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='tsn_2d_rgb_vgg16_seg_3_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=3, num_workers=32, partial_bn=False, resume_epoch=0, resume_params='', resume_states='', save_dir='/home/ubuntu/yizhu/logs/mxnet/pullrequest/tsn_2d_rgb_vgg16_seg_3_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=True, 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 ActionRecVGG16TSN( (basenet): 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) ) (tsn_consensus): Consensus( ) ) Load 9537 training samples and 3783 validation samples. Epoch[0] Batch [9] Speed: 101.801274 samples/sec accuracy=1.850000 lr=0.001000 Epoch[0] Batch [19] Speed: 488.458842 samples/sec accuracy=4.350000 lr=0.001000 Epoch[0] Batch [29] Speed: 468.875947 samples/sec accuracy=6.550000 lr=0.001000 Epoch[0] Batch [39] Speed: 474.635518 samples/sec accuracy=10.162500 lr=0.001000 [Epoch 0] training: accuracy=13.285100 [Epoch 0] speed: 215 samples/sec time cost: 60.572564 [Epoch 0] validation: acc-top1=46.444621 acc-top5=76.764473 successfully opened events file: /home/ubuntu/yizhu/logs/mxnet/pullrequest/tsn_2d_rgb_vgg16_seg_3_f1s1_b32_g8/events.out.tfevents.1563653454.ip-172-31-90-145 wrote 1 event to disk wrote 1 event to disk Epoch[1] Batch [9] Speed: 147.884653 samples/sec accuracy=35.650000 lr=0.001000 Epoch[1] Batch [19] Speed: 481.640509 samples/sec accuracy=37.750000 lr=0.001000 Epoch[1] Batch [29] Speed: 476.244324 samples/sec accuracy=38.733333 lr=0.001000 Epoch[1] Batch [39] Speed: 503.572839 samples/sec accuracy=39.787500 lr=0.001000 [Epoch 1] training: accuracy=40.683653 [Epoch 1] speed: 320 samples/sec time cost: 37.006300 [Epoch 1] validation: acc-top1=63.970394 acc-top5=86.862279 wrote 2 events to disk Epoch[2] Batch [9] Speed: 155.746774 samples/sec accuracy=50.250000 lr=0.001000 Epoch[2] Batch [19] Speed: 462.071616 samples/sec accuracy=50.900000 lr=0.001000 Epoch[2] Batch [29] Speed: 485.552306 samples/sec accuracy=51.316667 lr=0.001000 Epoch[2] Batch [39] Speed: 473.458715 samples/sec accuracy=51.412500 lr=0.001000 [Epoch 2] training: accuracy=51.924085 [Epoch 2] speed: 323 samples/sec time cost: 36.963060 [Epoch 2] validation: acc-top1=67.486122 acc-top5=89.902194 wrote 2 events to disk Epoch[3] Batch [9] Speed: 170.316221 samples/sec accuracy=55.800000 lr=0.001000 Epoch[3] Batch [19] Speed: 472.939216 samples/sec accuracy=56.325000 lr=0.001000 Epoch[3] Batch [29] Speed: 480.287813 samples/sec accuracy=56.333333 lr=0.001000 Epoch[3] Batch [39] Speed: 478.357325 samples/sec accuracy=56.700000 lr=0.001000 [Epoch 3] training: accuracy=56.873231 [Epoch 3] speed: 339 samples/sec time cost: 35.810404 [Epoch 3] validation: acc-top1=72.085646 acc-top5=92.043352 wrote 2 events to disk Epoch[4] Batch [9] Speed: 169.804066 samples/sec accuracy=60.950000 lr=0.001000 Epoch[4] Batch [19] Speed: 466.778107 samples/sec accuracy=60.650000 lr=0.001000 Epoch[4] Batch [29] Speed: 487.566502 samples/sec accuracy=61.283333 lr=0.001000 Epoch[4] Batch [39] Speed: 463.737966 samples/sec accuracy=61.425000 lr=0.001000 [Epoch 4] training: accuracy=61.602181 [Epoch 4] speed: 337 samples/sec time cost: 35.901869 [Epoch 4] validation: acc-top1=73.037272 acc-top5=93.285752 wrote 2 events to disk Epoch[5] Batch [9] Speed: 173.807749 samples/sec accuracy=65.500000 lr=0.001000 Epoch[5] Batch [19] Speed: 481.998589 samples/sec accuracy=65.550000 lr=0.001000 Epoch[5] Batch [29] Speed: 472.553653 samples/sec accuracy=65.050000 lr=0.001000 Epoch[5] Batch [39] Speed: 465.310220 samples/sec accuracy=65.037500 lr=0.001000 [Epoch 5] training: accuracy=64.810737 [Epoch 5] speed: 342 samples/sec time cost: 35.453083 [Epoch 5] validation: acc-top1=74.385408 acc-top5=92.994978 wrote 2 events to disk Epoch[6] Batch [9] Speed: 169.866265 samples/sec accuracy=66.150000 lr=0.001000 Epoch[6] Batch [19] Speed: 470.130021 samples/sec accuracy=66.500000 lr=0.001000 Epoch[6] Batch [29] Speed: 482.085705 samples/sec accuracy=66.433333 lr=0.001000 Epoch[6] Batch [39] Speed: 488.747817 samples/sec accuracy=66.350000 lr=0.001000 [Epoch 6] training: accuracy=66.163364 [Epoch 6] speed: 340 samples/sec time cost: 35.605331 [Epoch 6] validation: acc-top1=75.707111 acc-top5=94.105208 wrote 2 events to disk Epoch[7] Batch [9] Speed: 167.293670 samples/sec accuracy=68.900000 lr=0.001000 Epoch[7] Batch [19] Speed: 480.792505 samples/sec accuracy=69.275000 lr=0.001000 Epoch[7] Batch [29] Speed: 471.810892 samples/sec accuracy=69.366667 lr=0.001000 Epoch[7] Batch [39] Speed: 482.796805 samples/sec accuracy=69.562500 lr=0.001000 [Epoch 7] training: accuracy=69.613086 [Epoch 7] speed: 337 samples/sec time cost: 35.606064 [Epoch 7] validation: acc-top1=75.865715 acc-top5=93.602961 wrote 2 events to disk Epoch[8] Batch [9] Speed: 176.543966 samples/sec accuracy=70.000000 lr=0.001000 Epoch[8] Batch [19] Speed: 466.153709 samples/sec accuracy=70.275000 lr=0.001000 Epoch[8] Batch [29] Speed: 484.776027 samples/sec accuracy=71.016667 lr=0.001000 Epoch[8] Batch [39] Speed: 474.558214 samples/sec accuracy=70.700000 lr=0.001000 [Epoch 8] training: accuracy=70.839887 [Epoch 8] speed: 345 samples/sec time cost: 35.220156 [Epoch 8] validation: acc-top1=76.447264 acc-top5=93.735131 wrote 2 events to disk Epoch[9] Batch [9] Speed: 165.854278 samples/sec accuracy=72.550000 lr=0.001000 Epoch[9] Batch [19] Speed: 498.382868 samples/sec accuracy=71.750000 lr=0.001000 Epoch[9] Batch [29] Speed: 478.261707 samples/sec accuracy=71.833333 lr=0.001000 Epoch[9] Batch [39] Speed: 488.879383 samples/sec accuracy=72.425000 lr=0.001000 [Epoch 9] training: accuracy=72.643389 [Epoch 9] speed: 337 samples/sec time cost: 36.131751 [Epoch 9] validation: acc-top1=76.341528 acc-top5=94.131642 wrote 2 events to disk Epoch[10] Batch [9] Speed: 170.963049 samples/sec accuracy=73.150000 lr=0.001000 Epoch[10] Batch [19] Speed: 458.222109 samples/sec accuracy=73.000000 lr=0.001000 Epoch[10] Batch [29] Speed: 478.399037 samples/sec accuracy=73.816667 lr=0.001000 Epoch[10] Batch [39] Speed: 466.905282 samples/sec accuracy=73.537500 lr=0.001000 [Epoch 10] training: accuracy=73.786306 [Epoch 10] speed: 336 samples/sec time cost: 36.113971 [Epoch 10] validation: acc-top1=77.848269 acc-top5=94.448850 wrote 2 events to disk Epoch[11] Batch [9] Speed: 167.306533 samples/sec accuracy=75.950000 lr=0.001000 Epoch[11] Batch [19] Speed: 492.977200 samples/sec accuracy=74.725000 lr=0.001000 Epoch[11] Batch [29] Speed: 467.898222 samples/sec accuracy=75.266667 lr=0.001000 Epoch[11] Batch [39] Speed: 487.203020 samples/sec accuracy=74.862500 lr=0.001000 [Epoch 11] training: accuracy=75.034078 [Epoch 11] speed: 337 samples/sec time cost: 36.028165 [Epoch 11] validation: acc-top1=78.852762 acc-top5=95.109701 wrote 2 events to disk Epoch[12] Batch [9] Speed: 167.491765 samples/sec accuracy=75.650000 lr=0.001000 Epoch[12] Batch [19] Speed: 465.138000 samples/sec accuracy=76.625000 lr=0.001000 Epoch[12] Batch [29] Speed: 470.911902 samples/sec accuracy=76.283333 lr=0.001000 Epoch[12] Batch [39] Speed: 479.050867 samples/sec accuracy=76.500000 lr=0.001000 [Epoch 12] training: accuracy=76.680298 [Epoch 12] speed: 335 samples/sec time cost: 36.033546 [Epoch 12] validation: acc-top1=77.636796 acc-top5=94.818927 wrote 2 events to disk Epoch[13] Batch [9] Speed: 166.116671 samples/sec accuracy=78.600000 lr=0.001000 Epoch[13] Batch [19] Speed: 492.004336 samples/sec accuracy=78.225000 lr=0.001000 Epoch[13] Batch [29] Speed: 483.669998 samples/sec accuracy=78.300000 lr=0.001000 Epoch[13] Batch [39] Speed: 475.834758 samples/sec accuracy=78.362500 lr=0.001000 [Epoch 13] training: accuracy=78.295061 [Epoch 13] speed: 338 samples/sec time cost: 35.558987 [Epoch 13] validation: acc-top1=78.509120 acc-top5=95.374042 wrote 2 events to disk Epoch[14] Batch [9] Speed: 169.587770 samples/sec accuracy=78.450000 lr=0.001000 Epoch[14] Batch [19] Speed: 474.331576 samples/sec accuracy=78.200000 lr=0.001000 Epoch[14] Batch [29] Speed: 488.865850 samples/sec accuracy=78.033333 lr=0.001000 Epoch[14] Batch [39] Speed: 495.100554 samples/sec accuracy=78.275000 lr=0.001000 [Epoch 14] training: accuracy=77.865157 [Epoch 14] speed: 341 samples/sec time cost: 35.453147 [Epoch 14] validation: acc-top1=76.605868 acc-top5=94.448850 wrote 2 events to disk Epoch[15] Batch [9] Speed: 167.281830 samples/sec accuracy=76.500000 lr=0.001000 Epoch[15] Batch [19] Speed: 482.915706 samples/sec accuracy=77.500000 lr=0.001000 Epoch[15] Batch [29] Speed: 476.361534 samples/sec accuracy=78.100000 lr=0.001000 Epoch[15] Batch [39] Speed: 470.992809 samples/sec accuracy=78.375000 lr=0.001000 [Epoch 15] training: accuracy=78.536227 [Epoch 15] speed: 334 samples/sec time cost: 36.340152 [Epoch 15] validation: acc-top1=78.958499 acc-top5=95.268306 wrote 2 events to disk Epoch[16] Batch [9] Speed: 164.823316 samples/sec accuracy=80.350000 lr=0.001000 Epoch[16] Batch [19] Speed: 454.426193 samples/sec accuracy=79.875000 lr=0.001000 Epoch[16] Batch [29] Speed: 482.238408 samples/sec accuracy=79.700000 lr=0.001000 Epoch[16] Batch [39] Speed: 471.344283 samples/sec accuracy=79.637500 lr=0.001000 [Epoch 16] training: accuracy=79.951767 [Epoch 16] speed: 332 samples/sec time cost: 36.400970 [Epoch 16] validation: acc-top1=79.355009 acc-top5=95.849855 wrote 2 events to disk Epoch[17] Batch [9] Speed: 166.186399 samples/sec accuracy=80.350000 lr=0.001000 Epoch[17] Batch [19] Speed: 471.508887 samples/sec accuracy=81.250000 lr=0.001000 Epoch[17] Batch [29] Speed: 465.670632 samples/sec accuracy=81.233333 lr=0.001000 Epoch[17] Batch [39] Speed: 477.077051 samples/sec accuracy=80.787500 lr=0.001000 [Epoch 17] training: accuracy=80.738178 [Epoch 17] speed: 331 samples/sec time cost: 36.535723 [Epoch 17] validation: acc-top1=79.407877 acc-top5=95.532646 wrote 2 events to disk Epoch[18] Batch [9] Speed: 166.017504 samples/sec accuracy=81.700000 lr=0.001000 Epoch[18] Batch [19] Speed: 484.941681 samples/sec accuracy=80.925000 lr=0.001000 Epoch[18] Batch [29] Speed: 472.555330 samples/sec accuracy=80.883333 lr=0.001000 Epoch[18] Batch [39] Speed: 469.774593 samples/sec accuracy=81.037500 lr=0.001000 [Epoch 18] training: accuracy=81.199539 [Epoch 18] speed: 335 samples/sec time cost: 36.027837 [Epoch 18] validation: acc-top1=79.989426 acc-top5=95.559080 wrote 2 events to disk Epoch[19] Batch [9] Speed: 170.408274 samples/sec accuracy=82.150000 lr=0.001000 Epoch[19] Batch [19] Speed: 473.211476 samples/sec accuracy=81.900000 lr=0.001000 Epoch[19] Batch [29] Speed: 466.872410 samples/sec accuracy=82.483333 lr=0.001000 Epoch[19] Batch [39] Speed: 479.192018 samples/sec accuracy=82.625000 lr=0.001000 [Epoch 19] training: accuracy=82.489252 [Epoch 19] speed: 337 samples/sec time cost: 36.130941 [Epoch 19] validation: acc-top1=78.218345 acc-top5=94.713191 wrote 2 events to disk Epoch[20] Batch [9] Speed: 172.045918 samples/sec accuracy=81.900000 lr=0.001000 Epoch[20] Batch [19] Speed: 456.677148 samples/sec accuracy=82.525000 lr=0.001000 Epoch[20] Batch [29] Speed: 480.554864 samples/sec accuracy=82.633333 lr=0.001000 Epoch[20] Batch [39] Speed: 464.683665 samples/sec accuracy=82.862500 lr=0.001000 [Epoch 20] training: accuracy=82.583622 [Epoch 20] speed: 336 samples/sec time cost: 35.988758 [Epoch 20] validation: acc-top1=80.333069 acc-top5=95.849855 wrote 2 events to disk Epoch[21] Batch [9] Speed: 173.349808 samples/sec accuracy=82.950000 lr=0.001000 Epoch[21] Batch [19] Speed: 459.942781 samples/sec accuracy=82.775000 lr=0.001000 Epoch[21] Batch [29] Speed: 475.419725 samples/sec accuracy=83.050000 lr=0.001000 Epoch[21] Batch [39] Speed: 495.995575 samples/sec accuracy=83.250000 lr=0.001000 [Epoch 21] training: accuracy=83.055468 [Epoch 21] speed: 343 samples/sec time cost: 35.689253 [Epoch 21] validation: acc-top1=80.438805 acc-top5=95.611948 wrote 2 events to disk Epoch[22] Batch [9] Speed: 166.606150 samples/sec accuracy=84.500000 lr=0.001000 Epoch[22] Batch [19] Speed: 473.750971 samples/sec accuracy=83.375000 lr=0.001000 Epoch[22] Batch [29] Speed: 479.749551 samples/sec accuracy=83.450000 lr=0.001000 Epoch[22] Batch [39] Speed: 480.936917 samples/sec accuracy=83.300000 lr=0.001000 [Epoch 22] training: accuracy=83.443431 [Epoch 22] speed: 336 samples/sec time cost: 35.763256 [Epoch 22] validation: acc-top1=80.227333 acc-top5=95.982025 wrote 2 events to disk Epoch[23] Batch [9] Speed: 164.775377 samples/sec accuracy=82.950000 lr=0.001000 Epoch[23] Batch [19] Speed: 467.433820 samples/sec accuracy=83.525000 lr=0.001000 Epoch[23] Batch [29] Speed: 472.729599 samples/sec accuracy=83.750000 lr=0.001000 Epoch[23] Batch [39] Speed: 481.319523 samples/sec accuracy=84.162500 lr=0.001000 [Epoch 23] training: accuracy=84.051589 [Epoch 23] speed: 334 samples/sec time cost: 36.295321 [Epoch 23] validation: acc-top1=79.725086 acc-top5=95.982025 wrote 2 events to disk Epoch[24] Batch [9] Speed: 169.095880 samples/sec accuracy=84.950000 lr=0.001000 Epoch[24] Batch [19] Speed: 474.843013 samples/sec accuracy=85.150000 lr=0.001000 Epoch[24] Batch [29] Speed: 470.600194 samples/sec accuracy=85.483333 lr=0.001000 Epoch[24] Batch [39] Speed: 489.100462 samples/sec accuracy=85.162500 lr=0.001000 [Epoch 24] training: accuracy=85.089651 [Epoch 24] speed: 338 samples/sec time cost: 35.756586 [Epoch 24] validation: acc-top1=79.698652 acc-top5=96.140629 wrote 2 events to disk Epoch[25] Batch [9] Speed: 172.341275 samples/sec accuracy=85.500000 lr=0.001000 Epoch[25] Batch [19] Speed: 472.658241 samples/sec accuracy=85.175000 lr=0.001000 Epoch[25] Batch [29] Speed: 471.653132 samples/sec accuracy=85.033333 lr=0.001000 Epoch[25] Batch [39] Speed: 483.607315 samples/sec accuracy=85.437500 lr=0.001000 [Epoch 25] training: accuracy=85.288875 [Epoch 25] speed: 339 samples/sec time cost: 35.802302 [Epoch 25] validation: acc-top1=80.756014 acc-top5=95.638382 wrote 2 events to disk Epoch[26] Batch [9] Speed: 171.493535 samples/sec accuracy=86.100000 lr=0.001000 Epoch[26] Batch [19] Speed: 461.983390 samples/sec accuracy=86.725000 lr=0.001000 Epoch[26] Batch [29] Speed: 484.238146 samples/sec accuracy=86.533333 lr=0.001000 Epoch[26] Batch [39] Speed: 478.095708 samples/sec accuracy=86.037500 lr=0.001000 [Epoch 26] training: accuracy=85.760721 [Epoch 26] speed: 340 samples/sec time cost: 35.492368 [Epoch 26] validation: acc-top1=80.068729 acc-top5=95.532646 wrote 2 events to disk Epoch[27] Batch [9] Speed: 168.767527 samples/sec accuracy=86.450000 lr=0.001000 Epoch[27] Batch [19] Speed: 469.170994 samples/sec accuracy=85.850000 lr=0.001000 Epoch[27] Batch [29] Speed: 486.603678 samples/sec accuracy=85.366667 lr=0.001000 Epoch[27] Batch [39] Speed: 487.534935 samples/sec accuracy=85.562500 lr=0.001000 [Epoch 27] training: accuracy=85.697809 [Epoch 27] speed: 338 samples/sec time cost: 36.014613 [Epoch 27] validation: acc-top1=80.941052 acc-top5=95.691250 wrote 2 events to disk Epoch[28] Batch [9] Speed: 167.790392 samples/sec accuracy=86.650000 lr=0.001000 Epoch[28] Batch [19] Speed: 473.094530 samples/sec accuracy=87.250000 lr=0.001000 Epoch[28] Batch [29] Speed: 491.752401 samples/sec accuracy=87.283333 lr=0.001000 Epoch[28] Batch [39] Speed: 476.952763 samples/sec accuracy=87.250000 lr=0.001000 [Epoch 28] training: accuracy=87.375485 [Epoch 28] speed: 337 samples/sec time cost: 35.719385 [Epoch 28] validation: acc-top1=79.962992 acc-top5=95.162569 wrote 2 events to disk Epoch[29] Batch [9] Speed: 164.683630 samples/sec accuracy=87.150000 lr=0.001000 Epoch[29] Batch [19] Speed: 500.869173 samples/sec accuracy=87.250000 lr=0.001000 Epoch[29] Batch [29] Speed: 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[Epoch 66] validation: acc-top1=81.628337 acc-top5=95.982025 wrote 2 events to disk Epoch[67] Batch [9] Speed: 159.232925 samples/sec accuracy=91.450000 lr=0.000010 Epoch[67] Batch [19] Speed: 472.525890 samples/sec accuracy=91.325000 lr=0.000010 Epoch[67] Batch [29] Speed: 488.626510 samples/sec accuracy=90.883333 lr=0.000010 Epoch[67] Batch [39] Speed: 467.365249 samples/sec accuracy=91.025000 lr=0.000010 [Epoch 67] training: accuracy=90.951033 [Epoch 67] speed: 328 samples/sec time cost: 36.736301 [Epoch 67] validation: acc-top1=81.628337 acc-top5=96.008459 wrote 2 events to disk Epoch[68] Batch [9] Speed: 166.980323 samples/sec accuracy=89.850000 lr=0.000010 Epoch[68] Batch [19] Speed: 461.262327 samples/sec accuracy=90.300000 lr=0.000010 Epoch[68] Batch [29] Speed: 466.843258 samples/sec accuracy=90.533333 lr=0.000010 Epoch[68] Batch [39] Speed: 464.432929 samples/sec accuracy=90.850000 lr=0.000010 [Epoch 68] training: accuracy=90.856664 [Epoch 68] speed: 330 samples/sec time cost: 36.428542 [Epoch 68] validation: acc-top1=81.575469 acc-top5=96.008459 wrote 2 events to disk Epoch[69] Batch [9] Speed: 164.803120 samples/sec accuracy=90.550000 lr=0.000010 Epoch[69] Batch [19] Speed: 468.978992 samples/sec accuracy=89.900000 lr=0.000010 Epoch[69] Batch [29] Speed: 459.442715 samples/sec accuracy=89.600000 lr=0.000010 Epoch[69] Batch [39] Speed: 476.768187 samples/sec accuracy=89.637500 lr=0.000010 [Epoch 69] training: accuracy=89.724232 [Epoch 69] speed: 330 samples/sec time cost: 36.060617 [Epoch 69] validation: acc-top1=81.654771 acc-top5=95.902723 wrote 2 events to disk Epoch[70] Batch [9] Speed: 168.617751 samples/sec accuracy=90.100000 lr=0.000010 Epoch[70] Batch [19] Speed: 457.915371 samples/sec accuracy=90.500000 lr=0.000010 Epoch[70] Batch [29] Speed: 492.640353 samples/sec accuracy=90.483333 lr=0.000010 Epoch[70] Batch [39] Speed: 465.691184 samples/sec accuracy=90.237500 lr=0.000010 [Epoch 70] training: accuracy=90.332390 [Epoch 70] speed: 334 samples/sec time cost: 35.877162 [Epoch 70] validation: acc-top1=81.601903 acc-top5=95.929157 wrote 2 events to disk Epoch[71] Batch [9] Speed: 165.610548 samples/sec accuracy=90.250000 lr=0.000010 Epoch[71] Batch [19] Speed: 473.193351 samples/sec accuracy=90.200000 lr=0.000010 Epoch[71] Batch [29] Speed: 474.819441 samples/sec accuracy=89.983333 lr=0.000010 Epoch[71] Batch [39] Speed: 464.355288 samples/sec accuracy=90.137500 lr=0.000010 [Epoch 71] training: accuracy=90.049282 [Epoch 71] speed: 330 samples/sec time cost: 36.366948 [Epoch 71] validation: acc-top1=81.628337 acc-top5=95.876289 wrote 2 events to disk Epoch[72] Batch [9] Speed: 169.333633 samples/sec accuracy=90.000000 lr=0.000010 Epoch[72] Batch [19] Speed: 465.532529 samples/sec accuracy=90.375000 lr=0.000010 Epoch[72] Batch [29] Speed: 487.972932 samples/sec accuracy=90.383333 lr=0.000010 Epoch[72] Batch [39] Speed: 469.886797 samples/sec accuracy=90.275000 lr=0.000010 [Epoch 72] training: accuracy=90.342875 [Epoch 72] speed: 336 samples/sec time cost: 35.739835 [Epoch 72] validation: acc-top1=81.654771 acc-top5=95.929157 wrote 2 events to disk Epoch[73] Batch [9] Speed: 166.503282 samples/sec accuracy=90.050000 lr=0.000010 Epoch[73] Batch [19] Speed: 469.448862 samples/sec accuracy=90.025000 lr=0.000010 Epoch[73] Batch [29] Speed: 482.002466 samples/sec accuracy=90.300000 lr=0.000010 Epoch[73] Batch [39] Speed: 471.134013 samples/sec accuracy=90.462500 lr=0.000010 [Epoch 73] training: accuracy=90.458215 [Epoch 73] speed: 336 samples/sec time cost: 36.017062 [Epoch 73] validation: acc-top1=81.681205 acc-top5=95.929157 wrote 2 events to disk Epoch[74] Batch [9] Speed: 161.582774 samples/sec accuracy=90.550000 lr=0.000010 Epoch[74] Batch [19] Speed: 459.619431 samples/sec accuracy=90.650000 lr=0.000010 Epoch[74] Batch [29] Speed: 475.722528 samples/sec accuracy=90.516667 lr=0.000010 Epoch[74] Batch [39] Speed: 471.797731 samples/sec accuracy=90.387500 lr=0.000010 [Epoch 74] training: accuracy=90.258991 [Epoch 74] speed: 328 samples/sec time cost: 36.527619 [Epoch 74] validation: acc-top1=81.469733 acc-top5=95.955591 wrote 2 events to disk Epoch[75] Batch [9] Speed: 162.371656 samples/sec accuracy=89.150000 lr=0.000010 Epoch[75] Batch [19] Speed: 468.952250 samples/sec accuracy=89.575000 lr=0.000010 Epoch[75] Batch [29] Speed: 476.313686 samples/sec accuracy=89.916667 lr=0.000010 Epoch[75] Batch [39] Speed: 463.669834 samples/sec accuracy=90.150000 lr=0.000010 [Epoch 75] training: accuracy=90.416273 [Epoch 75] speed: 329 samples/sec time cost: 36.542005 [Epoch 75] validation: acc-top1=81.469733 acc-top5=96.034893 wrote 2 events to disk Epoch[76] Batch [9] Speed: 169.940244 samples/sec accuracy=90.250000 lr=0.000010 Epoch[76] Batch [19] Speed: 493.471042 samples/sec accuracy=91.225000 lr=0.000010 Epoch[76] Batch [29] Speed: 480.332503 samples/sec accuracy=90.650000 lr=0.000010 Epoch[76] Batch [39] Speed: 503.222810 samples/sec accuracy=90.850000 lr=0.000010 [Epoch 76] training: accuracy=90.961518 [Epoch 76] speed: 342 samples/sec time cost: 35.512478 [Epoch 76] validation: acc-top1=81.522601 acc-top5=96.034893 wrote 2 events to disk Epoch[77] Batch [9] Speed: 168.740484 samples/sec accuracy=91.000000 lr=0.000010 Epoch[77] Batch [19] Speed: 458.793281 samples/sec accuracy=90.375000 lr=0.000010 Epoch[77] Batch [29] Speed: 485.237090 samples/sec accuracy=90.500000 lr=0.000010 Epoch[77] Batch [39] Speed: 457.342716 samples/sec accuracy=90.387500 lr=0.000010 [Epoch 77] training: accuracy=90.405788 [Epoch 77] speed: 335 samples/sec time cost: 36.220712 [Epoch 77] validation: acc-top1=81.522601 acc-top5=96.061327 wrote 2 events to disk Epoch[78] Batch [9] Speed: 172.614234 samples/sec accuracy=90.150000 lr=0.000010 Epoch[78] Batch [19] Speed: 454.461718 samples/sec accuracy=90.550000 lr=0.000010 Epoch[78] Batch [29] Speed: 474.248580 samples/sec accuracy=90.450000 lr=0.000010 Epoch[78] Batch [39] Speed: 468.559862 samples/sec accuracy=90.925000 lr=0.000010 [Epoch 78] training: accuracy=90.510643 [Epoch 78] speed: 336 samples/sec time cost: 36.038647 [Epoch 78] validation: acc-top1=81.601903 acc-top5=95.982025 wrote 2 events to disk Epoch[79] Batch [9] Speed: 170.747406 samples/sec accuracy=90.400000 lr=0.000010 Epoch[79] Batch [19] Speed: 470.159321 samples/sec accuracy=90.025000 lr=0.000010 Epoch[79] Batch [29] Speed: 477.741252 samples/sec accuracy=90.150000 lr=0.000010 Epoch[79] Batch [39] Speed: 484.434120 samples/sec accuracy=90.137500 lr=0.000010 [Epoch 79] training: accuracy=90.353361 [Epoch 79] speed: 338 samples/sec time cost: 35.782670 [Epoch 79] validation: acc-top1=81.549035 acc-top5=95.955591 wrote 2 events to disk wrote 1 event to disk