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WARNING:tensorflow:From unet.py:152: calling argmax (from tensorflow.python.ops.math_ops) with dimension is deprecated and will be removed in a future version.
Instructions for updating:
Use the `axis` argument instead
2017-11-10 17:27:10.501604: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2017-11-10 17:27:10.736968: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:86:00.0
totalMemory: 11.17GiB freeMemory: 10.80GiB
2017-11-10 17:27:10.737021: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1055] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: Tesla K80, pci bus id: 0000:86:00.0, compute capability: 3.7)
Setting up summary op...
Setting up image reader...
FLAGS.data_dir: /home/CAD409/unet/Unet-sensing-image-tensorflow-master/Data/
Found pickle file!
107653
161
Setting up dataset reader
Initializing Batch Dataset Reader...
{'resize': False, 'resize_size': 160}
Initializing Batch Dataset Reader...
{'resize': False, 'resize_size': 160}
Setting up Saver...
Step: 0, Train_acc:0.656832
Step: 0, Val_acc:0.620604
==================>
2017-11-10 17:27:22.859770 ---> Validation_loss: 0.680551
Step: 10, Train_acc:0.77167
Step: 10, Val_acc:0.7562
==================>
Step: 20, Train_acc:0.787014
Step: 20, Val_acc:0.799305
==================>
Step: 30, Train_acc:0.798005
Step: 30, Val_acc:0.800789
==================>
Step: 40, Train_acc:0.763706
Step: 40, Val_acc:0.783076
==================>
Step: 50, Train_acc:0.795614
Step: 50, Val_acc:0.757697
==================>
Step: 60, Train_acc:0.807178
Step: 60, Val_acc:0.770615
==================>
Step: 70, Train_acc:0.851912
Step: 70, Val_acc:0.764796
==================>
Step: 80, Train_acc:0.807903
Step: 80, Val_acc:0.805048
==================>
Step: 90, Train_acc:0.811374
Step: 90, Val_acc:0.765996
==================>
Step: 100, Train_acc:0.85756
Step: 100, Val_acc:0.775607
==================>
2017-11-10 17:30:02.117289 ---> Validation_loss: 0.567218
Step: 110, Train_acc:0.767329
Step: 110, Val_acc:0.826421
==================>
Step: 120, Train_acc:0.812894
Step: 120, Val_acc:0.800181
==================>
Step: 130, Train_acc:0.81584
Step: 130, Val_acc:0.773888
==================>
Step: 140, Train_acc:0.842904
Step: 140, Val_acc:0.832108
==================>
Step: 150, Train_acc:0.840076
Step: 150, Val_acc:0.82094
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Step: 180, Val_acc:0.796295
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Step: 190, Val_acc:0.812983
==================>
Step: 200, Train_acc:0.863489
Step: 200, Val_acc:0.813473
==================>
2017-11-10 17:32:40.913782 ---> Validation_loss: 0.501522
Step: 210, Train_acc:0.808586
Step: 210, Val_acc:0.815944
==================>
Step: 220, Train_acc:0.841848
Step: 220, Val_acc:0.819866
==================>
Step: 230, Train_acc:0.840818
Step: 230, Val_acc:0.82136
==================>
Step: 240, Train_acc:0.835873
Step: 240, Val_acc:0.760497
==================>
Step: 250, Train_acc:0.772511
Step: 250, Val_acc:0.74975
==================>
Step: 260, Train_acc:0.823901
Step: 260, Val_acc:0.810165
==================>
Step: 270, Train_acc:0.852482
Step: 270, Val_acc:0.825587
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Step: 280, Train_acc:0.825443
Step: 280, Val_acc:0.822189
==================>
Step: 290, Train_acc:0.825142
Step: 290, Val_acc:0.819159
==================>
Step: 300, Train_acc:0.818357
Step: 300, Val_acc:0.86245
==================>
2017-11-10 17:35:17.445838 ---> Validation_loss: 0.430799
Step: 310, Train_acc:0.812554
Step: 310, Val_acc:0.846703
==================>
Step: 320, Train_acc:0.86816
Step: 320, Val_acc:0.813201
==================>
Step: 330, Train_acc:0.834677
Step: 330, Val_acc:0.835485
==================>
Step: 340, Train_acc:0.842847
Step: 340, Val_acc:0.792404
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Step: 350, Train_acc:0.834142
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Step: 360, Train_acc:0.83304
Step: 360, Val_acc:0.782286
==================>
Step: 370, Train_acc:0.877897
Step: 370, Val_acc:0.798302
==================>
Step: 380, Train_acc:0.842817
Step: 380, Val_acc:0.851694
==================>
Step: 390, Train_acc:0.845258
Step: 390, Val_acc:0.772678
==================>
Step: 400, Train_acc:0.821689
Step: 400, Val_acc:0.882681
==================>
2017-11-10 17:37:54.126222 ---> Validation_loss: 0.444099
Step: 410, Train_acc:0.840947
Step: 410, Val_acc:0.823586
==================>
Step: 420, Train_acc:0.862424
Step: 420, Val_acc:0.825647
==================>
Step: 430, Train_acc:0.860753
Step: 430, Val_acc:0.759047
==================>
Step: 440, Train_acc:0.864209
Step: 440, Val_acc:0.828873
==================>
Step: 450, Train_acc:0.851715
Step: 450, Val_acc:0.889644
==================>
Step: 460, Train_acc:0.830726
Step: 460, Val_acc:0.819043
==================>
Step: 470, Train_acc:0.830551
Step: 470, Val_acc:0.849719
==================>
Step: 480, Train_acc:0.815206
Step: 480, Val_acc:0.85723
==================>
Step: 490, Train_acc:0.845365
Step: 490, Val_acc:0.842118
==================>
Step: 500, Train_acc:0.800216
Step: 500, Val_acc:0.793406
==================>
****************** Epochs completed: 1******************
2017-11-10 17:40:30.346303 ---> Validation_loss: 0.365408
Step: 510, Train_acc:0.85213
Step: 510, Val_acc:0.834109
==================>
Step: 520, Train_acc:0.88239
Step: 520, Val_acc:0.816892
==================>
Step: 530, Train_acc:0.845552
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==================>
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Step: 580, Train_acc:0.833995
Step: 580, Val_acc:0.854927
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Step: 590, Val_acc:0.836219
==================>
Step: 600, Train_acc:0.841664
Step: 600, Val_acc:0.854255
==================>
2017-11-10 17:43:06.996591 ---> Validation_loss: 0.401171
Step: 610, Train_acc:0.858822
Step: 610, Val_acc:0.84657
==================>
Step: 620, Train_acc:0.864462
Step: 620, Val_acc:0.835533
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Step: 640, Val_acc:0.802203
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Step: 680, Val_acc:0.849174
==================>
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Step: 690, Val_acc:0.808285
==================>
Step: 700, Train_acc:0.83412
Step: 700, Val_acc:0.861217
==================>
2017-11-10 17:45:44.514471 ---> Validation_loss: 0.430761
Step: 710, Train_acc:0.845134
Step: 710, Val_acc:0.835464
==================>
Step: 720, Train_acc:0.840485
Step: 720, Val_acc:0.799663
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Step: 730, Val_acc:0.829222
==================>
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Step: 740, Val_acc:0.760553
==================>
Step: 750, Train_acc:0.862562
Step: 750, Val_acc:0.800435
==================>
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Step: 760, Val_acc:0.841772
==================>
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Step: 770, Val_acc:0.835803
==================>
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Step: 780, Val_acc:0.848229
==================>
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Step: 790, Val_acc:0.824136
==================>
Step: 800, Train_acc:0.797472
Step: 800, Val_acc:0.776135
==================>
2017-11-10 17:48:21.481900 ---> Validation_loss: 0.327784
Step: 810, Train_acc:0.87204
Step: 810, Val_acc:0.83718
==================>
Step: 820, Train_acc:0.838838
Step: 820, Val_acc:0.889631
==================>
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Step: 830, Val_acc:0.864344
==================>
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Step: 840, Val_acc:0.833112
==================>
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Step: 850, Val_acc:0.802474
==================>
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Step: 860, Val_acc:0.849803
==================>
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Step: 870, Val_acc:0.825645
==================>
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Step: 880, Val_acc:0.846904
==================>
Step: 890, Train_acc:0.83228
Step: 890, Val_acc:0.850275
==================>
Step: 900, Train_acc:0.838864
Step: 900, Val_acc:0.826699
==================>
2017-11-10 17:50:57.946802 ---> Validation_loss: 0.46193
Step: 910, Train_acc:0.828356
Step: 910, Val_acc:0.822583
==================>
Step: 920, Train_acc:0.855173
Step: 920, Val_acc:0.845479
==================>
Step: 930, Train_acc:0.853274
Step: 930, Val_acc:0.849309
==================>
Step: 940, Train_acc:0.827449
Step: 940, Val_acc:0.842273
==================>
Step: 950, Train_acc:0.843212
Step: 950, Val_acc:0.799923
==================>
Step: 960, Train_acc:0.814292
Step: 960, Val_acc:0.817518
==================>
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Step: 970, Val_acc:0.824113
==================>
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Step: 980, Val_acc:0.835198
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Step: 990, Train_acc:0.836364
Step: 990, Val_acc:0.888387
==================>
Step: 1000, Train_acc:0.842501
Step: 1000, Val_acc:0.813628
==================>
****************** Epochs completed: 2******************
2017-11-10 17:53:34.098343 ---> Validation_loss: 0.391118
Step: 1010, Train_acc:0.823423
Step: 1010, Val_acc:0.889933
==================>
Step: 1020, Train_acc:0.819835
Step: 1020, Val_acc:0.839364
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Step: 1030, Val_acc:0.850448
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Step: 1070, Val_acc:0.794785
==================>
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Step: 1080, Val_acc:0.804705
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Step: 1090, Val_acc:0.798671
==================>
Step: 1100, Train_acc:0.879652
Step: 1100, Val_acc:0.848947
==================>
2017-11-10 17:56:10.733078 ---> Validation_loss: 0.310394
Step: 1110, Train_acc:0.865745
Step: 1110, Val_acc:0.843867
==================>
Step: 1120, Train_acc:0.846439
Step: 1120, Val_acc:0.791581
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Step: 1190, Val_acc:0.855175
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Step: 1200, Train_acc:0.847142
Step: 1200, Val_acc:0.865629
==================>
2017-11-10 17:58:47.403376 ---> Validation_loss: 0.277686
Step: 1210, Train_acc:0.844824
Step: 1210, Val_acc:0.843186
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Step: 1220, Train_acc:0.866876
Step: 1220, Val_acc:0.833192
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Step: 1230, Train_acc:0.853859
Step: 1230, Val_acc:0.885431
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Step: 1240, Train_acc:0.871997
Step: 1240, Val_acc:0.795293
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Step: 1250, Train_acc:0.847528
Step: 1250, Val_acc:0.826681
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Step: 1260, Train_acc:0.874529
Step: 1260, Val_acc:0.889402
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Step: 1270, Train_acc:0.794871
Step: 1270, Val_acc:0.875491
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Step: 1280, Train_acc:0.904022
Step: 1280, Val_acc:0.855313
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Step: 1290, Train_acc:0.838171
Step: 1290, Val_acc:0.827581
==================>
Step: 1300, Train_acc:0.873809
Step: 1300, Val_acc:0.839713
==================>
2017-11-10 18:01:24.656241 ---> Validation_loss: 0.386475
Step: 1310, Train_acc:0.835709
Step: 1310, Val_acc:0.853375
==================>
Step: 1320, Train_acc:0.834941
Step: 1320, Val_acc:0.841251
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Step: 1330, Train_acc:0.819655
Step: 1330, Val_acc:0.85954
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Step: 1340, Train_acc:0.85437
Step: 1340, Val_acc:0.837799
==================>
Step: 1350, Train_acc:0.864244
Step: 1350, Val_acc:0.858076
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Step: 1360, Train_acc:0.818087
Step: 1360, Val_acc:0.845154
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Step: 1370, Train_acc:0.81359
Step: 1370, Val_acc:0.846213
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Step: 1380, Train_acc:0.819625
Step: 1380, Val_acc:0.829043
==================>
Step: 1390, Train_acc:0.873978
Step: 1390, Val_acc:0.824225
==================>
Step: 1400, Train_acc:0.850059
Step: 1400, Val_acc:0.857244
==================>
2017-11-10 18:04:00.607131 ---> Validation_loss: 0.354819
Step: 1410, Train_acc:0.900308
Step: 1410, Val_acc:0.855625
==================>
Step: 1420, Train_acc:0.851664
Step: 1420, Val_acc:0.793954
==================>
Step: 1430, Train_acc:0.830809
Step: 1430, Val_acc:0.841776
==================>
Step: 1440, Train_acc:0.866243
Step: 1440, Val_acc:0.879592
==================>
Step: 1450, Train_acc:0.82713
Step: 1450, Val_acc:0.83786
==================>
Step: 1460, Train_acc:0.846303
Step: 1460, Val_acc:0.774946
==================>
Step: 1470, Train_acc:0.829865
Step: 1470, Val_acc:0.863638
==================>
Step: 1480, Train_acc:0.869121
Step: 1480, Val_acc:0.862872
==================>
Step: 1490, Train_acc:0.886475
Step: 1490, Val_acc:0.80156
==================>
Step: 1500, Train_acc:0.804838
Step: 1500, Val_acc:0.844841
==================>
****************** Epochs completed: 3******************
2017-11-10 18:06:37.041944 ---> Validation_loss: 0.306696
Step: 1510, Train_acc:0.846063
Step: 1510, Val_acc:0.846785
==================>
Step: 1520, Train_acc:0.813358
Step: 1520, Val_acc:0.858783
==================>
Step: 1530, Train_acc:0.82718
Step: 1530, Val_acc:0.837954
==================>
Step: 1540, Train_acc:0.774864
Step: 1540, Val_acc:0.858655
==================>
Step: 1550, Train_acc:0.863577
Step: 1550, Val_acc:0.810297
==================>
Step: 1560, Train_acc:0.82283
Step: 1560, Val_acc:0.802607
==================>
Step: 1570, Train_acc:0.857488
Step: 1570, Val_acc:0.897776
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Step: 1580, Train_acc:0.850337
Step: 1580, Val_acc:0.848104
==================>
Step: 1590, Train_acc:0.807859
Step: 1590, Val_acc:0.85369
==================>
Step: 1600, Train_acc:0.850475
Step: 1600, Val_acc:0.869287
==================>
2017-11-10 18:09:13.178187 ---> Validation_loss: 0.356914
Step: 1610, Train_acc:0.842646
Step: 1610, Val_acc:0.858964
==================>
Step: 1620, Train_acc:0.905038
Step: 1620, Val_acc:0.890332
==================>
Step: 1630, Train_acc:0.87416
Step: 1630, Val_acc:0.862689
==================>
Step: 1640, Train_acc:0.85083
Step: 1640, Val_acc:0.850569
==================>
Step: 1650, Train_acc:0.856014
Step: 1650, Val_acc:0.761893
==================>
Step: 1660, Train_acc:0.852434
Step: 1660, Val_acc:0.834058
==================>
Step: 1670, Train_acc:0.857173
Step: 1670, Val_acc:0.832272
==================>
Step: 1680, Train_acc:0.859551
Step: 1680, Val_acc:0.865264
==================>
Step: 1690, Train_acc:0.901516
Step: 1690, Val_acc:0.858435
==================>
Step: 1700, Train_acc:0.857159
Step: 1700, Val_acc:0.852731
==================>
2017-11-10 18:11:49.347754 ---> Validation_loss: 0.346558
Step: 1710, Train_acc:0.88032
Step: 1710, Val_acc:0.843667
==================>
Step: 1720, Train_acc:0.88249
Step: 1720, Val_acc:0.850457
==================>
Step: 1730, Train_acc:0.856726
Step: 1730, Val_acc:0.826356
==================>
Step: 1740, Train_acc:0.860989
Step: 1740, Val_acc:0.866504
==================>
Step: 1750, Train_acc:0.849668
Step: 1750, Val_acc:0.825341
==================>
Step: 1760, Train_acc:0.839076
Step: 1760, Val_acc:0.848657
==================>
Step: 1770, Train_acc:0.820312
Step: 1770, Val_acc:0.810486
==================>
Step: 1780, Train_acc:0.834711
Step: 1780, Val_acc:0.820584
==================>
Step: 1790, Train_acc:0.881339
Step: 1790, Val_acc:0.837347
==================>
Step: 1800, Train_acc:0.888219
Step: 1800, Val_acc:0.864177
==================>
2017-11-10 18:14:25.313362 ---> Validation_loss: 0.296891
Step: 1810, Train_acc:0.895
Step: 1810, Val_acc:0.792458
==================>
Step: 1820, Train_acc:0.894142
Step: 1820, Val_acc:0.855023
==================>
Step: 1830, Train_acc:0.891371
Step: 1830, Val_acc:0.875712
==================>
Step: 1840, Train_acc:0.880988
Step: 1840, Val_acc:0.85749
==================>
Step: 1850, Train_acc:0.873212
Step: 1850, Val_acc:0.862637
==================>
Step: 1860, Train_acc:0.879066
Step: 1860, Val_acc:0.873761
==================>
Step: 1870, Train_acc:0.853662
Step: 1870, Val_acc:0.835707
==================>
Step: 1880, Train_acc:0.84391
Step: 1880, Val_acc:0.833887
==================>
Step: 1890, Train_acc:0.873303
Step: 1890, Val_acc:0.84371
==================>
Step: 1900, Train_acc:0.833628
Step: 1900, Val_acc:0.852861
==================>
2017-11-10 18:17:02.134302 ---> Validation_loss: 0.347101
Step: 1910, Train_acc:0.801398
Step: 1910, Val_acc:0.844143
==================>
Step: 1920, Train_acc:0.849008
Step: 1920, Val_acc:0.804596
==================>
Step: 1930, Train_acc:0.865576
Step: 1930, Val_acc:0.838108
==================>
Step: 1940, Train_acc:0.869662
Step: 1940, Val_acc:0.803022
==================>
Step: 1950, Train_acc:0.868325
Step: 1950, Val_acc:0.870291
==================>
Step: 1960, Train_acc:0.866549
Step: 1960, Val_acc:0.834117
==================>
Step: 1970, Train_acc:0.820344
Step: 1970, Val_acc:0.84304
==================>
Step: 1980, Train_acc:0.892603
Step: 1980, Val_acc:0.86756
==================>
Step: 1990, Train_acc:0.846089
Step: 1990, Val_acc:0.868202
==================>
Step: 2000, Train_acc:0.768059
Step: 2000, Val_acc:0.890066
==================>
****************** Epochs completed: 4******************
2017-11-10 18:19:38.638540 ---> Validation_loss: 0.327807
Step: 2010, Train_acc:0.868491
Step: 2010, Val_acc:0.836998
==================>
Step: 2020, Train_acc:0.870554
Step: 2020, Val_acc:0.868191
==================>
Step: 2030, Train_acc:0.870419
Step: 2030, Val_acc:0.848945
==================>
Step: 2040, Train_acc:0.871433
Step: 2040, Val_acc:0.856691
==================>
Step: 2050, Train_acc:0.870831
Step: 2050, Val_acc:0.832339
==================>
Step: 2060, Train_acc:0.844646
Step: 2060, Val_acc:0.836669
==================>
Step: 2070, Train_acc:0.833571
Step: 2070, Val_acc:0.871119
==================>
Step: 2080, Train_acc:0.841177
Step: 2080, Val_acc:0.843589
==================>
Step: 2090, Train_acc:0.824175
Step: 2090, Val_acc:0.812312
==================>
Step: 2100, Train_acc:0.887363
Step: 2100, Val_acc:0.831912
==================>
2017-11-10 18:22:14.317170 ---> Validation_loss: 0.394912
Step: 2110, Train_acc:0.863016
Step: 2110, Val_acc:0.856381
==================>
Step: 2120, Train_acc:0.838406
Step: 2120, Val_acc:0.759395
==================>
Step: 2130, Train_acc:0.850287
Step: 2130, Val_acc:0.790356
==================>
Step: 2140, Train_acc:0.805198
Step: 2140, Val_acc:0.840664
==================>
Step: 2150, Train_acc:0.856488
Step: 2150, Val_acc:0.87094
==================>
Step: 2160, Train_acc:0.824061
Step: 2160, Val_acc:0.865001
==================>
Step: 2170, Train_acc:0.88329
Step: 2170, Val_acc:0.835032
==================>
Step: 2180, Train_acc:0.821866
Step: 2180, Val_acc:0.852849
==================>
Step: 2190, Train_acc:0.843615
Step: 2190, Val_acc:0.810555
==================>
Step: 2200, Train_acc:0.861108
Step: 2200, Val_acc:0.839399
==================>
2017-11-10 18:24:50.759386 ---> Validation_loss: 0.290142
Step: 2210, Train_acc:0.863629
Step: 2210, Val_acc:0.781022
==================>
Step: 2220, Train_acc:0.851685
Step: 2220, Val_acc:0.843345
==================>
Step: 2230, Train_acc:0.869724
Step: 2230, Val_acc:0.816366
==================>
Step: 2240, Train_acc:0.81106
Step: 2240, Val_acc:0.823281
==================>
Step: 2250, Train_acc:0.87036
Step: 2250, Val_acc:0.856445
==================>
Step: 2260, Train_acc:0.857374
Step: 2260, Val_acc:0.855945
==================>
Step: 2270, Train_acc:0.830054
Step: 2270, Val_acc:0.895638
==================>
Step: 2280, Train_acc:0.868818
Step: 2280, Val_acc:0.859005
==================>
Step: 2290, Train_acc:0.847529
Step: 2290, Val_acc:0.838247
==================>
Step: 2300, Train_acc:0.826661
Step: 2300, Val_acc:0.865118
==================>
2017-11-10 18:27:26.660010 ---> Validation_loss: 0.343637
Step: 2310, Train_acc:0.816105
Step: 2310, Val_acc:0.88702
==================>
Step: 2320, Train_acc:0.854032
Step: 2320, Val_acc:0.862174
==================>
Step: 2330, Train_acc:0.868793
Step: 2330, Val_acc:0.849182
==================>
Step: 2340, Train_acc:0.817496
Step: 2340, Val_acc:0.832294
==================>
Step: 2350, Train_acc:0.864703
Step: 2350, Val_acc:0.883488
==================>
Step: 2360, Train_acc:0.903618
Step: 2360, Val_acc:0.844469
==================>
Step: 2370, Train_acc:0.84953
Step: 2370, Val_acc:0.856243
==================>
Step: 2380, Train_acc:0.837423
Step: 2380, Val_acc:0.84454
==================>
Step: 2390, Train_acc:0.862526
Step: 2390, Val_acc:0.816185
==================>
Step: 2400, Train_acc:0.889019
Step: 2400, Val_acc:0.861442
==================>
2017-11-10 18:30:03.069110 ---> Validation_loss: 0.359531
Step: 2410, Train_acc:0.878102
Step: 2410, Val_acc:0.861136
==================>
Step: 2420, Train_acc:0.850674
Step: 2420, Val_acc:0.836556
==================>
Step: 2430, Train_acc:0.85694
Step: 2430, Val_acc:0.783175
==================>
Step: 2440, Train_acc:0.867473
Step: 2440, Val_acc:0.862656
==================>
Step: 2450, Train_acc:0.844448
Step: 2450, Val_acc:0.819293
==================>
Step: 2460, Train_acc:0.799276
Step: 2460, Val_acc:0.860836
==================>
Step: 2470, Train_acc:0.83024
Step: 2470, Val_acc:0.836871
==================>
Step: 2480, Train_acc:0.851622
Step: 2480, Val_acc:0.834266
==================>
Step: 2490, Train_acc:0.852544
Step: 2490, Val_acc:0.822848
==================>
Step: 2500, Train_acc:0.871873
Step: 2500, Val_acc:0.825214
==================>
****************** Epochs completed: 5******************
2017-11-10 18:32:39.198981 ---> Validation_loss: 0.31849
Step: 2510, Train_acc:0.788491
Step: 2510, Val_acc:0.866498
==================>
Step: 2520, Train_acc:0.829425
Step: 2520, Val_acc:0.843364
==================>
Step: 2530, Train_acc:0.873314
Step: 2530, Val_acc:0.829529
==================>
Step: 2540, Train_acc:0.8308
Step: 2540, Val_acc:0.807784
==================>
Step: 2550, Train_acc:0.869626
Step: 2550, Val_acc:0.841134
==================>
Step: 2560, Train_acc:0.867721
Step: 2560, Val_acc:0.80662
==================>
Step: 2570, Train_acc:0.870137
Step: 2570, Val_acc:0.875198
==================>
Step: 2580, Train_acc:0.857612
Step: 2580, Val_acc:0.869072
==================>
Step: 2590, Train_acc:0.884344
Step: 2590, Val_acc:0.803403
==================>
Step: 2600, Train_acc:0.877183
Step: 2600, Val_acc:0.812875
==================>
2017-11-10 18:35:15.288404 ---> Validation_loss: 0.281264
Step: 2610, Train_acc:0.845908
Step: 2610, Val_acc:0.847211
==================>
Step: 2620, Train_acc:0.876567
Step: 2620, Val_acc:0.866454
==================>
Step: 2630, Train_acc:0.882036
Step: 2630, Val_acc:0.836207
==================>
Step: 2640, Train_acc:0.855491
Step: 2640, Val_acc:0.826013
==================>
Step: 2650, Train_acc:0.858677
Step: 2650, Val_acc:0.857876
==================>
Step: 2660, Train_acc:0.889006
Step: 2660, Val_acc:0.852607
==================>
Step: 2670, Train_acc:0.865536
Step: 2670, Val_acc:0.838925
==================>
Step: 2680, Train_acc:0.829932
Step: 2680, Val_acc:0.84433
==================>
Step: 2690, Train_acc:0.89568
Step: 2690, Val_acc:0.784794
==================>
Step: 2700, Train_acc:0.87425
Step: 2700, Val_acc:0.846035
==================>
2017-11-10 18:37:51.697423 ---> Validation_loss: 0.329265
Step: 2710, Train_acc:0.796222
Step: 2710, Val_acc:0.870615
==================>
Step: 2720, Train_acc:0.83095
Step: 2720, Val_acc:0.819091
==================>
Step: 2730, Train_acc:0.850729
Step: 2730, Val_acc:0.866819
==================>
Step: 2740, Train_acc:0.856
Step: 2740, Val_acc:0.858583
==================>
Step: 2750, Train_acc:0.908734
Step: 2750, Val_acc:0.835006
==================>
Step: 2760, Train_acc:0.847545
Step: 2760, Val_acc:0.832804
==================>
Step: 2770, Train_acc:0.87069
Step: 2770, Val_acc:0.827928
==================>
Step: 2780, Train_acc:0.872739
Step: 2780, Val_acc:0.821674
==================>
Step: 2790, Train_acc:0.869883
Step: 2790, Val_acc:0.862996
==================>
Step: 2800, Train_acc:0.858827
Step: 2800, Val_acc:0.831498
==================>
2017-11-10 18:40:27.566682 ---> Validation_loss: 0.311255
Step: 2810, Train_acc:0.861805
Step: 2810, Val_acc:0.793759
==================>
Step: 2820, Train_acc:0.873408
Step: 2820, Val_acc:0.790217
==================>
Step: 2830, Train_acc:0.872913
Step: 2830, Val_acc:0.851743
==================>
Step: 2840, Train_acc:0.855479
Step: 2840, Val_acc:0.869701
==================>
Step: 2850, Train_acc:0.860634
Step: 2850, Val_acc:0.830688
==================>
Step: 2860, Train_acc:0.844199
Step: 2860, Val_acc:0.788748
==================>
Step: 2870, Train_acc:0.903608
Step: 2870, Val_acc:0.851615
==================>
Step: 2880, Train_acc:0.851021
Step: 2880, Val_acc:0.795944
==================>
Step: 2890, Train_acc:0.885125
Step: 2890, Val_acc:0.845193
==================>
Step: 2900, Train_acc:0.893168
Step: 2900, Val_acc:0.790272
==================>
2017-11-10 18:43:03.943058 ---> Validation_loss: 0.361453
Step: 2910, Train_acc:0.854698
Step: 2910, Val_acc:0.859849
==================>
Step: 2920, Train_acc:0.892942
Step: 2920, Val_acc:0.850522
==================>
Step: 2930, Train_acc:0.858812
Step: 2930, Val_acc:0.838287
==================>
Step: 2940, Train_acc:0.840505
Step: 2940, Val_acc:0.85665
==================>
Step: 2950, Train_acc:0.838844
Step: 2950, Val_acc:0.777809
==================>
Step: 2960, Train_acc:0.841973
Step: 2960, Val_acc:0.854238
==================>
Step: 2970, Train_acc:0.858562
Step: 2970, Val_acc:0.827766
==================>
Step: 2980, Train_acc:0.84822
Step: 2980, Val_acc:0.838124
==================>
Step: 2990, Train_acc:0.86827
Step: 2990, Val_acc:0.84681
==================>
Step: 3000, Train_acc:0.877969
Step: 3000, Val_acc:0.840798
==================>
****************** Epochs completed: 6******************
2017-11-10 18:45:39.825331 ---> Validation_loss: 0.292645
Step: 3010, Train_acc:0.873085
Step: 3010, Val_acc:0.886124
==================>
Step: 3020, Train_acc:0.864036
Step: 3020, Val_acc:0.863661
==================>
Step: 3030, Train_acc:0.887512
Step: 3030, Val_acc:0.848456
==================>
Step: 3040, Train_acc:0.862366
Step: 3040, Val_acc:0.785636
==================>
Step: 3050, Train_acc:0.854484
Step: 3050, Val_acc:0.852999
==================>
Step: 3060, Train_acc:0.860098
Step: 3060, Val_acc:0.847103
==================>
Step: 3070, Train_acc:0.837476
Step: 3070, Val_acc:0.855365
==================>
Step: 3080, Train_acc:0.835874
Step: 3080, Val_acc:0.874955
==================>
Step: 3090, Train_acc:0.889324
Step: 3090, Val_acc:0.798355
==================>
Step: 3100, Train_acc:0.874147
Step: 3100, Val_acc:0.823351
==================>
2017-11-10 18:48:16.560904 ---> Validation_loss: 0.317375
Step: 3110, Train_acc:0.88743
Step: 3110, Val_acc:0.853645
==================>
Step: 3120, Train_acc:0.858864
Step: 3120, Val_acc:0.820251
==================>
Step: 3130, Train_acc:0.854491
Step: 3130, Val_acc:0.800446