoch[21] Validation-accuracy=0.822216
2016-05-03 08:35:39,456 Node[0] Epoch[22] Batch [50] Speed: 609.82 samples/sec Train-accuracy=0.860000
2016-05-03 08:35:49,857 Node[0] Epoch[22] Batch [100] Speed: 615.32 samples/sec Train-accuracy=0.871875
2016-05-03 08:36:00,315 Node[0] Epoch[22] Batch [150] Speed: 612.01 samples/sec Train-accuracy=0.868750
2016-05-03 08:36:10,895 Node[0] Epoch[22] Batch [200] Speed: 604.95 samples/sec Train-accuracy=0.867969
2016-05-03 08:36:21,467 Node[0] Epoch[22] Batch [250] Speed: 605.39 samples/sec Train-accuracy=0.867344
2016-05-03 08:36:32,029 Node[0] Epoch[22] Batch [300] Speed: 605.96 samples/sec Train-accuracy=0.871406
2016-05-03 08:36:42,572 Node[0] Epoch[22] Batch [350] Speed: 607.06 samples/sec Train-accuracy=0.871406
2016-05-03 08:36:51,224 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 08:36:51,224 Node[0] Epoch[22] Time cost=82.318
2016-05-03 08:36:51,393 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 08:36:53,305 Node[0] Epoch[22] Validation-accuracy=0.807692
2016-05-03 08:37:03,830 Node[0] Epoch[23] Batch [50] Speed: 611.29 samples/sec Train-accuracy=0.872344
2016-05-03 08:37:14,328 Node[0] Epoch[23] Batch [100] Speed: 609.64 samples/sec Train-accuracy=0.877812
2016-05-03 08:37:24,773 Node[0] Epoch[23] Batch [150] Speed: 612.74 samples/sec Train-accuracy=0.877812
2016-05-03 08:37:35,197 Node[0] Epoch[23] Batch [200] Speed: 613.98 samples/sec Train-accuracy=0.876094
2016-05-03 08:37:45,694 Node[0] Epoch[23] Batch [250] Speed: 609.74 samples/sec Train-accuracy=0.869687
2016-05-03 08:37:56,250 Node[0] Epoch[23] Batch [300] Speed: 606.30 samples/sec Train-accuracy=0.875313
2016-05-03 08:38:06,812 Node[0] Epoch[23] Batch [350] Speed: 605.96 samples/sec Train-accuracy=0.877500
2016-05-03 08:38:15,212 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 08:38:15,212 Node[0] Epoch[23] Time cost=81.906
2016-05-03 08:38:15,377 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 08:38:17,310 Node[0] Epoch[23] Validation-accuracy=0.829828
2016-05-03 08:38:27,886 Node[0] Epoch[24] Batch [50] Speed: 608.30 samples/sec Train-accuracy=0.872188
2016-05-03 08:38:38,421 Node[0] Epoch[24] Batch [100] Speed: 607.55 samples/sec Train-accuracy=0.876563
2016-05-03 08:38:48,911 Node[0] Epoch[24] Batch [150] Speed: 610.08 samples/sec Train-accuracy=0.878750
2016-05-03 08:38:59,386 Node[0] Epoch[24] Batch [200] Speed: 611.02 samples/sec Train-accuracy=0.878906
2016-05-03 08:39:09,921 Node[0] Epoch[24] Batch [250] Speed: 607.51 samples/sec Train-accuracy=0.870938
2016-05-03 08:39:20,477 Node[0] Epoch[24] Batch [300] Speed: 606.30 samples/sec Train-accuracy=0.882500
2016-05-03 08:39:31,014 Node[0] Epoch[24] Batch [350] Speed: 607.43 samples/sec Train-accuracy=0.875938
2016-05-03 08:39:39,664 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 08:39:39,664 Node[0] Epoch[24] Time cost=82.354
2016-05-03 08:39:39,833 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 08:39:41,956 Node[0] Epoch[24] Validation-accuracy=0.827037
2016-05-03 08:39:52,509 Node[0] Epoch[25] Batch [50] Speed: 609.58 samples/sec Train-accuracy=0.877969
2016-05-03 08:40:03,044 Node[0] Epoch[25] Batch [100] Speed: 607.53 samples/sec Train-accuracy=0.879375
2016-05-03 08:40:13,553 Node[0] Epoch[25] Batch [150] Speed: 609.03 samples/sec Train-accuracy=0.874219
2016-05-03 08:40:24,057 Node[0] Epoch[25] Batch [200] Speed: 609.29 samples/sec Train-accuracy=0.873906
2016-05-03 08:40:34,592 Node[0] Epoch[25] Batch [250] Speed: 607.48 samples/sec Train-accuracy=0.876250
2016-05-03 08:40:45,155 Node[0] Epoch[25] Batch [300] Speed: 605.94 samples/sec Train-accuracy=0.880625
2016-05-03 08:40:55,713 Node[0] Epoch[25] Batch [350] Speed: 606.17 samples/sec Train-accuracy=0.882656
2016-05-03 08:41:04,326 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 08:41:04,326 Node[0] Epoch[25] Time cost=82.370
2016-05-03 08:41:04,496 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 08:41:06,470 Node[0] Epoch[25] Validation-accuracy=0.827123
2016-05-03 08:41:17,028 Node[0] Epoch[26] Batch [50] Speed: 609.34 samples/sec Train-accuracy=0.875781
2016-05-03 08:41:27,586 Node[0] Epoch[26] Batch [100] Speed: 606.23 samples/sec Train-accuracy=0.881406
2016-05-03 08:41:38,096 Node[0] Epoch[26] Batch [150] Speed: 608.97 samples/sec Train-accuracy=0.885625
2016-05-03 08:41:48,516 Node[0] Epoch[26] Batch [200] Speed: 614.21 samples/sec Train-accuracy=0.880469
2016-05-03 08:41:59,005 Node[0] Epoch[26] Batch [250] Speed: 610.16 samples/sec Train-accuracy=0.877969
2016-05-03 08:42:09,553 Node[0] Epoch[26] Batch [300] Speed: 606.76 samples/sec Train-accuracy=0.890312
2016-05-03 08:42:20,124 Node[0] Epoch[26] Batch [350] Speed: 605.47 samples/sec Train-accuracy=0.889062
2016-05-03 08:42:28,551 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 08:42:28,551 Node[0] Epoch[26] Time cost=82.081
2016-05-03 08:42:28,721 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 08:42:30,665 Node[0] Epoch[26] Validation-accuracy=0.837941
2016-05-03 08:42:41,276 Node[0] Epoch[27] Batch [50] Speed: 606.33 samples/sec Train-accuracy=0.875625
2016-05-03 08:42:51,868 Node[0] Epoch[27] Batch [100] Speed: 604.26 samples/sec Train-accuracy=0.883125
2016-05-03 08:43:02,434 Node[0] Epoch[27] Batch [150] Speed: 605.72 samples/sec Train-accuracy=0.888594
2016-05-03 08:43:12,980 Node[0] Epoch[27] Batch [200] Speed: 606.86 samples/sec Train-accuracy=0.886719
2016-05-03 08:43:23,547 Node[0] Epoch[27] Batch [250] Speed: 605.71 samples/sec Train-accuracy=0.886406
2016-05-03 08:43:34,094 Node[0] Epoch[27] Batch [300] Speed: 606.83 samples/sec Train-accuracy=0.889219
2016-05-03 08:43:44,657 Node[0] Epoch[27] Batch [350] Speed: 605.91 samples/sec Train-accuracy=0.887344
2016-05-03 08:43:53,304 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 08:43:53,304 Node[0] Epoch[27] Time cost=82.639
2016-05-03 08:43:53,472 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 08:43:55,425 Node[0] Epoch[27] Validation-accuracy=0.822817
2016-05-03 08:44:05,964 Node[0] Epoch[28] Batch [50] Speed: 610.45 samples/sec Train-accuracy=0.888594
2016-05-03 08:44:16,475 Node[0] Epoch[28] Batch [100] Speed: 608.91 samples/sec Train-accuracy=0.891719
2016-05-03 08:44:27,013 Node[0] Epoch[28] Batch [150] Speed: 607.33 samples/sec Train-accuracy=0.895000
2016-05-03 08:44:37,608 Node[0] Epoch[28] Batch [200] Speed: 604.08 samples/sec Train-accuracy=0.879531
2016-05-03 08:44:48,194 Node[0] Epoch[28] Batch [250] Speed: 604.60 samples/sec Train-accuracy=0.889062
2016-05-03 08:44:58,757 Node[0] Epoch[28] Batch [300] Speed: 605.90 samples/sec Train-accuracy=0.898594
2016-05-03 08:45:09,291 Node[0] Epoch[28] Batch [350] Speed: 607.56 samples/sec Train-accuracy=0.890156
2016-05-03 08:45:17,913 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 08:45:17,913 Node[0] Epoch[28] Time cost=82.488
2016-05-03 08:45:18,082 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 08:45:20,036 Node[0] Epoch[28] Validation-accuracy=0.841446
2016-05-03 08:45:30,595 Node[0] Epoch[29] Batch [50] Speed: 609.44 samples/sec Train-accuracy=0.891875
2016-05-03 08:45:41,152 Node[0] Epoch[29] Batch [100] Speed: 606.23 samples/sec Train-accuracy=0.896250
2016-05-03 08:45:51,703 Node[0] Epoch[29] Batch [150] Speed: 606.64 samples/sec Train-accuracy=0.887969
2016-05-03 08:46:02,224 Node[0] Epoch[29] Batch [200] Speed: 608.33 samples/sec Train-accuracy=0.890938
2016-05-03 08:46:12,722 Node[0] Epoch[29] Batch [250] Speed: 609.65 samples/sec Train-accuracy=0.891094
2016-05-03 08:46:23,259 Node[0] Epoch[29] Batch [300] Speed: 607.39 samples/sec Train-accuracy=0.896719
2016-05-03 08:46:33,796 Node[0] Epoch[29] Batch [350] Speed: 607.41 samples/sec Train-accuracy=0.895000
2016-05-03 08:46:42,204 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 08:46:42,204 Node[0] Epoch[29] Time cost=82.168
2016-05-03 08:46:42,368 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 08:46:44,328 Node[0] Epoch[29] Validation-accuracy=0.808994
2016-05-03 08:46:54,914 Node[0] Epoch[30] Batch [50] Speed: 607.78 samples/sec Train-accuracy=0.887031
2016-05-03 08:47:05,479 Node[0] Epoch[30] Batch [100] Speed: 605.79 samples/sec Train-accuracy=0.892188
2016-05-03 08:47:16,040 Node[0] Epoch[30] Batch [150] Speed: 606.06 samples/sec Train-accuracy=0.894062
2016-05-03 08:47:26,572 Node[0] Epoch[30] Batch [200] Speed: 607.69 samples/sec Train-accuracy=0.892500
2016-05-03 08:47:37,159 Node[0] Epoch[30] Batch [250] Speed: 604.52 samples/sec Train-accuracy=0.893437
2016-05-03 08:47:47,690 Node[0] Epoch[30] Batch [300] Speed: 607.76 samples/sec Train-accuracy=0.898750
2016-05-03 08:47:58,208 Node[0] Epoch[30] Batch [350] Speed: 608.47 samples/sec Train-accuracy=0.895312
2016-05-03 08:48:06,881 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 08:48:06,882 Node[0] Epoch[30] Time cost=82.553
2016-05-03 08:48:07,052 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 08:48:08,975 Node[0] Epoch[30] Validation-accuracy=0.835437
2016-05-03 08:48:19,584 Node[0] Epoch[31] Batch [50] Speed: 606.46 samples/sec Train-accuracy=0.891875
2016-05-03 08:48:30,118 Node[0] Epoch[31] Batch [100] Speed: 607.59 samples/sec Train-accuracy=0.904062
2016-05-03 08:48:40,600 Node[0] Epoch[31] Batch [150] Speed: 610.59 samples/sec Train-accuracy=0.900937
2016-05-03 08:48:51,041 Node[0] Epoch[31] Batch [200] Speed: 612.95 samples/sec Train-accuracy=0.893281
2016-05-03 08:49:01,496 Node[0] Epoch[31] Batch [250] Speed: 612.21 samples/sec Train-accuracy=0.892969
2016-05-03 08:49:12,062 Node[0] Epoch[31] Batch [300] Speed: 605.69 samples/sec Train-accuracy=0.905781
2016-05-03 08:49:22,607 Node[0] Epoch[31] Batch [350] Speed: 606.93 samples/sec Train-accuracy=0.899687
2016-05-03 08:49:31,034 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 08:49:31,034 Node[0] Epoch[31] Time cost=82.059
2016-05-03 08:49:31,195 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 08:49:33,155 Node[0] Epoch[31] Validation-accuracy=0.826422
2016-05-03 08:49:43,758 Node[0] Epoch[32] Batch [50] Speed: 606.78 samples/sec Train-accuracy=0.895312
2016-05-03 08:49:54,321 Node[0] Epoch[32] Batch [100] Speed: 605.88 samples/sec Train-accuracy=0.897813
2016-05-03 08:50:04,861 Node[0] Epoch[32] Batch [150] Speed: 607.27 samples/sec Train-accuracy=0.905156
2016-05-03 08:50:15,346 Node[0] Epoch[32] Batch [200] Speed: 610.40 samples/sec Train-accuracy=0.895312
2016-05-03 08:50:25,805 Node[0] Epoch[32] Batch [250] Speed: 611.93 samples/sec Train-accuracy=0.890625
2016-05-03 08:50:36,332 Node[0] Epoch[32] Batch [300] Speed: 607.94 samples/sec Train-accuracy=0.903906
2016-05-03 08:50:46,892 Node[0] Epoch[32] Batch [350] Speed: 606.11 samples/sec Train-accuracy=0.907344
2016-05-03 08:50:55,574 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 08:50:55,574 Node[0] Epoch[32] Time cost=82.419
2016-05-03 08:50:55,738 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 08:50:57,877 Node[0] Epoch[32] Validation-accuracy=0.825356
2016-05-03 08:51:08,452 Node[0] Epoch[33] Batch [50] Speed: 608.37 samples/sec Train-accuracy=0.895938
2016-05-03 08:51:18,999 Node[0] Epoch[33] Batch [100] Speed: 606.82 samples/sec Train-accuracy=0.898750
2016-05-03 08:51:29,542 Node[0] Epoch[33] Batch [150] Speed: 607.00 samples/sec Train-accuracy=0.898906
2016-05-03 08:51:40,064 Node[0] Epoch[33] Batch [200] Speed: 608.27 samples/sec Train-accuracy=0.899844
2016-05-03 08:51:50,602 Node[0] Epoch[33] Batch [250] Speed: 607.35 samples/sec Train-accuracy=0.897031
2016-05-03 08:52:01,145 Node[0] Epoch[33] Batch [300] Speed: 607.07 samples/sec Train-accuracy=0.903750
2016-05-03 08:52:11,649 Node[0] Epoch[33] Batch [350] Speed: 609.32 samples/sec Train-accuracy=0.900781
2016-05-03 08:52:20,284 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 08:52:20,284 Node[0] Epoch[33] Time cost=82.407
2016-05-03 08:52:20,451 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 08:52:22,373 Node[0] Epoch[33] Validation-accuracy=0.843450
2016-05-03 08:52:32,959 Node[0] Epoch[34] Batch [50] Speed: 607.72 samples/sec Train-accuracy=0.894844
2016-05-03 08:52:43,540 Node[0] Epoch[34] Batch [100] Speed: 604.89 samples/sec Train-accuracy=0.901875
2016-05-03 08:52:54,078 Node[0] Epoch[34] Batch [150] Speed: 607.30 samples/sec Train-accuracy=0.896406
2016-05-03 08:53:04,651 Node[0] Epoch[34] Batch [200] Speed: 605.37 samples/sec Train-accuracy=0.905625
2016-05-03 08:53:15,223 Node[0] Epoch[34] Batch [250] Speed: 605.35 samples/sec Train-accuracy=0.905469
2016-05-03 08:53:25,785 Node[0] Epoch[34] Batch [300] Speed: 605.98 samples/sec Train-accuracy=0.903906
2016-05-03 08:53:36,303 Node[0] Epoch[34] Batch [350] Speed: 608.52 samples/sec Train-accuracy=0.902500
2016-05-03 08:53:44,732 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 08:53:44,732 Node[0] Epoch[34] Time cost=82.360
2016-05-03 08:53:44,898 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 08:53:46,861 Node[0] Epoch[34] Validation-accuracy=0.833333
2016-05-03 08:53:57,467 Node[0] Epoch[35] Batch [50] Speed: 606.66 samples/sec Train-accuracy=0.901250
2016-05-03 08:54:08,021 Node[0] Epoch[35] Batch [100] Speed: 606.40 samples/sec Train-accuracy=0.901875
2016-05-03 08:54:18,560 Node[0] Epoch[35] Batch [150] Speed: 607.26 samples/sec Train-accuracy=0.909531
2016-05-03 08:54:29,146 Node[0] Epoch[35] Batch [200] Speed: 604.62 samples/sec Train-accuracy=0.898125
2016-05-03 08:54:39,693 Node[0] Epoch[35] Batch [250] Speed: 606.83 samples/sec Train-accuracy=0.906719
2016-05-03 08:54:50,260 Node[0] Epoch[35] Batch [300] Speed: 605.62 samples/sec Train-accuracy=0.909062
2016-05-03 08:55:00,821 Node[0] Epoch[35] Batch [350] Speed: 606.05 samples/sec Train-accuracy=0.905469
2016-05-03 08:55:09,474 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 08:55:09,474 Node[0] Epoch[35] Time cost=82.613
2016-05-03 08:55:09,641 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 08:55:11,595 Node[0] Epoch[35] Validation-accuracy=0.847957
2016-05-03 08:55:22,191 Node[0] Epoch[36] Batch [50] Speed: 607.18 samples/sec Train-accuracy=0.905781
2016-05-03 08:55:32,781 Node[0] Epoch[36] Batch [100] Speed: 604.37 samples/sec Train-accuracy=0.904531
2016-05-03 08:55:43,316 Node[0] Epoch[36] Batch [150] Speed: 607.51 samples/sec Train-accuracy=0.901094
2016-05-03 08:55:53,908 Node[0] Epoch[36] Batch [200] Speed: 604.22 samples/sec Train-accuracy=0.903750
2016-05-03 08:56:04,441 Node[0] Epoch[36] Batch [250] Speed: 607.65 samples/sec Train-accuracy=0.909219
2016-05-03 08:56:15,018 Node[0] Epoch[36] Batch [300] Speed: 605.07 samples/sec Train-accuracy=0.910469
2016-05-03 08:56:25,584 Node[0] Epoch[36] Batch [350] Speed: 605.78 samples/sec Train-accuracy=0.903594
2016-05-03 08:56:34,229 Node[0] Epoch[36] Resetting Data Iterator
2016-05-03 08:56:34,230 Node[0] Epoch[36] Time cost=82.635
2016-05-03 08:56:34,394 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-03 08:56:36,372 Node[0] Epoch[36] Validation-accuracy=0.835837
2016-05-03 08:56:46,913 Node[0] Epoch[37] Batch [50] Speed: 610.25 samples/sec Train-accuracy=0.907031
2016-05-03 08:56:57,495 Node[0] Epoch[37] Batch [100] Speed: 604.82 samples/sec Train-accuracy=0.907813
2016-05-03 08:57:08,042 Node[0] Epoch[37] Batch [150] Speed: 606.86 samples/sec Train-accuracy=0.907500
2016-05-03 08:57:18,608 Node[0] Epoch[37] Batch [200] Speed: 605.71 samples/sec Train-accuracy=0.905937
2016-05-03 08:57:29,192 Node[0] Epoch[37] Batch [250] Speed: 604.70 samples/sec Train-accuracy=0.908906
2016-05-03 08:57:39,744 Node[0] Epoch[37] Batch [300] Speed: 606.52 samples/sec Train-accuracy=0.912031
2016-05-03 08:57:50,278 Node[0] Epoch[37] Batch [350] Speed: 607.61 samples/sec Train-accuracy=0.909062
2016-05-03 08:57:58,692 Node[0] Epoch[37] Resetting Data Iterator
2016-05-03 08:57:58,693 Node[0] Epoch[37] Time cost=82.321
2016-05-03 08:57:58,858 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-03 08:58:00,820 Node[0] Epoch[37] Validation-accuracy=0.845954
2016-05-03 08:58:11,500 Node[0] Epoch[38] Batch [50] Speed: 602.37 samples/sec Train-accuracy=0.905781
2016-05-03 08:58:22,121 Node[0] Epoch[38] Batch [100] Speed: 602.58 samples/sec Train-accuracy=0.911406
2016-05-03 08:58:32,765 Node[0] Epoch[38] Batch [150] Speed: 601.33 samples/sec Train-accuracy=0.916094
2016-05-03 08:58:43,321 Node[0] Epoch[38] Batch [200] Speed: 606.31 samples/sec Train-accuracy=0.910000
2016-05-03 08:58:53,877 Node[0] Epoch[38] Batch [250] Speed: 606.29 samples/sec Train-accuracy=0.907656
2016-05-03 08:59:04,431 Node[0] Epoch[38] Batch [300] Speed: 606.44 samples/sec Train-accuracy=0.913594
2016-05-03 08:59:14,946 Node[0] Epoch[38] Batch [350] Speed: 608.62 samples/sec Train-accuracy=0.907656
2016-05-03 08:59:23,579 Node[0] Epoch[38] Resetting Data Iterator
2016-05-03 08:59:23,579 Node[0] Epoch[38] Time cost=82.760
2016-05-03 08:59:23,747 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-03 08:59:25,714 Node[0] Epoch[38] Validation-accuracy=0.822917
2016-05-03 08:59:36,355 Node[0] Epoch[39] Batch [50] Speed: 604.60 samples/sec Train-accuracy=0.914062
2016-05-03 08:59:46,895 Node[0] Epoch[39] Batch [100] Speed: 607.27 samples/sec Train-accuracy=0.915312
2016-05-03 08:59:57,368 Node[0] Epoch[39] Batch [150] Speed: 611.08 samples/sec Train-accuracy=0.911406
2016-05-03 09:00:07,951 Node[0] Epoch[39] Batch [200] Speed: 604.78 samples/sec Train-accuracy=0.910312
2016-05-03 09:00:18,461 Node[0] Epoch[39] Batch [250] Speed: 608.93 samples/sec Train-accuracy=0.901094
2016-05-03 09:00:29,035 Node[0] Epoch[39] Batch [300] Speed: 605.31 samples/sec Train-accuracy=0.913125
2016-05-03 09:00:39,583 Node[0] Epoch[39] Batch [350] Speed: 606.73 samples/sec Train-accuracy=0.917813
2016-05-03 09:00:47,987 Node[0] Epoch[39] Resetting Data Iterator
2016-05-03 09:00:47,988 Node[0] Epoch[39] Time cost=82.273
2016-05-03 09:00:48,149 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-03 09:00:50,089 Node[0] Epoch[39] Validation-accuracy=0.844551
2016-05-03 09:01:00,741 Node[0] Epoch[40] Batch [50] Speed: 604.08 samples/sec Train-accuracy=0.910312
2016-05-03 09:01:11,281 Node[0] Epoch[40] Batch [100] Speed: 607.19 samples/sec Train-accuracy=0.911563
2016-05-03 09:01:21,789 Node[0] Epoch[40] Batch [150] Speed: 609.12 samples/sec Train-accuracy=0.915000
2016-05-03 09:01:32,250 Node[0] Epoch[40] Batch [200] Speed: 611.80 samples/sec Train-accuracy=0.912813
2016-05-03 09:01:42,836 Node[0] Epoch[40] Batch [250] Speed: 604.58 samples/sec Train-accuracy=0.910000
2016-05-03 09:01:53,383 Node[0] Epoch[40] Batch [300] Speed: 606.83 samples/sec Train-accuracy=0.911719
2016-05-03 09:02:03,963 Node[0] Epoch[40] Batch [350] Speed: 604.89 samples/sec Train-accuracy=0.916094
2016-05-03 09:02:12,606 Node[0] Epoch[40] Resetting Data Iterator
2016-05-03 09:02:12,607 Node[0] Epoch[40] Time cost=82.517
2016-05-03 09:02:12,774 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-03 09:02:14,905 Node[0] Epoch[40] Validation-accuracy=0.844047
2016-05-03 09:02:25,374 Node[0] Epoch[41] Batch [50] Speed: 614.49 samples/sec Train-accuracy=0.915781
2016-05-03 09:02:35,883 Node[0] Epoch[41] Batch [100] Speed: 609.03 samples/sec Train-accuracy=0.912656
2016-05-03 09:02:46,404 Node[0] Epoch[41] Batch [150] Speed: 608.31 samples/sec Train-accuracy=0.916875
2016-05-03 09:02:56,954 Node[0] Epoch[41] Batch [200] Speed: 606.70 samples/sec Train-accuracy=0.910937
2016-05-03 09:03:07,518 Node[0] Epoch[41] Batch [250] Speed: 605.79 samples/sec Train-accuracy=0.911875
2016-05-03 09:03:18,107 Node[0] Epoch[41] Batch [300] Speed: 604.47 samples/sec Train-accuracy=0.914531
2016-05-03 09:03:28,607 Node[0] Epoch[41] Batch [350] Speed: 609.49 samples/sec Train-accuracy=0.916406
2016-05-03 09:03:37,180 Node[0] Epoch[41] Resetting Data Iterator
2016-05-03 09:03:37,180 Node[0] Epoch[41] Time cost=82.274
2016-05-03 09:03:37,339 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-03 09:03:39,329 Node[0] Epoch[41] Validation-accuracy=0.846655
2016-05-03 09:03:49,924 Node[0] Epoch[42] Batch [50] Speed: 607.30 samples/sec Train-accuracy=0.919375
2016-05-03 09:04:00,428 Node[0] Epoch[42] Batch [100] Speed: 609.27 samples/sec Train-accuracy=0.917188
2016-05-03 09:04:10,880 Node[0] Epoch[42] Batch [150] Speed: 612.35 samples/sec Train-accuracy=0.916719
2016-05-03 09:04:21,411 Node[0] Epoch[42] Batch [200] Speed: 607.72 samples/sec Train-accuracy=0.912500
2016-05-03 09:04:31,952 Node[0] Epoch[42] Batch [250] Speed: 607.20 samples/sec Train-accuracy=0.920469
2016-05-03 09:04:42,502 Node[0] Epoch[42] Batch [300] Speed: 606.62 samples/sec Train-accuracy=0.920312
2016-05-03 09:04:53,064 Node[0] Epoch[42] Batch [350] Speed: 605.99 samples/sec Train-accuracy=0.915625
2016-05-03 09:05:01,478 Node[0] Epoch[42] Resetting Data Iterator
2016-05-03 09:05:01,479 Node[0] Epoch[42] Time cost=82.149
2016-05-03 09:05:01,644 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-03 09:05:03,580 Node[0] Epoch[42] Validation-accuracy=0.854868
2016-05-03 09:05:14,103 Node[0] Epoch[43] Batch [50] Speed: 611.40 samples/sec Train-accuracy=0.918906
2016-05-03 09:05:24,643 Node[0] Epoch[43] Batch [100] Speed: 607.22 samples/sec Train-accuracy=0.912813
2016-05-03 09:05:35,068 Node[0] Epoch[43] Batch [150] Speed: 613.94 samples/sec Train-accuracy=0.917188
2016-05-03 09:05:45,500 Node[0] Epoch[43] Batch [200] Speed: 613.52 samples/sec Train-accuracy=0.921562
2016-05-03 09:05:56,056 Node[0] Epoch[43] Batch [250] Speed: 606.29 samples/sec Train-accuracy=0.920625
2016-05-03 09:06:06,605 Node[0] Epoch[43] Batch [300] Speed: 606.69 samples/sec Train-accuracy=0.917344
2016-05-03 09:06:17,143 Node[0] Epoch[43] Batch [350] Speed: 607.34 samples/sec Train-accuracy=0.921406
2016-05-03 09:06:25,753 Node[0] Epoch[43] Resetting Data Iterator
2016-05-03 09:06:25,754 Node[0] Epoch[43] Time cost=82.173
2016-05-03 09:06:25,918 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-03 09:06:27,854 Node[0] Epoch[43] Validation-accuracy=0.856971
2016-05-03 09:06:38,472 Node[0] Epoch[44] Batch [50] Speed: 605.99 samples/sec Train-accuracy=0.914531
2016-05-03 09:06:49,067 Node[0] Epoch[44] Batch [100] Speed: 604.05 samples/sec Train-accuracy=0.915312
2016-05-03 09:06:59,524 Node[0] Epoch[44] Batch [150] Speed: 612.03 samples/sec Train-accuracy=0.912813
2016-05-03 09:07:09,940 Node[0] Epoch[44] Batch [200] Speed: 614.48 samples/sec Train-accuracy=0.915625
2016-05-03 09:07:20,403 Node[0] Epoch[44] Batch [250] Speed: 611.69 samples/sec Train-accuracy=0.911406
2016-05-03 09:07:30,924 Node[0] Epoch[44] Batch [300] Speed: 608.36 samples/sec Train-accuracy=0.917188
2016-05-03 09:07:41,493 Node[0] Epoch[44] Batch [350] Speed: 605.55 samples/sec Train-accuracy=0.916094
2016-05-03 09:07:50,164 Node[0] Epoch[44] Resetting Data Iterator
2016-05-03 09:07:50,165 Node[0] Epoch[44] Time cost=82.311
2016-05-03 09:07:50,329 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-03 09:07:52,275 Node[0] Epoch[44] Validation-accuracy=0.856771
2016-05-03 09:08:02,762 Node[0] Epoch[45] Batch [50] Speed: 613.42 samples/sec Train-accuracy=0.923438
2016-05-03 09:08:13,308 Node[0] Epoch[45] Batch [100] Speed: 606.86 samples/sec Train-accuracy=0.917656
2016-05-03 09:08:23,817 Node[0] Epoch[45] Batch [150] Speed: 609.03 samples/sec Train-accuracy=0.920937
2016-05-03 09:08:34,242 Node[0] Epoch[45] Batch [200] Speed: 613.95 samples/sec Train-accuracy=0.918594
2016-05-03 09:08:44,679 Node[0] Epoch[45] Batch [250] Speed: 613.20 samples/sec Train-accuracy=0.924531
2016-05-03 09:08:55,184 Node[0] Epoch[45] Batch [300] Speed: 609.24 samples/sec Train-accuracy=0.925469
2016-05-03 09:09:05,713 Node[0] Epoch[45] Batch [350] Speed: 607.88 samples/sec Train-accuracy=0.910312
2016-05-03 09:09:14,125 Node[0] Epoch[45] Resetting Data Iterator
2016-05-03 09:09:14,126 Node[0] Epoch[45] Time cost=81.851
2016-05-03 09:09:14,295 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-03 09:09:16,264 Node[0] Epoch[45] Validation-accuracy=0.859675
2016-05-03 09:09:26,860 Node[0] Epoch[46] Batch [50] Speed: 607.35 samples/sec Train-accuracy=0.915781
2016-05-03 09:09:37,428 Node[0] Epoch[46] Batch [100] Speed: 605.59 samples/sec Train-accuracy=0.923594
2016-05-03 09:09:47,925 Node[0] Epoch[46] Batch [150] Speed: 609.70 samples/sec Train-accuracy=0.925625
2016-05-03 09:09:58,375 Node[0] Epoch[46] Batch [200] Speed: 612.50 samples/sec Train-accuracy=0.918906
2016-05-03 09:10:08,803 Node[0] Epoch[46] Batch [250] Speed: 613.72 samples/sec Train-accuracy=0.920000
2016-05-03 09:10:19,336 Node[0] Epoch[46] Batch [300] Speed: 607.64 samples/sec Train-accuracy=0.924375
2016-05-03 09:10:29,893 Node[0] Epoch[46] Batch [350] Speed: 606.23 samples/sec Train-accuracy=0.920937
2016-05-03 09:10:38,496 Node[0] Epoch[46] Resetting Data Iterator
2016-05-03 09:10:38,496 Node[0] Epoch[46] Time cost=82.232
2016-05-03 09:10:38,661 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-03 09:10:40,607 Node[0] Epoch[46] Validation-accuracy=0.869792
2016-05-03 09:10:51,155 Node[0] Epoch[47] Batch [50] Speed: 610.02 samples/sec Train-accuracy=0.924063
2016-05-03 09:11:01,767 Node[0] Epoch[47] Batch [100] Speed: 603.13 samples/sec Train-accuracy=0.921094
2016-05-03 09:11:12,203 Node[0] Epoch[47] Batch [150] Speed: 613.23 samples/sec Train-accuracy=0.920312
2016-05-03 09:11:22,657 Node[0] Epoch[47] Batch [200] Speed: 612.22 samples/sec Train-accuracy=0.912969
2016-05-03 09:11:33,132 Node[0] Epoch[47] Batch [250] Speed: 611.00 samples/sec Train-accuracy=0.916875
2016-05-03 09:11:43,711 Node[0] Epoch[47] Batch [300] Speed: 605.01 samples/sec Train-accuracy=0.924375
2016-05-03 09:11:54,268 Node[0] Epoch[47] Batch [350] Speed: 606.25 samples/sec Train-accuracy=0.927344
2016-05-03 09:12:02,661 Node[0] Epoch[47] Resetting Data Iterator
2016-05-03 09:12:02,661 Node[0] Epoch[47] Time cost=82.054
2016-05-03 09:12:02,825 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-03 09:12:04,747 Node[0] Epoch[47] Validation-accuracy=0.847356
2016-05-03 09:12:15,276 Node[0] Epoch[48] Batch [50] Speed: 611.04 samples/sec Train-accuracy=0.925156
2016-05-03 09:12:25,850 Node[0] Epoch[48] Batch [100] Speed: 605.27 samples/sec Train-accuracy=0.922656
2016-05-03 09:12:36,366 Node[0] Epoch[48] Batch [150] Speed: 608.65 samples/sec Train-accuracy=0.925312
2016-05-03 09:12:46,923 Node[0] Epoch[48] Batch [200] Speed: 606.21 samples/sec Train-accuracy=0.922188
2016-05-03 09:12:57,501 Node[0] Epoch[48] Batch [250] Speed: 605.08 samples/sec Train-accuracy=0.921250
2016-05-03 09:13:08,093 Node[0] Epoch[48] Batch [300] Speed: 604.21 samples/sec Train-accuracy=0.921719
2016-05-03 09:13:18,648 Node[0] Epoch[48] Batch [350] Speed: 606.36 samples/sec Train-accuracy=0.925625
2016-05-03 09:13:27,291 Node[0] Epoch[48] Resetting Data Iterator
2016-05-03 09:13:27,291 Node[0] Epoch[48] Time cost=82.544
2016-05-03 09:13:27,459 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-03 09:13:29,585 Node[0] Epoch[48] Validation-accuracy=0.833762
2016-05-03 09:13:40,082 Node[0] Epoch[49] Batch [50] Speed: 612.86 samples/sec Train-accuracy=0.921094
2016-05-03 09:13:50,677 Node[0] Epoch[49] Batch [100] Speed: 604.09 samples/sec Train-accuracy=0.921875
2016-05-03 09:14:01,246 Node[0] Epoch[49] Batch [150] Speed: 605.56 samples/sec Train-accuracy=0.924219
2016-05-03 09:14:11,822 Node[0] Epoch[49] Batch [200] Speed: 605.19 samples/sec Train-accuracy=0.917813
2016-05-03 09:14:22,354 Node[0] Epoch[49] Batch [250] Speed: 607.65 samples/sec Train-accuracy=0.918594
2016-05-03 09:14:32,890 Node[0] Epoch[49] Batch [300] Speed: 607.46 samples/sec Train-accuracy=0.922344
2016-05-03 09:14:43,424 Node[0] Epoch[49] Batch [350] Speed: 607.60 samples/sec Train-accuracy=0.922344
2016-05-03 09:14:52,067 Node[0] Epoch[49] Resetting Data Iterator
2016-05-03 09:14:52,067 Node[0] Epoch[49] Time cost=82.482
2016-05-03 09:14:52,231 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-03 09:14:54,200 Node[0] Epoch[49] Validation-accuracy=0.852063
2016-05-03 09:15:04,826 Node[0] Epoch[50] Batch [50] Speed: 605.40 samples/sec Train-accuracy=0.920937
2016-05-03 09:15:15,390 Node[0] Epoch[50] Batch [100] Speed: 605.86 samples/sec Train-accuracy=0.927500
2016-05-03 09:15:25,925 Node[0] Epoch[50] Batch [150] Speed: 607.49 samples/sec Train-accuracy=0.927656
2016-05-03 09:15:36,459 Node[0] Epoch[50] Batch [200] Speed: 607.54 samples/sec Train-accuracy=0.923281
2016-05-03 09:15:46,955 Node[0] Epoch[50] Batch [250] Speed: 609.79 samples/sec Train-accuracy=0.922031
2016-05-03 09:15:57,495 Node[0] Epoch[50] Batch [300] Speed: 607.22 samples/sec Train-accuracy=0.929531
2016-05-03 09:16:08,036 Node[0] Epoch[50] Batch [350] Speed: 607.20 samples/sec Train-accuracy=0.926562
2016-05-03 09:16:16,464 Node[0] Epoch[50] Resetting Data Iterator
2016-05-03 09:16:16,464 Node[0] Epoch[50] Time cost=82.264
2016-05-03 09:16:16,628 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-03 09:16:18,579 Node[0] Epoch[50] Validation-accuracy=0.846254
2016-05-03 09:16:29,151 Node[0] Epoch[51] Batch [50] Speed: 608.58 samples/sec Train-accuracy=0.926250
2016-05-03 09:16:39,702 Node[0] Epoch[51] Batch [100] Speed: 606.55 samples/sec Train-accuracy=0.925781
2016-05-03 09:16:50,242 Node[0] Epoch[51] Batch [150] Speed: 607.25 samples/sec Train-accuracy=0.928438
2016-05-03 09:17:00,796 Node[0] Epoch[51] Batch [200] Speed: 606.43 samples/sec Train-accuracy=0.922500
2016-05-03 09:17:11,368 Node[0] Epoch[51] Batch [250] Speed: 605.39 samples/sec Train-accuracy=0.921094
2016-05-03 09:17:21,932 Node[0] Epoch[51] Batch [300] Speed: 605.84 samples/sec Train-accuracy=0.923750
2016-05-03 09:17:32,465 Node[0] Epoch[51] Batch [350] Speed: 607.62 samples/sec Train-accuracy=0.922813
2016-05-03 09:17:41,112 Node[0] Epoch[51] Resetting Data Iterator
2016-05-03 09:17:41,112 Node[0] Epoch[51] Time cost=82.533
2016-05-03 09:17:41,280 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-03 09:17:43,244 Node[0] Epoch[51] Validation-accuracy=0.847756
2016-05-03 09:17:53,842 Node[0] Epoch[52] Batch [50] Speed: 607.06 samples/sec Train-accuracy=0.924219
2016-05-03 09:18:04,361 Node[0] Epoch[52] Batch [100] Speed: 608.44 samples/sec Train-accuracy=0.929375
2016-05-03 09:18:14,923 Node[0] Epoch[52] Batch [150] Speed: 605.96 samples/sec Train-accuracy=0.927188
2016-05-03 09:18:25,450 Node[0] Epoch[52] Batch [200] Speed: 607.94 samples/sec Train-accuracy=0.925781
2016-05-03 09:18:35,998 Node[0] Epoch[52] Batch [250] Speed: 606.81 samples/sec Train-accuracy=0.925625
2016-05-03 09:18:46,564 Node[0] Epoch[52] Batch [300] Speed: 605.73 samples/sec Train-accuracy=0.929688
2016-05-03 09:18:57,148 Node[0] Epoch[52] Batch [350] Speed: 604.69 samples/sec Train-accuracy=0.930156
2016-05-03 09:19:05,795 Node[0] Epoch[52] Resetting Data Iterator
2016-05-03 09:19:05,803 Node[0] Epoch[52] Time cost=82.559
2016-05-03 09:19:05,960 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-03 09:19:07,896 Node[0] Epoch[52] Validation-accuracy=0.855970
2016-05-03 09:19:18,478 Node[0] Epoch[53] Batch [50] Speed: 608.18 samples/sec Train-accuracy=0.927813
2016-05-03 09:19:29,031 Node[0] Epoch[53] Batch [100] Speed: 606.49 samples/sec Train-accuracy=0.926875
2016-05-03 09:19:39,520 Node[0] Epoch[53] Batch [150] Speed: 610.13 samples/sec Train-accuracy=0.932656
2016-05-03 09:19:50,026 Node[0] Epoch[53] Batch [200] Speed: 609.24 samples/sec Train-accuracy=0.929063
2016-05-03 09:20:00,533 Node[0] Epoch[53] Batch [250] Speed: 609.11 samples/sec Train-accuracy=0.923438
2016-05-03 09:20:11,074 Node[0] Epoch[53] Batch [300] Speed: 607.17 samples/sec Train-accuracy=0.925781
2016-05-03 09:20:21,679 Node[0] Epoch[53] Batch [350] Speed: 603.48 samples/sec Train-accuracy=0.925937
2016-05-03 09:20:30,133 Node[0] Epoch[53] Resetting Data Iterator
2016-05-03 09:20:30,133 Node[0] Epoch[53] Time cost=82.237
2016-05-03 09:20:30,304 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-03 09:20:32,261 Node[0] Epoch[53] Validation-accuracy=0.865284
2016-05-03 09:20:42,894 Node[0] Epoch[54] Batch [50] Speed: 605.15 samples/sec Train-accuracy=0.927969
2016-05-03 09:20:53,509 Node[0] Epoch[54] Batch [100] Speed: 602.94 samples/sec Train-accuracy=0.926094
2016-05-03 09:21:04,053 Node[0] Epoch[54] Batch [150] Speed: 606.99 samples/sec Train-accuracy=0.923594
2016-05-03 09:21:14,445 Node[0] Epoch[54] Batch [200] Speed: 615.87 samples/sec Train-accuracy=0.926094
2016-05-03 09:21:24,916 Node[0] Epoch[54] Batch [250] Speed: 611.24 samples/sec Train-accuracy=0.922500
2016-05-03 09:21:35,432 Node[0] Epoch[54] Batch [300] Speed: 608.60 samples/sec Train-accuracy=0.924687
2016-05-03 09:21:46,001 Node[0] Epoch[54] Batch [350] Speed: 605.57 samples/sec Train-accuracy=0.928906
2016-05-03 09:21:54,600 Node[0] Epoch[54] Resetting Data Iterator
2016-05-03 09:21:54,600 Node[0] Epoch[54] Time cost=82.339
2016-05-03 09:21:54,764 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-03 09:21:56,708 Node[0] Epoch[54] Validation-accuracy=0.848758
2016-05-03 09:22:07,304 Node[0] Epoch[55] Batch [50] Speed: 607.16 samples/sec Train-accuracy=0.924844
2016-05-03 09:22:17,815 Node[0] Epoch[55] Batch [100] Speed: 608.87 samples/sec Train-accuracy=0.929688
2016-05-03 09:22:28,355 Node[0] Epoch[55] Batch [150] Speed: 607.23 samples/sec Train-accuracy=0.925937
2016-05-03 09:22:38,794 Node[0] Epoch[55] Batch [200] Speed: 613.12 samples/sec Train-accuracy=0.932969
2016-05-03 09:22:49,258 Node[0] Epoch[55] Batch [250] Speed: 611.64 samples/sec Train-accuracy=0.927813
2016-05-03 09:22:59,772 Node[0] Epoch[55] Batch [300] Speed: 608.75 samples/sec Train-accuracy=0.929844
2016-05-03 09:23:10,345 Node[0] Epoch[55] Batch [350] Speed: 605.32 samples/sec Train-accuracy=0.934219
2016-05-03 09:23:18,754 Node[0] Epoch[55] Resetting Data Iterator
2016-05-03 09:23:18,754 Node[0] Epoch[55] Time cost=82.046
2016-05-03 09:23:18,918 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-03 09:23:20,866 Node[0] Epoch[55] Validation-accuracy=0.852564
2016-05-03 09:23:31,391 Node[0] Epoch[56] Batch [50] Speed: 611.36 samples/sec Train-accuracy=0.922344
2016-05-03 09:23:41,834 Node[0] Epoch[56] Batch [100] Speed: 612.88 samples/sec Train-accuracy=0.930625
2016-05-03 09:23:52,308 Node[0] Epoch[56] Batch [150] Speed: 611.08 samples/sec Train-accuracy=0.925312
2016-05-03 09:24:02,732 Node[0] Epoch[56] Batch [200] Speed: 613.96 samples/sec Train-accuracy=0.923281
2016-05-03 09:24:13,240 Node[0] Epoch[56] Batch [250] Speed: 609.08 samples/sec Train-accuracy=0.932344
2016-05-03 09:24:23,801 Node[0] Epoch[56] Batch [300] Speed: 605.99 samples/sec Train-accuracy=0.933906
2016-05-03 09:24:34,377 Node[0] Epoch[56] Batch [350] Speed: 605.22 samples/sec Train-accuracy=0.929375
2016-05-03 09:24:42,992 Node[0] Epoch[56] Resetting Data Iterator
2016-05-03 09:24:42,992 Node[0] Epoch[56] Time cost=82.126
2016-05-03 09:24:43,162 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-03 09:24:45,288 Node[0] Epoch[56] Validation-accuracy=0.857595
2016-05-03 09:24:55,780 Node[0] Epoch[57] Batch [50] Speed: 613.20 samples/sec Train-accuracy=0.928594
2016-05-03 09:25:06,339 Node[0] Epoch[57] Batch [100] Speed: 606.13 samples/sec Train-accuracy=0.928906
2016-05-03 09:25:16,781 Node[0] Epoch[57] Batch [150] Speed: 612.93 samples/sec Train-accuracy=0.931875
2016-05-03 09:25:27,228 Node[0] Epoch[57] Batch [200] Speed: 612.63 samples/sec Train-accuracy=0.925156
2016-05-03 09:25:37,678 Node[0] Epoch[57] Batch [250] Speed: 612.46 samples/sec Train-accuracy=0.927656
2016-05-03 09:25:48,190 Node[0] Epoch[57] Batch [300] Speed: 608.84 samples/sec Train-accuracy=0.931562
2016-05-03 09:25:58,690 Node[0] Epoch[57] Batch [350] Speed: 609.54 samples/sec Train-accuracy=0.928438
2016-05-03 09:26:07,373 Node[0] Epoch[57] Resetting Data Iterator
2016-05-03 09:26:07,373 Node[0] Epoch[57] Time cost=82.085
2016-05-03 09:26:07,543 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-03 09:26:09,494 Node[0] Epoch[57] Validation-accuracy=0.850361
2016-05-03 09:26:19,976 Node[0] Epoch[58] Batch [50] Speed: 613.83 samples/sec Train-accuracy=0.932500
2016-05-03 09:26:30,486 Node[0] Epoch[58] Batch [100] Speed: 608.97 samples/sec Train-accuracy=0.929688
2016-05-03 09:26:40,991 Node[0] Epoch[58] Batch [150] Speed: 609.25 samples/sec Train-accuracy=0.928906
2016-05-03 09:26:51,503 Node[0] Epoch[58] Batch [200] Speed: 608.84 samples/sec Train-accuracy=0.930469
2016-05-03 09:27:01,924 Node[0] Epoch[58] Batch [250] Speed: 614.15 samples/sec Train-accuracy=0.931250
2016-05-03 09:27:12,339 Node[0] Epoch[58] Batch [300] Speed: 614.50 samples/sec Train-accuracy=0.930312
2016-05-03 09:27:22,796 Node[0] Epoch[58] Batch [350] Speed: 612.09 samples/sec Train-accuracy=0.930781
2016-05-03 09:27:31,184 Node[0] Epoch[58] Resetting Data Iterator
2016-05-03 09:27:31,185 Node[0] Epoch[58] Time cost=81.691
2016-05-03 09:27:31,353 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-03 09:27:33,269 Node[0] Epoch[58] Validation-accuracy=0.858874
2016-05-03 09:27:43,859 Node[0] Epoch[59] Batch [50] Speed: 607.49 samples/sec Train-accuracy=0.931250
2016-05-03 09:27:54,441 Node[0] Epoch[59] Batch [100] Speed: 604.84 samples/sec Train-accuracy=0.930469
2016-05-03 09:28:05,007 Node[0] Epoch[59] Batch [150] Speed: 605.74 samples/sec Train-accuracy=0.931562
2016-05-03 09:28:15,545 Node[0] Epoch[59] Batch [200] Speed: 607.34 samples/sec Train-accuracy=0.924219
2016-05-03 09:28:26,065 Node[0] Epoch[59] Batch [250] Speed: 608.38 samples/sec Train-accuracy=0.921875
2016-05-03 09:28:36,497 Node[0] Epoch[59] Batch [300] Speed: 613.50 samples/sec Train-accuracy=0.933906
2016-05-03 09:28:46,978 Node[0] Epoch[59] Batch [350] Speed: 610.61 samples/sec Train-accuracy=0.928750
2016-05-03 09:28:55,542 Node[0] Epoch[59] Resetting Data Iterator
2016-05-03 09:28:55,542 Node[0] Epoch[59] Time cost=82.274
2016-05-03 09:28:55,707 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-03 09:28:57,645 Node[0] Epoch[59] Validation-accuracy=0.857572
2016-05-03 09:29:08,339 Node[0] Epoch[60] Batch [50] Speed: 601.65 samples/sec Train-accuracy=0.929844
2016-05-03 09:29:18,929 Node[0] Epoch[60] Batch [100] Speed: 604.32 samples/sec Train-accuracy=0.929063
2016-05-03 09:29:29,337 Node[0] Epoch[60] Batch [150] Speed: 614.94 samples/sec Train-accuracy=0.930312
2016-05-03 09:29:39,812 Node[0] Epoch[60] Batch [200] Speed: 610.97 samples/sec Train-accuracy=0.929063
2016-05-03 09:29:50,311 Node[0] Epoch[60] Batch [250] Speed: 609.60 samples/sec Train-accuracy=0.930156
2016-05-03 09:30:00,901 Node[0] Epoch[60] Batch [300] Speed: 604.36 samples/sec Train-accuracy=0.935000
2016-05-03 09:30:11,458 Node[0] Epoch[60] Batch [350] Speed: 606.27 samples/sec Train-accuracy=0.929844
2016-05-03 09:30:20,116 Node[0] Epoch[60] Resetting Data Iterator
2016-05-03 09:30:20,117 Node[0] Epoch[60] Time cost=82.472
2016-05-03 09:30:20,280 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-03 09:30:22,254 Node[0] Epoch[60] Validation-accuracy=0.855068
2016-05-03 09:30:32,797 Node[0] Epoch[61] Batch [50] Speed: 610.17 samples/sec Train-accuracy=0.927031
2016-05-03 09:30:43,337 Node[0] Epoch[61] Batch [100] Speed: 607.26 samples/sec Train-accuracy=0.935000
2016-05-03 09:30:53,870 Node[0] Epoch[61] Batch [150] Speed: 607.64 samples/sec Train-accuracy=0.933281
2016-05-03 09:31:04,436 Node[0] Epoch[61] Batch [200] Speed: 605.72 samples/sec Train-accuracy=0.933594
2016-05-03 09:31:14,864 Node[0] Epoch[61] Batch [250] Speed: 613.71 samples/sec Train-accuracy=0.925625
2016-05-03 09:31:25,386 Node[0] Epoch[61] Batch [300] Speed: 608.31 samples/sec Train-accuracy=0.937031
2016-05-03 09:31:35,914 Node[0] Epoch[61] Batch [350] Speed: 607.92 samples/sec Train-accuracy=0.937500
2016-05-03 09:31:44,349 Node[0] Epoch[61] Resetting Data Iterator
2016-05-03 09:31:44,349 Node[0] Epoch[61] Time cost=82.096
2016-05-03 09:31:44,515 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-03 09:31:46,449 Node[0] Epoch[61] Validation-accuracy=0.867188
2016-05-03 09:31:57,035 Node[0] Epoch[62] Batch [50] Speed: 607.79 samples/sec Train-accuracy=0.933125
2016-05-03 09:32:07,572 Node[0] Epoch[62] Batch [100] Speed: 607.38 samples/sec Train-accuracy=0.931250
2016-05-03 09:32:18,124 Node[0] Epoch[62] Batch [150] Speed: 606.56 samples/sec Train-accuracy=0.930469
2016-05-03 09:32:28,683 Node[0] Epoch[62] Batch [200] Speed: 606.09 samples/sec Train-accuracy=0.929844
2016-05-03 09:32:39,223 Node[0] Epoch[62] Batch [250] Speed: 607.24 samples/sec Train-accuracy=0.932656
2016-05-03 09:32:49,768 Node[0] Epoch[62] Batch [300] Speed: 606.95 samples/sec Train-accuracy=0.935156
2016-05-03 09:33:00,320 Node[0] Epoch[62] Batch [350] Speed: 606.54 samples/sec Train-accuracy=0.926875
2016-05-03 09:33:08,947 Node[0] Epoch[62] Resetting Data Iterator
2016-05-03 09:33:08,948 Node[0] Epoch[62] Time cost=82.498
2016-05-03 09:33:09,115 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-03 09:33:11,076 Node[0] Epoch[62] Validation-accuracy=0.860176
2016-05-03 09:33:21,624 Node[0] Epoch[63] Batch [50] Speed: 609.97 samples/sec Train-accuracy=0.930625
2016-05-03 09:33:32,142 Node[0] Epoch[63] Batch [100] Speed: 608.45 samples/sec Train-accuracy=0.938594
2016-05-03 09:33:42,679 Node[0] Epoch[63] Batch [150] Speed: 607.41 samples/sec Train-accuracy=0.932656
2016-05-03 09:33:53,207 Node[0] Epoch[63] Batch [200] Speed: 607.93 samples/sec Train-accuracy=0.926406
2016-05-03 09:34:03,747 Node[0] Epoch[63] Batch [250] Speed: 607.23 samples/sec Train-accuracy=0.931562
2016-05-03 09:34:14,277 Node[0] Epoch[63] Batch [300] Speed: 607.83 samples/sec Train-accuracy=0.933750
2016-05-03 09:34:24,787 Node[0] Epoch[63] Batch [350] Speed: 608.93 samples/sec Train-accuracy=0.938594
2016-05-03 09:34:33,183 Node[0] Epoch[63] Resetting Data Iterator
2016-05-03 09:34:33,184 Node[0] Epoch[63] Time cost=82.107
2016-05-03 09:34:33,349 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-03 09:34:35,307 Node[0] Epoch[63] Validation-accuracy=0.856771
2016-05-03 09:34:45,928 Node[0] Epoch[64] Batch [50] Speed: 605.77 samples/sec Train-accuracy=0.934844
2016-05-03 09:34:56,383 Node[0] Epoch[64] Batch [100] Speed: 612.19 samples/sec Train-accuracy=0.937500
2016-05-03 09:35:06,861 Node[0] Epoch[64] Batch [150] Speed: 610.79 samples/sec Train-accuracy=0.940625
2016-05-03 09:35:17,433 Node[0] Epoch[64] Batch [200] Speed: 605.38 samples/sec Train-accuracy=0.930937
2016-05-03 09:35:27,997 Node[0] Epoch[64] Batch [250] Speed: 605.85 samples/sec Train-accuracy=0.922969
2016-05-03 09:35:38,571 Node[0] Epoch[64] Batch [300] Speed: 605.30 samples/sec Train-accuracy=0.934219
2016-05-03 09:35:49,072 Node[0] Epoch[64] Batch [350] Speed: 609.49 samples/sec Train-accuracy=0.936094
2016-05-03 09:35:57,682 Node[0] Epoch[64] Resetting Data Iterator
2016-05-03 09:35:57,682 Node[0] Epoch[64] Time cost=82.375
2016-05-03 09:35:57,852 Node[0] Saved checkpoint to "cifar10/resnet-0065.params"
2016-05-03 09:36:00,025 Node[0] Epoch[64] Validation-accuracy=0.848794
2016-05-03 09:36:10,603 Node[0] Epoch[65] Batch [50] Speed: 608.25 samples/sec Train-accuracy=0.929063
2016-05-03 09:36:21,137 Node[0] Epoch[65] Batch [100] Speed: 607.56 samples/sec Train-accuracy=0.937969
2016-05-03 09:36:31,559 Node[0] Epoch[65] Batch [150] Speed: 614.10 samples/sec Train-accuracy=0.935937
2016-05-03 09:36:42,010 Node[0] Epoch[65] Batch [200] Speed: 612.40 samples/sec Train-accuracy=0.933906
2016-05-03 09:36:52,561 Node[0] Epoch[65] Batch [250] Speed: 606.61 samples/sec Train-accuracy=0.930937
2016-05-03 09:37:03,103 Node[0] Epoch[65] Batch [300] Speed: 607.10 samples/sec Train-accuracy=0.936875
2016-05-03 09:37:13,675 Node[0] Epoch[65] Batch [350] Speed: 605.43 samples/sec Train-accuracy=0.928750
2016-05-03 09:37:22,316 Node[0] Epoch[65] Resetting Data Iterator
2016-05-03 09:37:22,317 Node[0] Epoch[65] Time cost=82.291
2016-05-03 09:37:22,479 Node[0] Saved checkpoint to "cifar10/resnet-0066.params"
2016-05-03 09:37:24,426 Node[0] Epoch[65] Validation-accuracy=0.865986
2016-05-03 09:37:35,023 Node[0] Epoch[66] Batch [50] Speed: 607.13 samples/sec Train-accuracy=0.937031
2016-05-03 09:37:45,556 Node[0] Epoch[66] Batch [100] Speed: 607.59 samples/sec Train-accuracy=0.937969
2016-05-03 09:37:56,095 Node[0] Epoch[66] Batch [150] Speed: 607.33 samples/sec Train-accuracy=0.939375
2016-05-03 09:38:06,437 Node[0] Epoch[66] Batch [200] Speed: 618.83 samples/sec Train-accuracy=0.930156
2016-05-03 09:38:16,920 Node[0] Epoch[66] Batch [250] Speed: 610.51 samples/sec Train-accuracy=0.934531
2016-05-03 09:38:27,475 Node[0] Epoch[66] Batch [300] Speed: 606.38 samples/sec Train-accuracy=0.936250
2016-05-03 09:38:38,066 Node[0] Epoch[66] Batch [350] Speed: 604.30 samples/sec Train-accuracy=0.929375
2016-05-03 09:38:46,483 Node[0] Epoch[66] Resetting Data Iterator
2016-05-03 09:38:46,484 Node[0] Epoch[66] Time cost=82.057
2016-05-03 09:38:46,648 Node[0] Saved checkpoint to "cifar10/resnet-0067.params"
2016-05-03 09:38:48,597 Node[0] Epoch[66] Validation-accuracy=0.851362
2016-05-03 09:38:59,134 Node[0] Epoch[67] Batch [50] Speed: 610.64 samples/sec Train-accuracy=0.935625
2016-05-03 09:39:09,680 Node[0] Epoch[67] Batch [100] Speed: 606.92 samples/sec Train-accuracy=0.936719
2016-05-03 09:39:20,165 Node[0] Epoch[67] Batch [150] Speed: 610.36 samples/sec Train-accuracy=0.940781
2016-05-03 09:39:30,641 Node[0] Epoch[67] Batch [200] Speed: 610.98 samples/sec Train-accuracy=0.936719
2016-05-03 09:39:41,157 Node[0] Epoch[67] Batch [250] Speed: 608.63 samples/sec Train-accuracy=0.936406
2016-05-03 09:39:51,699 Node[0] Epoch[67] Batch [300] Speed: 607.09 samples/sec Train-accuracy=0.937656
2016-05-03 09:40:02,265 Node[0] Epoch[67] Batch [350] Speed: 605.70 samples/sec Train-accuracy=0.936562
2016-05-03 09:40:10,905 Node[0] Epoch[67] Resetting Data Iterator
2016-05-03 09:40:10,905 Node[0] Epoch[67] Time cost=82.308
2016-05-03 09:40:11,074 Node[0] Saved checkpoint to "cifar10/resnet-0068.params"
2016-05-03 09:40:13,031 Node[0] Epoch[67] Validation-accuracy=0.865385
2016-05-03 09:40:23,559 Node[0] Epoch[68] Batch [50] Speed: 611.22 samples/sec Train-accuracy=0.933906
2016-05-03 09:40:34,103 Node[0] Epoch[68] Batch [100] Speed: 607.01 samples/sec Train-accuracy=0.933125
2016-05-03 09:40:44,531 Node[0] Epoch[68] Batch [150] Speed: 613.69 samples/sec Train-accuracy=0.937813
2016-05-03 09:40:54,981 Node[0] Epoch[68] Batch [200] Speed: 612.51 samples/sec Train-accuracy=0.931406
2016-05-03 09:41:05,450 Node[0] Epoch[68] Batch [250] Speed: 611.31 samples/sec Train-accuracy=0.932969
2016-05-03 09:41:15,940 Node[0] Epoch[68] Batch [300] Speed: 610.13 samples/sec Train-accuracy=0.940156
2016-05-03 09:41:26,465 Node[0] Epoch[68] Batch [350] Speed: 608.08 samples/sec Train-accuracy=0.933438
2016-05-03 09:41:35,095 Node[0] Epoch[68] Resetting Data Iterator
2016-05-03 09:41:35,095 Node[0] Epoch[68] Time cost=82.064
2016-05-03 09:41:35,261 Node[0] Saved checkpoint to "cifar10/resnet-0069.params"
2016-05-03 09:41:37,191 Node[0] Epoch[68] Validation-accuracy=0.867087
2016-05-03 09:41:47,736 Node[0] Epoch[69] Batch [50] Speed: 610.09 samples/sec Train-accuracy=0.936875
2016-05-03 09:41:58,246 Node[0] Epoch[69] Batch [100] Speed: 608.95 samples/sec Train-accuracy=0.935156
2016-05-03 09:42:08,773 Node[0] Epoch[69] Batch [150] Speed: 608.00 samples/sec Train-accuracy=0.940469
2016-05-03 09:42:19,245 Node[0] Epoch[69] Batch [200] Speed: 611.16 samples/sec Train-accuracy=0.935469
2016-05-03 09:42:29,694 Node[0] Epoch[69] Batch [250] Speed: 612.50 samples/sec Train-accuracy=0.934063
2016-05-03 09:42:40,104 Node[0] Epoch[69] Batch [300] Speed: 614.87 samples/sec Train-accuracy=0.937656
2016-05-03 09:42:50,587 Node[0] Epoch[69] Batch [350] Speed: 610.49 samples/sec Train-accuracy=0.935312
2016-05-03 09:42:59,021 Node[0] Epoch[69] Resetting Data Iterator
2016-05-03 09:42:59,021 Node[0] Epoch[69] Time cost=81.829
2016-05-03 09:42:59,184 Node[0] Saved checkpoint to "cifar10/resnet-0070.params"
2016-05-03 09:43:01,139 Node[0] Epoch[69] Validation-accuracy=0.853165
2016-05-03 09:43:11,787 Node[0] Epoch[70] Batch [50] Speed: 604.14 samples/sec Train-accuracy=0.937344
2016-05-03 09:43:22,319 Node[0] Epoch[70] Batch [100] Speed: 607.71 samples/sec Train-accuracy=0.942813
2016-05-03 09:43:32,784 Node[0] Epoch[70] Batch [150] Speed: 611.61 samples/sec Train-accuracy=0.935312
2016-05-03 09:43:43,237 Node[0] Epoch[70] Batch [200] Speed: 612.25 samples/sec Train-accuracy=0.937187
2016-05-03 09:43:53,723 Node[0] Epoch[70] Batch [250] Speed: 610.39 samples/sec Train-accuracy=0.937500
2016-05-03 09:44:04,253 Node[0] Epoch[70] Batch [300] Speed: 607.76 samples/sec Train-accuracy=0.937813
2016-05-03 09:44:14,820 Node[0] Epoch[70] Batch [350] Speed: 605.68 samples/sec Train-accuracy=0.936094
2016-05-03 09:44:23,457 Node[0] Epoch[70] Resetting Data Iterator
2016-05-03 09:44:23,457 Node[0] Epoch[70] Time cost=82.318
2016-05-03 09:44:23,623 Node[0] Saved checkpoint to "cifar10/resnet-0071.params"
2016-05-03 09:44:25,569 Node[0] Epoch[70] Validation-accuracy=0.868790
2016-05-03 09:44:36,061 Node[0] Epoch[71] Batch [50] Speed: 613.25 samples/sec Train-accuracy=0.937344
2016-05-03 09:44:46,586 Node[0] Epoch[71] Batch [100] Speed: 608.10 samples/sec Train-accuracy=0.939219
2016-05-03 09:44:57,062 Node[0] Epoch[71] Batch [150] Speed: 610.91 samples/sec Train-accuracy=0.934219
2016-05-03 09:45:07,515 Node[0] Epoch[71] Batch [200] Speed: 612.28 samples/sec Train-accuracy=0.937813
2016-05-03 09:45:18,015 Node[0] Epoch[71] Batch [250] Speed: 609.57 samples/sec Train-accuracy=0.933594
2016-05-03 09:45:28,568 Node[0] Epoch[71] Batch [300] Speed: 606.44 samples/sec Train-accuracy=0.936250
2016-05-03 09:45:39,095 Node[0] Epoch[71] Batch [350] Speed: 608.01 samples/sec Train-accuracy=0.940156
2016-05-03 09:45:47,517 Node[0] Epoch[71] Resetting Data Iterator
2016-05-03 09:45:47,517 Node[0] Epoch[71] Time cost=81.948
2016-05-03 09:45:47,684 Node[0] Saved checkpoint to "cifar10/resnet-0072.params"
2016-05-03 09:45:49,587 Node[0] Epoch[71] Validation-accuracy=0.863381
2016-05-03 09:46:00,153 Node[0] Epoch[72] Batch [50] Speed: 609.01 samples/sec Train-accuracy=0.946406
2016-05-03 09:46:10,637 Node[0] Epoch[72] Batch [100] Speed: 610.45 samples/sec Train-accuracy=0.937187
2016-05-03 09:46:21,032 Node[0] Epoch[72] Batch [150] Speed: 615.69 samples/sec Train-accuracy=0.939844
2016-05-03 09:46:31,429 Node[0] Epoch[72] Batch [200] Speed: 615.61 samples/sec Train-accuracy=0.936719
2016-05-03 09:46:41,982 Node[0] Epoch[72] Batch [250] Speed: 606.47 samples/sec Train-accuracy=0.938125
2016-05-03 09:46:52,532 Node[0] Epoch[72] Batch [300] Speed: 606.66 samples/sec Train-accuracy=0.937500
2016-05-03 09:47:03,037 Node[0] Epoch[72] Batch [350] Speed: 609.22 samples/sec Train-accuracy=0.936406
2016-05-03 09:47:11,682 Node[0] Epoch[72] Resetting Data Iterator
2016-05-03 09:47:11,682 Node[0] Epoch[72] Time cost=82.095
2016-05-03 09:47:11,846 Node[0] Saved checkpoint to "cifar10/resnet-0073.params"
2016-05-03 09:47:14,010 Node[0] Epoch[72] Validation-accuracy=0.850178
2016-05-03 09:47:24,580 Node[0] Epoch[73] Batch [50] Speed: 608.74 samples/sec Train-accuracy=0.936719
2016-05-03 09:47:35,151 Node[0] Epoch[73] Batch [100] Speed: 605.42 samples/sec Train-accuracy=0.941406
2016-05-03 09:47:45,667 Node[0] Epoch[73] Batch [150] Speed: 608.62 samples/sec Train-accuracy=0.942656
2016-05-03 09:47:56,167 Node[0] Epoch[73] Batch [200] Speed: 609.56 samples/sec Train-accuracy=0.939219
2016-05-03 09:48:06,653 Node[0] Epoch[73] Batch [250] Speed: 610.31 samples/sec Train-accuracy=0.932656
2016-05-03 09:48:17,106 Node[0] Epoch[73] Batch [300] Speed: 612.30 samples/sec Train-accuracy=0.941094
2016-05-03 09:48:27,616 Node[0] Epoch[73] Batch [350] Speed: 608.95 samples/sec Train-accuracy=0.937187
2016-05-03 09:48:36,211 Node[0] Epoch[73] Resetting Data Iterator
2016-05-03 09:48:36,212 Node[0] Epoch[73] Time cost=82.201
2016-05-03 09:48:36,377 Node[0] Saved checkpoint to "cifar10/resnet-0074.params"
2016-05-03 09:48:38,298 Node[0] Epoch[73] Validation-accuracy=0.853866
2016-05-03 09:48:48,881 Node[0] Epoch[74] Batch [50] Speed: 607.91 samples/sec Train-accuracy=0.945156
2016-05-03 09:48:59,405 Node[0] Epoch[74] Batch [100] Speed: 608.16 samples/sec Train-accuracy=0.936406
2016-05-03 09:49:09,921 Node[0] Epoch[74] Batch [150] Speed: 608.62 samples/sec Train-accuracy=0.940312
2016-05-03 09:49:20,400 Node[0] Epoch[74] Batch [200] Speed: 610.74 samples/sec Train-accuracy=0.937344
2016-05-03 09:49:30,826 Node[0] Epoch[74] Batch [250] Speed: 613.89 samples/sec Train-accuracy=0.935625
2016-05-03 09:49:41,295 Node[0] Epoch[74] Batch [300] Speed: 611.31 samples/sec Train-accuracy=0.941406
2016-05-03 09:49:51,812 Node[0] Epoch[74] Batch [350] Speed: 608.60 samples/sec Train-accuracy=0.943750
2016-05-03 09:50:00,215 Node[0] Epoch[74] Resetting Data Iterator
2016-05-03 09:50:00,216 Node[0] Epoch[74] Time cost=81.918
2016-05-03 09:50:00,382 Node[0] Saved checkpoint to "cifar10/resnet-0075.params"
2016-05-03 09:50:02,342 Node[0] Epoch[74] Validation-accuracy=0.847957
2016-05-03 09:50:12,910 Node[0] Epoch[75] Batch [50] Speed: 608.80 samples/sec Train-accuracy=0.934219
2016-05-03 09:50:23,477 Node[0] Epoch[75] Batch [100] Speed: 605.68 samples/sec Train-accuracy=0.942500
2016-05-03 09:50:33,885 Node[0] Epoch[75] Batch [150] Speed: 614.92 samples/sec Train-accuracy=0.939844
2016-05-03 09:50:44,354 Node[0] Epoch[75] Batch [200] Speed: 611.37 samples/sec Train-accuracy=0.939688
2016-05-03 09:50:54,768 Node[0] Epoch[75] Batch [250] Speed: 614.58 samples/sec Train-accuracy=0.932656
2016-05-03 09:51:05,236 Node[0] Epoch[75] Batch [300] Speed: 611.42 samples/sec Train-accuracy=0.933750
2016-05-03 09:51:15,789 Node[0] Epoch[75] Batch [350] Speed: 606.49 samples/sec Train-accuracy=0.937031
2016-05-03 09:51:24,457 Node[0] Epoch[75] Resetting Data Iterator
2016-05-03 09:51:24,457 Node[0] Epoch[75] Time cost=82.115
2016-05-03 09:51:24,620 Node[0] Saved checkpoint to "cifar10/resnet-0076.params"
2016-05-03 09:51:26,581 Node[0] Epoch[75] Validation-accuracy=0.870092
2016-05-03 09:51:37,119 Node[0] Epoch[76] Batch [50] Speed: 610.62 samples/sec Train-accuracy=0.938750
2016-05-03 09:51:47,697 Node[0] Epoch[76] Batch [100] Speed: 605.04 samples/sec Train-accuracy=0.935156
2016-05-03 09:51:58,191 Node[0] Epoch[76] Batch [150] Speed: 609.87 samples/sec Train-accuracy=0.943281
2016-05-03 09:52:08,671 Node[0] Epoch[76] Batch [200] Speed: 610.69 samples/sec Train-accuracy=0.936562
2016-05-03 09:52:19,139 Node[0] Epoch[76] Batch [250] Speed: 611.43 samples/sec Train-accuracy=0.938594
2016-05-03 09:52:29,550 Node[0] Epoch[76] Batch [300] Speed: 614.75 samples/sec Train-accuracy=0.939531
2016-05-03 09:52:39,979 Node[0] Epoch[76] Batch [350] Speed: 613.67 samples/sec Train-accuracy=0.940469
2016-05-03 09:52:48,615 Node[0] Epoch[76] Resetting Data Iterator
2016-05-03 09:52:48,615 Node[0] Epoch[76] Time cost=82.034
2016-05-03 09:52:48,780 Node[0] Saved checkpoint to "cifar10/resnet-0077.params"
2016-05-03 09:52:50,708 Node[0] Epoch[76] Validation-accuracy=0.860677
2016-05-03 09:53:01,331 Node[0] Epoch[77] Batch [50] Speed: 605.66 samples/sec Train-accuracy=0.934375
2016-05-03 09:53:11,766 Node[0] Epoch[77] Batch [100] Speed: 613.30 samples/sec Train-accuracy=0.943125
2016-05-03 09:53:22,242 Node[0] Epoch[77] Batch [150] Speed: 610.97 samples/sec Train-accuracy=0.940625
2016-05-03 09:53:32,701 Node[0] Epoch[77] Batch [200] Speed: 611.94 samples/sec Train-accuracy=0.938281
2016-05-03 09:53:43,159 Node[0] Epoch[77] Batch [250] Speed: 611.96 samples/sec Train-accuracy=0.939844
2016-05-03 09:53:53,634 Node[0] Epoch[77] Batch [300] Speed: 611.02 samples/sec Train-accuracy=0.938438
2016-05-03 09:54:04,193 Node[0] Epoch[77] Batch [350] Speed: 606.09 samples/sec Train-accuracy=0.937969
2016-05-03 09:54:12,604 Node[0] Epoch[77] Resetting Data Iterator
2016-05-03 09:54:12,605 Node[0] Epoch[77] Time cost=81.897
2016-05-03 09:54:12,776 Node[0] Saved checkpoint to "cifar10/resnet-0078.params"
2016-05-03 09:54:14,703 Node[0] Epoch[77] Validation-accuracy=0.855970
2016-05-03 09:54:25,194 Node[0] Epoch[78] Batch [50] Speed: 613.31 samples/sec Train-accuracy=0.937031
2016-05-03 09:54:35,665 Node[0] Epoch[78] Batch [100] Speed: 611.25 samples/sec Train-accuracy=0.939063
2016-05-03 09:54:46,079 Node[0] Epoch[78] Batch [150] Speed: 614.54 samples/sec Train-accuracy=0.940781
2016-05-03 09:54:56,526 Node[0] Epoch[78] Batch [200] Speed: 612.66 samples/sec Train-accuracy=0.933906
2016-05-03 09:55:07,003 Node[0] Epoch[78] Batch [250] Speed: 610.87 samples/sec Train-accuracy=0.938438
2016-05-03 09:55:17,397 Node[0] Epoch[78] Batch [300] Speed: 615.76 samples/sec Train-accuracy=0.941562
2016-05-03 09:55:27,948 Node[0] Epoch[78] Batch [350] Speed: 606.62 samples/sec Train-accuracy=0.940781
2016-05-03 09:55:36,574 Node[0] Epoch[78] Resetting Data Iterator
2016-05-03 09:55:36,575 Node[0] Epoch[78] Time cost=81.872
2016-05-03 09:55:36,740 Node[0] Saved checkpoint to "cifar10/resnet-0079.params"
2016-05-03 09:55:38,674 Node[0] Epoch[78] Validation-accuracy=0.840044
2016-05-03 09:55:49,181 Node[0] Epoch[79] Batch [50] Speed: 612.37 samples/sec Train-accuracy=0.939063
2016-05-03 09:55:59,625 Node[0] Epoch[79] Batch [100] Speed: 612.79 samples/sec Train-accuracy=0.944063
2016-05-03 09:56:10,027 Node[0] Epoch[79] Batch [150] Speed: 615.28 samples/sec Train-accuracy=0.942344
2016-05-03 09:56:20,484 Node[0] Epoch[79] Batch [200] Speed: 612.08 samples/sec Train-accuracy=0.937187
2016-05-03 09:56:30,987 Node[0] Epoch[79] Batch [250] Speed: 609.36 samples/sec Train-accuracy=0.941250
2016-05-03 09:56:41,425 Node[0] Epoch[79] Batch [300] Speed: 613.12 samples/sec Train-accuracy=0.941406
2016-05-03 09:56:51,889 Node[0] Epoch[79] Batch [350] Speed: 611.65 samples/sec Train-accuracy=0.939375
2016-05-03 09:57:00,281 Node[0] Epoch[79] Resetting Data Iterator
2016-05-03 09:57:00,281 Node[0] Epoch[79] Time cost=81.607
2016-05-03 09:57:00,449 Node[0] Saved checkpoint to "cifar10/resnet-0080.params"
2016-05-03 09:57:02,394 Node[0] Epoch[79] Validation-accuracy=0.869692
2016-05-03 09:57:02,395 Node[0] Update[31251]: Change learning rate to 1.00000e-02
2016-05-03 09:57:12,985 Node[0] Epoch[80] Batch [50] Speed: 607.49 samples/sec Train-accuracy=0.942969
2016-05-03 09:57:23,463 Node[0] Epoch[80] Batch [100] Speed: 610.81 samples/sec Train-accuracy=0.956094
2016-05-03 09:57:33,942 Node[0] Epoch[80] Batch [150] Speed: 610.79 samples/sec Train-accuracy=0.960781
2016-05-03 09:57:44,448 Node[0] Epoch[80] Batch [200] Speed: 609.15 samples/sec Train-accuracy=0.965313
2016-05-03 09:57:54,895 Node[0] Epoch[80] Batch [250] Speed: 612.68 samples/sec Train-accuracy=0.968437
2016-05-03 09:58:05,365 Node[0] Epoch[80] Batch [300] Speed: 611.29 samples/sec Train-accuracy=0.972812
2016-05-03 09:58:15,813 Node[0] Epoch[80] Batch [350] Speed: 612.52 samples/sec Train-accuracy=0.971406
2016-05-03 09:58:24,420 Node[0] Epoch[80] Resetting Data Iterator
2016-05-03 09:58:24,420 Node[0] Epoch[80] Time cost=82.026
2016-05-03 09:58:24,584 Node[0] Saved checkpoint to "cifar10/resnet-0081.params"
2016-05-03 09:58:26,737 Node[0] Epoch[80] Validation-accuracy=0.897152
2016-05-03 09:58:37,294 Node[0] Epoch[81] Batch [50] Speed: 609.43 samples/sec Train-accuracy=0.967812
2016-05-03 09:58:47,772 Node[0] Epoch[81] Batch [100] Speed: 610.79 samples/sec Train-accuracy=0.973281
2016-05-03 09:58:58,196 Node[0] Epoch[81] Batch [150] Speed: 614.03 samples/sec Train-accuracy=0.972344
2016-05-03 09:59:08,711 Node[0] Epoch[81] Batch [200] Speed: 608.63 samples/sec Train-accuracy=0.970156
2016-05-03 09:59:19,170 Node[0] Epoch[81] Batch [250] Speed: 611.96 samples/sec Train-accuracy=0.977187
2016-05-03 09:59:29,622 Node[0] Epoch[81] Batch [300] Speed: 612.32 samples/sec Train-accuracy=0.978906
2016-05-03 09:59:40,105 Node[0] Epoch[81] Batch [350] Speed: 610.55 samples/sec Train-accuracy=0.979844
2016-05-03 09:59:48,654 Node[0] Epoch[81] Resetting Data Iterator
2016-05-03 09:59:48,654 Node[0] Epoch[81] Time cost=81.917
2016-05-03 09:59:48,820 Node[0] Saved checkpoint to "cifar10/resnet-0082.params"
2016-05-03 09:59:50,800 Node[0] Epoch[81] Validation-accuracy=0.901542
2016-05-03 10:00:01,446 Node[0] Epoch[82] Batch [50] Speed: 604.31 samples/sec Train-accuracy=0.976562
2016-05-03 10:00:11,992 Node[0] Epoch[82] Batch [100] Speed: 606.87 samples/sec Train-accuracy=0.979844
2016-05-03 10:00:22,402 Node[0] Epoch[82] Batch [150] Speed: 614.80 samples/sec Train-accuracy=0.977031
2016-05-03 10:00:32,838 Node[0] Epoch[82] Batch [200] Speed: 613.26 samples/sec Train-accuracy=0.976562
2016-05-03 10:00:43,241 Node[0] Epoch[82] Batch [250] Speed: 615.25 samples/sec Train-accuracy=0.978750
2016-05-03 10:00:53,804 Node[0] Epoch[82] Batch [300] Speed: 605.87 samples/sec Train-accuracy=0.978125
2016-05-03 10:01:04,329 Node[0] Epoch[82] Batch [350] Speed: 608.12 samples/sec Train-accuracy=0.983906
2016-05-03 10:01:12,748 Node[0] Epoch[82] Resetting Data Iterator
2016-05-03 10:01:12,748 Node[0] Epoch[82] Time cost=81.948
2016-05-03 10:01:12,913 Node[0] Saved checkpoint to "cifar10/resnet-0083.params"
2016-05-03 10:01:14,865 Node[0] Epoch[82] Validation-accuracy=0.901042
2016-05-03 10:01:25,382 Node[0] Epoch[83] Batch [50] Speed: 611.73 samples/sec Train-accuracy=0.976094
2016-05-03 10:01:35,839 Node[0] Epoch[83] Batch [100] Speed: 612.06 samples/sec Train-accuracy=0.979375
2016-05-03 10:01:46,321 Node[0] Epoch[83] Batch [150] Speed: 610.56 samples/sec Train-accuracy=0.981406
2016-05-03 10:01:56,785 Node[0] Epoch[83] Batch [200] Speed: 611.64 samples/sec Train-accuracy=0.981250
2016-05-03 10:02:07,261 Node[0] Epoch[83] Batch [250] Speed: 610.94 samples/sec Train-accuracy=0.981406
2016-05-03 10:02:17,687 Node[0] Epoch[83] Batch [300] Speed: 613.87 samples/sec Train-accuracy=0.981094
2016-05-03 10:02:28,193 Node[0] Epoch[83] Batch [350] Speed: 609.18 samples/sec Train-accuracy=0.984062
2016-05-03 10:02:36,823 Node[0] Epoch[83] Resetting Data Iterator
2016-05-03 10:02:36,824 Node[0] Epoch[83] Time cost=81.959
2016-05-03 10:02:36,991 Node[0] Saved checkpoint to "cifar10/resnet-0084.params"
2016-05-03 10:02:38,905 Node[0] Epoch[83] Validation-accuracy=0.903746
2016-05-03 10:02:49,421 Node[0] Epoch[84] Batch [50] Speed: 611.84 samples/sec Train-accuracy=0.982969
2016-05-03 10:02:59,857 Node[0] Epoch[84] Batch [100] Speed: 613.31 samples/sec Train-accuracy=0.981250
2016-05-03 10:03:10,307 Node[0] Epoch[84] Batch [150] Speed: 612.46 samples/sec Train-accuracy=0.983125
2016-05-03 10:03:20,724 Node[0] Epoch[84] Batch [200] Speed: 614.38 samples/sec Train-accuracy=0.981250
2016-05-03 10:03:31,163 Node[0] Epoch[84] Batch [250] Speed: 613.12 samples/sec Train-accuracy=0.980000
2016-05-03 10:03:41,669 Node[0] Epoch[84] Batch [300] Speed: 609.17 samples/sec Train-accuracy=0.984531
2016-05-03 10:03:52,165 Node[0] Epoch[84] Batch [350] Speed: 609.76 samples/sec Train-accuracy=0.986875
2016-05-03 10:04:00,812 Node[0] Epoch[84] Resetting Data Iterator
2016-05-03 10:04:00,812 Node[0] Epoch[84] Time cost=81.907
2016-05-03 10:04:00,976 Node[0] Saved checkpoint to "cifar10/resnet-0085.params"
2016-05-03 10:04:02,936 Node[0] Epoch[84] Validation-accuracy=0.903846
2016-05-03 10:04:13,400 Node[0] Epoch[85] Batch [50] Speed: 614.82 samples/sec Train-accuracy=0.983281
2016-05-03 10:04:23,821 Node[0] Epoch[85] Batch [100] Speed: 614.17 samples/sec Train-accuracy=0.984375
2016-05-03 10:04:34,246 Node[0] Epoch[85] Batch [150] Speed: 613.87 samples/sec Train-accuracy=0.985313
2016-05-03 10:04:44,693 Node[0] Epoch[85] Batch [200] Speed: 612.67 samples/sec Train-accuracy=0.985625
2016-05-03 10:04:55,148 Node[0] Epoch[85] Batch [250] Speed: 612.16 samples/sec Train-accuracy=0.985469
2016-05-03 10:05:05,553 Node[0] Epoch[85] Batch [300] Speed: 615.09 samples/sec Train-accuracy=0.987344
2016-05-03 10:05:15,981 Node[0] Epoch[85] Batch [350] Speed: 613.78 samples/sec Train-accuracy=0.989062
2016-05-03 10:05:24,352 Node[0] Epoch[85] Resetting Data Iterator
2016-05-03 10:05:24,352 Node[0] Epoch[85] Time cost=81.416
2016-05-03 10:05:24,518 Node[0] Saved checkpoint to "cifar10/resnet-0086.params"
2016-05-03 10:05:26,469 Node[0] Epoch[85] Validation-accuracy=0.903546
2016-05-03 10:05:37,028 Node[0] Epoch[86] Batch [50] Speed: 609.32 samples/sec Train-accuracy=0.984688
2016-05-03 10:05:47,472 Node[0] Epoch[86] Batch [100] Speed: 612.82 samples/sec Train-accuracy=0.986719
2016-05-03 10:05:57,915 Node[0] Epoch[86] Batch [150] Speed: 612.88 samples/sec Train-accuracy=0.983125
2016-05-03 10:06:08,350 Node[0] Epoch[86] Batch [200] Speed: 613.34 samples/sec Train-accuracy=0.986719
2016-05-03 10:06:18,805 Node[0] Epoch[86] Batch [250] Speed: 612.16 samples/sec Train-accuracy=0.986250
2016-05-03 10:06:29,242 Node[0] Epoch[86] Batch [300] Speed: 613.23 samples/sec Train-accuracy=0.988125
2016-05-03 10:06:39,673 Node[0] Epoch[86] Batch [350] Speed: 613.59 samples/sec Train-accuracy=0.989062
2016-05-03 10:06:48,249 Node[0] Epoch[86] Resetting Data Iterator
2016-05-03 10:06:48,250 Node[0] Epoch[86] Time cost=81.780
2016-05-03 10:06:48,412 Node[0] Saved checkpoint to "cifar10/resnet-0087.params"
2016-05-03 10:06:50,378 Node[0] Epoch[86] Validation-accuracy=0.904647
2016-05-03 10:07:00,994 Node[0] Epoch[87] Batch [50] Speed: 606.00 samples/sec Train-accuracy=0.985625
2016-05-03 10:07:11,437 Node[0] Epoch[87] Batch [100] Speed: 612.90 samples/sec Train-accuracy=0.987500
2016-05-03 10:07:21,928 Node[0] Epoch[87] Batch [150] Speed: 610.06 samples/sec Train-accuracy=0.989062
2016-05-03 10:07:32,389 Node[0] Epoch[87] Batch [200] Speed: 611.81 samples/sec Train-accuracy=0.988125
2016-05-03 10:07:42,852 Node[0] Epoch[87] Batch [250] Speed: 611.71 samples/sec Train-accuracy=0.989062
2016-05-03 10:07:53,393 Node[0] Epoch[87] Batch [300] Speed: 607.13 samples/sec Train-accuracy=0.988750
2016-05-03 10:08:03,885 Node[0] Epoch[87] Batch [350] Speed: 610.05 samples/sec Train-accuracy=0.988125
2016-05-03 10:08:12,299 Node[0] Epoch[87] Resetting Data Iterator
2016-05-03 10:08:12,299 Node[0] Epoch[87] Time cost=81.921
2016-05-03 10:08:12,466 Node[0] Saved checkpoint to "cifar10/resnet-0088.params"
2016-05-03 10:08:14,399 Node[0] Epoch[87] Validation-accuracy=0.903846
2016-05-03 10:08:24,862 Node[0] Epoch[88] Batch [50] Speed: 614.93 samples/sec Train-accuracy=0.989062
2016-05-03 10:08:35,345 Node[0] Epoch[88] Batch [100] Speed: 610.53 samples/sec Train-accuracy=0.987031
2016-05-03 10:08:45,818 Node[0] Epoch[88] Batch [150] Speed: 611.10 samples/sec Train-accuracy=0.986875
2016-05-03 10:08:56,284 Node[0] Epoch[88] Batch [200] Speed: 611.52 samples/sec Train-accuracy=0.987344
2016-05-03 10:09:06,704 Node[0] Epoch[88] Batch [250] Speed: 614.21 samples/sec Train-accuracy=0.988750
2016-05-03 10:09:17,112 Node[0] Epoch[88] Batch [300] Speed: 614.95 samples/sec Train-accuracy=0.990469
2016-05-03 10:09:27,662 Node[0] Epoch[88] Batch [350] Speed: 606.64 samples/sec Train-accuracy=0.989531
2016-05-03 10:09:36,304 Node[0] Epoch[88] Resetting Data Iterator
2016-05-03 10:09:36,304 Node[0] Epoch[88] Time cost=81.905
2016-05-03 10:09:36,468 Node[0] Saved checkpoint to "cifar10/resnet-0089.params"
2016-05-03 10:09:38,721 Node[0] Epoch[88] Validation-accuracy=0.904173
2016-05-03 10:09:49,234 Node[0] Epoch[89] Batch [50] Speed: 612.02 samples/sec Train-accuracy=0.985156
2016-05-03 10:09:59,715 Node[0] Epoch[89] Batch [100] Speed: 610.65 samples/sec Train-accuracy=0.989844
2016-05-03 10:10:10,153 Node[0] Epoch[89] Batch [150] Speed: 613.13 samples/sec Train-accuracy=0.989688
2016-05-03 10:10:20,577 Node[0] Epoch[89] Batch [200] Speed: 613.98 samples/sec Train-accuracy=0.988750
2016-05-03 10:10:31,062 Node[0] Epoch[89] Batch [250] Speed: 610.39 samples/sec Train-accuracy=0.988594
2016-05-03 10:10:41,661 Node[0] Epoch[89] Batch [300] Speed: 603.87 samples/sec Train-accuracy=0.988906
2016-05-03 10:10:52,204 Node[0] Epoch[89] Batch [350] Speed: 607.04 samples/sec Train-accuracy=0.991250
2016-05-03 10:11:00,754 Node[0] Epoch[89] Resetting Data Iterator
2016-05-03 10:11:00,755 Node[0] Epoch[89] Time cost=82.033
2016-05-03 10:11:00,915 Node[0] Saved checkpoint to "cifar10/resnet-0090.params"
2016-05-03 10:11:02,809 Node[0] Epoch[89] Validation-accuracy=0.902344
2016-05-03 10:11:13,380 Node[0] Epoch[90] Batch [50] Speed: 608.61 samples/sec Train-accuracy=0.990625
2016-05-03 10:11:23,884 Node[0] Epoch[90] Batch [100] Speed: 609.31 samples/sec Train-accuracy=0.992656
2016-05-03 10:11:34,275 Node[0] Epoch[90] Batch [150] Speed: 615.89 samples/sec Train-accuracy=0.991406
2016-05-03 10:11:44,695 Node[0] Epoch[90] Batch [200] Speed: 614.24 samples/sec Train-accuracy=0.989844
2016-05-03 10:11:55,145 Node[0] Epoch[90] Batch [250] Speed: 612.48 samples/sec Train-accuracy=0.989844
2016-05-03 10:12:05,588 Node[0] Epoch[90] Batch [300] Speed: 612.87 samples/sec Train-accuracy=0.990156
2016-05-03 10:12:15,999 Node[0] Epoch[90] Batch [350] Speed: 614.75 samples/sec Train-accuracy=0.993125
2016-05-03 10:12:24,385 Node[0] Epoch[90] Resetting Data Iterator
2016-05-03 10:12:24,385 Node[0] Epoch[90] Time cost=81.576
2016-05-03 10:12:24,549 Node[0] Saved checkpoint to "cifar10/resnet-0091.params"
2016-05-03 10:12:26,520 Node[0] Epoch[90] Validation-accuracy=0.902143
2016-05-03 10:12:37,114 Node[0] Epoch[91] Batch [50] Speed: 607.35 samples/sec Train-accuracy=0.990313
2016-05-03 10:12:47,552 Node[0] Epoch[91] Batch [100] Speed: 613.15 samples/sec Train-accuracy=0.991094
2016-05-03 10:12:58,002 Node[0] Epoch[91] Batch [150] Speed: 612.45 samples/sec Train-accuracy=0.990469
2016-05-03 10:13:08,437 Node[0] Epoch[91] Batch [200] Speed: 613.32 samples/sec Train-accuracy=0.990625
2016-05-03 10:13:18,868 Node[0] Epoch[91] Batch [250] Speed: 613.59 samples/sec Train-accuracy=0.989219
2016-05-03 10:13:29,368 Node[0] Epoch[91] Batch [300] Speed: 609.53 samples/sec Train-accuracy=0.991094
2016-05-03 10:13:39,865 Node[0] Epoch[91] Batch [350] Speed: 609.75 samples/sec Train-accuracy=0.990000
2016-05-03 10:13:48,476 Node[0] Epoch[91] Resetting Data Iterator
2016-05-03 10:13:48,476 Node[0] Epoch[91] Time cost=81.956
2016-05-03 10:13:48,642 Node[0] Saved checkpoint to "cifar10/resnet-0092.params"
2016-05-03 10:13:50,542 Node[0] Epoch[91] Validation-accuracy=0.903846
2016-05-03 10:14:01,080 Node[0] Epoch[92] Batch [50] Speed: 610.54 samples/sec Train-accuracy=0.991094
2016-05-03 10:14:11,544 Node[0] Epoch[92] Batch [100] Speed: 611.63 samples/sec Train-accuracy=0.990938
2016-05-03 10:14:21,991 Node[0] Epoch[92] Batch [150] Speed: 612.64 samples/sec Train-accuracy=0.990000
2016-05-03 10:14:32,466 Node[0] Epoch[92] Batch [200] Speed: 611.01 samples/sec Train-accuracy=0.991094
2016-05-03 10:14:42,906 Node[0] Epoch[92] Batch [250] Speed: 613.03 samples/sec Train-accuracy=0.992188
2016-05-03 10:14:53,321 Node[0] Epoch[92] Batch [300] Speed: 614.50 samples/sec Train-accuracy=0.992344
2016-05-03 10:15:03,743 Node[0] Epoch[92] Batch [350] Speed: 614.09 samples/sec Train-accuracy=0.992812
2016-05-03 10:15:12,268 Node[0] Epoch[92] Resetting Data Iterator
2016-05-03 10:15:12,268 Node[0] Epoch[92] Time cost=81.727
2016-05-03 10:15:12,433 Node[0] Saved checkpoint to "cifar10/resnet-0093.params"
2016-05-03 10:15:14,387 Node[0] Epoch[92] Validation-accuracy=0.904447
2016-05-03 10:15:24,906 Node[0] Epoch[93] Batch [50] Speed: 611.63 samples/sec Train-accuracy=0.988437
2016-05-03 10:15:35,333 Node[0] Epoch[93] Batch [100] Speed: 613.80 samples/sec Train-accuracy=0.993125
2016-05-03 10:15:45,782 Node[0] Epoch[93] Batch [150] Speed: 612.53 samples/sec Train-accuracy=0.992656
2016-05-03 10:15:56,272 Node[0] Epoch[93] Batch [200] Speed: 610.11 samples/sec Train-accuracy=0.992500
2016-05-03 10:16:06,720 Node[0] Epoch[93] Batch [250] Speed: 612.59 samples/sec Train-accuracy=0.990625
2016-05-03 10:16:17,149 Node[0] Epoch[93] Batch [300] Speed: 613.71 samples/sec Train-accuracy=0.991563
2016-05-03 10:16:27,594 Node[0] Epoch[93] Batch [350] Speed: 612.73 samples/sec Train-accuracy=0.993594
2016-05-03 10:16:35,933 Node[0] Epoch[93] Resetting Data Iterator
2016-05-03 10:16:35,934 Node[0] Epoch[93] Time cost=81.547
2016-05-03 10:16:36,096 Node[0] Saved checkpoint to "cifar10/resnet-0094.params"
2016-05-03 10:16:38,067 Node[0] Epoch[93] Validation-accuracy=0.904447
2016-05-03 10:16:48,647 Node[0] Epoch[94] Batch [50] Speed: 608.08 samples/sec Train-accuracy=0.990625
2016-05-03 10:16:59,176 Node[0] Epoch[94] Batch [100] Speed: 607.90 samples/sec Train-accuracy=0.991563
2016-05-03 10:17:09,590 Node[0] Epoch[94] Batch [150] Speed: 614.58 samples/sec Train-accuracy=0.992031
2016-05-03 10:17:19,990 Node[0] Epoch[94] Batch [200] Speed: 615.40 samples/sec Train-accuracy=0.992031
2016-05-03 10:17:30,465 Node[0] Epoch[94] Batch [250] Speed: 610.94 samples/sec Train-accuracy=0.990000
2016-05-03 10:17:40,893 Node[0] Epoch[94] Batch [300] Speed: 613.76 samples/sec Train-accuracy=0.990313
2016-05-03 10:17:51,392 Node[0] Epoch[94] Batch [350] Speed: 609.63 samples/sec Train-accuracy=0.992656
2016-05-03 10:17:59,936 Node[0] Epoch[94] Resetting Data Iterator
2016-05-03 10:17:59,936 Node[0] Epoch[94] Time cost=81.868
2016-05-03 10:18:00,104 Node[0] Saved checkpoint to "cifar10/resnet-0095.params"
2016-05-03 10:18:02,063 Node[0] Epoch[94] Validation-accuracy=0.903646
2016-05-03 10:18:12,624 Node[0] Epoch[95] Batch [50] Speed: 609.22 samples/sec Train-accuracy=0.992344
2016-05-03 10:18:23,099 Node[0] Epoch[95] Batch [100] Speed: 610.97 samples/sec Train-accuracy=0.993594
2016-05-03 10:18:33,524 Node[0] Epoch[95] Batch [150] Speed: 613.93 samples/sec Train-accuracy=0.992188
2016-05-03 10:18:43,950 Node[0] Epoch[95] Batch [200] Speed: 613.85 samples/sec Train-accuracy=0.992500
2016-05-03 10:18:54,392 Node[0] Epoch[95] Batch [250] Speed: 612.96 samples/sec Train-accuracy=0.991094
2016-05-03 10:19:04,847 Node[0] Epoch[95] Batch [300] Speed: 612.15 samples/sec Train-accuracy=0.992656
2016-05-03 10:19:15,260 Node[0] Epoch[95] Batch [350] Speed: 614.61 samples/sec Train-accuracy=0.994531
2016-05-03 10:19:23,570 Node[0] Epoch[95] Resetting Data Iterator
2016-05-03 10:19:23,571 Node[0] Epoch[95] Time cost=81.508
2016-05-03 10:19:23,736 Node[0] Saved checkpoint to "cifar10/resnet-0096.params"
2016-05-03 10:19:25,691 Node[0] Epoch[95] Validation-accuracy=0.903345
2016-05-03 10:19:36,234 Node[0] Epoch[96] Batch [50] Speed: 610.39 samples/sec Train-accuracy=0.992500
2016-05-03 10:19:46,777 Node[0] Epoch[96] Batch [100] Speed: 607.08 samples/sec Train-accuracy=0.989531
2016-05-03 10:19:57,221 Node[0] Epoch[96] Batch [150] Speed: 612.78 samples/sec Train-accuracy=0.991875
2016-05-03 10:20:07,645 Node[0] Epoch[96] Batch [200] Speed: 613.99 samples/sec Train-accuracy=0.992969
2016-05-03 10:20:18,085 Node[0] Epoch[96] Batch [250] Speed: 613.01 samples/sec Train-accuracy=0.993281
2016-05-03 10:20:28,481 Node[0] Epoch[96] Batch [300] Speed: 615.64 samples/sec Train-accuracy=0.993594
2016-05-03 10:20:38,989 Node[0] Epoch[96] Batch [350] Speed: 609.10 samples/sec Train-accuracy=0.994687
2016-05-03 10:20:47,539 Node[0] Epoch[96] Resetting Data Iterator
2016-05-03 10:20:47,539 Node[0] Epoch[96] Time cost=81.848
2016-05-03 10:20:47,702 Node[0] Saved checkpoint to "cifar10/resnet-0097.params"
2016-05-03 10:20:49,850 Node[0] Epoch[96] Validation-accuracy=0.904964
2016-05-03 10:21:00,370 Node[0] Epoch[97] Batch [50] Speed: 611.61 samples/sec Train-accuracy=0.993437
2016-05-03 10:21:10,886 Node[0] Epoch[97] Batch [100] Speed: 608.62 samples/sec Train-accuracy=0.992969
2016-05-03 10:21:21,315 Node[0] Epoch[97] Batch [150] Speed: 613.72 samples/sec Train-accuracy=0.994062
2016-05-03 10:21:31,762 Node[0] Epoch[97] Batch [200] Speed: 612.60 samples/sec Train-accuracy=0.994687
2016-05-03 10:21:42,250 Node[0] Epoch[97] Batch [250] Speed: 610.24 samples/sec Train-accuracy=0.991563
2016-05-03 10:21:52,706 Node[0] Epoch[97] Batch [300] Speed: 612.10 samples/sec Train-accuracy=0.994844
2016-05-03 10:22:03,183 Node[0] Epoch[97] Batch [350] Speed: 610.88 samples/sec Train-accuracy=0.994531
2016-05-03 10:22:11,746 Node[0] Epoch[97] Resetting Data Iterator
2016-05-03 10:22:11,747 Node[0] Epoch[97] Time cost=81.896
2016-05-03 10:22:11,910 Node[0] Saved checkpoint to "cifar10/resnet-0098.params"
2016-05-03 10:22:13,885 Node[0] Epoch[97] Validation-accuracy=0.905349
2016-05-03 10:22:24,450 Node[0] Epoch[98] Batch [50] Speed: 608.95 samples/sec Train-accuracy=0.993750
2016-05-03 10:22:34,949 Node[0] Epoch[98] Batch [100] Speed: 609.60 samples/sec Train-accuracy=0.992812
2016-05-03 10:22:45,376 Node[0] Epoch[98] Batch [150] Speed: 613.81 samples/sec Train-accuracy=0.994531
2016-05-03 10:22:55,768 Node[0] Epoch[98] Batch [200] Speed: 615.87 samples/sec Train-accuracy=0.993594
2016-05-03 10:23:06,210 Node[0] Epoch[98] Batch [250] Speed: 612.95 samples/sec Train-accuracy=0.994687
2016-05-03 10:23:16,682 Node[0] Epoch[98] Batch [300] Speed: 611.15 samples/sec Train-accuracy=0.994375
2016-05-03 10:23:27,144 Node[0] Epoch[98] Batch [350] Speed: 611.77 samples/sec Train-accuracy=0.995469
2016-05-03 10:23:35,506 Node[0] Epoch[98] Resetting Data Iterator
2016-05-03 10:23:35,506 Node[0] Epoch[98] Time cost=81.621
2016-05-03 10:23:35,666 Node[0] Saved checkpoint to "cifar10/resnet-0099.params"
2016-05-03 10:23:37,625 Node[0] Epoch[98] Validation-accuracy=0.904347
2016-05-03 10:23:48,242 Node[0] Epoch[99] Batch [50] Speed: 605.94 samples/sec Train-accuracy=0.994062
2016-05-03 10:23:58,733 Node[0] Epoch[99] Batch [100] Speed: 610.11 samples/sec Train-accuracy=0.992969
2016-05-03 10:24:09,081 Node[0] Epoch[99] Batch [150] Speed: 618.46 samples/sec Train-accuracy=0.994062
2016-05-03 10:24:19,506 Node[0] Epoch[99] Batch [200] Speed: 613.94 samples/sec Train-accuracy=0.993281
2016-05-03 10:24:29,935 Node[0] Epoch[99] Batch [250] Speed: 613.69 samples/sec Train-accuracy=0.995313
2016-05-03 10:24:40,447 Node[0] Epoch[99] Batch [300] Speed: 608.84 samples/sec Train-accuracy=0.994062
2016-05-03 10:24:50,952 Node[0] Epoch[99] Batch [350] Speed: 609.27 samples/sec Train-accuracy=0.994531
2016-05-03 10:24:59,543 Node[0] Epoch[99] Resetting Data Iterator
2016-05-03 10:24:59,543 Node[0] Epoch[99] Time cost=81.918
2016-05-03 10:24:59,705 Node[0] Saved checkpoint to "cifar10/resnet-0100.params"
2016-05-03 10:25:01,667 Node[0] Epoch[99] Validation-accuracy=0.904046
2016-05-03 10:25:12,145 Node[0] Epoch[100] Batch [50] Speed: 614.04 samples/sec Train-accuracy=0.993125
2016-05-03 10:25:22,588 Node[0] Epoch[100] Batch [100] Speed: 612.91 samples/sec Train-accuracy=0.995000
2016-05-03 10:25:32,919 Node[0] Epoch[100] Batch [150] Speed: 619.51 samples/sec Train-accuracy=0.994687
2016-05-03 10:25:43,352 Node[0] Epoch[100] Batch [200] Speed: 613.46 samples/sec Train-accuracy=0.996563
2016-05-03 10:25:53,844 Node[0] Epoch[100] Batch [250] Speed: 609.98 samples/sec Train-accuracy=0.994531
2016-05-03 10:26:04,344 Node[0] Epoch[100] Batch [300] Speed: 609.55 samples/sec Train-accuracy=0.996250
2016-05-03 10:26:14,872 Node[0] Epoch[100] Batch [350] Speed: 607.91 samples/sec Train-accuracy=0.995781
2016-05-03 10:26:23,407 Node[0] Epoch[100] Resetting Data Iterator
2016-05-03 10:26:23,408 Node[0] Epoch[100] Time cost=81.740
2016-05-03 10:26:23,568 Node[0] Saved checkpoint to "cifar10/resnet-0101.params"
2016-05-03 10:26:25,514 Node[0] Epoch[100] Validation-accuracy=0.904848
2016-05-03 10:26:36,028 Node[0] Epoch[101] Batch [50] Speed: 611.99 samples/sec Train-accuracy=0.995156
2016-05-03 10:26:46,588 Node[0] Epoch[101] Batch [100] Speed: 606.07 samples/sec Train-accuracy=0.993906
2016-05-03 10:26:57,004 Node[0] Epoch[101] Batch [150] Speed: 614.44 samples/sec Train-accuracy=0.993594
2016-05-03 10:27:07,448 Node[0] Epoch[101] Batch [200] Speed: 612.81 samples/sec Train-accuracy=0.995156
2016-05-03 10:27:17,895 Node[0] Epoch[101] Batch [250] Speed: 612.61 samples/sec Train-accuracy=0.995781
2016-05-03 10:27:28,332 Node[0] Epoch[101] Batch [300] Speed: 613.25 samples/sec Train-accuracy=0.995313
2016-05-03 10:27:38,777 Node[0] Epoch[101] Batch [350] Speed: 612.74 samples/sec Train-accuracy=0.994375
2016-05-03 10:27:47,140 Node[0] Epoch[101] Resetting Data Iterator
2016-05-03 10:27:47,140 Node[0] Epoch[101] Time cost=81.626
2016-05-03 10:27:47,301 Node[0] Saved checkpoint to "cifar10/resnet-0102.params"
2016-05-03 10:27:49,217 Node[0] Epoch[101] Validation-accuracy=0.904447
2016-05-03 10:27:59,777 Node[0] Epoch[102] Batch [50] Speed: 609.28 samples/sec Train-accuracy=0.994219
2016-05-03 10:28:10,350 Node[0] Epoch[102] Batch [100] Speed: 605.28 samples/sec Train-accuracy=0.996094
2016-05-03 10:28:20,901 Node[0] Epoch[102] Batch [150] Speed: 606.62 samples/sec Train-accuracy=0.994062
2016-05-03 10:28:31,349 Node[0] Epoch[102] Batch [200] Speed: 612.59 samples/sec Train-accuracy=0.995469
2016-05-03 10:28:41,807 Node[0] Epoch[102] Batch [250] Speed: 611.95 samples/sec Train-accuracy=0.994531
2016-05-03 10:28:52,199 Node[0] Epoch[102] Batch [300] Speed: 615.89 samples/sec Train-accuracy=0.994219
2016-05-03 10:29:02,631 Node[0] Epoch[102] Batch [350] Speed: 613.54 samples/sec Train-accuracy=0.995000
2016-05-03 10:29:11,157 Node[0] Epoch[102] Resetting Data Iterator
2016-05-03 10:29:11,157 Node[0] Epoch[102] Time cost=81.940
2016-05-03 10:29:11,319 Node[0] Saved checkpoint to "cifar10/resnet-0103.params"
2016-05-03 10:29:13,265 Node[0] Epoch[102] Validation-accuracy=0.906851
2016-05-03 10:29:23,890 Node[0] Epoch[103] Batch [50] Speed: 605.61 samples/sec Train-accuracy=0.996094
2016-05-03 10:29:34,397 Node[0] Epoch[103] Batch [100] Speed: 609.16 samples/sec Train-accuracy=0.995938
2016-05-03 10:29:44,818 Node[0] Epoch[103] Batch [150] Speed: 614.12 samples/sec Train-accuracy=0.996406
2016-05-03 10:29:55,307 Node[0] Epoch[103] Batch [200] Speed: 610.19 samples/sec Train-accuracy=0.994844
2016-05-03 10:30:05,768 Node[0] Epoch[103] Batch [250] Speed: 611.81 samples/sec Train-accuracy=0.995000
2016-05-03 10:30:16,246 Node[0] Epoch[103] Batch [300] Speed: 610.82 samples/sec Train-accuracy=0.996094
2016-05-03 10:30:26,711 Node[0] Epoch[103] Batch [350] Speed: 611.56 samples/sec Train-accuracy=0.996250
2016-05-03 10:30:35,145 Node[0] Epoch[103] Resetting Data Iterator
2016-05-03 10:30:35,145 Node[0] Epoch[103] Time cost=81.879
2016-05-03 10:30:35,309 Node[0] Saved checkpoint to "cifar10/resnet-0104.params"
2016-05-03 10:30:37,244 Node[0] Epoch[103] Validation-accuracy=0.906150
2016-05-03 10:30:47,806 Node[0] Epoch[104] Batch [50] Speed: 609.22 samples/sec Train-accuracy=0.994687
2016-05-03 10:30:58,345 Node[0] Epoch[104] Batch [100] Speed: 607.30 samples/sec Train-accuracy=0.995938
2016-05-03 10:31:08,737 Node[0] Epoch[104] Batch [150] Speed: 615.86 samples/sec Train-accuracy=0.995313
2016-05-03 10:31:19,163 Node[0] Epoch[104] Batch [200] Speed: 613.88 samples/sec Train-accuracy=0.995938
2016-05-03 10:31:29,641 Node[0] Epoch[104] Batch [250] Speed: 610.80 samples/sec Train-accuracy=0.996094
2016-05-03 10:31:40,108 Node[0] Epoch[104] Batch [300] Speed: 611.50 samples/sec Train-accuracy=0.996406
2016-05-03 10:31:50,547 Node[0] Epoch[104] Batch [350] Speed: 613.05 samples/sec Train-accuracy=0.996719
2016-05-03 10:32:08,233 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 10:32:08,677 Node[0] Start training with [gpu(0)]
2016-05-03 10:32:29,622 Node[0] Epoch[0] Batch [50] Speed: 646.70 samples/sec Train-accuracy=0.104375
2016-05-03 10:32:39,752 Node[0] Epoch[0] Batch [100] Speed: 631.80 samples/sec Train-accuracy=0.105000
2016-05-03 10:32:49,941 Node[0] Epoch[0] Batch [150] Speed: 628.13 samples/sec Train-accuracy=0.099375
2016-05-03 10:33:00,765 Node[0] Epoch[0] Batch [200] Speed: 591.33 samples/sec Train-accuracy=0.126562
2016-05-03 10:33:11,817 Node[0] Epoch[0] Batch [250] Speed: 579.11 samples/sec Train-accuracy=0.127656
2016-05-03 10:33:22,917 Node[0] Epoch[0] Batch [300] Speed: 576.59 samples/sec Train-accuracy=0.142344
2016-05-03 10:33:33,992 Node[0] Epoch[0] Batch [350] Speed: 577.84 samples/sec Train-accuracy=0.170313
2016-05-03 10:33:43,095 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 10:33:43,095 Node[0] Epoch[0] Time cost=83.695
2016-05-03 10:33:43,273 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 10:33:45,428 Node[0] Epoch[0] Validation-accuracy=0.218453
2016-05-03 10:33:56,372 Node[0] Epoch[1] Batch [50] Speed: 587.81 samples/sec Train-accuracy=0.228594
2016-05-03 10:34:07,293 Node[0] Epoch[1] Batch [100] Speed: 586.04 samples/sec Train-accuracy=0.259375
2016-05-03 10:34:18,189 Node[0] Epoch[1] Batch [150] Speed: 587.42 samples/sec Train-accuracy=0.278750
2016-05-03 10:34:29,023 Node[0] Epoch[1] Batch [200] Speed: 590.73 samples/sec Train-accuracy=0.284062
2016-05-03 10:34:39,797 Node[0] Epoch[1] Batch [250] Speed: 594.04 samples/sec Train-accuracy=0.312188
2016-05-03 10:34:50,583 Node[0] Epoch[1] Batch [300] Speed: 593.38 samples/sec Train-accuracy=0.327500
2016-05-03 10:35:01,371 Node[0] Epoch[1] Batch [350] Speed: 593.29 samples/sec Train-accuracy=0.346562
2016-05-03 10:35:10,189 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 10:35:10,189 Node[0] Epoch[1] Time cost=84.761
2016-05-03 10:35:10,361 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 10:35:12,338 Node[0] Epoch[1] Validation-accuracy=0.349459
2016-05-03 10:35:23,224 Node[0] Epoch[2] Batch [50] Speed: 591.12 samples/sec Train-accuracy=0.383281
2016-05-03 10:35:33,968 Node[0] Epoch[2] Batch [100] Speed: 595.69 samples/sec Train-accuracy=0.392656
2016-05-03 10:35:44,717 Node[0] Epoch[2] Batch [150] Speed: 595.43 samples/sec Train-accuracy=0.411250
2016-05-03 10:35:55,432 Node[0] Epoch[2] Batch [200] Speed: 597.30 samples/sec Train-accuracy=0.418594
2016-05-03 10:36:06,102 Node[0] Epoch[2] Batch [250] Speed: 599.85 samples/sec Train-accuracy=0.431719
2016-05-03 10:36:16,769 Node[0] Epoch[2] Batch [300] Speed: 599.97 samples/sec Train-accuracy=0.439531
2016-05-03 10:36:27,516 Node[0] Epoch[2] Batch [350] Speed: 595.52 samples/sec Train-accuracy=0.443594
2016-05-03 10:36:36,065 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 10:36:36,066 Node[0] Epoch[2] Time cost=83.727
2016-05-03 10:36:36,231 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 10:36:38,180 Node[0] Epoch[2] Validation-accuracy=0.390725
2016-05-03 10:36:48,835 Node[0] Epoch[3] Batch [50] Speed: 603.83 samples/sec Train-accuracy=0.464375
2016-05-03 10:36:59,458 Node[0] Epoch[3] Batch [100] Speed: 602.52 samples/sec Train-accuracy=0.478281
2016-05-03 10:37:10,054 Node[0] Epoch[3] Batch [150] Speed: 604.01 samples/sec Train-accuracy=0.488281
2016-05-03 10:37:20,662 Node[0] Epoch[3] Batch [200] Speed: 603.34 samples/sec Train-accuracy=0.489687
2016-05-03 10:37:31,234 Node[0] Epoch[3] Batch [250] Speed: 605.36 samples/sec Train-accuracy=0.501406
2016-05-03 10:37:41,856 Node[0] Epoch[3] Batch [300] Speed: 602.57 samples/sec Train-accuracy=0.500781
2016-05-03 10:37:52,515 Node[0] Epoch[3] Batch [350] Speed: 600.45 samples/sec Train-accuracy=0.523750
2016-05-03 10:38:01,281 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 10:38:01,281 Node[0] Epoch[3] Time cost=83.100
2016-05-03 10:38:01,449 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 10:38:03,427 Node[0] Epoch[3] Validation-accuracy=0.520633
2016-05-03 10:38:14,079 Node[0] Epoch[4] Batch [50] Speed: 603.99 samples/sec Train-accuracy=0.535937
2016-05-03 10:38:24,714 Node[0] Epoch[4] Batch [100] Speed: 601.81 samples/sec Train-accuracy=0.550937
2016-05-03 10:38:35,350 Node[0] Epoch[4] Batch [150] Speed: 601.74 samples/sec Train-accuracy=0.567969
2016-05-03 10:38:45,965 Node[0] Epoch[4] Batch [200] Speed: 602.93 samples/sec Train-accuracy=0.572187
2016-05-03 10:38:56,578 Node[0] Epoch[4] Batch [250] Speed: 603.08 samples/sec Train-accuracy=0.568906
2016-05-03 10:39:07,186 Node[0] Epoch[4] Batch [300] Speed: 603.29 samples/sec Train-accuracy=0.580625
2016-05-03 10:39:17,761 Node[0] Epoch[4] Batch [350] Speed: 605.24 samples/sec Train-accuracy=0.594531
2016-05-03 10:39:26,419 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 10:39:26,419 Node[0] Epoch[4] Time cost=82.992
2016-05-03 10:39:26,585 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 10:39:28,533 Node[0] Epoch[4] Validation-accuracy=0.482672
2016-05-03 10:39:39,100 Node[0] Epoch[5] Batch [50] Speed: 608.78 samples/sec Train-accuracy=0.604531
2016-05-03 10:39:49,722 Node[0] Epoch[5] Batch [100] Speed: 602.53 samples/sec Train-accuracy=0.623437
2016-05-03 10:40:00,304 Node[0] Epoch[5] Batch [150] Speed: 604.84 samples/sec Train-accuracy=0.626094
2016-05-03 10:40:10,871 Node[0] Epoch[5] Batch [200] Speed: 605.66 samples/sec Train-accuracy=0.644531
2016-05-03 10:40:21,386 Node[0] Epoch[5] Batch [250] Speed: 608.66 samples/sec Train-accuracy=0.640938
2016-05-03 10:40:31,916 Node[0] Epoch[5] Batch [300] Speed: 607.78 samples/sec Train-accuracy=0.645312
2016-05-03 10:40:42,462 Node[0] Epoch[5] Batch [350] Speed: 606.89 samples/sec Train-accuracy=0.650312
2016-05-03 10:40:50,881 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 10:40:50,881 Node[0] Epoch[5] Time cost=82.348
2016-05-03 10:40:51,044 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 10:40:53,012 Node[0] Epoch[5] Validation-accuracy=0.590845
2016-05-03 10:41:03,664 Node[0] Epoch[6] Batch [50] Speed: 603.93 samples/sec Train-accuracy=0.665625
2016-05-03 10:41:14,245 Node[0] Epoch[6] Batch [100] Speed: 604.88 samples/sec Train-accuracy=0.668125
2016-05-03 10:41:24,812 Node[0] Epoch[6] Batch [150] Speed: 605.72 samples/sec Train-accuracy=0.681875
2016-05-03 10:41:35,351 Node[0] Epoch[6] Batch [200] Speed: 607.27 samples/sec Train-accuracy=0.679219
2016-05-03 10:41:45,904 Node[0] Epoch[6] Batch [250] Speed: 606.46 samples/sec Train-accuracy=0.683594
2016-05-03 10:41:56,430 Node[0] Epoch[6] Batch [300] Speed: 608.05 samples/sec Train-accuracy=0.687500
2016-05-03 10:42:06,941 Node[0] Epoch[6] Batch [350] Speed: 608.88 samples/sec Train-accuracy=0.703438
2016-05-03 10:42:15,573 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 10:42:15,573 Node[0] Epoch[6] Time cost=82.561
2016-05-03 10:42:15,736 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 10:42:17,675 Node[0] Epoch[6] Validation-accuracy=0.629407
2016-05-03 10:42:28,275 Node[0] Epoch[7] Batch [50] Speed: 606.96 samples/sec Train-accuracy=0.708125
2016-05-03 10:42:38,843 Node[0] Epoch[7] Batch [100] Speed: 605.66 samples/sec Train-accuracy=0.707031
2016-05-03 10:42:49,399 Node[0] Epoch[7] Batch [150] Speed: 606.26 samples/sec Train-accuracy=0.720000
2016-05-03 10:42:59,942 Node[0] Epoch[7] Batch [200] Speed: 607.09 samples/sec Train-accuracy=0.723281
2016-05-03 10:43:10,537 Node[0] Epoch[7] Batch [250] Speed: 604.04 samples/sec Train-accuracy=0.717344
2016-05-03 10:43:21,058 Node[0] Epoch[7] Batch [300] Speed: 608.34 samples/sec Train-accuracy=0.712344
2016-05-03 10:43:31,611 Node[0] Epoch[7] Batch [350] Speed: 606.51 samples/sec Train-accuracy=0.730000
2016-05-03 10:43:40,032 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 10:43:40,032 Node[0] Epoch[7] Time cost=82.356
2016-05-03 10:43:40,198 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 10:43:42,108 Node[0] Epoch[7] Validation-accuracy=0.660757
2016-05-03 10:43:52,609 Node[0] Epoch[8] Batch [50] Speed: 612.77 samples/sec Train-accuracy=0.728281
2016-05-03 10:44:03,117 Node[0] Epoch[8] Batch [100] Speed: 609.03 samples/sec Train-accuracy=0.733750
2016-05-03 10:44:13,549 Node[0] Epoch[8] Batch [150] Speed: 613.52 samples/sec Train-accuracy=0.740781
2016-05-03 10:44:24,050 Node[0] Epoch[8] Batch [200] Speed: 609.48 samples/sec Train-accuracy=0.739688
2016-05-03 10:44:34,551 Node[0] Epoch[8] Batch [250] Speed: 609.49 samples/sec Train-accuracy=0.741875
2016-05-03 10:44:45,140 Node[0] Epoch[8] Batch [300] Speed: 604.42 samples/sec Train-accuracy=0.743125
2016-05-03 10:44:55,693 Node[0] Epoch[8] Batch [350] Speed: 606.47 samples/sec Train-accuracy=0.744375
2016-05-03 10:45:04,277 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 10:45:04,278 Node[0] Epoch[8] Time cost=82.169
2016-05-03 10:45:04,444 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 10:45:06,525 Node[0] Epoch[8] Validation-accuracy=0.672765
2016-05-03 10:45:17,062 Node[0] Epoch[9] Batch [50] Speed: 610.53 samples/sec Train-accuracy=0.746094
2016-05-03 10:45:27,540 Node[0] Epoch[9] Batch [100] Speed: 610.82 samples/sec Train-accuracy=0.759219
2016-05-03 10:45:37,989 Node[0] Epoch[9] Batch [150] Speed: 612.50 samples/sec Train-accuracy=0.763750
2016-05-03 10:45:48,469 Node[0] Epoch[9] Batch [200] Speed: 610.73 samples/sec Train-accuracy=0.754219
2016-05-03 10:45:58,902 Node[0] Epoch[9] Batch [250] Speed: 613.43 samples/sec Train-accuracy=0.756250
2016-05-03 10:46:09,374 Node[0] Epoch[9] Batch [300] Speed: 611.20 samples/sec Train-accuracy=0.758906
2016-05-03 10:46:19,813 Node[0] Epoch[9] Batch [350] Speed: 613.08 samples/sec Train-accuracy=0.768437
2016-05-03 10:46:28,444 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 10:46:28,445 Node[0] Epoch[9] Time cost=81.920
2016-05-03 10:46:28,609 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 10:46:30,577 Node[0] Epoch[9] Validation-accuracy=0.691707
2016-05-03 10:46:41,162 Node[0] Epoch[10] Batch [50] Speed: 607.77 samples/sec Train-accuracy=0.764375
2016-05-03 10:46:51,683 Node[0] Epoch[10] Batch [100] Speed: 608.30 samples/sec Train-accuracy=0.775781
2016-05-03 10:47:02,108 Node[0] Epoch[10] Batch [150] Speed: 613.95 samples/sec Train-accuracy=0.777500
2016-05-03 10:47:12,567 Node[0] Epoch[10] Batch [200] Speed: 611.90 samples/sec Train-accuracy=0.778594
2016-05-03 10:47:23,038 Node[0] Epoch[10] Batch [250] Speed: 611.23 samples/sec Train-accuracy=0.771406
2016-05-03 10:47:33,520 Node[0] Epoch[10] Batch [300] Speed: 610.63 samples/sec Train-accuracy=0.775625
2016-05-03 10:47:43,930 Node[0] Epoch[10] Batch [350] Speed: 614.77 samples/sec Train-accuracy=0.780781
2016-05-03 10:47:52,308 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 10:47:52,308 Node[0] Epoch[10] Time cost=81.731
2016-05-03 10:47:52,471 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 10:47:54,461 Node[0] Epoch[10] Validation-accuracy=0.661859
2016-05-03 10:48:05,092 Node[0] Epoch[11] Batch [50] Speed: 605.22 samples/sec Train-accuracy=0.775156
2016-05-03 10:48:15,627 Node[0] Epoch[11] Batch [100] Speed: 607.48 samples/sec Train-accuracy=0.789844
2016-05-03 10:48:26,122 Node[0] Epoch[11] Batch [150] Speed: 609.87 samples/sec Train-accuracy=0.798125
2016-05-03 10:48:36,558 Node[0] Epoch[11] Batch [200] Speed: 613.24 samples/sec Train-accuracy=0.790625
2016-05-03 10:48:46,973 Node[0] Epoch[11] Batch [250] Speed: 614.56 samples/sec Train-accuracy=0.787813
2016-05-03 10:48:57,431 Node[0] Epoch[11] Batch [300] Speed: 611.94 samples/sec Train-accuracy=0.789375
2016-05-03 10:49:07,864 Node[0] Epoch[11] Batch [350] Speed: 613.46 samples/sec Train-accuracy=0.792500
2016-05-03 10:49:16,405 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 10:49:16,405 Node[0] Epoch[11] Time cost=81.944
2016-05-03 10:49:16,571 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 10:49:18,511 Node[0] Epoch[11] Validation-accuracy=0.676182
2016-05-03 10:49:29,099 Node[0] Epoch[12] Batch [50] Speed: 607.62 samples/sec Train-accuracy=0.798281
2016-05-03 10:49:39,548 Node[0] Epoch[12] Batch [100] Speed: 612.55 samples/sec Train-accuracy=0.799687
2016-05-03 10:49:50,021 Node[0] Epoch[12] Batch [150] Speed: 611.09 samples/sec Train-accuracy=0.812969
2016-05-03 10:50:00,472 Node[0] Epoch[12] Batch [200] Speed: 612.41 samples/sec Train-accuracy=0.796250
2016-05-03 10:50:10,912 Node[0] Epoch[12] Batch [250] Speed: 613.02 samples/sec Train-accuracy=0.799063
2016-05-03 10:50:21,315 Node[0] Epoch[12] Batch [300] Speed: 615.23 samples/sec Train-accuracy=0.810937
2016-05-03 10:50:31,784 Node[0] Epoch[12] Batch [350] Speed: 611.37 samples/sec Train-accuracy=0.807344
2016-05-03 10:50:40,346 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 10:50:40,347 Node[0] Epoch[12] Time cost=81.835
2016-05-03 10:50:40,512 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 10:50:42,479 Node[0] Epoch[12] Validation-accuracy=0.706130
2016-05-03 11:01:36,929 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:01:37,305 Node[0] Start training with [gpu(0)]
2016-05-03 11:01:58,570 Node[0] Epoch[0] Batch [50] Speed: 654.21 samples/sec Train-accuracy=0.106250
2016-05-03 11:02:08,563 Node[0] Epoch[0] Batch [100] Speed: 640.46 samples/sec Train-accuracy=0.178437
2016-05-03 11:02:18,574 Node[0] Epoch[0] Batch [150] Speed: 639.33 samples/sec Train-accuracy=0.232656
2016-05-03 11:02:28,705 Node[0] Epoch[0] Batch [200] Speed: 631.73 samples/sec Train-accuracy=0.264219
2016-05-03 11:02:38,744 Node[0] Epoch[0] Batch [250] Speed: 637.53 samples/sec Train-accuracy=0.287813
2016-05-03 11:02:48,819 Node[0] Epoch[0] Batch [300] Speed: 635.27 samples/sec Train-accuracy=0.319219
2016-05-03 11:02:58,935 Node[0] Epoch[0] Batch [350] Speed: 632.70 samples/sec Train-accuracy=0.330000
2016-05-03 11:03:07,442 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:03:07,443 Node[0] Epoch[0] Time cost=78.997
2016-05-03 11:03:07,608 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:03:09,786 Node[0] Epoch[0] Validation-accuracy=0.323873
2016-05-03 11:03:20,558 Node[0] Epoch[1] Batch [50] Speed: 597.29 samples/sec Train-accuracy=0.368750
2016-05-03 11:03:31,144 Node[0] Epoch[1] Batch [100] Speed: 604.57 samples/sec Train-accuracy=0.402500
2016-05-03 11:03:41,676 Node[0] Epoch[1] Batch [150] Speed: 607.73 samples/sec Train-accuracy=0.406719
2016-05-03 11:03:52,192 Node[0] Epoch[1] Batch [200] Speed: 608.61 samples/sec Train-accuracy=0.407187
2016-05-03 11:04:02,728 Node[0] Epoch[1] Batch [250] Speed: 607.43 samples/sec Train-accuracy=0.430312
2016-05-03 11:04:13,322 Node[0] Epoch[1] Batch [300] Speed: 604.12 samples/sec Train-accuracy=0.433906
2016-05-03 11:04:23,901 Node[0] Epoch[1] Batch [350] Speed: 605.03 samples/sec Train-accuracy=0.441406
2016-05-03 11:04:32,514 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:04:32,515 Node[0] Epoch[1] Time cost=82.728
2016-05-03 11:04:32,678 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:04:34,662 Node[0] Epoch[1] Validation-accuracy=0.470353
2016-05-03 11:04:45,388 Node[0] Epoch[2] Batch [50] Speed: 599.77 samples/sec Train-accuracy=0.466094
2016-05-03 11:05:06,278 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:05:06,627 Node[0] Start training with [gpu(0)]
2016-05-03 11:05:27,530 Node[0] Epoch[0] Batch [50] Speed: 648.99 samples/sec Train-accuracy=0.121406
2016-05-03 11:05:37,602 Node[0] Epoch[0] Batch [100] Speed: 635.41 samples/sec Train-accuracy=0.128906
2016-05-03 11:05:47,629 Node[0] Epoch[0] Batch [150] Speed: 638.30 samples/sec Train-accuracy=0.170156
2016-05-03 11:05:57,942 Node[0] Epoch[0] Batch [200] Speed: 620.57 samples/sec Train-accuracy=0.200469
2016-05-03 11:06:08,798 Node[0] Epoch[0] Batch [250] Speed: 589.59 samples/sec Train-accuracy=0.252812
2016-05-03 11:06:19,667 Node[0] Epoch[0] Batch [300] Speed: 588.81 samples/sec Train-accuracy=0.283281
2016-05-03 11:06:30,514 Node[0] Epoch[0] Batch [350] Speed: 590.06 samples/sec Train-accuracy=0.312812
2016-05-03 11:06:39,387 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:06:39,387 Node[0] Epoch[0] Time cost=81.985
2016-05-03 11:06:39,554 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:06:41,718 Node[0] Epoch[0] Validation-accuracy=0.325356
2016-05-03 11:06:52,398 Node[0] Epoch[1] Batch [50] Speed: 602.42 samples/sec Train-accuracy=0.349219
2016-05-03 11:07:03,099 Node[0] Epoch[1] Batch [100] Speed: 598.08 samples/sec Train-accuracy=0.385937
2016-05-03 11:07:13,794 Node[0] Epoch[1] Batch [150] Speed: 598.42 samples/sec Train-accuracy=0.400469
2016-05-03 11:07:24,491 Node[0] Epoch[1] Batch [200] Speed: 598.29 samples/sec Train-accuracy=0.397188
2016-05-03 11:07:35,168 Node[0] Epoch[1] Batch [250] Speed: 599.47 samples/sec Train-accuracy=0.429375
2016-05-03 11:07:45,851 Node[0] Epoch[1] Batch [300] Speed: 599.07 samples/sec Train-accuracy=0.432656
2016-05-03 11:07:56,516 Node[0] Epoch[1] Batch [350] Speed: 600.11 samples/sec Train-accuracy=0.446406
2016-05-03 11:08:05,287 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:08:05,287 Node[0] Epoch[1] Time cost=83.569
2016-05-03 11:08:05,457 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:08:07,434 Node[0] Epoch[1] Validation-accuracy=0.411659
2016-05-03 11:08:41,787 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:08:42,129 Node[0] Start training with [gpu(0)]
2016-05-03 11:09:02,977 Node[0] Epoch[0] Batch [50] Speed: 649.00 samples/sec Train-accuracy=0.096406
2016-05-03 11:09:13,058 Node[0] Epoch[0] Batch [100] Speed: 634.88 samples/sec Train-accuracy=0.109219
2016-05-03 11:09:23,144 Node[0] Epoch[0] Batch [150] Speed: 634.51 samples/sec Train-accuracy=0.127656
2016-05-03 11:09:33,618 Node[0] Epoch[0] Batch [200] Speed: 611.09 samples/sec Train-accuracy=0.185312
2016-05-03 11:09:44,546 Node[0] Epoch[0] Batch [250] Speed: 585.62 samples/sec Train-accuracy=0.219219
2016-05-03 11:09:55,540 Node[0] Epoch[0] Batch [300] Speed: 582.19 samples/sec Train-accuracy=0.252031
2016-05-03 11:10:06,581 Node[0] Epoch[0] Batch [350] Speed: 579.67 samples/sec Train-accuracy=0.263906
2016-05-03 11:10:15,602 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:10:15,602 Node[0] Epoch[0] Time cost=82.760
2016-05-03 11:10:15,780 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:10:17,935 Node[0] Epoch[0] Validation-accuracy=0.245253
2016-05-03 11:10:28,813 Node[0] Epoch[1] Batch [50] Speed: 591.50 samples/sec Train-accuracy=0.310781
2016-05-03 11:10:39,670 Node[0] Epoch[1] Batch [100] Speed: 589.50 samples/sec Train-accuracy=0.343438
2016-05-03 11:10:50,454 Node[0] Epoch[1] Batch [150] Speed: 593.47 samples/sec Train-accuracy=0.361406
2016-05-03 11:11:01,239 Node[0] Epoch[1] Batch [200] Speed: 593.43 samples/sec Train-accuracy=0.374219
2016-05-03 11:11:11,985 Node[0] Epoch[1] Batch [250] Speed: 595.61 samples/sec Train-accuracy=0.396875
2016-05-03 11:11:22,732 Node[0] Epoch[1] Batch [300] Speed: 595.50 samples/sec Train-accuracy=0.399219
2016-05-03 11:11:33,510 Node[0] Epoch[1] Batch [350] Speed: 593.80 samples/sec Train-accuracy=0.407187
2016-05-03 11:11:42,354 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:11:42,354 Node[0] Epoch[1] Time cost=84.419
2016-05-03 11:11:42,524 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:11:44,454 Node[0] Epoch[1] Validation-accuracy=0.402544
2016-05-03 11:13:02,379 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:13:24,582 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:13:31,559 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:13:31,994 Node[0] Start training with [gpu(0)]
2016-05-03 11:13:52,895 Node[0] Epoch[0] Batch [50] Speed: 655.68 samples/sec Train-accuracy=0.103281
2016-05-03 11:14:02,951 Node[0] Epoch[0] Batch [100] Speed: 636.45 samples/sec Train-accuracy=0.109844
2016-05-03 11:14:13,005 Node[0] Epoch[0] Batch [150] Speed: 636.57 samples/sec Train-accuracy=0.125312
2016-05-03 11:14:23,094 Node[0] Epoch[0] Batch [200] Speed: 634.37 samples/sec Train-accuracy=0.158438
2016-05-03 11:14:33,194 Node[0] Epoch[0] Batch [250] Speed: 633.70 samples/sec Train-accuracy=0.185000
2016-05-03 11:14:43,829 Node[0] Epoch[0] Batch [300] Speed: 601.80 samples/sec Train-accuracy=0.230937
2016-05-03 11:14:54,575 Node[0] Epoch[0] Batch [350] Speed: 595.56 samples/sec Train-accuracy=0.282187
2016-05-03 11:15:03,375 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:15:03,376 Node[0] Epoch[0] Time cost=80.505
2016-05-03 11:15:03,542 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:15:05,817 Node[0] Epoch[0] Validation-accuracy=0.330795
2016-05-03 11:15:16,734 Node[0] Epoch[1] Batch [50] Speed: 589.28 samples/sec Train-accuracy=0.344687
2016-05-03 11:15:27,476 Node[0] Epoch[1] Batch [100] Speed: 595.84 samples/sec Train-accuracy=0.372031
2016-05-03 11:15:38,152 Node[0] Epoch[1] Batch [150] Speed: 599.46 samples/sec Train-accuracy=0.396406
2016-05-03 11:15:48,847 Node[0] Epoch[1] Batch [200] Speed: 598.41 samples/sec Train-accuracy=0.409219
2016-05-03 11:15:59,528 Node[0] Epoch[1] Batch [250] Speed: 599.23 samples/sec Train-accuracy=0.440469
2016-05-03 11:16:10,173 Node[0] Epoch[1] Batch [300] Speed: 601.25 samples/sec Train-accuracy=0.462500
2016-05-03 11:16:20,823 Node[0] Epoch[1] Batch [350] Speed: 600.94 samples/sec Train-accuracy=0.488906
2016-05-03 11:16:29,541 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:16:29,542 Node[0] Epoch[1] Time cost=83.725
2016-05-03 11:16:29,710 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:16:31,703 Node[0] Epoch[1] Validation-accuracy=0.512821
2016-05-03 11:16:42,429 Node[0] Epoch[2] Batch [50] Speed: 599.83 samples/sec Train-accuracy=0.516875
2016-05-03 11:16:53,085 Node[0] Epoch[2] Batch [100] Speed: 600.59 samples/sec Train-accuracy=0.539062
2016-05-03 11:17:03,721 Node[0] Epoch[2] Batch [150] Speed: 601.76 samples/sec Train-accuracy=0.533125
2016-05-03 11:17:14,299 Node[0] Epoch[2] Batch [200] Speed: 605.02 samples/sec Train-accuracy=0.545781
2016-05-03 11:17:24,879 Node[0] Epoch[2] Batch [250] Speed: 604.96 samples/sec Train-accuracy=0.560781
2016-05-03 11:17:35,438 Node[0] Epoch[2] Batch [300] Speed: 606.10 samples/sec Train-accuracy=0.573125
2016-05-03 11:17:45,993 Node[0] Epoch[2] Batch [350] Speed: 606.39 samples/sec Train-accuracy=0.577969
2016-05-03 11:17:54,460 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 11:17:54,460 Node[0] Epoch[2] Time cost=82.757
2016-05-03 11:17:54,632 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 11:17:56,628 Node[0] Epoch[2] Validation-accuracy=0.592748
2016-05-03 11:18:07,343 Node[0] Epoch[3] Batch [50] Speed: 600.45 samples/sec Train-accuracy=0.595000
2016-05-03 11:18:17,944 Node[0] Epoch[3] Batch [100] Speed: 603.77 samples/sec Train-accuracy=0.605781
2016-05-03 11:18:28,469 Node[0] Epoch[3] Batch [150] Speed: 608.08 samples/sec Train-accuracy=0.621250
2016-05-03 11:18:38,951 Node[0] Epoch[3] Batch [200] Speed: 610.61 samples/sec Train-accuracy=0.617500
2016-05-03 11:18:49,423 Node[0] Epoch[3] Batch [250] Speed: 611.13 samples/sec Train-accuracy=0.622031
2016-05-03 11:18:59,894 Node[0] Epoch[3] Batch [300] Speed: 611.24 samples/sec Train-accuracy=0.625469
2016-05-03 11:19:10,422 Node[0] Epoch[3] Batch [350] Speed: 607.93 samples/sec Train-accuracy=0.641094
2016-05-03 11:19:19,046 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 11:19:19,046 Node[0] Epoch[3] Time cost=82.417
2016-05-03 11:19:19,211 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 11:19:21,160 Node[0] Epoch[3] Validation-accuracy=0.626302
2016-05-03 11:19:31,716 Node[0] Epoch[4] Batch [50] Speed: 609.51 samples/sec Train-accuracy=0.648594
2016-05-03 11:19:42,277 Node[0] Epoch[4] Batch [100] Speed: 605.99 samples/sec Train-accuracy=0.651563
2016-05-03 11:19:52,789 Node[0] Epoch[4] Batch [150] Speed: 608.86 samples/sec Train-accuracy=0.669687
2016-05-03 11:20:03,289 Node[0] Epoch[4] Batch [200] Speed: 609.53 samples/sec Train-accuracy=0.665156
2016-05-03 11:20:13,779 Node[0] Epoch[4] Batch [250] Speed: 610.12 samples/sec Train-accuracy=0.672500
2016-05-03 11:20:24,290 Node[0] Epoch[4] Batch [300] Speed: 608.94 samples/sec Train-accuracy=0.680781
2016-05-03 11:20:34,801 Node[0] Epoch[4] Batch [350] Speed: 608.88 samples/sec Train-accuracy=0.684688
2016-05-03 11:20:43,420 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 11:20:43,420 Node[0] Epoch[4] Time cost=82.260
2016-05-03 11:20:43,585 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 11:20:45,511 Node[0] Epoch[4] Validation-accuracy=0.670773
2016-05-03 11:20:56,044 Node[0] Epoch[5] Batch [50] Speed: 610.81 samples/sec Train-accuracy=0.688125
2016-05-03 11:21:06,632 Node[0] Epoch[5] Batch [100] Speed: 604.51 samples/sec Train-accuracy=0.699531
2016-05-03 11:21:17,071 Node[0] Epoch[5] Batch [150] Speed: 613.05 samples/sec Train-accuracy=0.704844
2016-05-03 11:21:27,444 Node[0] Epoch[5] Batch [200] Speed: 617.00 samples/sec Train-accuracy=0.710625
2016-05-03 11:21:37,897 Node[0] Epoch[5] Batch [250] Speed: 612.29 samples/sec Train-accuracy=0.700937
2016-05-03 11:21:48,421 Node[0] Epoch[5] Batch [300] Speed: 608.17 samples/sec Train-accuracy=0.714219
2016-05-03 11:21:58,880 Node[0] Epoch[5] Batch [350] Speed: 611.90 samples/sec Train-accuracy=0.717812
2016-05-03 11:22:07,292 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 11:22:07,292 Node[0] Epoch[5] Time cost=81.780
2016-05-03 11:22:07,456 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 11:22:09,363 Node[0] Epoch[5] Validation-accuracy=0.708233
2016-05-03 11:22:19,712 Node[0] Epoch[6] Batch [50] Speed: 621.68 samples/sec Train-accuracy=0.720156
2016-05-03 11:22:30,062 Node[0] Epoch[6] Batch [100] Speed: 618.41 samples/sec Train-accuracy=0.732187
2016-05-03 11:22:40,572 Node[0] Epoch[6] Batch [150] Speed: 608.95 samples/sec Train-accuracy=0.744844
2016-05-03 11:22:51,013 Node[0] Epoch[6] Batch [200] Speed: 613.00 samples/sec Train-accuracy=0.746094
2016-05-03 11:23:01,449 Node[0] Epoch[6] Batch [250] Speed: 613.25 samples/sec Train-accuracy=0.733750
2016-05-03 11:23:11,888 Node[0] Epoch[6] Batch [300] Speed: 613.11 samples/sec Train-accuracy=0.745781
2016-05-03 11:23:22,285 Node[0] Epoch[6] Batch [350] Speed: 615.59 samples/sec Train-accuracy=0.749531
2016-05-03 11:23:30,829 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 11:23:30,829 Node[0] Epoch[6] Time cost=81.467
2016-05-03 11:23:30,997 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 11:23:32,921 Node[0] Epoch[6] Validation-accuracy=0.720753
2016-05-03 11:23:43,419 Node[0] Epoch[7] Batch [50] Speed: 612.84 samples/sec Train-accuracy=0.739531
2016-05-03 11:23:53,893 Node[0] Epoch[7] Batch [100] Speed: 611.06 samples/sec Train-accuracy=0.756563
2016-05-03 11:24:04,320 Node[0] Epoch[7] Batch [150] Speed: 613.82 samples/sec Train-accuracy=0.761719
2016-05-03 11:24:14,778 Node[0] Epoch[7] Batch [200] Speed: 612.01 samples/sec Train-accuracy=0.758906
2016-05-03 11:24:25,218 Node[0] Epoch[7] Batch [250] Speed: 613.04 samples/sec Train-accuracy=0.750938
2016-05-03 11:24:35,634 Node[0] Epoch[7] Batch [300] Speed: 614.46 samples/sec Train-accuracy=0.758437
2016-05-03 11:24:46,019 Node[0] Epoch[7] Batch [350] Speed: 616.26 samples/sec Train-accuracy=0.768906
2016-05-03 11:24:54,357 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 11:24:54,357 Node[0] Epoch[7] Time cost=81.437
2016-05-03 11:24:54,524 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 11:24:56,466 Node[0] Epoch[7] Validation-accuracy=0.683994
2016-05-03 11:25:07,013 Node[0] Epoch[8] Batch [50] Speed: 610.15 samples/sec Train-accuracy=0.764375
2016-05-03 11:25:17,406 Node[0] Epoch[8] Batch [100] Speed: 615.84 samples/sec Train-accuracy=0.777344
2016-05-03 11:25:27,802 Node[0] Epoch[8] Batch [150] Speed: 615.63 samples/sec Train-accuracy=0.781563
2016-05-03 11:25:38,236 Node[0] Epoch[8] Batch [200] Speed: 613.41 samples/sec Train-accuracy=0.769531
2016-05-03 11:25:48,628 Node[0] Epoch[8] Batch [250] Speed: 615.84 samples/sec Train-accuracy=0.773906
2016-05-03 11:25:59,042 Node[0] Epoch[8] Batch [300] Speed: 614.61 samples/sec Train-accuracy=0.786563
2016-05-03 11:26:09,450 Node[0] Epoch[8] Batch [350] Speed: 614.94 samples/sec Train-accuracy=0.775625
2016-05-03 11:26:17,941 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 11:26:17,941 Node[0] Epoch[8] Time cost=81.475
2016-05-03 11:26:18,105 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 11:26:20,181 Node[0] Epoch[8] Validation-accuracy=0.715190
2016-05-03 11:26:30,664 Node[0] Epoch[9] Batch [50] Speed: 613.71 samples/sec Train-accuracy=0.778125
2016-05-03 11:26:41,140 Node[0] Epoch[9] Batch [100] Speed: 610.93 samples/sec Train-accuracy=0.791250
2016-05-03 11:26:51,548 Node[0] Epoch[9] Batch [150] Speed: 614.95 samples/sec Train-accuracy=0.793125
2016-05-03 11:27:01,934 Node[0] Epoch[9] Batch [200] Speed: 616.23 samples/sec Train-accuracy=0.790156
2016-05-03 11:27:12,367 Node[0] Epoch[9] Batch [250] Speed: 613.44 samples/sec Train-accuracy=0.778125
2016-05-03 11:27:22,789 Node[0] Epoch[9] Batch [300] Speed: 614.11 samples/sec Train-accuracy=0.797031
2016-05-03 11:27:33,180 Node[0] Epoch[9] Batch [350] Speed: 615.89 samples/sec Train-accuracy=0.796094
2016-05-03 11:27:41,732 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 11:27:41,733 Node[0] Epoch[9] Time cost=81.552
2016-05-03 11:27:41,895 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 11:27:43,846 Node[0] Epoch[9] Validation-accuracy=0.704928
2016-05-03 11:27:54,362 Node[0] Epoch[10] Batch [50] Speed: 611.75 samples/sec Train-accuracy=0.792813
2016-05-03 11:28:04,752 Node[0] Epoch[10] Batch [100] Speed: 615.99 samples/sec Train-accuracy=0.801875
2016-05-03 11:28:15,166 Node[0] Epoch[10] Batch [150] Speed: 614.60 samples/sec Train-accuracy=0.806562
2016-05-03 11:28:25,574 Node[0] Epoch[10] Batch [200] Speed: 614.94 samples/sec Train-accuracy=0.803281
2016-05-03 11:28:35,979 Node[0] Epoch[10] Batch [250] Speed: 615.06 samples/sec Train-accuracy=0.799531
2016-05-03 11:28:46,353 Node[0] Epoch[10] Batch [300] Speed: 617.00 samples/sec Train-accuracy=0.807344
2016-05-03 11:28:56,765 Node[0] Epoch[10] Batch [350] Speed: 614.68 samples/sec Train-accuracy=0.806094
2016-05-03 11:29:05,084 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 11:29:05,084 Node[0] Epoch[10] Time cost=81.238
2016-05-03 11:29:05,250 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 11:29:07,206 Node[0] Epoch[10] Validation-accuracy=0.720853
2016-05-03 11:29:17,684 Node[0] Epoch[11] Batch [50] Speed: 614.09 samples/sec Train-accuracy=0.806719
2016-05-03 11:29:28,096 Node[0] Epoch[11] Batch [100] Speed: 614.67 samples/sec Train-accuracy=0.806875
2016-05-03 11:29:38,463 Node[0] Epoch[11] Batch [150] Speed: 617.42 samples/sec Train-accuracy=0.818750
2016-05-03 11:29:48,891 Node[0] Epoch[11] Batch [200] Speed: 613.71 samples/sec Train-accuracy=0.811094
2016-05-03 11:29:59,305 Node[0] Epoch[11] Batch [250] Speed: 614.59 samples/sec Train-accuracy=0.813594
2016-05-03 11:30:09,737 Node[0] Epoch[11] Batch [300] Speed: 613.48 samples/sec Train-accuracy=0.810469
2016-05-03 11:30:20,151 Node[0] Epoch[11] Batch [350] Speed: 614.59 samples/sec Train-accuracy=0.824531
2016-05-03 11:30:28,701 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 11:30:28,702 Node[0] Epoch[11] Time cost=81.495
2016-05-03 11:30:28,869 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 11:30:30,821 Node[0] Epoch[11] Validation-accuracy=0.707232
2016-05-03 11:30:41,260 Node[0] Epoch[12] Batch [50] Speed: 616.37 samples/sec Train-accuracy=0.813594
2016-05-03 11:30:51,674 Node[0] Epoch[12] Batch [100] Speed: 614.59 samples/sec Train-accuracy=0.828906
2016-05-03 11:31:02,061 Node[0] Epoch[12] Batch [150] Speed: 616.16 samples/sec Train-accuracy=0.829375
2016-05-03 11:31:12,478 Node[0] Epoch[12] Batch [200] Speed: 614.35 samples/sec Train-accuracy=0.825313
2016-05-03 11:31:22,848 Node[0] Epoch[12] Batch [250] Speed: 617.23 samples/sec Train-accuracy=0.822187
2016-05-03 11:31:33,283 Node[0] Epoch[12] Batch [300] Speed: 613.31 samples/sec Train-accuracy=0.819688
2016-05-03 11:31:43,734 Node[0] Epoch[12] Batch [350] Speed: 612.39 samples/sec Train-accuracy=0.824844
2016-05-03 11:31:52,270 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 11:31:52,271 Node[0] Epoch[12] Time cost=81.449
2016-05-03 11:31:52,437 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 11:31:54,386 Node[0] Epoch[12] Validation-accuracy=0.739583
2016-05-03 11:32:04,879 Node[0] Epoch[13] Batch [50] Speed: 613.21 samples/sec Train-accuracy=0.827031
2016-05-03 11:32:15,324 Node[0] Epoch[13] Batch [100] Speed: 612.79 samples/sec Train-accuracy=0.833750
2016-05-03 11:32:25,765 Node[0] Epoch[13] Batch [150] Speed: 612.95 samples/sec Train-accuracy=0.835000
2016-05-03 11:32:36,166 Node[0] Epoch[13] Batch [200] Speed: 615.35 samples/sec Train-accuracy=0.832969
2016-05-03 11:32:46,583 Node[0] Epoch[13] Batch [250] Speed: 614.42 samples/sec Train-accuracy=0.832187
2016-05-03 11:32:57,003 Node[0] Epoch[13] Batch [300] Speed: 614.19 samples/sec Train-accuracy=0.836562
2016-05-03 11:33:07,447 Node[0] Epoch[13] Batch [350] Speed: 612.84 samples/sec Train-accuracy=0.839375
2016-05-03 11:33:15,760 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 11:33:15,760 Node[0] Epoch[13] Time cost=81.374
2016-05-03 11:33:15,927 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 11:33:17,890 Node[0] Epoch[13] Validation-accuracy=0.705128
2016-05-03 11:33:28,338 Node[0] Epoch[14] Batch [50] Speed: 615.78 samples/sec Train-accuracy=0.833750
2016-05-03 11:33:38,730 Node[0] Epoch[14] Batch [100] Speed: 615.87 samples/sec Train-accuracy=0.838594
2016-05-03 11:33:49,115 Node[0] Epoch[14] Batch [150] Speed: 616.31 samples/sec Train-accuracy=0.836250
2016-05-03 11:33:59,508 Node[0] Epoch[14] Batch [200] Speed: 615.78 samples/sec Train-accuracy=0.835938
2016-05-03 11:34:09,915 Node[0] Epoch[14] Batch [250] Speed: 615.00 samples/sec Train-accuracy=0.835313
2016-05-03 11:34:20,300 Node[0] Epoch[14] Batch [300] Speed: 616.31 samples/sec Train-accuracy=0.833438
2016-05-03 11:34:30,705 Node[0] Epoch[14] Batch [350] Speed: 615.10 samples/sec Train-accuracy=0.842344
2016-05-03 11:34:39,235 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 11:34:39,235 Node[0] Epoch[14] Time cost=81.345
2016-05-03 11:34:39,399 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 11:34:41,317 Node[0] Epoch[14] Validation-accuracy=0.669772
2016-05-03 11:34:51,814 Node[0] Epoch[15] Batch [50] Speed: 612.97 samples/sec Train-accuracy=0.840469
2016-05-03 11:35:02,195 Node[0] Epoch[15] Batch [100] Speed: 616.52 samples/sec Train-accuracy=0.848125
2016-05-03 11:35:12,522 Node[0] Epoch[15] Batch [150] Speed: 619.77 samples/sec Train-accuracy=0.845781
2016-05-03 11:35:22,857 Node[0] Epoch[15] Batch [200] Speed: 619.30 samples/sec Train-accuracy=0.849375
2016-05-03 11:35:33,242 Node[0] Epoch[15] Batch [250] Speed: 616.26 samples/sec Train-accuracy=0.835625
2016-05-03 11:35:43,589 Node[0] Epoch[15] Batch [300] Speed: 618.58 samples/sec Train-accuracy=0.845625
2016-05-03 11:35:53,982 Node[0] Epoch[15] Batch [350] Speed: 615.80 samples/sec Train-accuracy=0.852500
2016-05-03 11:36:02,260 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 11:36:02,261 Node[0] Epoch[15] Time cost=80.943
2016-05-03 11:36:02,425 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 11:36:04,365 Node[0] Epoch[15] Validation-accuracy=0.727764
2016-05-03 11:36:14,884 Node[0] Epoch[16] Batch [50] Speed: 611.61 samples/sec Train-accuracy=0.844063
2016-05-03 11:36:25,328 Node[0] Epoch[16] Batch [100] Speed: 612.82 samples/sec Train-accuracy=0.854688
2016-05-03 11:36:35,653 Node[0] Epoch[16] Batch [150] Speed: 619.84 samples/sec Train-accuracy=0.859844
2016-05-03 11:36:45,956 Node[0] Epoch[16] Batch [200] Speed: 621.24 samples/sec Train-accuracy=0.854062
2016-05-03 11:36:56,253 Node[0] Epoch[16] Batch [250] Speed: 621.52 samples/sec Train-accuracy=0.852500
2016-05-03 11:37:06,722 Node[0] Epoch[16] Batch [300] Speed: 611.37 samples/sec Train-accuracy=0.857500
2016-05-03 11:37:17,201 Node[0] Epoch[16] Batch [350] Speed: 610.76 samples/sec Train-accuracy=0.850938
2016-05-03 11:37:25,709 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 11:37:25,709 Node[0] Epoch[16] Time cost=81.344
2016-05-03 11:37:25,871 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 11:37:28,000 Node[0] Epoch[16] Validation-accuracy=0.696598
2016-05-03 11:37:38,388 Node[0] Epoch[17] Batch [50] Speed: 619.34 samples/sec Train-accuracy=0.850938
2016-05-03 11:38:35,452 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:38:35,814 Node[0] Start training with [gpu(0)]
2016-05-03 11:38:56,856 Node[0] Epoch[0] Batch [50] Speed: 650.50 samples/sec Train-accuracy=0.104531
2016-05-03 11:39:06,918 Node[0] Epoch[0] Batch [100] Speed: 636.09 samples/sec Train-accuracy=0.108594
2016-05-03 11:39:16,989 Node[0] Epoch[0] Batch [150] Speed: 635.54 samples/sec Train-accuracy=0.138437
2016-05-03 11:39:27,020 Node[0] Epoch[0] Batch [200] Speed: 638.02 samples/sec Train-accuracy=0.179063
2016-05-03 11:39:37,685 Node[0] Epoch[0] Batch [250] Speed: 600.12 samples/sec Train-accuracy=0.215781
2016-05-03 11:39:48,519 Node[0] Epoch[0] Batch [300] Speed: 590.72 samples/sec Train-accuracy=0.262031
2016-05-03 11:39:59,363 Node[0] Epoch[0] Batch [350] Speed: 590.19 samples/sec Train-accuracy=0.283594
2016-05-03 11:40:08,257 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:40:08,257 Node[0] Epoch[0] Time cost=81.548
2016-05-03 11:40:08,429 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:40:10,607 Node[0] Epoch[0] Validation-accuracy=0.292919
2016-05-03 11:40:21,478 Node[0] Epoch[1] Batch [50] Speed: 591.85 samples/sec Train-accuracy=0.336094
2016-05-03 11:40:32,253 Node[0] Epoch[1] Batch [100] Speed: 593.96 samples/sec Train-accuracy=0.382500
2016-05-03 11:40:43,010 Node[0] Epoch[1] Batch [150] Speed: 594.97 samples/sec Train-accuracy=0.399844
2016-05-03 11:40:53,778 Node[0] Epoch[1] Batch [200] Speed: 594.35 samples/sec Train-accuracy=0.411719
2016-05-03 11:41:04,568 Node[0] Epoch[1] Batch [250] Speed: 593.17 samples/sec Train-accuracy=0.450000
2016-05-03 11:41:15,275 Node[0] Epoch[1] Batch [300] Speed: 597.77 samples/sec Train-accuracy=0.461719
2016-05-03 11:41:25,957 Node[0] Epoch[1] Batch [350] Speed: 599.16 samples/sec Train-accuracy=0.480312
2016-05-03 11:41:34,715 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:41:34,716 Node[0] Epoch[1] Time cost=84.109
2016-05-03 11:41:34,880 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:41:36,808 Node[0] Epoch[1] Validation-accuracy=0.510717
2016-05-03 11:41:47,602 Node[0] Epoch[2] Batch [50] Speed: 596.04 samples/sec Train-accuracy=0.502344
2016-05-03 11:41:58,226 Node[0] Epoch[2] Batch [100] Speed: 602.46 samples/sec Train-accuracy=0.529219
2016-05-03 11:42:08,810 Node[0] Epoch[2] Batch [150] Speed: 604.70 samples/sec Train-accuracy=0.530000
2016-05-03 11:42:19,347 Node[0] Epoch[2] Batch [200] Speed: 607.41 samples/sec Train-accuracy=0.540156
2016-05-03 11:42:29,899 Node[0] Epoch[2] Batch [250] Speed: 606.53 samples/sec Train-accuracy=0.561094
2016-05-03 11:42:40,591 Node[0] Epoch[2] Batch [300] Speed: 598.58 samples/sec Train-accuracy=0.567187
2016-05-03 11:42:51,247 Node[0] Epoch[2] Batch [350] Speed: 600.60 samples/sec Train-accuracy=0.579531
2016-05-03 11:42:59,687 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 11:42:59,688 Node[0] Epoch[2] Time cost=82.879
2016-05-03 11:42:59,851 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 11:43:01,788 Node[0] Epoch[2] Validation-accuracy=0.583734
2016-05-03 11:43:12,297 Node[0] Epoch[3] Batch [50] Speed: 612.18 samples/sec Train-accuracy=0.598906
2016-05-03 11:43:22,851 Node[0] Epoch[3] Batch [100] Speed: 606.44 samples/sec Train-accuracy=0.608125
2016-05-03 11:43:33,361 Node[0] Epoch[3] Batch [150] Speed: 608.95 samples/sec Train-accuracy=0.616719
2016-05-03 11:43:43,856 Node[0] Epoch[3] Batch [200] Speed: 609.81 samples/sec Train-accuracy=0.614688
2016-05-03 11:43:54,365 Node[0] Epoch[3] Batch [250] Speed: 609.03 samples/sec Train-accuracy=0.623594
2016-05-03 11:44:04,895 Node[0] Epoch[3] Batch [300] Speed: 607.82 samples/sec Train-accuracy=0.635312
2016-05-03 11:44:15,412 Node[0] Epoch[3] Batch [350] Speed: 608.50 samples/sec Train-accuracy=0.648594
2016-05-03 11:44:24,027 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 11:44:24,027 Node[0] Epoch[3] Time cost=82.239
2016-05-03 11:44:24,194 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 11:44:26,105 Node[0] Epoch[3] Validation-accuracy=0.617288
2016-05-03 11:44:36,679 Node[0] Epoch[4] Batch [50] Speed: 608.48 samples/sec Train-accuracy=0.656719
2016-05-03 11:44:47,275 Node[0] Epoch[4] Batch [100] Speed: 604.04 samples/sec Train-accuracy=0.652031
2016-05-03 11:44:57,686 Node[0] Epoch[4] Batch [150] Speed: 614.74 samples/sec Train-accuracy=0.670625
2016-05-03 11:45:08,100 Node[0] Epoch[4] Batch [200] Speed: 614.61 samples/sec Train-accuracy=0.669219
2016-05-03 11:45:18,554 Node[0] Epoch[4] Batch [250] Speed: 612.20 samples/sec Train-accuracy=0.677188
2016-05-03 11:45:29,025 Node[0] Epoch[4] Batch [300] Speed: 611.26 samples/sec Train-accuracy=0.680937
2016-05-03 11:45:39,538 Node[0] Epoch[4] Batch [350] Speed: 608.75 samples/sec Train-accuracy=0.681562
2016-05-03 11:45:48,142 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 11:45:48,142 Node[0] Epoch[4] Time cost=82.037
2016-05-03 11:45:48,304 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 11:45:50,240 Node[0] Epoch[4] Validation-accuracy=0.674079
2016-05-03 11:46:00,723 Node[0] Epoch[5] Batch [50] Speed: 613.89 samples/sec Train-accuracy=0.693594
2016-05-03 11:46:11,158 Node[0] Epoch[5] Batch [100] Speed: 613.33 samples/sec Train-accuracy=0.698281
2016-05-03 11:46:21,571 Node[0] Epoch[5] Batch [150] Speed: 614.62 samples/sec Train-accuracy=0.709531
2016-05-03 11:46:31,979 Node[0] Epoch[5] Batch [200] Speed: 614.96 samples/sec Train-accuracy=0.704688
2016-05-03 11:46:42,365 Node[0] Epoch[5] Batch [250] Speed: 616.22 samples/sec Train-accuracy=0.712969
2016-05-03 11:46:52,770 Node[0] Epoch[5] Batch [300] Speed: 615.09 samples/sec Train-accuracy=0.719844
2016-05-03 11:47:03,191 Node[0] Epoch[5] Batch [350] Speed: 614.15 samples/sec Train-accuracy=0.708438
2016-05-03 11:47:11,510 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 11:47:11,510 Node[0] Epoch[5] Time cost=81.270
2016-05-03 11:47:11,674 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 11:47:13,647 Node[0] Epoch[5] Validation-accuracy=0.679688
2016-05-03 11:47:24,218 Node[0] Epoch[6] Batch [50] Speed: 608.63 samples/sec Train-accuracy=0.725781
2016-05-03 11:47:34,635 Node[0] Epoch[6] Batch [100] Speed: 614.43 samples/sec Train-accuracy=0.732969
2016-05-03 11:47:45,062 Node[0] Epoch[6] Batch [150] Speed: 613.78 samples/sec Train-accuracy=0.743594
2016-05-03 11:47:55,492 Node[0] Epoch[6] Batch [200] Speed: 613.62 samples/sec Train-accuracy=0.738906
2016-05-03 11:48:05,895 Node[0] Epoch[6] Batch [250] Speed: 615.23 samples/sec Train-accuracy=0.730313
2016-05-03 11:48:16,295 Node[0] Epoch[6] Batch [300] Speed: 615.42 samples/sec Train-accuracy=0.735938
2016-05-03 11:48:26,755 Node[0] Epoch[6] Batch [350] Speed: 611.86 samples/sec Train-accuracy=0.742500
2016-05-03 11:48:35,301 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 11:48:35,301 Node[0] Epoch[6] Time cost=81.654
2016-05-03 11:48:35,462 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 11:48:37,433 Node[0] Epoch[6] Validation-accuracy=0.693209
2016-05-03 11:48:47,872 Node[0] Epoch[7] Batch [50] Speed: 616.37 samples/sec Train-accuracy=0.752031
2016-05-03 11:48:58,221 Node[0] Epoch[7] Batch [100] Speed: 618.43 samples/sec Train-accuracy=0.750000
2016-05-03 11:49:08,581 Node[0] Epoch[7] Batch [150] Speed: 617.80 samples/sec Train-accuracy=0.765469
2016-05-03 11:49:18,990 Node[0] Epoch[7] Batch [200] Speed: 614.87 samples/sec Train-accuracy=0.755625
2016-05-03 11:49:29,424 Node[0] Epoch[7] Batch [250] Speed: 613.40 samples/sec Train-accuracy=0.757969
2016-05-03 11:49:40,624 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 11:49:41,008 Node[0] Start training with [gpu(0)]
2016-05-03 11:50:01,882 Node[0] Epoch[0] Batch [50] Speed: 649.84 samples/sec Train-accuracy=0.108281
2016-05-03 11:50:11,919 Node[0] Epoch[0] Batch [100] Speed: 637.64 samples/sec Train-accuracy=0.181719
2016-05-03 11:50:21,968 Node[0] Epoch[0] Batch [150] Speed: 636.88 samples/sec Train-accuracy=0.241563
2016-05-03 11:50:32,292 Node[0] Epoch[0] Batch [200] Speed: 619.96 samples/sec Train-accuracy=0.296875
2016-05-03 11:50:43,105 Node[0] Epoch[0] Batch [250] Speed: 591.89 samples/sec Train-accuracy=0.338594
2016-05-03 11:50:54,003 Node[0] Epoch[0] Batch [300] Speed: 587.27 samples/sec Train-accuracy=0.372812
2016-05-03 11:51:04,838 Node[0] Epoch[0] Batch [350] Speed: 590.67 samples/sec Train-accuracy=0.391406
2016-05-03 11:51:13,735 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 11:51:13,735 Node[0] Epoch[0] Time cost=82.026
2016-05-03 11:51:13,904 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 11:51:16,117 Node[0] Epoch[0] Validation-accuracy=0.381922
2016-05-03 11:51:26,907 Node[0] Epoch[1] Batch [50] Speed: 596.21 samples/sec Train-accuracy=0.431719
2016-05-03 11:51:37,642 Node[0] Epoch[1] Batch [100] Speed: 596.17 samples/sec Train-accuracy=0.460938
2016-05-03 11:51:48,339 Node[0] Epoch[1] Batch [150] Speed: 598.36 samples/sec Train-accuracy=0.474219
2016-05-03 11:51:59,024 Node[0] Epoch[1] Batch [200] Speed: 598.93 samples/sec Train-accuracy=0.501406
2016-05-03 11:52:09,701 Node[0] Epoch[1] Batch [250] Speed: 599.45 samples/sec Train-accuracy=0.488125
2016-05-03 11:52:20,390 Node[0] Epoch[1] Batch [300] Speed: 598.78 samples/sec Train-accuracy=0.522188
2016-05-03 11:52:31,028 Node[0] Epoch[1] Batch [350] Speed: 601.61 samples/sec Train-accuracy=0.536875
2016-05-03 11:52:39,656 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 11:52:39,656 Node[0] Epoch[1] Time cost=83.538
2016-05-03 11:52:39,821 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 11:52:41,790 Node[0] Epoch[1] Validation-accuracy=0.554788
2016-05-03 11:52:52,581 Node[0] Epoch[2] Batch [50] Speed: 596.22 samples/sec Train-accuracy=0.551094
2016-05-03 11:53:03,324 Node[0] Epoch[2] Batch [100] Speed: 595.76 samples/sec Train-accuracy=0.569688
2016-05-03 11:53:13,965 Node[0] Epoch[2] Batch [150] Speed: 601.46 samples/sec Train-accuracy=0.581562
2016-05-03 11:53:24,544 Node[0] Epoch[2] Batch [200] Speed: 604.99 samples/sec Train-accuracy=0.585156
2016-05-03 11:53:35,082 Node[0] Epoch[2] Batch [250] Speed: 607.34 samples/sec Train-accuracy=0.588125
2016-05-03 11:53:45,644 Node[0] Epoch[2] Batch [300] Speed: 605.94 samples/sec Train-accuracy=0.606719
2016-05-03 11:53:56,231 Node[0] Epoch[2] Batch [350] Speed: 604.52 samples/sec Train-accuracy=0.607812
2016-05-03 11:54:04,681 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 11:54:04,681 Node[0] Epoch[2] Time cost=82.891
2016-05-03 11:54:04,844 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 11:54:06,771 Node[0] Epoch[2] Validation-accuracy=0.611178
2016-05-03 11:54:17,252 Node[0] Epoch[3] Batch [50] Speed: 613.82 samples/sec Train-accuracy=0.633437
2016-05-03 11:54:27,834 Node[0] Epoch[3] Batch [100] Speed: 604.81 samples/sec Train-accuracy=0.639062
2016-05-03 11:54:38,351 Node[0] Epoch[3] Batch [150] Speed: 608.60 samples/sec Train-accuracy=0.648281
2016-05-03 11:54:48,850 Node[0] Epoch[3] Batch [200] Speed: 609.58 samples/sec Train-accuracy=0.643281
2016-05-03 11:54:59,393 Node[0] Epoch[3] Batch [250] Speed: 607.07 samples/sec Train-accuracy=0.649687
2016-05-03 11:55:09,922 Node[0] Epoch[3] Batch [300] Speed: 607.87 samples/sec Train-accuracy=0.667656
2016-05-03 11:55:20,454 Node[0] Epoch[3] Batch [350] Speed: 607.64 samples/sec Train-accuracy=0.666562
2016-05-03 11:55:29,075 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 11:55:29,076 Node[0] Epoch[3] Time cost=82.305
2016-05-03 11:55:29,244 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 11:55:31,149 Node[0] Epoch[3] Validation-accuracy=0.678586
2016-05-03 11:55:41,718 Node[0] Epoch[4] Batch [50] Speed: 608.77 samples/sec Train-accuracy=0.685312
2016-05-03 11:55:52,236 Node[0] Epoch[4] Batch [100] Speed: 608.48 samples/sec Train-accuracy=0.685000
2016-05-03 11:56:02,783 Node[0] Epoch[4] Batch [150] Speed: 606.84 samples/sec Train-accuracy=0.703438
2016-05-03 11:56:13,245 Node[0] Epoch[4] Batch [200] Speed: 611.72 samples/sec Train-accuracy=0.703438
2016-05-03 11:56:23,701 Node[0] Epoch[4] Batch [250] Speed: 612.12 samples/sec Train-accuracy=0.689688
2016-05-03 11:56:34,188 Node[0] Epoch[4] Batch [300] Speed: 610.32 samples/sec Train-accuracy=0.699219
2016-05-03 11:56:44,604 Node[0] Epoch[4] Batch [350] Speed: 614.42 samples/sec Train-accuracy=0.717656
2016-05-03 11:56:53,165 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 11:56:53,166 Node[0] Epoch[4] Time cost=82.016
2016-05-03 11:56:53,329 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 11:56:55,321 Node[0] Epoch[4] Validation-accuracy=0.695413
2016-05-03 11:57:05,814 Node[0] Epoch[5] Batch [50] Speed: 613.11 samples/sec Train-accuracy=0.720156
2016-05-03 11:57:16,304 Node[0] Epoch[5] Batch [100] Speed: 610.12 samples/sec Train-accuracy=0.723594
2016-05-03 11:57:26,748 Node[0] Epoch[5] Batch [150] Speed: 612.86 samples/sec Train-accuracy=0.728437
2016-05-03 11:57:37,193 Node[0] Epoch[5] Batch [200] Speed: 612.76 samples/sec Train-accuracy=0.718906
2016-05-03 11:57:47,607 Node[0] Epoch[5] Batch [250] Speed: 614.55 samples/sec Train-accuracy=0.725781
2016-05-03 11:57:58,000 Node[0] Epoch[5] Batch [300] Speed: 615.81 samples/sec Train-accuracy=0.736406
2016-05-03 11:58:08,411 Node[0] Epoch[5] Batch [350] Speed: 614.77 samples/sec Train-accuracy=0.740469
2016-05-03 11:58:16,740 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 11:58:16,740 Node[0] Epoch[5] Time cost=81.419
2016-05-03 11:58:16,903 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 11:58:18,872 Node[0] Epoch[5] Validation-accuracy=0.637520
2016-05-03 11:58:29,380 Node[0] Epoch[6] Batch [50] Speed: 612.24 samples/sec Train-accuracy=0.746875
2016-05-03 11:58:39,814 Node[0] Epoch[6] Batch [100] Speed: 613.42 samples/sec Train-accuracy=0.740000
2016-05-03 11:58:50,231 Node[0] Epoch[6] Batch [150] Speed: 614.39 samples/sec Train-accuracy=0.750469
2016-05-03 11:59:00,607 Node[0] Epoch[6] Batch [200] Speed: 616.82 samples/sec Train-accuracy=0.747969
2016-05-03 11:59:11,007 Node[0] Epoch[6] Batch [250] Speed: 615.39 samples/sec Train-accuracy=0.750938
2016-05-03 11:59:21,455 Node[0] Epoch[6] Batch [300] Speed: 612.60 samples/sec Train-accuracy=0.759531
2016-05-03 11:59:31,842 Node[0] Epoch[6] Batch [350] Speed: 616.16 samples/sec Train-accuracy=0.757969
2016-05-03 11:59:40,391 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 11:59:40,391 Node[0] Epoch[6] Time cost=81.519
2016-05-03 11:59:40,555 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 11:59:42,493 Node[0] Epoch[6] Validation-accuracy=0.732873
2016-05-03 11:59:52,921 Node[0] Epoch[7] Batch [50] Speed: 616.97 samples/sec Train-accuracy=0.765156
2016-05-03 12:00:03,342 Node[0] Epoch[7] Batch [100] Speed: 614.18 samples/sec Train-accuracy=0.750313
2016-05-03 12:00:13,766 Node[0] Epoch[7] Batch [150] Speed: 614.01 samples/sec Train-accuracy=0.778281
2016-05-03 12:00:24,223 Node[0] Epoch[7] Batch [200] Speed: 612.04 samples/sec Train-accuracy=0.768906
2016-05-03 12:00:34,612 Node[0] Epoch[7] Batch [250] Speed: 616.01 samples/sec Train-accuracy=0.772031
2016-05-03 12:00:45,048 Node[0] Epoch[7] Batch [300] Speed: 613.30 samples/sec Train-accuracy=0.770312
2016-05-03 12:00:55,477 Node[0] Epoch[7] Batch [350] Speed: 613.70 samples/sec Train-accuracy=0.774844
2016-05-03 12:01:03,811 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 12:01:03,812 Node[0] Epoch[7] Time cost=81.319
2016-05-03 12:01:03,978 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 12:01:05,935 Node[0] Epoch[7] Validation-accuracy=0.741186
2016-05-03 12:01:16,430 Node[0] Epoch[8] Batch [50] Speed: 612.99 samples/sec Train-accuracy=0.784375
2016-05-03 12:01:26,784 Node[0] Epoch[8] Batch [100] Speed: 618.16 samples/sec Train-accuracy=0.768594
2016-05-03 12:01:37,107 Node[0] Epoch[8] Batch [150] Speed: 619.95 samples/sec Train-accuracy=0.784531
2016-05-03 12:01:47,519 Node[0] Epoch[8] Batch [200] Speed: 614.69 samples/sec Train-accuracy=0.777813
2016-05-03 12:01:57,933 Node[0] Epoch[8] Batch [250] Speed: 614.57 samples/sec Train-accuracy=0.786094
2016-05-03 12:02:08,312 Node[0] Epoch[8] Batch [300] Speed: 616.65 samples/sec Train-accuracy=0.774531
2016-05-03 12:02:18,719 Node[0] Epoch[8] Batch [350] Speed: 614.98 samples/sec Train-accuracy=0.790937
2016-05-03 12:02:27,214 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 12:02:27,214 Node[0] Epoch[8] Time cost=81.279
2016-05-03 12:02:27,374 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 12:02:29,566 Node[0] Epoch[8] Validation-accuracy=0.694521
2016-05-03 12:02:40,020 Node[0] Epoch[9] Batch [50] Speed: 615.46 samples/sec Train-accuracy=0.796875
2016-05-03 12:02:50,511 Node[0] Epoch[9] Batch [100] Speed: 610.06 samples/sec Train-accuracy=0.796094
2016-05-03 12:03:00,878 Node[0] Epoch[9] Batch [150] Speed: 617.35 samples/sec Train-accuracy=0.797344
2016-05-03 12:03:11,219 Node[0] Epoch[9] Batch [200] Speed: 618.89 samples/sec Train-accuracy=0.792813
2016-05-03 12:03:21,581 Node[0] Epoch[9] Batch [250] Speed: 617.67 samples/sec Train-accuracy=0.788125
2016-05-03 12:03:31,948 Node[0] Epoch[9] Batch [300] Speed: 617.38 samples/sec Train-accuracy=0.796719
2016-05-03 12:03:42,339 Node[0] Epoch[9] Batch [350] Speed: 615.93 samples/sec Train-accuracy=0.798125
2016-05-03 12:03:50,831 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 12:03:50,832 Node[0] Epoch[9] Time cost=81.266
2016-05-03 12:03:50,997 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 12:03:52,906 Node[0] Epoch[9] Validation-accuracy=0.636819
2016-05-03 12:04:03,336 Node[0] Epoch[10] Batch [50] Speed: 616.92 samples/sec Train-accuracy=0.797969
2016-05-03 12:04:13,672 Node[0] Epoch[10] Batch [100] Speed: 619.20 samples/sec Train-accuracy=0.792969
2016-05-03 12:04:24,038 Node[0] Epoch[10] Batch [150] Speed: 617.38 samples/sec Train-accuracy=0.810469
2016-05-03 12:04:34,326 Node[0] Epoch[10] Batch [200] Speed: 622.13 samples/sec Train-accuracy=0.809375
2016-05-03 12:04:44,682 Node[0] Epoch[10] Batch [250] Speed: 618.00 samples/sec Train-accuracy=0.810469
2016-05-03 12:04:55,082 Node[0] Epoch[10] Batch [300] Speed: 615.39 samples/sec Train-accuracy=0.801875
2016-05-03 12:05:05,453 Node[0] Epoch[10] Batch [350] Speed: 617.16 samples/sec Train-accuracy=0.808594
2016-05-03 12:05:13,758 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 12:05:13,759 Node[0] Epoch[10] Time cost=80.852
2016-05-03 12:05:13,924 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 12:05:15,838 Node[0] Epoch[10] Validation-accuracy=0.677584
2016-05-03 12:05:26,296 Node[0] Epoch[11] Batch [50] Speed: 615.31 samples/sec Train-accuracy=0.805469
2016-05-03 12:05:36,632 Node[0] Epoch[11] Batch [100] Speed: 619.17 samples/sec Train-accuracy=0.814219
2016-05-03 12:05:46,964 Node[0] Epoch[11] Batch [150] Speed: 619.50 samples/sec Train-accuracy=0.813750
2016-05-03 12:05:57,297 Node[0] Epoch[11] Batch [200] Speed: 619.36 samples/sec Train-accuracy=0.820312
2016-05-03 12:06:07,647 Node[0] Epoch[11] Batch [250] Speed: 618.40 samples/sec Train-accuracy=0.813750
2016-05-03 12:06:17,928 Node[0] Epoch[11] Batch [300] Speed: 622.49 samples/sec Train-accuracy=0.809844
2016-05-03 12:06:28,261 Node[0] Epoch[11] Batch [350] Speed: 619.40 samples/sec Train-accuracy=0.825469
2016-05-03 12:06:36,694 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 12:06:36,694 Node[0] Epoch[11] Time cost=80.855
2016-05-03 12:06:36,854 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 12:06:38,830 Node[0] Epoch[11] Validation-accuracy=0.698217
2016-05-03 12:06:49,283 Node[0] Epoch[12] Batch [50] Speed: 615.54 samples/sec Train-accuracy=0.823438
2016-05-03 12:06:59,610 Node[0] Epoch[12] Batch [100] Speed: 619.75 samples/sec Train-accuracy=0.821562
2016-05-03 12:07:09,983 Node[0] Epoch[12] Batch [150] Speed: 616.98 samples/sec Train-accuracy=0.830625
2016-05-03 12:07:20,336 Node[0] Epoch[12] Batch [200] Speed: 618.17 samples/sec Train-accuracy=0.827656
2016-05-03 12:07:30,699 Node[0] Epoch[12] Batch [250] Speed: 617.64 samples/sec Train-accuracy=0.822656
2016-05-03 12:07:41,022 Node[0] Epoch[12] Batch [300] Speed: 619.96 samples/sec Train-accuracy=0.834531
2016-05-03 12:07:51,338 Node[0] Epoch[12] Batch [350] Speed: 620.41 samples/sec Train-accuracy=0.818750
2016-05-03 12:07:59,842 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 12:07:59,842 Node[0] Epoch[12] Time cost=81.012
2016-05-03 12:08:00,002 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 12:08:01,958 Node[0] Epoch[12] Validation-accuracy=0.733373
2016-05-03 12:08:12,438 Node[0] Epoch[13] Batch [50] Speed: 613.91 samples/sec Train-accuracy=0.824219
2016-05-03 12:08:22,757 Node[0] Epoch[13] Batch [100] Speed: 620.20 samples/sec Train-accuracy=0.827969
2016-05-03 12:08:33,089 Node[0] Epoch[13] Batch [150] Speed: 619.47 samples/sec Train-accuracy=0.832187
2016-05-03 12:08:43,425 Node[0] Epoch[13] Batch [200] Speed: 619.19 samples/sec Train-accuracy=0.826406
2016-05-03 12:08:53,766 Node[0] Epoch[13] Batch [250] Speed: 618.93 samples/sec Train-accuracy=0.825469
2016-05-03 12:09:04,147 Node[0] Epoch[13] Batch [300] Speed: 616.56 samples/sec Train-accuracy=0.843594
2016-05-03 12:09:14,525 Node[0] Epoch[13] Batch [350] Speed: 616.66 samples/sec Train-accuracy=0.825000
2016-05-03 12:09:22,823 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 12:09:22,823 Node[0] Epoch[13] Time cost=80.865
2016-05-03 12:09:22,994 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 12:09:24,922 Node[0] Epoch[13] Validation-accuracy=0.682292
2016-05-03 12:09:35,223 Node[0] Epoch[14] Batch [50] Speed: 624.63 samples/sec Train-accuracy=0.849063
2016-05-03 12:09:45,535 Node[0] Epoch[14] Batch [100] Speed: 620.64 samples/sec Train-accuracy=0.829219
2016-05-03 12:09:55,874 Node[0] Epoch[14] Batch [150] Speed: 619.05 samples/sec Train-accuracy=0.845781
2016-05-03 12:10:06,211 Node[0] Epoch[14] Batch [200] Speed: 619.14 samples/sec Train-accuracy=0.833125
2016-05-03 12:10:16,545 Node[0] Epoch[14] Batch [250] Speed: 619.29 samples/sec Train-accuracy=0.837969
2016-05-03 12:10:26,871 Node[0] Epoch[14] Batch [300] Speed: 619.84 samples/sec Train-accuracy=0.836562
2016-05-03 12:10:37,256 Node[0] Epoch[14] Batch [350] Speed: 616.31 samples/sec Train-accuracy=0.835000
2016-05-03 12:10:45,746 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 12:10:45,747 Node[0] Epoch[14] Time cost=80.824
2016-05-03 12:10:45,908 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 12:10:47,835 Node[0] Epoch[14] Validation-accuracy=0.706030
2016-05-03 12:10:58,247 Node[0] Epoch[15] Batch [50] Speed: 617.94 samples/sec Train-accuracy=0.839531
2016-05-03 12:11:08,598 Node[0] Epoch[15] Batch [100] Speed: 618.33 samples/sec Train-accuracy=0.847500
2016-05-03 12:11:18,899 Node[0] Epoch[15] Batch [150] Speed: 621.30 samples/sec Train-accuracy=0.843906
2016-05-03 12:11:29,202 Node[0] Epoch[15] Batch [200] Speed: 621.19 samples/sec Train-accuracy=0.846719
2016-05-03 12:11:39,512 Node[0] Epoch[15] Batch [250] Speed: 620.80 samples/sec Train-accuracy=0.839063
2016-05-03 12:11:49,859 Node[0] Epoch[15] Batch [300] Speed: 618.55 samples/sec Train-accuracy=0.839063
2016-05-03 12:12:00,310 Node[0] Epoch[15] Batch [350] Speed: 612.39 samples/sec Train-accuracy=0.840625
2016-05-03 12:12:08,617 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 12:12:08,617 Node[0] Epoch[15] Time cost=80.783
2016-05-03 12:12:08,778 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 12:12:10,716 Node[0] Epoch[15] Validation-accuracy=0.673778
2016-05-03 12:12:21,089 Node[0] Epoch[16] Batch [50] Speed: 620.24 samples/sec Train-accuracy=0.841250
2016-05-03 12:12:31,392 Node[0] Epoch[16] Batch [100] Speed: 621.21 samples/sec Train-accuracy=0.854219
2016-05-03 12:12:41,727 Node[0] Epoch[16] Batch [150] Speed: 619.26 samples/sec Train-accuracy=0.851562
2016-05-03 12:12:52,032 Node[0] Epoch[16] Batch [200] Speed: 621.06 samples/sec Train-accuracy=0.847812
2016-05-03 12:13:02,343 Node[0] Epoch[16] Batch [250] Speed: 620.75 samples/sec Train-accuracy=0.838750
2016-05-03 12:13:12,744 Node[0] Epoch[16] Batch [300] Speed: 615.35 samples/sec Train-accuracy=0.847812
2016-05-03 12:13:23,160 Node[0] Epoch[16] Batch [350] Speed: 614.46 samples/sec Train-accuracy=0.851875
2016-05-03 12:13:31,722 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 12:13:31,723 Node[0] Epoch[16] Time cost=81.006
2016-05-03 12:13:31,888 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 12:13:34,047 Node[0] Epoch[16] Validation-accuracy=0.617484
2016-05-03 12:13:44,372 Node[0] Epoch[17] Batch [50] Speed: 623.13 samples/sec Train-accuracy=0.849375
2016-05-03 12:13:54,714 Node[0] Epoch[17] Batch [100] Speed: 618.86 samples/sec Train-accuracy=0.848750
2016-05-03 12:14:05,042 Node[0] Epoch[17] Batch [150] Speed: 619.67 samples/sec Train-accuracy=0.855156
2016-05-03 12:14:15,339 Node[0] Epoch[17] Batch [200] Speed: 621.58 samples/sec Train-accuracy=0.852812
2016-05-03 12:14:25,659 Node[0] Epoch[17] Batch [250] Speed: 620.18 samples/sec Train-accuracy=0.853906
2016-05-03 12:14:36,007 Node[0] Epoch[17] Batch [300] Speed: 618.49 samples/sec Train-accuracy=0.861406
2016-05-03 12:14:46,392 Node[0] Epoch[17] Batch [350] Speed: 616.26 samples/sec Train-accuracy=0.859219
2016-05-03 12:14:54,908 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 12:14:54,908 Node[0] Epoch[17] Time cost=80.861
2016-05-03 12:14:55,068 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 12:14:56,971 Node[0] Epoch[17] Validation-accuracy=0.761118
2016-05-03 12:15:07,341 Node[0] Epoch[18] Batch [50] Speed: 620.40 samples/sec Train-accuracy=0.856563
2016-05-03 12:15:17,765 Node[0] Epoch[18] Batch [100] Speed: 613.99 samples/sec Train-accuracy=0.858906
2016-05-03 12:15:28,235 Node[0] Epoch[18] Batch [150] Speed: 611.27 samples/sec Train-accuracy=0.860469
2016-05-03 12:15:38,553 Node[0] Epoch[18] Batch [200] Speed: 620.33 samples/sec Train-accuracy=0.846875
2016-05-03 12:15:48,886 Node[0] Epoch[18] Batch [250] Speed: 619.40 samples/sec Train-accuracy=0.856406
2016-05-03 12:15:59,234 Node[0] Epoch[18] Batch [300] Speed: 618.46 samples/sec Train-accuracy=0.859688
2016-05-03 12:16:09,632 Node[0] Epoch[18] Batch [350] Speed: 615.52 samples/sec Train-accuracy=0.855938
2016-05-03 12:16:17,863 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 12:16:17,864 Node[0] Epoch[18] Time cost=80.892
2016-05-03 12:16:18,028 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 12:16:19,980 Node[0] Epoch[18] Validation-accuracy=0.737580
2016-05-03 12:16:30,377 Node[0] Epoch[19] Batch [50] Speed: 618.84 samples/sec Train-accuracy=0.861719
2016-05-03 12:16:40,749 Node[0] Epoch[19] Batch [100] Speed: 617.09 samples/sec Train-accuracy=0.858906
2016-05-03 12:16:51,094 Node[0] Epoch[19] Batch [150] Speed: 618.64 samples/sec Train-accuracy=0.864688
2016-05-03 12:17:01,444 Node[0] Epoch[19] Batch [200] Speed: 618.40 samples/sec Train-accuracy=0.851875
2016-05-03 12:17:11,776 Node[0] Epoch[19] Batch [250] Speed: 619.43 samples/sec Train-accuracy=0.863281
2016-05-03 12:17:22,134 Node[0] Epoch[19] Batch [300] Speed: 617.89 samples/sec Train-accuracy=0.859062
2016-05-03 12:17:32,457 Node[0] Epoch[19] Batch [350] Speed: 620.04 samples/sec Train-accuracy=0.860781
2016-05-03 12:17:40,916 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 12:17:40,916 Node[0] Epoch[19] Time cost=80.936
2016-05-03 12:17:41,078 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 12:17:43,020 Node[0] Epoch[19] Validation-accuracy=0.577925
2016-05-03 12:17:53,472 Node[0] Epoch[20] Batch [50] Speed: 615.69 samples/sec Train-accuracy=0.861250
2016-05-03 12:18:03,799 Node[0] Epoch[20] Batch [100] Speed: 619.77 samples/sec Train-accuracy=0.864062
2016-05-03 12:18:14,147 Node[0] Epoch[20] Batch [150] Speed: 618.49 samples/sec Train-accuracy=0.866719
2016-05-03 12:18:24,441 Node[0] Epoch[20] Batch [200] Speed: 621.71 samples/sec Train-accuracy=0.861563
2016-05-03 12:18:34,710 Node[0] Epoch[20] Batch [250] Speed: 623.27 samples/sec Train-accuracy=0.866094
2016-05-03 12:18:45,038 Node[0] Epoch[20] Batch [300] Speed: 619.65 samples/sec Train-accuracy=0.862812
2016-05-03 12:18:55,404 Node[0] Epoch[20] Batch [350] Speed: 617.47 samples/sec Train-accuracy=0.867500
2016-05-03 12:19:03,930 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 12:19:03,930 Node[0] Epoch[20] Time cost=80.910
2016-05-03 12:19:04,092 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 12:19:06,000 Node[0] Epoch[20] Validation-accuracy=0.672175
2016-05-03 12:19:16,350 Node[0] Epoch[21] Batch [50] Speed: 621.59 samples/sec Train-accuracy=0.869219
2016-05-03 12:19:26,766 Node[0] Epoch[21] Batch [100] Speed: 614.50 samples/sec Train-accuracy=0.867969
2016-05-03 12:19:51,545 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:19:51,950 Node[0] Start training with [gpu(0)]
2016-05-03 12:20:13,224 Node[0] Epoch[0] Batch [50] Speed: 648.64 samples/sec Train-accuracy=0.110312
2016-05-03 12:20:23,263 Node[0] Epoch[0] Batch [100] Speed: 637.53 samples/sec Train-accuracy=0.157500
2016-05-03 12:20:33,358 Node[0] Epoch[0] Batch [150] Speed: 634.00 samples/sec Train-accuracy=0.202656
2016-05-03 12:20:43,984 Node[0] Epoch[0] Batch [200] Speed: 602.32 samples/sec Train-accuracy=0.241719
2016-05-03 12:20:55,031 Node[0] Epoch[0] Batch [250] Speed: 579.32 samples/sec Train-accuracy=0.295000
2016-05-03 12:21:06,102 Node[0] Epoch[0] Batch [300] Speed: 578.11 samples/sec Train-accuracy=0.327969
2016-05-03 12:21:17,210 Node[0] Epoch[0] Batch [350] Speed: 576.20 samples/sec Train-accuracy=0.344375
2016-05-03 12:21:26,229 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 12:21:26,229 Node[0] Epoch[0] Time cost=83.134
2016-05-03 12:21:26,398 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 12:21:28,546 Node[0] Epoch[0] Validation-accuracy=0.400613
2016-05-03 12:21:39,293 Node[0] Epoch[1] Batch [50] Speed: 598.72 samples/sec Train-accuracy=0.390781
2016-05-03 12:21:50,157 Node[0] Epoch[1] Batch [100] Speed: 589.16 samples/sec Train-accuracy=0.408906
2016-05-03 12:22:01,040 Node[0] Epoch[1] Batch [150] Speed: 588.06 samples/sec Train-accuracy=0.429219
2016-05-03 12:22:11,870 Node[0] Epoch[1] Batch [200] Speed: 590.95 samples/sec Train-accuracy=0.457813
2016-05-03 12:22:22,679 Node[0] Epoch[1] Batch [250] Speed: 592.13 samples/sec Train-accuracy=0.461875
2016-05-03 12:22:33,480 Node[0] Epoch[1] Batch [300] Speed: 592.56 samples/sec Train-accuracy=0.482969
2016-05-03 12:22:44,272 Node[0] Epoch[1] Batch [350] Speed: 593.04 samples/sec Train-accuracy=0.492812
2016-05-03 12:22:53,079 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 12:22:53,080 Node[0] Epoch[1] Time cost=84.534
2016-05-03 12:22:53,245 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 12:22:55,247 Node[0] Epoch[1] Validation-accuracy=0.533053
2016-05-03 12:23:05,953 Node[0] Epoch[2] Batch [50] Speed: 600.91 samples/sec Train-accuracy=0.526250
2016-05-03 12:23:15,077 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:23:15,586 Node[0] Start training with [gpu(0)]
2016-05-03 12:23:33,168 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:24:42,451 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:24:48,074 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:32:04,968 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:32:18,935 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:32:24,871 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:34:17,194 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:34:29,274 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:34:45,692 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:34:50,164 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:35:23,568 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:35:56,348 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:44:37,018 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 12:44:37,450 Node[0] Start training with [gpu(0)]
2016-05-03 12:44:58,160 Node[0] Epoch[0] Batch [50] Speed: 663.46 samples/sec Train-accuracy=0.105781
2016-05-03 12:45:07,952 Node[0] Epoch[0] Batch [100] Speed: 653.66 samples/sec Train-accuracy=0.130625
2016-05-03 12:45:17,796 Node[0] Epoch[0] Batch [150] Speed: 650.13 samples/sec Train-accuracy=0.129844
2016-05-03 12:45:27,722 Node[0] Epoch[0] Batch [200] Speed: 644.80 samples/sec Train-accuracy=0.138437
2016-05-03 12:45:37,642 Node[0] Epoch[0] Batch [250] Speed: 645.19 samples/sec Train-accuracy=0.159844
2016-05-03 12:45:47,607 Node[0] Epoch[0] Batch [300] Speed: 642.24 samples/sec Train-accuracy=0.170156
2016-05-03 12:45:57,530 Node[0] Epoch[0] Batch [350] Speed: 644.97 samples/sec Train-accuracy=0.199687
2016-05-03 12:46:05,653 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 12:46:05,653 Node[0] Epoch[0] Time cost=77.394
2016-05-03 12:46:05,807 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 12:46:07,797 Node[0] Epoch[0] Validation-accuracy=0.271559
2016-05-03 12:46:17,782 Node[0] Epoch[1] Batch [50] Speed: 644.18 samples/sec Train-accuracy=0.268594
2016-05-03 12:46:28,039 Node[0] Epoch[1] Batch [100] Speed: 624.01 samples/sec Train-accuracy=0.297031
2016-05-03 12:46:38,303 Node[0] Epoch[1] Batch [150] Speed: 623.53 samples/sec Train-accuracy=0.338125
2016-05-03 12:46:48,599 Node[0] Epoch[1] Batch [200] Speed: 621.63 samples/sec Train-accuracy=0.358906
2016-05-03 12:46:58,879 Node[0] Epoch[1] Batch [250] Speed: 622.61 samples/sec Train-accuracy=0.383281
2016-05-03 12:47:09,113 Node[0] Epoch[1] Batch [300] Speed: 625.36 samples/sec Train-accuracy=0.393750
2016-05-03 12:47:19,336 Node[0] Epoch[1] Batch [350] Speed: 626.05 samples/sec Train-accuracy=0.414219
2016-05-03 12:47:27,760 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 12:47:27,761 Node[0] Epoch[1] Time cost=79.964
2016-05-03 12:47:27,921 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 12:47:29,872 Node[0] Epoch[1] Validation-accuracy=0.450921
2016-05-03 12:47:40,174 Node[0] Epoch[2] Batch [50] Speed: 624.49 samples/sec Train-accuracy=0.418438
2016-05-03 12:47:50,470 Node[0] Epoch[2] Batch [100] Speed: 621.66 samples/sec Train-accuracy=0.458906
2016-05-03 12:48:00,746 Node[0] Epoch[2] Batch [150] Speed: 622.79 samples/sec Train-accuracy=0.464687
2016-05-03 12:48:10,977 Node[0] Epoch[2] Batch [200] Speed: 625.60 samples/sec Train-accuracy=0.478594
2016-05-03 12:48:21,246 Node[0] Epoch[2] Batch [250] Speed: 623.22 samples/sec Train-accuracy=0.493125
2016-05-03 12:48:31,505 Node[0] Epoch[2] Batch [300] Speed: 623.86 samples/sec Train-accuracy=0.497500
2016-05-03 12:48:41,761 Node[0] Epoch[2] Batch [350] Speed: 624.05 samples/sec Train-accuracy=0.511406
2016-05-03 12:48:49,980 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 12:48:49,981 Node[0] Epoch[2] Time cost=80.108
2016-05-03 12:48:50,144 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 12:48:52,060 Node[0] Epoch[2] Validation-accuracy=0.503205
2016-05-03 12:49:02,400 Node[0] Epoch[3] Batch [50] Speed: 622.19 samples/sec Train-accuracy=0.530937
2016-05-03 12:49:12,748 Node[0] Epoch[3] Batch [100] Speed: 618.52 samples/sec Train-accuracy=0.547969
2016-05-03 12:49:23,066 Node[0] Epoch[3] Batch [150] Speed: 620.26 samples/sec Train-accuracy=0.555937
2016-05-03 12:49:33,296 Node[0] Epoch[3] Batch [200] Speed: 625.68 samples/sec Train-accuracy=0.560625
2016-05-03 12:49:43,600 Node[0] Epoch[3] Batch [250] Speed: 621.12 samples/sec Train-accuracy=0.579375
2016-05-03 12:49:53,897 Node[0] Epoch[3] Batch [300] Speed: 621.56 samples/sec Train-accuracy=0.586406
2016-05-03 12:50:04,154 Node[0] Epoch[3] Batch [350] Speed: 623.94 samples/sec Train-accuracy=0.586250
2016-05-03 12:50:12,547 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 12:50:12,547 Node[0] Epoch[3] Time cost=80.487
2016-05-03 12:50:12,709 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 12:50:14,685 Node[0] Epoch[3] Validation-accuracy=0.570012
2016-05-03 12:50:25,017 Node[0] Epoch[4] Batch [50] Speed: 622.60 samples/sec Train-accuracy=0.607812
2016-05-03 12:50:35,281 Node[0] Epoch[4] Batch [100] Speed: 623.60 samples/sec Train-accuracy=0.617031
2016-05-03 12:50:45,517 Node[0] Epoch[4] Batch [150] Speed: 625.27 samples/sec Train-accuracy=0.621094
2016-05-03 12:50:55,772 Node[0] Epoch[4] Batch [200] Speed: 624.09 samples/sec Train-accuracy=0.627656
2016-05-03 12:51:06,011 Node[0] Epoch[4] Batch [250] Speed: 625.05 samples/sec Train-accuracy=0.626406
2016-05-03 12:51:16,282 Node[0] Epoch[4] Batch [300] Speed: 623.12 samples/sec Train-accuracy=0.646719
2016-05-03 12:51:26,533 Node[0] Epoch[4] Batch [350] Speed: 624.35 samples/sec Train-accuracy=0.648125
2016-05-03 12:51:34,942 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 12:51:34,942 Node[0] Epoch[4] Time cost=80.257
2016-05-03 12:51:35,105 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 12:51:36,987 Node[0] Epoch[4] Validation-accuracy=0.655549
2016-05-03 12:51:47,307 Node[0] Epoch[5] Batch [50] Speed: 623.35 samples/sec Train-accuracy=0.655000
2016-05-03 12:51:57,521 Node[0] Epoch[5] Batch [100] Speed: 626.64 samples/sec Train-accuracy=0.668281
2016-05-03 12:52:07,706 Node[0] Epoch[5] Batch [150] Speed: 628.39 samples/sec Train-accuracy=0.667031
2016-05-03 12:52:17,881 Node[0] Epoch[5] Batch [200] Speed: 628.99 samples/sec Train-accuracy=0.662500
2016-05-03 12:52:28,070 Node[0] Epoch[5] Batch [250] Speed: 628.17 samples/sec Train-accuracy=0.670469
2016-05-03 12:52:38,290 Node[0] Epoch[5] Batch [300] Speed: 626.22 samples/sec Train-accuracy=0.670469
2016-05-03 12:52:48,557 Node[0] Epoch[5] Batch [350] Speed: 623.40 samples/sec Train-accuracy=0.680312
2016-05-03 12:52:56,741 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 12:52:56,741 Node[0] Epoch[5] Time cost=79.754
2016-05-03 12:52:56,905 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 12:52:58,852 Node[0] Epoch[5] Validation-accuracy=0.683193
2016-05-03 12:53:09,134 Node[0] Epoch[6] Batch [50] Speed: 625.77 samples/sec Train-accuracy=0.692969
2016-05-03 12:53:19,396 Node[0] Epoch[6] Batch [100] Speed: 623.68 samples/sec Train-accuracy=0.690000
2016-05-03 12:53:29,689 Node[0] Epoch[6] Batch [150] Speed: 621.79 samples/sec Train-accuracy=0.703125
2016-05-03 12:53:39,899 Node[0] Epoch[6] Batch [200] Speed: 626.89 samples/sec Train-accuracy=0.690781
2016-05-03 12:53:50,002 Node[0] Epoch[6] Batch [250] Speed: 633.45 samples/sec Train-accuracy=0.702031
2016-05-03 12:54:00,232 Node[0] Epoch[6] Batch [300] Speed: 625.66 samples/sec Train-accuracy=0.705781
2016-05-03 12:54:10,493 Node[0] Epoch[6] Batch [350] Speed: 623.70 samples/sec Train-accuracy=0.713281
2016-05-03 12:54:18,855 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 12:54:18,856 Node[0] Epoch[6] Time cost=80.003
2016-05-03 12:54:19,014 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 12:54:20,971 Node[0] Epoch[6] Validation-accuracy=0.700321
2016-05-03 12:54:31,185 Node[0] Epoch[7] Batch [50] Speed: 629.94 samples/sec Train-accuracy=0.715781
2016-05-03 12:54:41,435 Node[0] Epoch[7] Batch [100] Speed: 624.39 samples/sec Train-accuracy=0.717969
2016-05-03 12:54:51,594 Node[0] Epoch[7] Batch [150] Speed: 629.97 samples/sec Train-accuracy=0.730156
2016-05-03 12:55:01,760 Node[0] Epoch[7] Batch [200] Speed: 629.59 samples/sec Train-accuracy=0.730938
2016-05-03 12:55:11,929 Node[0] Epoch[7] Batch [250] Speed: 629.35 samples/sec Train-accuracy=0.726875
2016-05-03 12:55:22,107 Node[0] Epoch[7] Batch [300] Speed: 628.86 samples/sec Train-accuracy=0.731094
2016-05-03 12:55:32,349 Node[0] Epoch[7] Batch [350] Speed: 624.92 samples/sec Train-accuracy=0.732187
2016-05-03 12:55:40,546 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 12:55:40,547 Node[0] Epoch[7] Time cost=79.575
2016-05-03 12:55:40,706 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 12:55:42,628 Node[0] Epoch[7] Validation-accuracy=0.740385
2016-05-03 12:55:52,838 Node[0] Epoch[8] Batch [50] Speed: 630.30 samples/sec Train-accuracy=0.738125
2016-05-03 12:56:03,075 Node[0] Epoch[8] Batch [100] Speed: 625.25 samples/sec Train-accuracy=0.742812
2016-05-03 12:56:13,249 Node[0] Epoch[8] Batch [150] Speed: 629.07 samples/sec Train-accuracy=0.762500
2016-05-03 12:56:23,414 Node[0] Epoch[8] Batch [200] Speed: 629.57 samples/sec Train-accuracy=0.747969
2016-05-03 12:56:33,600 Node[0] Epoch[8] Batch [250] Speed: 628.38 samples/sec Train-accuracy=0.742344
2016-05-03 12:56:43,808 Node[0] Epoch[8] Batch [300] Speed: 626.95 samples/sec Train-accuracy=0.755156
2016-05-03 12:56:53,956 Node[0] Epoch[8] Batch [350] Speed: 630.65 samples/sec Train-accuracy=0.749687
2016-05-03 12:57:02,292 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 12:57:02,292 Node[0] Epoch[8] Time cost=79.664
2016-05-03 12:57:02,449 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 12:57:04,545 Node[0] Epoch[8] Validation-accuracy=0.709059
2016-05-03 12:57:14,803 Node[0] Epoch[9] Batch [50] Speed: 627.15 samples/sec Train-accuracy=0.754687
2016-05-03 12:57:25,007 Node[0] Epoch[9] Batch [100] Speed: 627.19 samples/sec Train-accuracy=0.756875
2016-05-03 12:57:35,173 Node[0] Epoch[9] Batch [150] Speed: 629.60 samples/sec Train-accuracy=0.767969
2016-05-03 12:57:45,350 Node[0] Epoch[9] Batch [200] Speed: 628.89 samples/sec Train-accuracy=0.766563
2016-05-03 12:57:55,532 Node[0] Epoch[9] Batch [250] Speed: 628.55 samples/sec Train-accuracy=0.755781
2016-05-03 12:58:05,667 Node[0] Epoch[9] Batch [300] Speed: 631.50 samples/sec Train-accuracy=0.764375
2016-05-03 12:58:15,799 Node[0] Epoch[9] Batch [350] Speed: 631.67 samples/sec Train-accuracy=0.764219
2016-05-03 12:58:24,128 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 12:58:24,128 Node[0] Epoch[9] Time cost=79.583
2016-05-03 12:58:24,288 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 12:58:26,182 Node[0] Epoch[9] Validation-accuracy=0.747496
2016-05-03 12:58:36,483 Node[0] Epoch[10] Batch [50] Speed: 624.56 samples/sec Train-accuracy=0.766875
2016-05-03 12:58:46,675 Node[0] Epoch[10] Batch [100] Speed: 627.93 samples/sec Train-accuracy=0.773125
2016-05-03 12:58:56,828 Node[0] Epoch[10] Batch [150] Speed: 630.40 samples/sec Train-accuracy=0.783281
2016-05-03 12:59:07,008 Node[0] Epoch[10] Batch [200] Speed: 628.67 samples/sec Train-accuracy=0.775156
2016-05-03 12:59:17,200 Node[0] Epoch[10] Batch [250] Speed: 627.97 samples/sec Train-accuracy=0.777656
2016-05-03 12:59:27,336 Node[0] Epoch[10] Batch [300] Speed: 631.44 samples/sec Train-accuracy=0.787656
2016-05-03 12:59:37,508 Node[0] Epoch[10] Batch [350] Speed: 629.21 samples/sec Train-accuracy=0.774062
2016-05-03 12:59:45,632 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 12:59:45,633 Node[0] Epoch[10] Time cost=79.451
2016-05-03 12:59:45,793 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 12:59:47,738 Node[0] Epoch[10] Validation-accuracy=0.757612
2016-05-03 12:59:58,013 Node[0] Epoch[11] Batch [50] Speed: 626.20 samples/sec Train-accuracy=0.787031
2016-05-03 13:00:08,155 Node[0] Epoch[11] Batch [100] Speed: 631.07 samples/sec Train-accuracy=0.794219
2016-05-03 13:00:18,295 Node[0] Epoch[11] Batch [150] Speed: 631.17 samples/sec Train-accuracy=0.795937
2016-05-03 13:00:28,473 Node[0] Epoch[11] Batch [200] Speed: 628.82 samples/sec Train-accuracy=0.786563
2016-05-03 13:00:38,657 Node[0] Epoch[11] Batch [250] Speed: 628.41 samples/sec Train-accuracy=0.785312
2016-05-03 13:00:48,876 Node[0] Epoch[11] Batch [300] Speed: 626.33 samples/sec Train-accuracy=0.793750
2016-05-03 13:00:59,009 Node[0] Epoch[11] Batch [350] Speed: 631.58 samples/sec Train-accuracy=0.792813
2016-05-03 13:01:07,333 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 13:01:07,333 Node[0] Epoch[11] Time cost=79.595
2016-05-03 13:01:07,497 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 13:01:09,360 Node[0] Epoch[11] Validation-accuracy=0.761218
2016-05-03 13:01:19,547 Node[0] Epoch[12] Batch [50] Speed: 631.63 samples/sec Train-accuracy=0.793438
2016-05-03 13:01:29,696 Node[0] Epoch[12] Batch [100] Speed: 630.64 samples/sec Train-accuracy=0.799687
2016-05-03 13:01:39,826 Node[0] Epoch[12] Batch [150] Speed: 631.84 samples/sec Train-accuracy=0.805000
2016-05-03 13:01:50,006 Node[0] Epoch[12] Batch [200] Speed: 628.65 samples/sec Train-accuracy=0.800937
2016-05-03 13:02:00,171 Node[0] Epoch[12] Batch [250] Speed: 629.66 samples/sec Train-accuracy=0.803750
2016-05-03 13:02:10,320 Node[0] Epoch[12] Batch [300] Speed: 630.60 samples/sec Train-accuracy=0.816094
2016-05-03 13:02:20,462 Node[0] Epoch[12] Batch [350] Speed: 631.07 samples/sec Train-accuracy=0.806562
2016-05-03 13:02:28,773 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 13:02:28,773 Node[0] Epoch[12] Time cost=79.413
2016-05-03 13:02:28,930 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 13:02:30,843 Node[0] Epoch[12] Validation-accuracy=0.784655
2016-05-03 13:02:41,018 Node[0] Epoch[13] Batch [50] Speed: 632.34 samples/sec Train-accuracy=0.803594
2016-05-03 13:02:51,201 Node[0] Epoch[13] Batch [100] Speed: 628.49 samples/sec Train-accuracy=0.811719
2016-05-03 13:03:01,384 Node[0] Epoch[13] Batch [150] Speed: 628.52 samples/sec Train-accuracy=0.816719
2016-05-03 13:03:11,550 Node[0] Epoch[13] Batch [200] Speed: 629.57 samples/sec Train-accuracy=0.811875
2016-05-03 13:03:21,756 Node[0] Epoch[13] Batch [250] Speed: 627.09 samples/sec Train-accuracy=0.807031
2016-05-03 13:03:32,018 Node[0] Epoch[13] Batch [300] Speed: 623.71 samples/sec Train-accuracy=0.813750
2016-05-03 13:03:42,248 Node[0] Epoch[13] Batch [350] Speed: 625.60 samples/sec Train-accuracy=0.818438
2016-05-03 13:03:50,418 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 13:03:50,418 Node[0] Epoch[13] Time cost=79.575
2016-05-03 13:03:50,580 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 13:03:52,476 Node[0] Epoch[13] Validation-accuracy=0.775240
2016-05-03 13:04:02,650 Node[0] Epoch[14] Batch [50] Speed: 632.29 samples/sec Train-accuracy=0.809219
2016-05-03 13:04:12,832 Node[0] Epoch[14] Batch [100] Speed: 628.62 samples/sec Train-accuracy=0.822031
2016-05-03 13:04:22,976 Node[0] Epoch[14] Batch [150] Speed: 630.93 samples/sec Train-accuracy=0.819844
2016-05-03 13:04:33,122 Node[0] Epoch[14] Batch [200] Speed: 630.76 samples/sec Train-accuracy=0.810156
2016-05-03 13:04:43,303 Node[0] Epoch[14] Batch [250] Speed: 628.67 samples/sec Train-accuracy=0.807344
2016-05-03 13:04:53,500 Node[0] Epoch[14] Batch [300] Speed: 627.62 samples/sec Train-accuracy=0.821719
2016-05-03 13:05:03,682 Node[0] Epoch[14] Batch [350] Speed: 628.60 samples/sec Train-accuracy=0.820625
2016-05-03 13:05:12,030 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 13:05:12,030 Node[0] Epoch[14] Time cost=79.554
2016-05-03 13:05:12,191 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 13:05:14,167 Node[0] Epoch[14] Validation-accuracy=0.785357
2016-05-03 13:05:24,469 Node[0] Epoch[15] Batch [50] Speed: 624.49 samples/sec Train-accuracy=0.817656
2016-05-03 13:05:34,700 Node[0] Epoch[15] Batch [100] Speed: 625.58 samples/sec Train-accuracy=0.834844
2016-05-03 13:05:44,861 Node[0] Epoch[15] Batch [150] Speed: 629.82 samples/sec Train-accuracy=0.830937
2016-05-03 13:05:55,030 Node[0] Epoch[15] Batch [200] Speed: 629.41 samples/sec Train-accuracy=0.826562
2016-05-03 13:06:05,166 Node[0] Epoch[15] Batch [250] Speed: 631.41 samples/sec Train-accuracy=0.820000
2016-05-03 13:06:15,333 Node[0] Epoch[15] Batch [300] Speed: 629.53 samples/sec Train-accuracy=0.827344
2016-05-03 13:06:25,501 Node[0] Epoch[15] Batch [350] Speed: 629.42 samples/sec Train-accuracy=0.828438
2016-05-03 13:06:33,656 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 13:06:33,656 Node[0] Epoch[15] Time cost=79.489
2016-05-03 13:06:33,813 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 13:06:35,689 Node[0] Epoch[15] Validation-accuracy=0.783253
2016-05-03 13:06:45,934 Node[0] Epoch[16] Batch [50] Speed: 628.01 samples/sec Train-accuracy=0.824531
2016-05-03 13:06:56,218 Node[0] Epoch[16] Batch [100] Speed: 622.31 samples/sec Train-accuracy=0.837344
2016-05-03 13:07:06,373 Node[0] Epoch[16] Batch [150] Speed: 630.28 samples/sec Train-accuracy=0.838594
2016-05-03 13:07:16,534 Node[0] Epoch[16] Batch [200] Speed: 629.89 samples/sec Train-accuracy=0.836875
2016-05-03 13:07:26,681 Node[0] Epoch[16] Batch [250] Speed: 630.76 samples/sec Train-accuracy=0.824375
2016-05-03 13:07:36,879 Node[0] Epoch[16] Batch [300] Speed: 627.58 samples/sec Train-accuracy=0.835625
2016-05-03 13:07:47,007 Node[0] Epoch[16] Batch [350] Speed: 631.94 samples/sec Train-accuracy=0.838281
2016-05-03 13:07:55,369 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 13:07:55,369 Node[0] Epoch[16] Time cost=79.680
2016-05-03 13:07:55,528 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 13:07:57,635 Node[0] Epoch[16] Validation-accuracy=0.800138
2016-05-03 13:08:07,880 Node[0] Epoch[17] Batch [50] Speed: 628.02 samples/sec Train-accuracy=0.833750
2016-05-03 13:08:18,024 Node[0] Epoch[17] Batch [100] Speed: 630.98 samples/sec Train-accuracy=0.840156
2016-05-03 13:08:28,162 Node[0] Epoch[17] Batch [150] Speed: 631.30 samples/sec Train-accuracy=0.842656
2016-05-03 13:08:38,278 Node[0] Epoch[17] Batch [200] Speed: 632.66 samples/sec Train-accuracy=0.841094
2016-05-03 13:08:48,437 Node[0] Epoch[17] Batch [250] Speed: 629.97 samples/sec Train-accuracy=0.834375
2016-05-03 13:08:58,678 Node[0] Epoch[17] Batch [300] Speed: 624.99 samples/sec Train-accuracy=0.841406
2016-05-03 13:09:08,901 Node[0] Epoch[17] Batch [350] Speed: 626.06 samples/sec Train-accuracy=0.838125
2016-05-03 13:09:17,231 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 13:09:17,232 Node[0] Epoch[17] Time cost=79.596
2016-05-03 13:09:17,390 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 13:09:19,289 Node[0] Epoch[17] Validation-accuracy=0.801783
2016-05-03 13:09:29,395 Node[0] Epoch[18] Batch [50] Speed: 636.60 samples/sec Train-accuracy=0.831094
2016-05-03 13:09:39,583 Node[0] Epoch[18] Batch [100] Speed: 628.22 samples/sec Train-accuracy=0.838594
2016-05-03 13:09:49,794 Node[0] Epoch[18] Batch [150] Speed: 626.79 samples/sec Train-accuracy=0.853437
2016-05-03 13:09:59,986 Node[0] Epoch[18] Batch [200] Speed: 627.98 samples/sec Train-accuracy=0.845938
2016-05-03 13:10:10,154 Node[0] Epoch[18] Batch [250] Speed: 629.44 samples/sec Train-accuracy=0.840156
2016-05-03 13:10:20,324 Node[0] Epoch[18] Batch [300] Speed: 629.31 samples/sec Train-accuracy=0.847656
2016-05-03 13:10:30,458 Node[0] Epoch[18] Batch [350] Speed: 631.57 samples/sec Train-accuracy=0.843437
2016-05-03 13:10:38,549 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 13:10:38,549 Node[0] Epoch[18] Time cost=79.259
2016-05-03 13:10:38,711 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 13:10:40,590 Node[0] Epoch[18] Validation-accuracy=0.800881
2016-05-03 13:10:50,737 Node[0] Epoch[19] Batch [50] Speed: 634.10 samples/sec Train-accuracy=0.835625
2016-05-03 13:11:00,906 Node[0] Epoch[19] Batch [100] Speed: 629.36 samples/sec Train-accuracy=0.848125
2016-05-03 13:11:11,085 Node[0] Epoch[19] Batch [150] Speed: 628.73 samples/sec Train-accuracy=0.850313
2016-05-03 13:11:21,266 Node[0] Epoch[19] Batch [200] Speed: 628.66 samples/sec Train-accuracy=0.846094
2016-05-03 13:11:31,388 Node[0] Epoch[19] Batch [250] Speed: 632.28 samples/sec Train-accuracy=0.844844
2016-05-03 13:11:41,536 Node[0] Epoch[19] Batch [300] Speed: 630.71 samples/sec Train-accuracy=0.850938
2016-05-03 13:11:51,702 Node[0] Epoch[19] Batch [350] Speed: 629.53 samples/sec Train-accuracy=0.854375
2016-05-03 13:12:00,015 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 13:12:00,015 Node[0] Epoch[19] Time cost=79.424
2016-05-03 13:12:00,175 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 13:12:02,126 Node[0] Epoch[19] Validation-accuracy=0.807292
2016-05-03 13:12:12,351 Node[0] Epoch[20] Batch [50] Speed: 629.26 samples/sec Train-accuracy=0.848437
2016-05-03 13:12:22,582 Node[0] Epoch[20] Batch [100] Speed: 625.56 samples/sec Train-accuracy=0.847187
2016-05-03 13:12:32,791 Node[0] Epoch[20] Batch [150] Speed: 626.91 samples/sec Train-accuracy=0.860781
2016-05-03 13:12:42,969 Node[0] Epoch[20] Batch [200] Speed: 628.84 samples/sec Train-accuracy=0.850469
2016-05-03 13:12:53,106 Node[0] Epoch[20] Batch [250] Speed: 631.33 samples/sec Train-accuracy=0.847969
2016-05-03 13:13:03,313 Node[0] Epoch[20] Batch [300] Speed: 627.06 samples/sec Train-accuracy=0.856875
2016-05-03 13:13:13,509 Node[0] Epoch[20] Batch [350] Speed: 627.71 samples/sec Train-accuracy=0.855625
2016-05-03 13:13:21,870 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 13:13:21,870 Node[0] Epoch[20] Time cost=79.744
2016-05-03 13:13:22,031 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 13:13:23,944 Node[0] Epoch[20] Validation-accuracy=0.806891
2016-05-03 13:13:34,177 Node[0] Epoch[21] Batch [50] Speed: 628.88 samples/sec Train-accuracy=0.847969
2016-05-03 13:13:44,360 Node[0] Epoch[21] Batch [100] Speed: 628.52 samples/sec Train-accuracy=0.855781
2016-05-03 13:13:54,567 Node[0] Epoch[21] Batch [150] Speed: 627.01 samples/sec Train-accuracy=0.861094
2016-05-03 13:14:04,769 Node[0] Epoch[21] Batch [200] Speed: 627.33 samples/sec Train-accuracy=0.857187
2016-05-03 13:14:14,913 Node[0] Epoch[21] Batch [250] Speed: 630.95 samples/sec Train-accuracy=0.859062
2016-05-03 13:14:25,089 Node[0] Epoch[21] Batch [300] Speed: 628.95 samples/sec Train-accuracy=0.862812
2016-05-03 13:14:35,263 Node[0] Epoch[21] Batch [350] Speed: 629.07 samples/sec Train-accuracy=0.852656
2016-05-03 13:14:43,376 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 13:14:43,376 Node[0] Epoch[21] Time cost=79.432
2016-05-03 13:14:43,534 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 13:14:45,462 Node[0] Epoch[21] Validation-accuracy=0.823618
2016-05-03 13:14:55,649 Node[0] Epoch[22] Batch [50] Speed: 631.48 samples/sec Train-accuracy=0.850781
2016-05-03 13:15:05,822 Node[0] Epoch[22] Batch [100] Speed: 629.17 samples/sec Train-accuracy=0.864844
2016-05-03 13:15:15,994 Node[0] Epoch[22] Batch [150] Speed: 629.17 samples/sec Train-accuracy=0.862812
2016-05-03 13:15:26,122 Node[0] Epoch[22] Batch [200] Speed: 631.91 samples/sec Train-accuracy=0.860156
2016-05-03 13:15:36,250 Node[0] Epoch[22] Batch [250] Speed: 631.94 samples/sec Train-accuracy=0.857500
2016-05-03 13:15:46,384 Node[0] Epoch[22] Batch [300] Speed: 631.54 samples/sec Train-accuracy=0.862812
2016-05-03 13:15:56,538 Node[0] Epoch[22] Batch [350] Speed: 630.29 samples/sec Train-accuracy=0.863906
2016-05-03 13:16:04,884 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 13:16:04,884 Node[0] Epoch[22] Time cost=79.422
2016-05-03 13:16:05,046 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 13:16:06,959 Node[0] Epoch[22] Validation-accuracy=0.806390
2016-05-03 13:16:17,125 Node[0] Epoch[23] Batch [50] Speed: 632.83 samples/sec Train-accuracy=0.856563
2016-05-03 13:16:27,311 Node[0] Epoch[23] Batch [100] Speed: 628.28 samples/sec Train-accuracy=0.865469
2016-05-03 13:16:37,451 Node[0] Epoch[23] Batch [150] Speed: 631.19 samples/sec Train-accuracy=0.867969
2016-05-03 13:16:47,567 Node[0] Epoch[23] Batch [200] Speed: 632.68 samples/sec Train-accuracy=0.861406
2016-05-03 13:16:57,716 Node[0] Epoch[23] Batch [250] Speed: 630.63 samples/sec Train-accuracy=0.860625
2016-05-03 13:17:07,976 Node[0] Epoch[23] Batch [300] Speed: 623.79 samples/sec Train-accuracy=0.868750
2016-05-03 13:17:18,221 Node[0] Epoch[23] Batch [350] Speed: 624.71 samples/sec Train-accuracy=0.865469
2016-05-03 13:17:26,322 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 13:17:26,322 Node[0] Epoch[23] Time cost=79.363
2016-05-03 13:17:26,479 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 13:17:28,388 Node[0] Epoch[23] Validation-accuracy=0.794071
2016-05-03 13:17:38,474 Node[0] Epoch[24] Batch [50] Speed: 637.96 samples/sec Train-accuracy=0.861406
2016-05-03 13:17:48,569 Node[0] Epoch[24] Batch [100] Speed: 633.97 samples/sec Train-accuracy=0.865625
2016-05-03 13:17:58,760 Node[0] Epoch[24] Batch [150] Speed: 628.00 samples/sec Train-accuracy=0.871250
2016-05-03 13:18:08,907 Node[0] Epoch[24] Batch [200] Speed: 630.77 samples/sec Train-accuracy=0.860469
2016-05-03 13:18:19,031 Node[0] Epoch[24] Batch [250] Speed: 632.17 samples/sec Train-accuracy=0.865156
2016-05-03 13:18:29,165 Node[0] Epoch[24] Batch [300] Speed: 631.57 samples/sec Train-accuracy=0.868125
2016-05-03 13:18:39,362 Node[0] Epoch[24] Batch [350] Speed: 627.60 samples/sec Train-accuracy=0.862656
2016-05-03 13:18:47,701 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 13:18:47,701 Node[0] Epoch[24] Time cost=79.313
2016-05-03 13:18:47,860 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 13:18:49,896 Node[0] Epoch[24] Validation-accuracy=0.786689
2016-05-03 13:19:00,045 Node[0] Epoch[25] Batch [50] Speed: 633.93 samples/sec Train-accuracy=0.864219
2016-05-03 13:19:10,242 Node[0] Epoch[25] Batch [100] Speed: 627.60 samples/sec Train-accuracy=0.870156
2016-05-03 13:19:20,428 Node[0] Epoch[25] Batch [150] Speed: 628.34 samples/sec Train-accuracy=0.869062
2016-05-03 13:19:30,598 Node[0] Epoch[25] Batch [200] Speed: 629.32 samples/sec Train-accuracy=0.868750
2016-05-03 13:19:40,738 Node[0] Epoch[25] Batch [250] Speed: 631.20 samples/sec Train-accuracy=0.866719
2016-05-03 13:19:50,897 Node[0] Epoch[25] Batch [300] Speed: 629.99 samples/sec Train-accuracy=0.869375
2016-05-03 13:20:01,069 Node[0] Epoch[25] Batch [350] Speed: 629.19 samples/sec Train-accuracy=0.873906
2016-05-03 13:20:09,362 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 13:20:09,362 Node[0] Epoch[25] Time cost=79.466
2016-05-03 13:20:09,523 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 13:20:11,417 Node[0] Epoch[25] Validation-accuracy=0.808694
2016-05-03 13:20:21,621 Node[0] Epoch[26] Batch [50] Speed: 630.60 samples/sec Train-accuracy=0.865625
2016-05-03 13:20:31,832 Node[0] Epoch[26] Batch [100] Speed: 626.81 samples/sec Train-accuracy=0.870000
2016-05-03 13:20:41,997 Node[0] Epoch[26] Batch [150] Speed: 629.62 samples/sec Train-accuracy=0.876094
2016-05-03 13:20:52,172 Node[0] Epoch[26] Batch [200] Speed: 629.01 samples/sec Train-accuracy=0.874687
2016-05-03 13:21:02,336 Node[0] Epoch[26] Batch [250] Speed: 629.69 samples/sec Train-accuracy=0.873281
2016-05-03 13:21:12,469 Node[0] Epoch[26] Batch [300] Speed: 631.63 samples/sec Train-accuracy=0.877969
2016-05-03 13:21:22,645 Node[0] Epoch[26] Batch [350] Speed: 628.94 samples/sec Train-accuracy=0.876094
2016-05-03 13:21:30,761 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 13:21:30,761 Node[0] Epoch[26] Time cost=79.344
2016-05-03 13:21:30,917 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 13:21:32,832 Node[0] Epoch[26] Validation-accuracy=0.793870
2016-05-03 13:21:43,059 Node[0] Epoch[27] Batch [50] Speed: 629.10 samples/sec Train-accuracy=0.866406
2016-05-03 13:21:53,264 Node[0] Epoch[27] Batch [100] Speed: 627.11 samples/sec Train-accuracy=0.874062
2016-05-03 13:22:03,461 Node[0] Epoch[27] Batch [150] Speed: 627.67 samples/sec Train-accuracy=0.876563
2016-05-03 13:22:13,667 Node[0] Epoch[27] Batch [200] Speed: 627.14 samples/sec Train-accuracy=0.875938
2016-05-03 13:22:23,886 Node[0] Epoch[27] Batch [250] Speed: 626.29 samples/sec Train-accuracy=0.872188
2016-05-03 13:22:34,056 Node[0] Epoch[27] Batch [300] Speed: 629.28 samples/sec Train-accuracy=0.875781
2016-05-03 13:22:44,218 Node[0] Epoch[27] Batch [350] Speed: 629.82 samples/sec Train-accuracy=0.875156
2016-05-03 13:22:52,549 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 13:22:52,549 Node[0] Epoch[27] Time cost=79.716
2016-05-03 13:22:52,711 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 13:22:54,646 Node[0] Epoch[27] Validation-accuracy=0.837640
2016-05-03 13:23:04,970 Node[0] Epoch[28] Batch [50] Speed: 623.10 samples/sec Train-accuracy=0.875625
2016-05-03 13:23:15,121 Node[0] Epoch[28] Batch [100] Speed: 630.50 samples/sec Train-accuracy=0.877812
2016-05-03 13:23:25,298 Node[0] Epoch[28] Batch [150] Speed: 628.90 samples/sec Train-accuracy=0.883906
2016-05-03 13:23:35,469 Node[0] Epoch[28] Batch [200] Speed: 629.25 samples/sec Train-accuracy=0.871406
2016-05-03 13:23:45,658 Node[0] Epoch[28] Batch [250] Speed: 628.17 samples/sec Train-accuracy=0.875781
2016-05-03 13:23:55,814 Node[0] Epoch[28] Batch [300] Speed: 630.15 samples/sec Train-accuracy=0.876250
2016-05-03 13:24:05,989 Node[0] Epoch[28] Batch [350] Speed: 629.04 samples/sec Train-accuracy=0.878750
2016-05-03 13:24:14,317 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 13:24:14,317 Node[0] Epoch[28] Time cost=79.671
2016-05-03 13:24:14,477 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 13:24:16,408 Node[0] Epoch[28] Validation-accuracy=0.818409
2016-05-03 13:24:26,655 Node[0] Epoch[29] Batch [50] Speed: 627.78 samples/sec Train-accuracy=0.874062
2016-05-03 13:24:36,789 Node[0] Epoch[29] Batch [100] Speed: 631.55 samples/sec Train-accuracy=0.880156
2016-05-03 13:24:46,933 Node[0] Epoch[29] Batch [150] Speed: 630.98 samples/sec Train-accuracy=0.885625
2016-05-03 13:24:57,088 Node[0] Epoch[29] Batch [200] Speed: 630.24 samples/sec Train-accuracy=0.876094
2016-05-03 13:25:07,294 Node[0] Epoch[29] Batch [250] Speed: 627.12 samples/sec Train-accuracy=0.882656
2016-05-03 13:25:17,451 Node[0] Epoch[29] Batch [300] Speed: 630.07 samples/sec Train-accuracy=0.876875
2016-05-03 13:25:27,641 Node[0] Epoch[29] Batch [350] Speed: 628.09 samples/sec Train-accuracy=0.886250
2016-05-03 13:25:35,767 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 13:25:35,768 Node[0] Epoch[29] Time cost=79.360
2016-05-03 13:25:35,927 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 13:25:37,823 Node[0] Epoch[29] Validation-accuracy=0.813502
2016-05-03 13:25:47,967 Node[0] Epoch[30] Batch [50] Speed: 634.20 samples/sec Train-accuracy=0.876094
2016-05-03 13:25:58,087 Node[0] Epoch[30] Batch [100] Speed: 632.43 samples/sec Train-accuracy=0.882656
2016-05-03 13:26:08,232 Node[0] Epoch[30] Batch [150] Speed: 630.89 samples/sec Train-accuracy=0.886094
2016-05-03 13:26:18,397 Node[0] Epoch[30] Batch [200] Speed: 629.66 samples/sec Train-accuracy=0.881719
2016-05-03 13:26:28,552 Node[0] Epoch[30] Batch [250] Speed: 630.21 samples/sec Train-accuracy=0.879687
2016-05-03 13:26:38,698 Node[0] Epoch[30] Batch [300] Speed: 630.81 samples/sec Train-accuracy=0.883281
2016-05-03 13:26:48,898 Node[0] Epoch[30] Batch [350] Speed: 627.47 samples/sec Train-accuracy=0.872812
2016-05-03 13:26:57,227 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 13:26:57,227 Node[0] Epoch[30] Time cost=79.404
2016-05-03 13:26:57,385 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 13:26:59,321 Node[0] Epoch[30] Validation-accuracy=0.821915
2016-05-03 13:27:09,486 Node[0] Epoch[31] Batch [50] Speed: 632.99 samples/sec Train-accuracy=0.880313
2016-05-03 13:27:19,676 Node[0] Epoch[31] Batch [100] Speed: 628.12 samples/sec Train-accuracy=0.890469
2016-05-03 13:27:29,806 Node[0] Epoch[31] Batch [150] Speed: 631.81 samples/sec Train-accuracy=0.892188
2016-05-03 13:27:39,924 Node[0] Epoch[31] Batch [200] Speed: 632.52 samples/sec Train-accuracy=0.886563
2016-05-03 13:27:50,069 Node[0] Epoch[31] Batch [250] Speed: 630.85 samples/sec Train-accuracy=0.880938
2016-05-03 13:28:00,257 Node[0] Epoch[31] Batch [300] Speed: 628.26 samples/sec Train-accuracy=0.888750
2016-05-03 13:28:10,400 Node[0] Epoch[31] Batch [350] Speed: 630.95 samples/sec Train-accuracy=0.882969
2016-05-03 13:28:18,550 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 13:28:18,551 Node[0] Epoch[31] Time cost=79.230
2016-05-03 13:28:18,707 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 13:28:20,590 Node[0] Epoch[31] Validation-accuracy=0.836338
2016-05-03 13:28:30,775 Node[0] Epoch[32] Batch [50] Speed: 631.65 samples/sec Train-accuracy=0.881406
2016-05-03 13:28:40,932 Node[0] Epoch[32] Batch [100] Speed: 630.13 samples/sec Train-accuracy=0.890000
2016-05-03 13:28:51,105 Node[0] Epoch[32] Batch [150] Speed: 629.16 samples/sec Train-accuracy=0.889062
2016-05-03 13:29:01,281 Node[0] Epoch[32] Batch [200] Speed: 628.96 samples/sec Train-accuracy=0.887813
2016-05-03 13:29:11,457 Node[0] Epoch[32] Batch [250] Speed: 628.93 samples/sec Train-accuracy=0.890469
2016-05-03 13:29:21,630 Node[0] Epoch[32] Batch [300] Speed: 629.10 samples/sec Train-accuracy=0.891719
2016-05-03 13:29:31,852 Node[0] Epoch[32] Batch [350] Speed: 626.14 samples/sec Train-accuracy=0.887813
2016-05-03 13:29:40,173 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 13:29:40,174 Node[0] Epoch[32] Time cost=79.584
2016-05-03 13:29:40,331 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 13:29:42,355 Node[0] Epoch[32] Validation-accuracy=0.847607
2016-05-03 13:29:52,511 Node[0] Epoch[33] Batch [50] Speed: 633.48 samples/sec Train-accuracy=0.885312
2016-05-03 13:30:02,663 Node[0] Epoch[33] Batch [100] Speed: 630.42 samples/sec Train-accuracy=0.890938
2016-05-03 13:30:12,816 Node[0] Epoch[33] Batch [150] Speed: 630.39 samples/sec Train-accuracy=0.891094
2016-05-03 13:30:22,965 Node[0] Epoch[33] Batch [200] Speed: 630.63 samples/sec Train-accuracy=0.885469
2016-05-03 13:30:33,141 Node[0] Epoch[33] Batch [250] Speed: 628.96 samples/sec Train-accuracy=0.885938
2016-05-03 13:30:43,301 Node[0] Epoch[33] Batch [300] Speed: 629.91 samples/sec Train-accuracy=0.888906
2016-05-03 13:30:53,504 Node[0] Epoch[33] Batch [350] Speed: 627.32 samples/sec Train-accuracy=0.888906
2016-05-03 13:31:01,818 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 13:31:01,818 Node[0] Epoch[33] Time cost=79.463
2016-05-03 13:31:01,979 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 13:31:03,859 Node[0] Epoch[33] Validation-accuracy=0.829527
2016-05-03 13:31:14,037 Node[0] Epoch[34] Batch [50] Speed: 632.21 samples/sec Train-accuracy=0.887813
2016-05-03 13:31:24,171 Node[0] Epoch[34] Batch [100] Speed: 631.55 samples/sec Train-accuracy=0.893594
2016-05-03 13:31:34,307 Node[0] Epoch[34] Batch [150] Speed: 631.43 samples/sec Train-accuracy=0.899687
2016-05-03 13:31:44,437 Node[0] Epoch[34] Batch [200] Speed: 631.79 samples/sec Train-accuracy=0.886719
2016-05-03 13:31:54,611 Node[0] Epoch[34] Batch [250] Speed: 629.05 samples/sec Train-accuracy=0.890469
2016-05-03 13:32:04,792 Node[0] Epoch[34] Batch [300] Speed: 628.66 samples/sec Train-accuracy=0.890781
2016-05-03 13:32:14,931 Node[0] Epoch[34] Batch [350] Speed: 631.25 samples/sec Train-accuracy=0.889531
2016-05-03 13:32:23,031 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 13:32:23,031 Node[0] Epoch[34] Time cost=79.172
2016-05-03 13:32:23,191 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 13:32:25,119 Node[0] Epoch[34] Validation-accuracy=0.826623
2016-05-03 13:32:35,283 Node[0] Epoch[35] Batch [50] Speed: 633.01 samples/sec Train-accuracy=0.892188
2016-05-03 13:32:45,463 Node[0] Epoch[35] Batch [100] Speed: 628.70 samples/sec Train-accuracy=0.893437
2016-05-03 13:32:55,604 Node[0] Epoch[35] Batch [150] Speed: 631.10 samples/sec Train-accuracy=0.896719
2016-05-03 13:33:05,717 Node[0] Epoch[35] Batch [200] Speed: 632.85 samples/sec Train-accuracy=0.890000
2016-05-03 13:33:15,861 Node[0] Epoch[35] Batch [250] Speed: 630.97 samples/sec Train-accuracy=0.891094
2016-05-03 13:33:26,039 Node[0] Epoch[35] Batch [300] Speed: 628.77 samples/sec Train-accuracy=0.889375
2016-05-03 13:33:36,206 Node[0] Epoch[35] Batch [350] Speed: 629.54 samples/sec Train-accuracy=0.896094
2016-05-03 13:33:44,537 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 13:33:44,538 Node[0] Epoch[35] Time cost=79.418
2016-05-03 13:33:44,698 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 13:33:46,620 Node[0] Epoch[35] Validation-accuracy=0.839744
2016-05-03 13:33:56,850 Node[0] Epoch[36] Batch [50] Speed: 628.97 samples/sec Train-accuracy=0.893437
2016-05-03 13:34:06,981 Node[0] Epoch[36] Batch [100] Speed: 631.74 samples/sec Train-accuracy=0.889844
2016-05-03 13:34:17,185 Node[0] Epoch[36] Batch [150] Speed: 627.19 samples/sec Train-accuracy=0.895938
2016-05-03 13:34:27,283 Node[0] Epoch[36] Batch [200] Speed: 633.81 samples/sec Train-accuracy=0.890781
2016-05-03 13:34:37,463 Node[0] Epoch[36] Batch [250] Speed: 628.70 samples/sec Train-accuracy=0.896719
2016-05-03 13:34:47,695 Node[0] Epoch[36] Batch [300] Speed: 625.50 samples/sec Train-accuracy=0.896406
2016-05-03 13:34:57,895 Node[0] Epoch[36] Batch [350] Speed: 627.49 samples/sec Train-accuracy=0.893750
2016-05-03 13:35:06,206 Node[0] Epoch[36] Resetting Data Iterator
2016-05-03 13:35:06,206 Node[0] Epoch[36] Time cost=79.587
2016-05-03 13:35:06,364 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-03 13:35:08,253 Node[0] Epoch[36] Validation-accuracy=0.833834
2016-05-03 13:35:18,406 Node[0] Epoch[37] Batch [50] Speed: 633.77 samples/sec Train-accuracy=0.892969
2016-05-03 13:35:28,532 Node[0] Epoch[37] Batch [100] Speed: 632.11 samples/sec Train-accuracy=0.895625
2016-05-03 13:35:38,723 Node[0] Epoch[37] Batch [150] Speed: 628.02 samples/sec Train-accuracy=0.894219
2016-05-03 13:35:48,908 Node[0] Epoch[37] Batch [200] Speed: 628.34 samples/sec Train-accuracy=0.893281
2016-05-03 13:35:59,054 Node[0] Epoch[37] Batch [250] Speed: 630.82 samples/sec Train-accuracy=0.892031
2016-05-03 13:36:09,226 Node[0] Epoch[37] Batch [300] Speed: 629.19 samples/sec Train-accuracy=0.895156
2016-05-03 13:36:19,403 Node[0] Epoch[37] Batch [350] Speed: 628.91 samples/sec Train-accuracy=0.895625
2016-05-03 13:36:27,548 Node[0] Epoch[37] Resetting Data Iterator
2016-05-03 13:36:27,548 Node[0] Epoch[37] Time cost=79.294
2016-05-03 13:36:27,708 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-03 13:36:29,654 Node[0] Epoch[37] Validation-accuracy=0.831530
2016-05-03 13:36:39,861 Node[0] Epoch[38] Batch [50] Speed: 630.26 samples/sec Train-accuracy=0.888594
2016-05-03 13:36:50,002 Node[0] Epoch[38] Batch [100] Speed: 631.16 samples/sec Train-accuracy=0.899219
2016-05-03 13:37:00,182 Node[0] Epoch[38] Batch [150] Speed: 628.70 samples/sec Train-accuracy=0.898750
2016-05-03 13:37:10,365 Node[0] Epoch[38] Batch [200] Speed: 628.47 samples/sec Train-accuracy=0.900000
2016-05-03 13:37:20,508 Node[0] Epoch[38] Batch [250] Speed: 631.02 samples/sec Train-accuracy=0.893750
2016-05-03 13:37:30,691 Node[0] Epoch[38] Batch [300] Speed: 628.50 samples/sec Train-accuracy=0.899531
2016-05-03 13:37:40,865 Node[0] Epoch[38] Batch [350] Speed: 629.10 samples/sec Train-accuracy=0.899062
2016-05-03 13:37:49,181 Node[0] Epoch[38] Resetting Data Iterator
2016-05-03 13:37:49,181 Node[0] Epoch[38] Time cost=79.527
2016-05-03 13:37:49,340 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-03 13:37:51,293 Node[0] Epoch[38] Validation-accuracy=0.816707
2016-05-03 13:38:01,483 Node[0] Epoch[39] Batch [50] Speed: 631.56 samples/sec Train-accuracy=0.893125
2016-05-03 13:38:11,800 Node[0] Epoch[39] Batch [100] Speed: 620.40 samples/sec Train-accuracy=0.907031
2016-05-03 13:38:21,982 Node[0] Epoch[39] Batch [150] Speed: 628.57 samples/sec Train-accuracy=0.899219
2016-05-03 13:38:32,136 Node[0] Epoch[39] Batch [200] Speed: 630.26 samples/sec Train-accuracy=0.894531
2016-05-03 13:40:02,573 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 13:40:02,966 Node[0] Start training with [gpu(0)]
2016-05-03 13:40:23,701 Node[0] Epoch[0] Batch [50] Speed: 651.37 samples/sec Train-accuracy=0.134063
2016-05-03 13:40:33,787 Node[0] Epoch[0] Batch [100] Speed: 634.62 samples/sec Train-accuracy=0.185781
2016-05-03 13:40:43,840 Node[0] Epoch[0] Batch [150] Speed: 636.64 samples/sec Train-accuracy=0.219375
2016-05-03 13:40:53,928 Node[0] Epoch[0] Batch [200] Speed: 634.43 samples/sec Train-accuracy=0.252969
2016-05-03 13:41:04,015 Node[0] Epoch[0] Batch [250] Speed: 634.49 samples/sec Train-accuracy=0.296094
2016-05-03 13:41:14,619 Node[0] Epoch[0] Batch [300] Speed: 603.56 samples/sec Train-accuracy=0.335000
2016-05-03 13:41:25,357 Node[0] Epoch[0] Batch [350] Speed: 595.99 samples/sec Train-accuracy=0.355312
2016-05-03 13:41:34,162 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 13:41:34,162 Node[0] Epoch[0] Time cost=80.553
2016-05-03 13:41:34,329 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 13:41:36,554 Node[0] Epoch[0] Validation-accuracy=0.301028
2016-05-03 13:41:47,373 Node[0] Epoch[1] Batch [50] Speed: 594.72 samples/sec Train-accuracy=0.383594
2016-05-03 13:41:58,100 Node[0] Epoch[1] Batch [100] Speed: 596.62 samples/sec Train-accuracy=0.410469
2016-05-03 13:42:08,831 Node[0] Epoch[1] Batch [150] Speed: 596.46 samples/sec Train-accuracy=0.437344
2016-05-03 13:42:19,470 Node[0] Epoch[1] Batch [200] Speed: 601.54 samples/sec Train-accuracy=0.433281
2016-05-03 13:42:30,024 Node[0] Epoch[1] Batch [250] Speed: 606.43 samples/sec Train-accuracy=0.461094
2016-05-03 13:42:40,620 Node[0] Epoch[1] Batch [300] Speed: 604.04 samples/sec Train-accuracy=0.471250
2016-05-03 13:42:51,194 Node[0] Epoch[1] Batch [350] Speed: 605.23 samples/sec Train-accuracy=0.477500
2016-05-03 13:42:59,850 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 13:42:59,850 Node[0] Epoch[1] Time cost=83.295
2016-05-03 13:43:00,013 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 13:43:01,990 Node[0] Epoch[1] Validation-accuracy=0.470052
2016-05-03 13:43:12,680 Node[0] Epoch[2] Batch [50] Speed: 602.02 samples/sec Train-accuracy=0.496875
2016-05-03 13:43:23,255 Node[0] Epoch[2] Batch [100] Speed: 605.22 samples/sec Train-accuracy=0.524062
2016-05-03 13:43:33,809 Node[0] Epoch[2] Batch [150] Speed: 606.37 samples/sec Train-accuracy=0.525000
2016-05-03 13:43:44,434 Node[0] Epoch[2] Batch [200] Speed: 602.41 samples/sec Train-accuracy=0.534375
2016-05-03 13:43:55,018 Node[0] Epoch[2] Batch [250] Speed: 604.70 samples/sec Train-accuracy=0.549844
2016-05-03 13:44:05,587 Node[0] Epoch[2] Batch [300] Speed: 605.54 samples/sec Train-accuracy=0.553906
2016-05-03 13:44:16,162 Node[0] Epoch[2] Batch [350] Speed: 605.22 samples/sec Train-accuracy=0.567344
2016-05-03 13:44:24,568 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 13:44:24,568 Node[0] Epoch[2] Time cost=82.577
2016-05-03 13:44:24,732 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 13:44:26,680 Node[0] Epoch[2] Validation-accuracy=0.537059
2016-05-03 13:44:37,189 Node[0] Epoch[3] Batch [50] Speed: 612.36 samples/sec Train-accuracy=0.583906
2016-05-03 13:44:47,590 Node[0] Epoch[3] Batch [100] Speed: 615.29 samples/sec Train-accuracy=0.591719
2016-05-03 13:44:58,015 Node[0] Epoch[3] Batch [150] Speed: 613.95 samples/sec Train-accuracy=0.605938
2016-05-03 13:45:08,436 Node[0] Epoch[3] Batch [200] Speed: 614.15 samples/sec Train-accuracy=0.616094
2016-05-03 13:45:18,931 Node[0] Epoch[3] Batch [250] Speed: 609.84 samples/sec Train-accuracy=0.614531
2016-05-03 13:45:29,466 Node[0] Epoch[3] Batch [300] Speed: 607.49 samples/sec Train-accuracy=0.622344
2016-05-03 13:45:39,985 Node[0] Epoch[3] Batch [350] Speed: 608.49 samples/sec Train-accuracy=0.634844
2016-05-03 13:45:48,635 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 13:45:48,635 Node[0] Epoch[3] Time cost=81.955
2016-05-03 13:45:48,799 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 13:45:50,747 Node[0] Epoch[3] Validation-accuracy=0.624900
2016-05-03 13:46:01,149 Node[0] Epoch[4] Batch [50] Speed: 618.49 samples/sec Train-accuracy=0.640156
2016-05-03 13:46:11,590 Node[0] Epoch[4] Batch [100] Speed: 613.02 samples/sec Train-accuracy=0.648594
2016-05-03 13:46:22,018 Node[0] Epoch[4] Batch [150] Speed: 613.72 samples/sec Train-accuracy=0.660000
2016-05-03 13:46:32,408 Node[0] Epoch[4] Batch [200] Speed: 616.01 samples/sec Train-accuracy=0.659062
2016-05-03 13:46:42,838 Node[0] Epoch[4] Batch [250] Speed: 613.61 samples/sec Train-accuracy=0.658750
2016-05-03 13:46:53,204 Node[0] Epoch[4] Batch [300] Speed: 617.44 samples/sec Train-accuracy=0.666562
2016-05-03 13:47:03,579 Node[0] Epoch[4] Batch [350] Speed: 616.89 samples/sec Train-accuracy=0.680781
2016-05-03 13:47:11,988 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 13:47:11,988 Node[0] Epoch[4] Time cost=81.241
2016-05-03 13:47:12,148 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 13:47:14,116 Node[0] Epoch[4] Validation-accuracy=0.665966
2016-05-03 13:47:24,514 Node[0] Epoch[5] Batch [50] Speed: 618.94 samples/sec Train-accuracy=0.667344
2016-05-03 13:47:34,958 Node[0] Epoch[5] Batch [100] Speed: 612.86 samples/sec Train-accuracy=0.694688
2016-05-03 13:47:45,351 Node[0] Epoch[5] Batch [150] Speed: 615.77 samples/sec Train-accuracy=0.696406
2016-05-03 13:47:55,654 Node[0] Epoch[5] Batch [200] Speed: 621.23 samples/sec Train-accuracy=0.700156
2016-05-03 13:48:05,985 Node[0] Epoch[5] Batch [250] Speed: 619.51 samples/sec Train-accuracy=0.697812
2016-05-03 13:48:16,274 Node[0] Epoch[5] Batch [300] Speed: 622.00 samples/sec Train-accuracy=0.713125
2016-05-03 13:48:26,556 Node[0] Epoch[5] Batch [350] Speed: 622.49 samples/sec Train-accuracy=0.716875
2016-05-03 13:48:34,776 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 13:48:34,777 Node[0] Epoch[5] Time cost=80.660
2016-05-03 13:48:34,937 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 13:48:36,898 Node[0] Epoch[5] Validation-accuracy=0.706230
2016-05-03 13:48:47,269 Node[0] Epoch[6] Batch [50] Speed: 620.40 samples/sec Train-accuracy=0.719531
2016-05-03 13:48:57,597 Node[0] Epoch[6] Batch [100] Speed: 619.68 samples/sec Train-accuracy=0.723125
2016-05-03 13:49:07,922 Node[0] Epoch[6] Batch [150] Speed: 619.90 samples/sec Train-accuracy=0.736719
2016-05-03 13:49:18,214 Node[0] Epoch[6] Batch [200] Speed: 621.87 samples/sec Train-accuracy=0.730469
2016-05-03 13:49:28,516 Node[0] Epoch[6] Batch [250] Speed: 621.26 samples/sec Train-accuracy=0.730938
2016-05-03 13:49:38,817 Node[0] Epoch[6] Batch [300] Speed: 621.29 samples/sec Train-accuracy=0.731406
2016-05-03 13:49:49,124 Node[0] Epoch[6] Batch [350] Speed: 620.94 samples/sec Train-accuracy=0.747344
2016-05-03 13:49:57,531 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 13:49:57,532 Node[0] Epoch[6] Time cost=80.633
2016-05-03 13:49:57,693 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 13:49:59,624 Node[0] Epoch[6] Validation-accuracy=0.702925
2016-05-03 13:50:09,989 Node[0] Epoch[7] Batch [50] Speed: 620.68 samples/sec Train-accuracy=0.744687
2016-05-03 13:50:20,374 Node[0] Epoch[7] Batch [100] Speed: 616.32 samples/sec Train-accuracy=0.739219
2016-05-03 13:50:30,666 Node[0] Epoch[7] Batch [150] Speed: 621.81 samples/sec Train-accuracy=0.753594
2016-05-03 13:50:40,920 Node[0] Epoch[7] Batch [200] Speed: 624.21 samples/sec Train-accuracy=0.748906
2016-05-03 13:50:51,202 Node[0] Epoch[7] Batch [250] Speed: 622.46 samples/sec Train-accuracy=0.760312
2016-05-03 13:51:01,515 Node[0] Epoch[7] Batch [300] Speed: 620.60 samples/sec Train-accuracy=0.754219
2016-05-03 13:51:11,792 Node[0] Epoch[7] Batch [350] Speed: 622.76 samples/sec Train-accuracy=0.764219
2016-05-03 13:51:20,014 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 13:51:20,015 Node[0] Epoch[7] Time cost=80.390
2016-05-03 13:51:20,178 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 13:51:22,114 Node[0] Epoch[7] Validation-accuracy=0.730970
2016-05-03 13:51:32,557 Node[0] Epoch[8] Batch [50] Speed: 616.17 samples/sec Train-accuracy=0.752031
2016-05-03 13:51:42,869 Node[0] Epoch[8] Batch [100] Speed: 620.68 samples/sec Train-accuracy=0.763437
2016-05-03 13:51:53,160 Node[0] Epoch[8] Batch [150] Speed: 621.91 samples/sec Train-accuracy=0.771875
2016-05-03 13:52:03,441 Node[0] Epoch[8] Batch [200] Speed: 622.50 samples/sec Train-accuracy=0.765469
2016-05-03 13:52:13,747 Node[0] Epoch[8] Batch [250] Speed: 621.02 samples/sec Train-accuracy=0.772188
2016-05-03 13:52:24,035 Node[0] Epoch[8] Batch [300] Speed: 622.10 samples/sec Train-accuracy=0.769219
2016-05-03 13:52:34,359 Node[0] Epoch[8] Batch [350] Speed: 619.98 samples/sec Train-accuracy=0.772656
2016-05-03 13:52:42,799 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 13:52:42,799 Node[0] Epoch[8] Time cost=80.686
2016-05-03 13:52:42,962 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 13:52:45,068 Node[0] Epoch[8] Validation-accuracy=0.753758
2016-05-03 13:52:55,387 Node[0] Epoch[9] Batch [50] Speed: 623.53 samples/sec Train-accuracy=0.769219
2016-05-03 13:53:05,668 Node[0] Epoch[9] Batch [100] Speed: 622.54 samples/sec Train-accuracy=0.782969
2016-05-03 13:53:15,894 Node[0] Epoch[9] Batch [150] Speed: 625.84 samples/sec Train-accuracy=0.785625
2016-05-03 13:53:26,134 Node[0] Epoch[9] Batch [200] Speed: 625.05 samples/sec Train-accuracy=0.781563
2016-05-03 13:53:36,415 Node[0] Epoch[9] Batch [250] Speed: 622.48 samples/sec Train-accuracy=0.779531
2016-05-03 13:53:46,756 Node[0] Epoch[9] Batch [300] Speed: 618.91 samples/sec Train-accuracy=0.782188
2016-05-03 13:53:57,059 Node[0] Epoch[9] Batch [350] Speed: 621.22 samples/sec Train-accuracy=0.779062
2016-05-03 13:54:05,466 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 13:54:05,466 Node[0] Epoch[9] Time cost=80.398
2016-05-03 13:54:05,625 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 13:54:07,564 Node[0] Epoch[9] Validation-accuracy=0.721554
2016-05-03 13:54:17,870 Node[0] Epoch[10] Batch [50] Speed: 624.27 samples/sec Train-accuracy=0.787656
2016-05-03 13:54:28,172 Node[0] Epoch[10] Batch [100] Speed: 621.26 samples/sec Train-accuracy=0.788906
2016-05-03 13:54:38,438 Node[0] Epoch[10] Batch [150] Speed: 623.38 samples/sec Train-accuracy=0.800312
2016-05-03 13:54:48,676 Node[0] Epoch[10] Batch [200] Speed: 625.14 samples/sec Train-accuracy=0.790156
2016-05-03 13:54:58,973 Node[0] Epoch[10] Batch [250] Speed: 621.58 samples/sec Train-accuracy=0.787031
2016-05-03 13:55:09,254 Node[0] Epoch[10] Batch [300] Speed: 622.54 samples/sec Train-accuracy=0.799063
2016-05-03 13:55:19,549 Node[0] Epoch[10] Batch [350] Speed: 621.66 samples/sec Train-accuracy=0.795625
2016-05-03 13:55:27,753 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 13:55:27,753 Node[0] Epoch[10] Time cost=80.189
2016-05-03 13:55:27,913 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 13:55:29,863 Node[0] Epoch[10] Validation-accuracy=0.779748
2016-05-03 13:55:40,054 Node[0] Epoch[11] Batch [50] Speed: 631.33 samples/sec Train-accuracy=0.797656
2016-05-03 13:55:50,288 Node[0] Epoch[11] Batch [100] Speed: 625.36 samples/sec Train-accuracy=0.799375
2016-05-03 13:56:00,522 Node[0] Epoch[11] Batch [150] Speed: 625.41 samples/sec Train-accuracy=0.807656
2016-05-03 13:56:10,764 Node[0] Epoch[11] Batch [200] Speed: 624.88 samples/sec Train-accuracy=0.796562
2016-05-03 13:56:21,102 Node[0] Epoch[11] Batch [250] Speed: 619.09 samples/sec Train-accuracy=0.802344
2016-05-03 13:56:31,399 Node[0] Epoch[11] Batch [300] Speed: 621.58 samples/sec Train-accuracy=0.802344
2016-05-03 13:56:41,693 Node[0] Epoch[11] Batch [350] Speed: 621.74 samples/sec Train-accuracy=0.804063
2016-05-03 13:56:50,129 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 13:56:50,130 Node[0] Epoch[11] Time cost=80.267
2016-05-03 13:56:50,290 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 13:56:52,216 Node[0] Epoch[11] Validation-accuracy=0.741987
2016-05-03 13:57:02,431 Node[0] Epoch[12] Batch [50] Speed: 629.84 samples/sec Train-accuracy=0.803281
2016-05-03 13:57:12,760 Node[0] Epoch[12] Batch [100] Speed: 619.62 samples/sec Train-accuracy=0.811250
2016-05-03 13:57:23,010 Node[0] Epoch[12] Batch [150] Speed: 624.40 samples/sec Train-accuracy=0.814375
2016-05-03 13:57:33,179 Node[0] Epoch[12] Batch [200] Speed: 629.37 samples/sec Train-accuracy=0.804531
2016-05-03 13:57:43,414 Node[0] Epoch[12] Batch [250] Speed: 625.32 samples/sec Train-accuracy=0.806250
2016-05-03 13:57:53,614 Node[0] Epoch[12] Batch [300] Speed: 627.47 samples/sec Train-accuracy=0.811094
2016-05-03 13:58:03,808 Node[0] Epoch[12] Batch [350] Speed: 627.85 samples/sec Train-accuracy=0.806719
2016-05-03 13:58:12,244 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 13:58:12,245 Node[0] Epoch[12] Time cost=80.029
2016-05-03 13:58:12,404 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 13:58:14,340 Node[0] Epoch[12] Validation-accuracy=0.791266
2016-05-03 13:58:24,698 Node[0] Epoch[13] Batch [50] Speed: 621.16 samples/sec Train-accuracy=0.810625
2016-05-03 13:58:34,982 Node[0] Epoch[13] Batch [100] Speed: 622.36 samples/sec Train-accuracy=0.822187
2016-05-03 13:58:45,249 Node[0] Epoch[13] Batch [150] Speed: 623.39 samples/sec Train-accuracy=0.822344
2016-05-03 13:58:55,471 Node[0] Epoch[13] Batch [200] Speed: 626.09 samples/sec Train-accuracy=0.814531
2016-05-03 13:59:05,736 Node[0] Epoch[13] Batch [250] Speed: 623.51 samples/sec Train-accuracy=0.813750
2016-05-03 13:59:15,973 Node[0] Epoch[13] Batch [300] Speed: 625.21 samples/sec Train-accuracy=0.818438
2016-05-03 13:59:26,231 Node[0] Epoch[13] Batch [350] Speed: 623.91 samples/sec Train-accuracy=0.817656
2016-05-03 13:59:34,430 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 13:59:34,430 Node[0] Epoch[13] Time cost=80.091
2016-05-03 13:59:34,596 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 13:59:36,531 Node[0] Epoch[13] Validation-accuracy=0.773938
2016-05-03 13:59:46,916 Node[0] Epoch[14] Batch [50] Speed: 619.55 samples/sec Train-accuracy=0.822969
2016-05-03 13:59:57,208 Node[0] Epoch[14] Batch [100] Speed: 621.87 samples/sec Train-accuracy=0.825313
2016-05-03 14:00:07,488 Node[0] Epoch[14] Batch [150] Speed: 622.59 samples/sec Train-accuracy=0.819688
2016-05-03 14:00:17,777 Node[0] Epoch[14] Batch [200] Speed: 622.00 samples/sec Train-accuracy=0.821875
2016-05-03 14:00:28,034 Node[0] Epoch[14] Batch [250] Speed: 624.00 samples/sec Train-accuracy=0.823125
2016-05-03 14:00:38,279 Node[0] Epoch[14] Batch [300] Speed: 624.71 samples/sec Train-accuracy=0.825937
2016-05-03 14:00:48,539 Node[0] Epoch[14] Batch [350] Speed: 623.83 samples/sec Train-accuracy=0.825937
2016-05-03 14:00:56,909 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 14:00:56,909 Node[0] Epoch[14] Time cost=80.378
2016-05-03 14:00:57,068 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 14:00:59,052 Node[0] Epoch[14] Validation-accuracy=0.755609
2016-05-03 14:01:09,406 Node[0] Epoch[15] Batch [50] Speed: 621.46 samples/sec Train-accuracy=0.828750
2016-05-03 14:01:19,708 Node[0] Epoch[15] Batch [100] Speed: 621.25 samples/sec Train-accuracy=0.832187
2016-05-03 14:01:29,996 Node[0] Epoch[15] Batch [150] Speed: 622.08 samples/sec Train-accuracy=0.836562
2016-05-03 14:01:40,302 Node[0] Epoch[15] Batch [200] Speed: 621.01 samples/sec Train-accuracy=0.829531
2016-05-03 14:01:50,529 Node[0] Epoch[15] Batch [250] Speed: 625.81 samples/sec Train-accuracy=0.824844
2016-05-03 14:02:00,814 Node[0] Epoch[15] Batch [300] Speed: 622.32 samples/sec Train-accuracy=0.823750
2016-05-03 14:02:11,072 Node[0] Epoch[15] Batch [350] Speed: 623.87 samples/sec Train-accuracy=0.825937
2016-05-03 14:02:19,269 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 14:02:19,269 Node[0] Epoch[15] Time cost=80.217
2016-05-03 14:02:19,427 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 14:02:21,376 Node[0] Epoch[15] Validation-accuracy=0.808193
2016-05-03 14:02:31,682 Node[0] Epoch[16] Batch [50] Speed: 624.29 samples/sec Train-accuracy=0.832656
2016-05-03 14:02:41,945 Node[0] Epoch[16] Batch [100] Speed: 623.59 samples/sec Train-accuracy=0.835156
2016-05-03 14:02:52,221 Node[0] Epoch[16] Batch [150] Speed: 622.83 samples/sec Train-accuracy=0.842812
2016-05-03 14:03:02,498 Node[0] Epoch[16] Batch [200] Speed: 622.79 samples/sec Train-accuracy=0.833906
2016-05-03 14:03:12,766 Node[0] Epoch[16] Batch [250] Speed: 623.30 samples/sec Train-accuracy=0.832969
2016-05-03 14:03:23,050 Node[0] Epoch[16] Batch [300] Speed: 622.32 samples/sec Train-accuracy=0.837344
2016-05-03 14:03:33,358 Node[0] Epoch[16] Batch [350] Speed: 620.92 samples/sec Train-accuracy=0.837969
2016-05-03 14:03:41,783 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 14:03:41,783 Node[0] Epoch[16] Time cost=80.407
2016-05-03 14:03:41,945 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 14:03:44,026 Node[0] Epoch[16] Validation-accuracy=0.787777
2016-05-03 14:03:54,300 Node[0] Epoch[17] Batch [50] Speed: 626.23 samples/sec Train-accuracy=0.836875
2016-05-03 14:04:04,596 Node[0] Epoch[17] Batch [100] Speed: 621.60 samples/sec Train-accuracy=0.837500
2016-05-03 14:04:14,848 Node[0] Epoch[17] Batch [150] Speed: 624.30 samples/sec Train-accuracy=0.842031
2016-05-03 14:04:25,106 Node[0] Epoch[17] Batch [200] Speed: 623.88 samples/sec Train-accuracy=0.839688
2016-05-03 14:04:35,328 Node[0] Epoch[17] Batch [250] Speed: 626.14 samples/sec Train-accuracy=0.839219
2016-05-03 14:04:45,570 Node[0] Epoch[17] Batch [300] Speed: 624.89 samples/sec Train-accuracy=0.839063
2016-05-03 14:04:55,792 Node[0] Epoch[17] Batch [350] Speed: 626.12 samples/sec Train-accuracy=0.836406
2016-05-03 14:05:04,160 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 14:05:04,160 Node[0] Epoch[17] Time cost=80.134
2016-05-03 14:05:04,323 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 14:05:06,278 Node[0] Epoch[17] Validation-accuracy=0.760917
2016-05-03 14:05:16,607 Node[0] Epoch[18] Batch [50] Speed: 622.83 samples/sec Train-accuracy=0.838281
2016-05-03 14:05:26,902 Node[0] Epoch[18] Batch [100] Speed: 621.73 samples/sec Train-accuracy=0.840938
2016-05-03 14:05:37,155 Node[0] Epoch[18] Batch [150] Speed: 624.24 samples/sec Train-accuracy=0.851562
2016-05-03 14:05:47,390 Node[0] Epoch[18] Batch [200] Speed: 625.31 samples/sec Train-accuracy=0.838750
2016-05-03 14:05:57,628 Node[0] Epoch[18] Batch [250] Speed: 625.11 samples/sec Train-accuracy=0.842031
2016-05-03 14:06:07,933 Node[0] Epoch[18] Batch [300] Speed: 621.10 samples/sec Train-accuracy=0.843906
2016-05-03 14:06:18,201 Node[0] Epoch[18] Batch [350] Speed: 623.29 samples/sec Train-accuracy=0.843437
2016-05-03 14:06:26,472 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 14:06:26,472 Node[0] Epoch[18] Time cost=80.194
2016-05-03 14:06:26,632 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 14:06:28,572 Node[0] Epoch[18] Validation-accuracy=0.808894
2016-05-03 14:06:38,870 Node[0] Epoch[19] Batch [50] Speed: 624.77 samples/sec Train-accuracy=0.847969
2016-05-03 14:06:49,109 Node[0] Epoch[19] Batch [100] Speed: 625.11 samples/sec Train-accuracy=0.847812
2016-05-03 14:06:59,348 Node[0] Epoch[19] Batch [150] Speed: 625.06 samples/sec Train-accuracy=0.851406
2016-05-03 14:07:09,631 Node[0] Epoch[19] Batch [200] Speed: 622.41 samples/sec Train-accuracy=0.849219
2016-05-03 14:07:19,917 Node[0] Epoch[19] Batch [250] Speed: 622.24 samples/sec Train-accuracy=0.843906
2016-05-03 14:07:30,161 Node[0] Epoch[19] Batch [300] Speed: 624.75 samples/sec Train-accuracy=0.851094
2016-05-03 14:07:40,420 Node[0] Epoch[19] Batch [350] Speed: 623.89 samples/sec Train-accuracy=0.848437
2016-05-03 14:07:48,854 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 14:07:48,854 Node[0] Epoch[19] Time cost=80.282
2016-05-03 14:07:49,014 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 14:07:50,955 Node[0] Epoch[19] Validation-accuracy=0.805188
2016-05-03 14:08:01,258 Node[0] Epoch[20] Batch [50] Speed: 624.41 samples/sec Train-accuracy=0.849219
2016-05-03 14:08:11,492 Node[0] Epoch[20] Batch [100] Speed: 625.44 samples/sec Train-accuracy=0.851094
2016-05-03 14:08:21,728 Node[0] Epoch[20] Batch [150] Speed: 625.26 samples/sec Train-accuracy=0.856406
2016-05-03 14:08:32,004 Node[0] Epoch[20] Batch [200] Speed: 622.80 samples/sec Train-accuracy=0.851094
2016-05-03 14:08:42,249 Node[0] Epoch[20] Batch [250] Speed: 624.73 samples/sec Train-accuracy=0.843906
2016-05-03 14:08:52,494 Node[0] Epoch[20] Batch [300] Speed: 624.70 samples/sec Train-accuracy=0.850000
2016-05-03 14:09:02,734 Node[0] Epoch[20] Batch [350] Speed: 625.05 samples/sec Train-accuracy=0.852656
2016-05-03 14:09:11,123 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 14:09:11,123 Node[0] Epoch[20] Time cost=80.168
2016-05-03 14:09:11,280 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 14:09:13,224 Node[0] Epoch[20] Validation-accuracy=0.821715
2016-05-03 14:09:23,595 Node[0] Epoch[21] Batch [50] Speed: 620.37 samples/sec Train-accuracy=0.851406
2016-05-03 14:09:33,829 Node[0] Epoch[21] Batch [100] Speed: 625.39 samples/sec Train-accuracy=0.850469
2016-05-03 14:09:44,066 Node[0] Epoch[21] Batch [150] Speed: 625.19 samples/sec Train-accuracy=0.864531
2016-05-03 14:09:54,329 Node[0] Epoch[21] Batch [200] Speed: 623.62 samples/sec Train-accuracy=0.856875
2016-05-03 14:10:04,614 Node[0] Epoch[21] Batch [250] Speed: 622.28 samples/sec Train-accuracy=0.849688
2016-05-03 14:10:14,876 Node[0] Epoch[21] Batch [300] Speed: 623.70 samples/sec Train-accuracy=0.860781
2016-05-03 14:10:25,188 Node[0] Epoch[21] Batch [350] Speed: 620.62 samples/sec Train-accuracy=0.853750
2016-05-03 14:10:33,411 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 14:10:33,411 Node[0] Epoch[21] Time cost=80.187
2016-05-03 14:10:33,573 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 14:10:35,494 Node[0] Epoch[21] Validation-accuracy=0.800080
2016-05-03 14:10:45,720 Node[0] Epoch[22] Batch [50] Speed: 629.09 samples/sec Train-accuracy=0.855781
2016-05-03 14:10:55,973 Node[0] Epoch[22] Batch [100] Speed: 624.24 samples/sec Train-accuracy=0.857969
2016-05-03 14:11:06,256 Node[0] Epoch[22] Batch [150] Speed: 622.37 samples/sec Train-accuracy=0.865469
2016-05-03 14:11:16,531 Node[0] Epoch[22] Batch [200] Speed: 622.88 samples/sec Train-accuracy=0.853281
2016-05-03 14:11:26,730 Node[0] Epoch[22] Batch [250] Speed: 627.53 samples/sec Train-accuracy=0.856250
2016-05-03 14:11:36,980 Node[0] Epoch[22] Batch [300] Speed: 624.41 samples/sec Train-accuracy=0.860469
2016-05-03 14:11:47,255 Node[0] Epoch[22] Batch [350] Speed: 622.94 samples/sec Train-accuracy=0.859531
2016-05-03 14:11:55,682 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 14:11:55,682 Node[0] Epoch[22] Time cost=80.188
2016-05-03 14:11:55,840 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 14:11:57,764 Node[0] Epoch[22] Validation-accuracy=0.792067
2016-05-03 14:12:08,020 Node[0] Epoch[23] Batch [50] Speed: 627.37 samples/sec Train-accuracy=0.860938
2016-05-03 14:12:18,327 Node[0] Epoch[23] Batch [100] Speed: 620.96 samples/sec Train-accuracy=0.862344
2016-05-03 14:12:28,553 Node[0] Epoch[23] Batch [150] Speed: 625.87 samples/sec Train-accuracy=0.864531
2016-05-03 14:12:38,811 Node[0] Epoch[23] Batch [200] Speed: 623.90 samples/sec Train-accuracy=0.861719
2016-05-03 14:12:49,054 Node[0] Epoch[23] Batch [250] Speed: 624.83 samples/sec Train-accuracy=0.860938
2016-05-03 14:12:59,288 Node[0] Epoch[23] Batch [300] Speed: 625.42 samples/sec Train-accuracy=0.861719
2016-05-03 14:13:09,498 Node[0] Epoch[23] Batch [350] Speed: 626.80 samples/sec Train-accuracy=0.867344
2016-05-03 14:13:17,713 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 14:13:17,713 Node[0] Epoch[23] Time cost=79.948
2016-05-03 14:13:17,873 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 14:13:19,826 Node[0] Epoch[23] Validation-accuracy=0.809495
2016-05-03 14:13:30,224 Node[0] Epoch[24] Batch [50] Speed: 618.89 samples/sec Train-accuracy=0.862656
2016-05-03 14:13:40,541 Node[0] Epoch[24] Batch [100] Speed: 620.30 samples/sec Train-accuracy=0.868437
2016-05-03 14:13:50,792 Node[0] Epoch[24] Batch [150] Speed: 624.34 samples/sec Train-accuracy=0.867500
2016-05-03 14:14:01,008 Node[0] Epoch[24] Batch [200] Speed: 626.51 samples/sec Train-accuracy=0.858594
2016-05-03 14:14:11,260 Node[0] Epoch[24] Batch [250] Speed: 624.28 samples/sec Train-accuracy=0.861875
2016-05-03 14:14:21,470 Node[0] Epoch[24] Batch [300] Speed: 626.86 samples/sec Train-accuracy=0.867500
2016-05-03 14:14:31,695 Node[0] Epoch[24] Batch [350] Speed: 625.92 samples/sec Train-accuracy=0.862656
2016-05-03 14:14:40,144 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 14:14:40,144 Node[0] Epoch[24] Time cost=80.318
2016-05-03 14:14:40,305 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 14:14:42,449 Node[0] Epoch[24] Validation-accuracy=0.814972
2016-05-03 14:14:52,696 Node[0] Epoch[25] Batch [50] Speed: 627.85 samples/sec Train-accuracy=0.867656
2016-05-03 14:15:02,922 Node[0] Epoch[25] Batch [100] Speed: 625.87 samples/sec Train-accuracy=0.870000
2016-05-03 14:15:13,178 Node[0] Epoch[25] Batch [150] Speed: 624.03 samples/sec Train-accuracy=0.869844
2016-05-03 14:15:23,439 Node[0] Epoch[25] Batch [200] Speed: 623.74 samples/sec Train-accuracy=0.870313
2016-05-03 14:15:33,704 Node[0] Epoch[25] Batch [250] Speed: 623.49 samples/sec Train-accuracy=0.867812
2016-05-03 14:15:43,955 Node[0] Epoch[25] Batch [300] Speed: 624.35 samples/sec Train-accuracy=0.874531
2016-05-03 14:15:54,198 Node[0] Epoch[25] Batch [350] Speed: 624.82 samples/sec Train-accuracy=0.870469
2016-05-03 14:16:02,649 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 14:16:02,649 Node[0] Epoch[25] Time cost=80.200
2016-05-03 14:16:02,812 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 14:16:04,734 Node[0] Epoch[25] Validation-accuracy=0.825621
2016-05-03 14:16:15,006 Node[0] Epoch[26] Batch [50] Speed: 626.33 samples/sec Train-accuracy=0.867656
2016-05-03 14:16:25,300 Node[0] Epoch[26] Batch [100] Speed: 621.76 samples/sec Train-accuracy=0.877656
2016-05-03 14:16:35,543 Node[0] Epoch[26] Batch [150] Speed: 624.81 samples/sec Train-accuracy=0.874687
2016-05-03 14:16:45,817 Node[0] Epoch[26] Batch [200] Speed: 622.96 samples/sec Train-accuracy=0.866094
2016-05-03 14:16:56,088 Node[0] Epoch[26] Batch [250] Speed: 623.14 samples/sec Train-accuracy=0.866094
2016-05-03 14:17:06,356 Node[0] Epoch[26] Batch [300] Speed: 623.27 samples/sec Train-accuracy=0.875156
2016-05-03 14:17:16,592 Node[0] Epoch[26] Batch [350] Speed: 625.27 samples/sec Train-accuracy=0.874844
2016-05-03 14:17:24,785 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 14:17:24,786 Node[0] Epoch[26] Time cost=80.051
2016-05-03 14:17:24,945 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 14:17:26,874 Node[0] Epoch[26] Validation-accuracy=0.814804
2016-05-03 14:17:37,135 Node[0] Epoch[27] Batch [50] Speed: 627.04 samples/sec Train-accuracy=0.867344
2016-05-03 14:17:47,399 Node[0] Epoch[27] Batch [100] Speed: 623.54 samples/sec Train-accuracy=0.870469
2016-05-03 14:17:57,651 Node[0] Epoch[27] Batch [150] Speed: 624.28 samples/sec Train-accuracy=0.878594
2016-05-03 14:18:07,946 Node[0] Epoch[27] Batch [200] Speed: 621.68 samples/sec Train-accuracy=0.876094
2016-05-03 14:18:18,205 Node[0] Epoch[27] Batch [250] Speed: 623.85 samples/sec Train-accuracy=0.875313
2016-05-03 14:18:28,433 Node[0] Epoch[27] Batch [300] Speed: 625.74 samples/sec Train-accuracy=0.876250
2016-05-03 14:18:38,681 Node[0] Epoch[27] Batch [350] Speed: 624.55 samples/sec Train-accuracy=0.879375
2016-05-03 14:18:47,112 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 14:18:47,112 Node[0] Epoch[27] Time cost=80.238
2016-05-03 14:18:47,272 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 14:18:49,186 Node[0] Epoch[27] Validation-accuracy=0.819111
2016-05-03 14:18:59,487 Node[0] Epoch[28] Batch [50] Speed: 624.52 samples/sec Train-accuracy=0.870938
2016-05-03 14:19:09,724 Node[0] Epoch[28] Batch [100] Speed: 625.20 samples/sec Train-accuracy=0.879687
2016-05-03 14:19:19,964 Node[0] Epoch[28] Batch [150] Speed: 625.06 samples/sec Train-accuracy=0.881094
2016-05-03 14:19:30,231 Node[0] Epoch[28] Batch [200] Speed: 623.36 samples/sec Train-accuracy=0.869844
2016-05-03 14:19:40,493 Node[0] Epoch[28] Batch [250] Speed: 623.67 samples/sec Train-accuracy=0.870156
2016-05-03 14:19:50,781 Node[0] Epoch[28] Batch [300] Speed: 622.10 samples/sec Train-accuracy=0.877188
2016-05-03 14:20:01,050 Node[0] Epoch[28] Batch [350] Speed: 623.29 samples/sec Train-accuracy=0.875156
2016-05-03 14:20:09,482 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 14:20:09,483 Node[0] Epoch[28] Time cost=80.297
2016-05-03 14:20:09,644 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 14:20:11,551 Node[0] Epoch[28] Validation-accuracy=0.813201
2016-05-03 14:20:21,826 Node[0] Epoch[29] Batch [50] Speed: 626.11 samples/sec Train-accuracy=0.878750
2016-05-03 14:20:32,031 Node[0] Epoch[29] Batch [100] Speed: 627.21 samples/sec Train-accuracy=0.877500
2016-05-03 14:20:42,348 Node[0] Epoch[29] Batch [150] Speed: 620.32 samples/sec Train-accuracy=0.877344
2016-05-03 14:20:52,622 Node[0] Epoch[29] Batch [200] Speed: 622.97 samples/sec Train-accuracy=0.876094
2016-05-03 14:21:02,908 Node[0] Epoch[29] Batch [250] Speed: 622.17 samples/sec Train-accuracy=0.869687
2016-05-03 14:21:13,131 Node[0] Epoch[29] Batch [300] Speed: 626.06 samples/sec Train-accuracy=0.878906
2016-05-03 14:21:23,403 Node[0] Epoch[29] Batch [350] Speed: 623.10 samples/sec Train-accuracy=0.876875
2016-05-03 14:21:31,587 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 14:21:31,587 Node[0] Epoch[29] Time cost=80.036
2016-05-03 14:21:31,748 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 14:21:33,681 Node[0] Epoch[29] Validation-accuracy=0.808393
2016-05-03 14:21:43,926 Node[0] Epoch[30] Batch [50] Speed: 628.03 samples/sec Train-accuracy=0.880781
2016-05-03 14:21:54,176 Node[0] Epoch[30] Batch [100] Speed: 624.41 samples/sec Train-accuracy=0.882344
2016-05-03 14:22:04,367 Node[0] Epoch[30] Batch [150] Speed: 628.00 samples/sec Train-accuracy=0.877812
2016-05-03 14:22:14,632 Node[0] Epoch[30] Batch [200] Speed: 623.51 samples/sec Train-accuracy=0.875313
2016-05-03 14:22:24,966 Node[0] Epoch[30] Batch [250] Speed: 619.31 samples/sec Train-accuracy=0.879375
2016-05-03 14:22:35,302 Node[0] Epoch[30] Batch [300] Speed: 619.21 samples/sec Train-accuracy=0.881563
2016-05-03 14:22:45,581 Node[0] Epoch[30] Batch [350] Speed: 622.66 samples/sec Train-accuracy=0.878125
2016-05-03 14:22:54,034 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 14:22:54,034 Node[0] Epoch[30] Time cost=80.353
2016-05-03 14:22:54,194 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 14:22:56,152 Node[0] Epoch[30] Validation-accuracy=0.815405
2016-05-03 14:23:06,462 Node[0] Epoch[31] Batch [50] Speed: 623.98 samples/sec Train-accuracy=0.881406
2016-05-03 14:23:16,701 Node[0] Epoch[31] Batch [100] Speed: 625.08 samples/sec Train-accuracy=0.883437
2016-05-03 14:23:26,903 Node[0] Epoch[31] Batch [150] Speed: 627.33 samples/sec Train-accuracy=0.886406
2016-05-03 14:23:37,186 Node[0] Epoch[31] Batch [200] Speed: 622.37 samples/sec Train-accuracy=0.883125
2016-05-03 14:23:47,477 Node[0] Epoch[31] Batch [250] Speed: 621.93 samples/sec Train-accuracy=0.886094
2016-05-03 14:23:57,768 Node[0] Epoch[31] Batch [300] Speed: 621.95 samples/sec Train-accuracy=0.884687
2016-05-03 14:24:08,075 Node[0] Epoch[31] Batch [350] Speed: 620.96 samples/sec Train-accuracy=0.884375
2016-05-03 14:24:16,288 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 14:24:16,288 Node[0] Epoch[31] Time cost=80.136
2016-05-03 14:24:16,453 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 14:24:18,325 Node[0] Epoch[31] Validation-accuracy=0.823317
2016-05-03 14:24:28,584 Node[0] Epoch[32] Batch [50] Speed: 627.18 samples/sec Train-accuracy=0.882188
2016-05-03 14:24:38,834 Node[0] Epoch[32] Batch [100] Speed: 624.41 samples/sec Train-accuracy=0.889844
2016-05-03 14:24:49,088 Node[0] Epoch[32] Batch [150] Speed: 624.21 samples/sec Train-accuracy=0.883125
2016-05-03 14:24:59,337 Node[0] Epoch[32] Batch [200] Speed: 624.44 samples/sec Train-accuracy=0.882969
2016-05-03 14:25:09,593 Node[0] Epoch[32] Batch [250] Speed: 624.03 samples/sec Train-accuracy=0.879531
2016-05-03 14:25:19,844 Node[0] Epoch[32] Batch [300] Speed: 624.38 samples/sec Train-accuracy=0.885469
2016-05-03 14:25:30,108 Node[0] Epoch[32] Batch [350] Speed: 623.51 samples/sec Train-accuracy=0.890938
2016-05-03 14:25:38,511 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 14:25:38,511 Node[0] Epoch[32] Time cost=80.186
2016-05-03 14:25:38,670 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 14:25:40,793 Node[0] Epoch[32] Validation-accuracy=0.815269
2016-05-03 14:25:51,132 Node[0] Epoch[33] Batch [50] Speed: 622.22 samples/sec Train-accuracy=0.883750
2016-05-03 14:26:01,382 Node[0] Epoch[33] Batch [100] Speed: 624.40 samples/sec Train-accuracy=0.886719
2016-05-03 14:26:11,641 Node[0] Epoch[33] Batch [150] Speed: 623.90 samples/sec Train-accuracy=0.888125
2016-05-03 14:26:21,879 Node[0] Epoch[33] Batch [200] Speed: 625.14 samples/sec Train-accuracy=0.883906
2016-05-03 14:26:32,085 Node[0] Epoch[33] Batch [250] Speed: 627.06 samples/sec Train-accuracy=0.886563
2016-05-03 14:26:42,328 Node[0] Epoch[33] Batch [300] Speed: 624.83 samples/sec Train-accuracy=0.885312
2016-05-03 14:26:52,631 Node[0] Epoch[33] Batch [350] Speed: 621.22 samples/sec Train-accuracy=0.885000
2016-05-03 14:27:01,056 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 14:27:01,056 Node[0] Epoch[33] Time cost=80.263
2016-05-03 14:27:01,216 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 14:27:03,128 Node[0] Epoch[33] Validation-accuracy=0.828325
2016-05-03 14:27:13,470 Node[0] Epoch[34] Batch [50] Speed: 622.11 samples/sec Train-accuracy=0.885625
2016-05-03 14:27:23,712 Node[0] Epoch[34] Batch [100] Speed: 624.92 samples/sec Train-accuracy=0.892813
2016-05-03 14:27:33,978 Node[0] Epoch[34] Batch [150] Speed: 623.43 samples/sec Train-accuracy=0.890625
2016-05-03 14:27:44,241 Node[0] Epoch[34] Batch [200] Speed: 623.60 samples/sec Train-accuracy=0.886094
2016-05-03 14:27:54,474 Node[0] Epoch[34] Batch [250] Speed: 625.47 samples/sec Train-accuracy=0.891094
2016-05-03 14:28:04,781 Node[0] Epoch[34] Batch [300] Speed: 620.93 samples/sec Train-accuracy=0.892344
2016-05-03 14:28:15,023 Node[0] Epoch[34] Batch [350] Speed: 624.92 samples/sec Train-accuracy=0.884375
2016-05-03 14:28:23,243 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 14:28:23,243 Node[0] Epoch[34] Time cost=80.115
2016-05-03 14:28:23,405 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 14:28:25,361 Node[0] Epoch[34] Validation-accuracy=0.824419
2016-05-03 14:28:35,685 Node[0] Epoch[35] Batch [50] Speed: 623.14 samples/sec Train-accuracy=0.885938
2016-05-03 14:28:45,950 Node[0] Epoch[35] Batch [100] Speed: 623.51 samples/sec Train-accuracy=0.887969
2016-05-03 14:28:56,221 Node[0] Epoch[35] Batch [150] Speed: 623.14 samples/sec Train-accuracy=0.892031
2016-05-03 14:29:06,477 Node[0] Epoch[35] Batch [200] Speed: 624.03 samples/sec Train-accuracy=0.887344
2016-05-03 14:29:16,761 Node[0] Epoch[35] Batch [250] Speed: 622.35 samples/sec Train-accuracy=0.892344
2016-05-03 14:29:27,038 Node[0] Epoch[35] Batch [300] Speed: 622.76 samples/sec Train-accuracy=0.886250
2016-05-03 14:29:37,246 Node[0] Epoch[35] Batch [350] Speed: 626.96 samples/sec Train-accuracy=0.891719
2016-05-03 14:29:45,663 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 14:29:45,663 Node[0] Epoch[35] Time cost=80.302
2016-05-03 14:29:45,822 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 14:29:47,769 Node[0] Epoch[35] Validation-accuracy=0.824820
2016-05-03 14:29:58,081 Node[0] Epoch[36] Batch [50] Speed: 623.99 samples/sec Train-accuracy=0.889687
2016-05-03 14:30:08,355 Node[0] Epoch[36] Batch [100] Speed: 622.91 samples/sec Train-accuracy=0.898125
2016-05-03 14:30:18,605 Node[0] Epoch[36] Batch [150] Speed: 624.42 samples/sec Train-accuracy=0.894844
2016-05-03 14:30:28,864 Node[0] Epoch[36] Batch [200] Speed: 623.84 samples/sec Train-accuracy=0.888125
2016-05-03 14:30:39,116 Node[0] Epoch[36] Batch [250] Speed: 624.32 samples/sec Train-accuracy=0.892500
2016-05-03 14:30:49,365 Node[0] Epoch[36] Batch [300] Speed: 624.49 samples/sec Train-accuracy=0.890625
2016-05-03 14:31:00,385 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 14:31:05,580 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 14:31:05,969 Node[0] Start training with [gpu(0)]
2016-05-03 14:31:27,145 Node[0] Epoch[0] Batch [50] Speed: 649.49 samples/sec Train-accuracy=0.130781
2016-05-03 14:31:37,191 Node[0] Epoch[0] Batch [100] Speed: 637.10 samples/sec Train-accuracy=0.214688
2016-05-03 14:31:47,224 Node[0] Epoch[0] Batch [150] Speed: 637.90 samples/sec Train-accuracy=0.260469
2016-05-03 14:31:57,503 Node[0] Epoch[0] Batch [200] Speed: 622.65 samples/sec Train-accuracy=0.291250
2016-05-03 14:32:08,253 Node[0] Epoch[0] Batch [250] Speed: 595.39 samples/sec Train-accuracy=0.337656
2016-05-03 14:32:19,136 Node[0] Epoch[0] Batch [300] Speed: 588.08 samples/sec Train-accuracy=0.360781
2016-05-03 14:32:29,959 Node[0] Epoch[0] Batch [350] Speed: 591.35 samples/sec Train-accuracy=0.369063
2016-05-03 14:32:38,781 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 14:32:38,782 Node[0] Epoch[0] Time cost=81.743
2016-05-03 14:32:38,952 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 14:32:41,104 Node[0] Epoch[0] Validation-accuracy=0.417128
2016-05-03 14:32:51,840 Node[0] Epoch[1] Batch [50] Speed: 599.24 samples/sec Train-accuracy=0.401875
2016-05-03 14:33:02,614 Node[0] Epoch[1] Batch [100] Speed: 594.01 samples/sec Train-accuracy=0.433125
2016-05-03 14:33:13,344 Node[0] Epoch[1] Batch [150] Speed: 596.49 samples/sec Train-accuracy=0.446094
2016-05-03 14:33:24,047 Node[0] Epoch[1] Batch [200] Speed: 597.99 samples/sec Train-accuracy=0.447031
2016-05-03 14:33:34,682 Node[0] Epoch[1] Batch [250] Speed: 601.79 samples/sec Train-accuracy=0.468594
2016-05-03 14:33:45,235 Node[0] Epoch[1] Batch [300] Speed: 606.48 samples/sec Train-accuracy=0.475625
2016-05-03 14:33:55,827 Node[0] Epoch[1] Batch [350] Speed: 604.25 samples/sec Train-accuracy=0.481563
2016-05-03 14:34:04,492 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 14:34:04,492 Node[0] Epoch[1] Time cost=83.388
2016-05-03 14:34:04,659 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 14:34:06,598 Node[0] Epoch[1] Validation-accuracy=0.494191
2016-05-03 14:34:17,314 Node[0] Epoch[2] Batch [50] Speed: 600.44 samples/sec Train-accuracy=0.499219
2016-05-03 14:34:27,888 Node[0] Epoch[2] Batch [100] Speed: 605.26 samples/sec Train-accuracy=0.520000
2016-05-03 14:34:38,456 Node[0] Epoch[2] Batch [150] Speed: 605.63 samples/sec Train-accuracy=0.529375
2016-05-03 14:34:49,017 Node[0] Epoch[2] Batch [200] Speed: 606.01 samples/sec Train-accuracy=0.532188
2016-05-03 14:34:59,587 Node[0] Epoch[2] Batch [250] Speed: 605.52 samples/sec Train-accuracy=0.541875
2016-05-03 14:35:10,163 Node[0] Epoch[2] Batch [300] Speed: 605.16 samples/sec Train-accuracy=0.542969
2016-05-03 14:35:20,638 Node[0] Epoch[2] Batch [350] Speed: 610.95 samples/sec Train-accuracy=0.560312
2016-05-03 14:35:29,015 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 14:35:29,015 Node[0] Epoch[2] Time cost=82.417
2016-05-03 14:35:29,181 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 14:35:31,136 Node[0] Epoch[2] Validation-accuracy=0.553886
2016-05-03 14:35:41,642 Node[0] Epoch[3] Batch [50] Speed: 612.45 samples/sec Train-accuracy=0.575937
2016-05-03 14:35:52,083 Node[0] Epoch[3] Batch [100] Speed: 612.98 samples/sec Train-accuracy=0.583438
2016-05-03 14:36:02,484 Node[0] Epoch[3] Batch [150] Speed: 615.34 samples/sec Train-accuracy=0.594688
2016-05-03 14:36:12,929 Node[0] Epoch[3] Batch [200] Speed: 612.77 samples/sec Train-accuracy=0.596250
2016-05-03 14:36:23,447 Node[0] Epoch[3] Batch [250] Speed: 608.49 samples/sec Train-accuracy=0.598750
2016-05-03 14:36:33,951 Node[0] Epoch[3] Batch [300] Speed: 609.30 samples/sec Train-accuracy=0.606719
2016-05-03 14:36:44,483 Node[0] Epoch[3] Batch [350] Speed: 607.69 samples/sec Train-accuracy=0.620313
2016-05-03 14:36:53,004 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 14:36:53,004 Node[0] Epoch[3] Time cost=81.868
2016-05-03 14:36:53,167 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 14:36:55,132 Node[0] Epoch[3] Validation-accuracy=0.606370
2016-05-03 14:37:05,630 Node[0] Epoch[4] Batch [50] Speed: 612.92 samples/sec Train-accuracy=0.632969
2016-05-03 14:37:16,034 Node[0] Epoch[4] Batch [100] Speed: 615.18 samples/sec Train-accuracy=0.645625
2016-05-03 14:37:26,374 Node[0] Epoch[4] Batch [150] Speed: 618.96 samples/sec Train-accuracy=0.645312
2016-05-03 14:37:36,783 Node[0] Epoch[4] Batch [200] Speed: 614.90 samples/sec Train-accuracy=0.647969
2016-05-03 14:37:47,175 Node[0] Epoch[4] Batch [250] Speed: 615.87 samples/sec Train-accuracy=0.651250
2016-05-03 14:37:57,570 Node[0] Epoch[4] Batch [300] Speed: 615.69 samples/sec Train-accuracy=0.661563
2016-05-03 14:38:07,920 Node[0] Epoch[4] Batch [350] Speed: 618.36 samples/sec Train-accuracy=0.666250
2016-05-03 14:38:16,405 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 14:38:16,405 Node[0] Epoch[4] Time cost=81.272
2016-05-03 14:38:16,571 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 14:38:18,464 Node[0] Epoch[4] Validation-accuracy=0.638221
2016-05-03 14:38:28,921 Node[0] Epoch[5] Batch [50] Speed: 615.25 samples/sec Train-accuracy=0.665156
2016-05-03 14:38:39,310 Node[0] Epoch[5] Batch [100] Speed: 616.06 samples/sec Train-accuracy=0.687656
2016-05-03 14:38:49,647 Node[0] Epoch[5] Batch [150] Speed: 619.15 samples/sec Train-accuracy=0.677188
2016-05-03 14:38:59,950 Node[0] Epoch[5] Batch [200] Speed: 621.16 samples/sec Train-accuracy=0.681875
2016-05-03 14:39:10,284 Node[0] Epoch[5] Batch [250] Speed: 619.32 samples/sec Train-accuracy=0.689375
2016-05-03 14:39:20,671 Node[0] Epoch[5] Batch [300] Speed: 616.17 samples/sec Train-accuracy=0.686250
2016-05-03 14:39:31,071 Node[0] Epoch[5] Batch [350] Speed: 615.44 samples/sec Train-accuracy=0.691094
2016-05-03 14:39:39,364 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 14:39:39,364 Node[0] Epoch[5] Time cost=80.900
2016-05-03 14:39:39,525 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 14:39:41,426 Node[0] Epoch[5] Validation-accuracy=0.660457
2016-05-03 14:39:51,733 Node[0] Epoch[6] Batch [50] Speed: 624.21 samples/sec Train-accuracy=0.693281
2016-05-03 14:40:02,022 Node[0] Epoch[6] Batch [100] Speed: 622.04 samples/sec Train-accuracy=0.708125
2016-05-03 14:40:12,320 Node[0] Epoch[6] Batch [150] Speed: 621.48 samples/sec Train-accuracy=0.712969
2016-05-03 14:40:22,613 Node[0] Epoch[6] Batch [200] Speed: 621.81 samples/sec Train-accuracy=0.704844
2016-05-03 14:40:32,894 Node[0] Epoch[6] Batch [250] Speed: 622.51 samples/sec Train-accuracy=0.704688
2016-05-03 14:40:43,216 Node[0] Epoch[6] Batch [300] Speed: 620.01 samples/sec Train-accuracy=0.712656
2016-05-03 14:40:53,604 Node[0] Epoch[6] Batch [350] Speed: 616.16 samples/sec Train-accuracy=0.721250
2016-05-03 14:41:02,098 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 14:41:02,098 Node[0] Epoch[6] Time cost=80.673
2016-05-03 14:41:02,264 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 14:41:04,193 Node[0] Epoch[6] Validation-accuracy=0.674980
2016-05-03 14:41:14,565 Node[0] Epoch[7] Batch [50] Speed: 620.23 samples/sec Train-accuracy=0.716719
2016-05-03 14:41:24,902 Node[0] Epoch[7] Batch [100] Speed: 619.17 samples/sec Train-accuracy=0.721250
2016-05-03 14:41:35,226 Node[0] Epoch[7] Batch [150] Speed: 619.95 samples/sec Train-accuracy=0.727656
2016-05-03 14:41:45,557 Node[0] Epoch[7] Batch [200] Speed: 619.49 samples/sec Train-accuracy=0.725781
2016-05-03 14:41:55,843 Node[0] Epoch[7] Batch [250] Speed: 622.26 samples/sec Train-accuracy=0.730625
2016-05-03 14:42:06,129 Node[0] Epoch[7] Batch [300] Speed: 622.20 samples/sec Train-accuracy=0.733125
2016-05-03 14:42:16,467 Node[0] Epoch[7] Batch [350] Speed: 619.07 samples/sec Train-accuracy=0.734688
2016-05-03 14:42:24,701 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 14:42:24,701 Node[0] Epoch[7] Time cost=80.508
2016-05-03 14:42:24,867 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 14:42:26,765 Node[0] Epoch[7] Validation-accuracy=0.664563
2016-05-03 14:42:37,103 Node[0] Epoch[8] Batch [50] Speed: 622.30 samples/sec Train-accuracy=0.732500
2016-05-03 14:42:47,358 Node[0] Epoch[8] Batch [100] Speed: 624.10 samples/sec Train-accuracy=0.742812
2016-05-03 14:42:57,603 Node[0] Epoch[8] Batch [150] Speed: 624.69 samples/sec Train-accuracy=0.753125
2016-05-03 14:43:07,847 Node[0] Epoch[8] Batch [200] Speed: 624.82 samples/sec Train-accuracy=0.745156
2016-05-03 14:43:18,177 Node[0] Epoch[8] Batch [250] Speed: 619.55 samples/sec Train-accuracy=0.735469
2016-05-03 14:43:28,503 Node[0] Epoch[8] Batch [300] Speed: 619.83 samples/sec Train-accuracy=0.746719
2016-05-03 14:43:38,838 Node[0] Epoch[8] Batch [350] Speed: 619.27 samples/sec Train-accuracy=0.741406
2016-05-03 14:43:47,278 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 14:43:47,279 Node[0] Epoch[8] Time cost=80.514
2016-05-03 14:43:47,441 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 14:43:49,546 Node[0] Epoch[8] Validation-accuracy=0.622033
2016-05-03 14:43:59,898 Node[0] Epoch[9] Batch [50] Speed: 621.56 samples/sec Train-accuracy=0.754531
2016-05-03 14:44:10,187 Node[0] Epoch[9] Batch [100] Speed: 622.07 samples/sec Train-accuracy=0.758437
2016-05-03 14:44:20,519 Node[0] Epoch[9] Batch [150] Speed: 619.43 samples/sec Train-accuracy=0.763281
2016-05-03 14:44:30,800 Node[0] Epoch[9] Batch [200] Speed: 622.53 samples/sec Train-accuracy=0.758750
2016-05-03 14:44:41,079 Node[0] Epoch[9] Batch [250] Speed: 622.62 samples/sec Train-accuracy=0.749844
2016-05-03 14:44:51,330 Node[0] Epoch[9] Batch [300] Speed: 624.38 samples/sec Train-accuracy=0.757812
2016-05-03 14:45:01,641 Node[0] Epoch[9] Batch [350] Speed: 620.71 samples/sec Train-accuracy=0.753437
2016-05-03 14:45:10,098 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 14:45:10,098 Node[0] Epoch[9] Time cost=80.551
2016-05-03 14:45:10,256 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 14:45:12,217 Node[0] Epoch[9] Validation-accuracy=0.676282
2016-05-03 14:45:22,617 Node[0] Epoch[10] Batch [50] Speed: 618.61 samples/sec Train-accuracy=0.765469
2016-05-03 14:45:32,973 Node[0] Epoch[10] Batch [100] Speed: 618.06 samples/sec Train-accuracy=0.771875
2016-05-03 14:45:43,270 Node[0] Epoch[10] Batch [150] Speed: 621.53 samples/sec Train-accuracy=0.771719
2016-05-03 14:45:53,570 Node[0] Epoch[10] Batch [200] Speed: 621.36 samples/sec Train-accuracy=0.761094
2016-05-03 14:46:03,812 Node[0] Epoch[10] Batch [250] Speed: 624.94 samples/sec Train-accuracy=0.765156
2016-05-03 14:46:14,086 Node[0] Epoch[10] Batch [300] Speed: 622.93 samples/sec Train-accuracy=0.770781
2016-05-03 14:46:24,344 Node[0] Epoch[10] Batch [350] Speed: 623.93 samples/sec Train-accuracy=0.765156
2016-05-03 14:46:32,588 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 14:46:32,588 Node[0] Epoch[10] Time cost=80.371
2016-05-03 14:46:32,749 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 14:46:34,683 Node[0] Epoch[10] Validation-accuracy=0.657652
2016-05-03 14:46:45,028 Node[0] Epoch[11] Batch [50] Speed: 621.89 samples/sec Train-accuracy=0.770469
2016-05-03 14:46:55,315 Node[0] Epoch[11] Batch [100] Speed: 622.18 samples/sec Train-accuracy=0.779531
2016-05-03 14:47:05,651 Node[0] Epoch[11] Batch [150] Speed: 619.19 samples/sec Train-accuracy=0.795156
2016-05-03 14:47:15,868 Node[0] Epoch[11] Batch [200] Speed: 626.43 samples/sec Train-accuracy=0.778750
2016-05-03 14:47:26,150 Node[0] Epoch[11] Batch [250] Speed: 622.47 samples/sec Train-accuracy=0.775937
2016-05-03 14:47:36,425 Node[0] Epoch[11] Batch [300] Speed: 622.87 samples/sec Train-accuracy=0.789531
2016-05-03 14:47:46,672 Node[0] Epoch[11] Batch [350] Speed: 624.58 samples/sec Train-accuracy=0.782656
2016-05-03 14:47:55,059 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 14:47:55,060 Node[0] Epoch[11] Time cost=80.377
2016-05-03 14:47:55,220 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 14:47:57,185 Node[0] Epoch[11] Validation-accuracy=0.630008
2016-05-03 14:48:07,509 Node[0] Epoch[12] Batch [50] Speed: 623.22 samples/sec Train-accuracy=0.789219
2016-05-03 14:48:17,793 Node[0] Epoch[12] Batch [100] Speed: 622.37 samples/sec Train-accuracy=0.797656
2016-05-03 14:48:28,036 Node[0] Epoch[12] Batch [150] Speed: 624.79 samples/sec Train-accuracy=0.792656
2016-05-03 14:48:38,307 Node[0] Epoch[12] Batch [200] Speed: 623.16 samples/sec Train-accuracy=0.777500
2016-05-03 14:48:48,607 Node[0] Epoch[12] Batch [250] Speed: 621.35 samples/sec Train-accuracy=0.793438
2016-05-03 14:48:58,860 Node[0] Epoch[12] Batch [300] Speed: 624.24 samples/sec Train-accuracy=0.792656
2016-05-03 14:49:09,103 Node[0] Epoch[12] Batch [350] Speed: 624.82 samples/sec Train-accuracy=0.792813
2016-05-03 14:49:17,577 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 14:49:17,577 Node[0] Epoch[12] Time cost=80.392
2016-05-03 14:49:17,736 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 14:49:19,600 Node[0] Epoch[12] Validation-accuracy=0.675881
2016-05-03 14:49:29,915 Node[0] Epoch[13] Batch [50] Speed: 623.79 samples/sec Train-accuracy=0.794531
2016-05-03 14:49:40,245 Node[0] Epoch[13] Batch [100] Speed: 619.54 samples/sec Train-accuracy=0.797656
2016-05-03 14:49:50,473 Node[0] Epoch[13] Batch [150] Speed: 625.77 samples/sec Train-accuracy=0.803594
2016-05-03 14:50:00,660 Node[0] Epoch[13] Batch [200] Speed: 628.25 samples/sec Train-accuracy=0.797969
2016-05-03 14:50:10,879 Node[0] Epoch[13] Batch [250] Speed: 626.36 samples/sec Train-accuracy=0.794687
2016-05-03 14:50:21,135 Node[0] Epoch[13] Batch [300] Speed: 624.05 samples/sec Train-accuracy=0.802031
2016-05-03 14:50:31,358 Node[0] Epoch[13] Batch [350] Speed: 626.03 samples/sec Train-accuracy=0.800156
2016-05-03 14:50:39,566 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 14:50:39,567 Node[0] Epoch[13] Time cost=79.967
2016-05-03 14:50:39,732 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 14:50:41,680 Node[0] Epoch[13] Validation-accuracy=0.655449
2016-05-03 14:50:51,991 Node[0] Epoch[14] Batch [50] Speed: 623.97 samples/sec Train-accuracy=0.796875
2016-05-03 14:51:02,262 Node[0] Epoch[14] Batch [100] Speed: 623.13 samples/sec Train-accuracy=0.810000
2016-05-03 14:51:12,514 Node[0] Epoch[14] Batch [150] Speed: 624.28 samples/sec Train-accuracy=0.812656
2016-05-03 14:51:22,731 Node[0] Epoch[14] Batch [200] Speed: 626.41 samples/sec Train-accuracy=0.802031
2016-05-03 14:51:32,947 Node[0] Epoch[14] Batch [250] Speed: 626.44 samples/sec Train-accuracy=0.807656
2016-05-03 14:51:43,196 Node[0] Epoch[14] Batch [300] Speed: 624.52 samples/sec Train-accuracy=0.806250
2016-05-03 14:51:53,486 Node[0] Epoch[14] Batch [350] Speed: 621.93 samples/sec Train-accuracy=0.813281
2016-05-03 14:52:01,885 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 14:52:01,885 Node[0] Epoch[14] Time cost=80.205
2016-05-03 14:52:02,043 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 14:52:03,925 Node[0] Epoch[14] Validation-accuracy=0.683093
2016-05-03 14:52:14,230 Node[0] Epoch[15] Batch [50] Speed: 624.33 samples/sec Train-accuracy=0.806562
2016-05-03 14:52:24,491 Node[0] Epoch[15] Batch [100] Speed: 623.79 samples/sec Train-accuracy=0.811875
2016-05-03 14:52:34,733 Node[0] Epoch[15] Batch [150] Speed: 624.84 samples/sec Train-accuracy=0.812656
2016-05-03 14:52:44,935 Node[0] Epoch[15] Batch [200] Speed: 627.36 samples/sec Train-accuracy=0.811094
2016-05-03 14:52:55,165 Node[0] Epoch[15] Batch [250] Speed: 625.65 samples/sec Train-accuracy=0.812813
2016-05-03 14:53:05,479 Node[0] Epoch[15] Batch [300] Speed: 620.55 samples/sec Train-accuracy=0.813438
2016-05-03 14:53:15,836 Node[0] Epoch[15] Batch [350] Speed: 617.93 samples/sec Train-accuracy=0.816562
2016-05-03 14:53:24,046 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 14:53:24,046 Node[0] Epoch[15] Time cost=80.121
2016-05-03 14:53:24,206 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 14:53:26,100 Node[0] Epoch[15] Validation-accuracy=0.644832
2016-05-03 14:53:36,335 Node[0] Epoch[16] Batch [50] Speed: 628.65 samples/sec Train-accuracy=0.818281
2016-05-03 14:53:46,634 Node[0] Epoch[16] Batch [100] Speed: 621.46 samples/sec Train-accuracy=0.821875
2016-05-03 14:53:56,894 Node[0] Epoch[16] Batch [150] Speed: 623.79 samples/sec Train-accuracy=0.827656
2016-05-03 14:54:07,183 Node[0] Epoch[16] Batch [200] Speed: 622.05 samples/sec Train-accuracy=0.823594
2016-05-03 14:54:17,419 Node[0] Epoch[16] Batch [250] Speed: 625.24 samples/sec Train-accuracy=0.819531
2016-05-03 14:54:27,675 Node[0] Epoch[16] Batch [300] Speed: 624.04 samples/sec Train-accuracy=0.821094
2016-05-03 14:54:37,932 Node[0] Epoch[16] Batch [350] Speed: 623.97 samples/sec Train-accuracy=0.822187
2016-05-03 14:54:46,351 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 14:54:46,351 Node[0] Epoch[16] Time cost=80.250
2016-05-03 14:54:46,513 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 14:54:48,652 Node[0] Epoch[16] Validation-accuracy=0.643888
2016-05-03 14:54:58,978 Node[0] Epoch[17] Batch [50] Speed: 623.16 samples/sec Train-accuracy=0.829375
2016-05-03 14:55:09,233 Node[0] Epoch[17] Batch [100] Speed: 624.13 samples/sec Train-accuracy=0.834219
2016-05-03 14:55:19,494 Node[0] Epoch[17] Batch [150] Speed: 623.71 samples/sec Train-accuracy=0.826875
2016-05-03 14:55:29,781 Node[0] Epoch[17] Batch [200] Speed: 622.18 samples/sec Train-accuracy=0.828906
2016-05-03 14:55:40,034 Node[0] Epoch[17] Batch [250] Speed: 624.20 samples/sec Train-accuracy=0.824531
2016-05-03 14:55:50,316 Node[0] Epoch[17] Batch [300] Speed: 622.44 samples/sec Train-accuracy=0.833125
2016-05-03 14:56:00,580 Node[0] Epoch[17] Batch [350] Speed: 623.58 samples/sec Train-accuracy=0.824844
2016-05-03 14:56:09,030 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 14:56:09,030 Node[0] Epoch[17] Time cost=80.379
2016-05-03 14:56:09,189 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 14:56:11,096 Node[0] Epoch[17] Validation-accuracy=0.629908
2016-05-03 14:56:21,349 Node[0] Epoch[18] Batch [50] Speed: 627.46 samples/sec Train-accuracy=0.832656
2016-05-03 14:56:31,663 Node[0] Epoch[18] Batch [100] Speed: 620.58 samples/sec Train-accuracy=0.837031
2016-05-03 14:56:41,997 Node[0] Epoch[18] Batch [150] Speed: 619.32 samples/sec Train-accuracy=0.843281
2016-05-03 14:56:52,232 Node[0] Epoch[18] Batch [200] Speed: 625.30 samples/sec Train-accuracy=0.826250
2016-05-03 14:57:02,491 Node[0] Epoch[18] Batch [250] Speed: 623.89 samples/sec Train-accuracy=0.828281
2016-05-03 14:57:12,749 Node[0] Epoch[18] Batch [300] Speed: 623.88 samples/sec Train-accuracy=0.838750
2016-05-03 14:57:23,019 Node[0] Epoch[18] Batch [350] Speed: 623.20 samples/sec Train-accuracy=0.831406
2016-05-03 14:57:31,260 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 14:57:31,260 Node[0] Epoch[18] Time cost=80.164
2016-05-03 14:57:31,424 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 14:57:33,365 Node[0] Epoch[18] Validation-accuracy=0.594852
2016-05-03 14:57:43,692 Node[0] Epoch[19] Batch [50] Speed: 623.12 samples/sec Train-accuracy=0.836406
2016-05-03 14:57:54,039 Node[0] Epoch[19] Batch [100] Speed: 618.53 samples/sec Train-accuracy=0.845156
2016-05-03 14:58:04,309 Node[0] Epoch[19] Batch [150] Speed: 623.21 samples/sec Train-accuracy=0.846406
2016-05-03 14:58:14,569 Node[0] Epoch[19] Batch [200] Speed: 623.79 samples/sec Train-accuracy=0.847812
2016-05-03 14:58:24,821 Node[0] Epoch[19] Batch [250] Speed: 624.29 samples/sec Train-accuracy=0.835156
2016-05-03 14:58:35,082 Node[0] Epoch[19] Batch [300] Speed: 623.71 samples/sec Train-accuracy=0.839375
2016-05-03 14:58:45,337 Node[0] Epoch[19] Batch [350] Speed: 624.12 samples/sec Train-accuracy=0.836250
2016-05-03 14:58:53,779 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 14:58:53,779 Node[0] Epoch[19] Time cost=80.414
2016-05-03 14:58:53,941 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 14:58:55,849 Node[0] Epoch[19] Validation-accuracy=0.581330
2016-05-03 14:59:06,173 Node[0] Epoch[20] Batch [50] Speed: 623.17 samples/sec Train-accuracy=0.846875
2016-05-03 14:59:16,458 Node[0] Epoch[20] Batch [100] Speed: 622.30 samples/sec Train-accuracy=0.842969
2016-05-03 14:59:26,722 Node[0] Epoch[20] Batch [150] Speed: 623.55 samples/sec Train-accuracy=0.836406
2016-05-03 14:59:36,985 Node[0] Epoch[20] Batch [200] Speed: 623.62 samples/sec Train-accuracy=0.846250
2016-05-03 14:59:47,271 Node[0] Epoch[20] Batch [250] Speed: 622.21 samples/sec Train-accuracy=0.841250
2016-05-03 14:59:57,547 Node[0] Epoch[20] Batch [300] Speed: 622.81 samples/sec Train-accuracy=0.848125
2016-05-03 15:00:07,841 Node[0] Epoch[20] Batch [350] Speed: 621.77 samples/sec Train-accuracy=0.847656
2016-05-03 15:00:16,283 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 15:00:16,283 Node[0] Epoch[20] Time cost=80.434
2016-05-03 15:00:16,444 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 15:00:18,349 Node[0] Epoch[20] Validation-accuracy=0.560497
2016-05-03 15:00:28,530 Node[0] Epoch[21] Batch [50] Speed: 632.02 samples/sec Train-accuracy=0.844375
2016-05-03 15:00:38,775 Node[0] Epoch[21] Batch [100] Speed: 624.73 samples/sec Train-accuracy=0.845313
2016-05-03 15:00:49,011 Node[0] Epoch[21] Batch [150] Speed: 625.28 samples/sec Train-accuracy=0.856563
2016-05-03 15:00:59,317 Node[0] Epoch[21] Batch [200] Speed: 621.01 samples/sec Train-accuracy=0.858437
2016-05-03 15:01:09,589 Node[0] Epoch[21] Batch [250] Speed: 623.04 samples/sec Train-accuracy=0.850000
2016-05-03 15:01:19,924 Node[0] Epoch[21] Batch [300] Speed: 619.31 samples/sec Train-accuracy=0.852187
2016-05-03 15:01:30,198 Node[0] Epoch[21] Batch [350] Speed: 622.92 samples/sec Train-accuracy=0.846562
2016-05-03 15:01:38,416 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 15:01:38,416 Node[0] Epoch[21] Time cost=80.067
2016-05-03 15:01:38,578 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 15:01:40,500 Node[0] Epoch[21] Validation-accuracy=0.594351
2016-05-03 15:01:50,743 Node[0] Epoch[22] Batch [50] Speed: 628.08 samples/sec Train-accuracy=0.848750
2016-05-03 15:02:01,043 Node[0] Epoch[22] Batch [100] Speed: 621.39 samples/sec Train-accuracy=0.856250
2016-05-03 15:02:11,317 Node[0] Epoch[22] Batch [150] Speed: 622.94 samples/sec Train-accuracy=0.855469
2016-05-03 15:02:21,581 Node[0] Epoch[22] Batch [200] Speed: 623.59 samples/sec Train-accuracy=0.850156
2016-05-03 15:02:31,894 Node[0] Epoch[22] Batch [250] Speed: 620.57 samples/sec Train-accuracy=0.851875
2016-05-03 15:02:42,119 Node[0] Epoch[22] Batch [300] Speed: 625.94 samples/sec Train-accuracy=0.857656
2016-05-03 15:02:52,382 Node[0] Epoch[22] Batch [350] Speed: 623.59 samples/sec Train-accuracy=0.851719
2016-05-03 15:03:00,827 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 15:03:00,827 Node[0] Epoch[22] Time cost=80.327
2016-05-03 15:03:00,991 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 15:03:02,889 Node[0] Epoch[22] Validation-accuracy=0.527744
2016-05-03 15:03:13,164 Node[0] Epoch[23] Batch [50] Speed: 626.20 samples/sec Train-accuracy=0.853750
2016-05-03 15:03:23,429 Node[0] Epoch[23] Batch [100] Speed: 623.50 samples/sec Train-accuracy=0.860625
2016-05-03 15:03:33,692 Node[0] Epoch[23] Batch [150] Speed: 623.61 samples/sec Train-accuracy=0.856875
2016-05-03 15:03:43,956 Node[0] Epoch[23] Batch [200] Speed: 623.57 samples/sec Train-accuracy=0.853906
2016-05-03 15:03:54,235 Node[0] Epoch[23] Batch [250] Speed: 622.65 samples/sec Train-accuracy=0.851719
2016-05-03 15:04:04,509 Node[0] Epoch[23] Batch [300] Speed: 622.95 samples/sec Train-accuracy=0.858281
2016-05-03 15:04:14,871 Node[0] Epoch[23] Batch [350] Speed: 617.69 samples/sec Train-accuracy=0.858281
2016-05-03 15:04:23,114 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 15:04:23,114 Node[0] Epoch[23] Time cost=80.225
2016-05-03 15:04:23,279 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 15:04:25,171 Node[0] Epoch[23] Validation-accuracy=0.591546
2016-05-03 15:04:35,367 Node[0] Epoch[24] Batch [50] Speed: 631.08 samples/sec Train-accuracy=0.850156
2016-05-03 15:04:45,720 Node[0] Epoch[24] Batch [100] Speed: 618.20 samples/sec Train-accuracy=0.858594
2016-05-03 15:04:55,995 Node[0] Epoch[24] Batch [150] Speed: 622.85 samples/sec Train-accuracy=0.867031
2016-05-03 15:05:06,285 Node[0] Epoch[24] Batch [200] Speed: 621.97 samples/sec Train-accuracy=0.860781
2016-05-03 15:05:16,550 Node[0] Epoch[24] Batch [250] Speed: 623.55 samples/sec Train-accuracy=0.861250
2016-05-03 15:05:26,832 Node[0] Epoch[24] Batch [300] Speed: 622.41 samples/sec Train-accuracy=0.865156
2016-05-03 15:05:37,086 Node[0] Epoch[24] Batch [350] Speed: 624.17 samples/sec Train-accuracy=0.856094
2016-05-03 15:05:45,508 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 15:05:45,508 Node[0] Epoch[24] Time cost=80.337
2016-05-03 15:05:45,677 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 15:05:47,779 Node[0] Epoch[24] Validation-accuracy=0.513054
2016-05-03 15:05:58,025 Node[0] Epoch[25] Batch [50] Speed: 627.97 samples/sec Train-accuracy=0.869844
2016-05-03 15:06:08,223 Node[0] Epoch[25] Batch [100] Speed: 627.60 samples/sec Train-accuracy=0.862500
2016-05-03 15:06:18,454 Node[0] Epoch[25] Batch [150] Speed: 625.56 samples/sec Train-accuracy=0.865625
2016-05-03 15:06:28,719 Node[0] Epoch[25] Batch [200] Speed: 623.51 samples/sec Train-accuracy=0.864375
2016-05-03 15:06:38,952 Node[0] Epoch[25] Batch [250] Speed: 625.44 samples/sec Train-accuracy=0.862500
2016-05-03 15:06:49,210 Node[0] Epoch[25] Batch [300] Speed: 623.90 samples/sec Train-accuracy=0.860781
2016-05-03 15:06:59,485 Node[0] Epoch[25] Batch [350] Speed: 622.91 samples/sec Train-accuracy=0.862969
2016-05-03 15:07:07,889 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 15:07:07,889 Node[0] Epoch[25] Time cost=80.110
2016-05-03 15:07:08,049 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 15:07:09,954 Node[0] Epoch[25] Validation-accuracy=0.572917
2016-05-03 15:07:20,162 Node[0] Epoch[26] Batch [50] Speed: 630.35 samples/sec Train-accuracy=0.864375
2016-05-03 15:07:30,410 Node[0] Epoch[26] Batch [100] Speed: 624.50 samples/sec Train-accuracy=0.866250
2016-05-03 15:07:40,687 Node[0] Epoch[26] Batch [150] Speed: 622.79 samples/sec Train-accuracy=0.871875
2016-05-03 15:07:50,945 Node[0] Epoch[26] Batch [200] Speed: 623.91 samples/sec Train-accuracy=0.862969
2016-05-03 15:08:01,236 Node[0] Epoch[26] Batch [250] Speed: 621.93 samples/sec Train-accuracy=0.861719
2016-05-03 15:08:11,455 Node[0] Epoch[26] Batch [300] Speed: 626.34 samples/sec Train-accuracy=0.866094
2016-05-03 15:08:21,686 Node[0] Epoch[26] Batch [350] Speed: 625.56 samples/sec Train-accuracy=0.862969
2016-05-03 15:08:29,880 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 15:08:29,880 Node[0] Epoch[26] Time cost=79.926
2016-05-03 15:08:30,040 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 15:08:31,988 Node[0] Epoch[26] Validation-accuracy=0.442408
2016-05-03 15:08:42,291 Node[0] Epoch[27] Batch [50] Speed: 624.49 samples/sec Train-accuracy=0.864531
2016-05-03 15:08:52,548 Node[0] Epoch[27] Batch [100] Speed: 624.02 samples/sec Train-accuracy=0.867188
2016-05-03 15:09:02,777 Node[0] Epoch[27] Batch [150] Speed: 625.65 samples/sec Train-accuracy=0.876094
2016-05-03 15:09:13,062 Node[0] Epoch[27] Batch [200] Speed: 622.28 samples/sec Train-accuracy=0.875313
2016-05-03 15:09:23,388 Node[0] Epoch[27] Batch [250] Speed: 619.84 samples/sec Train-accuracy=0.871719
2016-05-03 15:09:33,659 Node[0] Epoch[27] Batch [300] Speed: 623.13 samples/sec Train-accuracy=0.875313
2016-05-03 15:09:43,955 Node[0] Epoch[27] Batch [350] Speed: 621.61 samples/sec Train-accuracy=0.862969
2016-05-03 15:09:52,342 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 15:09:52,343 Node[0] Epoch[27] Time cost=80.355
2016-05-03 15:09:52,500 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 15:09:54,418 Node[0] Epoch[27] Validation-accuracy=0.450721
2016-05-03 15:10:04,781 Node[0] Epoch[28] Batch [50] Speed: 620.85 samples/sec Train-accuracy=0.874062
2016-05-03 15:10:15,013 Node[0] Epoch[28] Batch [100] Speed: 625.54 samples/sec Train-accuracy=0.867969
2016-05-03 15:10:25,242 Node[0] Epoch[28] Batch [150] Speed: 625.67 samples/sec Train-accuracy=0.880625
2016-05-03 15:10:35,504 Node[0] Epoch[28] Batch [200] Speed: 623.66 samples/sec Train-accuracy=0.865625
2016-05-03 15:10:45,742 Node[0] Epoch[28] Batch [250] Speed: 625.18 samples/sec Train-accuracy=0.870625
2016-05-03 15:10:55,979 Node[0] Epoch[28] Batch [300] Speed: 625.19 samples/sec Train-accuracy=0.880625
2016-05-03 15:11:06,310 Node[0] Epoch[28] Batch [350] Speed: 619.50 samples/sec Train-accuracy=0.870313
2016-05-03 15:11:14,761 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 15:11:14,762 Node[0] Epoch[28] Time cost=80.344
2016-05-03 15:11:14,922 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 15:11:16,805 Node[0] Epoch[28] Validation-accuracy=0.466546
2016-05-03 15:11:27,091 Node[0] Epoch[29] Batch [50] Speed: 625.50 samples/sec Train-accuracy=0.878750
2016-05-03 15:11:37,360 Node[0] Epoch[29] Batch [100] Speed: 623.22 samples/sec Train-accuracy=0.878281
2016-05-03 15:11:47,625 Node[0] Epoch[29] Batch [150] Speed: 623.50 samples/sec Train-accuracy=0.878125
2016-05-03 15:11:57,904 Node[0] Epoch[29] Batch [200] Speed: 622.64 samples/sec Train-accuracy=0.879375
2016-05-03 15:12:08,160 Node[0] Epoch[29] Batch [250] Speed: 624.05 samples/sec Train-accuracy=0.878281
2016-05-03 15:12:18,414 Node[0] Epoch[29] Batch [300] Speed: 624.18 samples/sec Train-accuracy=0.874219
2016-05-03 15:12:28,681 Node[0] Epoch[29] Batch [350] Speed: 623.35 samples/sec Train-accuracy=0.870313
2016-05-03 15:12:36,873 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 15:12:36,873 Node[0] Epoch[29] Time cost=80.068
2016-05-03 15:12:37,032 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 15:12:38,915 Node[0] Epoch[29] Validation-accuracy=0.460337
2016-05-03 15:12:49,305 Node[0] Epoch[30] Batch [50] Speed: 619.28 samples/sec Train-accuracy=0.866250
2016-05-03 15:12:59,575 Node[0] Epoch[30] Batch [100] Speed: 623.21 samples/sec Train-accuracy=0.881875
2016-05-03 15:13:09,896 Node[0] Epoch[30] Batch [150] Speed: 620.13 samples/sec Train-accuracy=0.885625
2016-05-03 15:13:20,127 Node[0] Epoch[30] Batch [200] Speed: 625.53 samples/sec Train-accuracy=0.881719
2016-05-03 15:13:30,404 Node[0] Epoch[30] Batch [250] Speed: 622.77 samples/sec Train-accuracy=0.873125
2016-05-03 15:13:40,687 Node[0] Epoch[30] Batch [300] Speed: 622.37 samples/sec Train-accuracy=0.878437
2016-05-03 15:13:50,940 Node[0] Epoch[30] Batch [350] Speed: 624.25 samples/sec Train-accuracy=0.873437
2016-05-03 15:13:59,356 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 15:13:59,356 Node[0] Epoch[30] Time cost=80.441
2016-05-03 15:13:59,518 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 15:14:01,466 Node[0] Epoch[30] Validation-accuracy=0.398337
2016-05-03 15:14:11,666 Node[0] Epoch[31] Batch [50] Speed: 630.88 samples/sec Train-accuracy=0.874844
2016-05-03 15:14:21,976 Node[0] Epoch[31] Batch [100] Speed: 620.75 samples/sec Train-accuracy=0.879531
2016-05-03 15:14:32,281 Node[0] Epoch[31] Batch [150] Speed: 621.04 samples/sec Train-accuracy=0.886094
2016-05-03 15:14:42,577 Node[0] Epoch[31] Batch [200] Speed: 621.62 samples/sec Train-accuracy=0.881875
2016-05-03 15:14:52,799 Node[0] Epoch[31] Batch [250] Speed: 626.13 samples/sec Train-accuracy=0.883281
2016-05-03 15:15:03,050 Node[0] Epoch[31] Batch [300] Speed: 624.35 samples/sec Train-accuracy=0.877500
2016-05-03 15:15:13,311 Node[0] Epoch[31] Batch [350] Speed: 623.77 samples/sec Train-accuracy=0.872500
2016-05-03 15:15:21,503 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 15:15:21,503 Node[0] Epoch[31] Time cost=80.037
2016-05-03 15:15:21,662 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 15:15:23,590 Node[0] Epoch[31] Validation-accuracy=0.406951
2016-05-03 15:15:33,916 Node[0] Epoch[32] Batch [50] Speed: 623.08 samples/sec Train-accuracy=0.881250
2016-05-03 15:15:44,172 Node[0] Epoch[32] Batch [100] Speed: 624.10 samples/sec Train-accuracy=0.880938
2016-05-03 15:15:54,434 Node[0] Epoch[32] Batch [150] Speed: 623.67 samples/sec Train-accuracy=0.886563
2016-05-03 15:16:04,675 Node[0] Epoch[32] Batch [200] Speed: 624.91 samples/sec Train-accuracy=0.883594
2016-05-03 15:16:14,904 Node[0] Epoch[32] Batch [250] Speed: 625.70 samples/sec Train-accuracy=0.883906
2016-05-03 15:16:25,185 Node[0] Epoch[32] Batch [300] Speed: 622.54 samples/sec Train-accuracy=0.879062
2016-05-03 15:16:35,470 Node[0] Epoch[32] Batch [350] Speed: 622.29 samples/sec Train-accuracy=0.879062
2016-05-03 15:16:43,846 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 15:16:43,846 Node[0] Epoch[32] Time cost=80.256
2016-05-03 15:16:44,011 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 15:16:46,121 Node[0] Epoch[32] Validation-accuracy=0.383307
2016-05-03 15:16:56,439 Node[0] Epoch[33] Batch [50] Speed: 623.60 samples/sec Train-accuracy=0.876563
2016-05-03 15:17:06,692 Node[0] Epoch[33] Batch [100] Speed: 624.21 samples/sec Train-accuracy=0.884062
2016-05-03 15:17:16,899 Node[0] Epoch[33] Batch [150] Speed: 627.01 samples/sec Train-accuracy=0.885312
2016-05-03 15:17:27,149 Node[0] Epoch[33] Batch [200] Speed: 624.43 samples/sec Train-accuracy=0.886094
2016-05-03 15:17:37,404 Node[0] Epoch[33] Batch [250] Speed: 624.13 samples/sec Train-accuracy=0.882188
2016-05-03 15:17:47,698 Node[0] Epoch[33] Batch [300] Speed: 621.69 samples/sec Train-accuracy=0.885000
2016-05-03 15:17:57,964 Node[0] Epoch[33] Batch [350] Speed: 623.45 samples/sec Train-accuracy=0.882656
2016-05-03 15:18:06,350 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 15:18:06,350 Node[0] Epoch[33] Time cost=80.229
2016-05-03 15:18:06,510 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 15:18:08,408 Node[0] Epoch[33] Validation-accuracy=0.376502
2016-05-03 15:18:18,717 Node[0] Epoch[34] Batch [50] Speed: 624.05 samples/sec Train-accuracy=0.882812
2016-05-03 15:18:29,029 Node[0] Epoch[34] Batch [100] Speed: 620.68 samples/sec Train-accuracy=0.883437
2016-05-03 15:18:39,188 Node[0] Epoch[34] Batch [150] Speed: 629.95 samples/sec Train-accuracy=0.884219
2016-05-03 15:18:49,414 Node[0] Epoch[34] Batch [200] Speed: 625.87 samples/sec Train-accuracy=0.886719
2016-05-03 15:18:59,677 Node[0] Epoch[34] Batch [250] Speed: 623.66 samples/sec Train-accuracy=0.885156
2016-05-03 15:19:09,937 Node[0] Epoch[34] Batch [300] Speed: 623.79 samples/sec Train-accuracy=0.887656
2016-05-03 15:19:20,237 Node[0] Epoch[34] Batch [350] Speed: 621.39 samples/sec Train-accuracy=0.888281
2016-05-03 15:19:28,403 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 15:19:28,404 Node[0] Epoch[34] Time cost=79.996
2016-05-03 15:19:28,563 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 15:19:30,489 Node[0] Epoch[34] Validation-accuracy=0.321514
2016-05-03 15:19:40,736 Node[0] Epoch[35] Batch [50] Speed: 627.90 samples/sec Train-accuracy=0.885156
2016-05-03 15:19:50,975 Node[0] Epoch[35] Batch [100] Speed: 625.12 samples/sec Train-accuracy=0.890625
2016-05-03 15:20:01,223 Node[0] Epoch[35] Batch [150] Speed: 624.52 samples/sec Train-accuracy=0.889375
2016-05-03 15:20:11,421 Node[0] Epoch[35] Batch [200] Speed: 627.60 samples/sec Train-accuracy=0.881875
2016-05-03 15:20:21,639 Node[0] Epoch[35] Batch [250] Speed: 626.34 samples/sec Train-accuracy=0.883281
2016-05-03 15:20:31,870 Node[0] Epoch[35] Batch [300] Speed: 625.59 samples/sec Train-accuracy=0.891094
2016-05-03 15:20:42,131 Node[0] Epoch[35] Batch [350] Speed: 623.69 samples/sec Train-accuracy=0.892500
2016-05-03 15:20:50,497 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 15:20:50,497 Node[0] Epoch[35] Time cost=80.008
2016-05-03 15:20:50,656 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 15:20:52,569 Node[0] Epoch[35] Validation-accuracy=0.245292
2016-05-03 15:21:02,814 Node[0] Epoch[36] Batch [50] Speed: 628.00 samples/sec Train-accuracy=0.886719
2016-05-03 15:21:13,012 Node[0] Epoch[36] Batch [100] Speed: 627.54 samples/sec Train-accuracy=0.887344
2016-05-03 15:21:23,181 Node[0] Epoch[36] Batch [150] Speed: 629.38 samples/sec Train-accuracy=0.888750
2016-05-03 15:21:33,316 Node[0] Epoch[36] Batch [200] Speed: 631.49 samples/sec Train-accuracy=0.893437
2016-05-03 15:21:43,546 Node[0] Epoch[36] Batch [250] Speed: 625.66 samples/sec Train-accuracy=0.895156
2016-05-03 15:21:53,785 Node[0] Epoch[36] Batch [300] Speed: 625.06 samples/sec Train-accuracy=0.895312
2016-05-03 15:22:03,991 Node[0] Epoch[36] Batch [350] Speed: 627.12 samples/sec Train-accuracy=0.893594
2016-05-03 15:22:12,366 Node[0] Epoch[36] Resetting Data Iterator
2016-05-03 15:22:12,366 Node[0] Epoch[36] Time cost=79.797
2016-05-03 15:22:12,526 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-03 15:22:14,401 Node[0] Epoch[36] Validation-accuracy=0.341947
2016-05-03 15:22:24,592 Node[0] Epoch[37] Batch [50] Speed: 631.39 samples/sec Train-accuracy=0.890156
2016-05-03 15:22:34,762 Node[0] Epoch[37] Batch [100] Speed: 629.30 samples/sec Train-accuracy=0.891875
2016-05-03 15:22:44,947 Node[0] Epoch[37] Batch [150] Speed: 628.40 samples/sec Train-accuracy=0.895469
2016-05-03 15:22:55,223 Node[0] Epoch[37] Batch [200] Speed: 622.83 samples/sec Train-accuracy=0.889531
2016-05-03 15:23:05,470 Node[0] Epoch[37] Batch [250] Speed: 624.60 samples/sec Train-accuracy=0.888594
2016-05-03 15:23:15,692 Node[0] Epoch[37] Batch [300] Speed: 626.11 samples/sec Train-accuracy=0.891406
2016-05-03 15:23:25,916 Node[0] Epoch[37] Batch [350] Speed: 625.99 samples/sec Train-accuracy=0.893281
2016-05-03 15:23:34,065 Node[0] Epoch[37] Resetting Data Iterator
2016-05-03 15:23:34,065 Node[0] Epoch[37] Time cost=79.663
2016-05-03 15:23:34,228 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-03 15:23:36,149 Node[0] Epoch[37] Validation-accuracy=0.309395
2016-05-03 15:23:46,376 Node[0] Epoch[38] Batch [50] Speed: 629.10 samples/sec Train-accuracy=0.895625
2016-05-03 15:23:56,700 Node[0] Epoch[38] Batch [100] Speed: 619.96 samples/sec Train-accuracy=0.898125
2016-05-03 15:24:06,955 Node[0] Epoch[38] Batch [150] Speed: 624.10 samples/sec Train-accuracy=0.899531
2016-05-03 15:24:17,208 Node[0] Epoch[38] Batch [200] Speed: 624.20 samples/sec Train-accuracy=0.894219
2016-05-03 15:24:27,492 Node[0] Epoch[38] Batch [250] Speed: 622.34 samples/sec Train-accuracy=0.890938
2016-05-03 15:24:37,752 Node[0] Epoch[38] Batch [300] Speed: 623.82 samples/sec Train-accuracy=0.893437
2016-05-03 15:24:47,992 Node[0] Epoch[38] Batch [350] Speed: 625.04 samples/sec Train-accuracy=0.891250
2016-05-03 15:24:56,412 Node[0] Epoch[38] Resetting Data Iterator
2016-05-03 15:24:56,413 Node[0] Epoch[38] Time cost=80.264
2016-05-03 15:24:56,570 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-03 15:24:58,497 Node[0] Epoch[38] Validation-accuracy=0.300381
2016-05-03 15:25:08,741 Node[0] Epoch[39] Batch [50] Speed: 628.05 samples/sec Train-accuracy=0.896406
2016-05-03 15:25:19,043 Node[0] Epoch[39] Batch [100] Speed: 621.22 samples/sec Train-accuracy=0.900469
2016-05-03 15:25:29,274 Node[0] Epoch[39] Batch [150] Speed: 625.57 samples/sec Train-accuracy=0.898281
2016-05-03 15:25:39,520 Node[0] Epoch[39] Batch [200] Speed: 624.67 samples/sec Train-accuracy=0.891406
2016-05-03 15:25:49,739 Node[0] Epoch[39] Batch [250] Speed: 626.32 samples/sec Train-accuracy=0.890156
2016-05-03 15:26:00,001 Node[0] Epoch[39] Batch [300] Speed: 623.66 samples/sec Train-accuracy=0.899687
2016-05-03 15:26:10,275 Node[0] Epoch[39] Batch [350] Speed: 622.92 samples/sec Train-accuracy=0.892656
2016-05-03 15:26:18,471 Node[0] Epoch[39] Resetting Data Iterator
2016-05-03 15:26:18,471 Node[0] Epoch[39] Time cost=79.974
2016-05-03 15:26:18,627 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-03 15:26:20,523 Node[0] Epoch[39] Validation-accuracy=0.319411
2016-05-03 15:26:30,849 Node[0] Epoch[40] Batch [50] Speed: 623.18 samples/sec Train-accuracy=0.896719
2016-05-03 15:26:41,155 Node[0] Epoch[40] Batch [100] Speed: 621.01 samples/sec Train-accuracy=0.890156
2016-05-03 15:26:51,431 Node[0] Epoch[40] Batch [150] Speed: 622.84 samples/sec Train-accuracy=0.901406
2016-05-03 15:27:01,658 Node[0] Epoch[40] Batch [200] Speed: 625.76 samples/sec Train-accuracy=0.896250
2016-05-03 15:27:11,888 Node[0] Epoch[40] Batch [250] Speed: 625.67 samples/sec Train-accuracy=0.900156
2016-05-03 15:27:22,143 Node[0] Epoch[40] Batch [300] Speed: 624.06 samples/sec Train-accuracy=0.899531
2016-05-03 15:27:32,422 Node[0] Epoch[40] Batch [350] Speed: 622.66 samples/sec Train-accuracy=0.899687
2016-05-03 15:27:40,859 Node[0] Epoch[40] Resetting Data Iterator
2016-05-03 15:27:40,860 Node[0] Epoch[40] Time cost=80.337
2016-05-03 15:27:41,020 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-03 15:27:43,152 Node[0] Epoch[40] Validation-accuracy=0.257417
2016-05-03 15:27:53,423 Node[0] Epoch[41] Batch [50] Speed: 626.50 samples/sec Train-accuracy=0.897969
2016-05-03 15:28:03,666 Node[0] Epoch[41] Batch [100] Speed: 624.82 samples/sec Train-accuracy=0.897813
2016-05-03 15:28:13,854 Node[0] Epoch[41] Batch [150] Speed: 628.23 samples/sec Train-accuracy=0.906875
2016-05-03 15:28:24,115 Node[0] Epoch[41] Batch [200] Speed: 623.70 samples/sec Train-accuracy=0.897969
2016-05-03 15:28:34,367 Node[0] Epoch[41] Batch [250] Speed: 624.30 samples/sec Train-accuracy=0.891406
2016-05-03 15:28:44,652 Node[0] Epoch[41] Batch [300] Speed: 622.26 samples/sec Train-accuracy=0.895938
2016-05-03 15:28:54,903 Node[0] Epoch[41] Batch [350] Speed: 624.34 samples/sec Train-accuracy=0.889219
2016-05-03 15:29:03,332 Node[0] Epoch[41] Resetting Data Iterator
2016-05-03 15:29:03,332 Node[0] Epoch[41] Time cost=80.179
2016-05-03 15:29:03,492 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-03 15:29:05,366 Node[0] Epoch[41] Validation-accuracy=0.175280
2016-05-03 15:29:15,598 Node[0] Epoch[42] Batch [50] Speed: 628.74 samples/sec Train-accuracy=0.903906
2016-05-03 15:29:25,873 Node[0] Epoch[42] Batch [100] Speed: 622.87 samples/sec Train-accuracy=0.899219
2016-05-03 15:29:36,101 Node[0] Epoch[42] Batch [150] Speed: 625.77 samples/sec Train-accuracy=0.893906
2016-05-03 15:29:46,343 Node[0] Epoch[42] Batch [200] Speed: 624.88 samples/sec Train-accuracy=0.898750
2016-05-03 15:29:56,600 Node[0] Epoch[42] Batch [250] Speed: 623.98 samples/sec Train-accuracy=0.899219
2016-05-03 15:30:06,835 Node[0] Epoch[42] Batch [300] Speed: 625.34 samples/sec Train-accuracy=0.902344
2016-05-03 15:30:17,093 Node[0] Epoch[42] Batch [350] Speed: 623.92 samples/sec Train-accuracy=0.893125
2016-05-03 15:30:25,258 Node[0] Epoch[42] Resetting Data Iterator
2016-05-03 15:30:25,259 Node[0] Epoch[42] Time cost=79.893
2016-05-03 15:30:25,419 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-03 15:30:27,334 Node[0] Epoch[42] Validation-accuracy=0.211839
2016-05-03 15:30:37,645 Node[0] Epoch[43] Batch [50] Speed: 624.03 samples/sec Train-accuracy=0.890312
2016-05-03 15:30:47,948 Node[0] Epoch[43] Batch [100] Speed: 621.20 samples/sec Train-accuracy=0.901094
2016-05-03 15:30:58,204 Node[0] Epoch[43] Batch [150] Speed: 624.06 samples/sec Train-accuracy=0.898594
2016-05-03 15:31:08,520 Node[0] Epoch[43] Batch [200] Speed: 620.40 samples/sec Train-accuracy=0.903438
2016-05-03 15:31:18,780 Node[0] Epoch[43] Batch [250] Speed: 623.77 samples/sec Train-accuracy=0.895781
2016-05-03 15:31:29,043 Node[0] Epoch[43] Batch [300] Speed: 623.63 samples/sec Train-accuracy=0.901563
2016-05-03 15:31:39,317 Node[0] Epoch[43] Batch [350] Speed: 622.93 samples/sec Train-accuracy=0.896875
2016-05-03 15:31:47,683 Node[0] Epoch[43] Resetting Data Iterator
2016-05-03 15:31:47,683 Node[0] Epoch[43] Time cost=80.349
2016-05-03 15:31:47,845 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-03 15:31:49,795 Node[0] Epoch[43] Validation-accuracy=0.275341
2016-05-03 15:32:00,030 Node[0] Epoch[44] Batch [50] Speed: 628.61 samples/sec Train-accuracy=0.895312
2016-05-03 15:32:10,322 Node[0] Epoch[44] Batch [100] Speed: 621.89 samples/sec Train-accuracy=0.899687
2016-05-03 15:32:20,482 Node[0] Epoch[44] Batch [150] Speed: 629.92 samples/sec Train-accuracy=0.905937
2016-05-03 15:32:30,741 Node[0] Epoch[44] Batch [200] Speed: 623.86 samples/sec Train-accuracy=0.898125
2016-05-03 15:32:41,006 Node[0] Epoch[44] Batch [250] Speed: 623.50 samples/sec Train-accuracy=0.905156
2016-05-03 15:32:51,233 Node[0] Epoch[44] Batch [300] Speed: 625.83 samples/sec Train-accuracy=0.903750
2016-05-03 15:33:01,537 Node[0] Epoch[44] Batch [350] Speed: 621.10 samples/sec Train-accuracy=0.900156
2016-05-03 15:33:09,967 Node[0] Epoch[44] Resetting Data Iterator
2016-05-03 15:33:09,967 Node[0] Epoch[44] Time cost=80.172
2016-05-03 15:33:10,131 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-03 15:33:12,048 Node[0] Epoch[44] Validation-accuracy=0.237380
2016-05-03 15:33:22,273 Node[0] Epoch[45] Batch [50] Speed: 629.18 samples/sec Train-accuracy=0.904844
2016-05-03 15:33:32,486 Node[0] Epoch[45] Batch [100] Speed: 626.71 samples/sec Train-accuracy=0.899687
2016-05-03 15:33:42,713 Node[0] Epoch[45] Batch [150] Speed: 625.76 samples/sec Train-accuracy=0.903906
2016-05-03 15:33:52,937 Node[0] Epoch[45] Batch [200] Speed: 626.02 samples/sec Train-accuracy=0.905156
2016-05-03 15:34:03,222 Node[0] Epoch[45] Batch [250] Speed: 622.26 samples/sec Train-accuracy=0.904844
2016-05-03 15:34:13,446 Node[0] Epoch[45] Batch [300] Speed: 626.01 samples/sec Train-accuracy=0.903438
2016-05-03 15:34:23,652 Node[0] Epoch[45] Batch [350] Speed: 627.11 samples/sec Train-accuracy=0.896719
2016-05-03 15:34:31,811 Node[0] Epoch[45] Resetting Data Iterator
2016-05-03 15:34:31,811 Node[0] Epoch[45] Time cost=79.763
2016-05-03 15:34:31,970 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-03 15:34:33,898 Node[0] Epoch[45] Validation-accuracy=0.199519
2016-05-03 15:34:44,217 Node[0] Epoch[46] Batch [50] Speed: 623.48 samples/sec Train-accuracy=0.904844
2016-05-03 15:34:54,491 Node[0] Epoch[46] Batch [100] Speed: 622.97 samples/sec Train-accuracy=0.900937
2016-05-03 15:35:04,780 Node[0] Epoch[46] Batch [150] Speed: 621.99 samples/sec Train-accuracy=0.909844
2016-05-03 15:35:15,010 Node[0] Epoch[46] Batch [200] Speed: 625.65 samples/sec Train-accuracy=0.905781
2016-05-03 15:35:25,283 Node[0] Epoch[46] Batch [250] Speed: 622.98 samples/sec Train-accuracy=0.905156
2016-05-03 15:35:35,538 Node[0] Epoch[46] Batch [300] Speed: 624.14 samples/sec Train-accuracy=0.901875
2016-05-03 15:35:45,765 Node[0] Epoch[46] Batch [350] Speed: 625.78 samples/sec Train-accuracy=0.897500
2016-05-03 15:35:54,163 Node[0] Epoch[46] Resetting Data Iterator
2016-05-03 15:35:54,164 Node[0] Epoch[46] Time cost=80.266
2016-05-03 15:35:54,325 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-03 15:35:56,272 Node[0] Epoch[46] Validation-accuracy=0.168069
2016-05-03 15:36:06,537 Node[0] Epoch[47] Batch [50] Speed: 626.77 samples/sec Train-accuracy=0.901875
2016-05-03 15:36:16,859 Node[0] Epoch[47] Batch [100] Speed: 620.04 samples/sec Train-accuracy=0.906250
2016-05-03 15:36:27,130 Node[0] Epoch[47] Batch [150] Speed: 623.12 samples/sec Train-accuracy=0.906875
2016-05-03 15:36:37,383 Node[0] Epoch[47] Batch [200] Speed: 624.23 samples/sec Train-accuracy=0.900625
2016-05-03 15:36:47,663 Node[0] Epoch[47] Batch [250] Speed: 622.60 samples/sec Train-accuracy=0.900312
2016-05-03 15:36:57,945 Node[0] Epoch[47] Batch [300] Speed: 622.47 samples/sec Train-accuracy=0.908750
2016-05-03 15:37:08,202 Node[0] Epoch[47] Batch [350] Speed: 623.98 samples/sec Train-accuracy=0.901563
2016-05-03 15:37:16,403 Node[0] Epoch[47] Resetting Data Iterator
2016-05-03 15:37:16,403 Node[0] Epoch[47] Time cost=80.131
2016-05-03 15:37:16,566 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-03 15:37:18,441 Node[0] Epoch[47] Validation-accuracy=0.172576
2016-05-03 15:37:28,642 Node[0] Epoch[48] Batch [50] Speed: 630.70 samples/sec Train-accuracy=0.904687
2016-05-03 15:37:38,893 Node[0] Epoch[48] Batch [100] Speed: 624.36 samples/sec Train-accuracy=0.900781
2016-05-03 15:37:49,179 Node[0] Epoch[48] Batch [150] Speed: 622.23 samples/sec Train-accuracy=0.907969
2016-05-03 15:37:59,448 Node[0] Epoch[48] Batch [200] Speed: 623.22 samples/sec Train-accuracy=0.906094
2016-05-03 15:38:09,689 Node[0] Epoch[48] Batch [250] Speed: 624.99 samples/sec Train-accuracy=0.906563
2016-05-03 15:38:19,921 Node[0] Epoch[48] Batch [300] Speed: 625.50 samples/sec Train-accuracy=0.910625
2016-05-03 15:38:30,182 Node[0] Epoch[48] Batch [350] Speed: 623.71 samples/sec Train-accuracy=0.902813
2016-05-03 15:38:38,635 Node[0] Epoch[48] Resetting Data Iterator
2016-05-03 15:38:38,635 Node[0] Epoch[48] Time cost=80.194
2016-05-03 15:38:38,796 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-03 15:38:40,978 Node[0] Epoch[48] Validation-accuracy=0.187599
2016-05-03 15:38:51,221 Node[0] Epoch[49] Batch [50] Speed: 628.07 samples/sec Train-accuracy=0.900312
2016-05-03 15:39:01,475 Node[0] Epoch[49] Batch [100] Speed: 624.15 samples/sec Train-accuracy=0.905937
2016-05-03 15:39:11,758 Node[0] Epoch[49] Batch [150] Speed: 622.42 samples/sec Train-accuracy=0.908906
2016-05-03 15:39:22,025 Node[0] Epoch[49] Batch [200] Speed: 623.37 samples/sec Train-accuracy=0.910156
2016-05-03 15:39:32,294 Node[0] Epoch[49] Batch [250] Speed: 623.29 samples/sec Train-accuracy=0.903438
2016-05-03 15:39:42,541 Node[0] Epoch[49] Batch [300] Speed: 624.53 samples/sec Train-accuracy=0.905781
2016-05-03 15:39:52,842 Node[0] Epoch[49] Batch [350] Speed: 621.35 samples/sec Train-accuracy=0.905469
2016-05-03 15:40:01,226 Node[0] Epoch[49] Resetting Data Iterator
2016-05-03 15:40:01,226 Node[0] Epoch[49] Time cost=80.247
2016-05-03 15:40:01,385 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-03 15:40:03,312 Node[0] Epoch[49] Validation-accuracy=0.175881
2016-05-03 15:40:13,658 Node[0] Epoch[50] Batch [50] Speed: 621.88 samples/sec Train-accuracy=0.905156
2016-05-03 15:40:23,844 Node[0] Epoch[50] Batch [100] Speed: 628.34 samples/sec Train-accuracy=0.906719
2016-05-03 15:40:34,090 Node[0] Epoch[50] Batch [150] Speed: 624.61 samples/sec Train-accuracy=0.909375
2016-05-03 15:40:44,327 Node[0] Epoch[50] Batch [200] Speed: 625.23 samples/sec Train-accuracy=0.906875
2016-05-03 15:40:54,622 Node[0] Epoch[50] Batch [250] Speed: 621.68 samples/sec Train-accuracy=0.909687
2016-05-03 15:41:04,905 Node[0] Epoch[50] Batch [300] Speed: 622.41 samples/sec Train-accuracy=0.902188
2016-05-03 15:41:15,174 Node[0] Epoch[50] Batch [350] Speed: 623.21 samples/sec Train-accuracy=0.912031
2016-05-03 15:41:23,401 Node[0] Epoch[50] Resetting Data Iterator
2016-05-03 15:41:23,401 Node[0] Epoch[50] Time cost=80.089
2016-05-03 15:41:23,561 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-03 15:41:25,456 Node[0] Epoch[50] Validation-accuracy=0.138421
2016-05-03 15:41:35,610 Node[0] Epoch[51] Batch [50] Speed: 633.62 samples/sec Train-accuracy=0.908906
2016-05-03 15:41:45,792 Node[0] Epoch[51] Batch [100] Speed: 628.55 samples/sec Train-accuracy=0.912500
2016-05-03 15:41:56,037 Node[0] Epoch[51] Batch [150] Speed: 624.73 samples/sec Train-accuracy=0.911563
2016-05-03 15:42:06,280 Node[0] Epoch[51] Batch [200] Speed: 624.80 samples/sec Train-accuracy=0.910937
2016-05-03 15:42:16,471 Node[0] Epoch[51] Batch [250] Speed: 628.07 samples/sec Train-accuracy=0.905312
2016-05-03 15:42:26,676 Node[0] Epoch[51] Batch [300] Speed: 627.14 samples/sec Train-accuracy=0.905781
2016-05-03 15:42:36,857 Node[0] Epoch[51] Batch [350] Speed: 628.65 samples/sec Train-accuracy=0.904062
2016-05-03 15:42:45,206 Node[0] Epoch[51] Resetting Data Iterator
2016-05-03 15:42:45,206 Node[0] Epoch[51] Time cost=79.750
2016-05-03 15:42:45,365 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-03 15:42:47,285 Node[0] Epoch[51] Validation-accuracy=0.213442
2016-05-03 15:42:57,479 Node[0] Epoch[52] Batch [50] Speed: 631.12 samples/sec Train-accuracy=0.906094
2016-05-03 15:43:07,744 Node[0] Epoch[52] Batch [100] Speed: 623.51 samples/sec Train-accuracy=0.910000
2016-05-03 15:43:17,994 Node[0] Epoch[52] Batch [150] Speed: 624.42 samples/sec Train-accuracy=0.913125
2016-05-03 15:43:28,316 Node[0] Epoch[52] Batch [200] Speed: 620.01 samples/sec Train-accuracy=0.903438
2016-05-03 15:43:38,559 Node[0] Epoch[52] Batch [250] Speed: 624.85 samples/sec Train-accuracy=0.908906
2016-05-03 15:43:48,811 Node[0] Epoch[52] Batch [300] Speed: 624.28 samples/sec Train-accuracy=0.907344
2016-05-03 15:43:59,057 Node[0] Epoch[52] Batch [350] Speed: 624.68 samples/sec Train-accuracy=0.903594
2016-05-03 15:44:07,438 Node[0] Epoch[52] Resetting Data Iterator
2016-05-03 15:44:07,438 Node[0] Epoch[52] Time cost=80.153
2016-05-03 15:44:07,600 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-03 15:44:09,484 Node[0] Epoch[52] Validation-accuracy=0.143930
2016-05-03 15:44:19,724 Node[0] Epoch[53] Batch [50] Speed: 628.32 samples/sec Train-accuracy=0.908594
2016-05-03 15:44:30,014 Node[0] Epoch[53] Batch [100] Speed: 622.00 samples/sec Train-accuracy=0.916094
2016-05-03 15:44:40,269 Node[0] Epoch[53] Batch [150] Speed: 624.08 samples/sec Train-accuracy=0.913594
2016-05-03 15:44:50,499 Node[0] Epoch[53] Batch [200] Speed: 625.61 samples/sec Train-accuracy=0.914687
2016-05-03 15:45:00,759 Node[0] Epoch[53] Batch [250] Speed: 623.83 samples/sec Train-accuracy=0.905469
2016-05-03 15:45:11,000 Node[0] Epoch[53] Batch [300] Speed: 624.94 samples/sec Train-accuracy=0.911094
2016-05-03 15:45:21,143 Node[0] Epoch[53] Batch [350] Speed: 631.00 samples/sec Train-accuracy=0.910469
2016-05-03 15:45:29,241 Node[0] Epoch[53] Resetting Data Iterator
2016-05-03 15:45:29,242 Node[0] Epoch[53] Time cost=79.757
2016-05-03 15:45:29,403 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-03 15:45:31,338 Node[0] Epoch[53] Validation-accuracy=0.107071
2016-05-03 15:45:41,633 Node[0] Epoch[54] Batch [50] Speed: 624.90 samples/sec Train-accuracy=0.905625
2016-05-03 15:45:51,851 Node[0] Epoch[54] Batch [100] Speed: 626.38 samples/sec Train-accuracy=0.912500
2016-05-03 15:46:02,076 Node[0] Epoch[54] Batch [150] Speed: 625.94 samples/sec Train-accuracy=0.909687
2016-05-03 15:46:12,278 Node[0] Epoch[54] Batch [200] Speed: 627.37 samples/sec Train-accuracy=0.909844
2016-05-03 15:46:22,456 Node[0] Epoch[54] Batch [250] Speed: 628.80 samples/sec Train-accuracy=0.918125
2016-05-03 15:46:32,729 Node[0] Epoch[54] Batch [300] Speed: 623.06 samples/sec Train-accuracy=0.909844
2016-05-03 15:46:42,916 Node[0] Epoch[54] Batch [350] Speed: 628.27 samples/sec Train-accuracy=0.913125
2016-05-03 15:46:51,314 Node[0] Epoch[54] Resetting Data Iterator
2016-05-03 15:46:51,314 Node[0] Epoch[54] Time cost=79.976
2016-05-03 15:46:51,473 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-03 15:46:53,375 Node[0] Epoch[54] Validation-accuracy=0.131611
2016-05-03 15:47:03,640 Node[0] Epoch[55] Batch [50] Speed: 626.81 samples/sec Train-accuracy=0.909844
2016-05-03 15:47:13,901 Node[0] Epoch[55] Batch [100] Speed: 623.71 samples/sec Train-accuracy=0.917031
2016-05-03 15:47:24,167 Node[0] Epoch[55] Batch [150] Speed: 623.41 samples/sec Train-accuracy=0.917500
2016-05-03 15:47:34,394 Node[0] Epoch[55] Batch [200] Speed: 625.86 samples/sec Train-accuracy=0.912188
2016-05-03 15:47:44,645 Node[0] Epoch[55] Batch [250] Speed: 624.36 samples/sec Train-accuracy=0.913281
2016-05-03 15:47:54,868 Node[0] Epoch[55] Batch [300] Speed: 626.00 samples/sec Train-accuracy=0.912188
2016-05-03 15:48:05,092 Node[0] Epoch[55] Batch [350] Speed: 626.02 samples/sec Train-accuracy=0.906250
2016-05-03 15:48:13,266 Node[0] Epoch[55] Resetting Data Iterator
2016-05-03 15:48:13,266 Node[0] Epoch[55] Time cost=79.891
2016-05-03 15:48:13,426 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-03 15:48:15,327 Node[0] Epoch[55] Validation-accuracy=0.172276
2016-05-03 15:48:25,610 Node[0] Epoch[56] Batch [50] Speed: 625.82 samples/sec Train-accuracy=0.908594
2016-05-03 15:48:35,837 Node[0] Epoch[56] Batch [100] Speed: 625.79 samples/sec Train-accuracy=0.912188
2016-05-03 15:48:46,103 Node[0] Epoch[56] Batch [150] Speed: 623.45 samples/sec Train-accuracy=0.917656
2016-05-03 15:48:56,391 Node[0] Epoch[56] Batch [200] Speed: 622.10 samples/sec Train-accuracy=0.909531
2016-05-03 15:49:06,612 Node[0] Epoch[56] Batch [250] Speed: 626.15 samples/sec Train-accuracy=0.914844
2016-05-03 15:49:16,871 Node[0] Epoch[56] Batch [300] Speed: 623.87 samples/sec Train-accuracy=0.916094
2016-05-03 15:49:27,100 Node[0] Epoch[56] Batch [350] Speed: 625.67 samples/sec Train-accuracy=0.911875
2016-05-03 15:49:35,491 Node[0] Epoch[56] Resetting Data Iterator
2016-05-03 15:49:35,492 Node[0] Epoch[56] Time cost=80.164
2016-05-03 15:49:35,651 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-03 15:49:37,760 Node[0] Epoch[56] Validation-accuracy=0.142108
2016-05-03 15:49:48,050 Node[0] Epoch[57] Batch [50] Speed: 625.25 samples/sec Train-accuracy=0.915625
2016-05-03 15:49:58,344 Node[0] Epoch[57] Batch [100] Speed: 621.75 samples/sec Train-accuracy=0.918281
2016-05-03 15:50:08,580 Node[0] Epoch[57] Batch [150] Speed: 625.30 samples/sec Train-accuracy=0.917031
2016-05-03 15:50:18,810 Node[0] Epoch[57] Batch [200] Speed: 625.60 samples/sec Train-accuracy=0.916094
2016-05-03 15:50:29,108 Node[0] Epoch[57] Batch [250] Speed: 621.50 samples/sec Train-accuracy=0.916406
2016-05-03 15:50:39,329 Node[0] Epoch[57] Batch [300] Speed: 626.15 samples/sec Train-accuracy=0.911719
2016-05-03 15:50:49,549 Node[0] Epoch[57] Batch [350] Speed: 626.25 samples/sec Train-accuracy=0.913281
2016-05-03 15:50:57,986 Node[0] Epoch[57] Resetting Data Iterator
2016-05-03 15:50:57,986 Node[0] Epoch[57] Time cost=80.226
2016-05-03 15:50:58,147 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-03 15:51:00,082 Node[0] Epoch[57] Validation-accuracy=0.138321
2016-05-03 15:51:10,386 Node[0] Epoch[58] Batch [50] Speed: 624.33 samples/sec Train-accuracy=0.911250
2016-05-03 15:51:20,689 Node[0] Epoch[58] Batch [100] Speed: 621.19 samples/sec Train-accuracy=0.911875
2016-05-03 15:51:30,911 Node[0] Epoch[58] Batch [150] Speed: 626.11 samples/sec Train-accuracy=0.915000
2016-05-03 15:51:41,165 Node[0] Epoch[58] Batch [200] Speed: 624.15 samples/sec Train-accuracy=0.911406
2016-05-03 15:51:51,389 Node[0] Epoch[58] Batch [250] Speed: 625.96 samples/sec Train-accuracy=0.921562
2016-05-03 15:52:01,620 Node[0] Epoch[58] Batch [300] Speed: 625.61 samples/sec Train-accuracy=0.916250
2016-05-03 15:52:11,953 Node[0] Epoch[58] Batch [350] Speed: 619.40 samples/sec Train-accuracy=0.907500
2016-05-03 15:52:20,185 Node[0] Epoch[58] Resetting Data Iterator
2016-05-03 15:52:20,185 Node[0] Epoch[58] Time cost=80.103
2016-05-03 15:52:20,345 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-03 15:52:22,255 Node[0] Epoch[58] Validation-accuracy=0.119391
2016-05-03 15:52:32,385 Node[0] Epoch[59] Batch [50] Speed: 635.07 samples/sec Train-accuracy=0.914375
2016-05-03 15:52:42,597 Node[0] Epoch[59] Batch [100] Speed: 626.75 samples/sec Train-accuracy=0.913750
2016-05-03 15:52:52,835 Node[0] Epoch[59] Batch [150] Speed: 625.16 samples/sec Train-accuracy=0.920937
2016-05-03 15:53:03,090 Node[0] Epoch[59] Batch [200] Speed: 624.06 samples/sec Train-accuracy=0.912656
2016-05-03 15:53:13,383 Node[0] Epoch[59] Batch [250] Speed: 621.84 samples/sec Train-accuracy=0.915469
2016-05-03 15:53:23,695 Node[0] Epoch[59] Batch [300] Speed: 620.66 samples/sec Train-accuracy=0.914844
2016-05-03 15:53:33,984 Node[0] Epoch[59] Batch [350] Speed: 622.00 samples/sec Train-accuracy=0.913594
2016-05-03 15:53:42,367 Node[0] Epoch[59] Resetting Data Iterator
2016-05-03 15:53:42,368 Node[0] Epoch[59] Time cost=80.113
2016-05-03 15:53:42,528 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-03 15:53:44,425 Node[0] Epoch[59] Validation-accuracy=0.143530
2016-05-03 15:53:54,702 Node[0] Epoch[60] Batch [50] Speed: 626.00 samples/sec Train-accuracy=0.914219
2016-05-03 15:54:04,926 Node[0] Epoch[60] Batch [100] Speed: 626.04 samples/sec Train-accuracy=0.910156
2016-05-03 15:54:15,139 Node[0] Epoch[60] Batch [150] Speed: 626.67 samples/sec Train-accuracy=0.919219
2016-05-03 15:54:25,394 Node[0] Epoch[60] Batch [200] Speed: 624.10 samples/sec Train-accuracy=0.907813
2016-05-03 15:54:35,641 Node[0] Epoch[60] Batch [250] Speed: 624.60 samples/sec Train-accuracy=0.917813
2016-05-03 15:54:45,896 Node[0] Epoch[60] Batch [300] Speed: 624.09 samples/sec Train-accuracy=0.915625
2016-05-03 15:54:56,165 Node[0] Epoch[60] Batch [350] Speed: 623.26 samples/sec Train-accuracy=0.910625
2016-05-03 15:55:04,577 Node[0] Epoch[60] Resetting Data Iterator
2016-05-03 15:55:04,578 Node[0] Epoch[60] Time cost=80.152
2016-05-03 15:55:04,739 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-03 15:55:06,689 Node[0] Epoch[60] Validation-accuracy=0.106070
2016-05-03 15:55:16,920 Node[0] Epoch[61] Batch [50] Speed: 628.86 samples/sec Train-accuracy=0.914844
2016-05-03 15:55:27,186 Node[0] Epoch[61] Batch [100] Speed: 623.47 samples/sec Train-accuracy=0.919531
2016-05-03 15:55:37,414 Node[0] Epoch[61] Batch [150] Speed: 625.74 samples/sec Train-accuracy=0.919531
2016-05-03 15:55:47,675 Node[0] Epoch[61] Batch [200] Speed: 623.70 samples/sec Train-accuracy=0.919219
2016-05-03 15:55:57,923 Node[0] Epoch[61] Batch [250] Speed: 624.57 samples/sec Train-accuracy=0.916719
2016-05-03 15:56:08,218 Node[0] Epoch[61] Batch [300] Speed: 621.68 samples/sec Train-accuracy=0.921406
2016-05-03 15:56:18,503 Node[0] Epoch[61] Batch [350] Speed: 622.28 samples/sec Train-accuracy=0.918125
2016-05-03 15:56:26,692 Node[0] Epoch[61] Resetting Data Iterator
2016-05-03 15:56:26,692 Node[0] Epoch[61] Time cost=80.003
2016-05-03 15:56:26,854 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-03 15:56:28,757 Node[0] Epoch[61] Validation-accuracy=0.116887
2016-05-03 15:56:39,074 Node[0] Epoch[62] Batch [50] Speed: 623.63 samples/sec Train-accuracy=0.910625
2016-05-03 15:56:49,381 Node[0] Epoch[62] Batch [100] Speed: 620.96 samples/sec Train-accuracy=0.922344
2016-05-03 15:56:59,661 Node[0] Epoch[62] Batch [150] Speed: 622.58 samples/sec Train-accuracy=0.927656
2016-05-03 15:57:09,922 Node[0] Epoch[62] Batch [200] Speed: 623.73 samples/sec Train-accuracy=0.919063
2016-05-03 15:57:20,163 Node[0] Epoch[62] Batch [250] Speed: 624.97 samples/sec Train-accuracy=0.910156
2016-05-03 15:57:30,467 Node[0] Epoch[62] Batch [300] Speed: 621.10 samples/sec Train-accuracy=0.920156
2016-05-03 15:57:40,686 Node[0] Epoch[62] Batch [350] Speed: 626.30 samples/sec Train-accuracy=0.912969
2016-05-03 15:57:49,076 Node[0] Epoch[62] Resetting Data Iterator
2016-05-03 15:57:49,076 Node[0] Epoch[62] Time cost=80.319
2016-05-03 15:57:49,234 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-03 15:57:51,126 Node[0] Epoch[62] Validation-accuracy=0.102965
2016-05-03 15:58:01,394 Node[0] Epoch[63] Batch [50] Speed: 626.72 samples/sec Train-accuracy=0.909375
2016-05-03 15:58:11,677 Node[0] Epoch[63] Batch [100] Speed: 622.38 samples/sec Train-accuracy=0.919531
2016-05-03 15:58:21,987 Node[0] Epoch[63] Batch [150] Speed: 620.76 samples/sec Train-accuracy=0.918438
2016-05-03 15:58:32,241 Node[0] Epoch[63] Batch [200] Speed: 624.20 samples/sec Train-accuracy=0.916094
2016-05-03 15:58:42,523 Node[0] Epoch[63] Batch [250] Speed: 622.46 samples/sec Train-accuracy=0.914687
2016-05-03 15:58:52,759 Node[0] Epoch[63] Batch [300] Speed: 625.26 samples/sec Train-accuracy=0.918281
2016-05-03 15:59:02,965 Node[0] Epoch[63] Batch [350] Speed: 627.09 samples/sec Train-accuracy=0.919687
2016-05-03 15:59:11,171 Node[0] Epoch[63] Resetting Data Iterator
2016-05-03 15:59:11,171 Node[0] Epoch[63] Time cost=80.045
2016-05-03 15:59:11,340 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-03 15:59:13,237 Node[0] Epoch[63] Validation-accuracy=0.099960
2016-05-03 15:59:23,513 Node[0] Epoch[64] Batch [50] Speed: 626.09 samples/sec Train-accuracy=0.916562
2016-05-03 15:59:33,766 Node[0] Epoch[64] Batch [100] Speed: 624.25 samples/sec Train-accuracy=0.918281
2016-05-03 15:59:44,037 Node[0] Epoch[64] Batch [150] Speed: 623.11 samples/sec Train-accuracy=0.923438
2016-05-03 15:59:54,318 Node[0] Epoch[64] Batch [200] Speed: 622.51 samples/sec Train-accuracy=0.913438
2016-05-03 16:00:04,588 Node[0] Epoch[64] Batch [250] Speed: 623.22 samples/sec Train-accuracy=0.920781
2016-05-03 16:01:05,985 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 16:01:12,209 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 16:01:12,588 Node[0] Start training with [gpu(0)]
2016-05-03 16:01:33,249 Node[0] Epoch[0] Batch [50] Speed: 661.07 samples/sec Train-accuracy=0.138906
2016-05-03 16:01:43,136 Node[0] Epoch[0] Batch [100] Speed: 647.30 samples/sec Train-accuracy=0.237344
2016-05-03 16:01:53,065 Node[0] Epoch[0] Batch [150] Speed: 644.62 samples/sec Train-accuracy=0.293125
2016-05-03 16:02:02,995 Node[0] Epoch[0] Batch [200] Speed: 644.52 samples/sec Train-accuracy=0.302344
2016-05-03 16:02:13,050 Node[0] Epoch[0] Batch [250] Speed: 636.53 samples/sec Train-accuracy=0.350781
2016-05-03 16:02:23,718 Node[0] Epoch[0] Batch [300] Speed: 599.94 samples/sec Train-accuracy=0.367656
2016-05-03 16:02:34,437 Node[0] Epoch[0] Batch [350] Speed: 597.08 samples/sec Train-accuracy=0.366563
2016-05-03 16:02:43,175 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 16:02:43,175 Node[0] Epoch[0] Time cost=79.873
2016-05-03 16:02:43,346 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 16:02:45,623 Node[0] Epoch[0] Validation-accuracy=0.398339
2016-05-03 16:02:56,120 Node[0] Epoch[1] Batch [50] Speed: 612.95 samples/sec Train-accuracy=0.393594
2016-05-03 16:03:06,624 Node[0] Epoch[1] Batch [100] Speed: 609.31 samples/sec Train-accuracy=0.414062
2016-05-03 16:03:17,012 Node[0] Epoch[1] Batch [150] Speed: 616.07 samples/sec Train-accuracy=0.428125
2016-05-03 16:03:27,436 Node[0] Epoch[1] Batch [200] Speed: 613.98 samples/sec Train-accuracy=0.422031
2016-05-03 16:03:37,840 Node[0] Epoch[1] Batch [250] Speed: 615.21 samples/sec Train-accuracy=0.442344
2016-05-03 16:03:48,262 Node[0] Epoch[1] Batch [300] Speed: 614.10 samples/sec Train-accuracy=0.455313
2016-05-03 16:03:58,680 Node[0] Epoch[1] Batch [350] Speed: 614.30 samples/sec Train-accuracy=0.456719
2016-05-03 16:04:07,265 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 16:04:07,265 Node[0] Epoch[1] Time cost=81.642
2016-05-03 16:04:07,429 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 16:04:09,390 Node[0] Epoch[1] Validation-accuracy=0.466847
2016-05-03 16:04:19,877 Node[0] Epoch[2] Batch [50] Speed: 613.47 samples/sec Train-accuracy=0.472187
2016-05-03 16:04:30,252 Node[0] Epoch[2] Batch [100] Speed: 616.89 samples/sec Train-accuracy=0.511250
2016-05-03 16:04:40,634 Node[0] Epoch[2] Batch [150] Speed: 616.49 samples/sec Train-accuracy=0.510625
2016-05-03 16:04:50,994 Node[0] Epoch[2] Batch [200] Speed: 617.79 samples/sec Train-accuracy=0.517500
2016-05-03 16:05:01,404 Node[0] Epoch[2] Batch [250] Speed: 614.77 samples/sec Train-accuracy=0.526875
2016-05-03 16:05:11,776 Node[0] Epoch[2] Batch [300] Speed: 617.09 samples/sec Train-accuracy=0.545156
2016-05-03 16:05:22,119 Node[0] Epoch[2] Batch [350] Speed: 618.77 samples/sec Train-accuracy=0.548750
2016-05-03 16:05:30,341 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 16:05:30,342 Node[0] Epoch[2] Time cost=80.951
2016-05-03 16:05:30,503 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 16:05:32,459 Node[0] Epoch[2] Validation-accuracy=0.564303
2016-05-03 16:05:42,822 Node[0] Epoch[3] Batch [50] Speed: 620.82 samples/sec Train-accuracy=0.566875
2016-05-03 16:05:53,092 Node[0] Epoch[3] Batch [100] Speed: 623.14 samples/sec Train-accuracy=0.582812
2016-05-03 16:06:03,373 Node[0] Epoch[3] Batch [150] Speed: 622.53 samples/sec Train-accuracy=0.595156
2016-05-03 16:06:13,652 Node[0] Epoch[3] Batch [200] Speed: 622.68 samples/sec Train-accuracy=0.589063
2016-05-03 16:06:23,935 Node[0] Epoch[3] Batch [250] Speed: 622.37 samples/sec Train-accuracy=0.602656
2016-05-03 16:06:34,214 Node[0] Epoch[3] Batch [300] Speed: 622.68 samples/sec Train-accuracy=0.608750
2016-05-03 16:06:44,476 Node[0] Epoch[3] Batch [350] Speed: 623.64 samples/sec Train-accuracy=0.615156
2016-05-03 16:06:52,901 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 16:06:52,901 Node[0] Epoch[3] Time cost=80.442
2016-05-03 16:06:53,064 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 16:06:55,013 Node[0] Epoch[3] Validation-accuracy=0.637019
2016-05-03 16:07:05,323 Node[0] Epoch[4] Batch [50] Speed: 624.02 samples/sec Train-accuracy=0.626406
2016-05-03 16:07:15,560 Node[0] Epoch[4] Batch [100] Speed: 625.20 samples/sec Train-accuracy=0.642500
2016-05-03 16:07:25,691 Node[0] Epoch[4] Batch [150] Speed: 631.70 samples/sec Train-accuracy=0.652031
2016-05-03 16:07:35,845 Node[0] Epoch[4] Batch [200] Speed: 630.31 samples/sec Train-accuracy=0.649844
2016-05-03 16:07:46,024 Node[0] Epoch[4] Batch [250] Speed: 628.75 samples/sec Train-accuracy=0.648281
2016-05-03 16:07:56,271 Node[0] Epoch[4] Batch [300] Speed: 624.62 samples/sec Train-accuracy=0.662656
2016-05-03 16:08:06,568 Node[0] Epoch[4] Batch [350] Speed: 621.55 samples/sec Train-accuracy=0.668750
2016-05-03 16:08:14,918 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 16:08:14,918 Node[0] Epoch[4] Time cost=79.905
2016-05-03 16:08:15,081 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 16:08:16,954 Node[0] Epoch[4] Validation-accuracy=0.684095
2016-05-03 16:08:27,165 Node[0] Epoch[5] Batch [50] Speed: 630.12 samples/sec Train-accuracy=0.673750
2016-05-03 16:08:37,428 Node[0] Epoch[5] Batch [100] Speed: 623.62 samples/sec Train-accuracy=0.687031
2016-05-03 16:08:47,661 Node[0] Epoch[5] Batch [150] Speed: 625.44 samples/sec Train-accuracy=0.695469
2016-05-03 16:08:57,828 Node[0] Epoch[5] Batch [200] Speed: 629.49 samples/sec Train-accuracy=0.693906
2016-05-03 16:09:08,043 Node[0] Epoch[5] Batch [250] Speed: 626.57 samples/sec Train-accuracy=0.696875
2016-05-03 16:09:18,225 Node[0] Epoch[5] Batch [300] Speed: 628.58 samples/sec Train-accuracy=0.702812
2016-05-03 16:09:28,398 Node[0] Epoch[5] Batch [350] Speed: 629.14 samples/sec Train-accuracy=0.704219
2016-05-03 16:09:36,528 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 16:09:36,528 Node[0] Epoch[5] Time cost=79.574
2016-05-03 16:09:36,691 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 16:09:38,663 Node[0] Epoch[5] Validation-accuracy=0.693510
2016-05-03 16:09:48,937 Node[0] Epoch[6] Batch [50] Speed: 626.18 samples/sec Train-accuracy=0.716094
2016-05-03 16:09:59,124 Node[0] Epoch[6] Batch [100] Speed: 628.31 samples/sec Train-accuracy=0.725625
2016-05-03 16:10:09,280 Node[0] Epoch[6] Batch [150] Speed: 630.15 samples/sec Train-accuracy=0.733125
2016-05-03 16:10:19,487 Node[0] Epoch[6] Batch [200] Speed: 627.02 samples/sec Train-accuracy=0.727187
2016-05-03 16:10:29,629 Node[0] Epoch[6] Batch [250] Speed: 631.05 samples/sec Train-accuracy=0.723125
2016-05-03 16:10:39,810 Node[0] Epoch[6] Batch [300] Speed: 628.67 samples/sec Train-accuracy=0.735625
2016-05-03 16:10:49,983 Node[0] Epoch[6] Batch [350] Speed: 629.11 samples/sec Train-accuracy=0.739844
2016-05-03 16:10:58,330 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 16:10:58,330 Node[0] Epoch[6] Time cost=79.667
2016-05-03 16:10:58,493 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 16:11:00,389 Node[0] Epoch[6] Validation-accuracy=0.733774
2016-05-03 16:11:10,581 Node[0] Epoch[7] Batch [50] Speed: 631.35 samples/sec Train-accuracy=0.738906
2016-05-03 16:11:20,745 Node[0] Epoch[7] Batch [100] Speed: 629.73 samples/sec Train-accuracy=0.742344
2016-05-03 16:11:30,854 Node[0] Epoch[7] Batch [150] Speed: 633.13 samples/sec Train-accuracy=0.762813
2016-05-03 16:11:40,968 Node[0] Epoch[7] Batch [200] Speed: 632.77 samples/sec Train-accuracy=0.755156
2016-05-03 16:11:51,135 Node[0] Epoch[7] Batch [250] Speed: 629.54 samples/sec Train-accuracy=0.748437
2016-05-03 16:12:01,262 Node[0] Epoch[7] Batch [300] Speed: 631.94 samples/sec Train-accuracy=0.761719
2016-05-03 16:12:11,470 Node[0] Epoch[7] Batch [350] Speed: 626.99 samples/sec Train-accuracy=0.765781
2016-05-03 16:12:19,603 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 16:12:19,603 Node[0] Epoch[7] Time cost=79.214
2016-05-03 16:12:19,764 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 16:12:21,655 Node[0] Epoch[7] Validation-accuracy=0.747196
2016-05-03 16:12:31,832 Node[0] Epoch[8] Batch [50] Speed: 632.19 samples/sec Train-accuracy=0.762656
2016-05-03 16:12:42,001 Node[0] Epoch[8] Batch [100] Speed: 629.39 samples/sec Train-accuracy=0.766406
2016-05-03 16:12:52,211 Node[0] Epoch[8] Batch [150] Speed: 626.88 samples/sec Train-accuracy=0.777031
2016-05-03 16:13:02,373 Node[0] Epoch[8] Batch [200] Speed: 629.79 samples/sec Train-accuracy=0.775000
2016-05-03 16:13:12,546 Node[0] Epoch[8] Batch [250] Speed: 629.13 samples/sec Train-accuracy=0.774375
2016-05-03 16:13:22,730 Node[0] Epoch[8] Batch [300] Speed: 628.45 samples/sec Train-accuracy=0.781406
2016-05-03 16:13:32,878 Node[0] Epoch[8] Batch [350] Speed: 630.71 samples/sec Train-accuracy=0.775937
2016-05-03 16:13:41,239 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 16:13:41,239 Node[0] Epoch[8] Time cost=79.584
2016-05-03 16:13:41,402 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 16:13:43,527 Node[0] Epoch[8] Validation-accuracy=0.767504
2016-05-03 16:13:53,655 Node[0] Epoch[9] Batch [50] Speed: 635.10 samples/sec Train-accuracy=0.780781
2016-05-03 16:14:03,842 Node[0] Epoch[9] Batch [100] Speed: 628.27 samples/sec Train-accuracy=0.788438
2016-05-03 16:14:13,957 Node[0] Epoch[9] Batch [150] Speed: 632.76 samples/sec Train-accuracy=0.795937
2016-05-03 16:14:24,169 Node[0] Epoch[9] Batch [200] Speed: 626.75 samples/sec Train-accuracy=0.790312
2016-05-03 16:14:34,257 Node[0] Epoch[9] Batch [250] Speed: 634.40 samples/sec Train-accuracy=0.790156
2016-05-03 16:14:44,407 Node[0] Epoch[9] Batch [300] Speed: 630.57 samples/sec Train-accuracy=0.787188
2016-05-03 16:14:54,552 Node[0] Epoch[9] Batch [350] Speed: 630.88 samples/sec Train-accuracy=0.788281
2016-05-03 16:15:02,818 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 16:15:02,818 Node[0] Epoch[9] Time cost=79.291
2016-05-03 16:15:02,979 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 16:15:04,893 Node[0] Epoch[9] Validation-accuracy=0.770833
2016-05-03 16:15:15,057 Node[0] Epoch[10] Batch [50] Speed: 632.94 samples/sec Train-accuracy=0.793906
2016-05-03 16:15:25,207 Node[0] Epoch[10] Batch [100] Speed: 630.55 samples/sec Train-accuracy=0.797500
2016-05-03 16:15:35,339 Node[0] Epoch[10] Batch [150] Speed: 631.72 samples/sec Train-accuracy=0.808906
2016-05-03 16:15:45,511 Node[0] Epoch[10] Batch [200] Speed: 629.17 samples/sec Train-accuracy=0.803750
2016-05-03 16:15:55,625 Node[0] Epoch[10] Batch [250] Speed: 632.82 samples/sec Train-accuracy=0.789062
2016-05-03 16:16:05,721 Node[0] Epoch[10] Batch [300] Speed: 633.91 samples/sec Train-accuracy=0.810312
2016-05-03 16:16:15,831 Node[0] Epoch[10] Batch [350] Speed: 633.06 samples/sec Train-accuracy=0.804063
2016-05-03 16:16:23,917 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 16:16:23,917 Node[0] Epoch[10] Time cost=79.024
2016-05-03 16:16:24,073 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 16:16:25,962 Node[0] Epoch[10] Validation-accuracy=0.792969
2016-05-03 16:16:36,061 Node[0] Epoch[11] Batch [50] Speed: 637.02 samples/sec Train-accuracy=0.805781
2016-05-03 16:16:46,227 Node[0] Epoch[11] Batch [100] Speed: 629.54 samples/sec Train-accuracy=0.808438
2016-05-03 16:16:56,308 Node[0] Epoch[11] Batch [150] Speed: 634.92 samples/sec Train-accuracy=0.813438
2016-05-03 16:17:06,391 Node[0] Epoch[11] Batch [200] Speed: 634.72 samples/sec Train-accuracy=0.816406
2016-05-03 16:17:16,556 Node[0] Epoch[11] Batch [250] Speed: 629.62 samples/sec Train-accuracy=0.810625
2016-05-03 16:17:26,694 Node[0] Epoch[11] Batch [300] Speed: 631.32 samples/sec Train-accuracy=0.818750
2016-05-03 16:17:36,826 Node[0] Epoch[11] Batch [350] Speed: 631.69 samples/sec Train-accuracy=0.810625
2016-05-03 16:17:45,135 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 16:17:45,135 Node[0] Epoch[11] Time cost=79.173
2016-05-03 16:17:45,294 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 16:17:47,235 Node[0] Epoch[11] Validation-accuracy=0.801783
2016-05-03 16:17:57,372 Node[0] Epoch[12] Batch [50] Speed: 634.71 samples/sec Train-accuracy=0.816562
2016-05-03 16:18:07,525 Node[0] Epoch[12] Batch [100] Speed: 630.37 samples/sec Train-accuracy=0.819063
2016-05-03 16:18:17,726 Node[0] Epoch[12] Batch [150] Speed: 627.38 samples/sec Train-accuracy=0.825937
2016-05-03 16:18:27,892 Node[0] Epoch[12] Batch [200] Speed: 629.57 samples/sec Train-accuracy=0.822500
2016-05-03 16:18:38,018 Node[0] Epoch[12] Batch [250] Speed: 632.06 samples/sec Train-accuracy=0.817031
2016-05-03 16:18:48,113 Node[0] Epoch[12] Batch [300] Speed: 634.04 samples/sec Train-accuracy=0.830469
2016-05-03 16:18:58,244 Node[0] Epoch[12] Batch [350] Speed: 631.72 samples/sec Train-accuracy=0.821406
2016-05-03 16:19:06,521 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 16:19:06,522 Node[0] Epoch[12] Time cost=79.286
2016-05-03 16:19:06,679 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 16:19:08,570 Node[0] Epoch[12] Validation-accuracy=0.799179
2016-05-03 16:19:18,719 Node[0] Epoch[13] Batch [50] Speed: 633.99 samples/sec Train-accuracy=0.828125
2016-05-03 16:19:28,886 Node[0] Epoch[13] Batch [100] Speed: 629.51 samples/sec Train-accuracy=0.829063
2016-05-03 16:19:39,001 Node[0] Epoch[13] Batch [150] Speed: 632.71 samples/sec Train-accuracy=0.835625
2016-05-03 16:19:49,102 Node[0] Epoch[13] Batch [200] Speed: 633.62 samples/sec Train-accuracy=0.834375
2016-05-03 16:19:59,179 Node[0] Epoch[13] Batch [250] Speed: 635.13 samples/sec Train-accuracy=0.831719
2016-05-03 16:20:09,285 Node[0] Epoch[13] Batch [300] Speed: 633.32 samples/sec Train-accuracy=0.841250
2016-05-03 16:20:19,434 Node[0] Epoch[13] Batch [350] Speed: 630.60 samples/sec Train-accuracy=0.831719
2016-05-03 16:20:27,518 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 16:20:27,518 Node[0] Epoch[13] Time cost=78.948
2016-05-03 16:20:27,678 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 16:20:29,574 Node[0] Epoch[13] Validation-accuracy=0.783454
2016-05-03 16:20:39,757 Node[0] Epoch[14] Batch [50] Speed: 631.77 samples/sec Train-accuracy=0.836250
2016-05-03 16:20:49,875 Node[0] Epoch[14] Batch [100] Speed: 632.55 samples/sec Train-accuracy=0.834219
2016-05-03 16:20:59,958 Node[0] Epoch[14] Batch [150] Speed: 634.76 samples/sec Train-accuracy=0.840781
2016-05-03 16:21:10,049 Node[0] Epoch[14] Batch [200] Speed: 634.25 samples/sec Train-accuracy=0.839063
2016-05-03 16:21:20,157 Node[0] Epoch[14] Batch [250] Speed: 633.16 samples/sec Train-accuracy=0.833125
2016-05-03 16:21:30,299 Node[0] Epoch[14] Batch [300] Speed: 631.05 samples/sec Train-accuracy=0.836562
2016-05-03 16:21:40,392 Node[0] Epoch[14] Batch [350] Speed: 634.13 samples/sec Train-accuracy=0.833750
2016-05-03 16:21:48,652 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 16:21:48,653 Node[0] Epoch[14] Time cost=79.079
2016-05-03 16:21:48,814 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 16:21:50,775 Node[0] Epoch[14] Validation-accuracy=0.798377
2016-05-03 16:22:00,856 Node[0] Epoch[15] Batch [50] Speed: 638.21 samples/sec Train-accuracy=0.836562
2016-05-03 16:22:11,006 Node[0] Epoch[15] Batch [100] Speed: 630.57 samples/sec Train-accuracy=0.843125
2016-05-03 16:22:21,047 Node[0] Epoch[15] Batch [150] Speed: 637.37 samples/sec Train-accuracy=0.846406
2016-05-03 16:22:31,065 Node[0] Epoch[15] Batch [200] Speed: 638.86 samples/sec Train-accuracy=0.838906
2016-05-03 16:22:41,169 Node[0] Epoch[15] Batch [250] Speed: 633.44 samples/sec Train-accuracy=0.845156
2016-05-03 16:22:51,284 Node[0] Epoch[15] Batch [300] Speed: 632.79 samples/sec Train-accuracy=0.847344
2016-05-03 16:23:01,390 Node[0] Epoch[15] Batch [350] Speed: 633.30 samples/sec Train-accuracy=0.849375
2016-05-03 16:23:09,475 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 16:23:09,476 Node[0] Epoch[15] Time cost=78.700
2016-05-03 16:23:09,634 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 16:23:11,533 Node[0] Epoch[15] Validation-accuracy=0.806591
2016-05-03 16:23:21,567 Node[0] Epoch[16] Batch [50] Speed: 641.27 samples/sec Train-accuracy=0.844688
2016-05-03 16:23:31,670 Node[0] Epoch[16] Batch [100] Speed: 633.54 samples/sec Train-accuracy=0.844844
2016-05-03 16:23:41,828 Node[0] Epoch[16] Batch [150] Speed: 630.02 samples/sec Train-accuracy=0.852969
2016-05-03 16:23:51,900 Node[0] Epoch[16] Batch [200] Speed: 635.48 samples/sec Train-accuracy=0.854219
2016-05-03 16:24:01,924 Node[0] Epoch[16] Batch [250] Speed: 638.48 samples/sec Train-accuracy=0.839531
2016-05-03 16:24:11,948 Node[0] Epoch[16] Batch [300] Speed: 638.47 samples/sec Train-accuracy=0.847812
2016-05-03 16:24:22,072 Node[0] Epoch[16] Batch [350] Speed: 632.20 samples/sec Train-accuracy=0.853281
2016-05-03 16:24:30,329 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 16:24:30,329 Node[0] Epoch[16] Time cost=78.796
2016-05-03 16:24:30,489 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 16:24:32,547 Node[0] Epoch[16] Validation-accuracy=0.814775
2016-05-03 16:24:42,644 Node[0] Epoch[17] Batch [50] Speed: 637.14 samples/sec Train-accuracy=0.844219
2016-05-03 16:24:52,710 Node[0] Epoch[17] Batch [100] Speed: 635.82 samples/sec Train-accuracy=0.853594
2016-05-03 16:25:02,766 Node[0] Epoch[17] Batch [150] Speed: 636.46 samples/sec Train-accuracy=0.856719
2016-05-03 16:25:12,835 Node[0] Epoch[17] Batch [200] Speed: 635.64 samples/sec Train-accuracy=0.854531
2016-05-03 16:25:22,933 Node[0] Epoch[17] Batch [250] Speed: 633.78 samples/sec Train-accuracy=0.855781
2016-05-03 16:25:33,036 Node[0] Epoch[17] Batch [300] Speed: 633.54 samples/sec Train-accuracy=0.859844
2016-05-03 16:25:43,131 Node[0] Epoch[17] Batch [350] Speed: 633.98 samples/sec Train-accuracy=0.855000
2016-05-03 16:25:51,415 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 16:25:51,415 Node[0] Epoch[17] Time cost=78.868
2016-05-03 16:25:51,569 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 16:25:53,455 Node[0] Epoch[17] Validation-accuracy=0.821214
2016-05-03 16:26:03,566 Node[0] Epoch[18] Batch [50] Speed: 636.27 samples/sec Train-accuracy=0.856563
2016-05-03 16:26:13,644 Node[0] Epoch[18] Batch [100] Speed: 635.07 samples/sec Train-accuracy=0.850625
2016-05-03 16:26:23,707 Node[0] Epoch[18] Batch [150] Speed: 636.03 samples/sec Train-accuracy=0.865313
2016-05-03 16:26:33,753 Node[0] Epoch[18] Batch [200] Speed: 637.09 samples/sec Train-accuracy=0.853906
2016-05-03 16:26:43,768 Node[0] Epoch[18] Batch [250] Speed: 639.05 samples/sec Train-accuracy=0.861875
2016-05-03 16:26:53,841 Node[0] Epoch[18] Batch [300] Speed: 635.37 samples/sec Train-accuracy=0.867969
2016-05-03 16:27:03,911 Node[0] Epoch[18] Batch [350] Speed: 635.60 samples/sec Train-accuracy=0.856875
2016-05-03 16:27:11,962 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 16:27:11,963 Node[0] Epoch[18] Time cost=78.508
2016-05-03 16:27:12,122 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 16:27:14,006 Node[0] Epoch[18] Validation-accuracy=0.804187
2016-05-03 16:27:24,047 Node[0] Epoch[19] Batch [50] Speed: 640.77 samples/sec Train-accuracy=0.856719
2016-05-03 16:27:34,157 Node[0] Epoch[19] Batch [100] Speed: 633.09 samples/sec Train-accuracy=0.860938
2016-05-03 16:27:44,181 Node[0] Epoch[19] Batch [150] Speed: 638.42 samples/sec Train-accuracy=0.871719
2016-05-03 16:27:54,219 Node[0] Epoch[19] Batch [200] Speed: 637.60 samples/sec Train-accuracy=0.865469
2016-05-03 16:28:04,310 Node[0] Epoch[19] Batch [250] Speed: 634.26 samples/sec Train-accuracy=0.868594
2016-05-03 16:28:14,418 Node[0] Epoch[19] Batch [300] Speed: 633.15 samples/sec Train-accuracy=0.870000
2016-05-03 16:28:24,576 Node[0] Epoch[19] Batch [350] Speed: 630.06 samples/sec Train-accuracy=0.864219
2016-05-03 16:28:32,844 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 16:28:32,844 Node[0] Epoch[19] Time cost=78.838
2016-05-03 16:28:32,999 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 16:28:34,886 Node[0] Epoch[19] Validation-accuracy=0.831330
2016-05-03 16:28:44,959 Node[0] Epoch[20] Batch [50] Speed: 638.74 samples/sec Train-accuracy=0.866719
2016-05-03 16:28:55,136 Node[0] Epoch[20] Batch [100] Speed: 628.87 samples/sec Train-accuracy=0.869687
2016-05-03 16:29:05,280 Node[0] Epoch[20] Batch [150] Speed: 630.92 samples/sec Train-accuracy=0.873437
2016-05-03 16:29:15,318 Node[0] Epoch[20] Batch [200] Speed: 637.63 samples/sec Train-accuracy=0.861094
2016-05-03 16:29:25,412 Node[0] Epoch[20] Batch [250] Speed: 634.07 samples/sec Train-accuracy=0.868437
2016-05-03 16:29:35,508 Node[0] Epoch[20] Batch [300] Speed: 633.91 samples/sec Train-accuracy=0.870781
2016-05-03 16:29:45,630 Node[0] Epoch[20] Batch [350] Speed: 632.30 samples/sec Train-accuracy=0.878281
2016-05-03 16:29:53,925 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 16:29:53,926 Node[0] Epoch[20] Time cost=79.039
2016-05-03 16:29:54,083 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 16:29:55,986 Node[0] Epoch[20] Validation-accuracy=0.810497
2016-05-03 16:30:06,121 Node[0] Epoch[21] Batch [50] Speed: 634.76 samples/sec Train-accuracy=0.865781
2016-05-03 16:30:16,276 Node[0] Epoch[21] Batch [100] Speed: 630.28 samples/sec Train-accuracy=0.870625
2016-05-03 16:30:26,382 Node[0] Epoch[21] Batch [150] Speed: 633.28 samples/sec Train-accuracy=0.881406
2016-05-03 16:30:36,467 Node[0] Epoch[21] Batch [200] Speed: 634.59 samples/sec Train-accuracy=0.869844
2016-05-03 16:30:46,565 Node[0] Epoch[21] Batch [250] Speed: 633.85 samples/sec Train-accuracy=0.869062
2016-05-03 16:30:56,658 Node[0] Epoch[21] Batch [300] Speed: 634.10 samples/sec Train-accuracy=0.881094
2016-05-03 16:31:06,766 Node[0] Epoch[21] Batch [350] Speed: 633.20 samples/sec Train-accuracy=0.871094
2016-05-03 16:31:14,825 Node[0] Epoch[21] Resetting Data Iterator
2016-05-03 16:31:14,825 Node[0] Epoch[21] Time cost=78.839
2016-05-03 16:31:14,981 Node[0] Saved checkpoint to "cifar10/resnet-0022.params"
2016-05-03 16:31:16,878 Node[0] Epoch[21] Validation-accuracy=0.828626
2016-05-03 16:31:27,026 Node[0] Epoch[22] Batch [50] Speed: 633.98 samples/sec Train-accuracy=0.867969
2016-05-03 16:31:37,191 Node[0] Epoch[22] Batch [100] Speed: 629.66 samples/sec Train-accuracy=0.875313
2016-05-03 16:31:47,343 Node[0] Epoch[22] Batch [150] Speed: 630.44 samples/sec Train-accuracy=0.875313
2016-05-03 16:31:57,486 Node[0] Epoch[22] Batch [200] Speed: 631.01 samples/sec Train-accuracy=0.878437
2016-05-03 16:32:07,582 Node[0] Epoch[22] Batch [250] Speed: 633.92 samples/sec Train-accuracy=0.876563
2016-05-03 16:32:17,662 Node[0] Epoch[22] Batch [300] Speed: 634.93 samples/sec Train-accuracy=0.876563
2016-05-03 16:32:27,785 Node[0] Epoch[22] Batch [350] Speed: 632.20 samples/sec Train-accuracy=0.876250
2016-05-03 16:32:36,081 Node[0] Epoch[22] Resetting Data Iterator
2016-05-03 16:32:36,082 Node[0] Epoch[22] Time cost=79.203
2016-05-03 16:32:36,242 Node[0] Saved checkpoint to "cifar10/resnet-0023.params"
2016-05-03 16:32:38,174 Node[0] Epoch[22] Validation-accuracy=0.831631
2016-05-03 16:32:48,283 Node[0] Epoch[23] Batch [50] Speed: 636.47 samples/sec Train-accuracy=0.878125
2016-05-03 16:32:58,492 Node[0] Epoch[23] Batch [100] Speed: 626.95 samples/sec Train-accuracy=0.885781
2016-05-03 16:33:08,678 Node[0] Epoch[23] Batch [150] Speed: 628.32 samples/sec Train-accuracy=0.886250
2016-05-03 16:33:18,789 Node[0] Epoch[23] Batch [200] Speed: 632.95 samples/sec Train-accuracy=0.878750
2016-05-03 16:33:28,871 Node[0] Epoch[23] Batch [250] Speed: 634.81 samples/sec Train-accuracy=0.867188
2016-05-03 16:33:39,044 Node[0] Epoch[23] Batch [300] Speed: 629.16 samples/sec Train-accuracy=0.878281
2016-05-03 16:33:49,174 Node[0] Epoch[23] Batch [350] Speed: 631.79 samples/sec Train-accuracy=0.880000
2016-05-03 16:33:57,254 Node[0] Epoch[23] Resetting Data Iterator
2016-05-03 16:33:57,254 Node[0] Epoch[23] Time cost=79.080
2016-05-03 16:33:57,412 Node[0] Saved checkpoint to "cifar10/resnet-0024.params"
2016-05-03 16:33:59,336 Node[0] Epoch[23] Validation-accuracy=0.826623
2016-05-03 16:34:09,552 Node[0] Epoch[24] Batch [50] Speed: 629.77 samples/sec Train-accuracy=0.874375
2016-05-03 16:34:19,685 Node[0] Epoch[24] Batch [100] Speed: 631.66 samples/sec Train-accuracy=0.883437
2016-05-03 16:34:29,807 Node[0] Epoch[24] Batch [150] Speed: 632.29 samples/sec Train-accuracy=0.880313
2016-05-03 16:34:39,952 Node[0] Epoch[24] Batch [200] Speed: 630.87 samples/sec Train-accuracy=0.882031
2016-05-03 16:34:50,049 Node[0] Epoch[24] Batch [250] Speed: 633.87 samples/sec Train-accuracy=0.883125
2016-05-03 16:35:00,186 Node[0] Epoch[24] Batch [300] Speed: 631.36 samples/sec Train-accuracy=0.888125
2016-05-03 16:35:10,335 Node[0] Epoch[24] Batch [350] Speed: 630.66 samples/sec Train-accuracy=0.882031
2016-05-03 16:35:18,636 Node[0] Epoch[24] Resetting Data Iterator
2016-05-03 16:35:18,636 Node[0] Epoch[24] Time cost=79.299
2016-05-03 16:35:18,799 Node[0] Saved checkpoint to "cifar10/resnet-0025.params"
2016-05-03 16:35:20,949 Node[0] Epoch[24] Validation-accuracy=0.838805
2016-05-03 16:35:31,062 Node[0] Epoch[25] Batch [50] Speed: 636.13 samples/sec Train-accuracy=0.890469
2016-05-03 16:35:41,195 Node[0] Epoch[25] Batch [100] Speed: 631.63 samples/sec Train-accuracy=0.883281
2016-05-03 16:35:51,323 Node[0] Epoch[25] Batch [150] Speed: 631.92 samples/sec Train-accuracy=0.882812
2016-05-03 16:36:01,468 Node[0] Epoch[25] Batch [200] Speed: 630.87 samples/sec Train-accuracy=0.880469
2016-05-03 16:36:11,619 Node[0] Epoch[25] Batch [250] Speed: 630.47 samples/sec Train-accuracy=0.882969
2016-05-03 16:36:21,744 Node[0] Epoch[25] Batch [300] Speed: 632.11 samples/sec Train-accuracy=0.888281
2016-05-03 16:36:31,886 Node[0] Epoch[25] Batch [350] Speed: 631.02 samples/sec Train-accuracy=0.884687
2016-05-03 16:36:40,189 Node[0] Epoch[25] Resetting Data Iterator
2016-05-03 16:36:40,189 Node[0] Epoch[25] Time cost=79.240
2016-05-03 16:36:40,350 Node[0] Saved checkpoint to "cifar10/resnet-0026.params"
2016-05-03 16:36:42,219 Node[0] Epoch[25] Validation-accuracy=0.818309
2016-05-03 16:36:52,335 Node[0] Epoch[26] Batch [50] Speed: 636.13 samples/sec Train-accuracy=0.884531
2016-05-03 16:37:02,474 Node[0] Epoch[26] Batch [100] Speed: 631.18 samples/sec Train-accuracy=0.886563
2016-05-03 16:37:12,586 Node[0] Epoch[26] Batch [150] Speed: 632.97 samples/sec Train-accuracy=0.888594
2016-05-03 16:37:22,709 Node[0] Epoch[26] Batch [200] Speed: 632.25 samples/sec Train-accuracy=0.881875
2016-05-03 16:37:32,847 Node[0] Epoch[26] Batch [250] Speed: 631.30 samples/sec Train-accuracy=0.887656
2016-05-03 16:37:42,996 Node[0] Epoch[26] Batch [300] Speed: 630.58 samples/sec Train-accuracy=0.885469
2016-05-03 16:37:53,120 Node[0] Epoch[26] Batch [350] Speed: 632.19 samples/sec Train-accuracy=0.891250
2016-05-03 16:38:01,221 Node[0] Epoch[26] Resetting Data Iterator
2016-05-03 16:38:01,221 Node[0] Epoch[26] Time cost=79.002
2016-05-03 16:38:01,382 Node[0] Saved checkpoint to "cifar10/resnet-0027.params"
2016-05-03 16:38:03,292 Node[0] Epoch[26] Validation-accuracy=0.823317
2016-05-03 16:38:13,513 Node[0] Epoch[27] Batch [50] Speed: 629.46 samples/sec Train-accuracy=0.882031
2016-05-03 16:38:23,669 Node[0] Epoch[27] Batch [100] Speed: 630.22 samples/sec Train-accuracy=0.887656
2016-05-03 16:38:33,791 Node[0] Epoch[27] Batch [150] Speed: 632.31 samples/sec Train-accuracy=0.895312
2016-05-03 16:38:43,938 Node[0] Epoch[27] Batch [200] Speed: 630.76 samples/sec Train-accuracy=0.887813
2016-05-03 16:38:54,072 Node[0] Epoch[27] Batch [250] Speed: 631.55 samples/sec Train-accuracy=0.888125
2016-05-03 16:39:04,171 Node[0] Epoch[27] Batch [300] Speed: 633.75 samples/sec Train-accuracy=0.887344
2016-05-03 16:39:14,286 Node[0] Epoch[27] Batch [350] Speed: 632.68 samples/sec Train-accuracy=0.889687
2016-05-03 16:39:22,556 Node[0] Epoch[27] Resetting Data Iterator
2016-05-03 16:39:22,556 Node[0] Epoch[27] Time cost=79.264
2016-05-03 16:39:22,716 Node[0] Saved checkpoint to "cifar10/resnet-0028.params"
2016-05-03 16:39:24,666 Node[0] Epoch[27] Validation-accuracy=0.839143
2016-05-03 16:39:34,829 Node[0] Epoch[28] Batch [50] Speed: 633.07 samples/sec Train-accuracy=0.891406
2016-05-03 16:39:44,950 Node[0] Epoch[28] Batch [100] Speed: 632.35 samples/sec Train-accuracy=0.891094
2016-05-03 16:39:55,042 Node[0] Epoch[28] Batch [150] Speed: 634.22 samples/sec Train-accuracy=0.892031
2016-05-03 16:40:05,179 Node[0] Epoch[28] Batch [200] Speed: 631.39 samples/sec Train-accuracy=0.892813
2016-05-03 16:40:15,312 Node[0] Epoch[28] Batch [250] Speed: 631.56 samples/sec Train-accuracy=0.890469
2016-05-03 16:40:25,430 Node[0] Epoch[28] Batch [300] Speed: 632.57 samples/sec Train-accuracy=0.888437
2016-05-03 16:40:35,559 Node[0] Epoch[28] Batch [350] Speed: 631.88 samples/sec Train-accuracy=0.896875
2016-05-03 16:40:43,859 Node[0] Epoch[28] Resetting Data Iterator
2016-05-03 16:40:43,860 Node[0] Epoch[28] Time cost=79.194
2016-05-03 16:40:44,023 Node[0] Saved checkpoint to "cifar10/resnet-0029.params"
2016-05-03 16:40:45,915 Node[0] Epoch[28] Validation-accuracy=0.819010
2016-05-03 16:40:56,094 Node[0] Epoch[29] Batch [50] Speed: 632.10 samples/sec Train-accuracy=0.896406
2016-05-03 16:41:06,177 Node[0] Epoch[29] Batch [100] Speed: 634.69 samples/sec Train-accuracy=0.892656
2016-05-03 16:41:16,248 Node[0] Epoch[29] Batch [150] Speed: 635.52 samples/sec Train-accuracy=0.888437
2016-05-03 16:41:26,371 Node[0] Epoch[29] Batch [200] Speed: 632.25 samples/sec Train-accuracy=0.884531
2016-05-03 16:41:36,516 Node[0] Epoch[29] Batch [250] Speed: 630.86 samples/sec Train-accuracy=0.889219
2016-05-03 16:41:46,637 Node[0] Epoch[29] Batch [300] Speed: 632.40 samples/sec Train-accuracy=0.896875
2016-05-03 16:41:56,757 Node[0] Epoch[29] Batch [350] Speed: 632.41 samples/sec Train-accuracy=0.899844
2016-05-03 16:42:04,817 Node[0] Epoch[29] Resetting Data Iterator
2016-05-03 16:42:04,818 Node[0] Epoch[29] Time cost=78.902
2016-05-03 16:42:04,977 Node[0] Saved checkpoint to "cifar10/resnet-0030.params"
2016-05-03 16:42:06,883 Node[0] Epoch[29] Validation-accuracy=0.838542
2016-05-03 16:42:16,991 Node[0] Epoch[30] Batch [50] Speed: 636.45 samples/sec Train-accuracy=0.887813
2016-05-03 16:42:27,054 Node[0] Epoch[30] Batch [100] Speed: 636.02 samples/sec Train-accuracy=0.891250
2016-05-03 16:42:37,082 Node[0] Epoch[30] Batch [150] Speed: 638.24 samples/sec Train-accuracy=0.900781
2016-05-03 16:42:47,185 Node[0] Epoch[30] Batch [200] Speed: 633.49 samples/sec Train-accuracy=0.894687
2016-05-03 16:42:57,248 Node[0] Epoch[30] Batch [250] Speed: 635.99 samples/sec Train-accuracy=0.892969
2016-05-03 16:43:07,352 Node[0] Epoch[30] Batch [300] Speed: 633.44 samples/sec Train-accuracy=0.900156
2016-05-03 16:43:17,429 Node[0] Epoch[30] Batch [350] Speed: 635.14 samples/sec Train-accuracy=0.883281
2016-05-03 16:43:25,674 Node[0] Epoch[30] Resetting Data Iterator
2016-05-03 16:43:25,674 Node[0] Epoch[30] Time cost=78.790
2016-05-03 16:43:25,833 Node[0] Saved checkpoint to "cifar10/resnet-0031.params"
2016-05-03 16:43:27,772 Node[0] Epoch[30] Validation-accuracy=0.820813
2016-05-03 16:43:37,887 Node[0] Epoch[31] Batch [50] Speed: 636.13 samples/sec Train-accuracy=0.896719
2016-05-03 16:43:48,071 Node[0] Epoch[31] Batch [100] Speed: 628.48 samples/sec Train-accuracy=0.905000
2016-05-03 16:43:58,152 Node[0] Epoch[31] Batch [150] Speed: 634.89 samples/sec Train-accuracy=0.900937
2016-05-03 16:44:08,232 Node[0] Epoch[31] Batch [200] Speed: 634.91 samples/sec Train-accuracy=0.899687
2016-05-03 16:44:18,301 Node[0] Epoch[31] Batch [250] Speed: 635.66 samples/sec Train-accuracy=0.894687
2016-05-03 16:44:28,454 Node[0] Epoch[31] Batch [300] Speed: 630.34 samples/sec Train-accuracy=0.895000
2016-05-03 16:44:38,592 Node[0] Epoch[31] Batch [350] Speed: 631.32 samples/sec Train-accuracy=0.893437
2016-05-03 16:44:46,721 Node[0] Epoch[31] Resetting Data Iterator
2016-05-03 16:44:46,721 Node[0] Epoch[31] Time cost=78.949
2016-05-03 16:44:46,878 Node[0] Saved checkpoint to "cifar10/resnet-0032.params"
2016-05-03 16:44:48,752 Node[0] Epoch[31] Validation-accuracy=0.824619
2016-05-03 16:44:58,788 Node[0] Epoch[32] Batch [50] Speed: 641.12 samples/sec Train-accuracy=0.901563
2016-05-03 16:45:08,902 Node[0] Epoch[32] Batch [100] Speed: 632.83 samples/sec Train-accuracy=0.901250
2016-05-03 16:45:19,010 Node[0] Epoch[32] Batch [150] Speed: 633.14 samples/sec Train-accuracy=0.898594
2016-05-03 16:45:29,136 Node[0] Epoch[32] Batch [200] Speed: 632.08 samples/sec Train-accuracy=0.903594
2016-05-03 16:45:39,262 Node[0] Epoch[32] Batch [250] Speed: 632.05 samples/sec Train-accuracy=0.894531
2016-05-03 16:45:49,442 Node[0] Epoch[32] Batch [300] Speed: 628.67 samples/sec Train-accuracy=0.901563
2016-05-03 16:45:59,594 Node[0] Epoch[32] Batch [350] Speed: 630.47 samples/sec Train-accuracy=0.900000
2016-05-03 16:46:07,870 Node[0] Epoch[32] Resetting Data Iterator
2016-05-03 16:46:07,870 Node[0] Epoch[32] Time cost=79.117
2016-05-03 16:46:08,025 Node[0] Saved checkpoint to "cifar10/resnet-0033.params"
2016-05-03 16:46:10,104 Node[0] Epoch[32] Validation-accuracy=0.826741
2016-05-03 16:46:20,237 Node[0] Epoch[33] Batch [50] Speed: 635.09 samples/sec Train-accuracy=0.895938
2016-05-03 16:46:30,373 Node[0] Epoch[33] Batch [100] Speed: 631.42 samples/sec Train-accuracy=0.900000
2016-05-03 16:46:40,495 Node[0] Epoch[33] Batch [150] Speed: 632.29 samples/sec Train-accuracy=0.905781
2016-05-03 16:46:50,616 Node[0] Epoch[33] Batch [200] Speed: 632.38 samples/sec Train-accuracy=0.901563
2016-05-03 16:47:00,770 Node[0] Epoch[33] Batch [250] Speed: 630.31 samples/sec Train-accuracy=0.904531
2016-05-03 16:47:10,906 Node[0] Epoch[33] Batch [300] Speed: 631.44 samples/sec Train-accuracy=0.903594
2016-05-03 16:47:21,025 Node[0] Epoch[33] Batch [350] Speed: 632.49 samples/sec Train-accuracy=0.900000
2016-05-03 16:47:29,323 Node[0] Epoch[33] Resetting Data Iterator
2016-05-03 16:47:29,323 Node[0] Epoch[33] Time cost=79.219
2016-05-03 16:47:29,480 Node[0] Saved checkpoint to "cifar10/resnet-0034.params"
2016-05-03 16:47:31,401 Node[0] Epoch[33] Validation-accuracy=0.839343
2016-05-03 16:47:41,527 Node[0] Epoch[34] Batch [50] Speed: 635.39 samples/sec Train-accuracy=0.895938
2016-05-03 16:47:51,639 Node[0] Epoch[34] Batch [100] Speed: 632.88 samples/sec Train-accuracy=0.902188
2016-05-03 16:48:01,777 Node[0] Epoch[34] Batch [150] Speed: 631.35 samples/sec Train-accuracy=0.913906
2016-05-03 16:48:11,869 Node[0] Epoch[34] Batch [200] Speed: 634.14 samples/sec Train-accuracy=0.905156
2016-05-03 16:48:21,981 Node[0] Epoch[34] Batch [250] Speed: 632.96 samples/sec Train-accuracy=0.901094
2016-05-03 16:48:32,074 Node[0] Epoch[34] Batch [300] Speed: 634.10 samples/sec Train-accuracy=0.897813
2016-05-03 16:48:42,107 Node[0] Epoch[34] Batch [350] Speed: 637.92 samples/sec Train-accuracy=0.902344
2016-05-03 16:48:50,161 Node[0] Epoch[34] Resetting Data Iterator
2016-05-03 16:48:50,161 Node[0] Epoch[34] Time cost=78.760
2016-05-03 16:48:50,318 Node[0] Saved checkpoint to "cifar10/resnet-0035.params"
2016-05-03 16:48:52,246 Node[0] Epoch[34] Validation-accuracy=0.834836
2016-05-03 16:49:02,361 Node[0] Epoch[35] Batch [50] Speed: 636.13 samples/sec Train-accuracy=0.898594
2016-05-03 16:49:12,465 Node[0] Epoch[35] Batch [100] Speed: 633.41 samples/sec Train-accuracy=0.904219
2016-05-03 16:49:22,566 Node[0] Epoch[35] Batch [150] Speed: 633.63 samples/sec Train-accuracy=0.903750
2016-05-03 16:49:32,665 Node[0] Epoch[35] Batch [200] Speed: 633.72 samples/sec Train-accuracy=0.907813
2016-05-03 16:49:42,705 Node[0] Epoch[35] Batch [250] Speed: 637.49 samples/sec Train-accuracy=0.905937
2016-05-03 16:49:52,744 Node[0] Epoch[35] Batch [300] Speed: 637.50 samples/sec Train-accuracy=0.907031
2016-05-03 16:50:02,801 Node[0] Epoch[35] Batch [350] Speed: 636.42 samples/sec Train-accuracy=0.904062
2016-05-03 16:50:11,053 Node[0] Epoch[35] Resetting Data Iterator
2016-05-03 16:50:11,054 Node[0] Epoch[35] Time cost=78.807
2016-05-03 16:50:11,211 Node[0] Saved checkpoint to "cifar10/resnet-0036.params"
2016-05-03 16:50:13,105 Node[0] Epoch[35] Validation-accuracy=0.839944
2016-05-03 16:50:23,192 Node[0] Epoch[36] Batch [50] Speed: 637.82 samples/sec Train-accuracy=0.904531
2016-05-03 16:50:33,334 Node[0] Epoch[36] Batch [100] Speed: 631.05 samples/sec Train-accuracy=0.906563
2016-05-03 16:50:43,427 Node[0] Epoch[36] Batch [150] Speed: 634.11 samples/sec Train-accuracy=0.902813
2016-05-03 16:50:53,562 Node[0] Epoch[36] Batch [200] Speed: 631.48 samples/sec Train-accuracy=0.910312
2016-05-03 16:51:03,647 Node[0] Epoch[36] Batch [250] Speed: 634.64 samples/sec Train-accuracy=0.903750
2016-05-03 16:51:13,725 Node[0] Epoch[36] Batch [300] Speed: 635.06 samples/sec Train-accuracy=0.905156
2016-05-03 16:51:23,823 Node[0] Epoch[36] Batch [350] Speed: 633.85 samples/sec Train-accuracy=0.903906
2016-05-03 16:51:32,087 Node[0] Epoch[36] Resetting Data Iterator
2016-05-03 16:51:32,087 Node[0] Epoch[36] Time cost=78.982
2016-05-03 16:51:32,243 Node[0] Saved checkpoint to "cifar10/resnet-0037.params"
2016-05-03 16:51:34,138 Node[0] Epoch[36] Validation-accuracy=0.838642
2016-05-03 16:51:44,332 Node[0] Epoch[37] Batch [50] Speed: 631.10 samples/sec Train-accuracy=0.905625
2016-05-03 16:51:54,470 Node[0] Epoch[37] Batch [100] Speed: 631.30 samples/sec Train-accuracy=0.906719
2016-05-03 16:52:04,610 Node[0] Epoch[37] Batch [150] Speed: 631.19 samples/sec Train-accuracy=0.914531
2016-05-03 16:52:14,748 Node[0] Epoch[37] Batch [200] Speed: 631.33 samples/sec Train-accuracy=0.903594
2016-05-03 16:52:24,831 Node[0] Epoch[37] Batch [250] Speed: 634.75 samples/sec Train-accuracy=0.906094
2016-05-03 16:52:34,950 Node[0] Epoch[37] Batch [300] Speed: 632.51 samples/sec Train-accuracy=0.909687
2016-05-03 16:52:45,092 Node[0] Epoch[37] Batch [350] Speed: 631.01 samples/sec Train-accuracy=0.906406
2016-05-03 16:52:53,158 Node[0] Epoch[37] Resetting Data Iterator
2016-05-03 16:52:53,158 Node[0] Epoch[37] Time cost=79.020
2016-05-03 16:52:53,315 Node[0] Saved checkpoint to "cifar10/resnet-0038.params"
2016-05-03 16:52:55,253 Node[0] Epoch[37] Validation-accuracy=0.850160
2016-05-03 16:53:05,397 Node[0] Epoch[38] Batch [50] Speed: 634.20 samples/sec Train-accuracy=0.904531
2016-05-03 16:53:15,565 Node[0] Epoch[38] Batch [100] Speed: 629.40 samples/sec Train-accuracy=0.913906
2016-05-03 16:53:25,672 Node[0] Epoch[38] Batch [150] Speed: 633.27 samples/sec Train-accuracy=0.912500
2016-05-03 16:53:35,792 Node[0] Epoch[38] Batch [200] Speed: 632.42 samples/sec Train-accuracy=0.907031
2016-05-03 16:53:45,920 Node[0] Epoch[38] Batch [250] Speed: 631.95 samples/sec Train-accuracy=0.907813
2016-05-03 16:53:55,996 Node[0] Epoch[38] Batch [300] Speed: 635.19 samples/sec Train-accuracy=0.904062
2016-05-03 16:54:06,100 Node[0] Epoch[38] Batch [350] Speed: 633.45 samples/sec Train-accuracy=0.903125
2016-05-03 16:54:14,375 Node[0] Epoch[38] Resetting Data Iterator
2016-05-03 16:54:14,375 Node[0] Epoch[38] Time cost=79.122
2016-05-03 16:54:14,532 Node[0] Saved checkpoint to "cifar10/resnet-0039.params"
2016-05-03 16:54:16,433 Node[0] Epoch[38] Validation-accuracy=0.847656
2016-05-03 16:54:26,484 Node[0] Epoch[39] Batch [50] Speed: 640.21 samples/sec Train-accuracy=0.909531
2016-05-03 16:54:36,632 Node[0] Epoch[39] Batch [100] Speed: 630.63 samples/sec Train-accuracy=0.907344
2016-05-03 16:54:46,710 Node[0] Epoch[39] Batch [150] Speed: 635.09 samples/sec Train-accuracy=0.911406
2016-05-03 16:54:56,807 Node[0] Epoch[39] Batch [200] Speed: 633.88 samples/sec Train-accuracy=0.904219
2016-05-03 16:55:06,887 Node[0] Epoch[39] Batch [250] Speed: 634.93 samples/sec Train-accuracy=0.911250
2016-05-03 16:55:17,008 Node[0] Epoch[39] Batch [300] Speed: 632.38 samples/sec Train-accuracy=0.913281
2016-05-03 16:55:27,080 Node[0] Epoch[39] Batch [350] Speed: 635.39 samples/sec Train-accuracy=0.907188
2016-05-03 16:55:35,136 Node[0] Epoch[39] Resetting Data Iterator
2016-05-03 16:55:35,136 Node[0] Epoch[39] Time cost=78.702
2016-05-03 16:55:35,290 Node[0] Saved checkpoint to "cifar10/resnet-0040.params"
2016-05-03 16:55:37,176 Node[0] Epoch[39] Validation-accuracy=0.816707
2016-05-03 16:55:47,220 Node[0] Epoch[40] Batch [50] Speed: 640.53 samples/sec Train-accuracy=0.911094
2016-05-03 16:55:57,361 Node[0] Epoch[40] Batch [100] Speed: 631.08 samples/sec Train-accuracy=0.908438
2016-05-03 16:56:07,478 Node[0] Epoch[40] Batch [150] Speed: 632.66 samples/sec Train-accuracy=0.912031
2016-05-03 16:56:17,585 Node[0] Epoch[40] Batch [200] Speed: 633.21 samples/sec Train-accuracy=0.907344
2016-05-03 16:56:27,703 Node[0] Epoch[40] Batch [250] Speed: 632.54 samples/sec Train-accuracy=0.904531
2016-05-03 16:56:37,847 Node[0] Epoch[40] Batch [300] Speed: 630.93 samples/sec Train-accuracy=0.913438
2016-05-03 16:56:47,972 Node[0] Epoch[40] Batch [350] Speed: 632.17 samples/sec Train-accuracy=0.909844
2016-05-03 16:56:56,236 Node[0] Epoch[40] Resetting Data Iterator
2016-05-03 16:56:56,236 Node[0] Epoch[40] Time cost=79.061
2016-05-03 16:56:56,395 Node[0] Saved checkpoint to "cifar10/resnet-0041.params"
2016-05-03 16:56:58,476 Node[0] Epoch[40] Validation-accuracy=0.840091
2016-05-03 16:57:08,596 Node[0] Epoch[41] Batch [50] Speed: 635.69 samples/sec Train-accuracy=0.911563
2016-05-03 16:57:18,729 Node[0] Epoch[41] Batch [100] Speed: 631.57 samples/sec Train-accuracy=0.910937
2016-05-03 16:57:28,828 Node[0] Epoch[41] Batch [150] Speed: 633.76 samples/sec Train-accuracy=0.912344
2016-05-03 16:57:38,924 Node[0] Epoch[41] Batch [200] Speed: 633.91 samples/sec Train-accuracy=0.916094
2016-05-03 16:57:48,935 Node[0] Epoch[41] Batch [250] Speed: 639.33 samples/sec Train-accuracy=0.909687
2016-05-03 16:57:58,940 Node[0] Epoch[41] Batch [300] Speed: 639.73 samples/sec Train-accuracy=0.912188
2016-05-03 16:58:09,002 Node[0] Epoch[41] Batch [350] Speed: 636.08 samples/sec Train-accuracy=0.910469
2016-05-03 16:58:17,238 Node[0] Epoch[41] Resetting Data Iterator
2016-05-03 16:58:17,238 Node[0] Epoch[41] Time cost=78.762
2016-05-03 16:58:17,403 Node[0] Saved checkpoint to "cifar10/resnet-0042.params"
2016-05-03 16:58:19,302 Node[0] Epoch[41] Validation-accuracy=0.845152
2016-05-03 16:58:29,424 Node[0] Epoch[42] Batch [50] Speed: 635.68 samples/sec Train-accuracy=0.904531
2016-05-03 16:58:39,544 Node[0] Epoch[42] Batch [100] Speed: 632.44 samples/sec Train-accuracy=0.911875
2016-05-03 16:58:49,665 Node[0] Epoch[42] Batch [150] Speed: 632.40 samples/sec Train-accuracy=0.910781
2016-05-03 16:58:59,777 Node[0] Epoch[42] Batch [200] Speed: 632.88 samples/sec Train-accuracy=0.908281
2016-05-03 16:59:09,901 Node[0] Epoch[42] Batch [250] Speed: 632.22 samples/sec Train-accuracy=0.913594
2016-05-03 16:59:20,038 Node[0] Epoch[42] Batch [300] Speed: 631.37 samples/sec Train-accuracy=0.917969
2016-05-03 16:59:30,156 Node[0] Epoch[42] Batch [350] Speed: 632.55 samples/sec Train-accuracy=0.911406
2016-05-03 16:59:38,254 Node[0] Epoch[42] Resetting Data Iterator
2016-05-03 16:59:38,254 Node[0] Epoch[42] Time cost=78.952
2016-05-03 16:59:38,413 Node[0] Saved checkpoint to "cifar10/resnet-0043.params"
2016-05-03 16:59:40,314 Node[0] Epoch[42] Validation-accuracy=0.829026
2016-05-03 16:59:50,415 Node[0] Epoch[43] Batch [50] Speed: 636.99 samples/sec Train-accuracy=0.908750
2016-05-03 17:00:00,537 Node[0] Epoch[43] Batch [100] Speed: 632.35 samples/sec Train-accuracy=0.912031
2016-05-03 17:00:10,650 Node[0] Epoch[43] Batch [150] Speed: 632.83 samples/sec Train-accuracy=0.920000
2016-05-03 17:00:20,753 Node[0] Epoch[43] Batch [200] Speed: 633.50 samples/sec Train-accuracy=0.916094
2016-05-03 17:00:30,876 Node[0] Epoch[43] Batch [250] Speed: 632.27 samples/sec Train-accuracy=0.913281
2016-05-03 17:00:40,990 Node[0] Epoch[43] Batch [300] Speed: 632.81 samples/sec Train-accuracy=0.915781
2016-05-03 17:00:51,060 Node[0] Epoch[43] Batch [350] Speed: 635.54 samples/sec Train-accuracy=0.913125
2016-05-03 17:00:59,326 Node[0] Epoch[43] Resetting Data Iterator
2016-05-03 17:00:59,327 Node[0] Epoch[43] Time cost=79.012
2016-05-03 17:00:59,485 Node[0] Saved checkpoint to "cifar10/resnet-0044.params"
2016-05-03 17:01:01,432 Node[0] Epoch[43] Validation-accuracy=0.841947
2016-05-03 17:01:11,593 Node[0] Epoch[44] Batch [50] Speed: 633.18 samples/sec Train-accuracy=0.910312
2016-05-03 17:01:21,740 Node[0] Epoch[44] Batch [100] Speed: 630.75 samples/sec Train-accuracy=0.915312
2016-05-03 17:01:31,850 Node[0] Epoch[44] Batch [150] Speed: 633.04 samples/sec Train-accuracy=0.921562
2016-05-03 17:01:41,948 Node[0] Epoch[44] Batch [200] Speed: 633.83 samples/sec Train-accuracy=0.913594
2016-05-03 17:01:52,038 Node[0] Epoch[44] Batch [250] Speed: 634.29 samples/sec Train-accuracy=0.912969
2016-05-03 17:02:02,206 Node[0] Epoch[44] Batch [300] Speed: 629.44 samples/sec Train-accuracy=0.913594
2016-05-03 17:02:12,357 Node[0] Epoch[44] Batch [350] Speed: 630.52 samples/sec Train-accuracy=0.917188
2016-05-03 17:02:20,629 Node[0] Epoch[44] Resetting Data Iterator
2016-05-03 17:02:20,629 Node[0] Epoch[44] Time cost=79.197
2016-05-03 17:02:20,787 Node[0] Saved checkpoint to "cifar10/resnet-0045.params"
2016-05-03 17:02:22,735 Node[0] Epoch[44] Validation-accuracy=0.838341
2016-05-03 17:02:32,785 Node[0] Epoch[45] Batch [50] Speed: 640.11 samples/sec Train-accuracy=0.909062
2016-05-03 17:02:42,911 Node[0] Epoch[45] Batch [100] Speed: 632.02 samples/sec Train-accuracy=0.918594
2016-05-03 17:02:53,049 Node[0] Epoch[45] Batch [150] Speed: 631.30 samples/sec Train-accuracy=0.917656
2016-05-03 17:03:03,183 Node[0] Epoch[45] Batch [200] Speed: 631.59 samples/sec Train-accuracy=0.910781
2016-05-03 17:03:13,322 Node[0] Epoch[45] Batch [250] Speed: 631.24 samples/sec Train-accuracy=0.915781
2016-05-03 17:03:23,448 Node[0] Epoch[45] Batch [300] Speed: 632.03 samples/sec Train-accuracy=0.916250
2016-05-03 17:03:33,525 Node[0] Epoch[45] Batch [350] Speed: 635.13 samples/sec Train-accuracy=0.918906
2016-05-03 17:03:41,621 Node[0] Epoch[45] Resetting Data Iterator
2016-05-03 17:03:41,621 Node[0] Epoch[45] Time cost=78.886
2016-05-03 17:03:41,783 Node[0] Saved checkpoint to "cifar10/resnet-0046.params"
2016-05-03 17:03:43,705 Node[0] Epoch[45] Validation-accuracy=0.836238
2016-05-03 17:03:53,807 Node[0] Epoch[46] Batch [50] Speed: 637.03 samples/sec Train-accuracy=0.912500
2016-05-03 17:04:03,916 Node[0] Epoch[46] Batch [100] Speed: 633.13 samples/sec Train-accuracy=0.917188
2016-05-03 17:04:14,001 Node[0] Epoch[46] Batch [150] Speed: 634.59 samples/sec Train-accuracy=0.925469
2016-05-03 17:04:24,074 Node[0] Epoch[46] Batch [200] Speed: 635.42 samples/sec Train-accuracy=0.917344
2016-05-03 17:04:34,231 Node[0] Epoch[46] Batch [250] Speed: 630.10 samples/sec Train-accuracy=0.915312
2016-05-03 17:04:44,317 Node[0] Epoch[46] Batch [300] Speed: 634.59 samples/sec Train-accuracy=0.913281
2016-05-03 17:04:54,447 Node[0] Epoch[46] Batch [350] Speed: 631.76 samples/sec Train-accuracy=0.911094
2016-05-03 17:05:02,703 Node[0] Epoch[46] Resetting Data Iterator
2016-05-03 17:05:02,703 Node[0] Epoch[46] Time cost=78.998
2016-05-03 17:05:02,864 Node[0] Saved checkpoint to "cifar10/resnet-0047.params"
2016-05-03 17:05:04,803 Node[0] Epoch[46] Validation-accuracy=0.815304
2016-05-03 17:05:14,943 Node[0] Epoch[47] Batch [50] Speed: 634.46 samples/sec Train-accuracy=0.912813
2016-05-03 17:05:25,144 Node[0] Epoch[47] Batch [100] Speed: 627.41 samples/sec Train-accuracy=0.920000
2016-05-03 17:05:35,272 Node[0] Epoch[47] Batch [150] Speed: 631.91 samples/sec Train-accuracy=0.913594
2016-05-03 17:05:45,371 Node[0] Epoch[47] Batch [200] Speed: 633.75 samples/sec Train-accuracy=0.910781
2016-05-03 17:05:55,469 Node[0] Epoch[47] Batch [250] Speed: 633.81 samples/sec Train-accuracy=0.914375
2016-05-03 17:06:05,610 Node[0] Epoch[47] Batch [300] Speed: 631.11 samples/sec Train-accuracy=0.918281
2016-05-03 17:06:15,688 Node[0] Epoch[47] Batch [350] Speed: 635.09 samples/sec Train-accuracy=0.915937
2016-05-03 17:06:23,763 Node[0] Epoch[47] Resetting Data Iterator
2016-05-03 17:06:23,763 Node[0] Epoch[47] Time cost=78.960
2016-05-03 17:06:23,923 Node[0] Saved checkpoint to "cifar10/resnet-0048.params"
2016-05-03 17:06:25,838 Node[0] Epoch[47] Validation-accuracy=0.844351
2016-05-03 17:06:36,010 Node[0] Epoch[48] Batch [50] Speed: 632.69 samples/sec Train-accuracy=0.915625
2016-05-03 17:06:46,107 Node[0] Epoch[48] Batch [100] Speed: 633.82 samples/sec Train-accuracy=0.918750
2016-05-03 17:06:56,231 Node[0] Epoch[48] Batch [150] Speed: 632.18 samples/sec Train-accuracy=0.922656
2016-05-03 17:07:06,302 Node[0] Epoch[48] Batch [200] Speed: 635.54 samples/sec Train-accuracy=0.913906
2016-05-03 17:07:16,436 Node[0] Epoch[48] Batch [250] Speed: 631.52 samples/sec Train-accuracy=0.916719
2016-05-03 17:07:26,558 Node[0] Epoch[48] Batch [300] Speed: 632.30 samples/sec Train-accuracy=0.920469
2016-05-03 17:07:36,645 Node[0] Epoch[48] Batch [350] Speed: 634.51 samples/sec Train-accuracy=0.916562
2016-05-03 17:07:44,917 Node[0] Epoch[48] Resetting Data Iterator
2016-05-03 17:07:44,917 Node[0] Epoch[48] Time cost=79.078
2016-05-03 17:07:45,083 Node[0] Saved checkpoint to "cifar10/resnet-0049.params"
2016-05-03 17:07:47,183 Node[0] Epoch[48] Validation-accuracy=0.854727
2016-05-03 17:07:57,336 Node[0] Epoch[49] Batch [50] Speed: 633.72 samples/sec Train-accuracy=0.916719
2016-05-03 17:08:07,493 Node[0] Epoch[49] Batch [100] Speed: 630.12 samples/sec Train-accuracy=0.920156
2016-05-03 17:08:17,607 Node[0] Epoch[49] Batch [150] Speed: 632.79 samples/sec Train-accuracy=0.924687
2016-05-03 17:08:27,710 Node[0] Epoch[49] Batch [200] Speed: 633.50 samples/sec Train-accuracy=0.923438
2016-05-03 17:08:37,816 Node[0] Epoch[49] Batch [250] Speed: 633.30 samples/sec Train-accuracy=0.915781
2016-05-03 17:08:47,957 Node[0] Epoch[49] Batch [300] Speed: 631.15 samples/sec Train-accuracy=0.919219
2016-05-03 17:08:58,070 Node[0] Epoch[49] Batch [350] Speed: 632.83 samples/sec Train-accuracy=0.923906
2016-05-03 17:09:06,363 Node[0] Epoch[49] Resetting Data Iterator
2016-05-03 17:09:06,363 Node[0] Epoch[49] Time cost=79.180
2016-05-03 17:09:06,519 Node[0] Saved checkpoint to "cifar10/resnet-0050.params"
2016-05-03 17:09:08,423 Node[0] Epoch[49] Validation-accuracy=0.845152
2016-05-03 17:09:18,509 Node[0] Epoch[50] Batch [50] Speed: 637.89 samples/sec Train-accuracy=0.917969
2016-05-03 17:09:28,587 Node[0] Epoch[50] Batch [100] Speed: 635.09 samples/sec Train-accuracy=0.919531
2016-05-03 17:09:38,693 Node[0] Epoch[50] Batch [150] Speed: 633.30 samples/sec Train-accuracy=0.925937
2016-05-03 17:09:48,809 Node[0] Epoch[50] Batch [200] Speed: 632.66 samples/sec Train-accuracy=0.915156
2016-05-03 17:09:58,893 Node[0] Epoch[50] Batch [250] Speed: 634.68 samples/sec Train-accuracy=0.922656
2016-05-03 17:10:09,010 Node[0] Epoch[50] Batch [300] Speed: 632.65 samples/sec Train-accuracy=0.920156
2016-05-03 17:10:19,105 Node[0] Epoch[50] Batch [350] Speed: 633.95 samples/sec Train-accuracy=0.919063
2016-05-03 17:10:27,209 Node[0] Epoch[50] Resetting Data Iterator
2016-05-03 17:10:27,209 Node[0] Epoch[50] Time cost=78.786
2016-05-03 17:10:27,371 Node[0] Saved checkpoint to "cifar10/resnet-0051.params"
2016-05-03 17:10:29,298 Node[0] Epoch[50] Validation-accuracy=0.827424
2016-05-03 17:10:39,333 Node[0] Epoch[51] Batch [50] Speed: 641.23 samples/sec Train-accuracy=0.912969
2016-05-03 17:10:49,496 Node[0] Epoch[51] Batch [100] Speed: 629.69 samples/sec Train-accuracy=0.918281
2016-05-03 17:10:59,580 Node[0] Epoch[51] Batch [150] Speed: 634.73 samples/sec Train-accuracy=0.914844
2016-05-03 17:11:09,703 Node[0] Epoch[51] Batch [200] Speed: 632.24 samples/sec Train-accuracy=0.920937
2016-05-03 17:11:19,796 Node[0] Epoch[51] Batch [250] Speed: 634.13 samples/sec Train-accuracy=0.922500
2016-05-03 17:11:29,879 Node[0] Epoch[51] Batch [300] Speed: 634.71 samples/sec Train-accuracy=0.924531
2016-05-03 17:11:39,940 Node[0] Epoch[51] Batch [350] Speed: 636.15 samples/sec Train-accuracy=0.927031
2016-05-03 17:11:48,225 Node[0] Epoch[51] Resetting Data Iterator
2016-05-03 17:11:48,225 Node[0] Epoch[51] Time cost=78.927
2016-05-03 17:11:48,383 Node[0] Saved checkpoint to "cifar10/resnet-0052.params"
2016-05-03 17:11:50,322 Node[0] Epoch[51] Validation-accuracy=0.825421
2016-05-03 17:12:00,450 Node[0] Epoch[52] Batch [50] Speed: 635.24 samples/sec Train-accuracy=0.918906
2016-05-03 17:12:10,575 Node[0] Epoch[52] Batch [100] Speed: 632.13 samples/sec Train-accuracy=0.919531
2016-05-03 17:12:20,710 Node[0] Epoch[52] Batch [150] Speed: 631.46 samples/sec Train-accuracy=0.926094
2016-05-03 17:12:30,883 Node[0] Epoch[52] Batch [200] Speed: 629.13 samples/sec Train-accuracy=0.917656
2016-05-03 17:12:41,004 Node[0] Epoch[52] Batch [250] Speed: 632.37 samples/sec Train-accuracy=0.920156
2016-05-03 17:12:51,129 Node[0] Epoch[52] Batch [300] Speed: 632.10 samples/sec Train-accuracy=0.921250
2016-05-03 17:13:01,211 Node[0] Epoch[52] Batch [350] Speed: 634.82 samples/sec Train-accuracy=0.920781
2016-05-03 17:13:09,497 Node[0] Epoch[52] Resetting Data Iterator
2016-05-03 17:13:09,497 Node[0] Epoch[52] Time cost=79.175
2016-05-03 17:13:09,655 Node[0] Saved checkpoint to "cifar10/resnet-0053.params"
2016-05-03 17:13:11,575 Node[0] Epoch[52] Validation-accuracy=0.848057
2016-05-03 17:13:21,719 Node[0] Epoch[53] Batch [50] Speed: 634.27 samples/sec Train-accuracy=0.919687
2016-05-03 17:13:31,864 Node[0] Epoch[53] Batch [100] Speed: 630.89 samples/sec Train-accuracy=0.917656
2016-05-03 17:13:41,971 Node[0] Epoch[53] Batch [150] Speed: 633.22 samples/sec Train-accuracy=0.927031
2016-05-03 17:13:52,041 Node[0] Epoch[53] Batch [200] Speed: 635.58 samples/sec Train-accuracy=0.923281
2016-05-03 17:14:02,158 Node[0] Epoch[53] Batch [250] Speed: 632.66 samples/sec Train-accuracy=0.920625
2016-05-03 17:14:12,245 Node[0] Epoch[53] Batch [300] Speed: 634.46 samples/sec Train-accuracy=0.928750
2016-05-03 17:14:22,376 Node[0] Epoch[53] Batch [350] Speed: 631.78 samples/sec Train-accuracy=0.918281
2016-05-03 17:14:30,431 Node[0] Epoch[53] Resetting Data Iterator
2016-05-03 17:14:30,431 Node[0] Epoch[53] Time cost=78.856
2016-05-03 17:14:30,592 Node[0] Saved checkpoint to "cifar10/resnet-0054.params"
2016-05-03 17:14:32,512 Node[0] Epoch[53] Validation-accuracy=0.820112
2016-05-03 17:14:42,623 Node[0] Epoch[54] Batch [50] Speed: 636.36 samples/sec Train-accuracy=0.919063
2016-05-03 17:14:52,738 Node[0] Epoch[54] Batch [100] Speed: 632.75 samples/sec Train-accuracy=0.922813
2016-05-03 17:15:02,852 Node[0] Epoch[54] Batch [150] Speed: 632.78 samples/sec Train-accuracy=0.927813
2016-05-03 17:15:12,933 Node[0] Epoch[54] Batch [200] Speed: 634.84 samples/sec Train-accuracy=0.923594
2016-05-03 17:15:23,016 Node[0] Epoch[54] Batch [250] Speed: 634.76 samples/sec Train-accuracy=0.922500
2016-05-03 17:15:33,121 Node[0] Epoch[54] Batch [300] Speed: 633.40 samples/sec Train-accuracy=0.921406
2016-05-03 17:15:43,197 Node[0] Epoch[54] Batch [350] Speed: 635.19 samples/sec Train-accuracy=0.922656
2016-05-03 17:15:51,489 Node[0] Epoch[54] Resetting Data Iterator
2016-05-03 17:15:51,489 Node[0] Epoch[54] Time cost=78.977
2016-05-03 17:15:51,648 Node[0] Saved checkpoint to "cifar10/resnet-0055.params"
2016-05-03 17:15:53,581 Node[0] Epoch[54] Validation-accuracy=0.845753
2016-05-03 17:16:03,762 Node[0] Epoch[55] Batch [50] Speed: 631.94 samples/sec Train-accuracy=0.928438
2016-05-03 17:16:13,890 Node[0] Epoch[55] Batch [100] Speed: 631.94 samples/sec Train-accuracy=0.927031
2016-05-03 17:16:24,020 Node[0] Epoch[55] Batch [150] Speed: 631.81 samples/sec Train-accuracy=0.927188
2016-05-03 17:16:34,145 Node[0] Epoch[55] Batch [200] Speed: 632.12 samples/sec Train-accuracy=0.915312
2016-05-03 17:16:44,247 Node[0] Epoch[55] Batch [250] Speed: 633.58 samples/sec Train-accuracy=0.924219
2016-05-03 17:16:54,318 Node[0] Epoch[55] Batch [300] Speed: 635.51 samples/sec Train-accuracy=0.924531
2016-05-03 17:17:04,430 Node[0] Epoch[55] Batch [350] Speed: 632.94 samples/sec Train-accuracy=0.927188
2016-05-03 17:17:12,535 Node[0] Epoch[55] Resetting Data Iterator
2016-05-03 17:17:12,536 Node[0] Epoch[55] Time cost=78.955
2016-05-03 17:17:12,696 Node[0] Saved checkpoint to "cifar10/resnet-0056.params"
2016-05-03 17:17:14,617 Node[0] Epoch[55] Validation-accuracy=0.851262
2016-05-03 17:17:24,745 Node[0] Epoch[56] Batch [50] Speed: 635.28 samples/sec Train-accuracy=0.925312
2016-05-03 17:17:34,884 Node[0] Epoch[56] Batch [100] Speed: 631.29 samples/sec Train-accuracy=0.922031
2016-05-03 17:17:45,019 Node[0] Epoch[56] Batch [150] Speed: 631.47 samples/sec Train-accuracy=0.923906
2016-05-03 17:17:55,106 Node[0] Epoch[56] Batch [200] Speed: 634.51 samples/sec Train-accuracy=0.918281
2016-05-03 17:18:05,204 Node[0] Epoch[56] Batch [250] Speed: 633.77 samples/sec Train-accuracy=0.920625
2016-05-03 17:18:15,344 Node[0] Epoch[56] Batch [300] Speed: 631.21 samples/sec Train-accuracy=0.927813
2016-05-03 17:18:25,441 Node[0] Epoch[56] Batch [350] Speed: 633.88 samples/sec Train-accuracy=0.924844
2016-05-03 17:18:33,755 Node[0] Epoch[56] Resetting Data Iterator
2016-05-03 17:18:33,755 Node[0] Epoch[56] Time cost=79.138
2016-05-03 17:18:33,914 Node[0] Saved checkpoint to "cifar10/resnet-0057.params"
2016-05-03 17:18:35,988 Node[0] Epoch[56] Validation-accuracy=0.856606
2016-05-03 17:18:46,154 Node[0] Epoch[57] Batch [50] Speed: 632.97 samples/sec Train-accuracy=0.920937
2016-05-03 17:18:56,315 Node[0] Epoch[57] Batch [100] Speed: 629.91 samples/sec Train-accuracy=0.927813
2016-05-03 17:19:06,406 Node[0] Epoch[57] Batch [150] Speed: 634.24 samples/sec Train-accuracy=0.929844
2016-05-03 17:19:16,519 Node[0] Epoch[57] Batch [200] Speed: 632.87 samples/sec Train-accuracy=0.923125
2016-05-03 17:19:26,636 Node[0] Epoch[57] Batch [250] Speed: 632.62 samples/sec Train-accuracy=0.917031
2016-05-03 17:19:36,732 Node[0] Epoch[57] Batch [300] Speed: 633.92 samples/sec Train-accuracy=0.921562
2016-05-03 17:19:46,894 Node[0] Epoch[57] Batch [350] Speed: 629.83 samples/sec Train-accuracy=0.922813
2016-05-03 17:19:55,172 Node[0] Epoch[57] Resetting Data Iterator
2016-05-03 17:19:55,173 Node[0] Epoch[57] Time cost=79.184
2016-05-03 17:19:55,331 Node[0] Saved checkpoint to "cifar10/resnet-0058.params"
2016-05-03 17:19:57,234 Node[0] Epoch[57] Validation-accuracy=0.847556
2016-05-03 17:20:07,320 Node[0] Epoch[58] Batch [50] Speed: 638.01 samples/sec Train-accuracy=0.923594
2016-05-03 17:20:17,447 Node[0] Epoch[58] Batch [100] Speed: 631.98 samples/sec Train-accuracy=0.925000
2016-05-03 17:20:27,613 Node[0] Epoch[58] Batch [150] Speed: 629.54 samples/sec Train-accuracy=0.927344
2016-05-03 17:20:37,730 Node[0] Epoch[58] Batch [200] Speed: 632.63 samples/sec Train-accuracy=0.922344
2016-05-03 17:20:47,851 Node[0] Epoch[58] Batch [250] Speed: 632.34 samples/sec Train-accuracy=0.920156
2016-05-03 17:20:57,981 Node[0] Epoch[58] Batch [300] Speed: 631.80 samples/sec Train-accuracy=0.924844
2016-05-03 17:21:08,118 Node[0] Epoch[58] Batch [350] Speed: 631.40 samples/sec Train-accuracy=0.924375
2016-05-03 17:21:16,195 Node[0] Epoch[58] Resetting Data Iterator
2016-05-03 17:21:16,195 Node[0] Epoch[58] Time cost=78.960
2016-05-03 17:21:16,353 Node[0] Saved checkpoint to "cifar10/resnet-0059.params"
2016-05-03 17:21:18,275 Node[0] Epoch[58] Validation-accuracy=0.841446
2016-05-03 17:21:28,374 Node[0] Epoch[59] Batch [50] Speed: 637.09 samples/sec Train-accuracy=0.918438
2016-05-03 17:21:38,497 Node[0] Epoch[59] Batch [100] Speed: 632.23 samples/sec Train-accuracy=0.922813
2016-05-03 17:21:48,628 Node[0] Epoch[59] Batch [150] Speed: 631.71 samples/sec Train-accuracy=0.929219
2016-05-03 17:21:58,764 Node[0] Epoch[59] Batch [200] Speed: 631.45 samples/sec Train-accuracy=0.928281
2016-05-03 17:22:08,830 Node[0] Epoch[59] Batch [250] Speed: 635.82 samples/sec Train-accuracy=0.919531
2016-05-03 17:22:18,918 Node[0] Epoch[59] Batch [300] Speed: 634.44 samples/sec Train-accuracy=0.926875
2016-05-03 17:22:29,042 Node[0] Epoch[59] Batch [350] Speed: 632.16 samples/sec Train-accuracy=0.924219
2016-05-03 17:22:37,327 Node[0] Epoch[59] Resetting Data Iterator
2016-05-03 17:22:37,327 Node[0] Epoch[59] Time cost=79.052
2016-05-03 17:22:37,485 Node[0] Saved checkpoint to "cifar10/resnet-0060.params"
2016-05-03 17:22:39,397 Node[0] Epoch[59] Validation-accuracy=0.820613
2016-05-03 17:22:49,531 Node[0] Epoch[60] Batch [50] Speed: 634.85 samples/sec Train-accuracy=0.927656
2016-05-03 17:22:59,701 Node[0] Epoch[60] Batch [100] Speed: 629.32 samples/sec Train-accuracy=0.930000
2016-05-03 17:23:09,802 Node[0] Epoch[60] Batch [150] Speed: 633.62 samples/sec Train-accuracy=0.924375
2016-05-03 17:23:19,865 Node[0] Epoch[60] Batch [200] Speed: 636.00 samples/sec Train-accuracy=0.923125
2016-05-03 17:23:29,987 Node[0] Epoch[60] Batch [250] Speed: 632.31 samples/sec Train-accuracy=0.927656
2016-05-03 17:23:40,084 Node[0] Epoch[60] Batch [300] Speed: 633.85 samples/sec Train-accuracy=0.923750
2016-05-03 17:23:50,183 Node[0] Epoch[60] Batch [350] Speed: 633.76 samples/sec Train-accuracy=0.930312
2016-05-03 17:23:58,440 Node[0] Epoch[60] Resetting Data Iterator
2016-05-03 17:23:58,440 Node[0] Epoch[60] Time cost=79.043
2016-05-03 17:23:58,599 Node[0] Saved checkpoint to "cifar10/resnet-0061.params"
2016-05-03 17:24:00,491 Node[0] Epoch[60] Validation-accuracy=0.833734
2016-05-03 17:24:10,632 Node[0] Epoch[61] Batch [50] Speed: 634.50 samples/sec Train-accuracy=0.929063
2016-05-03 17:24:20,757 Node[0] Epoch[61] Batch [100] Speed: 632.10 samples/sec Train-accuracy=0.922188
2016-05-03 17:24:30,835 Node[0] Epoch[61] Batch [150] Speed: 635.07 samples/sec Train-accuracy=0.927969
2016-05-03 17:24:40,926 Node[0] Epoch[61] Batch [200] Speed: 634.26 samples/sec Train-accuracy=0.924687
2016-05-03 17:24:51,008 Node[0] Epoch[61] Batch [250] Speed: 634.82 samples/sec Train-accuracy=0.917500
2016-05-03 17:25:01,097 Node[0] Epoch[61] Batch [300] Speed: 634.38 samples/sec Train-accuracy=0.925469
2016-05-03 17:25:11,174 Node[0] Epoch[61] Batch [350] Speed: 635.12 samples/sec Train-accuracy=0.928906
2016-05-03 17:25:19,255 Node[0] Epoch[61] Resetting Data Iterator
2016-05-03 17:25:19,255 Node[0] Epoch[61] Time cost=78.764
2016-05-03 17:25:19,420 Node[0] Saved checkpoint to "cifar10/resnet-0062.params"
2016-05-03 17:25:21,369 Node[0] Epoch[61] Validation-accuracy=0.840244
2016-05-03 17:25:31,482 Node[0] Epoch[62] Batch [50] Speed: 636.23 samples/sec Train-accuracy=0.923125
2016-05-03 17:25:41,652 Node[0] Epoch[62] Batch [100] Speed: 629.32 samples/sec Train-accuracy=0.926406
2016-05-03 17:25:51,740 Node[0] Epoch[62] Batch [150] Speed: 634.43 samples/sec Train-accuracy=0.926406
2016-05-03 17:26:01,850 Node[0] Epoch[62] Batch [200] Speed: 633.11 samples/sec Train-accuracy=0.923750
2016-05-03 17:26:12,015 Node[0] Epoch[62] Batch [250] Speed: 629.59 samples/sec Train-accuracy=0.924375
2016-05-03 17:26:22,080 Node[0] Epoch[62] Batch [300] Speed: 635.91 samples/sec Train-accuracy=0.934531
2016-05-03 17:26:32,220 Node[0] Epoch[62] Batch [350] Speed: 631.17 samples/sec Train-accuracy=0.926250
2016-05-03 17:26:40,526 Node[0] Epoch[62] Resetting Data Iterator
2016-05-03 17:26:40,526 Node[0] Epoch[62] Time cost=79.157
2016-05-03 17:26:40,687 Node[0] Saved checkpoint to "cifar10/resnet-0063.params"
2016-05-03 17:26:42,615 Node[0] Epoch[62] Validation-accuracy=0.847857
2016-05-03 17:26:52,793 Node[0] Epoch[63] Batch [50] Speed: 632.13 samples/sec Train-accuracy=0.925000
2016-05-03 17:27:02,915 Node[0] Epoch[63] Batch [100] Speed: 632.33 samples/sec Train-accuracy=0.935312
2016-05-03 17:27:13,000 Node[0] Epoch[63] Batch [150] Speed: 634.64 samples/sec Train-accuracy=0.925000
2016-05-03 17:27:23,074 Node[0] Epoch[63] Batch [200] Speed: 635.28 samples/sec Train-accuracy=0.921406
2016-05-03 17:27:33,152 Node[0] Epoch[63] Batch [250] Speed: 635.08 samples/sec Train-accuracy=0.928125
2016-05-03 17:27:43,281 Node[0] Epoch[63] Batch [300] Speed: 631.88 samples/sec Train-accuracy=0.929375
2016-05-03 17:27:53,387 Node[0] Epoch[63] Batch [350] Speed: 633.30 samples/sec Train-accuracy=0.931406
2016-05-03 17:28:01,466 Node[0] Epoch[63] Resetting Data Iterator
2016-05-03 17:28:01,466 Node[0] Epoch[63] Time cost=78.850
2016-05-03 17:28:01,622 Node[0] Saved checkpoint to "cifar10/resnet-0064.params"
2016-05-03 17:28:03,537 Node[0] Epoch[63] Validation-accuracy=0.846755
2016-05-03 17:28:13,734 Node[0] Epoch[64] Batch [50] Speed: 631.06 samples/sec Train-accuracy=0.922344
2016-05-03 17:28:23,906 Node[0] Epoch[64] Batch [100] Speed: 629.20 samples/sec Train-accuracy=0.927813
2016-05-03 17:28:34,019 Node[0] Epoch[64] Batch [150] Speed: 632.83 samples/sec Train-accuracy=0.930000
2016-05-03 17:28:44,049 Node[0] Epoch[64] Batch [200] Speed: 638.12 samples/sec Train-accuracy=0.921875
2016-05-03 17:28:54,051 Node[0] Epoch[64] Batch [250] Speed: 639.91 samples/sec Train-accuracy=0.925469
2016-05-03 17:29:04,176 Node[0] Epoch[64] Batch [300] Speed: 632.10 samples/sec Train-accuracy=0.931094
2016-05-03 17:29:14,309 Node[0] Epoch[64] Batch [350] Speed: 631.65 samples/sec Train-accuracy=0.920469
2016-05-03 17:29:22,558 Node[0] Epoch[64] Resetting Data Iterator
2016-05-03 17:29:22,558 Node[0] Epoch[64] Time cost=79.020
2016-05-03 17:29:22,714 Node[0] Saved checkpoint to "cifar10/resnet-0065.params"
2016-05-03 17:29:24,838 Node[0] Epoch[64] Validation-accuracy=0.841970
2016-05-03 17:29:34,931 Node[0] Epoch[65] Batch [50] Speed: 637.43 samples/sec Train-accuracy=0.930156
2016-05-03 17:29:45,007 Node[0] Epoch[65] Batch [100] Speed: 635.18 samples/sec Train-accuracy=0.931406
2016-05-03 17:29:55,064 Node[0] Epoch[65] Batch [150] Speed: 636.38 samples/sec Train-accuracy=0.932344
2016-05-03 17:30:05,113 Node[0] Epoch[65] Batch [200] Speed: 636.94 samples/sec Train-accuracy=0.928281
2016-05-03 17:30:15,161 Node[0] Epoch[65] Batch [250] Speed: 636.94 samples/sec Train-accuracy=0.923438
2016-05-03 17:30:25,230 Node[0] Epoch[65] Batch [300] Speed: 635.63 samples/sec Train-accuracy=0.927813
2016-05-03 17:30:35,313 Node[0] Epoch[65] Batch [350] Speed: 634.74 samples/sec Train-accuracy=0.925781
2016-05-03 17:30:43,561 Node[0] Epoch[65] Resetting Data Iterator
2016-05-03 17:30:43,562 Node[0] Epoch[65] Time cost=78.723
2016-05-03 17:30:43,720 Node[0] Saved checkpoint to "cifar10/resnet-0066.params"
2016-05-03 17:30:45,619 Node[0] Epoch[65] Validation-accuracy=0.853666
2016-05-03 17:30:55,676 Node[0] Epoch[66] Batch [50] Speed: 639.80 samples/sec Train-accuracy=0.930937
2016-05-03 17:31:05,772 Node[0] Epoch[66] Batch [100] Speed: 633.92 samples/sec Train-accuracy=0.933750
2016-05-03 17:31:15,816 Node[0] Epoch[66] Batch [150] Speed: 637.26 samples/sec Train-accuracy=0.934531
2016-05-03 17:31:25,871 Node[0] Epoch[66] Batch [200] Speed: 636.49 samples/sec Train-accuracy=0.928906
2016-05-03 17:31:35,917 Node[0] Epoch[66] Batch [250] Speed: 637.08 samples/sec Train-accuracy=0.930937
2016-05-03 17:31:45,947 Node[0] Epoch[66] Batch [300] Speed: 638.13 samples/sec Train-accuracy=0.923594
2016-05-03 17:31:56,033 Node[0] Epoch[66] Batch [350] Speed: 634.54 samples/sec Train-accuracy=0.927656
2016-05-03 17:32:04,113 Node[0] Epoch[66] Resetting Data Iterator
2016-05-03 17:32:04,114 Node[0] Epoch[66] Time cost=78.495
2016-05-03 17:32:04,271 Node[0] Saved checkpoint to "cifar10/resnet-0067.params"
2016-05-03 17:32:06,200 Node[0] Epoch[66] Validation-accuracy=0.866587
2016-05-03 17:32:16,270 Node[0] Epoch[67] Batch [50] Speed: 638.98 samples/sec Train-accuracy=0.931562
2016-05-03 17:32:26,311 Node[0] Epoch[67] Batch [100] Speed: 637.39 samples/sec Train-accuracy=0.923438
2016-05-03 17:32:36,312 Node[0] Epoch[67] Batch [150] Speed: 639.96 samples/sec Train-accuracy=0.929063
2016-05-03 17:32:46,331 Node[0] Epoch[67] Batch [200] Speed: 638.76 samples/sec Train-accuracy=0.924687
2016-05-03 17:33:01,756 Node[0] start with arguments Namespace(batch_size=128, data_dir='cifar10/', gpus='0', kv_store='local', load_epoch=None, log_dir='cifar10', log_file='log', lr=0.1, model_prefix=None, num_epochs=200, num_examples=50000, save_model_prefix='cifar10/resnet')
2016-05-03 17:33:02,143 Node[0] Start training with [gpu(0)]
2016-05-03 17:33:23,058 Node[0] Epoch[0] Batch [50] Speed: 655.92 samples/sec Train-accuracy=0.099844
2016-05-03 17:33:32,960 Node[0] Epoch[0] Batch [100] Speed: 646.32 samples/sec Train-accuracy=0.108594
2016-05-03 17:33:42,859 Node[0] Epoch[0] Batch [150] Speed: 646.57 samples/sec Train-accuracy=0.112656
2016-05-03 17:33:52,891 Node[0] Epoch[0] Batch [200] Speed: 637.94 samples/sec Train-accuracy=0.154062
2016-05-03 17:34:03,398 Node[0] Epoch[0] Batch [250] Speed: 609.14 samples/sec Train-accuracy=0.184219
2016-05-03 17:34:14,030 Node[0] Epoch[0] Batch [300] Speed: 601.96 samples/sec Train-accuracy=0.250937
2016-05-03 17:34:24,598 Node[0] Epoch[0] Batch [350] Speed: 605.63 samples/sec Train-accuracy=0.299531
2016-05-03 17:34:33,271 Node[0] Epoch[0] Resetting Data Iterator
2016-05-03 17:34:33,271 Node[0] Epoch[0] Time cost=80.247
2016-05-03 17:34:33,438 Node[0] Saved checkpoint to "cifar10/resnet-0001.params"
2016-05-03 17:34:35,638 Node[0] Epoch[0] Validation-accuracy=0.338113
2016-05-03 17:34:46,058 Node[0] Epoch[1] Batch [50] Speed: 617.44 samples/sec Train-accuracy=0.351875
2016-05-03 17:34:56,460 Node[0] Epoch[1] Batch [100] Speed: 615.31 samples/sec Train-accuracy=0.388281
2016-05-03 17:35:06,895 Node[0] Epoch[1] Batch [150] Speed: 613.31 samples/sec Train-accuracy=0.416094
2016-05-03 17:35:17,302 Node[0] Epoch[1] Batch [200] Speed: 615.01 samples/sec Train-accuracy=0.435156
2016-05-03 17:35:27,657 Node[0] Epoch[1] Batch [250] Speed: 618.08 samples/sec Train-accuracy=0.455000
2016-05-03 17:35:38,036 Node[0] Epoch[1] Batch [300] Speed: 616.63 samples/sec Train-accuracy=0.478594
2016-05-03 17:35:48,305 Node[0] Epoch[1] Batch [350] Speed: 623.26 samples/sec Train-accuracy=0.501719
2016-05-03 17:35:56,717 Node[0] Epoch[1] Resetting Data Iterator
2016-05-03 17:35:56,717 Node[0] Epoch[1] Time cost=81.079
2016-05-03 17:35:56,879 Node[0] Saved checkpoint to "cifar10/resnet-0002.params"
2016-05-03 17:35:58,858 Node[0] Epoch[1] Validation-accuracy=0.387420
2016-05-03 17:36:09,183 Node[0] Epoch[2] Batch [50] Speed: 623.15 samples/sec Train-accuracy=0.533125
2016-05-03 17:36:19,500 Node[0] Epoch[2] Batch [100] Speed: 620.36 samples/sec Train-accuracy=0.552344
2016-05-03 17:36:29,777 Node[0] Epoch[2] Batch [150] Speed: 622.76 samples/sec Train-accuracy=0.561562
2016-05-03 17:36:40,070 Node[0] Epoch[2] Batch [200] Speed: 621.82 samples/sec Train-accuracy=0.572187
2016-05-03 17:36:50,372 Node[0] Epoch[2] Batch [250] Speed: 621.24 samples/sec Train-accuracy=0.578125
2016-05-03 17:37:00,647 Node[0] Epoch[2] Batch [300] Speed: 622.92 samples/sec Train-accuracy=0.575000
2016-05-03 17:37:10,902 Node[0] Epoch[2] Batch [350] Speed: 624.10 samples/sec Train-accuracy=0.591250
2016-05-03 17:37:19,092 Node[0] Epoch[2] Resetting Data Iterator
2016-05-03 17:37:19,093 Node[0] Epoch[2] Time cost=80.234
2016-05-03 17:37:19,254 Node[0] Saved checkpoint to "cifar10/resnet-0003.params"
2016-05-03 17:37:21,129 Node[0] Epoch[2] Validation-accuracy=0.512119
2016-05-03 17:37:31,168 Node[0] Epoch[3] Batch [50] Speed: 641.01 samples/sec Train-accuracy=0.606094
2016-05-03 17:37:41,309 Node[0] Epoch[3] Batch [100] Speed: 631.16 samples/sec Train-accuracy=0.624687
2016-05-03 17:37:51,508 Node[0] Epoch[3] Batch [150] Speed: 627.51 samples/sec Train-accuracy=0.638906
2016-05-03 17:38:01,671 Node[0] Epoch[3] Batch [200] Speed: 629.78 samples/sec Train-accuracy=0.635469
2016-05-03 17:38:11,791 Node[0] Epoch[3] Batch [250] Speed: 632.42 samples/sec Train-accuracy=0.634062
2016-05-03 17:38:21,921 Node[0] Epoch[3] Batch [300] Speed: 631.77 samples/sec Train-accuracy=0.647031
2016-05-03 17:38:32,085 Node[0] Epoch[3] Batch [350] Speed: 629.69 samples/sec Train-accuracy=0.643281
2016-05-03 17:38:40,407 Node[0] Epoch[3] Resetting Data Iterator
2016-05-03 17:38:40,407 Node[0] Epoch[3] Time cost=79.278
2016-05-03 17:38:40,563 Node[0] Saved checkpoint to "cifar10/resnet-0004.params"
2016-05-03 17:38:42,467 Node[0] Epoch[3] Validation-accuracy=0.628005
2016-05-03 17:38:52,684 Node[0] Epoch[4] Batch [50] Speed: 629.79 samples/sec Train-accuracy=0.657344
2016-05-03 17:39:02,815 Node[0] Epoch[4] Batch [100] Speed: 631.68 samples/sec Train-accuracy=0.666094
2016-05-03 17:39:12,962 Node[0] Epoch[4] Batch [150] Speed: 630.75 samples/sec Train-accuracy=0.684375
2016-05-03 17:39:23,136 Node[0] Epoch[4] Batch [200] Speed: 629.11 samples/sec Train-accuracy=0.674844
2016-05-03 17:39:33,288 Node[0] Epoch[4] Batch [250] Speed: 630.43 samples/sec Train-accuracy=0.679844
2016-05-03 17:39:43,412 Node[0] Epoch[4] Batch [300] Speed: 632.14 samples/sec Train-accuracy=0.678906
2016-05-03 17:39:53,482 Node[0] Epoch[4] Batch [350] Speed: 635.58 samples/sec Train-accuracy=0.692187
2016-05-03 17:40:01,759 Node[0] Epoch[4] Resetting Data Iterator
2016-05-03 17:40:01,759 Node[0] Epoch[4] Time cost=79.292
2016-05-03 17:40:01,918 Node[0] Saved checkpoint to "cifar10/resnet-0005.params"
2016-05-03 17:40:03,805 Node[0] Epoch[4] Validation-accuracy=0.663161
2016-05-03 17:40:14,048 Node[0] Epoch[5] Batch [50] Speed: 628.08 samples/sec Train-accuracy=0.692344
2016-05-03 17:40:24,200 Node[0] Epoch[5] Batch [100] Speed: 630.44 samples/sec Train-accuracy=0.701875
2016-05-03 17:40:34,362 Node[0] Epoch[5] Batch [150] Speed: 629.81 samples/sec Train-accuracy=0.714063
2016-05-03 17:40:44,485 Node[0] Epoch[5] Batch [200] Speed: 632.26 samples/sec Train-accuracy=0.714844
2016-05-03 17:40:54,650 Node[0] Epoch[5] Batch [250] Speed: 629.60 samples/sec Train-accuracy=0.710781
2016-05-03 17:41:04,762 Node[0] Epoch[5] Batch [300] Speed: 632.94 samples/sec Train-accuracy=0.718594
2016-05-03 17:41:14,835 Node[0] Epoch[5] Batch [350] Speed: 635.40 samples/sec Train-accuracy=0.718906
2016-05-03 17:41:22,934 Node[0] Epoch[5] Resetting Data Iterator
2016-05-03 17:41:22,935 Node[0] Epoch[5] Time cost=79.130
2016-05-03 17:41:23,091 Node[0] Saved checkpoint to "cifar10/resnet-0006.params"
2016-05-03 17:41:24,952 Node[0] Epoch[5] Validation-accuracy=0.697316
2016-05-03 17:41:35,101 Node[0] Epoch[6] Batch [50] Speed: 633.86 samples/sec Train-accuracy=0.728125
2016-05-03 17:41:45,215 Node[0] Epoch[6] Batch [100] Speed: 632.76 samples/sec Train-accuracy=0.737500
2016-05-03 17:41:55,272 Node[0] Epoch[6] Batch [150] Speed: 636.45 samples/sec Train-accuracy=0.755156
2016-05-03 17:42:05,276 Node[0] Epoch[6] Batch [200] Speed: 639.72 samples/sec Train-accuracy=0.740938
2016-05-03 17:42:15,314 Node[0] Epoch[6] Batch [250] Speed: 637.60 samples/sec Train-accuracy=0.738750
2016-05-03 17:42:25,437 Node[0] Epoch[6] Batch [300] Speed: 632.25 samples/sec Train-accuracy=0.754844
2016-05-03 17:42:35,590 Node[0] Epoch[6] Batch [350] Speed: 630.40 samples/sec Train-accuracy=0.760312
2016-05-03 17:42:43,888 Node[0] Epoch[6] Resetting Data Iterator
2016-05-03 17:42:43,888 Node[0] Epoch[6] Time cost=78.936
2016-05-03 17:42:44,043 Node[0] Saved checkpoint to "cifar10/resnet-0007.params"
2016-05-03 17:42:45,920 Node[0] Epoch[6] Validation-accuracy=0.703826
2016-05-03 17:42:55,967 Node[0] Epoch[7] Batch [50] Speed: 640.34 samples/sec Train-accuracy=0.757188
2016-05-03 17:43:06,082 Node[0] Epoch[7] Batch [100] Speed: 632.73 samples/sec Train-accuracy=0.767813
2016-05-03 17:43:16,188 Node[0] Epoch[7] Batch [150] Speed: 633.27 samples/sec Train-accuracy=0.773281
2016-05-03 17:43:26,303 Node[0] Epoch[7] Batch [200] Speed: 632.76 samples/sec Train-accuracy=0.766094
2016-05-03 17:43:36,414 Node[0] Epoch[7] Batch [250] Speed: 633.01 samples/sec Train-accuracy=0.771094
2016-05-03 17:43:46,488 Node[0] Epoch[7] Batch [300] Speed: 635.31 samples/sec Train-accuracy=0.779531
2016-05-03 17:43:56,577 Node[0] Epoch[7] Batch [350] Speed: 634.36 samples/sec Train-accuracy=0.776094
2016-05-03 17:44:04,714 Node[0] Epoch[7] Resetting Data Iterator
2016-05-03 17:44:04,715 Node[0] Epoch[7] Time cost=78.794
2016-05-03 17:44:04,874 Node[0] Saved checkpoint to "cifar10/resnet-0008.params"
2016-05-03 17:44:06,775 Node[0] Epoch[7] Validation-accuracy=0.761819
2016-05-03 17:44:16,881 Node[0] Epoch[8] Batch [50] Speed: 636.62 samples/sec Train-accuracy=0.777500
2016-05-03 17:44:27,026 Node[0] Epoch[8] Batch [100] Speed: 630.91 samples/sec Train-accuracy=0.780312
2016-05-03 17:44:37,123 Node[0] Epoch[8] Batch [150] Speed: 633.85 samples/sec Train-accuracy=0.796562
2016-05-03 17:44:47,240 Node[0] Epoch[8] Batch [200] Speed: 632.60 samples/sec Train-accuracy=0.782188
2016-05-03 17:44:57,352 Node[0] Epoch[8] Batch [250] Speed: 632.97 samples/sec Train-accuracy=0.783125
2016-05-03 17:45:07,475 Node[0] Epoch[8] Batch [300] Speed: 632.24 samples/sec Train-accuracy=0.790469
2016-05-03 17:45:17,607 Node[0] Epoch[8] Batch [350] Speed: 631.63 samples/sec Train-accuracy=0.792031
2016-05-03 17:45:25,891 Node[0] Epoch[8] Resetting Data Iterator
2016-05-03 17:45:25,891 Node[0] Epoch[8] Time cost=79.116
2016-05-03 17:45:26,053 Node[0] Saved checkpoint to "cifar10/resnet-0009.params"
2016-05-03 17:45:28,138 Node[0] Epoch[8] Validation-accuracy=0.734474
2016-05-03 17:45:38,210 Node[0] Epoch[9] Batch [50] Speed: 638.84 samples/sec Train-accuracy=0.790625
2016-05-03 17:45:48,343 Node[0] Epoch[9] Batch [100] Speed: 631.62 samples/sec Train-accuracy=0.796406
2016-05-03 17:45:58,386 Node[0] Epoch[9] Batch [150] Speed: 637.26 samples/sec Train-accuracy=0.801562
2016-05-03 17:46:08,457 Node[0] Epoch[9] Batch [200] Speed: 635.53 samples/sec Train-accuracy=0.789062
2016-05-03 17:46:18,583 Node[0] Epoch[9] Batch [250] Speed: 632.02 samples/sec Train-accuracy=0.794063
2016-05-03 17:46:28,688 Node[0] Epoch[9] Batch [300] Speed: 633.38 samples/sec Train-accuracy=0.805625
2016-05-03 17:46:38,842 Node[0] Epoch[9] Batch [350] Speed: 630.34 samples/sec Train-accuracy=0.794531
2016-05-03 17:46:47,148 Node[0] Epoch[9] Resetting Data Iterator
2016-05-03 17:46:47,148 Node[0] Epoch[9] Time cost=79.010
2016-05-03 17:46:47,309 Node[0] Saved checkpoint to "cifar10/resnet-0010.params"
2016-05-03 17:46:49,175 Node[0] Epoch[9] Validation-accuracy=0.781050
2016-05-03 17:46:59,283 Node[0] Epoch[10] Batch [50] Speed: 636.52 samples/sec Train-accuracy=0.804688
2016-05-03 17:47:09,400 Node[0] Epoch[10] Batch [100] Speed: 632.59 samples/sec Train-accuracy=0.801094
2016-05-03 17:47:19,477 Node[0] Epoch[10] Batch [150] Speed: 635.12 samples/sec Train-accuracy=0.812813
2016-05-03 17:47:29,502 Node[0] Epoch[10] Batch [200] Speed: 638.42 samples/sec Train-accuracy=0.804063
2016-05-03 17:47:39,545 Node[0] Epoch[10] Batch [250] Speed: 637.28 samples/sec Train-accuracy=0.805469
2016-05-03 17:47:49,616 Node[0] Epoch[10] Batch [300] Speed: 635.51 samples/sec Train-accuracy=0.812031
2016-05-03 17:47:59,713 Node[0] Epoch[10] Batch [350] Speed: 633.85 samples/sec Train-accuracy=0.805781
2016-05-03 17:48:07,776 Node[0] Epoch[10] Resetting Data Iterator
2016-05-03 17:48:07,776 Node[0] Epoch[10] Time cost=78.601
2016-05-03 17:48:07,930 Node[0] Saved checkpoint to "cifar10/resnet-0011.params"
2016-05-03 17:48:09,809 Node[0] Epoch[10] Validation-accuracy=0.761018
2016-05-03 17:48:19,899 Node[0] Epoch[11] Batch [50] Speed: 637.75 samples/sec Train-accuracy=0.810312
2016-05-03 17:48:30,006 Node[0] Epoch[11] Batch [100] Speed: 633.28 samples/sec Train-accuracy=0.816562
2016-05-03 17:48:40,098 Node[0] Epoch[11] Batch [150] Speed: 634.18 samples/sec Train-accuracy=0.816875
2016-05-03 17:48:50,201 Node[0] Epoch[11] Batch [200] Speed: 633.44 samples/sec Train-accuracy=0.811562
2016-05-03 17:49:00,268 Node[0] Epoch[11] Batch [250] Speed: 635.76 samples/sec Train-accuracy=0.814219
2016-05-03 17:49:10,346 Node[0] Epoch[11] Batch [300] Speed: 635.07 samples/sec Train-accuracy=0.815781
2016-05-03 17:49:20,365 Node[0] Epoch[11] Batch [350] Speed: 638.83 samples/sec Train-accuracy=0.823281
2016-05-03 17:49:28,583 Node[0] Epoch[11] Resetting Data Iterator
2016-05-03 17:49:28,584 Node[0] Epoch[11] Time cost=78.774
2016-05-03 17:49:28,743 Node[0] Saved checkpoint to "cifar10/resnet-0012.params"
2016-05-03 17:49:30,666 Node[0] Epoch[11] Validation-accuracy=0.791166
2016-05-03 17:49:40,723 Node[0] Epoch[12] Batch [50] Speed: 639.78 samples/sec Train-accuracy=0.818750
2016-05-03 17:49:50,858 Node[0] Epoch[12] Batch [100] Speed: 631.49 samples/sec Train-accuracy=0.823750
2016-05-03 17:50:00,968 Node[0] Epoch[12] Batch [150] Speed: 633.04 samples/sec Train-accuracy=0.825313
2016-05-03 17:50:10,988 Node[0] Epoch[12] Batch [200] Speed: 638.77 samples/sec Train-accuracy=0.818594
2016-05-03 17:50:21,004 Node[0] Epoch[12] Batch [250] Speed: 638.99 samples/sec Train-accuracy=0.824219
2016-05-03 17:50:31,033 Node[0] Epoch[12] Batch [300] Speed: 638.15 samples/sec Train-accuracy=0.833750
2016-05-03 17:50:41,069 Node[0] Epoch[12] Batch [350] Speed: 637.72 samples/sec Train-accuracy=0.819531
2016-05-03 17:50:49,275 Node[0] Epoch[12] Resetting Data Iterator
2016-05-03 17:50:49,276 Node[0] Epoch[12] Time cost=78.610
2016-05-03 17:50:49,434 Node[0] Saved checkpoint to "cifar10/resnet-0013.params"
2016-05-03 17:50:51,295 Node[0] Epoch[12] Validation-accuracy=0.795072
2016-05-03 17:51:01,360 Node[0] Epoch[13] Batch [50] Speed: 639.27 samples/sec Train-accuracy=0.828750
2016-05-03 17:51:11,468 Node[0] Epoch[13] Batch [100] Speed: 633.19 samples/sec Train-accuracy=0.833125
2016-05-03 17:51:21,465 Node[0] Epoch[13] Batch [150] Speed: 640.20 samples/sec Train-accuracy=0.837187
2016-05-03 17:51:31,518 Node[0] Epoch[13] Batch [200] Speed: 636.66 samples/sec Train-accuracy=0.825781
2016-05-03 17:51:41,510 Node[0] Epoch[13] Batch [250] Speed: 640.51 samples/sec Train-accuracy=0.828281
2016-05-03 17:51:51,579 Node[0] Epoch[13] Batch [300] Speed: 635.65 samples/sec Train-accuracy=0.829375
2016-05-03 17:52:01,649 Node[0] Epoch[13] Batch [350] Speed: 635.55 samples/sec Train-accuracy=0.823750
2016-05-03 17:52:09,682 Node[0] Epoch[13] Resetting Data Iterator
2016-05-03 17:52:09,682 Node[0] Epoch[13] Time cost=78.387
2016-05-03 17:52:09,840 Node[0] Saved checkpoint to "cifar10/resnet-0014.params"
2016-05-03 17:52:11,682 Node[0] Epoch[13] Validation-accuracy=0.765325
2016-05-03 17:52:21,740 Node[0] Epoch[14] Batch [50] Speed: 639.64 samples/sec Train-accuracy=0.841406
2016-05-03 17:52:31,866 Node[0] Epoch[14] Batch [100] Speed: 632.06 samples/sec Train-accuracy=0.833438
2016-05-03 17:52:41,913 Node[0] Epoch[14] Batch [150] Speed: 637.00 samples/sec Train-accuracy=0.845469
2016-05-03 17:52:51,961 Node[0] Epoch[14] Batch [200] Speed: 636.97 samples/sec Train-accuracy=0.837500
2016-05-03 17:53:02,011 Node[0] Epoch[14] Batch [250] Speed: 636.83 samples/sec Train-accuracy=0.831562
2016-05-03 17:53:12,069 Node[0] Epoch[14] Batch [300] Speed: 636.28 samples/sec Train-accuracy=0.835156
2016-05-03 17:53:22,183 Node[0] Epoch[14] Batch [350] Speed: 632.81 samples/sec Train-accuracy=0.842344
2016-05-03 17:53:30,438 Node[0] Epoch[14] Resetting Data Iterator
2016-05-03 17:53:30,438 Node[0] Epoch[14] Time cost=78.756
2016-05-03 17:53:30,595 Node[0] Saved checkpoint to "cifar10/resnet-0015.params"
2016-05-03 17:53:32,488 Node[0] Epoch[14] Validation-accuracy=0.794071
2016-05-03 17:53:42,549 Node[0] Epoch[15] Batch [50] Speed: 639.53 samples/sec Train-accuracy=0.841719
2016-05-03 17:53:52,647 Node[0] Epoch[15] Batch [100] Speed: 633.79 samples/sec Train-accuracy=0.845781
2016-05-03 17:54:02,693 Node[0] Epoch[15] Batch [150] Speed: 637.13 samples/sec Train-accuracy=0.846719
2016-05-03 17:54:12,713 Node[0] Epoch[15] Batch [200] Speed: 638.69 samples/sec Train-accuracy=0.835000
2016-05-03 17:54:22,721 Node[0] Epoch[15] Batch [250] Speed: 639.56 samples/sec Train-accuracy=0.837969
2016-05-03 17:54:32,834 Node[0] Epoch[15] Batch [300] Speed: 632.80 samples/sec Train-accuracy=0.851875
2016-05-03 17:54:42,901 Node[0] Epoch[15] Batch [350] Speed: 635.80 samples/sec Train-accuracy=0.851875
2016-05-03 17:54:50,941 Node[0] Epoch[15] Resetting Data Iterator
2016-05-03 17:54:50,942 Node[0] Epoch[15] Time cost=78.454
2016-05-03 17:54:51,101 Node[0] Saved checkpoint to "cifar10/resnet-0016.params"
2016-05-03 17:54:52,978 Node[0] Epoch[15] Validation-accuracy=0.799079
2016-05-03 17:55:03,046 Node[0] Epoch[16] Batch [50] Speed: 639.10 samples/sec Train-accuracy=0.846875
2016-05-03 17:55:13,179 Node[0] Epoch[16] Batch [100] Speed: 631.65 samples/sec Train-accuracy=0.856719
2016-05-03 17:55:23,287 Node[0] Epoch[16] Batch [150] Speed: 633.15 samples/sec Train-accuracy=0.856094
2016-05-03 17:55:33,409 Node[0] Epoch[16] Batch [200] Speed: 632.32 samples/sec Train-accuracy=0.847812
2016-05-03 17:55:43,462 Node[0] Epoch[16] Batch [250] Speed: 636.60 samples/sec Train-accuracy=0.843906
2016-05-03 17:55:53,530 Node[0] Epoch[16] Batch [300] Speed: 635.74 samples/sec Train-accuracy=0.850156
2016-05-03 17:56:03,616 Node[0] Epoch[16] Batch [350] Speed: 634.56 samples/sec Train-accuracy=0.849375
2016-05-03 17:56:11,870 Node[0] Epoch[16] Resetting Data Iterator
2016-05-03 17:56:11,871 Node[0] Epoch[16] Time cost=78.892
2016-05-03 17:56:12,030 Node[0] Saved checkpoint to "cifar10/resnet-0017.params"
2016-05-03 17:56:14,143 Node[0] Epoch[16] Validation-accuracy=0.756428
2016-05-03 17:56:24,291 Node[0] Epoch[17] Batch [50] Speed: 633.94 samples/sec Train-accuracy=0.844688
2016-05-03 17:56:34,319 Node[0] Epoch[17] Batch [100] Speed: 638.26 samples/sec Train-accuracy=0.852969
2016-05-03 17:56:44,360 Node[0] Epoch[17] Batch [150] Speed: 637.37 samples/sec Train-accuracy=0.858125
2016-05-03 17:56:54,480 Node[0] Epoch[17] Batch [200] Speed: 632.46 samples/sec Train-accuracy=0.849688
2016-05-03 17:57:04,581 Node[0] Epoch[17] Batch [250] Speed: 633.57 samples/sec Train-accuracy=0.843906
2016-05-03 17:57:14,642 Node[0] Epoch[17] Batch [300] Speed: 636.18 samples/sec Train-accuracy=0.852812
2016-05-03 17:57:24,753 Node[0] Epoch[17] Batch [350] Speed: 632.95 samples/sec Train-accuracy=0.853281
2016-05-03 17:57:33,019 Node[0] Epoch[17] Resetting Data Iterator
2016-05-03 17:57:33,019 Node[0] Epoch[17] Time cost=78.876
2016-05-03 17:57:33,181 Node[0] Saved checkpoint to "cifar10/resnet-0018.params"
2016-05-03 17:57:35,047 Node[0] Epoch[17] Validation-accuracy=0.762420
2016-05-03 17:57:45,101 Node[0] Epoch[18] Batch [50] Speed: 639.89 samples/sec Train-accuracy=0.853906
2016-05-03 17:57:55,170 Node[0] Epoch[18] Batch [100] Speed: 635.67 samples/sec Train-accuracy=0.855156
2016-05-03 17:58:05,289 Node[0] Epoch[18] Batch [150] Speed: 632.47 samples/sec Train-accuracy=0.863750
2016-05-03 17:58:15,406 Node[0] Epoch[18] Batch [200] Speed: 632.61 samples/sec Train-accuracy=0.851719
2016-05-03 17:58:25,533 Node[0] Epoch[18] Batch [250] Speed: 632.01 samples/sec Train-accuracy=0.853750
2016-05-03 17:58:35,693 Node[0] Epoch[18] Batch [300] Speed: 629.88 samples/sec Train-accuracy=0.851562
2016-05-03 17:58:45,811 Node[0] Epoch[18] Batch [350] Speed: 632.58 samples/sec Train-accuracy=0.854531
2016-05-03 17:58:53,894 Node[0] Epoch[18] Resetting Data Iterator
2016-05-03 17:58:53,894 Node[0] Epoch[18] Time cost=78.847
2016-05-03 17:58:54,053 Node[0] Saved checkpoint to "cifar10/resnet-0019.params"
2016-05-03 17:58:55,950 Node[0] Epoch[18] Validation-accuracy=0.762921
2016-05-03 17:59:05,943 Node[0] Epoch[19] Batch [50] Speed: 643.81 samples/sec Train-accuracy=0.857812
2016-05-03 17:59:16,094 Node[0] Epoch[19] Batch [100] Speed: 630.47 samples/sec Train-accuracy=0.862969
2016-05-03 17:59:26,130 Node[0] Epoch[19] Batch [150] Speed: 637.75 samples/sec Train-accuracy=0.859688
2016-05-03 17:59:36,171 Node[0] Epoch[19] Batch [200] Speed: 637.36 samples/sec Train-accuracy=0.854531
2016-05-03 17:59:46,244 Node[0] Epoch[19] Batch [250] Speed: 635.41 samples/sec Train-accuracy=0.859375
2016-05-03 17:59:56,338 Node[0] Epoch[19] Batch [300] Speed: 634.06 samples/sec Train-accuracy=0.866563
2016-05-03 18:00:06,441 Node[0] Epoch[19] Batch [350] Speed: 633.49 samples/sec Train-accuracy=0.865156
2016-05-03 18:00:14,689 Node[0] Epoch[19] Resetting Data Iterator
2016-05-03 18:00:14,689 Node[0] Epoch[19] Time cost=78.739
2016-05-03 18:00:14,848 Node[0] Saved checkpoint to "cifar10/resnet-0020.params"
2016-05-03 18:00:16,711 Node[0] Epoch[19] Validation-accuracy=0.801082
2016-05-03 18:00:26,808 Node[0] Epoch[20] Batch [50] Speed: 637.16 samples/sec Train-accuracy=0.864688
2016-05-03 18:00:36,917 Node[0] Epoch[20] Batch [100] Speed: 633.11 samples/sec Train-accuracy=0.859375
2016-05-03 18:00:46,963 Node[0] Epoch[20] Batch [150] Speed: 637.10 samples/sec Train-accuracy=0.861719
2016-05-03 18:00:56,986 Node[0] Epoch[20] Batch [200] Speed: 638.55 samples/sec Train-accuracy=0.855000
2016-05-03 18:01:07,009 Node[0] Epoch[20] Batch [250] Speed: 638.54 samples/sec Train-accuracy=0.862812
2016-05-03 18:01:17,104 Node[0] Epoch[20] Batch [300] Speed: 633.95 samples/sec Train-accuracy=0.859062
2016-05-03 18:01:27,185 Node[0] Epoch[20] Batch [350] Speed: 634.90 samples/sec Train-accuracy=0.867031
2016-05-03 18:01:35,459 Node[0] Epoch[20] Resetting Data Iterator
2016-05-03 18:01:35,459 Node[0] Epoch[20] Time cost=78.748
2016-05-03 18:01:35,619 Node[0] Saved checkpoint to "cifar10/resnet-0021.params"
2016-05-03 18:01:37,477 Node[0] Epoch[20] Validation-accuracy=0.797276
2016-05-03 18:01:47,494 Node[0] Epoch[21] Batch [50] Speed: 642.28 samples/sec Train-accuracy=0.863906
2016-05-03 18:01:57,548 Node[0] Epoch[21] Batch [100] Speed: 636.59 samples/sec Train-accuracy=0.865469
2016-05-03 18:02:07,613 Node[0] Epoch[21] Batch [150] Speed: 635.87 samples/sec Train-accuracy=0.872500
2016-05-03 18:02:17,662 Node[0] Epoch[21] Batch [200] Speed: 636
View raw

(Sorry about that, but we can’t show files that are this big right now.)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment