Namespace(batch_norm=False, batch_size=25, clip_grad=0, crop_ratio=0.875, data_dir='/home/ubuntu/yizhu/data/UCF101/rawframes', dtype='float32', eval=False, hard_weight=0.5, input_size=224, label_smoothing=False, last_gamma=False, log_interval=10, logging_file='2d_rgb_vgg16_f1s1_b32_g8.txt', lr=0.001, lr_decay=0.1, lr_decay_epoch='30,60,80', lr_decay_period=0, lr_mode='step', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='vgg16_ucf101', momentum=0.9, new_height=256, new_width=340, no_wd=False, num_classes=101, num_epochs=80, num_gpus=8, num_segments=1, num_workers=32, partial_bn=False, resume_epoch=0, resume_params='', resume_states='', save_dir='/home/ubuntu/yizhu/logs/mxnet/pullrequest/2d_rgb_vgg16_f1s1_b32_g8', save_frequency=5, teacher=None, temperature=20, train_list='/home/ubuntu/yizhu/data/UCF101/ucfTrainTestlist/ucf101_train_split_1_rawframes.txt', use_gn=False, use_pretrained=True, use_se=False, use_tsn=False, val_list='/home/ubuntu/yizhu/data/UCF101/ucfTrainTestlist/ucf101_val_split_1_rawframes.txt', warmup_epochs=0, warmup_lr=0.0, wd=0.0005) Total batch size is set to 200 on 8 GPUs ActionRecVGG16( (features): HybridSequential( (0): Conv2D(3 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (1): Activation(relu) (2): Conv2D(64 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (3): Activation(relu) (4): MaxPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (5): Conv2D(64 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (6): Activation(relu) (7): Conv2D(128 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (8): Activation(relu) (9): MaxPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (10): Conv2D(128 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (11): Activation(relu) (12): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (13): Activation(relu) (14): Conv2D(256 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (15): Activation(relu) (16): MaxPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (17): Conv2D(256 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (18): Activation(relu) (19): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (20): Activation(relu) (21): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (22): Activation(relu) (23): MaxPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (24): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (25): Activation(relu) (26): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (27): Activation(relu) (28): Conv2D(512 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (29): Activation(relu) (30): MaxPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) (31): Dense(25088 -> 4096, Activation(relu)) (32): Dropout(p = 0.9, axes=()) (33): Dense(4096 -> 4096, Activation(relu)) (34): Dropout(p = 0.9, axes=()) ) (output): Dense(4096 -> 101, linear) ) Load 9537 training samples and 3783 validation samples. Epoch[0] Batch [9] Speed: 206.053349 samples/sec accuracy=1.150000 lr=0.001000 Epoch[0] Batch [19] Speed: 712.369785 samples/sec accuracy=3.175000 lr=0.001000 Epoch[0] Batch [29] Speed: 750.377487 samples/sec accuracy=4.616667 lr=0.001000 Epoch[0] Batch [39] Speed: 769.872523 samples/sec accuracy=6.475000 lr=0.001000 [Epoch 0] training: accuracy=7.832652 [Epoch 0] speed: 394 samples/sec time cost: 30.907833 [Epoch 0] validation: acc-top1=41.395718 acc-top5=74.200370 successfully opened events file: /home/ubuntu/yizhu/logs/mxnet/pullrequest/2d_rgb_vgg16_f1s1_b32_g8/events.out.tfevents.1563660782.ip-172-31-90-145 wrote 1 event to disk wrote 1 event to disk Epoch[1] Batch [9] Speed: 455.436405 samples/sec accuracy=18.450000 lr=0.001000 Epoch[1] Batch [19] Speed: 755.759591 samples/sec accuracy=19.000000 lr=0.001000 Epoch[1] Batch [29] Speed: 721.981273 samples/sec accuracy=20.233333 lr=0.001000 Epoch[1] Batch [39] Speed: 773.319783 samples/sec accuracy=20.725000 lr=0.001000 [Epoch 1] training: accuracy=21.369403 [Epoch 1] speed: 648 samples/sec time cost: 17.425212 [Epoch 1] validation: acc-top1=53.766852 acc-top5=81.628337 wrote 2 events to disk Epoch[2] Batch [9] Speed: 446.539619 samples/sec accuracy=25.650000 lr=0.001000 Epoch[2] Batch [19] Speed: 765.832471 samples/sec accuracy=26.750000 lr=0.001000 Epoch[2] Batch [29] Speed: 769.800461 samples/sec accuracy=26.850000 lr=0.001000 Epoch[2] Batch [39] Speed: 778.571132 samples/sec accuracy=27.312500 lr=0.001000 [Epoch 2] training: accuracy=27.681661 [Epoch 2] speed: 650 samples/sec time cost: 17.280995 [Epoch 2] validation: acc-top1=57.309014 acc-top5=83.954533 wrote 2 events to disk Epoch[3] Batch [9] Speed: 430.876372 samples/sec accuracy=30.850000 lr=0.001000 Epoch[3] Batch [19] Speed: 761.660077 samples/sec accuracy=31.550000 lr=0.001000 Epoch[3] Batch [29] Speed: 769.931737 samples/sec accuracy=32.033333 lr=0.001000 Epoch[3] Batch [39] Speed: 771.153875 samples/sec accuracy=32.725000 lr=0.001000 [Epoch 3] training: accuracy=32.746147 [Epoch 3] speed: 643 samples/sec time cost: 17.455495 [Epoch 3] validation: acc-top1=61.168385 acc-top5=85.831351 wrote 2 events to disk Epoch[4] Batch [9] Speed: 428.335779 samples/sec accuracy=34.950000 lr=0.001000 Epoch[4] Batch [19] Speed: 755.402905 samples/sec accuracy=35.250000 lr=0.001000 Epoch[4] Batch [29] Speed: 757.959808 samples/sec accuracy=35.383333 lr=0.001000 Epoch[4] Batch [39] Speed: 735.339293 samples/sec accuracy=35.800000 lr=0.001000 [Epoch 4] training: accuracy=35.965188 [Epoch 4] speed: 634 samples/sec time cost: 17.749789 [Epoch 4] validation: acc-top1=63.521015 acc-top5=86.122125 wrote 2 events to disk Epoch[5] Batch [9] Speed: 419.823292 samples/sec accuracy=39.250000 lr=0.001000 Epoch[5] Batch [19] Speed: 733.041047 samples/sec accuracy=38.550000 lr=0.001000 Epoch[5] Batch [29] Speed: 738.156150 samples/sec accuracy=39.233333 lr=0.001000 Epoch[5] Batch [39] Speed: 779.848857 samples/sec accuracy=39.525000 lr=0.001000 [Epoch 5] training: accuracy=39.771417 [Epoch 5] speed: 631 samples/sec time cost: 17.765326 [Epoch 5] validation: acc-top1=63.098070 acc-top5=87.602432 wrote 2 events to disk Epoch[6] Batch [9] Speed: 422.351021 samples/sec accuracy=39.950000 lr=0.001000 Epoch[6] Batch [19] Speed: 736.505145 samples/sec accuracy=41.800000 lr=0.001000 Epoch[6] Batch [29] Speed: 748.180967 samples/sec accuracy=41.766667 lr=0.001000 Epoch[6] Batch [39] Speed: 777.473585 samples/sec accuracy=42.000000 lr=0.001000 [Epoch 6] training: accuracy=41.994338 [Epoch 6] speed: 634 samples/sec time cost: 17.649794 [Epoch 6] validation: acc-top1=65.609305 acc-top5=88.316151 wrote 2 events to disk Epoch[7] Batch [9] Speed: 452.752192 samples/sec accuracy=43.850000 lr=0.001000 Epoch[7] Batch [19] Speed: 731.691995 samples/sec accuracy=43.950000 lr=0.001000 Epoch[7] Batch [29] Speed: 765.847153 samples/sec accuracy=43.850000 lr=0.001000 Epoch[7] Batch [39] Speed: 740.570636 samples/sec accuracy=44.137500 lr=0.001000 [Epoch 7] training: accuracy=44.311628 [Epoch 7] speed: 643 samples/sec time cost: 17.394132 [Epoch 7] validation: acc-top1=65.873645 acc-top5=88.659794 wrote 2 events to disk Epoch[8] Batch [9] Speed: 447.759159 samples/sec accuracy=45.000000 lr=0.001000 Epoch[8] Batch [19] Speed: 697.628841 samples/sec accuracy=45.050000 lr=0.001000 Epoch[8] Batch [29] Speed: 734.959115 samples/sec accuracy=46.450000 lr=0.001000 Epoch[8] Batch [39] Speed: 769.991385 samples/sec accuracy=46.212500 lr=0.001000 [Epoch 8] training: accuracy=45.947363 [Epoch 8] speed: 631 samples/sec time cost: 17.724521 [Epoch 8] validation: acc-top1=67.565424 acc-top5=89.267777 wrote 2 events to disk Epoch[9] Batch [9] Speed: 437.638024 samples/sec accuracy=47.250000 lr=0.001000 Epoch[9] Batch [19] Speed: 768.295614 samples/sec accuracy=48.350000 lr=0.001000 Epoch[9] Batch [29] Speed: 762.919628 samples/sec accuracy=47.833333 lr=0.001000 Epoch[9] Batch [39] Speed: 772.048566 samples/sec accuracy=48.087500 lr=0.001000 [Epoch 9] training: accuracy=48.117857 [Epoch 9] speed: 645 samples/sec time cost: 17.468874 [Epoch 9] validation: acc-top1=68.384880 acc-top5=90.351573 wrote 2 events to disk Epoch[10] Batch [9] Speed: 437.946356 samples/sec accuracy=48.500000 lr=0.001000 Epoch[10] Batch [19] Speed: 753.934998 samples/sec accuracy=48.925000 lr=0.001000 Epoch[10] Batch [29] Speed: 751.153893 samples/sec accuracy=49.183333 lr=0.001000 Epoch[10] Batch [39] Speed: 746.989795 samples/sec accuracy=49.712500 lr=0.001000 [Epoch 10] training: accuracy=49.795533 [Epoch 10] speed: 641 samples/sec time cost: 17.542967 [Epoch 10] validation: acc-top1=68.332012 acc-top5=90.563045 wrote 2 events to disk Epoch[11] Batch [9] Speed: 438.409658 samples/sec accuracy=52.550000 lr=0.001000 Epoch[11] Batch [19] Speed: 750.748994 samples/sec accuracy=50.950000 lr=0.001000 Epoch[11] Batch [29] Speed: 752.315413 samples/sec accuracy=51.183333 lr=0.001000 Epoch[11] Batch [39] Speed: 732.016735 samples/sec accuracy=51.162500 lr=0.001000 [Epoch 11] training: accuracy=51.462724 [Epoch 11] speed: 638 samples/sec time cost: 17.690479 [Epoch 11] validation: acc-top1=68.464182 acc-top5=90.272271 wrote 2 events to disk Epoch[12] Batch [9] Speed: 429.594740 samples/sec accuracy=51.800000 lr=0.001000 Epoch[12] Batch [19] Speed: 769.835219 samples/sec accuracy=51.650000 lr=0.001000 Epoch[12] Batch [29] Speed: 777.003116 samples/sec accuracy=51.900000 lr=0.001000 Epoch[12] Batch [39] Speed: 766.058297 samples/sec accuracy=51.800000 lr=0.001000 [Epoch 12] training: accuracy=51.850687 [Epoch 12] speed: 644 samples/sec time cost: 17.417272 [Epoch 12] validation: acc-top1=69.521544 acc-top5=90.906688 wrote 2 events to disk Epoch[13] Batch [9] Speed: 444.382523 samples/sec accuracy=51.450000 lr=0.001000 Epoch[13] Batch [19] Speed: 778.443323 samples/sec accuracy=53.900000 lr=0.001000 Epoch[13] Batch [29] Speed: 762.879317 samples/sec accuracy=53.766667 lr=0.001000 Epoch[13] Batch [39] Speed: 772.423283 samples/sec accuracy=53.475000 lr=0.001000 [Epoch 13] training: accuracy=53.780015 [Epoch 13] speed: 652 samples/sec time cost: 17.251067 [Epoch 13] validation: acc-top1=70.288131 acc-top5=90.933122 wrote 2 events to disk Epoch[14] Batch [9] Speed: 456.410092 samples/sec accuracy=55.750000 lr=0.001000 Epoch[14] Batch [19] Speed: 773.837052 samples/sec accuracy=55.375000 lr=0.001000 Epoch[14] Batch [29] Speed: 770.689676 samples/sec accuracy=55.366667 lr=0.001000 Epoch[14] Batch [39] Speed: 777.346280 samples/sec accuracy=55.237500 lr=0.001000 [Epoch 14] training: accuracy=55.174583 [Epoch 14] speed: 657 samples/sec time cost: 17.216147 [Epoch 14] validation: acc-top1=70.155961 acc-top5=91.329633 wrote 2 events to disk Epoch[15] Batch [9] Speed: 459.750773 samples/sec accuracy=54.100000 lr=0.001000 Epoch[15] Batch [19] Speed: 709.905536 samples/sec accuracy=55.250000 lr=0.001000 Epoch[15] Batch [29] Speed: 760.190509 samples/sec accuracy=54.833333 lr=0.001000 Epoch[15] Batch [39] Speed: 747.878868 samples/sec accuracy=54.700000 lr=0.001000 [Epoch 15] training: accuracy=55.122156 [Epoch 15] speed: 637 samples/sec time cost: 17.708784 [Epoch 15] validation: acc-top1=72.217817 acc-top5=91.831879 wrote 2 events to disk Epoch[16] Batch [9] Speed: 435.981795 samples/sec accuracy=56.600000 lr=0.001000 Epoch[16] Batch [19] Speed: 772.821289 samples/sec accuracy=56.650000 lr=0.001000 Epoch[16] Batch [29] Speed: 770.026442 samples/sec accuracy=56.950000 lr=0.001000 Epoch[16] Batch [39] Speed: 762.748146 samples/sec accuracy=57.250000 lr=0.001000 [Epoch 16] training: accuracy=57.407990 [Epoch 16] speed: 646 samples/sec time cost: 17.506273 [Epoch 16] validation: acc-top1=71.134021 acc-top5=91.593973 wrote 2 events to disk Epoch[17] Batch [9] Speed: 451.747027 samples/sec accuracy=58.300000 lr=0.001000 Epoch[17] Batch [19] Speed: 754.836004 samples/sec accuracy=57.975000 lr=0.001000 Epoch[17] Batch [29] Speed: 766.387238 samples/sec accuracy=58.166667 lr=0.001000 Epoch[17] Batch [39] Speed: 766.949049 samples/sec accuracy=58.550000 lr=0.001000 [Epoch 17] training: accuracy=58.875957 [Epoch 17] speed: 650 samples/sec time cost: 17.367606 [Epoch 17] validation: acc-top1=72.112080 acc-top5=91.884748 wrote 2 events to disk Epoch[18] Batch [9] Speed: 445.177721 samples/sec accuracy=59.050000 lr=0.001000 Epoch[18] Batch [19] Speed: 747.166775 samples/sec accuracy=59.100000 lr=0.001000 Epoch[18] Batch [29] Speed: 734.039195 samples/sec accuracy=59.650000 lr=0.001000 Epoch[18] Batch [39] Speed: 756.653704 samples/sec accuracy=59.550000 lr=0.001000 [Epoch 18] training: accuracy=59.756737 [Epoch 18] speed: 640 samples/sec time cost: 17.599734 [Epoch 18] validation: acc-top1=71.424795 acc-top5=92.201956 wrote 2 events to disk Epoch[19] Batch [9] Speed: 436.294173 samples/sec accuracy=59.750000 lr=0.001000 Epoch[19] Batch [19] Speed: 761.857016 samples/sec accuracy=60.150000 lr=0.001000 Epoch[19] Batch [29] Speed: 750.786958 samples/sec accuracy=60.450000 lr=0.001000 Epoch[19] Batch [39] Speed: 777.550262 samples/sec accuracy=60.087500 lr=0.001000 [Epoch 19] training: accuracy=60.134214 [Epoch 19] speed: 645 samples/sec time cost: 17.451673 [Epoch 19] validation: acc-top1=71.451229 acc-top5=92.043352 wrote 2 events to disk Epoch[20] Batch [9] Speed: 445.982622 samples/sec accuracy=60.650000 lr=0.001000 Epoch[20] Batch [19] Speed: 777.150756 samples/sec accuracy=60.625000 lr=0.001000 Epoch[20] Batch [29] Speed: 764.906782 samples/sec accuracy=60.450000 lr=0.001000 Epoch[20] Batch [39] Speed: 772.912504 samples/sec accuracy=60.475000 lr=0.001000 [Epoch 20] training: accuracy=60.469749 [Epoch 20] speed: 652 samples/sec time cost: 17.297302 [Epoch 20] validation: acc-top1=72.429289 acc-top5=92.016918 wrote 2 events to disk Epoch[21] Batch [9] Speed: 456.583986 samples/sec accuracy=61.350000 lr=0.001000 Epoch[21] Batch [19] Speed: 775.345361 samples/sec accuracy=62.750000 lr=0.001000 Epoch[21] Batch [29] Speed: 736.406610 samples/sec accuracy=62.483333 lr=0.001000 Epoch[21] Batch [39] Speed: 757.810127 samples/sec accuracy=62.425000 lr=0.001000 [Epoch 21] training: accuracy=62.294223 [Epoch 21] speed: 649 samples/sec time cost: 17.382804 [Epoch 21] validation: acc-top1=71.054718 acc-top5=91.964050 wrote 2 events to disk Epoch[22] Batch [9] Speed: 442.438064 samples/sec accuracy=63.450000 lr=0.001000 Epoch[22] Batch [19] Speed: 764.969839 samples/sec accuracy=62.775000 lr=0.001000 Epoch[22] Batch [29] Speed: 770.456583 samples/sec accuracy=62.450000 lr=0.001000 Epoch[22] Batch [39] Speed: 775.632911 samples/sec accuracy=62.337500 lr=0.001000 [Epoch 22] training: accuracy=62.210339 [Epoch 22] speed: 651 samples/sec time cost: 17.443846 [Epoch 22] validation: acc-top1=73.222310 acc-top5=92.466297 wrote 2 events to disk Epoch[23] Batch [9] Speed: 432.864300 samples/sec accuracy=63.950000 lr=0.001000 Epoch[23] Batch [19] Speed: 751.462347 samples/sec accuracy=62.625000 lr=0.001000 Epoch[23] Batch [29] Speed: 778.317577 samples/sec accuracy=63.383333 lr=0.001000 Epoch[23] Batch [39] Speed: 741.423974 samples/sec accuracy=63.275000 lr=0.001000 [Epoch 23] training: accuracy=63.143546 [Epoch 23] speed: 641 samples/sec time cost: 17.483192 [Epoch 23] validation: acc-top1=71.874174 acc-top5=92.519165 wrote 2 events to disk Epoch[24] Batch [9] Speed: 433.778603 samples/sec accuracy=62.100000 lr=0.001000 Epoch[24] Batch [19] Speed: 778.750165 samples/sec accuracy=64.225000 lr=0.001000 Epoch[24] Batch [29] Speed: 767.913291 samples/sec accuracy=63.766667 lr=0.001000 Epoch[24] Batch [39] Speed: 770.627584 samples/sec accuracy=63.712500 lr=0.001000 [Epoch 24] training: accuracy=63.573451 [Epoch 24] speed: 641 samples/sec time cost: 17.584409 [Epoch 24] validation: acc-top1=73.169442 acc-top5=92.572033 wrote 2 events to disk Epoch[25] Batch [9] Speed: 446.220165 samples/sec accuracy=62.950000 lr=0.001000 Epoch[25] Batch [19] Speed: 741.596621 samples/sec accuracy=64.525000 lr=0.001000 Epoch[25] Batch [29] Speed: 776.163909 samples/sec accuracy=64.850000 lr=0.001000 Epoch[25] Batch [39] Speed: 746.397191 samples/sec accuracy=64.800000 lr=0.001000 [Epoch 25] training: accuracy=64.621999 [Epoch 25] speed: 644 samples/sec time cost: 17.432683 [Epoch 25] validation: acc-top1=73.830293 acc-top5=92.862807 wrote 2 events to disk Epoch[26] Batch [9] Speed: 434.237913 samples/sec accuracy=65.250000 lr=0.001000 Epoch[26] Batch [19] Speed: 751.091547 samples/sec accuracy=65.325000 lr=0.001000 Epoch[26] Batch [29] Speed: 771.318591 samples/sec accuracy=65.483333 lr=0.001000 Epoch[26] Batch [39] Speed: 763.089590 samples/sec accuracy=65.175000 lr=0.001000 [Epoch 26] training: accuracy=65.020447 [Epoch 26] speed: 643 samples/sec time cost: 17.489232 [Epoch 26] validation: acc-top1=73.010838 acc-top5=92.809939 wrote 2 events to disk Epoch[27] Batch [9] Speed: 455.401222 samples/sec accuracy=67.300000 lr=0.001000 Epoch[27] Batch [19] Speed: 765.974357 samples/sec accuracy=66.125000 lr=0.001000 Epoch[27] Batch [29] Speed: 768.515291 samples/sec accuracy=66.100000 lr=0.001000 Epoch[27] Batch [39] Speed: 762.467088 samples/sec accuracy=66.250000 lr=0.001000 [Epoch 27] training: accuracy=66.142393 [Epoch 27] speed: 649 samples/sec time cost: 17.336525 [Epoch 27] validation: acc-top1=73.513085 acc-top5=92.545599 wrote 2 events to disk Epoch[28] Batch [9] Speed: 445.975770 samples/sec accuracy=65.550000 lr=0.001000 Epoch[28] Batch [19] Speed: 761.073391 samples/sec accuracy=66.350000 lr=0.001000 Epoch[28] Batch [29] Speed: 761.547092 samples/sec accuracy=66.683333 lr=0.001000 Epoch[28] Batch [39] Speed: 741.821235 samples/sec accuracy=66.825000 lr=0.001000 [Epoch 28] training: accuracy=66.687638 [Epoch 28] speed: 643 samples/sec time cost: 17.453518 [Epoch 28] validation: acc-top1=73.671689 acc-top5=92.439863 wrote 2 events to disk Epoch[29] Batch [9] Speed: 426.217184 samples/sec accuracy=66.550000 lr=0.001000 Epoch[29] Batch [19] Speed: 776.560029 samples/sec accuracy=67.025000 lr=0.001000 Epoch[29] Batch [29] Speed: 771.217754 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acc-top1=75.125562 acc-top5=93.259318 wrote 2 events to disk Epoch[65] Batch [9] Speed: 443.697104 samples/sec accuracy=72.200000 lr=0.000010 Epoch[65] Batch [19] Speed: 728.254333 samples/sec accuracy=72.225000 lr=0.000010 Epoch[65] Batch [29] Speed: 785.135104 samples/sec accuracy=72.200000 lr=0.000010 Epoch[65] Batch [39] Speed: 767.918352 samples/sec accuracy=72.650000 lr=0.000010 [Epoch 65] training: accuracy=72.706302 [Epoch 65] speed: 640 samples/sec time cost: 17.570692 [Epoch 65] validation: acc-top1=75.363468 acc-top5=93.365054 wrote 2 events to disk Epoch[66] Batch [9] Speed: 464.206917 samples/sec accuracy=70.600000 lr=0.000010 Epoch[66] Batch [19] Speed: 730.653946 samples/sec accuracy=70.950000 lr=0.000010 Epoch[66] Batch [29] Speed: 769.847371 samples/sec accuracy=71.266667 lr=0.000010 Epoch[66] Batch [39] Speed: 723.858317 samples/sec accuracy=71.325000 lr=0.000010 [Epoch 66] training: accuracy=71.615812 [Epoch 66] speed: 648 samples/sec time cost: 17.240807 [Epoch 66] validation: acc-top1=75.416336 acc-top5=93.285752 wrote 2 events to disk Epoch[67] Batch [9] Speed: 461.039719 samples/sec accuracy=73.050000 lr=0.000010 Epoch[67] Batch [19] Speed: 768.943674 samples/sec accuracy=73.225000 lr=0.000010 Epoch[67] Batch [29] Speed: 772.252337 samples/sec accuracy=73.450000 lr=0.000010 Epoch[67] Batch [39] Speed: 762.789691 samples/sec accuracy=73.050000 lr=0.000010 [Epoch 67] training: accuracy=73.387858 [Epoch 67] speed: 656 samples/sec time cost: 17.119558 [Epoch 67] validation: acc-top1=75.337034 acc-top5=93.365054 wrote 2 events to disk Epoch[68] Batch [9] Speed: 475.289055 samples/sec accuracy=74.250000 lr=0.000010 Epoch[68] Batch [19] Speed: 763.153459 samples/sec accuracy=73.150000 lr=0.000010 Epoch[68] Batch [29] Speed: 774.226441 samples/sec accuracy=73.200000 lr=0.000010 Epoch[68] Batch [39] Speed: 771.837020 samples/sec accuracy=73.000000 lr=0.000010 [Epoch 68] training: accuracy=72.947468 [Epoch 68] speed: 666 samples/sec time cost: 16.931285 [Epoch 68] validation: acc-top1=75.046260 acc-top5=93.391488 wrote 2 events to disk Epoch[69] Batch [9] Speed: 446.064060 samples/sec accuracy=71.800000 lr=0.000010 Epoch[69] Batch [19] Speed: 761.286401 samples/sec accuracy=72.925000 lr=0.000010 Epoch[69] Batch [29] Speed: 765.495413 samples/sec accuracy=72.500000 lr=0.000010 Epoch[69] Batch [39] Speed: 748.040260 samples/sec accuracy=72.712500 lr=0.000010 [Epoch 69] training: accuracy=72.528049 [Epoch 69] speed: 648 samples/sec time cost: 17.417022 [Epoch 69] validation: acc-top1=75.125562 acc-top5=93.365054 wrote 2 events to disk Epoch[70] Batch [9] Speed: 444.462082 samples/sec accuracy=73.350000 lr=0.000010 Epoch[70] Batch [19] Speed: 773.408335 samples/sec accuracy=73.500000 lr=0.000010 Epoch[70] Batch [29] Speed: 770.566281 samples/sec accuracy=73.216667 lr=0.000010 Epoch[70] Batch [39] Speed: 775.177202 samples/sec accuracy=72.737500 lr=0.000010 [Epoch 70] training: accuracy=73.115235 [Epoch 70] speed: 652 samples/sec time cost: 17.175776 [Epoch 70] validation: acc-top1=75.416336 acc-top5=93.259318 wrote 2 events to disk Epoch[71] Batch [9] Speed: 453.720116 samples/sec accuracy=71.450000 lr=0.000010 Epoch[71] Batch [19] Speed: 760.395856 samples/sec accuracy=72.600000 lr=0.000010 Epoch[71] Batch [29] Speed: 726.128168 samples/sec accuracy=72.516667 lr=0.000010 Epoch[71] Batch [39] Speed: 779.988878 samples/sec accuracy=72.412500 lr=0.000010 [Epoch 71] training: accuracy=72.580476 [Epoch 71] speed: 648 samples/sec time cost: 17.395952 [Epoch 71] validation: acc-top1=75.151996 acc-top5=93.391488 wrote 2 events to disk Epoch[72] Batch [9] Speed: 474.177218 samples/sec accuracy=72.400000 lr=0.000010 Epoch[72] Batch [19] Speed: 759.041238 samples/sec accuracy=72.500000 lr=0.000010 Epoch[72] Batch [29] Speed: 772.230654 samples/sec accuracy=72.083333 lr=0.000010 Epoch[72] Batch [39] Speed: 777.016790 samples/sec accuracy=72.437500 lr=0.000010 [Epoch 72] training: accuracy=72.936982 [Epoch 72] speed: 663 samples/sec time cost: 16.953462 [Epoch 72] validation: acc-top1=75.257732 acc-top5=93.338620 wrote 2 events to disk Epoch[73] Batch [9] Speed: 428.254957 samples/sec accuracy=71.400000 lr=0.000010 Epoch[73] Batch [19] Speed: 776.381858 samples/sec accuracy=71.400000 lr=0.000010 Epoch[73] Batch [29] Speed: 773.364413 samples/sec accuracy=72.183333 lr=0.000010 Epoch[73] Batch [39] Speed: 760.246727 samples/sec accuracy=72.387500 lr=0.000010 [Epoch 73] training: accuracy=72.590962 [Epoch 73] speed: 638 samples/sec time cost: 17.556012 [Epoch 73] validation: acc-top1=75.231298 acc-top5=93.285752 wrote 2 events to disk Epoch[74] Batch [9] Speed: 442.483526 samples/sec accuracy=72.950000 lr=0.000010 Epoch[74] Batch [19] Speed: 776.113139 samples/sec accuracy=72.725000 lr=0.000010 Epoch[74] Batch [29] Speed: 773.543128 samples/sec accuracy=72.783333 lr=0.000010 Epoch[74] Batch [39] Speed: 741.965651 samples/sec accuracy=72.775000 lr=0.000010 [Epoch 74] training: accuracy=73.062808 [Epoch 74] speed: 648 samples/sec time cost: 17.304685 [Epoch 74] validation: acc-top1=75.099128 acc-top5=93.417922 wrote 2 events to disk Epoch[75] Batch [9] Speed: 450.131217 samples/sec accuracy=73.900000 lr=0.000010 Epoch[75] Batch [19] Speed: 769.355882 samples/sec accuracy=72.475000 lr=0.000010 Epoch[75] Batch [29] Speed: 758.543485 samples/sec accuracy=72.633333 lr=0.000010 Epoch[75] Batch [39] Speed: 800.970949 samples/sec accuracy=72.350000 lr=0.000010 [Epoch 75] training: accuracy=72.255426 [Epoch 75] speed: 658 samples/sec time cost: 17.134220 [Epoch 75] validation: acc-top1=75.151996 acc-top5=93.365054 wrote 2 events to disk Epoch[76] Batch [9] Speed: 436.636111 samples/sec accuracy=75.350000 lr=0.000010 Epoch[76] Batch [19] Speed: 769.800814 samples/sec accuracy=74.750000 lr=0.000010 Epoch[76] Batch [29] Speed: 770.679268 samples/sec accuracy=73.166667 lr=0.000010 Epoch[76] Batch [39] Speed: 779.889966 samples/sec accuracy=72.900000 lr=0.000010 [Epoch 76] training: accuracy=72.884555 [Epoch 76] speed: 647 samples/sec time cost: 17.621810 [Epoch 76] validation: acc-top1=75.046260 acc-top5=93.338620 wrote 2 events to disk Epoch[77] Batch [9] Speed: 444.518231 samples/sec accuracy=72.700000 lr=0.000010 Epoch[77] Batch [19] Speed: 742.809447 samples/sec accuracy=72.150000 lr=0.000010 Epoch[77] Batch [29] Speed: 756.374800 samples/sec accuracy=72.183333 lr=0.000010 Epoch[77] Batch [39] Speed: 771.678259 samples/sec accuracy=72.312500 lr=0.000010 [Epoch 77] training: accuracy=72.108630 [Epoch 77] speed: 643 samples/sec time cost: 17.511645 [Epoch 77] validation: acc-top1=75.046260 acc-top5=93.417922 wrote 2 events to disk Epoch[78] Batch [9] Speed: 450.284840 samples/sec accuracy=71.700000 lr=0.000010 Epoch[78] Batch [19] Speed: 752.045226 samples/sec accuracy=72.025000 lr=0.000010 Epoch[78] Batch [29] Speed: 787.300786 samples/sec accuracy=72.266667 lr=0.000010 Epoch[78] Batch [39] Speed: 764.467557 samples/sec accuracy=71.887500 lr=0.000010 [Epoch 78] training: accuracy=72.328825 [Epoch 78] speed: 653 samples/sec time cost: 17.157336 [Epoch 78] validation: acc-top1=75.125562 acc-top5=93.338620 wrote 2 events to disk Epoch[79] Batch [9] Speed: 445.384089 samples/sec accuracy=72.400000 lr=0.000010 Epoch[79] Batch [19] Speed: 775.282947 samples/sec accuracy=72.825000 lr=0.000010 Epoch[79] Batch [29] Speed: 774.938881 samples/sec accuracy=71.800000 lr=0.000010 Epoch[79] Batch [39] Speed: 773.803503 samples/sec accuracy=72.162500 lr=0.000010 [Epoch 79] training: accuracy=72.507078 [Epoch 79] speed: 652 samples/sec time cost: 17.244695 [Epoch 79] validation: acc-top1=75.099128 acc-top5=93.470790 wrote 2 events to disk wrote 1 event to disk