Namespace(batch_size=32, data_shape=300, dataset='voc', epochs=240, gpus='0,1,2,3', log_interval=100, lr=0.001, lr_decay=0.1, lr_decay_epoch='160,200', momentum=0.9, network='vgg16_atrous', num_workers=32, resume='', save_interval=10, save_prefix='ssd_300_vgg16_atrous_voc', seed=233, start_epoch=0, wd=0.0005)
Start training from [Epoch 0]
[Epoch 0][Batch 99], Speed: 92.447021 samples/sec, CrossEntropy=7.182524, SmoothL1=2.768559, accuracy=0.660349
[Epoch 0][Batch 199], Speed: 75.517937 samples/sec, CrossEntropy=6.111448, SmoothL1=2.551640, accuracy=0.705433
[Epoch 0][Batch 299], Speed: 72.216988 samples/sec, CrossEntropy=5.681694, SmoothL1=2.412826, accuracy=0.720396
[Epoch 0][Batch 399], Speed: 93.719610 samples/sec, CrossEntropy=5.429523, SmoothL1=2.296371, accuracy=0.727636
[Epoch 0][Batch 499], Speed: 91.579377 samples/sec, CrossEntropy=5.241380, SmoothL1=2.217668, accuracy=0.732310
[Epoch 0] Training cost: 198.206915, CrossEntropy=5.215453, SmoothL1=2.205441, accuracy=0.732902
[Epoch 0] Validation:
aeroplane=0.080252
bicycle=0.135449
bird=0.024775
boat=0.008941
bottle=0.002186
bus=0.089648
car=0.230829
cat=0.337195
chair=0.035145
cow=0.117627
diningtable=0.047916
dog=0.194008
horse=0.179304
motorbike=0.178756
person=0.369763
pottedplant=0.009124
sheep=0.086518
sofa=0.035818
train=0.079945
tvmonitor=0.048415
mAP=0.114581
[Epoch 1][Batch 99], Speed: 87.735818 samples/sec, CrossEntropy=4.352636, SmoothL1=1.844328, accuracy=0.752681
[Epoch 1][Batch 199], Speed: 92.475811 samples/sec, CrossEntropy=4.277152, SmoothL1=1.837585, accuracy=0.753168
[Epoch 1][Batch 299], Speed: 82.616980 samples/sec, CrossEntropy=4.217445, SmoothL1=1.828060, accuracy=0.753841
[Epoch 1][Batch 399], Speed: 93.781493 samples/sec, CrossEntropy=4.171121, SmoothL1=1.816448, accuracy=0.754662
[Epoch 1][Batch 499], Speed: 97.833534 samples/sec, CrossEntropy=4.120539, SmoothL1=1.796631, accuracy=0.755432
[Epoch 1] Training cost: 191.673599, CrossEntropy=4.111482, SmoothL1=1.794864, accuracy=0.755517
[Epoch 1] Validation:
aeroplane=0.334569
bicycle=0.298223
bird=0.307649
boat=0.024106
bottle=0.036071
bus=0.253218
car=0.601374
cat=0.537798
chair=0.083498
cow=0.273159
diningtable=0.099075
dog=0.324676
horse=0.355786
motorbike=0.354885
person=0.490556
pottedplant=0.069855
sheep=0.300548
sofa=0.138812
train=0.268500
tvmonitor=0.245076
mAP=0.269872
[Epoch 2][Batch 99], Speed: 93.129406 samples/sec, CrossEntropy=3.818571, SmoothL1=1.706131, accuracy=0.758971
[Epoch 2][Batch 199], Speed: 88.555851 samples/sec, CrossEntropy=3.782349, SmoothL1=1.714385, accuracy=0.759451
[Epoch 2][Batch 299], Speed: 84.458232 samples/sec, CrossEntropy=3.751173, SmoothL1=1.707619, accuracy=0.759895
[Epoch 2][Batch 399], Speed: 93.929425 samples/sec, CrossEntropy=3.717429, SmoothL1=1.689311, accuracy=0.760968
[Epoch 2][Batch 499], Speed: 90.587640 samples/sec, CrossEntropy=3.687258, SmoothL1=1.676611, accuracy=0.761770
[Epoch 2] Training cost: 191.628685, CrossEntropy=3.686468, SmoothL1=1.674733, accuracy=0.761899
[Epoch 2] Validation:
aeroplane=0.475284
bicycle=0.444206
bird=0.449821
boat=0.080601
bottle=0.128271
bus=0.453216
car=0.659597
cat=0.659092
chair=0.229877
cow=0.320088
diningtable=0.158713
dog=0.562494
horse=0.299988
motorbike=0.423761
person=0.539360
pottedplant=0.119163
sheep=0.296689
sofa=0.328692
train=0.385938
tvmonitor=0.401238
mAP=0.370804
[Epoch 3][Batch 99], Speed: 93.477386 samples/sec, CrossEntropy=3.484466, SmoothL1=1.626930, accuracy=0.766789
[Epoch 3][Batch 199], Speed: 92.800303 samples/sec, CrossEntropy=3.473538, SmoothL1=1.629044, accuracy=0.766731
[Epoch 3][Batch 299], Speed: 92.171490 samples/sec, CrossEntropy=3.464717, SmoothL1=1.621444, accuracy=0.767007
[Epoch 3][Batch 399], Speed: 93.635071 samples/sec, CrossEntropy=3.447769, SmoothL1=1.609599, accuracy=0.767724
[Epoch 3][Batch 499], Speed: 85.530729 samples/sec, CrossEntropy=3.434060, SmoothL1=1.602433, accuracy=0.768358
[Epoch 3] Training cost: 192.119103, CrossEntropy=3.428697, SmoothL1=1.599942, accuracy=0.768491
[Epoch 3] Validation:
aeroplane=0.540545
bicycle=0.602543
bird=0.481859
boat=0.216172
bottle=0.169204
bus=0.572680
car=0.696129
cat=0.689287
chair=0.316945
cow=0.439123
diningtable=0.307796
dog=0.615455
horse=0.493758
motorbike=0.565862
person=0.592135
pottedplant=0.115435
sheep=0.453249
sofa=0.493841
train=0.523526
tvmonitor=0.484685
mAP=0.468512
[Epoch 4][Batch 99], Speed: 91.652858 samples/sec, CrossEntropy=3.274576, SmoothL1=1.549084, accuracy=0.771873
[Epoch 4][Batch 199], Speed: 87.625956 samples/sec, CrossEntropy=3.257358, SmoothL1=1.528152, accuracy=0.772624
[Epoch 4][Batch 299], Speed: 84.617546 samples/sec, CrossEntropy=3.256265, SmoothL1=1.530673, accuracy=0.772611
[Epoch 4][Batch 399], Speed: 89.199588 samples/sec, CrossEntropy=3.250352, SmoothL1=1.529170, accuracy=0.773251
[Epoch 4][Batch 499], Speed: 95.402334 samples/sec, CrossEntropy=3.237188, SmoothL1=1.523721, accuracy=0.773448
[Epoch 4] Training cost: 191.788936, CrossEntropy=3.231534, SmoothL1=1.521836, accuracy=0.773653
[Epoch 4] Validation:
aeroplane=0.595224
bicycle=0.625590
bird=0.498797
boat=0.299248
bottle=0.209427
bus=0.603292
car=0.736443
cat=0.713252
chair=0.302221
cow=0.425670
diningtable=0.353803
dog=0.663035
horse=0.646975
motorbike=0.634170
person=0.628831
pottedplant=0.188048
sheep=0.426415
sofa=0.477551
train=0.628203
tvmonitor=0.523775
mAP=0.508998
[Epoch 5][Batch 99], Speed: 89.844692 samples/sec, CrossEntropy=3.145900, SmoothL1=1.467151, accuracy=0.776881
[Epoch 5][Batch 199], Speed: 89.500443 samples/sec, CrossEntropy=3.141537, SmoothL1=1.471711, accuracy=0.777137
[Epoch 5][Batch 299], Speed: 92.587640 samples/sec, CrossEntropy=3.124883, SmoothL1=1.474498, accuracy=0.777757
[Epoch 5][Batch 399], Speed: 93.320360 samples/sec, CrossEntropy=3.119229, SmoothL1=1.475426, accuracy=0.777879
[Epoch 5][Batch 499], Speed: 95.970781 samples/sec, CrossEntropy=3.121626, SmoothL1=1.478074, accuracy=0.777808
[Epoch 5] Training cost: 191.913315, CrossEntropy=3.121624, SmoothL1=1.476401, accuracy=0.777877
[Epoch 5] Validation:
aeroplane=0.580445
bicycle=0.664227
bird=0.540777
boat=0.326947
bottle=0.235158
bus=0.663567
car=0.744768
cat=0.761530
chair=0.342519
cow=0.376597
diningtable=0.426465
dog=0.716167
horse=0.605759
motorbike=0.652755
person=0.632341
pottedplant=0.198805
sheep=0.482173
sofa=0.517266
train=0.680937
tvmonitor=0.529557
mAP=0.533938
[Epoch 6][Batch 99], Speed: 91.729089 samples/sec, CrossEntropy=3.029643, SmoothL1=1.464300, accuracy=0.782293
[Epoch 6][Batch 199], Speed: 92.330704 samples/sec, CrossEntropy=3.035624, SmoothL1=1.454912, accuracy=0.780871
[Epoch 6][Batch 299], Speed: 93.032062 samples/sec, CrossEntropy=3.028691, SmoothL1=1.446187, accuracy=0.781270
[Epoch 6][Batch 399], Speed: 85.709441 samples/sec, CrossEntropy=3.028272, SmoothL1=1.445395, accuracy=0.780987
[Epoch 6][Batch 499], Speed: 88.192579 samples/sec, CrossEntropy=3.020819, SmoothL1=1.439514, accuracy=0.781410
[Epoch 6] Training cost: 192.574202, CrossEntropy=3.018071, SmoothL1=1.438106, accuracy=0.781449
[Epoch 6] Validation:
aeroplane=0.636612
bicycle=0.668747
bird=0.566637
boat=0.417726
bottle=0.273511
bus=0.684648
car=0.749559
cat=0.776837
chair=0.360581
cow=0.520769
diningtable=0.521583
dog=0.729472
horse=0.677911
motorbike=0.677813
person=0.647326
pottedplant=0.221440
sheep=0.554344
sofa=0.604301
train=0.721705
tvmonitor=0.575461
mAP=0.579349
[Epoch 7][Batch 99], Speed: 85.860825 samples/sec, CrossEntropy=2.974062, SmoothL1=1.408688, accuracy=0.782145
[Epoch 7][Batch 199], Speed: 90.677055 samples/sec, CrossEntropy=2.988465, SmoothL1=1.425037, accuracy=0.782769
[Epoch 7][Batch 299], Speed: 90.315773 samples/sec, CrossEntropy=2.967546, SmoothL1=1.415699, accuracy=0.783411
[Epoch 7][Batch 399], Speed: 92.926427 samples/sec, CrossEntropy=2.968551, SmoothL1=1.413510, accuracy=0.783153
[Epoch 7][Batch 499], Speed: 91.802433 samples/sec, CrossEntropy=2.956663, SmoothL1=1.406439, accuracy=0.783868
[Epoch 7] Training cost: 192.389031, CrossEntropy=2.952922, SmoothL1=1.403891, accuracy=0.783930
[Epoch 7] Validation:
aeroplane=0.654484
bicycle=0.708714
bird=0.590171
boat=0.458387
bottle=0.272124
bus=0.693569
car=0.757859
cat=0.790921
chair=0.336324
cow=0.548423
diningtable=0.550348
dog=0.746403
horse=0.749584
motorbike=0.710103
person=0.666655
pottedplant=0.204871
sheep=0.550001
sofa=0.579794
train=0.729860
tvmonitor=0.608971
mAP=0.595378
[Epoch 8][Batch 99], Speed: 92.940713 samples/sec, CrossEntropy=2.864247, SmoothL1=1.365950, accuracy=0.787671
[Epoch 8][Batch 199], Speed: 88.858019 samples/sec, CrossEntropy=2.890938, SmoothL1=1.384621, accuracy=0.786201
[Epoch 8][Batch 299], Speed: 91.649666 samples/sec, CrossEntropy=2.895385, SmoothL1=1.385951, accuracy=0.786220
[Epoch 8][Batch 399], Speed: 91.833211 samples/sec, CrossEntropy=2.889345, SmoothL1=1.372744, accuracy=0.786078
[Epoch 8][Batch 499], Speed: 93.843064 samples/sec, CrossEntropy=2.879678, SmoothL1=1.368193, accuracy=0.786245
[Epoch 8] Training cost: 191.815854, CrossEntropy=2.877921, SmoothL1=1.368176, accuracy=0.786317
[Epoch 8] Validation:
aeroplane=0.650418
bicycle=0.715607
bird=0.614287
boat=0.423964
bottle=0.258346
bus=0.729961
car=0.763351
cat=0.814183
chair=0.376472
cow=0.584629
diningtable=0.569946
dog=0.747169
horse=0.775782
motorbike=0.728827
person=0.653746
pottedplant=0.277089
sheep=0.610073
sofa=0.621853
train=0.754631
tvmonitor=0.585613
mAP=0.612797
[Epoch 9][Batch 99], Speed: 86.404446 samples/sec, CrossEntropy=2.819460, SmoothL1=1.357635, accuracy=0.788601
[Epoch 9][Batch 199], Speed: 95.955412 samples/sec, CrossEntropy=2.835740, SmoothL1=1.365914, accuracy=0.788630
[Epoch 9][Batch 299], Speed: 89.350119 samples/sec, CrossEntropy=2.847715, SmoothL1=1.375630, accuracy=0.787958
[Epoch 9][Batch 399], Speed: 91.634148 samples/sec, CrossEntropy=2.838355, SmoothL1=1.359453, accuracy=0.788350
[Epoch 9][Batch 499], Speed: 98.538293 samples/sec, CrossEntropy=2.831332, SmoothL1=1.350243, accuracy=0.788526
[Epoch 9] Training cost: 191.953331, CrossEntropy=2.830126, SmoothL1=1.349805, accuracy=0.788600
[Epoch 9] Validation:
aeroplane=0.638329
bicycle=0.740995
bird=0.534847
boat=0.465978
bottle=0.273544
bus=0.676953
car=0.760453
cat=0.779479
chair=0.371131
cow=0.495595
diningtable=0.599303
dog=0.714274
horse=0.724777
motorbike=0.721423
person=0.672370
pottedplant=0.286027
sheep=0.560837
sofa=0.633425
train=0.722882
tvmonitor=0.603472
mAP=0.598805
[Epoch 10][Batch 99], Speed: 90.850325 samples/sec, CrossEntropy=2.781604, SmoothL1=1.325337, accuracy=0.790136
[Epoch 10][Batch 199], Speed: 95.360783 samples/sec, CrossEntropy=2.788136, SmoothL1=1.329112, accuracy=0.790164
[Epoch 10][Batch 299], Speed: 94.851574 samples/sec, CrossEntropy=2.787684, SmoothL1=1.323434, accuracy=0.790485
[Epoch 10][Batch 399], Speed: 89.775042 samples/sec, CrossEntropy=2.781445, SmoothL1=1.316746, accuracy=0.790964
[Epoch 10][Batch 499], Speed: 99.146454 samples/sec, CrossEntropy=2.781025, SmoothL1=1.315324, accuracy=0.790771
[Epoch 10] Training cost: 192.122175, CrossEntropy=2.780684, SmoothL1=1.316563, accuracy=0.790692
[Epoch 10] Validation:
aeroplane=0.670847
bicycle=0.729713
bird=0.605548
boat=0.540443
bottle=0.329793
bus=0.746576
car=0.766453
cat=0.793875
chair=0.412003
cow=0.636403
diningtable=0.592024
dog=0.787860
horse=0.775244
motorbike=0.735203
person=0.691308
pottedplant=0.293375
sheep=0.634837
sofa=0.606641
train=0.769215
tvmonitor=0.627521
mAP=0.637244
[Epoch 11][Batch 99], Speed: 91.803124 samples/sec, CrossEntropy=2.730461, SmoothL1=1.292444, accuracy=0.793832
[Epoch 11][Batch 199], Speed: 91.065947 samples/sec, CrossEntropy=2.738578, SmoothL1=1.295395, accuracy=0.792796
[Epoch 11][Batch 299], Speed: 82.176199 samples/sec, CrossEntropy=2.743088, SmoothL1=1.295224, accuracy=0.792708
[Epoch 11][Batch 399], Speed: 90.679505 samples/sec, CrossEntropy=2.741766, SmoothL1=1.296174, accuracy=0.792583
[Epoch 11][Batch 499], Speed: 91.427039 samples/sec, CrossEntropy=2.741200, SmoothL1=1.291837, accuracy=0.792609
[Epoch 11] Training cost: 191.771700, CrossEntropy=2.739439, SmoothL1=1.290903, accuracy=0.792637
[Epoch 11] Validation:
aeroplane=0.674225
bicycle=0.764232
bird=0.595115
boat=0.506454
bottle=0.287790
bus=0.749662
car=0.787230
cat=0.799330
chair=0.399638
cow=0.619709
diningtable=0.629121
dog=0.769885
horse=0.776041
motorbike=0.752058
person=0.675642
pottedplant=0.263474
sheep=0.571269
sofa=0.640616
train=0.781162
tvmonitor=0.643434
mAP=0.634304
[Epoch 12][Batch 99], Speed: 85.960412 samples/sec, CrossEntropy=2.667955, SmoothL1=1.266932, accuracy=0.796330
[Epoch 12][Batch 199], Speed: 91.265960 samples/sec, CrossEntropy=2.695808, SmoothL1=1.289239, accuracy=0.794239
[Epoch 12][Batch 299], Speed: 72.278707 samples/sec, CrossEntropy=2.705035, SmoothL1=1.290946, accuracy=0.793777
[Epoch 12][Batch 399], Speed: 89.925535 samples/sec, CrossEntropy=2.694844, SmoothL1=1.280815, accuracy=0.794336
[Epoch 12][Batch 499], Speed: 95.055385 samples/sec, CrossEntropy=2.701076, SmoothL1=1.284622, accuracy=0.793959
[Epoch 12] Training cost: 191.991792, CrossEntropy=2.697815, SmoothL1=1.283224, accuracy=0.794026
[Epoch 12] Validation:
aeroplane=0.698475
bicycle=0.749707
bird=0.629186
boat=0.501984
bottle=0.290633
bus=0.740939
car=0.780407
cat=0.837076
chair=0.435651
cow=0.661473
diningtable=0.608455
dog=0.782606
horse=0.775792
motorbike=0.759095
person=0.696372
pottedplant=0.342092
sheep=0.652577
sofa=0.671947
train=0.785169
tvmonitor=0.656077
mAP=0.652786
[Epoch 13][Batch 99], Speed: 92.728560 samples/sec, CrossEntropy=2.645683, SmoothL1=1.254334, accuracy=0.796736
[Epoch 13][Batch 199], Speed: 89.842587 samples/sec, CrossEntropy=2.677728, SmoothL1=1.283777, accuracy=0.795213
[Epoch 13][Batch 299], Speed: 90.973483 samples/sec, CrossEntropy=2.680580, SmoothL1=1.277663, accuracy=0.794983
[Epoch 13][Batch 399], Speed: 86.363804 samples/sec, CrossEntropy=2.678981, SmoothL1=1.269129, accuracy=0.795727
[Epoch 13][Batch 499], Speed: 94.648302 samples/sec, CrossEntropy=2.671129, SmoothL1=1.265270, accuracy=0.795991
[Epoch 13] Training cost: 191.447024, CrossEntropy=2.671048, SmoothL1=1.263958, accuracy=0.795919
[Epoch 13] Validation:
aeroplane=0.695930
bicycle=0.759046
bird=0.632217
boat=0.545912
bottle=0.324252
bus=0.760810
car=0.783115
cat=0.811133
chair=0.438009
cow=0.674030
diningtable=0.632111
dog=0.785128
horse=0.797611
motorbike=0.754776
person=0.699497
pottedplant=0.348476
sheep=0.582065
sofa=0.669390
train=0.779491
tvmonitor=0.665602
mAP=0.656930
[Epoch 14][Batch 99], Speed: 95.551347 samples/sec, CrossEntropy=2.607297, SmoothL1=1.220557, accuracy=0.798343
[Epoch 14][Batch 199], Speed: 97.514173 samples/sec, CrossEntropy=2.625689, SmoothL1=1.238135, accuracy=0.797370
[Epoch 14][Batch 299], Speed: 94.480271 samples/sec, CrossEntropy=2.635573, SmoothL1=1.242952, accuracy=0.796639
[Epoch 14][Batch 399], Speed: 88.567831 samples/sec, CrossEntropy=2.633249, SmoothL1=1.237153, accuracy=0.796470
[Epoch 14][Batch 499], Speed: 99.982441 samples/sec, CrossEntropy=2.628727, SmoothL1=1.236782, accuracy=0.796967
[Epoch 14] Training cost: 192.234820, CrossEntropy=2.628127, SmoothL1=1.237828, accuracy=0.797023
[Epoch 14] Validation:
aeroplane=0.695926
bicycle=0.756919
bird=0.637815
boat=0.573342
bottle=0.331081
bus=0.735668
car=0.790640
cat=0.818469
chair=0.410077
cow=0.665791
diningtable=0.647392
dog=0.752019
horse=0.789581
motorbike=0.781735
person=0.696258
pottedplant=0.339865
sheep=0.630105
sofa=0.673469
train=0.792012
tvmonitor=0.647738
mAP=0.658295
[Epoch 15][Batch 99], Speed: 85.757743 samples/sec, CrossEntropy=2.590278, SmoothL1=1.238813, accuracy=0.799925
[Epoch 15][Batch 199], Speed: 96.929592 samples/sec, CrossEntropy=2.591277, SmoothL1=1.229015, accuracy=0.799361
[Epoch 15][Batch 299], Speed: 92.986945 samples/sec, CrossEntropy=2.605431, SmoothL1=1.227681, accuracy=0.798839
[Epoch 15][Batch 399], Speed: 89.423103 samples/sec, CrossEntropy=2.608246, SmoothL1=1.228643, accuracy=0.798976
[Epoch 15][Batch 499], Speed: 88.100072 samples/sec, CrossEntropy=2.605984, SmoothL1=1.230458, accuracy=0.798919
[Epoch 15] Training cost: 192.592482, CrossEntropy=2.602865, SmoothL1=1.229413, accuracy=0.798989
[Epoch 15] Validation:
aeroplane=0.706550
bicycle=0.767294
bird=0.624085
boat=0.565386
bottle=0.358773
bus=0.766152
car=0.800993
cat=0.768962
chair=0.440502
cow=0.694431
diningtable=0.658218
dog=0.755032
horse=0.801452
motorbike=0.770525
person=0.687349
pottedplant=0.337173
sheep=0.629541
sofa=0.657815
train=0.805446
tvmonitor=0.641968
mAP=0.661882
[Epoch 16][Batch 99], Speed: 82.657276 samples/sec, CrossEntropy=2.554451, SmoothL1=1.191436, accuracy=0.800909
[Epoch 16][Batch 199], Speed: 90.576575 samples/sec, CrossEntropy=2.560904, SmoothL1=1.206712, accuracy=0.800094
[Epoch 16][Batch 299], Speed: 85.464992 samples/sec, CrossEntropy=2.565733, SmoothL1=1.205789, accuracy=0.800060
[Epoch 16][Batch 399], Speed: 89.390346 samples/sec, CrossEntropy=2.568047, SmoothL1=1.204550, accuracy=0.799662
[Epoch 16][Batch 499], Speed: 96.310495 samples/sec, CrossEntropy=2.566942, SmoothL1=1.205531, accuracy=0.799414
[Epoch 16] Training cost: 192.068861, CrossEntropy=2.566007, SmoothL1=1.205203, accuracy=0.799452
[Epoch 16] Validation:
aeroplane=0.704205
bicycle=0.761856
bird=0.653048
boat=0.559812
bottle=0.337322
bus=0.764033
car=0.794022
cat=0.841000
chair=0.459954
cow=0.689443
diningtable=0.642479
dog=0.795153
horse=0.825658
motorbike=0.748293
person=0.711946
pottedplant=0.350326
sheep=0.641791
sofa=0.658538
train=0.798048
tvmonitor=0.651865
mAP=0.669440
[Epoch 17][Batch 99], Speed: 90.760692 samples/sec, CrossEntropy=2.547634, SmoothL1=1.198653, accuracy=0.800844
[Epoch 17][Batch 199], Speed: 94.858546 samples/sec, CrossEntropy=2.548561, SmoothL1=1.203357, accuracy=0.800883
[Epoch 17][Batch 299], Speed: 91.585376 samples/sec, CrossEntropy=2.559408, SmoothL1=1.204219, accuracy=0.800133
[Epoch 17][Batch 399], Speed: 90.689247 samples/sec, CrossEntropy=2.561229, SmoothL1=1.203259, accuracy=0.800439
[Epoch 17][Batch 499], Speed: 89.085973 samples/sec, CrossEntropy=2.554822, SmoothL1=1.197375, accuracy=0.800999
[Epoch 17] Training cost: 191.760885, CrossEntropy=2.554384, SmoothL1=1.197289, accuracy=0.801114
[Epoch 17] Validation:
aeroplane=0.721252
bicycle=0.777390
bird=0.637251
boat=0.574687
bottle=0.350483
bus=0.769677
car=0.801424
cat=0.823581
chair=0.428883
cow=0.713342
diningtable=0.682349
dog=0.767505
horse=0.798331
motorbike=0.778359
person=0.701756
pottedplant=0.360219
sheep=0.617837
sofa=0.672043
train=0.796674
tvmonitor=0.670061
mAP=0.672155
[Epoch 18][Batch 99], Speed: 89.590354 samples/sec, CrossEntropy=2.476140, SmoothL1=1.164790, accuracy=0.803412
[Epoch 18][Batch 199], Speed: 91.370898 samples/sec, CrossEntropy=2.504401, SmoothL1=1.176947, accuracy=0.802516
[Epoch 18][Batch 299], Speed: 94.650438 samples/sec, CrossEntropy=2.517073, SmoothL1=1.179451, accuracy=0.802128
[Epoch 18][Batch 399], Speed: 87.811760 samples/sec, CrossEntropy=2.521695, SmoothL1=1.190116, accuracy=0.802154
[Epoch 18][Batch 499], Speed: 101.136031 samples/sec, CrossEntropy=2.523230, SmoothL1=1.192435, accuracy=0.802148
[Epoch 18] Training cost: 192.713253, CrossEntropy=2.523045, SmoothL1=1.191467, accuracy=0.802322
[Epoch 18] Validation:
aeroplane=0.724720
bicycle=0.767070
bird=0.631627
boat=0.598972
bottle=0.320518
bus=0.772885
car=0.798293
cat=0.831129
chair=0.463226
cow=0.708948
diningtable=0.670642
dog=0.794420
horse=0.785801
motorbike=0.771831
person=0.696649
pottedplant=0.347641
sheep=0.657937
sofa=0.698797
train=0.805411
tvmonitor=0.655590
mAP=0.675105
[Epoch 19][Batch 99], Speed: 87.300796 samples/sec, CrossEntropy=2.471146, SmoothL1=1.174598, accuracy=0.805915
[Epoch 19][Batch 199], Speed: 78.451041 samples/sec, CrossEntropy=2.509667, SmoothL1=1.187222, accuracy=0.804018
[Epoch 19][Batch 299], Speed: 64.830243 samples/sec, CrossEntropy=2.503893, SmoothL1=1.176941, accuracy=0.803982
[Epoch 19][Batch 399], Speed: 86.472973 samples/sec, CrossEntropy=2.501959, SmoothL1=1.175514, accuracy=0.803656
[Epoch 19][Batch 499], Speed: 92.102169 samples/sec, CrossEntropy=2.506993, SmoothL1=1.178366, accuracy=0.803464
[Epoch 19] Training cost: 192.714946, CrossEntropy=2.507389, SmoothL1=1.176293, accuracy=0.803436
[Epoch 19] Validation:
aeroplane=0.712312
bicycle=0.776535
bird=0.622276
boat=0.581718
bottle=0.345471
bus=0.772856
car=0.804557
cat=0.825766
chair=0.476724
cow=0.748806
diningtable=0.690498
dog=0.790898
horse=0.809413
motorbike=0.758308
person=0.715767
pottedplant=0.319945
sheep=0.655206
sofa=0.714899
train=0.805104
tvmonitor=0.668508
mAP=0.679778
[Epoch 20][Batch 99], Speed: 83.577730 samples/sec, CrossEntropy=2.456443, SmoothL1=1.146622, accuracy=0.806850
[Epoch 20][Batch 199], Speed: 87.488530 samples/sec, CrossEntropy=2.492387, SmoothL1=1.172249, accuracy=0.804467
[Epoch 20][Batch 299], Speed: 79.352662 samples/sec, CrossEntropy=2.498185, SmoothL1=1.173795, accuracy=0.803634
[Epoch 20][Batch 399], Speed: 87.797572 samples/sec, CrossEntropy=2.489423, SmoothL1=1.167537, accuracy=0.804543
[Epoch 20][Batch 499], Speed: 91.488924 samples/sec, CrossEntropy=2.483872, SmoothL1=1.161166, accuracy=0.804804
[Epoch 20] Training cost: 194.053097, CrossEntropy=2.484399, SmoothL1=1.161580, accuracy=0.804696
[Epoch 20] Validation:
aeroplane=0.715039
bicycle=0.785521
bird=0.628922
boat=0.552229
bottle=0.343185
bus=0.772092
car=0.800769
cat=0.835741
chair=0.449764
cow=0.729545
diningtable=0.652549
dog=0.792907
horse=0.807419
motorbike=0.786258
person=0.713326
pottedplant=0.364399
sheep=0.650077
sofa=0.702543
train=0.806535
tvmonitor=0.688669
mAP=0.678875
[Epoch 21][Batch 99], Speed: 86.928074 samples/sec, CrossEntropy=2.489702, SmoothL1=1.140049, accuracy=0.805610
[Epoch 21][Batch 199], Speed: 94.796104 samples/sec, CrossEntropy=2.476299, SmoothL1=1.146990, accuracy=0.805337
[Epoch 21][Batch 299], Speed: 87.632764 samples/sec, CrossEntropy=2.471491, SmoothL1=1.155468, accuracy=0.805280
[Epoch 21][Batch 399], Speed: 89.154439 samples/sec, CrossEntropy=2.460368, SmoothL1=1.148651, accuracy=0.805866
[Epoch 21][Batch 499], Speed: 96.077539 samples/sec, CrossEntropy=2.461200, SmoothL1=1.145088, accuracy=0.805695
[Epoch 21] Training cost: 194.118013, CrossEntropy=2.459990, SmoothL1=1.145802, accuracy=0.805773
[Epoch 21] Validation:
aeroplane=0.725060
bicycle=0.786298
bird=0.695714
boat=0.603005
bottle=0.366464
bus=0.764340
car=0.803266
cat=0.853705
chair=0.462953
cow=0.730627
diningtable=0.662419
dog=0.806216
horse=0.819871
motorbike=0.785209
person=0.724442
pottedplant=0.387877
sheep=0.682583
sofa=0.728958
train=0.814354
tvmonitor=0.677178
mAP=0.694027
[Epoch 22][Batch 99], Speed: 90.100056 samples/sec, CrossEntropy=2.412315, SmoothL1=1.125449, accuracy=0.807807
[Epoch 22][Batch 199], Speed: 87.047368 samples/sec, CrossEntropy=2.424389, SmoothL1=1.130568, accuracy=0.807664
[Epoch 22][Batch 299], Speed: 81.483736 samples/sec, CrossEntropy=2.432603, SmoothL1=1.138146, accuracy=0.807422
[Epoch 22][Batch 399], Speed: 94.598470 samples/sec, CrossEntropy=2.434243, SmoothL1=1.137807, accuracy=0.807110
[Epoch 22][Batch 499], Speed: 97.557764 samples/sec, CrossEntropy=2.434133, SmoothL1=1.138636, accuracy=0.807045
[Epoch 22] Training cost: 194.461910, CrossEntropy=2.432994, SmoothL1=1.137829, accuracy=0.807230
[Epoch 22] Validation:
aeroplane=0.716630
bicycle=0.775661
bird=0.656453
boat=0.641231
bottle=0.348928
bus=0.781397
car=0.804915
cat=0.850338
chair=0.500078
cow=0.740311
diningtable=0.673283
dog=0.785316
horse=0.774456
motorbike=0.757008
person=0.711702
pottedplant=0.373395
sheep=0.650202
sofa=0.694093
train=0.826538
tvmonitor=0.661140
mAP=0.686154
[Epoch 23][Batch 99], Speed: 91.735923 samples/sec, CrossEntropy=2.431521, SmoothL1=1.160016, accuracy=0.806849
[Epoch 23][Batch 199], Speed: 84.956747 samples/sec, CrossEntropy=2.420063, SmoothL1=1.139845, accuracy=0.808436
[Epoch 23][Batch 299], Speed: 93.581602 samples/sec, CrossEntropy=2.425593, SmoothL1=1.139580, accuracy=0.807624
[Epoch 23][Batch 399], Speed: 86.480662 samples/sec, CrossEntropy=2.414069, SmoothL1=1.132578, accuracy=0.808164
[Epoch 23][Batch 499], Speed: 88.807456 samples/sec, CrossEntropy=2.419905, SmoothL1=1.134553, accuracy=0.807759
[Epoch 23] Training cost: 194.118674, CrossEntropy=2.424063, SmoothL1=1.134996, accuracy=0.807626
[Epoch 23] Validation:
aeroplane=0.718235
bicycle=0.782613
bird=0.660016
boat=0.607587
bottle=0.317819
bus=0.765917
car=0.809584
cat=0.834590
chair=0.497142
cow=0.696136
diningtable=0.693573
dog=0.797032
horse=0.808549
motorbike=0.767316
person=0.721855
pottedplant=0.360354
sheep=0.667762
sofa=0.702724
train=0.827500
tvmonitor=0.680498
mAP=0.685840
[Epoch 24][Batch 99], Speed: 93.468597 samples/sec, CrossEntropy=2.396912, SmoothL1=1.123768, accuracy=0.811103
[Epoch 24][Batch 199], Speed: 85.056026 samples/sec, CrossEntropy=2.391825, SmoothL1=1.119387, accuracy=0.810712
[Epoch 24][Batch 299], Speed: 82.984095 samples/sec, CrossEntropy=2.400748, SmoothL1=1.123657, accuracy=0.809787
[Epoch 24][Batch 399], Speed: 90.433828 samples/sec, CrossEntropy=2.401597, SmoothL1=1.126743, accuracy=0.809531
[Epoch 24][Batch 499], Speed: 90.358456 samples/sec, CrossEntropy=2.406233, SmoothL1=1.122897, accuracy=0.809169
[Epoch 24] Training cost: 193.550459, CrossEntropy=2.405673, SmoothL1=1.122840, accuracy=0.809126
[Epoch 24] Validation:
aeroplane=0.732329
bicycle=0.790621
bird=0.683381
boat=0.624853
bottle=0.368092
bus=0.774473
car=0.810861
cat=0.851161
chair=0.485866
cow=0.748037
diningtable=0.682345
dog=0.815493
horse=0.825184
motorbike=0.782412
person=0.727146
pottedplant=0.379241
sheep=0.683109
sofa=0.719363
train=0.805402
tvmonitor=0.674438
mAP=0.698190
[Epoch 25][Batch 99], Speed: 85.179964 samples/sec, CrossEntropy=2.350221, SmoothL1=1.088248, accuracy=0.811288
[Epoch 25][Batch 199], Speed: 87.383097 samples/sec, CrossEntropy=2.381395, SmoothL1=1.117373, accuracy=0.809197
[Epoch 25][Batch 299], Speed: 88.100823 samples/sec, CrossEntropy=2.384604, SmoothL1=1.114697, accuracy=0.809353
[Epoch 25][Batch 399], Speed: 87.293585 samples/sec, CrossEntropy=2.392098, SmoothL1=1.117593, accuracy=0.809007
[Epoch 25][Batch 499], Speed: 90.986496 samples/sec, CrossEntropy=2.393711, SmoothL1=1.114265, accuracy=0.808842
[Epoch 25] Training cost: 193.724708, CrossEntropy=2.392030, SmoothL1=1.112236, accuracy=0.808819
[Epoch 25] Validation:
aeroplane=0.728397
bicycle=0.781058
bird=0.654728
boat=0.617728
bottle=0.382230
bus=0.763701
car=0.806475
cat=0.844505
chair=0.509256
cow=0.746553
diningtable=0.683680
dog=0.808649
horse=0.828946
motorbike=0.779279
person=0.730830
pottedplant=0.370271
sheep=0.692416
sofa=0.710759
train=0.811065
tvmonitor=0.688203
mAP=0.696936
[Epoch 26][Batch 99], Speed: 84.347302 samples/sec, CrossEntropy=2.318062, SmoothL1=1.084307, accuracy=0.812279
[Epoch 26][Batch 199], Speed: 91.852694 samples/sec, CrossEntropy=2.346360, SmoothL1=1.096972, accuracy=0.812116
[Epoch 26][Batch 299], Speed: 93.805548 samples/sec, CrossEntropy=2.351323, SmoothL1=1.102034, accuracy=0.811764
[Epoch 26][Batch 399], Speed: 88.949355 samples/sec, CrossEntropy=2.350118, SmoothL1=1.098655, accuracy=0.811601
[Epoch 26][Batch 499], Speed: 89.832425 samples/sec, CrossEntropy=2.361603, SmoothL1=1.096524, accuracy=0.811193
[Epoch 26] Training cost: 194.026925, CrossEntropy=2.363715, SmoothL1=1.095940, accuracy=0.811097
[Epoch 26] Validation:
aeroplane=0.726505
bicycle=0.785153
bird=0.667688
boat=0.637996
bottle=0.371224
bus=0.787970
car=0.815032
cat=0.844099
chair=0.510259
cow=0.722629
diningtable=0.700101
dog=0.815827
horse=0.821006
motorbike=0.793491
person=0.740136
pottedplant=0.421737
sheep=0.699687
sofa=0.734143
train=0.815367
tvmonitor=0.703213
mAP=0.705663
[Epoch 27][Batch 99], Speed: 84.513913 samples/sec, CrossEntropy=2.332822, SmoothL1=1.077099, accuracy=0.813050
[Epoch 27][Batch 199], Speed: 89.583298 samples/sec, CrossEntropy=2.345249, SmoothL1=1.086085, accuracy=0.811780
[Epoch 27][Batch 299], Speed: 86.186506 samples/sec, CrossEntropy=2.345798, SmoothL1=1.090638, accuracy=0.811848
[Epoch 27][Batch 399], Speed: 92.830085 samples/sec, CrossEntropy=2.350286, SmoothL1=1.087834, accuracy=0.811789
[Epoch 27][Batch 499], Speed: 91.589626 samples/sec, CrossEntropy=2.344443, SmoothL1=1.081645, accuracy=0.812114
[Epoch 27] Training cost: 194.204354, CrossEntropy=2.343754, SmoothL1=1.080301, accuracy=0.812093
[Epoch 27] Validation:
aeroplane=0.713811
bicycle=0.781840
bird=0.657818
boat=0.623985
bottle=0.374756
bus=0.763580
car=0.820264
cat=0.844235
chair=0.513106
cow=0.721758
diningtable=0.713079
dog=0.814281
horse=0.818563
motorbike=0.778322
person=0.719325
pottedplant=0.397423
sheep=0.695954
sofa=0.694927
train=0.808379
tvmonitor=0.693389
mAP=0.697440
[Epoch 28][Batch 99], Speed: 90.013224 samples/sec, CrossEntropy=2.354479, SmoothL1=1.089990, accuracy=0.811979
[Epoch 28][Batch 199], Speed: 89.539611 samples/sec, CrossEntropy=2.359159, SmoothL1=1.102927, accuracy=0.811150
[Epoch 28][Batch 299], Speed: 95.432588 samples/sec, CrossEntropy=2.352620, SmoothL1=1.094685, accuracy=0.811439
[Epoch 28][Batch 399], Speed: 89.753610 samples/sec, CrossEntropy=2.356876, SmoothL1=1.095645, accuracy=0.811233
[Epoch 28][Batch 499], Speed: 93.933698 samples/sec, CrossEntropy=2.343779, SmoothL1=1.085899, accuracy=0.811758
[Epoch 28] Training cost: 193.108285, CrossEntropy=2.341347, SmoothL1=1.083259, accuracy=0.811908
[Epoch 28] Validation:
aeroplane=0.736531
bicycle=0.790001
bird=0.658019
boat=0.619466
bottle=0.397111
bus=0.788270
car=0.812509
cat=0.850043
chair=0.508636
cow=0.781033
diningtable=0.680970
dog=0.806044
horse=0.829680
motorbike=0.798416
person=0.736415
pottedplant=0.368285
sheep=0.685898
sofa=0.730982
train=0.822862
tvmonitor=0.680102
mAP=0.704064
[Epoch 29][Batch 99], Speed: 87.604966 samples/sec, CrossEntropy=2.314184, SmoothL1=1.080880, accuracy=0.814143
[Epoch 29][Batch 199], Speed: 89.581444 samples/sec, CrossEntropy=2.328153, SmoothL1=1.081254, accuracy=0.813159
[Epoch 29][Batch 299], Speed: 90.717996 samples/sec, CrossEntropy=2.329108, SmoothL1=1.074744, accuracy=0.813415
[Epoch 29][Batch 399], Speed: 83.316921 samples/sec, CrossEntropy=2.328993, SmoothL1=1.076778, accuracy=0.813074
[Epoch 29][Batch 499], Speed: 91.150984 samples/sec, CrossEntropy=2.323760, SmoothL1=1.074872, accuracy=0.813607
[Epoch 29] Training cost: 193.403768, CrossEntropy=2.324320, SmoothL1=1.071598, accuracy=0.813565
[Epoch 29] Validation:
aeroplane=0.741070
bicycle=0.772656
bird=0.666641
boat=0.639863
bottle=0.394530
bus=0.778388
car=0.816271
cat=0.847756
chair=0.510235
cow=0.762016
diningtable=0.673970
dog=0.810802
horse=0.824766
motorbike=0.785812
person=0.726579
pottedplant=0.366507
sheep=0.698733
sofa=0.716849
train=0.835749
tvmonitor=0.695700
mAP=0.703245
[Epoch 30][Batch 99], Speed: 94.874773 samples/sec, CrossEntropy=2.271433, SmoothL1=1.036147, accuracy=0.817341
[Epoch 30][Batch 199], Speed: 93.756010 samples/sec, CrossEntropy=2.287462, SmoothL1=1.048741, accuracy=0.815598
[Epoch 30][Batch 299], Speed: 94.172481 samples/sec, CrossEntropy=2.300156, SmoothL1=1.060944, accuracy=0.814374
[Epoch 30][Batch 399], Speed: 91.077070 samples/sec, CrossEntropy=2.311722, SmoothL1=1.067605, accuracy=0.813848
[Epoch 30][Batch 499], Speed: 92.066474 samples/sec, CrossEntropy=2.311321, SmoothL1=1.068985, accuracy=0.814191
[Epoch 30] Training cost: 193.649497, CrossEntropy=2.309602, SmoothL1=1.070090, accuracy=0.814185
[Epoch 30] Validation:
aeroplane=0.729203
bicycle=0.792397
bird=0.686228
boat=0.597950
bottle=0.374878
bus=0.761677
car=0.811643
cat=0.859023
chair=0.511185
cow=0.761190
diningtable=0.713862
dog=0.815903
horse=0.826475
motorbike=0.807091
person=0.737352
pottedplant=0.411006
sheep=0.682400
sofa=0.726552
train=0.797300
tvmonitor=0.660790
mAP=0.703205
[Epoch 31][Batch 99], Speed: 89.521097 samples/sec, CrossEntropy=2.295722, SmoothL1=1.063982, accuracy=0.814610
[Epoch 31][Batch 199], Speed: 86.203776 samples/sec, CrossEntropy=2.309323, SmoothL1=1.079328, accuracy=0.814061
[Epoch 31][Batch 299], Speed: 82.636818 samples/sec, CrossEntropy=2.313224, SmoothL1=1.077348, accuracy=0.814289
[Epoch 31][Batch 399], Speed: 80.384482 samples/sec, CrossEntropy=2.301532, SmoothL1=1.065985, accuracy=0.815202
[Epoch 31][Batch 499], Speed: 98.673617 samples/sec, CrossEntropy=2.307268, SmoothL1=1.067808, accuracy=0.814480
[Epoch 31] Training cost: 195.000659, CrossEntropy=2.306316, SmoothL1=1.067307, accuracy=0.814525
[Epoch 31] Validation:
aeroplane=0.753502
bicycle=0.777467
bird=0.680476
boat=0.662609
bottle=0.391546
bus=0.792588
car=0.816046
cat=0.836960
chair=0.500223
cow=0.757422
diningtable=0.705563
dog=0.806317
horse=0.828234
motorbike=0.788450
person=0.733902
pottedplant=0.406711
sheep=0.684618
sofa=0.741850
train=0.846958
tvmonitor=0.687213
mAP=0.709933
[Epoch 32][Batch 99], Speed: 88.874730 samples/sec, CrossEntropy=2.215679, SmoothL1=1.014405, accuracy=0.818647
[Epoch 32][Batch 199], Speed: 86.221663 samples/sec, CrossEntropy=2.259051, SmoothL1=1.035375, accuracy=0.817020
[Epoch 32][Batch 299], Speed: 82.789737 samples/sec, CrossEntropy=2.271428, SmoothL1=1.045771, accuracy=0.816103
[Epoch 32][Batch 399], Speed: 77.670004 samples/sec, CrossEntropy=2.271268, SmoothL1=1.047737, accuracy=0.816242
[Epoch 32][Batch 499], Speed: 98.552547 samples/sec, CrossEntropy=2.271151, SmoothL1=1.049207, accuracy=0.816096
[Epoch 32] Training cost: 193.205511, CrossEntropy=2.273368, SmoothL1=1.048958, accuracy=0.816025
[Epoch 32] Validation:
aeroplane=0.740627
bicycle=0.790855
bird=0.664333
boat=0.616975
bottle=0.384950
bus=0.784334
car=0.826573
cat=0.847422
chair=0.501410
cow=0.762297
diningtable=0.720775
dog=0.790510
horse=0.796633
motorbike=0.759649
person=0.724731
pottedplant=0.410117
sheep=0.691797
sofa=0.726472
train=0.824175
tvmonitor=0.708599
mAP=0.703662
[Epoch 33][Batch 99], Speed: 89.615956 samples/sec, CrossEntropy=2.280690, SmoothL1=1.055376, accuracy=0.814653
[Epoch 33][Batch 199], Speed: 94.226562 samples/sec, CrossEntropy=2.301656, SmoothL1=1.069071, accuracy=0.813863
[Epoch 33][Batch 299], Speed: 85.772321 samples/sec, CrossEntropy=2.301529, SmoothL1=1.062998, accuracy=0.814374
[Epoch 33][Batch 399], Speed: 83.948622 samples/sec, CrossEntropy=2.296845, SmoothL1=1.055541, accuracy=0.814348
[Epoch 33][Batch 499], Speed: 94.808425 samples/sec, CrossEntropy=2.292843, SmoothL1=1.049500, accuracy=0.814734
[Epoch 33] Training cost: 193.997524, CrossEntropy=2.289616, SmoothL1=1.048367, accuracy=0.814903
[Epoch 33] Validation:
aeroplane=0.732387
bicycle=0.808092
bird=0.694870
boat=0.618010
bottle=0.372304
bus=0.783873
car=0.819372
cat=0.866207
chair=0.523466
cow=0.765220
diningtable=0.683524
dog=0.806769
horse=0.819566
motorbike=0.800547
person=0.741894
pottedplant=0.418600
sheep=0.725862
sofa=0.714011
train=0.832903
tvmonitor=0.710748
mAP=0.711911
[Epoch 34][Batch 99], Speed: 88.865079 samples/sec, CrossEntropy=2.255191, SmoothL1=1.044109, accuracy=0.816657
[Epoch 34][Batch 199], Speed: 87.878396 samples/sec, CrossEntropy=2.272481, SmoothL1=1.045235, accuracy=0.816218
[Epoch 34][Batch 299], Speed: 82.457960 samples/sec, CrossEntropy=2.269452, SmoothL1=1.044760, accuracy=0.816777
[Epoch 34][Batch 399], Speed: 72.640630 samples/sec, CrossEntropy=2.266954, SmoothL1=1.048462, accuracy=0.816690
[Epoch 34][Batch 499], Speed: 96.718789 samples/sec, CrossEntropy=2.265588, SmoothL1=1.044521, accuracy=0.816807
[Epoch 34] Training cost: 194.613520, CrossEntropy=2.264180, SmoothL1=1.044555, accuracy=0.816879
[Epoch 34] Validation:
aeroplane=0.750863
bicycle=0.785621
bird=0.711358
boat=0.633000
bottle=0.377794
bus=0.799631
car=0.817694
cat=0.850324
chair=0.508304
cow=0.734149
diningtable=0.708305
dog=0.814637
horse=0.843516
motorbike=0.794260
person=0.735940
pottedplant=0.395144
sheep=0.720131
sofa=0.744247
train=0.841801
tvmonitor=0.699039
mAP=0.713288
[Epoch 35][Batch 99], Speed: 94.305215 samples/sec, CrossEntropy=2.222389, SmoothL1=1.034558, accuracy=0.819018
[Epoch 35][Batch 199], Speed: 87.557646 samples/sec, CrossEntropy=2.246933, SmoothL1=1.047291, accuracy=0.818305
[Epoch 35][Batch 299], Speed: 89.885848 samples/sec, CrossEntropy=2.235979, SmoothL1=1.038696, accuracy=0.818634
[Epoch 35][Batch 399], Speed: 79.790342 samples/sec, CrossEntropy=2.236437, SmoothL1=1.029377, accuracy=0.819031
[Epoch 35][Batch 499], Speed: 97.807655 samples/sec, CrossEntropy=2.237606, SmoothL1=1.030611, accuracy=0.818709
[Epoch 35] Training cost: 194.378284, CrossEntropy=2.239049, SmoothL1=1.031551, accuracy=0.818575
[Epoch 35] Validation:
aeroplane=0.759835
bicycle=0.806067
bird=0.682582
boat=0.616532
bottle=0.408568
bus=0.788817
car=0.829418
cat=0.846608
chair=0.518370
cow=0.767031
diningtable=0.681895
dog=0.815609
horse=0.854745
motorbike=0.808726
person=0.738069
pottedplant=0.414962
sheep=0.719339
sofa=0.757312
train=0.840840
tvmonitor=0.710399
mAP=0.718286
[Epoch 36][Batch 99], Speed: 86.253191 samples/sec, CrossEntropy=2.176525, SmoothL1=1.011010, accuracy=0.820758
[Epoch 36][Batch 199], Speed: 95.119651 samples/sec, CrossEntropy=2.192677, SmoothL1=1.022036, accuracy=0.820678
[Epoch 36][Batch 299], Speed: 82.042433 samples/sec, CrossEntropy=2.219124, SmoothL1=1.023675, accuracy=0.819056
[Epoch 36][Batch 399], Speed: 89.767957 samples/sec, CrossEntropy=2.215067, SmoothL1=1.016765, accuracy=0.819319
[Epoch 36][Batch 499], Speed: 93.455581 samples/sec, CrossEntropy=2.226376, SmoothL1=1.022936, accuracy=0.818650
[Epoch 36] Training cost: 193.852087, CrossEntropy=2.226513, SmoothL1=1.021442, accuracy=0.818641
[Epoch 36] Validation:
aeroplane=0.748067
bicycle=0.809816
bird=0.693488
boat=0.663194
bottle=0.407553
bus=0.796233
car=0.835507
cat=0.841760
chair=0.530638
cow=0.763213
diningtable=0.711575
dog=0.818577
horse=0.839869
motorbike=0.805498
person=0.747754
pottedplant=0.380463
sheep=0.707350
sofa=0.735753
train=0.865544
tvmonitor=0.721608
mAP=0.721173
[Epoch 37][Batch 99], Speed: 86.035737 samples/sec, CrossEntropy=2.177104, SmoothL1=1.008521, accuracy=0.821253
[Epoch 37][Batch 199], Speed: 88.228406 samples/sec, CrossEntropy=2.204614, SmoothL1=1.007900, accuracy=0.820343
[Epoch 37][Batch 299], Speed: 87.088713 samples/sec, CrossEntropy=2.204382, SmoothL1=1.006765, accuracy=0.820265
[Epoch 37][Batch 399], Speed: 86.792096 samples/sec, CrossEntropy=2.201165, SmoothL1=1.002475, accuracy=0.820291
[Epoch 37][Batch 499], Speed: 94.279843 samples/sec, CrossEntropy=2.206179, SmoothL1=1.005461, accuracy=0.819970
[Epoch 37] Training cost: 193.515965, CrossEntropy=2.207201, SmoothL1=1.007264, accuracy=0.819966
[Epoch 37] Validation:
aeroplane=0.726119
bicycle=0.811852
bird=0.683710
boat=0.625648
bottle=0.415300
bus=0.803730
car=0.816575
cat=0.858764
chair=0.515585
cow=0.747347
diningtable=0.711907
dog=0.811995
horse=0.822602
motorbike=0.812317
person=0.738736
pottedplant=0.430583
sheep=0.676456
sofa=0.712772
train=0.838201
tvmonitor=0.713089
mAP=0.713664
[Epoch 38][Batch 99], Speed: 92.905522 samples/sec, CrossEntropy=2.180404, SmoothL1=1.013344, accuracy=0.821763
[Epoch 38][Batch 199], Speed: 87.047651 samples/sec, CrossEntropy=2.206225, SmoothL1=1.016289, accuracy=0.820684
[Epoch 38][Batch 299], Speed: 86.382980 samples/sec, CrossEntropy=2.202389, SmoothL1=1.006814, accuracy=0.820439
[Epoch 38][Batch 399], Speed: 93.586822 samples/sec, CrossEntropy=2.203702, SmoothL1=1.004391, accuracy=0.820413
[Epoch 38][Batch 499], Speed: 89.703042 samples/sec, CrossEntropy=2.205057, SmoothL1=1.004096, accuracy=0.820237
[Epoch 38] Training cost: 193.845771, CrossEntropy=2.204500, SmoothL1=1.003607, accuracy=0.820197
[Epoch 38] Validation:
aeroplane=0.738997
bicycle=0.776672
bird=0.681536
boat=0.628790
bottle=0.387755
bus=0.791809
car=0.826478
cat=0.861453
chair=0.500446
cow=0.736578
diningtable=0.712775
dog=0.805921
horse=0.822741
motorbike=0.784745
person=0.733151
pottedplant=0.423762
sheep=0.674987
sofa=0.741967
train=0.820245
tvmonitor=0.711027
mAP=0.708092
[Epoch 39][Batch 99], Speed: 84.363101 samples/sec, CrossEntropy=2.189969, SmoothL1=1.011521, accuracy=0.821580
[Epoch 39][Batch 199], Speed: 93.283131 samples/sec, CrossEntropy=2.206193, SmoothL1=1.015163, accuracy=0.820800
[Epoch 39][Batch 299], Speed: 88.401461 samples/sec, CrossEntropy=2.202622, SmoothL1=1.007135, accuracy=0.820798
[Epoch 39][Batch 399], Speed: 83.345480 samples/sec, CrossEntropy=2.198579, SmoothL1=1.006146, accuracy=0.820919
[Epoch 39][Batch 499], Speed: 95.360716 samples/sec, CrossEntropy=2.193747, SmoothL1=1.003620, accuracy=0.821161
[Epoch 39] Training cost: 193.887152, CrossEntropy=2.193365, SmoothL1=1.002957, accuracy=0.821100
[Epoch 39] Validation:
aeroplane=0.765283
bicycle=0.803450
bird=0.700004
boat=0.669322
bottle=0.403918
bus=0.808298
car=0.828647
cat=0.848549
chair=0.504133
cow=0.784451
diningtable=0.707928
dog=0.795594
horse=0.842526
motorbike=0.803163
person=0.741374
pottedplant=0.409794
sheep=0.696050
sofa=0.686322
train=0.832902
tvmonitor=0.710477
mAP=0.717109
[Epoch 40][Batch 99], Speed: 91.678463 samples/sec, CrossEntropy=2.160966, SmoothL1=0.997833, accuracy=0.821773
[Epoch 40][Batch 199], Speed: 85.469346 samples/sec, CrossEntropy=2.180198, SmoothL1=1.007459, accuracy=0.820417
[Epoch 40][Batch 299], Speed: 92.138904 samples/sec, CrossEntropy=2.184807, SmoothL1=1.000443, accuracy=0.820823
[Epoch 40][Batch 399], Speed: 79.865406 samples/sec, CrossEntropy=2.188828, SmoothL1=1.001159, accuracy=0.820905
[Epoch 40][Batch 499], Speed: 91.180150 samples/sec, CrossEntropy=2.189087, SmoothL1=0.996868, accuracy=0.820905
[Epoch 40] Training cost: 193.554856, CrossEntropy=2.189252, SmoothL1=0.996521, accuracy=0.821083
[Epoch 40] Validation:
aeroplane=0.759827
bicycle=0.777248
bird=0.707785
boat=0.646581
bottle=0.397273
bus=0.816470
car=0.831164
cat=0.868197
chair=0.526120
cow=0.781098
diningtable=0.728936
dog=0.815175
horse=0.834889
motorbike=0.802389
person=0.748041
pottedplant=0.365384
sheep=0.702309
sofa=0.767225
train=0.840805
tvmonitor=0.687887
mAP=0.720240
[Epoch 41][Batch 99], Speed: 89.489164 samples/sec, CrossEntropy=2.176498, SmoothL1=1.006849, accuracy=0.819829
[Epoch 41][Batch 199], Speed: 91.641781 samples/sec, CrossEntropy=2.196657, SmoothL1=1.017220, accuracy=0.820231
[Epoch 41][Batch 299], Speed: 90.126071 samples/sec, CrossEntropy=2.189436, SmoothL1=1.003619, accuracy=0.821078
[Epoch 41][Batch 399], Speed: 83.776542 samples/sec, CrossEntropy=2.188430, SmoothL1=0.995402, accuracy=0.821326
[Epoch 41][Batch 499], Speed: 97.343235 samples/sec, CrossEntropy=2.180407, SmoothL1=0.992902, accuracy=0.822000
[Epoch 41] Training cost: 194.855619, CrossEntropy=2.178362, SmoothL1=0.991317, accuracy=0.822106
[Epoch 41] Validation:
aeroplane=0.754795
bicycle=0.804243
bird=0.687439
boat=0.660142
bottle=0.400142
bus=0.799178
car=0.830246
cat=0.850493
chair=0.530160
cow=0.756656
diningtable=0.712213
dog=0.837931
horse=0.836696
motorbike=0.812217
person=0.747953
pottedplant=0.423833
sheep=0.721554
sofa=0.737613
train=0.839838
tvmonitor=0.691093
mAP=0.721722
[Epoch 42][Batch 99], Speed: 87.418725 samples/sec, CrossEntropy=2.119802, SmoothL1=0.972986, accuracy=0.825400
[Epoch 42][Batch 199], Speed: 91.939334 samples/sec, CrossEntropy=2.151009, SmoothL1=0.990515, accuracy=0.823644
[Epoch 42][Batch 299], Speed: 92.057318 samples/sec, CrossEntropy=2.152665, SmoothL1=0.995547, accuracy=0.823376
[Epoch 42][Batch 399], Speed: 90.921778 samples/sec, CrossEntropy=2.149254, SmoothL1=0.987870, accuracy=0.823851
[Epoch 42][Batch 499], Speed: 95.365797 samples/sec, CrossEntropy=2.150724, SmoothL1=0.987191, accuracy=0.823765
[Epoch 42] Training cost: 194.746761, CrossEntropy=2.153286, SmoothL1=0.987692, accuracy=0.823631
[Epoch 42] Validation:
aeroplane=0.773546
bicycle=0.818510
bird=0.716442
boat=0.645191
bottle=0.416404
bus=0.801286
car=0.822173
cat=0.864482
chair=0.529684
cow=0.751226
diningtable=0.706979
dog=0.815480
horse=0.828397
motorbike=0.808703
person=0.746990
pottedplant=0.420665
sheep=0.718643
sofa=0.728486
train=0.794300
tvmonitor=0.723807
mAP=0.721570
[Epoch 43][Batch 99], Speed: 87.475700 samples/sec, CrossEntropy=2.119207, SmoothL1=0.965723, accuracy=0.824642
[Epoch 43][Batch 199], Speed: 93.222940 samples/sec, CrossEntropy=2.139539, SmoothL1=0.982423, accuracy=0.823306
[Epoch 43][Batch 299], Speed: 94.798649 samples/sec, CrossEntropy=2.146916, SmoothL1=0.979688, accuracy=0.823114
[Epoch 43][Batch 399], Speed: 85.665240 samples/sec, CrossEntropy=2.158838, SmoothL1=0.984296, accuracy=0.822896
[Epoch 43][Batch 499], Speed: 91.830949 samples/sec, CrossEntropy=2.162983, SmoothL1=0.980871, accuracy=0.822809
[Epoch 43] Training cost: 193.733856, CrossEntropy=2.162142, SmoothL1=0.980689, accuracy=0.822856
[Epoch 43] Validation:
aeroplane=0.764645
bicycle=0.810808
bird=0.688152
boat=0.659946
bottle=0.425866
bus=0.800363
car=0.835287
cat=0.851397
chair=0.544055
cow=0.787483
diningtable=0.713369
dog=0.822230
horse=0.840275
motorbike=0.831156
person=0.751246
pottedplant=0.420480
sheep=0.704083
sofa=0.742189
train=0.837308
tvmonitor=0.726623
mAP=0.727848
[Epoch 44][Batch 99], Speed: 94.092532 samples/sec, CrossEntropy=2.109050, SmoothL1=0.955130, accuracy=0.826122
[Epoch 44][Batch 199], Speed: 87.250401 samples/sec, CrossEntropy=2.138973, SmoothL1=0.965866, accuracy=0.824610
[Epoch 44][Batch 299], Speed: 92.771567 samples/sec, CrossEntropy=2.135061, SmoothL1=0.972035, accuracy=0.824399
[Epoch 44][Batch 399], Speed: 86.705471 samples/sec, CrossEntropy=2.136820, SmoothL1=0.969694, accuracy=0.824267
[Epoch 44][Batch 499], Speed: 87.665161 samples/sec, CrossEntropy=2.147586, SmoothL1=0.976460, accuracy=0.823380
[Epoch 44] Training cost: 194.467755, CrossEntropy=2.148177, SmoothL1=0.977071, accuracy=0.823481
[Epoch 44] Validation:
aeroplane=0.724954
bicycle=0.806644
bird=0.684072
boat=0.663543
bottle=0.405678
bus=0.804157
car=0.828676
cat=0.847130
chair=0.539448
cow=0.763849
diningtable=0.719524
dog=0.810759
horse=0.838752
motorbike=0.797325
person=0.744517
pottedplant=0.392401
sheep=0.701839
sofa=0.762707
train=0.840013
tvmonitor=0.710902
mAP=0.719345
[Epoch 45][Batch 99], Speed: 91.622013 samples/sec, CrossEntropy=2.127923, SmoothL1=0.955823, accuracy=0.825229
[Epoch 45][Batch 199], Speed: 90.364114 samples/sec, CrossEntropy=2.132827, SmoothL1=0.964448, accuracy=0.824845
[Epoch 45][Batch 299], Speed: 83.654775 samples/sec, CrossEntropy=2.134761, SmoothL1=0.966007, accuracy=0.824850
[Epoch 45][Batch 399], Speed: 90.152889 samples/sec, CrossEntropy=2.138439, SmoothL1=0.967813, accuracy=0.824599
[Epoch 45][Batch 499], Speed: 93.337298 samples/sec, CrossEntropy=2.138473, SmoothL1=0.971859, accuracy=0.824466
[Epoch 45] Training cost: 195.223020, CrossEntropy=2.136489, SmoothL1=0.970813, accuracy=0.824733
[Epoch 45] Validation:
aeroplane=0.762503
bicycle=0.794813
bird=0.712820
boat=0.666199
bottle=0.389864
bus=0.810480
car=0.830844
cat=0.861086
chair=0.536040
cow=0.783121
diningtable=0.709598
dog=0.822824
horse=0.845975
motorbike=0.830667
person=0.751426
pottedplant=0.415343
sheep=0.730955
sofa=0.749862
train=0.839808
tvmonitor=0.720151
mAP=0.728219
[Epoch 46][Batch 99], Speed: 93.621812 samples/sec, CrossEntropy=2.080307, SmoothL1=0.939442, accuracy=0.828027
[Epoch 46][Batch 199], Speed: 83.185347 samples/sec, CrossEntropy=2.112712, SmoothL1=0.957517, accuracy=0.826750
[Epoch 46][Batch 299], Speed: 92.209611 samples/sec, CrossEntropy=2.130584, SmoothL1=0.966428, accuracy=0.825714
[Epoch 46][Batch 399], Speed: 89.497339 samples/sec, CrossEntropy=2.132254, SmoothL1=0.964264, accuracy=0.824977
[Epoch 46][Batch 499], Speed: 91.834091 samples/sec, CrossEntropy=2.126734, SmoothL1=0.964238, accuracy=0.825017
[Epoch 46] Training cost: 194.141665, CrossEntropy=2.125609, SmoothL1=0.963346, accuracy=0.825072
[Epoch 46] Validation:
aeroplane=0.764018
bicycle=0.803406
bird=0.690660
boat=0.624291
bottle=0.411116
bus=0.818378
car=0.835296
cat=0.861315
chair=0.543698
cow=0.787789
diningtable=0.722827
dog=0.812824
horse=0.831388
motorbike=0.798300
person=0.746173
pottedplant=0.437956
sheep=0.707653
sofa=0.735913
train=0.833702
tvmonitor=0.715825
mAP=0.724126
[Epoch 47][Batch 99], Speed: 90.226948 samples/sec, CrossEntropy=2.093705, SmoothL1=0.938537, accuracy=0.826007
[Epoch 47][Batch 199], Speed: 86.178758 samples/sec, CrossEntropy=2.107412, SmoothL1=0.951836, accuracy=0.825834
[Epoch 47][Batch 299], Speed: 85.406747 samples/sec, CrossEntropy=2.110933, SmoothL1=0.959986, accuracy=0.825621
[Epoch 47][Batch 399], Speed: 87.599934 samples/sec, CrossEntropy=2.119108, SmoothL1=0.960400, accuracy=0.825394
[Epoch 47][Batch 499], Speed: 91.821903 samples/sec, CrossEntropy=2.117008, SmoothL1=0.960120, accuracy=0.825613
[Epoch 47] Training cost: 194.987541, CrossEntropy=2.116171, SmoothL1=0.960485, accuracy=0.825654
[Epoch 47] Validation:
aeroplane=0.752481
bicycle=0.794106
bird=0.705035
boat=0.645111
bottle=0.433847
bus=0.813512
car=0.833389
cat=0.869025
chair=0.538673
cow=0.754271
diningtable=0.677366
dog=0.811556
horse=0.824004
motorbike=0.809726
person=0.759332
pottedplant=0.461274
sheep=0.726149
sofa=0.707998
train=0.826019
tvmonitor=0.724537
mAP=0.723371
[Epoch 48][Batch 99], Speed: 86.450972 samples/sec, CrossEntropy=2.093047, SmoothL1=0.971935, accuracy=0.825951
[Epoch 48][Batch 199], Speed: 90.262323 samples/sec, CrossEntropy=2.116899, SmoothL1=0.974637, accuracy=0.825969
[Epoch 48][Batch 299], Speed: 93.362749 samples/sec, CrossEntropy=2.106264, SmoothL1=0.967063, accuracy=0.826202
[Epoch 48][Batch 399], Speed: 91.308490 samples/sec, CrossEntropy=2.111759, SmoothL1=0.965593, accuracy=0.825738
[Epoch 48][Batch 499], Speed: 88.617419 samples/sec, CrossEntropy=2.108783, SmoothL1=0.960187, accuracy=0.826058
[Epoch 48] Training cost: 193.903296, CrossEntropy=2.108136, SmoothL1=0.959101, accuracy=0.826179
[Epoch 48] Validation:
aeroplane=0.758176
bicycle=0.811327
bird=0.685955
boat=0.655127
bottle=0.437631
bus=0.814741
car=0.830848
cat=0.863597
chair=0.554637
cow=0.800277
diningtable=0.732335
dog=0.826244
horse=0.827984
motorbike=0.812030
person=0.748366
pottedplant=0.424798
sheep=0.720036
sofa=0.729788
train=0.865498
tvmonitor=0.719523
mAP=0.730946
[Epoch 49][Batch 99], Speed: 91.892753 samples/sec, CrossEntropy=2.086886, SmoothL1=0.946360, accuracy=0.826256
[Epoch 49][Batch 199], Speed: 87.233615 samples/sec, CrossEntropy=2.081627, SmoothL1=0.948564, accuracy=0.827252
[Epoch 49][Batch 299], Speed: 89.148339 samples/sec, CrossEntropy=2.074847, SmoothL1=0.944593, accuracy=0.828102
[Epoch 49][Batch 399], Speed: 87.821355 samples/sec, CrossEntropy=2.080877, SmoothL1=0.943911, accuracy=0.827890
[Epoch 49][Batch 499], Speed: 97.897972 samples/sec, CrossEntropy=2.084425, SmoothL1=0.940552, accuracy=0.827484
[Epoch 49] Training cost: 194.097994, CrossEntropy=2.087068, SmoothL1=0.942642, accuracy=0.827375
[Epoch 49] Validation:
aeroplane=0.777847
bicycle=0.795615
bird=0.700229
boat=0.648797
bottle=0.432790
bus=0.811265
car=0.837364
cat=0.864060
chair=0.539273
cow=0.801256
diningtable=0.711772
dog=0.805960
horse=0.837493
motorbike=0.808042
person=0.748703
pottedplant=0.434218
sheep=0.716310
sofa=0.737509
train=0.856258
tvmonitor=0.721909
mAP=0.729333
[Epoch 50][Batch 99], Speed: 87.853776 samples/sec, CrossEntropy=2.020906, SmoothL1=0.902795, accuracy=0.831450
[Epoch 50][Batch 199], Speed: 90.681649 samples/sec, CrossEntropy=2.057972, SmoothL1=0.934929, accuracy=0.830063
[Epoch 50][Batch 299], Speed: 92.684696 samples/sec, CrossEntropy=2.080305, SmoothL1=0.944834, accuracy=0.828490
[Epoch 50][Batch 399], Speed: 92.509912 samples/sec, CrossEntropy=2.084201, SmoothL1=0.941985, accuracy=0.828232
[Epoch 50][Batch 499], Speed: 91.693307 samples/sec, CrossEntropy=2.087652, SmoothL1=0.942220, accuracy=0.827863
[Epoch 50] Training cost: 193.952450, CrossEntropy=2.087835, SmoothL1=0.941212, accuracy=0.827766
[Epoch 50] Validation:
aeroplane=0.771186
bicycle=0.796806
bird=0.700126
boat=0.658210
bottle=0.419367
bus=0.802582
car=0.835615
cat=0.840849
chair=0.530841
cow=0.770315
diningtable=0.731785
dog=0.831467
horse=0.824759
motorbike=0.801333
person=0.753773
pottedplant=0.442999
sheep=0.708640
sofa=0.731409
train=0.840410
tvmonitor=0.714747
mAP=0.725361
[Epoch 51][Batch 99], Speed: 84.442078 samples/sec, CrossEntropy=2.038190, SmoothL1=0.923195, accuracy=0.830068
[Epoch 51][Batch 199], Speed: 89.024224 samples/sec, CrossEntropy=2.068893, SmoothL1=0.944480, accuracy=0.828551
[Epoch 51][Batch 299], Speed: 94.660317 samples/sec, CrossEntropy=2.080053, SmoothL1=0.950307, accuracy=0.827729
[Epoch 51][Batch 399], Speed: 94.469631 samples/sec, CrossEntropy=2.080973, SmoothL1=0.945623, accuracy=0.827687
[Epoch 51][Batch 499], Speed: 93.742978 samples/sec, CrossEntropy=2.083454, SmoothL1=0.940599, accuracy=0.827611
[Epoch 51] Training cost: 194.178996, CrossEntropy=2.086243, SmoothL1=0.942112, accuracy=0.827457
[Epoch 51] Validation:
aeroplane=0.749419
bicycle=0.818737
bird=0.723133
boat=0.631728
bottle=0.424183
bus=0.796890
car=0.836508
cat=0.867948
chair=0.550099
cow=0.765905
diningtable=0.727969
dog=0.814359
horse=0.859067
motorbike=0.810408
person=0.752652
pottedplant=0.413205
sheep=0.703328
sofa=0.762088
train=0.823382
tvmonitor=0.723317
mAP=0.727716
[Epoch 52][Batch 99], Speed: 95.658196 samples/sec, CrossEntropy=2.071743, SmoothL1=0.919875, accuracy=0.829071
[Epoch 52][Batch 199], Speed: 91.747022 samples/sec, CrossEntropy=2.083775, SmoothL1=0.936472, accuracy=0.828742
[Epoch 52][Batch 299], Speed: 88.100592 samples/sec, CrossEntropy=2.080061, SmoothL1=0.938386, accuracy=0.828520
[Epoch 52][Batch 399], Speed: 87.063461 samples/sec, CrossEntropy=2.079118, SmoothL1=0.932178, accuracy=0.828504
[Epoch 52][Batch 499], Speed: 92.965755 samples/sec, CrossEntropy=2.075249, SmoothL1=0.935681, accuracy=0.828657
[Epoch 52] Training cost: 194.119407, CrossEntropy=2.075442, SmoothL1=0.935526, accuracy=0.828762
[Epoch 52] Validation:
aeroplane=0.763838
bicycle=0.811087
bird=0.725278
boat=0.664884
bottle=0.418576
bus=0.810843
car=0.838841
cat=0.855119
chair=0.519489
cow=0.777012
diningtable=0.696389
dog=0.818446
horse=0.822738
motorbike=0.800711
person=0.740643
pottedplant=0.416371
sheep=0.718012
sofa=0.729143
train=0.856359
tvmonitor=0.717664
mAP=0.725072
[Epoch 53][Batch 99], Speed: 82.735437 samples/sec, CrossEntropy=2.064860, SmoothL1=0.941096, accuracy=0.829792
[Epoch 53][Batch 199], Speed: 95.220740 samples/sec, CrossEntropy=2.068023, SmoothL1=0.942168, accuracy=0.829611
[Epoch 53][Batch 299], Speed: 91.063599 samples/sec, CrossEntropy=2.057118, SmoothL1=0.938509, accuracy=0.829952
[Epoch 53][Batch 399], Speed: 86.819774 samples/sec, CrossEntropy=2.052876, SmoothL1=0.931371, accuracy=0.830333
[Epoch 53][Batch 499], Speed: 93.480446 samples/sec, CrossEntropy=2.053198, SmoothL1=0.932075, accuracy=0.830491
[Epoch 53] Training cost: 194.315264, CrossEntropy=2.053021, SmoothL1=0.931462, accuracy=0.830595
[Epoch 53] Validation:
aeroplane=0.766964
bicycle=0.806769
bird=0.692853
boat=0.668494
bottle=0.391824
bus=0.812533
car=0.833652
cat=0.851528
chair=0.541458
cow=0.769136
diningtable=0.740942
dog=0.840097
horse=0.838816
motorbike=0.786860
person=0.745874
pottedplant=0.436408
sheep=0.716706
sofa=0.743597
train=0.852455
tvmonitor=0.704520
mAP=0.727074
[Epoch 54][Batch 99], Speed: 84.264374 samples/sec, CrossEntropy=2.008575, SmoothL1=0.895644, accuracy=0.832427
[Epoch 54][Batch 199], Speed: 84.131850 samples/sec, CrossEntropy=2.034786, SmoothL1=0.911529, accuracy=0.831797
[Epoch 54][Batch 299], Speed: 94.502490 samples/sec, CrossEntropy=2.039346, SmoothL1=0.917056, accuracy=0.831736
[Epoch 54][Batch 399], Speed: 95.046769 samples/sec, CrossEntropy=2.044093, SmoothL1=0.915621, accuracy=0.830983
[Epoch 54][Batch 499], Speed: 90.931818 samples/sec, CrossEntropy=2.050799, SmoothL1=0.922077, accuracy=0.830379
[Epoch 54] Training cost: 194.577790, CrossEntropy=2.050954, SmoothL1=0.921252, accuracy=0.830342
[Epoch 54] Validation:
aeroplane=0.763174
bicycle=0.813449
bird=0.674636
boat=0.670516
bottle=0.451050
bus=0.800329
car=0.826743
cat=0.866687
chair=0.528848
cow=0.798207
diningtable=0.705176
dog=0.826502
horse=0.828659
motorbike=0.816715
person=0.747351
pottedplant=0.450826
sheep=0.719087
sofa=0.728580
train=0.856581
tvmonitor=0.730077
mAP=0.730160
[Epoch 55][Batch 99], Speed: 91.954325 samples/sec, CrossEntropy=2.014891, SmoothL1=0.906770, accuracy=0.834524
[Epoch 55][Batch 199], Speed: 88.704743 samples/sec, CrossEntropy=2.046191, SmoothL1=0.925093, accuracy=0.831562
[Epoch 55][Batch 299], Speed: 88.778085 samples/sec, CrossEntropy=2.049340, SmoothL1=0.930767, accuracy=0.830758
[Epoch 55][Batch 399], Speed: 90.230163 samples/sec, CrossEntropy=2.052677, SmoothL1=0.926435, accuracy=0.830008
[Epoch 55][Batch 499], Speed: 98.384009 samples/sec, CrossEntropy=2.046527, SmoothL1=0.920942, accuracy=0.830585
[Epoch 55] Training cost: 193.281954, CrossEntropy=2.047182, SmoothL1=0.922553, accuracy=0.830558
[Epoch 55] Validation:
aeroplane=0.755571
bicycle=0.818839
bird=0.693441
boat=0.658906
bottle=0.393262
bus=0.822882
car=0.824163
cat=0.869606
chair=0.539108
cow=0.811525
diningtable=0.714841
dog=0.833773
horse=0.834235
motorbike=0.823514
person=0.750539
pottedplant=0.430360
sheep=0.719434
sofa=0.744393
train=0.833297
tvmonitor=0.722937
mAP=0.729731
[Epoch 56][Batch 99], Speed: 87.969919 samples/sec, CrossEntropy=2.045946, SmoothL1=0.942314, accuracy=0.828987
[Epoch 56][Batch 199], Speed: 81.114303 samples/sec, CrossEntropy=2.046452, SmoothL1=0.946365, accuracy=0.829506
[Epoch 56][Batch 299], Speed: 91.916919 samples/sec, CrossEntropy=2.046915, SmoothL1=0.936028, accuracy=0.829730
[Epoch 56][Batch 399], Speed: 94.330003 samples/sec, CrossEntropy=2.043150, SmoothL1=0.926895, accuracy=0.830362
[Epoch 56][Batch 499], Speed: 97.682016 samples/sec, CrossEntropy=2.043984, SmoothL1=0.922770, accuracy=0.830302
[Epoch 56] Training cost: 194.424778, CrossEntropy=2.043761, SmoothL1=0.922176, accuracy=0.830303
[Epoch 56] Validation:
aeroplane=0.766814
bicycle=0.800549
bird=0.725643
boat=0.630287
bottle=0.434847
bus=0.822152
car=0.839511
cat=0.868911
chair=0.537432
cow=0.810836
diningtable=0.726179
dog=0.841312
horse=0.831476
motorbike=0.827287
person=0.755715
pottedplant=0.415232
sheep=0.747894
sofa=0.746462
train=0.849492
tvmonitor=0.702243
mAP=0.734014
[Epoch 57][Batch 99], Speed: 95.538628 samples/sec, CrossEntropy=2.022600, SmoothL1=0.914822, accuracy=0.832724
[Epoch 57][Batch 199], Speed: 93.297526 samples/sec, CrossEntropy=2.049777, SmoothL1=0.933820, accuracy=0.831600
[Epoch 57][Batch 299], Speed: 87.179221 samples/sec, CrossEntropy=2.035246, SmoothL1=0.924389, accuracy=0.832202
[Epoch 57][Batch 399], Speed: 83.259655 samples/sec, CrossEntropy=2.033937, SmoothL1=0.915441, accuracy=0.831686
[Epoch 57][Batch 499], Speed: 97.852008 samples/sec, CrossEntropy=2.032093, SmoothL1=0.914063, accuracy=0.831380
[Epoch 57] Training cost: 193.799480, CrossEntropy=2.032256, SmoothL1=0.913574, accuracy=0.831383
[Epoch 57] Validation:
aeroplane=0.770629
bicycle=0.815657
bird=0.719414
boat=0.646810
bottle=0.435464
bus=0.822648
car=0.842007
cat=0.861808
chair=0.550114
cow=0.803540
diningtable=0.721856
dog=0.831590
horse=0.823190
motorbike=0.828711
person=0.755029
pottedplant=0.461446
sheep=0.719893
sofa=0.740620
train=0.843426
tvmonitor=0.720447
mAP=0.735715
[Epoch 58][Batch 99], Speed: 83.942111 samples/sec, CrossEntropy=2.015323, SmoothL1=0.895648, accuracy=0.832754
[Epoch 58][Batch 199], Speed: 92.330323 samples/sec, CrossEntropy=2.008142, SmoothL1=0.904782, accuracy=0.833001
[Epoch 58][Batch 299], Speed: 90.221125 samples/sec, CrossEntropy=2.012190, SmoothL1=0.904310, accuracy=0.832475
[Epoch 58][Batch 399], Speed: 83.493192 samples/sec, CrossEntropy=2.014266, SmoothL1=0.905083, accuracy=0.832024
[Epoch 58][Batch 499], Speed: 98.444192 samples/sec, CrossEntropy=2.021405, SmoothL1=0.907942, accuracy=0.831597
[Epoch 58] Training cost: 194.388141, CrossEntropy=2.017764, SmoothL1=0.905161, accuracy=0.831811
[Epoch 58] Validation:
aeroplane=0.745636
bicycle=0.823385
bird=0.715017
boat=0.664709
bottle=0.438708
bus=0.811963
car=0.841002
cat=0.867177
chair=0.528545
cow=0.815654
diningtable=0.733124
dog=0.827986
horse=0.822524
motorbike=0.798611
person=0.754136
pottedplant=0.459545
sheep=0.732877
sofa=0.719966
train=0.823491
tvmonitor=0.726429
mAP=0.732524
[Epoch 59][Batch 99], Speed: 94.037815 samples/sec, CrossEntropy=1.986290, SmoothL1=0.876756, accuracy=0.833272
[Epoch 59][Batch 199], Speed: 91.884323 samples/sec, CrossEntropy=2.008542, SmoothL1=0.898486, accuracy=0.832615
[Epoch 59][Batch 299], Speed: 88.271810 samples/sec, CrossEntropy=2.012165, SmoothL1=0.893991, accuracy=0.832919
[Epoch 59][Batch 399], Speed: 87.558902 samples/sec, CrossEntropy=2.017704, SmoothL1=0.898717, accuracy=0.832487
[Epoch 59][Batch 499], Speed: 96.405407 samples/sec, CrossEntropy=2.009125, SmoothL1=0.896836, accuracy=0.833066
[Epoch 59] Training cost: 194.749072, CrossEntropy=2.009303, SmoothL1=0.897711, accuracy=0.833015
[Epoch 59] Validation:
aeroplane=0.757057
bicycle=0.821316
bird=0.700148
boat=0.651236
bottle=0.421902
bus=0.825684
car=0.838177
cat=0.880701
chair=0.549737
cow=0.810391
diningtable=0.747666
dog=0.838252
horse=0.853592
motorbike=0.816075
person=0.748014
pottedplant=0.466138
sheep=0.722470
sofa=0.749185
train=0.851327
tvmonitor=0.725418
mAP=0.738724
[Epoch 60][Batch 99], Speed: 90.792925 samples/sec, CrossEntropy=1.996450, SmoothL1=0.903616, accuracy=0.835604
[Epoch 60][Batch 199], Speed: 85.063141 samples/sec, CrossEntropy=1.999597, SmoothL1=0.906798, accuracy=0.834495
[Epoch 60][Batch 299], Speed: 77.623647 samples/sec, CrossEntropy=2.005578, SmoothL1=0.905226, accuracy=0.833844
[Epoch 60][Batch 399], Speed: 89.589576 samples/sec, CrossEntropy=2.009993, SmoothL1=0.902159, accuracy=0.833639
[Epoch 60][Batch 499], Speed: 96.322936 samples/sec, CrossEntropy=2.014759, SmoothL1=0.905353, accuracy=0.833514
[Epoch 60] Training cost: 194.615751, CrossEntropy=2.015818, SmoothL1=0.905402, accuracy=0.833393
[Epoch 60] Validation:
aeroplane=0.781934
bicycle=0.808071
bird=0.718092
boat=0.674553
bottle=0.432281
bus=0.835896
car=0.832562
cat=0.867929
chair=0.541426
cow=0.795676
diningtable=0.723905
dog=0.817022
horse=0.853051
motorbike=0.829268
person=0.758023
pottedplant=0.471685
sheep=0.739327
sofa=0.726758
train=0.855839
tvmonitor=0.716517
mAP=0.738991
[Epoch 61][Batch 99], Speed: 87.369388 samples/sec, CrossEntropy=1.963862, SmoothL1=0.896973, accuracy=0.835634
[Epoch 61][Batch 199], Speed: 86.835053 samples/sec, CrossEntropy=1.961446, SmoothL1=0.883932, accuracy=0.835892
[Epoch 61][Batch 299], Speed: 89.487434 samples/sec, CrossEntropy=1.963764, SmoothL1=0.887672, accuracy=0.835514
[Epoch 61][Batch 399], Speed: 88.373638 samples/sec, CrossEntropy=1.966635, SmoothL1=0.887687, accuracy=0.835162
[Epoch 61][Batch 499], Speed: 91.730092 samples/sec, CrossEntropy=1.975480, SmoothL1=0.890538, accuracy=0.834803
[Epoch 61] Training cost: 193.946919, CrossEntropy=1.975840, SmoothL1=0.890323, accuracy=0.834852
[Epoch 61] Validation:
aeroplane=0.765198
bicycle=0.815812
bird=0.675195
boat=0.683779
bottle=0.434215
bus=0.820047
car=0.838115
cat=0.840891
chair=0.545623
cow=0.827314
diningtable=0.733297
dog=0.828529
horse=0.856670
motorbike=0.817286
person=0.758004
pottedplant=0.459594
sheep=0.751959
sofa=0.738161
train=0.841926
tvmonitor=0.725760
mAP=0.737869
[Epoch 62][Batch 99], Speed: 80.690873 samples/sec, CrossEntropy=2.004451, SmoothL1=0.900949, accuracy=0.833434
[Epoch 62][Batch 199], Speed: 85.780708 samples/sec, CrossEntropy=2.007733, SmoothL1=0.909502, accuracy=0.833567
[Epoch 62][Batch 299], Speed: 94.035377 samples/sec, CrossEntropy=1.992869, SmoothL1=0.900268, accuracy=0.834465
[Epoch 62][Batch 399], Speed: 93.072318 samples/sec, CrossEntropy=1.987016, SmoothL1=0.889402, accuracy=0.834637
[Epoch 62][Batch 499], Speed: 90.738664 samples/sec, CrossEntropy=1.987669, SmoothL1=0.892378, accuracy=0.834389
[Epoch 62] Training cost: 194.959869, CrossEntropy=1.984548, SmoothL1=0.891385, accuracy=0.834555
[Epoch 62] Validation:
aeroplane=0.764905
bicycle=0.817994
bird=0.708166
boat=0.648164
bottle=0.408912
bus=0.815071
car=0.834248
cat=0.858622
chair=0.547939
cow=0.775740
diningtable=0.740625
dog=0.828721
horse=0.855939
motorbike=0.812920
person=0.747670
pottedplant=0.435960
sheep=0.728241
sofa=0.721951
train=0.842661
tvmonitor=0.738826
mAP=0.731664
[Epoch 63][Batch 99], Speed: 82.338022 samples/sec, CrossEntropy=1.946627, SmoothL1=0.867621, accuracy=0.837461
[Epoch 63][Batch 199], Speed: 80.954417 samples/sec, CrossEntropy=1.976910, SmoothL1=0.889028, accuracy=0.835587
[Epoch 63][Batch 299], Speed: 90.091468 samples/sec, CrossEntropy=1.988519, SmoothL1=0.891901, accuracy=0.835241
[Epoch 63][Batch 399], Speed: 94.400927 samples/sec, CrossEntropy=2.000466, SmoothL1=0.895371, accuracy=0.834395
[Epoch 63][Batch 499], Speed: 95.019651 samples/sec, CrossEntropy=1.988314, SmoothL1=0.888647, accuracy=0.835056
[Epoch 63] Training cost: 195.574846, CrossEntropy=1.990728, SmoothL1=0.890111, accuracy=0.834920
[Epoch 63] Validation:
aeroplane=0.764275
bicycle=0.817496
bird=0.703547
boat=0.641295
bottle=0.420025
bus=0.808995
car=0.833786
cat=0.849584
chair=0.562925
cow=0.788643
diningtable=0.739557
dog=0.816154
horse=0.831946
motorbike=0.823974
person=0.753941
pottedplant=0.478976
sheep=0.742493
sofa=0.763410
train=0.833418
tvmonitor=0.707766
mAP=0.734110
[Epoch 64][Batch 99], Speed: 92.579402 samples/sec, CrossEntropy=1.943817, SmoothL1=0.860396, accuracy=0.837461
[Epoch 64][Batch 199], Speed: 90.246058 samples/sec, CrossEntropy=1.949789, SmoothL1=0.870378, accuracy=0.837260
[Epoch 64][Batch 299], Speed: 82.681055 samples/sec, CrossEntropy=1.955420, SmoothL1=0.879152, accuracy=0.836404
[Epoch 64][Batch 399], Speed: 73.772595 samples/sec, CrossEntropy=1.957091, SmoothL1=0.878399, accuracy=0.836175
[Epoch 64][Batch 499], Speed: 91.814554 samples/sec, CrossEntropy=1.959455, SmoothL1=0.878463, accuracy=0.836222
[Epoch 64] Training cost: 194.133163, CrossEntropy=1.960486, SmoothL1=0.880343, accuracy=0.836184
[Epoch 64] Validation:
aeroplane=0.774430
bicycle=0.833104
bird=0.700591
boat=0.680190
bottle=0.377329
bus=0.813571
car=0.841835
cat=0.840164
chair=0.535783
cow=0.734081
diningtable=0.717934
dog=0.820503
horse=0.834683
motorbike=0.812084
person=0.746319
pottedplant=0.452719
sheep=0.687304
sofa=0.739513
train=0.836563
tvmonitor=0.698728
mAP=0.723871
[Epoch 65][Batch 99], Speed: 80.748885 samples/sec, CrossEntropy=1.939010, SmoothL1=0.876440, accuracy=0.838280
[Epoch 65][Batch 199], Speed: 86.672324 samples/sec, CrossEntropy=1.975821, SmoothL1=0.896369, accuracy=0.836244
[Epoch 65][Batch 299], Speed: 89.150471 samples/sec, CrossEntropy=1.968434, SmoothL1=0.886903, accuracy=0.836230
[Epoch 65][Batch 399], Speed: 90.882868 samples/sec, CrossEntropy=1.962106, SmoothL1=0.882143, accuracy=0.836599
[Epoch 65][Batch 499], Speed: 91.549206 samples/sec, CrossEntropy=1.971995, SmoothL1=0.886263, accuracy=0.835922
[Epoch 65] Training cost: 195.662911, CrossEntropy=1.974983, SmoothL1=0.886610, accuracy=0.835658
[Epoch 65] Validation:
aeroplane=0.767902
bicycle=0.809991
bird=0.699945
boat=0.682288
bottle=0.416684
bus=0.825787
car=0.841346
cat=0.820349
chair=0.547255
cow=0.781328
diningtable=0.709089
dog=0.818391
horse=0.837422
motorbike=0.821105
person=0.750666
pottedplant=0.434291
sheep=0.696211
sofa=0.728813
train=0.860278
tvmonitor=0.713181
mAP=0.728116
[Epoch 66][Batch 99], Speed: 90.240658 samples/sec, CrossEntropy=1.965106, SmoothL1=0.885004, accuracy=0.836431
[Epoch 66][Batch 199], Speed: 83.974673 samples/sec, CrossEntropy=1.969201, SmoothL1=0.880376, accuracy=0.836323
[Epoch 66][Batch 299], Speed: 89.971650 samples/sec, CrossEntropy=1.950217, SmoothL1=0.872822, accuracy=0.837280
[Epoch 66][Batch 399], Speed: 89.156156 samples/sec, CrossEntropy=1.965044, SmoothL1=0.876421, accuracy=0.836377
[Epoch 66][Batch 499], Speed: 93.447643 samples/sec, CrossEntropy=1.964994, SmoothL1=0.874693, accuracy=0.836282
[Epoch 66] Training cost: 194.322514, CrossEntropy=1.966532, SmoothL1=0.875369, accuracy=0.836185
[Epoch 66] Validation:
aeroplane=0.776539
bicycle=0.814430
bird=0.691099
boat=0.668626
bottle=0.439405
bus=0.804993
car=0.845282
cat=0.837110
chair=0.537384
cow=0.791350
diningtable=0.698259
dog=0.804666
horse=0.851562
motorbike=0.835894
person=0.745419
pottedplant=0.427828
sheep=0.718272
sofa=0.731022
train=0.837225
tvmonitor=0.743654
mAP=0.730001
[Epoch 67][Batch 99], Speed: 80.805618 samples/sec, CrossEntropy=1.947796, SmoothL1=0.873737, accuracy=0.837160
[Epoch 67][Batch 199], Speed: 84.075460 samples/sec, CrossEntropy=1.970147, SmoothL1=0.885953, accuracy=0.835245
[Epoch 67][Batch 299], Speed: 87.530523 samples/sec, CrossEntropy=1.957845, SmoothL1=0.876586, accuracy=0.836260
[Epoch 67][Batch 399], Speed: 85.852203 samples/sec, CrossEntropy=1.959415, SmoothL1=0.876576, accuracy=0.836193
[Epoch 67][Batch 499], Speed: 93.689124 samples/sec, CrossEntropy=1.958510, SmoothL1=0.873672, accuracy=0.836266
[Epoch 67] Training cost: 194.088687, CrossEntropy=1.960075, SmoothL1=0.874254, accuracy=0.836258
[Epoch 67] Validation:
aeroplane=0.764785
bicycle=0.810996
bird=0.716226
boat=0.662475
bottle=0.431209
bus=0.824112
car=0.836636
cat=0.850828
chair=0.562475
cow=0.796125
diningtable=0.735828
dog=0.825316
horse=0.844970
motorbike=0.834572
person=0.762640
pottedplant=0.452594
sheep=0.738331
sofa=0.761072
train=0.843207
tvmonitor=0.742783
mAP=0.739859
[Epoch 68][Batch 99], Speed: 86.563042 samples/sec, CrossEntropy=1.937365, SmoothL1=0.861909, accuracy=0.837851
[Epoch 68][Batch 199], Speed: 92.690713 samples/sec, CrossEntropy=1.938731, SmoothL1=0.863199, accuracy=0.838057
[Epoch 68][Batch 299], Speed: 91.206731 samples/sec, CrossEntropy=1.945057, SmoothL1=0.868271, accuracy=0.837980
[Epoch 68][Batch 399], Speed: 93.294543 samples/sec, CrossEntropy=1.954902, SmoothL1=0.873144, accuracy=0.837138
[Epoch 68][Batch 499], Speed: 98.197076 samples/sec, CrossEntropy=1.959792, SmoothL1=0.872967, accuracy=0.836763
[Epoch 68] Training cost: 194.333996, CrossEntropy=1.958986, SmoothL1=0.873048, accuracy=0.836679
[Epoch 68] Validation:
aeroplane=0.774219
bicycle=0.805104
bird=0.720729
boat=0.658439
bottle=0.449898
bus=0.811637
car=0.835020
cat=0.874564
chair=0.554314
cow=0.789170
diningtable=0.733653
dog=0.840436
horse=0.853124
motorbike=0.823743
person=0.756465
pottedplant=0.476578
sheep=0.744075
sofa=0.754626
train=0.850958
tvmonitor=0.738312
mAP=0.742253
[Epoch 69][Batch 99], Speed: 82.530060 samples/sec, CrossEntropy=1.915721, SmoothL1=0.841629, accuracy=0.839496
[Epoch 69][Batch 199], Speed: 93.470095 samples/sec, CrossEntropy=1.930492, SmoothL1=0.861990, accuracy=0.838430
[Epoch 69][Batch 299], Speed: 87.583128 samples/sec, CrossEntropy=1.934852, SmoothL1=0.862932, accuracy=0.838267
[Epoch 69][Batch 399], Speed: 89.246860 samples/sec, CrossEntropy=1.942169, SmoothL1=0.866753, accuracy=0.837997
[Epoch 69][Batch 499], Speed: 72.894144 samples/sec, CrossEntropy=1.944232, SmoothL1=0.868566, accuracy=0.837927
[Epoch 69] Training cost: 194.415704, CrossEntropy=1.943566, SmoothL1=0.866624, accuracy=0.837979
[Epoch 69] Validation:
aeroplane=0.774701
bicycle=0.820332
bird=0.739196
boat=0.677727
bottle=0.463497
bus=0.834534
car=0.840655
cat=0.868913
chair=0.546855
cow=0.810295
diningtable=0.738748
dog=0.821313
horse=0.823051
motorbike=0.821500
person=0.759366
pottedplant=0.464763
sheep=0.734792
sofa=0.757984
train=0.865339
tvmonitor=0.725556
mAP=0.744456
[Epoch 70][Batch 99], Speed: 80.370330 samples/sec, CrossEntropy=1.904840, SmoothL1=0.856849, accuracy=0.841682
[Epoch 70][Batch 199], Speed: 88.988279 samples/sec, CrossEntropy=1.919722, SmoothL1=0.865620, accuracy=0.839507
[Epoch 70][Batch 299], Speed: 82.148134 samples/sec, CrossEntropy=1.930552, SmoothL1=0.863464, accuracy=0.838750
[Epoch 70][Batch 399], Speed: 86.545906 samples/sec, CrossEntropy=1.931655, SmoothL1=0.867495, accuracy=0.838848
[Epoch 70][Batch 499], Speed: 93.504867 samples/sec, CrossEntropy=1.935169, SmoothL1=0.864879, accuracy=0.838538
[Epoch 70] Training cost: 194.937537, CrossEntropy=1.935847, SmoothL1=0.864566, accuracy=0.838359
[Epoch 70] Validation:
aeroplane=0.772309
bicycle=0.810040
bird=0.729137
boat=0.672243
bottle=0.446786
bus=0.834458
car=0.837630
cat=0.840965
chair=0.556352
cow=0.777422
diningtable=0.732336
dog=0.828507
horse=0.846486
motorbike=0.827035
person=0.757756
pottedplant=0.454559
sheep=0.732350
sofa=0.749386
train=0.855858
tvmonitor=0.730456
mAP=0.739604
[Epoch 71][Batch 99], Speed: 89.128211 samples/sec, CrossEntropy=1.907678, SmoothL1=0.852045, accuracy=0.839713
[Epoch 71][Batch 199], Speed: 91.056309 samples/sec, CrossEntropy=1.932900, SmoothL1=0.865978, accuracy=0.837341
[Epoch 71][Batch 299], Speed: 85.842484 samples/sec, CrossEntropy=1.924976, SmoothL1=0.854951, accuracy=0.838106
[Epoch 71][Batch 399], Speed: 91.768162 samples/sec, CrossEntropy=1.929067, SmoothL1=0.854955, accuracy=0.837834
[Epoch 71][Batch 499], Speed: 90.784941 samples/sec, CrossEntropy=1.930618, SmoothL1=0.856484, accuracy=0.837863
[Epoch 71] Training cost: 193.325677, CrossEntropy=1.929390, SmoothL1=0.855588, accuracy=0.837957
[Epoch 71] Validation:
aeroplane=0.768620
bicycle=0.819732
bird=0.717224
boat=0.653507
bottle=0.435525
bus=0.828580
car=0.844161
cat=0.868604
chair=0.552973
cow=0.780037
diningtable=0.726190
dog=0.826116
horse=0.838093
motorbike=0.803320
person=0.756260
pottedplant=0.425046
sheep=0.739756
sofa=0.751709
train=0.857342
tvmonitor=0.720396
mAP=0.735660
[Epoch 72][Batch 99], Speed: 86.059789 samples/sec, CrossEntropy=1.858434, SmoothL1=0.820642, accuracy=0.842125
[Epoch 72][Batch 199], Speed: 84.005999 samples/sec, CrossEntropy=1.897504, SmoothL1=0.843562, accuracy=0.840024
[Epoch 72][Batch 299], Speed: 89.629062 samples/sec, CrossEntropy=1.917583, SmoothL1=0.849478, accuracy=0.839238
[Epoch 72][Batch 399], Speed: 89.491253 samples/sec, CrossEntropy=1.920160, SmoothL1=0.847992, accuracy=0.839121
[Epoch 72][Batch 499], Speed: 90.755905 samples/sec, CrossEntropy=1.920321, SmoothL1=0.850114, accuracy=0.839238
[Epoch 72] Training cost: 193.859173, CrossEntropy=1.920797, SmoothL1=0.851786, accuracy=0.839182
[Epoch 72] Validation:
aeroplane=0.789890
bicycle=0.811820
bird=0.713741
boat=0.664789
bottle=0.438796
bus=0.842989
car=0.849948
cat=0.852517
chair=0.544085
cow=0.777715
diningtable=0.710256
dog=0.828947
horse=0.845241
motorbike=0.812776
person=0.753173
pottedplant=0.463949
sheep=0.735358
sofa=0.757113
train=0.857935
tvmonitor=0.753751
mAP=0.740239
[Epoch 73][Batch 99], Speed: 87.390835 samples/sec, CrossEntropy=1.894290, SmoothL1=0.832068, accuracy=0.839928
[Epoch 73][Batch 199], Speed: 86.788673 samples/sec, CrossEntropy=1.908885, SmoothL1=0.849431, accuracy=0.839286
[Epoch 73][Batch 299], Speed: 89.142004 samples/sec, CrossEntropy=1.905479, SmoothL1=0.849063, accuracy=0.839562
[Epoch 73][Batch 399], Speed: 89.193957 samples/sec, CrossEntropy=1.910745, SmoothL1=0.846738, accuracy=0.839284
[Epoch 73][Batch 499], Speed: 95.812729 samples/sec, CrossEntropy=1.914863, SmoothL1=0.847393, accuracy=0.839141
[Epoch 73] Training cost: 194.159959, CrossEntropy=1.914929, SmoothL1=0.848200, accuracy=0.839148
[Epoch 73] Validation:
aeroplane=0.779552
bicycle=0.812816
bird=0.734437
boat=0.673816
bottle=0.416586
bus=0.800625
car=0.836398
cat=0.879301
chair=0.563740
cow=0.791883
diningtable=0.718514
dog=0.833817
horse=0.832399
motorbike=0.828796
person=0.763169
pottedplant=0.440976
sheep=0.763400
sofa=0.765409
train=0.827355
tvmonitor=0.742584
mAP=0.740279
[Epoch 74][Batch 99], Speed: 88.767106 samples/sec, CrossEntropy=1.900781, SmoothL1=0.845461, accuracy=0.840248
[Epoch 74][Batch 199], Speed: 94.586937 samples/sec, CrossEntropy=1.910362, SmoothL1=0.858873, accuracy=0.839592
[Epoch 74][Batch 299], Speed: 90.339238 samples/sec, CrossEntropy=1.903150, SmoothL1=0.854763, accuracy=0.840328
[Epoch 74][Batch 399], Speed: 89.095080 samples/sec, CrossEntropy=1.911511, SmoothL1=0.851712, accuracy=0.839951
[Epoch 74][Batch 499], Speed: 98.537497 samples/sec, CrossEntropy=1.910336, SmoothL1=0.848868, accuracy=0.839965
[Epoch 74] Training cost: 194.364717, CrossEntropy=1.910388, SmoothL1=0.848092, accuracy=0.839901
[Epoch 74] Validation:
aeroplane=0.776914
bicycle=0.822870
bird=0.727799
boat=0.681396
bottle=0.452542
bus=0.829836
car=0.837950
cat=0.846929
chair=0.564134
cow=0.783984
diningtable=0.721800
dog=0.833769
horse=0.836317
motorbike=0.812150
person=0.757159
pottedplant=0.468498
sheep=0.743114
sofa=0.749504
train=0.846678
tvmonitor=0.743197
mAP=0.741827
[Epoch 75][Batch 99], Speed: 92.013582 samples/sec, CrossEntropy=1.870682, SmoothL1=0.831435, accuracy=0.843080
[Epoch 75][Batch 199], Speed: 87.458885 samples/sec, CrossEntropy=1.897538, SmoothL1=0.849607, accuracy=0.840891
[Epoch 75][Batch 299], Speed: 93.725697 samples/sec, CrossEntropy=1.906257, SmoothL1=0.854840, accuracy=0.840434
[Epoch 75][Batch 399], Speed: 92.888612 samples/sec, CrossEntropy=1.901609, SmoothL1=0.849399, accuracy=0.840834
[Epoch 75][Batch 499], Speed: 96.555071 samples/sec, CrossEntropy=1.908583, SmoothL1=0.848420, accuracy=0.840299
[Epoch 75] Training cost: 193.684409, CrossEntropy=1.906173, SmoothL1=0.845728, accuracy=0.840413
[Epoch 75] Validation:
aeroplane=0.778407
bicycle=0.823717
bird=0.714057
boat=0.662698
bottle=0.430111
bus=0.825630
car=0.842205
cat=0.881685
chair=0.565814
cow=0.787990
diningtable=0.744258
dog=0.826905
horse=0.839471
motorbike=0.816620
person=0.764206
pottedplant=0.459799
sheep=0.746624
sofa=0.759776
train=0.843920
tvmonitor=0.734447
mAP=0.742417
[Epoch 76][Batch 99], Speed: 88.221969 samples/sec, CrossEntropy=1.878960, SmoothL1=0.843378, accuracy=0.841964
[Epoch 76][Batch 199], Speed: 79.382934 samples/sec, CrossEntropy=1.889471, SmoothL1=0.850054, accuracy=0.840868
[Epoch 76][Batch 299], Speed: 86.398605 samples/sec, CrossEntropy=1.882410, SmoothL1=0.840820, accuracy=0.841415
[Epoch 76][Batch 399], Speed: 90.811477 samples/sec, CrossEntropy=1.893259, SmoothL1=0.842847, accuracy=0.841032
[Epoch 76][Batch 499], Speed: 97.307313 samples/sec, CrossEntropy=1.896853, SmoothL1=0.843274, accuracy=0.840841
[Epoch 76] Training cost: 193.973222, CrossEntropy=1.896577, SmoothL1=0.842315, accuracy=0.840950
[Epoch 76] Validation:
aeroplane=0.783686
bicycle=0.805539
bird=0.731116
boat=0.689598
bottle=0.417936
bus=0.825476
car=0.843399
cat=0.865188
chair=0.546318
cow=0.799056
diningtable=0.734727
dog=0.810989
horse=0.832897
motorbike=0.816061
person=0.758066
pottedplant=0.463281
sheep=0.741850
sofa=0.767808
train=0.847760
tvmonitor=0.746473
mAP=0.741361
[Epoch 77][Batch 99], Speed: 85.159156 samples/sec, CrossEntropy=1.892348, SmoothL1=0.835573, accuracy=0.841869
[Epoch 77][Batch 199], Speed: 89.731048 samples/sec, CrossEntropy=1.908454, SmoothL1=0.846916, accuracy=0.839955
[Epoch 77][Batch 299], Speed: 87.349828 samples/sec, CrossEntropy=1.890946, SmoothL1=0.837792, accuracy=0.841012
[Epoch 77][Batch 399], Speed: 91.916415 samples/sec, CrossEntropy=1.909563, SmoothL1=0.848121, accuracy=0.839973
[Epoch 77][Batch 499], Speed: 92.831626 samples/sec, CrossEntropy=1.909648, SmoothL1=0.845116, accuracy=0.840065
[Epoch 77] Training cost: 194.740102, CrossEntropy=1.909491, SmoothL1=0.846237, accuracy=0.840127
[Epoch 77] Validation:
aeroplane=0.793426
bicycle=0.830760
bird=0.735467
boat=0.640878
bottle=0.455786
bus=0.809584
car=0.839162
cat=0.859077
chair=0.549647
cow=0.780352
diningtable=0.728731
dog=0.824573
horse=0.835793
motorbike=0.821753
person=0.758822
pottedplant=0.474924
sheep=0.726862
sofa=0.772253
train=0.846892
tvmonitor=0.736675
mAP=0.741071
[Epoch 78][Batch 99], Speed: 88.438274 samples/sec, CrossEntropy=1.849354, SmoothL1=0.825941, accuracy=0.842818
[Epoch 78][Batch 199], Speed: 92.515077 samples/sec, CrossEntropy=1.855669, SmoothL1=0.833633, accuracy=0.843028
[Epoch 78][Batch 299], Speed: 89.733028 samples/sec, CrossEntropy=1.865075, SmoothL1=0.834550, accuracy=0.842946
[Epoch 78][Batch 399], Speed: 88.427495 samples/sec, CrossEntropy=1.869762, SmoothL1=0.836261, accuracy=0.842531
[Epoch 78][Batch 499], Speed: 90.077138 samples/sec, CrossEntropy=1.875478, SmoothL1=0.835352, accuracy=0.842019
[Epoch 78] Training cost: 194.633219, CrossEntropy=1.877172, SmoothL1=0.834740, accuracy=0.841920
[Epoch 78] Validation:
aeroplane=0.783431
bicycle=0.817567
bird=0.737235
boat=0.657652
bottle=0.439028
bus=0.821200
car=0.847585
cat=0.864806
chair=0.547320
cow=0.827665
diningtable=0.737546
dog=0.836666
horse=0.848056
motorbike=0.817814
person=0.761680
pottedplant=0.480855
sheep=0.749099
sofa=0.765302
train=0.833111
tvmonitor=0.735424
mAP=0.745452
[Epoch 79][Batch 99], Speed: 89.525695 samples/sec, CrossEntropy=1.821623, SmoothL1=0.807478, accuracy=0.847249
[Epoch 79][Batch 199], Speed: 94.367409 samples/sec, CrossEntropy=1.853804, SmoothL1=0.830950, accuracy=0.844289
[Epoch 79][Batch 299], Speed: 94.329738 samples/sec, CrossEntropy=1.858862, SmoothL1=0.828889, accuracy=0.843757
[Epoch 79][Batch 399], Speed: 85.785094 samples/sec, CrossEntropy=1.862359, SmoothL1=0.830377, accuracy=0.843001
[Epoch 79][Batch 499], Speed: 93.950070 samples/sec, CrossEntropy=1.860936, SmoothL1=0.828936, accuracy=0.843098
[Epoch 79] Training cost: 194.560987, CrossEntropy=1.861464, SmoothL1=0.828610, accuracy=0.843152
[Epoch 79] Validation:
aeroplane=0.794064
bicycle=0.813858
bird=0.712011
boat=0.686141
bottle=0.430287
bus=0.806236
car=0.833141
cat=0.860660
chair=0.548725
cow=0.733723
diningtable=0.753489
dog=0.803817
horse=0.837174
motorbike=0.818263
person=0.752063
pottedplant=0.454372
sheep=0.716527
sofa=0.749749
train=0.850835
tvmonitor=0.723743
mAP=0.733944
[Epoch 80][Batch 99], Speed: 85.431591 samples/sec, CrossEntropy=1.853402, SmoothL1=0.808369, accuracy=0.843161
[Epoch 80][Batch 199], Speed: 90.575964 samples/sec, CrossEntropy=1.872817, SmoothL1=0.822478, accuracy=0.842139
[Epoch 80][Batch 299], Speed: 96.362493 samples/sec, CrossEntropy=1.873040, SmoothL1=0.826810, accuracy=0.842377
[Epoch 80][Batch 399], Speed: 93.776316 samples/sec, CrossEntropy=1.876387, SmoothL1=0.830656, accuracy=0.842174
[Epoch 80][Batch 499], Speed: 96.058423 samples/sec, CrossEntropy=1.879134, SmoothL1=0.831286, accuracy=0.841985
[Epoch 80] Training cost: 193.533066, CrossEntropy=1.880838, SmoothL1=0.831615, accuracy=0.841935
[Epoch 80] Validation:
aeroplane=0.786988
bicycle=0.819760
bird=0.727969
boat=0.667215
bottle=0.411289
bus=0.842763
car=0.842615
cat=0.858505
chair=0.544616
cow=0.773561
diningtable=0.724456
dog=0.820582
horse=0.833335
motorbike=0.819817
person=0.751864
pottedplant=0.458945
sheep=0.719340
sofa=0.766975
train=0.854401
tvmonitor=0.746858
mAP=0.738593
[Epoch 81][Batch 99], Speed: 92.527577 samples/sec, CrossEntropy=1.832209, SmoothL1=0.807790, accuracy=0.845195
[Epoch 81][Batch 199], Speed: 94.186095 samples/sec, CrossEntropy=1.847937, SmoothL1=0.820440, accuracy=0.843876
[Epoch 81][Batch 299], Speed: 87.090069 samples/sec, CrossEntropy=1.855520, SmoothL1=0.824565, accuracy=0.843668
[Epoch 81][Batch 399], Speed: 92.527833 samples/sec, CrossEntropy=1.862985, SmoothL1=0.828649, accuracy=0.843188
[Epoch 81][Batch 499], Speed: 87.048272 samples/sec, CrossEntropy=1.865733, SmoothL1=0.828002, accuracy=0.843306
[Epoch 81] Training cost: 194.978845, CrossEntropy=1.865922, SmoothL1=0.826938, accuracy=0.843300
[Epoch 81] Validation:
aeroplane=0.780512
bicycle=0.800876
bird=0.726636
boat=0.704381
bottle=0.433818
bus=0.818644
car=0.837044
cat=0.861731
chair=0.567244
cow=0.765096
diningtable=0.741695
dog=0.807972
horse=0.791904
motorbike=0.817470
person=0.763501
pottedplant=0.449302
sheep=0.717439
sofa=0.763903
train=0.849997
tvmonitor=0.735435
mAP=0.736730
[Epoch 82][Batch 99], Speed: 83.733685 samples/sec, CrossEntropy=1.860176, SmoothL1=0.831688, accuracy=0.844220
[Epoch 82][Batch 199], Speed: 89.517455 samples/sec, CrossEntropy=1.873254, SmoothL1=0.833085, accuracy=0.843072
[Epoch 82][Batch 299], Speed: 95.382605 samples/sec, CrossEntropy=1.870807, SmoothL1=0.835681, accuracy=0.842574
[Epoch 82][Batch 399], Speed: 93.946782 samples/sec, CrossEntropy=1.868897, SmoothL1=0.833512, accuracy=0.842598
[Epoch 82][Batch 499], Speed: 97.413815 samples/sec, CrossEntropy=1.863719, SmoothL1=0.828665, accuracy=0.842766
[Epoch 82] Training cost: 194.582376, CrossEntropy=1.865404, SmoothL1=0.830530, accuracy=0.842604
[Epoch 82] Validation:
aeroplane=0.776315
bicycle=0.808289
bird=0.716088
boat=0.662387
bottle=0.433343
bus=0.806726
car=0.845298
cat=0.841818
chair=0.530695
cow=0.810286
diningtable=0.728532
dog=0.805097
horse=0.845165
motorbike=0.807229
person=0.764872
pottedplant=0.461410
sheep=0.716021
sofa=0.736084
train=0.840222
tvmonitor=0.721720
mAP=0.732880
[Epoch 83][Batch 99], Speed: 88.947351 samples/sec, CrossEntropy=1.858185, SmoothL1=0.808665, accuracy=0.843660
[Epoch 83][Batch 199], Speed: 95.547265 samples/sec, CrossEntropy=1.856847, SmoothL1=0.818820, accuracy=0.843796
[Epoch 83][Batch 299], Speed: 93.646765 samples/sec, CrossEntropy=1.849146, SmoothL1=0.818233, accuracy=0.844229
[Epoch 83][Batch 399], Speed: 88.422718 samples/sec, CrossEntropy=1.848267, SmoothL1=0.818749, accuracy=0.844300
[Epoch 83][Batch 499], Speed: 92.907130 samples/sec, CrossEntropy=1.850340, SmoothL1=0.820442, accuracy=0.844094
[Epoch 83] Training cost: 193.790162, CrossEntropy=1.849778, SmoothL1=0.819308, accuracy=0.844070
[Epoch 83] Validation:
aeroplane=0.772544
bicycle=0.836629
bird=0.722760
boat=0.678496
bottle=0.461668
bus=0.838035
car=0.832520
cat=0.867501
chair=0.581279
cow=0.800089
diningtable=0.731348
dog=0.811042
horse=0.845579
motorbike=0.823918
person=0.758005
pottedplant=0.460340
sheep=0.718453
sofa=0.783111
train=0.847832
tvmonitor=0.743574
mAP=0.745736
[Epoch 84][Batch 99], Speed: 89.718572 samples/sec, CrossEntropy=1.807470, SmoothL1=0.805574, accuracy=0.846593
[Epoch 84][Batch 199], Speed: 92.971615 samples/sec, CrossEntropy=1.842887, SmoothL1=0.822247, accuracy=0.844947
[Epoch 84][Batch 299], Speed: 89.652950 samples/sec, CrossEntropy=1.841511, SmoothL1=0.820938, accuracy=0.844807
[Epoch 84][Batch 399], Speed: 87.944902 samples/sec, CrossEntropy=1.842519, SmoothL1=0.819309, accuracy=0.844741
[Epoch 84][Batch 499], Speed: 91.782784 samples/sec, CrossEntropy=1.842067, SmoothL1=0.820209, accuracy=0.844662
[Epoch 84] Training cost: 194.750146, CrossEntropy=1.841850, SmoothL1=0.819794, accuracy=0.844768
[Epoch 84] Validation:
aeroplane=0.795167
bicycle=0.830247
bird=0.709428
boat=0.678199
bottle=0.456873
bus=0.813691
car=0.840885
cat=0.872864
chair=0.561651
cow=0.817732
diningtable=0.740154
dog=0.831193
horse=0.856369
motorbike=0.838033
person=0.763603
pottedplant=0.471908
sheep=0.755203
sofa=0.766330
train=0.837183
tvmonitor=0.741441
mAP=0.748908
[Epoch 85][Batch 99], Speed: 87.981279 samples/sec, CrossEntropy=1.809835, SmoothL1=0.829140, accuracy=0.846496
[Epoch 85][Batch 199], Speed: 94.014431 samples/sec, CrossEntropy=1.835532, SmoothL1=0.830482, accuracy=0.844946
[Epoch 85][Batch 299], Speed: 90.792679 samples/sec, CrossEntropy=1.841608, SmoothL1=0.826430, accuracy=0.845036
[Epoch 85][Batch 399], Speed: 80.336079 samples/sec, CrossEntropy=1.844330, SmoothL1=0.821311, accuracy=0.845093
[Epoch 85][Batch 499], Speed: 92.510103 samples/sec, CrossEntropy=1.843655, SmoothL1=0.817708, accuracy=0.845002
[Epoch 85] Training cost: 193.786481, CrossEntropy=1.842632, SmoothL1=0.817425, accuracy=0.845073
[Epoch 85] Validation:
aeroplane=0.794726
bicycle=0.814115
bird=0.722955
boat=0.673871
bottle=0.420911
bus=0.839723
car=0.842388
cat=0.859650
chair=0.558169
cow=0.807570
diningtable=0.702141
dog=0.829842
horse=0.846778
motorbike=0.835549
person=0.767095
pottedplant=0.476971
sheep=0.736249
sofa=0.755973
train=0.853319
tvmonitor=0.742487
mAP=0.744024
[Epoch 86][Batch 99], Speed: 87.462076 samples/sec, CrossEntropy=1.784235, SmoothL1=0.798259, accuracy=0.848142
[Epoch 86][Batch 199], Speed: 84.901609 samples/sec, CrossEntropy=1.808419, SmoothL1=0.796330, accuracy=0.847347
[Epoch 86][Batch 299], Speed: 94.351753 samples/sec, CrossEntropy=1.821570, SmoothL1=0.799830, accuracy=0.846108
[Epoch 86][Batch 399], Speed: 88.576540 samples/sec, CrossEntropy=1.829318, SmoothL1=0.804896, accuracy=0.845174
[Epoch 86][Batch 499], Speed: 97.468710 samples/sec, CrossEntropy=1.828102, SmoothL1=0.803994, accuracy=0.845324
[Epoch 86] Training cost: 194.937745, CrossEntropy=1.830329, SmoothL1=0.805574, accuracy=0.845233
[Epoch 86] Validation:
aeroplane=0.773208
bicycle=0.814116
bird=0.734951
boat=0.672843
bottle=0.426310
bus=0.802526
car=0.839860
cat=0.872207
chair=0.560289
cow=0.824055
diningtable=0.762289
dog=0.825224
horse=0.848106
motorbike=0.829618
person=0.767090
pottedplant=0.466353
sheep=0.730670
sofa=0.777729
train=0.848470
tvmonitor=0.745246
mAP=0.746058
[Epoch 87][Batch 99], Speed: 90.261595 samples/sec, CrossEntropy=1.844849, SmoothL1=0.818757, accuracy=0.843638
[Epoch 87][Batch 199], Speed: 86.793331 samples/sec, CrossEntropy=1.855432, SmoothL1=0.825934, accuracy=0.843602
[Epoch 87][Batch 299], Speed: 86.831233 samples/sec, CrossEntropy=1.855706, SmoothL1=0.825231, accuracy=0.843536
[Epoch 87][Batch 399], Speed: 89.564407 samples/sec, CrossEntropy=1.848979, SmoothL1=0.816923, accuracy=0.844256
[Epoch 87][Batch 499], Speed: 94.861429 samples/sec, CrossEntropy=1.852827, SmoothL1=0.816881, accuracy=0.843981
[Epoch 87] Training cost: 194.033523, CrossEntropy=1.852624, SmoothL1=0.816590, accuracy=0.843960
[Epoch 87] Validation:
aeroplane=0.787614
bicycle=0.805614
bird=0.727128
boat=0.658843
bottle=0.444586
bus=0.831359
car=0.845017
cat=0.849185
chair=0.561958
cow=0.767685
diningtable=0.764123
dog=0.828199
horse=0.837232
motorbike=0.819810
person=0.773540
pottedplant=0.465651
sheep=0.723979
sofa=0.773718
train=0.845626
tvmonitor=0.730688
mAP=0.742078
[Epoch 88][Batch 99], Speed: 88.815977 samples/sec, CrossEntropy=1.814733, SmoothL1=0.820300, accuracy=0.845570
[Epoch 88][Batch 199], Speed: 83.799295 samples/sec, CrossEntropy=1.835354, SmoothL1=0.825617, accuracy=0.844922
[Epoch 88][Batch 299], Speed: 91.846094 samples/sec, CrossEntropy=1.830635, SmoothL1=0.825289, accuracy=0.844995
[Epoch 88][Batch 399], Speed: 80.423256 samples/sec, CrossEntropy=1.836352, SmoothL1=0.822709, accuracy=0.844956
[Epoch 88][Batch 499], Speed: 89.500741 samples/sec, CrossEntropy=1.834855, SmoothL1=0.821551, accuracy=0.844887
[Epoch 88] Training cost: 194.809743, CrossEntropy=1.835810, SmoothL1=0.821180, accuracy=0.844882
[Epoch 88] Validation:
aeroplane=0.770578
bicycle=0.811014
bird=0.741127
boat=0.687552
bottle=0.464696
bus=0.827887
car=0.842497
cat=0.880196
chair=0.544506
cow=0.798780
diningtable=0.739224
dog=0.838031
horse=0.831709
motorbike=0.813829
person=0.766894
pottedplant=0.469688
sheep=0.718614
sofa=0.774643
train=0.857364
tvmonitor=0.735891
mAP=0.745736
[Epoch 89][Batch 99], Speed: 88.871022 samples/sec, CrossEntropy=1.805788, SmoothL1=0.805677, accuracy=0.846276
[Epoch 89][Batch 199], Speed: 84.864783 samples/sec, CrossEntropy=1.830519, SmoothL1=0.824183, accuracy=0.845081
[Epoch 89][Batch 299], Speed: 91.100128 samples/sec, CrossEntropy=1.825844, SmoothL1=0.819809, accuracy=0.845890
[Epoch 89][Batch 399], Speed: 89.437821 samples/sec, CrossEntropy=1.836007, SmoothL1=0.818764, accuracy=0.845542
[Epoch 89][Batch 499], Speed: 92.487154 samples/sec, CrossEntropy=1.831612, SmoothL1=0.812560, accuracy=0.845865
[Epoch 89] Training cost: 194.647900, CrossEntropy=1.832224, SmoothL1=0.812649, accuracy=0.845810
[Epoch 89] Validation:
aeroplane=0.789467
bicycle=0.815504
bird=0.736400
boat=0.698874
bottle=0.468965
bus=0.819683
car=0.841002
cat=0.851056
chair=0.566206
cow=0.793087
diningtable=0.750397
dog=0.821513
horse=0.844522
motorbike=0.834244
person=0.759157
pottedplant=0.495586
sheep=0.727777
sofa=0.761740
train=0.843175
tvmonitor=0.730459
mAP=0.747441
[Epoch 90][Batch 99], Speed: 87.909247 samples/sec, CrossEntropy=1.835954, SmoothL1=0.824289, accuracy=0.845801
[Epoch 90][Batch 199], Speed: 88.573033 samples/sec, CrossEntropy=1.856658, SmoothL1=0.832503, accuracy=0.844860
[Epoch 90][Batch 299], Speed: 89.506531 samples/sec, CrossEntropy=1.843226, SmoothL1=0.818133, accuracy=0.845700
[Epoch 90][Batch 399], Speed: 84.906282 samples/sec, CrossEntropy=1.840538, SmoothL1=0.815642, accuracy=0.845507
[Epoch 90][Batch 499], Speed: 88.458850 samples/sec, CrossEntropy=1.842021, SmoothL1=0.813577, accuracy=0.845290
[Epoch 90] Training cost: 194.139889, CrossEntropy=1.844102, SmoothL1=0.813695, accuracy=0.845167
[Epoch 90] Validation:
aeroplane=0.797188
bicycle=0.817764
bird=0.729325
boat=0.679493
bottle=0.457113
bus=0.833620
car=0.839794
cat=0.842565
chair=0.561004
cow=0.789337
diningtable=0.754955
dog=0.817411
horse=0.833977
motorbike=0.828488
person=0.764829
pottedplant=0.468585
sheep=0.737457
sofa=0.779834
train=0.837482
tvmonitor=0.741922
mAP=0.745607
[Epoch 91][Batch 99], Speed: 92.891441 samples/sec, CrossEntropy=1.752345, SmoothL1=0.761276, accuracy=0.851023
[Epoch 91][Batch 199], Speed: 88.202200 samples/sec, CrossEntropy=1.804759, SmoothL1=0.789079, accuracy=0.847681
[Epoch 91][Batch 299], Speed: 87.567128 samples/sec, CrossEntropy=1.816776, SmoothL1=0.802228, accuracy=0.846604
[Epoch 91][Batch 399], Speed: 83.560195 samples/sec, CrossEntropy=1.818686, SmoothL1=0.804583, accuracy=0.846233
[Epoch 91][Batch 499], Speed: 92.458102 samples/sec, CrossEntropy=1.813227, SmoothL1=0.799118, accuracy=0.846644
[Epoch 91] Training cost: 194.799224, CrossEntropy=1.814037, SmoothL1=0.799274, accuracy=0.846577
[Epoch 91] Validation:
aeroplane=0.787766
bicycle=0.808494
bird=0.741212
boat=0.671959
bottle=0.447620
bus=0.793537
car=0.839581
cat=0.851819
chair=0.546129
cow=0.807922
diningtable=0.736058
dog=0.827424
horse=0.854275
motorbike=0.814943
person=0.763132
pottedplant=0.464849
sheep=0.736344
sofa=0.782912
train=0.840243
tvmonitor=0.742250
mAP=0.742923
[Epoch 92][Batch 99], Speed: 90.882683 samples/sec, CrossEntropy=1.791052, SmoothL1=0.791870, accuracy=0.848077
[Epoch 92][Batch 199], Speed: 95.543185 samples/sec, CrossEntropy=1.826833, SmoothL1=0.809499, accuracy=0.846236
[Epoch 92][Batch 299], Speed: 88.558422 samples/sec, CrossEntropy=1.822054, SmoothL1=0.805903, accuracy=0.846669
[Epoch 92][Batch 399], Speed: 90.098120 samples/sec, CrossEntropy=1.812722, SmoothL1=0.798923, accuracy=0.847309
[Epoch 92][Batch 499], Speed: 97.411764 samples/sec, CrossEntropy=1.814973, SmoothL1=0.800057, accuracy=0.847066
[Epoch 92] Training cost: 193.899822, CrossEntropy=1.817145, SmoothL1=0.802391, accuracy=0.846809
[Epoch 92] Validation:
aeroplane=0.790734
bicycle=0.823512
bird=0.738963
boat=0.673160
bottle=0.462131
bus=0.827046
car=0.849727
cat=0.866319
chair=0.559497
cow=0.790519
diningtable=0.740275
dog=0.832664
horse=0.843895
motorbike=0.826472
person=0.767358
pottedplant=0.458672
sheep=0.708197
sofa=0.782368
train=0.825551
tvmonitor=0.753408
mAP=0.746023
[Epoch 93][Batch 99], Speed: 87.595017 samples/sec, CrossEntropy=1.802826, SmoothL1=0.795359, accuracy=0.847998
[Epoch 93][Batch 199], Speed: 85.125885 samples/sec, CrossEntropy=1.815841, SmoothL1=0.799890, accuracy=0.847337
[Epoch 93][Batch 299], Speed: 86.179533 samples/sec, CrossEntropy=1.806459, SmoothL1=0.794653, accuracy=0.848029
[Epoch 93][Batch 399], Speed: 93.445431 samples/sec, CrossEntropy=1.810354, SmoothL1=0.794636, accuracy=0.847389
[Epoch 93][Batch 499], Speed: 95.218308 samples/sec, CrossEntropy=1.811582, SmoothL1=0.796383, accuracy=0.847010
[Epoch 93] Training cost: 193.687865, CrossEntropy=1.813467, SmoothL1=0.796439, accuracy=0.846863
[Epoch 93] Validation:
aeroplane=0.786405
bicycle=0.823194
bird=0.712074
boat=0.662603
bottle=0.436265
bus=0.800519
car=0.840942
cat=0.858705
chair=0.552885
cow=0.759269
diningtable=0.736610
dog=0.813976
horse=0.832635
motorbike=0.824026
person=0.766047
pottedplant=0.479384
sheep=0.732756
sofa=0.781447
train=0.847696
tvmonitor=0.736879
mAP=0.739216
[Epoch 94][Batch 99], Speed: 88.280577 samples/sec, CrossEntropy=1.808088, SmoothL1=0.790659, accuracy=0.847118
[Epoch 94][Batch 199], Speed: 81.287915 samples/sec, CrossEntropy=1.804742, SmoothL1=0.800978, accuracy=0.847476
[Epoch 94][Batch 299], Speed: 83.240963 samples/sec, CrossEntropy=1.807113, SmoothL1=0.804464, accuracy=0.847665
[Epoch 94][Batch 399], Speed: 86.722166 samples/sec, CrossEntropy=1.810310, SmoothL1=0.797923, accuracy=0.847199
[Epoch 94][Batch 499], Speed: 95.551211 samples/sec, CrossEntropy=1.807813, SmoothL1=0.794464, accuracy=0.847646
[Epoch 94] Training cost: 194.215552, CrossEntropy=1.806193, SmoothL1=0.794211, accuracy=0.847707
[Epoch 94] Validation:
aeroplane=0.779430
bicycle=0.806319
bird=0.710447
boat=0.664638
bottle=0.451193
bus=0.833315
car=0.842763
cat=0.824635
chair=0.559881
cow=0.802296
diningtable=0.760086
dog=0.830952
horse=0.842842
motorbike=0.816413
person=0.762789
pottedplant=0.493480
sheep=0.711542
sofa=0.729393
train=0.848894
tvmonitor=0.740705
mAP=0.740601
[Epoch 95][Batch 99], Speed: 86.811744 samples/sec, CrossEntropy=1.776794, SmoothL1=0.769302, accuracy=0.849335
[Epoch 95][Batch 199], Speed: 83.666508 samples/sec, CrossEntropy=1.803199, SmoothL1=0.787348, accuracy=0.847237
[Epoch 95][Batch 299], Speed: 89.472282 samples/sec, CrossEntropy=1.802618, SmoothL1=0.792001, accuracy=0.847568
[Epoch 95][Batch 399], Speed: 80.454639 samples/sec, CrossEntropy=1.799186, SmoothL1=0.790596, accuracy=0.848082
[Epoch 95][Batch 499], Speed: 100.771625 samples/sec, CrossEntropy=1.803317, SmoothL1=0.790919, accuracy=0.847806
[Epoch 95] Training cost: 193.897949, CrossEntropy=1.804597, SmoothL1=0.791388, accuracy=0.847860
[Epoch 95] Validation:
aeroplane=0.785864
bicycle=0.823366
bird=0.724472
boat=0.696270
bottle=0.432484
bus=0.840098
car=0.841509
cat=0.868051
chair=0.548315
cow=0.817196
diningtable=0.740788
dog=0.846003
horse=0.843361
motorbike=0.821934
person=0.767776
pottedplant=0.466471
sheep=0.752475
sofa=0.777358
train=0.846036
tvmonitor=0.753819
mAP=0.749682
[Epoch 96][Batch 99], Speed: 93.292144 samples/sec, CrossEntropy=1.765338, SmoothL1=0.784764, accuracy=0.851994
[Epoch 96][Batch 199], Speed: 94.383203 samples/sec, CrossEntropy=1.794121, SmoothL1=0.804252, accuracy=0.849070
[Epoch 96][Batch 299], Speed: 83.748784 samples/sec, CrossEntropy=1.812732, SmoothL1=0.808970, accuracy=0.847871
[Epoch 96][Batch 399], Speed: 82.494450 samples/sec, CrossEntropy=1.811053, SmoothL1=0.803212, accuracy=0.848140
[Epoch 96][Batch 499], Speed: 91.236119 samples/sec, CrossEntropy=1.807167, SmoothL1=0.799495, accuracy=0.848449
[Epoch 96] Training cost: 194.362266, CrossEntropy=1.806150, SmoothL1=0.798592, accuracy=0.848448
[Epoch 96] Validation:
aeroplane=0.807816
bicycle=0.822543
bird=0.734469
boat=0.673721
bottle=0.444580
bus=0.823417
car=0.843079
cat=0.870453
chair=0.559274
cow=0.799564
diningtable=0.753848
dog=0.820979
horse=0.848581
motorbike=0.820764
person=0.766059
pottedplant=0.487476
sheep=0.743406
sofa=0.754021
train=0.839404
tvmonitor=0.746724
mAP=0.748009
[Epoch 97][Batch 99], Speed: 79.588878 samples/sec, CrossEntropy=1.790446, SmoothL1=0.777689, accuracy=0.850575
[Epoch 97][Batch 199], Speed: 92.088267 samples/sec, CrossEntropy=1.812799, SmoothL1=0.790541, accuracy=0.848219
[Epoch 97][Batch 299], Speed: 86.750024 samples/sec, CrossEntropy=1.802291, SmoothL1=0.789492, accuracy=0.848771
[Epoch 97][Batch 399], Speed: 83.416705 samples/sec, CrossEntropy=1.800228, SmoothL1=0.791095, accuracy=0.848330
[Epoch 97][Batch 499], Speed: 96.352324 samples/sec, CrossEntropy=1.798471, SmoothL1=0.788727, accuracy=0.848358
[Epoch 97] Training cost: 194.575964, CrossEntropy=1.800775, SmoothL1=0.788720, accuracy=0.848240
[Epoch 97] Validation:
aeroplane=0.800652
bicycle=0.821153
bird=0.731824
boat=0.689381
bottle=0.466821
bus=0.822711
car=0.848725
cat=0.881687
chair=0.565616
cow=0.782099
diningtable=0.721773
dog=0.824622
horse=0.849665
motorbike=0.826376
person=0.772858
pottedplant=0.456342
sheep=0.742778
sofa=0.771034
train=0.841711
tvmonitor=0.755867
mAP=0.748685
[Epoch 98][Batch 99], Speed: 89.744728 samples/sec, CrossEntropy=1.770703, SmoothL1=0.784107, accuracy=0.849010
[Epoch 98][Batch 199], Speed: 86.131640 samples/sec, CrossEntropy=1.774042, SmoothL1=0.786201, accuracy=0.849441
[Epoch 98][Batch 299], Speed: 92.143838 samples/sec, CrossEntropy=1.781122, SmoothL1=0.790352, accuracy=0.849355
[Epoch 98][Batch 399], Speed: 86.497828 samples/sec, CrossEntropy=1.787372, SmoothL1=0.796233, accuracy=0.849085
[Epoch 98][Batch 499], Speed: 97.718429 samples/sec, CrossEntropy=1.785443, SmoothL1=0.794579, accuracy=0.849324
[Epoch 98] Training cost: 194.044728, CrossEntropy=1.787649, SmoothL1=0.794950, accuracy=0.849146
[Epoch 98] Validation:
aeroplane=0.784347
bicycle=0.821027
bird=0.746455
boat=0.686594
bottle=0.475925
bus=0.818834
car=0.847919
cat=0.881493
chair=0.550692
cow=0.805192
diningtable=0.747052
dog=0.834178
horse=0.841416
motorbike=0.800938
person=0.770333
pottedplant=0.478188
sheep=0.732111
sofa=0.780740
train=0.857919
tvmonitor=0.747197
mAP=0.750427
[Epoch 99][Batch 99], Speed: 93.275417 samples/sec, CrossEntropy=1.734143, SmoothL1=0.766048, accuracy=0.851358
[Epoch 99][Batch 199], Speed: 84.159018 samples/sec, CrossEntropy=1.759794, SmoothL1=0.777745, accuracy=0.850561
[Epoch 99][Batch 299], Speed: 86.766063 samples/sec, CrossEntropy=1.767232, SmoothL1=0.782370, accuracy=0.850657
[Epoch 99][Batch 399], Speed: 86.592138 samples/sec, CrossEntropy=1.775844, SmoothL1=0.787007, accuracy=0.849851
[Epoch 99][Batch 499], Speed: 98.163824 samples/sec, CrossEntropy=1.774388, SmoothL1=0.783961, accuracy=0.849954
[Epoch 99] Training cost: 194.024897, CrossEntropy=1.773826, SmoothL1=0.782989, accuracy=0.850070
[Epoch 99] Validation:
aeroplane=0.807737
bicycle=0.819080
bird=0.757791
boat=0.679034
bottle=0.486830
bus=0.843756
car=0.846969
cat=0.884153
chair=0.573894
cow=0.830842
diningtable=0.752907
dog=0.831540
horse=0.866454
motorbike=0.839334
person=0.769711
pottedplant=0.459765
sheep=0.738822
sofa=0.783696
train=0.851398
tvmonitor=0.751204
mAP=0.758746
[Epoch 100][Batch 99], Speed: 85.789480 samples/sec, CrossEntropy=1.766483, SmoothL1=0.780100, accuracy=0.851446
[Epoch 100][Batch 199], Speed: 93.403032 samples/sec, CrossEntropy=1.757533, SmoothL1=0.771982, accuracy=0.851475
[Epoch 100][Batch 299], Speed: 90.183964 samples/sec, CrossEntropy=1.767147, SmoothL1=0.774924, accuracy=0.850673
[Epoch 100][Batch 399], Speed: 81.429752 samples/sec, CrossEntropy=1.771206, SmoothL1=0.774522, accuracy=0.850361
[Epoch 100][Batch 499], Speed: 97.434605 samples/sec, CrossEntropy=1.770226, SmoothL1=0.776361, accuracy=0.850308
[Epoch 100] Training cost: 194.694993, CrossEntropy=1.767299, SmoothL1=0.775279, accuracy=0.850549
[Epoch 100] Validation:
aeroplane=0.792324
bicycle=0.820259
bird=0.694447
boat=0.658597
bottle=0.444078
bus=0.823762
car=0.847495
cat=0.869396
chair=0.572436
cow=0.793548
diningtable=0.737481
dog=0.828901
horse=0.854912
motorbike=0.821808
person=0.761747
pottedplant=0.486745
sheep=0.740502
sofa=0.781049
train=0.828664
tvmonitor=0.750592
mAP=0.745437
[Epoch 101][Batch 99], Speed: 82.357120 samples/sec, CrossEntropy=1.746148, SmoothL1=0.752282, accuracy=0.852641
[Epoch 101][Batch 199], Speed: 92.413603 samples/sec, CrossEntropy=1.762333, SmoothL1=0.776172, accuracy=0.851490
[Epoch 101][Batch 299], Speed: 86.185841 samples/sec, CrossEntropy=1.762469, SmoothL1=0.775615, accuracy=0.851065
[Epoch 101][Batch 399], Speed: 93.370933 samples/sec, CrossEntropy=1.772175, SmoothL1=0.780279, accuracy=0.850238
[Epoch 101][Batch 499], Speed: 96.461875 samples/sec, CrossEntropy=1.780072, SmoothL1=0.782028, accuracy=0.849673
[Epoch 101] Training cost: 193.849438, CrossEntropy=1.781180, SmoothL1=0.782706, accuracy=0.849654
[Epoch 101] Validation:
aeroplane=0.801057
bicycle=0.820419
bird=0.734966
boat=0.686168
bottle=0.442713
bus=0.835755
car=0.843697
cat=0.865542
chair=0.567391
cow=0.784058
diningtable=0.733458
dog=0.821626
horse=0.829886
motorbike=0.845484
person=0.763412
pottedplant=0.479349
sheep=0.742635
sofa=0.754502
train=0.839610
tvmonitor=0.732212
mAP=0.746197
[Epoch 102][Batch 99], Speed: 93.749854 samples/sec, CrossEntropy=1.733314, SmoothL1=0.754892, accuracy=0.852979
[Epoch 102][Batch 199], Speed: 85.332465 samples/sec, CrossEntropy=1.771691, SmoothL1=0.775638, accuracy=0.849882
[Epoch 102][Batch 299], Speed: 89.299351 samples/sec, CrossEntropy=1.762581, SmoothL1=0.774124, accuracy=0.850300
[Epoch 102][Batch 399], Speed: 84.719401 samples/sec, CrossEntropy=1.768533, SmoothL1=0.780301, accuracy=0.850071
[Epoch 102][Batch 499], Speed: 96.305727 samples/sec, CrossEntropy=1.764128, SmoothL1=0.778235, accuracy=0.850317
[Epoch 102] Training cost: 194.589132, CrossEntropy=1.762680, SmoothL1=0.777880, accuracy=0.850309
[Epoch 102] Validation:
aeroplane=0.783678
bicycle=0.821110
bird=0.734292
boat=0.666305
bottle=0.463979
bus=0.840994
car=0.843076
cat=0.878779
chair=0.561186
cow=0.827820
diningtable=0.742343
dog=0.832353
horse=0.847612
motorbike=0.819505
person=0.765582
pottedplant=0.488363
sheep=0.742137
sofa=0.781476
train=0.853415
tvmonitor=0.741992
mAP=0.751800
[Epoch 103][Batch 99], Speed: 85.135011 samples/sec, CrossEntropy=1.744285, SmoothL1=0.760051, accuracy=0.854002
[Epoch 103][Batch 199], Speed: 88.411826 samples/sec, CrossEntropy=1.759323, SmoothL1=0.779290, accuracy=0.852277
[Epoch 103][Batch 299], Speed: 89.348513 samples/sec, CrossEntropy=1.769555, SmoothL1=0.785874, accuracy=0.851168
[Epoch 103][Batch 399], Speed: 91.532973 samples/sec, CrossEntropy=1.774200, SmoothL1=0.782675, accuracy=0.850867
[Epoch 103][Batch 499], Speed: 89.548034 samples/sec, CrossEntropy=1.774385, SmoothL1=0.780891, accuracy=0.850356
[Epoch 103] Training cost: 194.625368, CrossEntropy=1.772110, SmoothL1=0.779425, accuracy=0.850403
[Epoch 103] Validation:
aeroplane=0.803578
bicycle=0.830428
bird=0.740242
boat=0.699583
bottle=0.453024
bus=0.818846
car=0.843524
cat=0.844401
chair=0.545041
cow=0.807512
diningtable=0.715117
dog=0.814839
horse=0.849129
motorbike=0.843727
person=0.774161
pottedplant=0.475855
sheep=0.749694
sofa=0.781138
train=0.858537
tvmonitor=0.752375
mAP=0.750037
[Epoch 104][Batch 99], Speed: 84.079515 samples/sec, CrossEntropy=1.697719, SmoothL1=0.725559, accuracy=0.855745
[Epoch 104][Batch 199], Speed: 91.412904 samples/sec, CrossEntropy=1.730735, SmoothL1=0.748301, accuracy=0.854047
[Epoch 104][Batch 299], Speed: 85.210355 samples/sec, CrossEntropy=1.744266, SmoothL1=0.760955, accuracy=0.852751
[Epoch 104][Batch 399], Speed: 93.478753 samples/sec, CrossEntropy=1.753063, SmoothL1=0.763559, accuracy=0.851768
[Epoch 104][Batch 499], Speed: 95.618057 samples/sec, CrossEntropy=1.754116, SmoothL1=0.766570, accuracy=0.851549
[Epoch 104] Training cost: 194.690142, CrossEntropy=1.754166, SmoothL1=0.767201, accuracy=0.851611
[Epoch 104] Validation:
aeroplane=0.810730
bicycle=0.815191
bird=0.736233
boat=0.708486
bottle=0.417798
bus=0.827217
car=0.845144
cat=0.858706
chair=0.561340
cow=0.842237
diningtable=0.756274
dog=0.833951
horse=0.847171
motorbike=0.815936
person=0.763528
pottedplant=0.482715
sheep=0.739216
sofa=0.759140
train=0.831848
tvmonitor=0.758618
mAP=0.750574
[Epoch 105][Batch 99], Speed: 92.512016 samples/sec, CrossEntropy=1.730794, SmoothL1=0.761572, accuracy=0.853311
[Epoch 105][Batch 199], Speed: 83.730342 samples/sec, CrossEntropy=1.743722, SmoothL1=0.776890, accuracy=0.852613
[Epoch 105][Batch 299], Speed: 95.984370 samples/sec, CrossEntropy=1.757504, SmoothL1=0.777753, accuracy=0.851823
[Epoch 105][Batch 399], Speed: 93.876276 samples/sec, CrossEntropy=1.762589, SmoothL1=0.778306, accuracy=0.851186
[Epoch 105][Batch 499], Speed: 85.420771 samples/sec, CrossEntropy=1.762348, SmoothL1=0.779134, accuracy=0.851068
[Epoch 105] Training cost: 194.631923, CrossEntropy=1.761976, SmoothL1=0.778468, accuracy=0.851088
[Epoch 105] Validation:
aeroplane=0.790288
bicycle=0.817871
bird=0.735781
boat=0.693595
bottle=0.419366
bus=0.838664
car=0.850653
cat=0.863204
chair=0.552776
cow=0.817635
diningtable=0.726604
dog=0.842248
horse=0.848697
motorbike=0.811736
person=0.767146
pottedplant=0.483332
sheep=0.742835
sofa=0.753019
train=0.850183
tvmonitor=0.755722
mAP=0.748068
[Epoch 106][Batch 99], Speed: 88.273145 samples/sec, CrossEntropy=1.720766, SmoothL1=0.747069, accuracy=0.853549
[Epoch 106][Batch 199], Speed: 92.053214 samples/sec, CrossEntropy=1.751150, SmoothL1=0.771771, accuracy=0.851543
[Epoch 106][Batch 299], Speed: 84.816196 samples/sec, CrossEntropy=1.747795, SmoothL1=0.769687, accuracy=0.851696
[Epoch 106][Batch 399], Speed: 90.032123 samples/sec, CrossEntropy=1.746217, SmoothL1=0.764722, accuracy=0.851803
[Epoch 106][Batch 499], Speed: 94.993625 samples/sec, CrossEntropy=1.751619, SmoothL1=0.769983, accuracy=0.851427
[Epoch 106] Training cost: 194.328139, CrossEntropy=1.751738, SmoothL1=0.769753, accuracy=0.851439
[Epoch 106] Validation:
aeroplane=0.787125
bicycle=0.821608
bird=0.740443
boat=0.689021
bottle=0.430460
bus=0.822646
car=0.846072
cat=0.857303
chair=0.580062
cow=0.813095
diningtable=0.760798
dog=0.829437
horse=0.847228
motorbike=0.832678
person=0.770079
pottedplant=0.477201
sheep=0.739646
sofa=0.772684
train=0.855003
tvmonitor=0.736667
mAP=0.750463
[Epoch 107][Batch 99], Speed: 94.747990 samples/sec, CrossEntropy=1.744282, SmoothL1=0.771747, accuracy=0.852439
[Epoch 107][Batch 199], Speed: 92.758295 samples/sec, CrossEntropy=1.741071, SmoothL1=0.771744, accuracy=0.852971
[Epoch 107][Batch 299], Speed: 94.796305 samples/sec, CrossEntropy=1.737376, SmoothL1=0.768738, accuracy=0.852904
[Epoch 107][Batch 399], Speed: 94.934296 samples/sec, CrossEntropy=1.740963, SmoothL1=0.768675, accuracy=0.852650
[Epoch 107][Batch 499], Speed: 92.796903 samples/sec, CrossEntropy=1.748266, SmoothL1=0.771351, accuracy=0.851968
[Epoch 107] Training cost: 194.267671, CrossEntropy=1.748882, SmoothL1=0.771439, accuracy=0.851917
[Epoch 107] Validation:
aeroplane=0.796615
bicycle=0.825024
bird=0.723878
boat=0.703959
bottle=0.440525
bus=0.837967
car=0.848680
cat=0.856148
chair=0.569101
cow=0.791264
diningtable=0.758816
dog=0.818103
horse=0.831959
motorbike=0.821686
person=0.768140
pottedplant=0.481197
sheep=0.744093
sofa=0.771124
train=0.833176
tvmonitor=0.742074
mAP=0.748176
[Epoch 108][Batch 99], Speed: 83.665934 samples/sec, CrossEntropy=1.708747, SmoothL1=0.750032, accuracy=0.854338
[Epoch 108][Batch 199], Speed: 84.169363 samples/sec, CrossEntropy=1.734467, SmoothL1=0.763169, accuracy=0.853028
[Epoch 108][Batch 299], Speed: 84.426356 samples/sec, CrossEntropy=1.736995, SmoothL1=0.762995, accuracy=0.853125
[Epoch 108][Batch 399], Speed: 91.076081 samples/sec, CrossEntropy=1.746561, SmoothL1=0.769119, accuracy=0.852241
[Epoch 108][Batch 499], Speed: 95.969134 samples/sec, CrossEntropy=1.744231, SmoothL1=0.768330, accuracy=0.852604
[Epoch 108] Training cost: 194.208527, CrossEntropy=1.743121, SmoothL1=0.766527, accuracy=0.852691
[Epoch 108] Validation:
aeroplane=0.788836
bicycle=0.824393
bird=0.736012
boat=0.695479
bottle=0.440201
bus=0.833803
car=0.851280
cat=0.840044
chair=0.567156
cow=0.793253
diningtable=0.730067
dog=0.815594
horse=0.841158
motorbike=0.812456
person=0.772294
pottedplant=0.464092
sheep=0.696906
sofa=0.790302
train=0.829251
tvmonitor=0.740968
mAP=0.743177
[Epoch 109][Batch 99], Speed: 90.635355 samples/sec, CrossEntropy=1.740396, SmoothL1=0.762639, accuracy=0.852489
[Epoch 109][Batch 199], Speed: 89.264014 samples/sec, CrossEntropy=1.755811, SmoothL1=0.776886, accuracy=0.851737
[Epoch 109][Batch 299], Speed: 94.537635 samples/sec, CrossEntropy=1.738807, SmoothL1=0.769017, accuracy=0.852643
[Epoch 109][Batch 399], Speed: 94.524519 samples/sec, CrossEntropy=1.742770, SmoothL1=0.768118, accuracy=0.852248
[Epoch 109][Batch 499], Speed: 89.624693 samples/sec, CrossEntropy=1.743575, SmoothL1=0.765412, accuracy=0.852254
[Epoch 109] Training cost: 195.179374, CrossEntropy=1.743964, SmoothL1=0.765969, accuracy=0.852216
[Epoch 109] Validation:
aeroplane=0.768280
bicycle=0.823141
bird=0.739110
boat=0.699756
bottle=0.421370
bus=0.833956
car=0.852454
cat=0.861782
chair=0.562062
cow=0.804504
diningtable=0.755040
dog=0.818073
horse=0.843472
motorbike=0.809515
person=0.757112
pottedplant=0.488945
sheep=0.752084
sofa=0.773596
train=0.835300
tvmonitor=0.756921
mAP=0.747824
[Epoch 110][Batch 99], Speed: 86.652684 samples/sec, CrossEntropy=1.669659, SmoothL1=0.741096, accuracy=0.857770
[Epoch 110][Batch 199], Speed: 87.750789 samples/sec, CrossEntropy=1.704843, SmoothL1=0.755393, accuracy=0.855389
[Epoch 110][Batch 299], Speed: 93.952109 samples/sec, CrossEntropy=1.700459, SmoothL1=0.748349, accuracy=0.855563
[Epoch 110][Batch 399], Speed: 87.110757 samples/sec, CrossEntropy=1.716782, SmoothL1=0.752002, accuracy=0.854447
[Epoch 110][Batch 499], Speed: 91.819453 samples/sec, CrossEntropy=1.721186, SmoothL1=0.758891, accuracy=0.854075
[Epoch 110] Training cost: 194.913737, CrossEntropy=1.722098, SmoothL1=0.758431, accuracy=0.853956
[Epoch 110] Validation:
aeroplane=0.782337
bicycle=0.820794
bird=0.749145
boat=0.675345
bottle=0.445843
bus=0.825345
car=0.850120
cat=0.850353
chair=0.550891
cow=0.805348
diningtable=0.731403
dog=0.810841
horse=0.841162
motorbike=0.813496
person=0.763057
pottedplant=0.501293
sheep=0.754201
sofa=0.777477
train=0.840333
tvmonitor=0.748714
mAP=0.746875
[Epoch 111][Batch 99], Speed: 85.170072 samples/sec, CrossEntropy=1.699245, SmoothL1=0.745730, accuracy=0.856552
[Epoch 111][Batch 199], Speed: 90.246119 samples/sec, CrossEntropy=1.696236, SmoothL1=0.737303, accuracy=0.855656
[Epoch 111][Batch 299], Speed: 94.377097 samples/sec, CrossEntropy=1.702343, SmoothL1=0.747882, accuracy=0.855268
[Epoch 111][Batch 399], Speed: 85.037757 samples/sec, CrossEntropy=1.713227, SmoothL1=0.749740, accuracy=0.854744
[Epoch 111][Batch 499], Speed: 96.720532 samples/sec, CrossEntropy=1.718486, SmoothL1=0.755298, accuracy=0.854341
[Epoch 111] Training cost: 194.048660, CrossEntropy=1.717151, SmoothL1=0.754006, accuracy=0.854486
[Epoch 111] Validation:
aeroplane=0.777911
bicycle=0.824541
bird=0.722603
boat=0.679098
bottle=0.453022
bus=0.818313
car=0.853970
cat=0.863179
chair=0.561155
cow=0.787714
diningtable=0.748413
dog=0.831193
horse=0.837302
motorbike=0.808419
person=0.767083
pottedplant=0.465244
sheep=0.760028
sofa=0.748096
train=0.835820
tvmonitor=0.749326
mAP=0.744622
[Epoch 112][Batch 99], Speed: 93.485394 samples/sec, CrossEntropy=1.684735, SmoothL1=0.728366, accuracy=0.855471
[Epoch 112][Batch 199], Speed: 89.727269 samples/sec, CrossEntropy=1.716335, SmoothL1=0.751074, accuracy=0.854133
[Epoch 112][Batch 299], Speed: 93.985662 samples/sec, CrossEntropy=1.725415, SmoothL1=0.758716, accuracy=0.853661
[Epoch 112][Batch 399], Speed: 86.134459 samples/sec, CrossEntropy=1.725225, SmoothL1=0.755628, accuracy=0.853675
[Epoch 112][Batch 499], Speed: 97.573934 samples/sec, CrossEntropy=1.720230, SmoothL1=0.750130, accuracy=0.853947
[Epoch 112] Training cost: 193.761179, CrossEntropy=1.721781, SmoothL1=0.748394, accuracy=0.853847
[Epoch 112] Validation:
aeroplane=0.779975
bicycle=0.827842
bird=0.699136
boat=0.651717
bottle=0.456832
bus=0.824611
car=0.849425
cat=0.839566
chair=0.552264
cow=0.799354
diningtable=0.748029
dog=0.801955
horse=0.852110
motorbike=0.822811
person=0.761955
pottedplant=0.427163
sheep=0.718484
sofa=0.742061
train=0.837606
tvmonitor=0.741790
mAP=0.736734
[Epoch 113][Batch 99], Speed: 84.266543 samples/sec, CrossEntropy=1.693267, SmoothL1=0.765859, accuracy=0.857507
[Epoch 113][Batch 199], Speed: 84.028351 samples/sec, CrossEntropy=1.700181, SmoothL1=0.755818, accuracy=0.855609
[Epoch 113][Batch 299], Speed: 90.922270 samples/sec, CrossEntropy=1.705016, SmoothL1=0.751061, accuracy=0.855214
[Epoch 113][Batch 399], Speed: 92.786125 samples/sec, CrossEntropy=1.718188, SmoothL1=0.751736, accuracy=0.854698
[Epoch 113][Batch 499], Speed: 88.714945 samples/sec, CrossEntropy=1.719956, SmoothL1=0.753607, accuracy=0.854453
[Epoch 113] Training cost: 194.327351, CrossEntropy=1.721704, SmoothL1=0.753718, accuracy=0.854288
[Epoch 113] Validation:
aeroplane=0.790967
bicycle=0.814765
bird=0.735296
boat=0.669276
bottle=0.455311
bus=0.809588
car=0.851142
cat=0.857664
chair=0.573550
cow=0.788689
diningtable=0.749496
dog=0.818143
horse=0.846733
motorbike=0.823460
person=0.764684
pottedplant=0.473954
sheep=0.754483
sofa=0.778296
train=0.865460
tvmonitor=0.750751
mAP=0.748585
[Epoch 114][Batch 99], Speed: 93.408492 samples/sec, CrossEntropy=1.715591, SmoothL1=0.736325, accuracy=0.855661
[Epoch 114][Batch 199], Speed: 84.783621 samples/sec, CrossEntropy=1.732412, SmoothL1=0.757432, accuracy=0.853239
[Epoch 114][Batch 299], Speed: 85.926457 samples/sec, CrossEntropy=1.721775, SmoothL1=0.752192, accuracy=0.853854
[Epoch 114][Batch 399], Speed: 88.875436 samples/sec, CrossEntropy=1.722324, SmoothL1=0.754664, accuracy=0.853990
[Epoch 114][Batch 499], Speed: 91.835222 samples/sec, CrossEntropy=1.720509, SmoothL1=0.754205, accuracy=0.853828
[Epoch 114] Training cost: 194.864551, CrossEntropy=1.722593, SmoothL1=0.755344, accuracy=0.853570
[Epoch 114] Validation:
aeroplane=0.782990
bicycle=0.830960
bird=0.743577
boat=0.695274
bottle=0.450039
bus=0.839124
car=0.856593
cat=0.852656
chair=0.566938
cow=0.773472
diningtable=0.744870
dog=0.822304
horse=0.861573
motorbike=0.831111
person=0.766910
pottedplant=0.471114
sheep=0.735921
sofa=0.784247
train=0.846511
tvmonitor=0.748670
mAP=0.750243
[Epoch 115][Batch 99], Speed: 92.096102 samples/sec, CrossEntropy=1.673599, SmoothL1=0.731360, accuracy=0.857853
[Epoch 115][Batch 199], Speed: 88.358279 samples/sec, CrossEntropy=1.702497, SmoothL1=0.748234, accuracy=0.855811
[Epoch 115][Batch 299], Speed: 90.526419 samples/sec, CrossEntropy=1.707191, SmoothL1=0.745829, accuracy=0.855412
[Epoch 115][Batch 399], Speed: 83.292465 samples/sec, CrossEntropy=1.722113, SmoothL1=0.754164, accuracy=0.854486
[Epoch 115][Batch 499], Speed: 92.575698 samples/sec, CrossEntropy=1.718598, SmoothL1=0.753272, accuracy=0.854396
[Epoch 115] Training cost: 194.023623, CrossEntropy=1.717458, SmoothL1=0.751488, accuracy=0.854427
[Epoch 115] Validation:
aeroplane=0.791960
bicycle=0.831543
bird=0.753104
boat=0.674346
bottle=0.421559
bus=0.811484
car=0.837177
cat=0.868732
chair=0.577504
cow=0.817163
diningtable=0.739203
dog=0.828656
horse=0.848910
motorbike=0.801401
person=0.768368
pottedplant=0.470202
sheep=0.763339
sofa=0.797186
train=0.854654
tvmonitor=0.742664
mAP=0.749958
[Epoch 116][Batch 99], Speed: 70.082353 samples/sec, CrossEntropy=1.684792, SmoothL1=0.738629, accuracy=0.856214
[Epoch 116][Batch 199], Speed: 91.767723 samples/sec, CrossEntropy=1.687902, SmoothL1=0.747164, accuracy=0.856059
[Epoch 116][Batch 299], Speed: 90.287279 samples/sec, CrossEntropy=1.702969, SmoothL1=0.750652, accuracy=0.855420
[Epoch 116][Batch 399], Speed: 88.326008 samples/sec, CrossEntropy=1.703066, SmoothL1=0.745350, accuracy=0.855360
[Epoch 116][Batch 499], Speed: 92.498818 samples/sec, CrossEntropy=1.701266, SmoothL1=0.745108, accuracy=0.855475
[Epoch 116] Training cost: 194.274832, CrossEntropy=1.700262, SmoothL1=0.746065, accuracy=0.855382
[Epoch 116] Validation:
aeroplane=0.776926
bicycle=0.828714
bird=0.725786
boat=0.676235
bottle=0.457621
bus=0.824436
car=0.849317
cat=0.852460
chair=0.572107
cow=0.800068
diningtable=0.732983
dog=0.828436
horse=0.851104
motorbike=0.829526
person=0.768989
pottedplant=0.466277
sheep=0.754697
sofa=0.792360
train=0.859091
tvmonitor=0.743231
mAP=0.749518
[Epoch 117][Batch 99], Speed: 95.215606 samples/sec, CrossEntropy=1.658948, SmoothL1=0.726625, accuracy=0.858830
[Epoch 117][Batch 199], Speed: 93.017555 samples/sec, CrossEntropy=1.697710, SmoothL1=0.745743, accuracy=0.855605
[Epoch 117][Batch 299], Speed: 92.199793 samples/sec, CrossEntropy=1.698860, SmoothL1=0.745365, accuracy=0.855414
[Epoch 117][Batch 399], Speed: 86.068508 samples/sec, CrossEntropy=1.705951, SmoothL1=0.747550, accuracy=0.854971
[Epoch 117][Batch 499], Speed: 84.733200 samples/sec, CrossEntropy=1.709006, SmoothL1=0.748504, accuracy=0.854557
[Epoch 117] Training cost: 194.022168, CrossEntropy=1.709228, SmoothL1=0.747516, accuracy=0.854490
[Epoch 117] Validation:
aeroplane=0.778610
bicycle=0.831586
bird=0.736475
boat=0.676281
bottle=0.446132
bus=0.827734
car=0.849140
cat=0.842568
chair=0.570321
cow=0.807457
diningtable=0.705875
dog=0.811318
horse=0.843137
motorbike=0.822470
person=0.767028
pottedplant=0.466851
sheep=0.732728
sofa=0.771855
train=0.837251
tvmonitor=0.762272
mAP=0.744355
[Epoch 118][Batch 99], Speed: 85.008242 samples/sec, CrossEntropy=1.671420, SmoothL1=0.725267, accuracy=0.857356
[Epoch 118][Batch 199], Speed: 88.593145 samples/sec, CrossEntropy=1.686278, SmoothL1=0.737268, accuracy=0.856683
[Epoch 118][Batch 299], Speed: 86.546911 samples/sec, CrossEntropy=1.689060, SmoothL1=0.735824, accuracy=0.856361
[Epoch 118][Batch 399], Speed: 90.012379 samples/sec, CrossEntropy=1.694048, SmoothL1=0.739199, accuracy=0.855775
[Epoch 118][Batch 499], Speed: 96.450368 samples/sec, CrossEntropy=1.697900, SmoothL1=0.741415, accuracy=0.855498
[Epoch 118] Training cost: 194.162104, CrossEntropy=1.698337, SmoothL1=0.741445, accuracy=0.855430
[Epoch 118] Validation:
aeroplane=0.794295
bicycle=0.825517
bird=0.741383
boat=0.667872
bottle=0.489197
bus=0.837508
car=0.845748
cat=0.863568
chair=0.574369
cow=0.807903
diningtable=0.736387
dog=0.829588
horse=0.857512
motorbike=0.838057
person=0.766654
pottedplant=0.478350
sheep=0.758791
sofa=0.760180
train=0.861685
tvmonitor=0.761402
mAP=0.754798
[Epoch 119][Batch 99], Speed: 89.991919 samples/sec, CrossEntropy=1.656107, SmoothL1=0.724040, accuracy=0.858802
[Epoch 119][Batch 199], Speed: 86.729002 samples/sec, CrossEntropy=1.683063, SmoothL1=0.741763, accuracy=0.856750
[Epoch 119][Batch 299], Speed: 86.676970 samples/sec, CrossEntropy=1.692989, SmoothL1=0.747365, accuracy=0.856345
[Epoch 119][Batch 399], Speed: 90.927075 samples/sec, CrossEntropy=1.705479, SmoothL1=0.748440, accuracy=0.855019
[Epoch 119][Batch 499], Speed: 93.662580 samples/sec, CrossEntropy=1.703277, SmoothL1=0.745374, accuracy=0.855503
[Epoch 119] Training cost: 194.176885, CrossEntropy=1.702566, SmoothL1=0.744755, accuracy=0.855550
[Epoch 119] Validation:
aeroplane=0.805450
bicycle=0.831943
bird=0.742983
boat=0.699942
bottle=0.461496
bus=0.825061
car=0.851721
cat=0.869284
chair=0.577461
cow=0.766279
diningtable=0.725456
dog=0.832728
horse=0.841971
motorbike=0.841102
person=0.769537
pottedplant=0.483898
sheep=0.734076
sofa=0.762895
train=0.845340
tvmonitor=0.748203
mAP=0.750841
[Epoch 120][Batch 99], Speed: 84.764880 samples/sec, CrossEntropy=1.657983, SmoothL1=0.736843, accuracy=0.859300
[Epoch 120][Batch 199], Speed: 86.054271 samples/sec, CrossEntropy=1.673467, SmoothL1=0.739176, accuracy=0.857639
[Epoch 120][Batch 299], Speed: 91.741817 samples/sec, CrossEntropy=1.685073, SmoothL1=0.747125, accuracy=0.856800
[Epoch 120][Batch 399], Speed: 94.776090 samples/sec, CrossEntropy=1.699373, SmoothL1=0.752986, accuracy=0.855428
[Epoch 120][Batch 499], Speed: 94.414341 samples/sec, CrossEntropy=1.695146, SmoothL1=0.748922, accuracy=0.856008
[Epoch 120] Training cost: 194.208110, CrossEntropy=1.693418, SmoothL1=0.747851, accuracy=0.856206
[Epoch 120] Validation:
aeroplane=0.781677
bicycle=0.835829
bird=0.717013
boat=0.681064
bottle=0.452946
bus=0.826166
car=0.844798
cat=0.868350
chair=0.553962
cow=0.809307
diningtable=0.752706
dog=0.816222
horse=0.845322
motorbike=0.839033
person=0.769325
pottedplant=0.496075
sheep=0.744156
sofa=0.750923
train=0.835652
tvmonitor=0.755807
mAP=0.748817
[Epoch 121][Batch 99], Speed: 95.933053 samples/sec, CrossEntropy=1.681821, SmoothL1=0.754173, accuracy=0.855728
[Epoch 121][Batch 199], Speed: 70.259401 samples/sec, CrossEntropy=1.676271, SmoothL1=0.740169, accuracy=0.856798
[Epoch 121][Batch 299], Speed: 87.673178 samples/sec, CrossEntropy=1.674626, SmoothL1=0.738436, accuracy=0.856877
[Epoch 121][Batch 399], Speed: 93.903533 samples/sec, CrossEntropy=1.683279, SmoothL1=0.738906, accuracy=0.855966
[Epoch 121][Batch 499], Speed: 90.055078 samples/sec, CrossEntropy=1.681872, SmoothL1=0.739737, accuracy=0.856331
[Epoch 121] Training cost: 194.324408, CrossEntropy=1.680210, SmoothL1=0.738264, accuracy=0.856472
[Epoch 121] Validation:
aeroplane=0.761923
bicycle=0.826335
bird=0.724309
boat=0.684464
bottle=0.444051
bus=0.828948
car=0.840061
cat=0.841869
chair=0.561987
cow=0.819252
diningtable=0.753236
dog=0.827681
horse=0.855840
motorbike=0.825518
person=0.775337
pottedplant=0.477658
sheep=0.763133
sofa=0.760709
train=0.856682
tvmonitor=0.760920
mAP=0.749496
[Epoch 122][Batch 99], Speed: 93.053411 samples/sec, CrossEntropy=1.665114, SmoothL1=0.724112, accuracy=0.858588
[Epoch 122][Batch 199], Speed: 80.297965 samples/sec, CrossEntropy=1.683441, SmoothL1=0.738881, accuracy=0.857875
[Epoch 122][Batch 299], Speed: 93.060186 samples/sec, CrossEntropy=1.694526, SmoothL1=0.741905, accuracy=0.856682
[Epoch 122][Batch 399], Speed: 85.816742 samples/sec, CrossEntropy=1.695867, SmoothL1=0.743671, accuracy=0.856592
[Epoch 122][Batch 499], Speed: 97.230265 samples/sec, CrossEntropy=1.694904, SmoothL1=0.740170, accuracy=0.856610
[Epoch 122] Training cost: 194.459175, CrossEntropy=1.697544, SmoothL1=0.741060, accuracy=0.856514
[Epoch 122] Validation:
aeroplane=0.788381
bicycle=0.812716
bird=0.733746
boat=0.701699
bottle=0.442103
bus=0.817914
car=0.852975
cat=0.856740
chair=0.556459
cow=0.790506
diningtable=0.743877
dog=0.835213
horse=0.855864
motorbike=0.814063
person=0.768641
pottedplant=0.459978
sheep=0.721939
sofa=0.744026
train=0.867452
tvmonitor=0.756986
mAP=0.746064
[Epoch 123][Batch 99], Speed: 84.241104 samples/sec, CrossEntropy=1.701299, SmoothL1=0.744299, accuracy=0.856666
[Epoch 123][Batch 199], Speed: 91.275580 samples/sec, CrossEntropy=1.691098, SmoothL1=0.737762, accuracy=0.856860
[Epoch 123][Batch 299], Speed: 87.282232 samples/sec, CrossEntropy=1.687761, SmoothL1=0.734828, accuracy=0.857124
[Epoch 123][Batch 399], Speed: 84.354352 samples/sec, CrossEntropy=1.690610, SmoothL1=0.737244, accuracy=0.856486
[Epoch 123][Batch 499], Speed: 84.439316 samples/sec, CrossEntropy=1.690432, SmoothL1=0.735649, accuracy=0.856506
[Epoch 123] Training cost: 194.554699, CrossEntropy=1.692393, SmoothL1=0.735112, accuracy=0.856384
[Epoch 123] Validation:
aeroplane=0.786163
bicycle=0.813735
bird=0.728920
boat=0.669999
bottle=0.453075
bus=0.810764
car=0.842127
cat=0.842333
chair=0.550674
cow=0.794379
diningtable=0.733228
dog=0.818755
horse=0.863502
motorbike=0.828099
person=0.759247
pottedplant=0.463627
sheep=0.743132
sofa=0.751961
train=0.857823
tvmonitor=0.748203
mAP=0.742987
[Epoch 124][Batch 99], Speed: 89.145852 samples/sec, CrossEntropy=1.654466, SmoothL1=0.722587, accuracy=0.858480
[Epoch 124][Batch 199], Speed: 87.528125 samples/sec, CrossEntropy=1.670129, SmoothL1=0.731296, accuracy=0.857435
[Epoch 124][Batch 299], Speed: 89.851308 samples/sec, CrossEntropy=1.666894, SmoothL1=0.730630, accuracy=0.857454
[Epoch 124][Batch 399], Speed: 96.816812 samples/sec, CrossEntropy=1.671945, SmoothL1=0.728876, accuracy=0.857092
[Epoch 124][Batch 499], Speed: 91.041794 samples/sec, CrossEntropy=1.681549, SmoothL1=0.730030, accuracy=0.856546
[Epoch 124] Training cost: 193.840915, CrossEntropy=1.679808, SmoothL1=0.729118, accuracy=0.856634
[Epoch 124] Validation:
aeroplane=0.786494
bicycle=0.826607
bird=0.718926
boat=0.697981
bottle=0.453927
bus=0.833252
car=0.837951
cat=0.869291
chair=0.550716
cow=0.796250
diningtable=0.749034
dog=0.825223
horse=0.857072
motorbike=0.820954
person=0.774475
pottedplant=0.478536
sheep=0.769460
sofa=0.774622
train=0.862714
tvmonitor=0.745603
mAP=0.751454
[Epoch 125][Batch 99], Speed: 87.098999 samples/sec, CrossEntropy=1.652242, SmoothL1=0.724557, accuracy=0.858790
[Epoch 125][Batch 199], Speed: 82.983017 samples/sec, CrossEntropy=1.684412, SmoothL1=0.735468, accuracy=0.856812
[Epoch 125][Batch 299], Speed: 93.752211 samples/sec, CrossEntropy=1.680646, SmoothL1=0.732962, accuracy=0.857045
[Epoch 125][Batch 399], Speed: 87.732148 samples/sec, CrossEntropy=1.679595, SmoothL1=0.729990, accuracy=0.856849
[Epoch 125][Batch 499], Speed: 93.371582 samples/sec, CrossEntropy=1.676433, SmoothL1=0.728065, accuracy=0.856798
[Epoch 125] Training cost: 194.572279, CrossEntropy=1.679147, SmoothL1=0.729868, accuracy=0.856699
[Epoch 125] Validation:
aeroplane=0.804294
bicycle=0.827525
bird=0.726154
boat=0.674259
bottle=0.481331
bus=0.828776
car=0.844872
cat=0.865412
chair=0.593059
cow=0.796443
diningtable=0.721679
dog=0.822684
horse=0.848996
motorbike=0.841939
person=0.775946
pottedplant=0.495096
sheep=0.755900
sofa=0.774358
train=0.859682
tvmonitor=0.751358
mAP=0.754488
[Epoch 126][Batch 99], Speed: 95.249324 samples/sec, CrossEntropy=1.658694, SmoothL1=0.711063, accuracy=0.858235
[Epoch 126][Batch 199], Speed: 80.051417 samples/sec, CrossEntropy=1.670871, SmoothL1=0.728452, accuracy=0.856710
[Epoch 126][Batch 299], Speed: 93.000798 samples/sec, CrossEntropy=1.666868, SmoothL1=0.724895, accuracy=0.857137
[Epoch 126][Batch 399], Speed: 93.183848 samples/sec, CrossEntropy=1.678582, SmoothL1=0.727788, accuracy=0.856795
[Epoch 126][Batch 499], Speed: 83.792390 samples/sec, CrossEntropy=1.679363, SmoothL1=0.727832, accuracy=0.856854
[Epoch 126] Training cost: 194.406830, CrossEntropy=1.682801, SmoothL1=0.730169, accuracy=0.856660
[Epoch 126] Validation:
aeroplane=0.783265
bicycle=0.810554
bird=0.720952
boat=0.662060
bottle=0.478646
bus=0.834258
car=0.842611
cat=0.836022
chair=0.567963
cow=0.786867
diningtable=0.727971
dog=0.798731
horse=0.848873
motorbike=0.818254
person=0.762837
pottedplant=0.475019
sheep=0.745226
sofa=0.777116
train=0.843635
tvmonitor=0.741763
mAP=0.743131
[Epoch 127][Batch 99], Speed: 84.590614 samples/sec, CrossEntropy=1.646355, SmoothL1=0.715085, accuracy=0.860367
[Epoch 127][Batch 199], Speed: 93.027484 samples/sec, CrossEntropy=1.660184, SmoothL1=0.721478, accuracy=0.858817
[Epoch 127][Batch 299], Speed: 88.944993 samples/sec, CrossEntropy=1.670121, SmoothL1=0.725697, accuracy=0.858269
[Epoch 127][Batch 399], Speed: 92.785997 samples/sec, CrossEntropy=1.672428, SmoothL1=0.729170, accuracy=0.857991
[Epoch 127][Batch 499], Speed: 99.009321 samples/sec, CrossEntropy=1.668107, SmoothL1=0.724845, accuracy=0.858100
[Epoch 127] Training cost: 194.810000, CrossEntropy=1.667642, SmoothL1=0.725073, accuracy=0.858045
[Epoch 127] Validation:
aeroplane=0.784948
bicycle=0.820275
bird=0.742084
boat=0.686380
bottle=0.488530
bus=0.821169
car=0.846919
cat=0.855180
chair=0.576001
cow=0.800593
diningtable=0.751804
dog=0.827545
horse=0.853393
motorbike=0.843606
person=0.760542
pottedplant=0.460780
sheep=0.769461
sofa=0.775762
train=0.859234
tvmonitor=0.759201
mAP=0.754170
[Epoch 128][Batch 99], Speed: 84.948521 samples/sec, CrossEntropy=1.675877, SmoothL1=0.739522, accuracy=0.857509
[Epoch 128][Batch 199], Speed: 91.778202 samples/sec, CrossEntropy=1.676068, SmoothL1=0.734828, accuracy=0.857311
[Epoch 128][Batch 299], Speed: 83.298668 samples/sec, CrossEntropy=1.672458, SmoothL1=0.732659, accuracy=0.857849
[Epoch 128][Batch 399], Speed: 87.494347 samples/sec, CrossEntropy=1.680797, SmoothL1=0.734491, accuracy=0.857232
[Epoch 128][Batch 499], Speed: 85.805056 samples/sec, CrossEntropy=1.675607, SmoothL1=0.733935, accuracy=0.857486
[Epoch 128] Training cost: 194.390980, CrossEntropy=1.673014, SmoothL1=0.732424, accuracy=0.857557
[Epoch 128] Validation:
aeroplane=0.786692
bicycle=0.811927
bird=0.723934
boat=0.686074
bottle=0.472782
bus=0.825343
car=0.848954
cat=0.850592
chair=0.567920
cow=0.805135
diningtable=0.770208
dog=0.817005
horse=0.859286
motorbike=0.839085
person=0.765154
pottedplant=0.471531
sheep=0.760524
sofa=0.764981
train=0.858647
tvmonitor=0.752606
mAP=0.751919
[Epoch 129][Batch 99], Speed: 87.229704 samples/sec, CrossEntropy=1.642471, SmoothL1=0.711114, accuracy=0.859835
[Epoch 129][Batch 199], Speed: 89.670020 samples/sec, CrossEntropy=1.647109, SmoothL1=0.718584, accuracy=0.859822
[Epoch 129][Batch 299], Speed: 82.628373 samples/sec, CrossEntropy=1.652075, SmoothL1=0.723615, accuracy=0.859448
[Epoch 129][Batch 399], Speed: 88.827439 samples/sec, CrossEntropy=1.655373, SmoothL1=0.720649, accuracy=0.859327
[Epoch 129][Batch 499], Speed: 92.250426 samples/sec, CrossEntropy=1.656197, SmoothL1=0.720308, accuracy=0.859205
[Epoch 129] Training cost: 193.889088, CrossEntropy=1.656105, SmoothL1=0.720133, accuracy=0.859295
[Epoch 129] Validation:
aeroplane=0.775984
bicycle=0.832859
bird=0.737461
boat=0.670416
bottle=0.435427
bus=0.823254
car=0.839101
cat=0.856631
chair=0.558293
cow=0.809294
diningtable=0.743292
dog=0.821461
horse=0.855486
motorbike=0.823390
person=0.776672
pottedplant=0.457597
sheep=0.752399
sofa=0.762621
train=0.846859
tvmonitor=0.754114
mAP=0.746631
[Epoch 130][Batch 99], Speed: 83.600428 samples/sec, CrossEntropy=1.623105, SmoothL1=0.696921, accuracy=0.861974
[Epoch 130][Batch 199], Speed: 89.777504 samples/sec, CrossEntropy=1.655183, SmoothL1=0.720571, accuracy=0.859179
[Epoch 130][Batch 299], Speed: 86.860622 samples/sec, CrossEntropy=1.650939, SmoothL1=0.717539, accuracy=0.859614
[Epoch 130][Batch 399], Speed: 89.839160 samples/sec, CrossEntropy=1.654547, SmoothL1=0.716361, accuracy=0.859234
[Epoch 130][Batch 499], Speed: 97.002027 samples/sec, CrossEntropy=1.653883, SmoothL1=0.716023, accuracy=0.859274
[Epoch 130] Training cost: 194.529555, CrossEntropy=1.656396, SmoothL1=0.718516, accuracy=0.859045
[Epoch 130] Validation:
aeroplane=0.785253
bicycle=0.838533
bird=0.716747
boat=0.682644
bottle=0.450825
bus=0.812300
car=0.852835
cat=0.860787
chair=0.555852
cow=0.807561
diningtable=0.732248
dog=0.829597
horse=0.848201
motorbike=0.816695
person=0.775790
pottedplant=0.468284
sheep=0.763147
sofa=0.758344
train=0.843819
tvmonitor=0.754372
mAP=0.747692
[Epoch 131][Batch 99], Speed: 88.716998 samples/sec, CrossEntropy=1.639158, SmoothL1=0.713623, accuracy=0.860379
[Epoch 131][Batch 199], Speed: 93.783983 samples/sec, CrossEntropy=1.667116, SmoothL1=0.724832, accuracy=0.859135
[Epoch 131][Batch 299], Speed: 83.685027 samples/sec, CrossEntropy=1.658635, SmoothL1=0.723982, accuracy=0.859663
[Epoch 131][Batch 399], Speed: 82.403588 samples/sec, CrossEntropy=1.662578, SmoothL1=0.726382, accuracy=0.859095
[Epoch 131][Batch 499], Speed: 97.404907 samples/sec, CrossEntropy=1.668060, SmoothL1=0.728049, accuracy=0.858548
[Epoch 131] Training cost: 194.722465, CrossEntropy=1.667182, SmoothL1=0.727088, accuracy=0.858596
[Epoch 131] Validation:
aeroplane=0.774951
bicycle=0.822556
bird=0.726589
boat=0.669529
bottle=0.451168
bus=0.834142
car=0.852534
cat=0.844998
chair=0.582443
cow=0.771169
diningtable=0.743262
dog=0.816483
horse=0.856600
motorbike=0.830419
person=0.759611
pottedplant=0.443658
sheep=0.709682
sofa=0.767492
train=0.841393
tvmonitor=0.753938
mAP=0.742631
[Epoch 132][Batch 99], Speed: 85.984533 samples/sec, CrossEntropy=1.629647, SmoothL1=0.707607, accuracy=0.861239
[Epoch 132][Batch 199], Speed: 91.652107 samples/sec, CrossEntropy=1.656442, SmoothL1=0.722888, accuracy=0.859041
[Epoch 132][Batch 299], Speed: 92.924497 samples/sec, CrossEntropy=1.660773, SmoothL1=0.726784, accuracy=0.858911
[Epoch 132][Batch 399], Speed: 93.541426 samples/sec, CrossEntropy=1.658732, SmoothL1=0.724253, accuracy=0.858931
[Epoch 132][Batch 499], Speed: 92.059275 samples/sec, CrossEntropy=1.664196, SmoothL1=0.728529, accuracy=0.858529
[Epoch 132] Training cost: 194.842152, CrossEntropy=1.668404, SmoothL1=0.729727, accuracy=0.858233
[Epoch 132] Validation:
aeroplane=0.774017
bicycle=0.828138
bird=0.720736
boat=0.665733
bottle=0.468839
bus=0.829139
car=0.844019
cat=0.870020
chair=0.561827
cow=0.821019
diningtable=0.744078
dog=0.818493
horse=0.846863
motorbike=0.828252
person=0.774084
pottedplant=0.474867
sheep=0.753773
sofa=0.766709
train=0.854443
tvmonitor=0.749502
mAP=0.749728
[Epoch 133][Batch 99], Speed: 90.197964 samples/sec, CrossEntropy=1.673767, SmoothL1=0.734369, accuracy=0.857978
[Epoch 133][Batch 199], Speed: 88.444044 samples/sec, CrossEntropy=1.679028, SmoothL1=0.741730, accuracy=0.857684
[Epoch 133][Batch 299], Speed: 92.906165 samples/sec, CrossEntropy=1.675420, SmoothL1=0.734693, accuracy=0.857922
[Epoch 133][Batch 399], Speed: 91.294640 samples/sec, CrossEntropy=1.678893, SmoothL1=0.731422, accuracy=0.857838
[Epoch 133][Batch 499], Speed: 90.231983 samples/sec, CrossEntropy=1.677714, SmoothL1=0.730667, accuracy=0.857804
[Epoch 133] Training cost: 194.598096, CrossEntropy=1.677104, SmoothL1=0.730005, accuracy=0.857851
[Epoch 133] Validation:
aeroplane=0.799588
bicycle=0.824681
bird=0.737748
boat=0.701416
bottle=0.447556
bus=0.818715
car=0.846107
cat=0.869809
chair=0.591505
cow=0.823873
diningtable=0.748817
dog=0.828251
horse=0.864486
motorbike=0.834756
person=0.773107
pottedplant=0.487640
sheep=0.759222
sofa=0.764654
train=0.867668
tvmonitor=0.737697
mAP=0.756365
[Epoch 134][Batch 99], Speed: 93.797878 samples/sec, CrossEntropy=1.611324, SmoothL1=0.688410, accuracy=0.862434
[Epoch 134][Batch 199], Speed: 93.665064 samples/sec, CrossEntropy=1.627584, SmoothL1=0.707710, accuracy=0.861379
[Epoch 134][Batch 299], Speed: 86.517733 samples/sec, CrossEntropy=1.646849, SmoothL1=0.720889, accuracy=0.859727
[Epoch 134][Batch 399], Speed: 88.125524 samples/sec, CrossEntropy=1.649917, SmoothL1=0.718261, accuracy=0.859754
[Epoch 134][Batch 499], Speed: 96.123297 samples/sec, CrossEntropy=1.651086, SmoothL1=0.719385, accuracy=0.859394
[Epoch 134] Training cost: 194.257668, CrossEntropy=1.654358, SmoothL1=0.721449, accuracy=0.859242
[Epoch 134] Validation:
aeroplane=0.802494
bicycle=0.813565
bird=0.723960
boat=0.674947
bottle=0.434722
bus=0.823479
car=0.849319
cat=0.867937
chair=0.556412
cow=0.792341
diningtable=0.730345
dog=0.823042
horse=0.853427
motorbike=0.826963
person=0.770158
pottedplant=0.462278
sheep=0.739915
sofa=0.780569
train=0.854326
tvmonitor=0.754820
mAP=0.746751
[Epoch 135][Batch 99], Speed: 87.963750 samples/sec, CrossEntropy=1.604035, SmoothL1=0.705886, accuracy=0.862383
[Epoch 135][Batch 199], Speed: 88.662788 samples/sec, CrossEntropy=1.641563, SmoothL1=0.728244, accuracy=0.859143
[Epoch 135][Batch 299], Speed: 83.068684 samples/sec, CrossEntropy=1.643467, SmoothL1=0.722260, accuracy=0.859233
[Epoch 135][Batch 399], Speed: 87.917020 samples/sec, CrossEntropy=1.647121, SmoothL1=0.720151, accuracy=0.859148
[Epoch 135][Batch 499], Speed: 91.687544 samples/sec, CrossEntropy=1.652137, SmoothL1=0.724070, accuracy=0.858958
[Epoch 135] Training cost: 194.178321, CrossEntropy=1.649836, SmoothL1=0.723015, accuracy=0.859204
[Epoch 135] Validation:
aeroplane=0.784056
bicycle=0.800738
bird=0.729293
boat=0.666479
bottle=0.451113
bus=0.784980
car=0.841270
cat=0.845947
chair=0.557307
cow=0.788822
diningtable=0.729651
dog=0.792790
horse=0.860157
motorbike=0.821878
person=0.764064
pottedplant=0.467131
sheep=0.722267
sofa=0.751376
train=0.842569
tvmonitor=0.763986
mAP=0.738294
[Epoch 136][Batch 99], Speed: 90.222217 samples/sec, CrossEntropy=1.618695, SmoothL1=0.693695, accuracy=0.860321
[Epoch 136][Batch 199], Speed: 91.989744 samples/sec, CrossEntropy=1.637113, SmoothL1=0.718289, accuracy=0.859802
[Epoch 136][Batch 299], Speed: 87.050248 samples/sec, CrossEntropy=1.641386, SmoothL1=0.722914, accuracy=0.859562
[Epoch 136][Batch 399], Speed: 80.268384 samples/sec, CrossEntropy=1.648187, SmoothL1=0.719595, accuracy=0.859464
[Epoch 136][Batch 499], Speed: 94.318469 samples/sec, CrossEntropy=1.650039, SmoothL1=0.716698, accuracy=0.859373
[Epoch 136] Training cost: 193.848688, CrossEntropy=1.652656, SmoothL1=0.718467, accuracy=0.859190
[Epoch 136] Validation:
aeroplane=0.803750
bicycle=0.836145
bird=0.734489
boat=0.693232
bottle=0.434766
bus=0.819812
car=0.848878
cat=0.870516
chair=0.567172
cow=0.804852
diningtable=0.736315
dog=0.828113
horse=0.853571
motorbike=0.833171
person=0.771835
pottedplant=0.482199
sheep=0.759519
sofa=0.763820
train=0.851412
tvmonitor=0.748089
mAP=0.752083
[Epoch 137][Batch 99], Speed: 87.438031 samples/sec, CrossEntropy=1.613328, SmoothL1=0.721238, accuracy=0.862321
[Epoch 137][Batch 199], Speed: 94.616542 samples/sec, CrossEntropy=1.638990, SmoothL1=0.724161, accuracy=0.859885
[Epoch 137][Batch 299], Speed: 83.620949 samples/sec, CrossEntropy=1.636877, SmoothL1=0.719356, accuracy=0.859996
[Epoch 137][Batch 399], Speed: 96.586408 samples/sec, CrossEntropy=1.639137, SmoothL1=0.718589, accuracy=0.859778
[Epoch 137][Batch 499], Speed: 97.361523 samples/sec, CrossEntropy=1.643734, SmoothL1=0.720608, accuracy=0.859431
[Epoch 137] Training cost: 194.764252, CrossEntropy=1.644791, SmoothL1=0.720277, accuracy=0.859441
[Epoch 137] Validation:
aeroplane=0.787343
bicycle=0.802151
bird=0.751222
boat=0.685761
bottle=0.463759
bus=0.829622
car=0.843101
cat=0.849362
chair=0.551544
cow=0.798768
diningtable=0.745707
dog=0.811000
horse=0.850285
motorbike=0.818272
person=0.773489
pottedplant=0.484558
sheep=0.741575
sofa=0.780948
train=0.858613
tvmonitor=0.744961
mAP=0.748602
[Epoch 138][Batch 99], Speed: 89.651393 samples/sec, CrossEntropy=1.650182, SmoothL1=0.721827, accuracy=0.859831
[Epoch 138][Batch 199], Speed: 82.221002 samples/sec, CrossEntropy=1.644175, SmoothL1=0.711146, accuracy=0.860207
[Epoch 138][Batch 299], Speed: 90.687715 samples/sec, CrossEntropy=1.650538, SmoothL1=0.716097, accuracy=0.859915
[Epoch 138][Batch 399], Speed: 88.784898 samples/sec, CrossEntropy=1.646080, SmoothL1=0.712558, accuracy=0.859919
[Epoch 138][Batch 499], Speed: 91.271049 samples/sec, CrossEntropy=1.641904, SmoothL1=0.711170, accuracy=0.860377
[Epoch 138] Training cost: 194.212942, CrossEntropy=1.642896, SmoothL1=0.711626, accuracy=0.860351
[Epoch 138] Validation:
aeroplane=0.784653
bicycle=0.813580
bird=0.731711
boat=0.637027
bottle=0.469653
bus=0.830202
car=0.848569
cat=0.862044
chair=0.559256
cow=0.806796
diningtable=0.757866
dog=0.834883
horse=0.857174
motorbike=0.826063
person=0.776009
pottedplant=0.468864
sheep=0.738734
sofa=0.780229
train=0.866916
tvmonitor=0.758469
mAP=0.750435
[Epoch 139][Batch 99], Speed: 91.936563 samples/sec, CrossEntropy=1.590407, SmoothL1=0.686381, accuracy=0.863302
[Epoch 139][Batch 199], Speed: 92.040967 samples/sec, CrossEntropy=1.620700, SmoothL1=0.706982, accuracy=0.861508
[Epoch 139][Batch 299], Speed: 91.874071 samples/sec, CrossEntropy=1.621589, SmoothL1=0.710436, accuracy=0.861659
[Epoch 139][Batch 399], Speed: 87.934934 samples/sec, CrossEntropy=1.631274, SmoothL1=0.711959, accuracy=0.861021
[Epoch 139][Batch 499], Speed: 91.965288 samples/sec, CrossEntropy=1.636202, SmoothL1=0.709705, accuracy=0.860720
[Epoch 139] Training cost: 194.315763, CrossEntropy=1.636579, SmoothL1=0.709909, accuracy=0.860744
[Epoch 139] Validation:
aeroplane=0.808181
bicycle=0.827717
bird=0.752961
boat=0.699789
bottle=0.452736
bus=0.825908
car=0.847027
cat=0.882783
chair=0.560207
cow=0.808521
diningtable=0.743375
dog=0.824291
horse=0.849889
motorbike=0.833735
person=0.771872
pottedplant=0.481325
sheep=0.742504
sofa=0.782162
train=0.863861
tvmonitor=0.748125
mAP=0.755348
[Epoch 140][Batch 99], Speed: 74.311425 samples/sec, CrossEntropy=1.610720, SmoothL1=0.704278, accuracy=0.861902
[Epoch 140][Batch 199], Speed: 90.025359 samples/sec, CrossEntropy=1.633729, SmoothL1=0.717510, accuracy=0.860712
[Epoch 140][Batch 299], Speed: 90.464915 samples/sec, CrossEntropy=1.626523, SmoothL1=0.709202, accuracy=0.861522
[Epoch 140][Batch 399], Speed: 90.127766 samples/sec, CrossEntropy=1.628090, SmoothL1=0.708772, accuracy=0.860896
[Epoch 140][Batch 499], Speed: 92.406477 samples/sec, CrossEntropy=1.635792, SmoothL1=0.711789, accuracy=0.860671
[Epoch 140] Training cost: 193.980676, CrossEntropy=1.633577, SmoothL1=0.708964, accuracy=0.860764
[Epoch 140] Validation:
aeroplane=0.778891
bicycle=0.827007
bird=0.732385
boat=0.664428
bottle=0.449893
bus=0.829732
car=0.839812
cat=0.866144
chair=0.559484
cow=0.804291
diningtable=0.733613
dog=0.831750
horse=0.845046
motorbike=0.826831
person=0.769020
pottedplant=0.466038
sheep=0.765332
sofa=0.757923
train=0.841822
tvmonitor=0.742236
mAP=0.746584
[Epoch 141][Batch 99], Speed: 89.597351 samples/sec, CrossEntropy=1.626825, SmoothL1=0.700599, accuracy=0.861888
[Epoch 141][Batch 199], Speed: 89.989144 samples/sec, CrossEntropy=1.629125, SmoothL1=0.710108, accuracy=0.860968
[Epoch 141][Batch 299], Speed: 89.572656 samples/sec, CrossEntropy=1.625736, SmoothL1=0.707937, accuracy=0.861237
[Epoch 141][Batch 399], Speed: 83.670054 samples/sec, CrossEntropy=1.631538, SmoothL1=0.706206, accuracy=0.860975
[Epoch 141][Batch 499], Speed: 94.340877 samples/sec, CrossEntropy=1.628574, SmoothL1=0.704822, accuracy=0.861080
[Epoch 141] Training cost: 195.449259, CrossEntropy=1.626288, SmoothL1=0.702621, accuracy=0.861223
[Epoch 141] Validation:
aeroplane=0.792775
bicycle=0.826876
bird=0.757881
boat=0.677848
bottle=0.469588
bus=0.828554
car=0.849228
cat=0.869285
chair=0.550567
cow=0.819143
diningtable=0.705663
dog=0.843358
horse=0.851427
motorbike=0.831894
person=0.774729
pottedplant=0.489654
sheep=0.774117
sofa=0.772951
train=0.856297
tvmonitor=0.756830
mAP=0.754933
[Epoch 142][Batch 99], Speed: 92.203910 samples/sec, CrossEntropy=1.594840, SmoothL1=0.662107, accuracy=0.864034
[Epoch 142][Batch 199], Speed: 83.767078 samples/sec, CrossEntropy=1.610077, SmoothL1=0.692810, accuracy=0.862413
[Epoch 142][Batch 299], Speed: 82.376176 samples/sec, CrossEntropy=1.621120, SmoothL1=0.698687, accuracy=0.861527
[Epoch 142][Batch 399], Speed: 90.777634 samples/sec, CrossEntropy=1.623909, SmoothL1=0.703046, accuracy=0.861300
[Epoch 142][Batch 499], Speed: 94.875175 samples/sec, CrossEntropy=1.622963, SmoothL1=0.702624, accuracy=0.861540
[Epoch 142] Training cost: 194.543175, CrossEntropy=1.623753, SmoothL1=0.702120, accuracy=0.861463
[Epoch 142] Validation:
aeroplane=0.777269
bicycle=0.838455
bird=0.720179
boat=0.686595
bottle=0.447694
bus=0.841655
car=0.853636
cat=0.847879
chair=0.556361
cow=0.816644
diningtable=0.736922
dog=0.813671
horse=0.861006
motorbike=0.825693
person=0.767019
pottedplant=0.468948
sheep=0.729527
sofa=0.773076
train=0.864340
tvmonitor=0.734659
mAP=0.748061
[Epoch 143][Batch 99], Speed: 88.828145 samples/sec, CrossEntropy=1.584129, SmoothL1=0.701395, accuracy=0.865485
[Epoch 143][Batch 199], Speed: 87.507068 samples/sec, CrossEntropy=1.597058, SmoothL1=0.704375, accuracy=0.864199
[Epoch 143][Batch 299], Speed: 88.208634 samples/sec, CrossEntropy=1.602265, SmoothL1=0.704507, accuracy=0.863764
[Epoch 143][Batch 399], Speed: 87.792633 samples/sec, CrossEntropy=1.606222, SmoothL1=0.699431, accuracy=0.862954
[Epoch 143][Batch 499], Speed: 94.310185 samples/sec, CrossEntropy=1.608409, SmoothL1=0.701853, accuracy=0.862635
[Epoch 143] Training cost: 194.463616, CrossEntropy=1.611343, SmoothL1=0.701617, accuracy=0.862376
[Epoch 143] Validation:
aeroplane=0.803158
bicycle=0.824478
bird=0.724911
boat=0.688087
bottle=0.438839
bus=0.839833
car=0.850054
cat=0.849717
chair=0.577253
cow=0.822003
diningtable=0.734933
dog=0.825555
horse=0.866623
motorbike=0.836502
person=0.772433
pottedplant=0.475245
sheep=0.738594
sofa=0.782488
train=0.861820
tvmonitor=0.759109
mAP=0.753582
[Epoch 144][Batch 99], Speed: 84.037400 samples/sec, CrossEntropy=1.598549, SmoothL1=0.699194, accuracy=0.862809
[Epoch 144][Batch 199], Speed: 90.684039 samples/sec, CrossEntropy=1.607701, SmoothL1=0.699007, accuracy=0.862445
[Epoch 144][Batch 299], Speed: 87.388616 samples/sec, CrossEntropy=1.609423, SmoothL1=0.705029, accuracy=0.862604
[Epoch 144][Batch 399], Speed: 87.691966 samples/sec, CrossEntropy=1.613778, SmoothL1=0.704849, accuracy=0.862205
[Epoch 144][Batch 499], Speed: 92.849543 samples/sec, CrossEntropy=1.617300, SmoothL1=0.702661, accuracy=0.862110
[Epoch 144] Training cost: 193.755169, CrossEntropy=1.618243, SmoothL1=0.704154, accuracy=0.862033
[Epoch 144] Validation:
aeroplane=0.770679
bicycle=0.818743
bird=0.715121
boat=0.657313
bottle=0.461793
bus=0.802870
car=0.843301
cat=0.862047
chair=0.578072
cow=0.804873
diningtable=0.756589
dog=0.831183
horse=0.852018
motorbike=0.840775
person=0.767554
pottedplant=0.454829
sheep=0.752983
sofa=0.761053
train=0.827323
tvmonitor=0.747416
mAP=0.745327
[Epoch 145][Batch 99], Speed: 86.361581 samples/sec, CrossEntropy=1.577291, SmoothL1=0.686576, accuracy=0.864468
[Epoch 145][Batch 199], Speed: 95.506880 samples/sec, CrossEntropy=1.602094, SmoothL1=0.698770, accuracy=0.863423
[Epoch 145][Batch 299], Speed: 84.139972 samples/sec, CrossEntropy=1.616256, SmoothL1=0.704067, accuracy=0.862575
[Epoch 145][Batch 399], Speed: 88.724504 samples/sec, CrossEntropy=1.617681, SmoothL1=0.703535, accuracy=0.862346
[Epoch 145][Batch 499], Speed: 89.592746 samples/sec, CrossEntropy=1.619462, SmoothL1=0.705767, accuracy=0.861979
[Epoch 145] Training cost: 194.244878, CrossEntropy=1.617043, SmoothL1=0.704896, accuracy=0.862101
[Epoch 145] Validation:
aeroplane=0.790063
bicycle=0.832975
bird=0.741140
boat=0.697851
bottle=0.462630
bus=0.844620
car=0.848980
cat=0.856607
chair=0.557539
cow=0.814369
diningtable=0.724671
dog=0.819643
horse=0.858547
motorbike=0.834745
person=0.780675
pottedplant=0.488555
sheep=0.750104
sofa=0.719342
train=0.860930
tvmonitor=0.754811
mAP=0.751940
[Epoch 146][Batch 99], Speed: 84.486196 samples/sec, CrossEntropy=1.594609, SmoothL1=0.696344, accuracy=0.863515
[Epoch 146][Batch 199], Speed: 88.183192 samples/sec, CrossEntropy=1.603405, SmoothL1=0.691901, accuracy=0.863504
[Epoch 146][Batch 299], Speed: 94.951892 samples/sec, CrossEntropy=1.605118, SmoothL1=0.688564, accuracy=0.863179
[Epoch 146][Batch 399], Speed: 93.614433 samples/sec, CrossEntropy=1.609326, SmoothL1=0.689071, accuracy=0.862968
[Epoch 146][Batch 499], Speed: 83.332802 samples/sec, CrossEntropy=1.606997, SmoothL1=0.688961, accuracy=0.863037
[Epoch 146] Training cost: 194.321113, CrossEntropy=1.608018, SmoothL1=0.689949, accuracy=0.862844
[Epoch 146] Validation:
aeroplane=0.807806
bicycle=0.815292
bird=0.712187
boat=0.680454
bottle=0.472001
bus=0.839159
car=0.848838
cat=0.862405
chair=0.564680
cow=0.771238
diningtable=0.740589
dog=0.834121
horse=0.844536
motorbike=0.825478
person=0.773666
pottedplant=0.477701
sheep=0.733006
sofa=0.773070
train=0.859615
tvmonitor=0.760231
mAP=0.749804
[Epoch 147][Batch 99], Speed: 93.891183 samples/sec, CrossEntropy=1.605455, SmoothL1=0.715102, accuracy=0.863841
[Epoch 147][Batch 199], Speed: 96.670583 samples/sec, CrossEntropy=1.615332, SmoothL1=0.708767, accuracy=0.862807
[Epoch 147][Batch 299], Speed: 94.568742 samples/sec, CrossEntropy=1.612862, SmoothL1=0.706303, accuracy=0.862831
[Epoch 147][Batch 399], Speed: 86.293840 samples/sec, CrossEntropy=1.613113, SmoothL1=0.704166, accuracy=0.862663
[Epoch 147][Batch 499], Speed: 90.054957 samples/sec, CrossEntropy=1.611695, SmoothL1=0.702957, accuracy=0.862921
[Epoch 147] Training cost: 194.093409, CrossEntropy=1.610106, SmoothL1=0.701487, accuracy=0.863018
[Epoch 147] Validation:
aeroplane=0.793082
bicycle=0.822178
bird=0.741303
boat=0.683442
bottle=0.473325
bus=0.845998
car=0.861653
cat=0.850360
chair=0.575528
cow=0.822962
diningtable=0.767638
dog=0.824073
horse=0.874323
motorbike=0.837775
person=0.774379
pottedplant=0.456451
sheep=0.723377
sofa=0.776583
train=0.859792
tvmonitor=0.757262
mAP=0.756074
[Epoch 148][Batch 99], Speed: 88.463805 samples/sec, CrossEntropy=1.568640, SmoothL1=0.681571, accuracy=0.865349
[Epoch 148][Batch 199], Speed: 87.831700 samples/sec, CrossEntropy=1.605222, SmoothL1=0.696028, accuracy=0.862995
[Epoch 148][Batch 299], Speed: 86.610187 samples/sec, CrossEntropy=1.611719, SmoothL1=0.701017, accuracy=0.862140
[Epoch 148][Batch 399], Speed: 88.120432 samples/sec, CrossEntropy=1.609723, SmoothL1=0.697172, accuracy=0.862554
[Epoch 148][Batch 499], Speed: 86.674003 samples/sec, CrossEntropy=1.612015, SmoothL1=0.696185, accuracy=0.862667
[Epoch 148] Training cost: 194.427418, CrossEntropy=1.611105, SmoothL1=0.695690, accuracy=0.862714
[Epoch 148] Validation:
aeroplane=0.790061
bicycle=0.828264
bird=0.738980
boat=0.699778
bottle=0.464616
bus=0.830018
car=0.849430
cat=0.866833
chair=0.567841
cow=0.813052
diningtable=0.728105
dog=0.820688
horse=0.852170
motorbike=0.839035
person=0.779980
pottedplant=0.474026
sheep=0.756099
sofa=0.774007
train=0.873460
tvmonitor=0.755489
mAP=0.755097
[Epoch 149][Batch 99], Speed: 95.379894 samples/sec, CrossEntropy=1.561607, SmoothL1=0.672887, accuracy=0.866199
[Epoch 149][Batch 199], Speed: 89.470135 samples/sec, CrossEntropy=1.586269, SmoothL1=0.688050, accuracy=0.864965
[Epoch 149][Batch 299], Speed: 88.557838 samples/sec, CrossEntropy=1.594330, SmoothL1=0.689462, accuracy=0.864941
[Epoch 149][Batch 399], Speed: 92.508382 samples/sec, CrossEntropy=1.600606, SmoothL1=0.687858, accuracy=0.863986
[Epoch 149][Batch 499], Speed: 89.815774 samples/sec, CrossEntropy=1.603892, SmoothL1=0.690185, accuracy=0.863280
[Epoch 149] Training cost: 194.519696, CrossEntropy=1.601947, SmoothL1=0.689269, accuracy=0.863386
[Epoch 149] Validation:
aeroplane=0.782074
bicycle=0.841558
bird=0.736262
boat=0.696233
bottle=0.469552
bus=0.836771
car=0.855410
cat=0.862777
chair=0.571827
cow=0.820698
diningtable=0.754623
dog=0.828333
horse=0.875775
motorbike=0.821216
person=0.778399
pottedplant=0.486121
sheep=0.762316
sofa=0.791819
train=0.855429
tvmonitor=0.754418
mAP=0.759081
[Epoch 150][Batch 99], Speed: 85.496732 samples/sec, CrossEntropy=1.563708, SmoothL1=0.688837, accuracy=0.865222
[Epoch 150][Batch 199], Speed: 91.654923 samples/sec, CrossEntropy=1.583409, SmoothL1=0.692604, accuracy=0.864264
[Epoch 150][Batch 299], Speed: 88.795706 samples/sec, CrossEntropy=1.605957, SmoothL1=0.705469, accuracy=0.862789
[Epoch 150][Batch 399], Speed: 88.899689 samples/sec, CrossEntropy=1.603710, SmoothL1=0.699775, accuracy=0.863158
[Epoch 150][Batch 499], Speed: 93.009627 samples/sec, CrossEntropy=1.608292, SmoothL1=0.699442, accuracy=0.863062
[Epoch 150] Training cost: 194.805698, CrossEntropy=1.607434, SmoothL1=0.698652, accuracy=0.863138
[Epoch 150] Validation:
aeroplane=0.791571
bicycle=0.825888
bird=0.721142
boat=0.713429
bottle=0.441204
bus=0.824187
car=0.847701
cat=0.868524
chair=0.557086
cow=0.802305
diningtable=0.741238
dog=0.808442
horse=0.839529
motorbike=0.836278
person=0.772013
pottedplant=0.469242
sheep=0.752798
sofa=0.760224
train=0.861324
tvmonitor=0.756768
mAP=0.749545
[Epoch 151][Batch 99], Speed: 89.539133 samples/sec, CrossEntropy=1.598321, SmoothL1=0.685426, accuracy=0.862931
[Epoch 151][Batch 199], Speed: 90.457415 samples/sec, CrossEntropy=1.611160, SmoothL1=0.696135, accuracy=0.862595
[Epoch 151][Batch 299], Speed: 94.078946 samples/sec, CrossEntropy=1.609875, SmoothL1=0.697650, accuracy=0.862601
[Epoch 151][Batch 399], Speed: 93.064445 samples/sec, CrossEntropy=1.613811, SmoothL1=0.698327, accuracy=0.862642
[Epoch 151][Batch 499], Speed: 86.795183 samples/sec, CrossEntropy=1.609691, SmoothL1=0.695789, accuracy=0.862975
[Epoch 151] Training cost: 193.688398, CrossEntropy=1.607840, SmoothL1=0.695419, accuracy=0.862979
[Epoch 151] Validation:
aeroplane=0.786215
bicycle=0.814798
bird=0.731855
boat=0.665970
bottle=0.477006
bus=0.839099
car=0.846488
cat=0.840021
chair=0.566970
cow=0.806633
diningtable=0.752502
dog=0.824143
horse=0.849500
motorbike=0.823122
person=0.776464
pottedplant=0.481152
sheep=0.788468
sofa=0.780578
train=0.829094
tvmonitor=0.755083
mAP=0.751758
[Epoch 152][Batch 99], Speed: 81.751597 samples/sec, CrossEntropy=1.553816, SmoothL1=0.681657, accuracy=0.867282
[Epoch 152][Batch 199], Speed: 90.490959 samples/sec, CrossEntropy=1.579196, SmoothL1=0.691214, accuracy=0.865588
[Epoch 152][Batch 299], Speed: 73.325791 samples/sec, CrossEntropy=1.593809, SmoothL1=0.698334, accuracy=0.864298
[Epoch 152][Batch 399], Speed: 83.383849 samples/sec, CrossEntropy=1.600013, SmoothL1=0.697767, accuracy=0.863831
[Epoch 152][Batch 499], Speed: 90.120867 samples/sec, CrossEntropy=1.601470, SmoothL1=0.698559, accuracy=0.863860
[Epoch 152] Training cost: 194.184459, CrossEntropy=1.600783, SmoothL1=0.697976, accuracy=0.863825
[Epoch 152] Validation:
aeroplane=0.799831
bicycle=0.805654
bird=0.739494
boat=0.677433
bottle=0.472746
bus=0.834586
car=0.854298
cat=0.863556
chair=0.547633
cow=0.809164
diningtable=0.716228
dog=0.822388
horse=0.854515
motorbike=0.827827
person=0.767229
pottedplant=0.498621
sheep=0.748151
sofa=0.789600
train=0.852740
tvmonitor=0.758293
mAP=0.751999
[Epoch 153][Batch 99], Speed: 90.922086 samples/sec, CrossEntropy=1.523256, SmoothL1=0.655837, accuracy=0.869487
[Epoch 153][Batch 199], Speed: 95.703555 samples/sec, CrossEntropy=1.572337, SmoothL1=0.682374, accuracy=0.865966
[Epoch 153][Batch 299], Speed: 89.083194 samples/sec, CrossEntropy=1.577484, SmoothL1=0.686321, accuracy=0.865559
[Epoch 153][Batch 399], Speed: 88.020629 samples/sec, CrossEntropy=1.594195, SmoothL1=0.688188, accuracy=0.864323
[Epoch 153][Batch 499], Speed: 97.790196 samples/sec, CrossEntropy=1.603566, SmoothL1=0.689677, accuracy=0.863676
[Epoch 153] Training cost: 194.626552, CrossEntropy=1.604904, SmoothL1=0.690100, accuracy=0.863549
[Epoch 153] Validation:
aeroplane=0.788748
bicycle=0.825648
bird=0.740085
boat=0.690219
bottle=0.418535
bus=0.835242
car=0.854904
cat=0.848126
chair=0.554824
cow=0.799438
diningtable=0.745148
dog=0.818307
horse=0.861678
motorbike=0.815667
person=0.767377
pottedplant=0.445653
sheep=0.715252
sofa=0.762889
train=0.866141
tvmonitor=0.752993
mAP=0.745344
[Epoch 154][Batch 99], Speed: 88.753664 samples/sec, CrossEntropy=1.593109, SmoothL1=0.676444, accuracy=0.864289
[Epoch 154][Batch 199], Speed: 81.232862 samples/sec, CrossEntropy=1.598706, SmoothL1=0.686625, accuracy=0.863109
[Epoch 154][Batch 299], Speed: 91.513252 samples/sec, CrossEntropy=1.602305, SmoothL1=0.691201, accuracy=0.863201
[Epoch 154][Batch 399], Speed: 91.021111 samples/sec, CrossEntropy=1.600204, SmoothL1=0.692276, accuracy=0.863233
[Epoch 154][Batch 499], Speed: 95.640269 samples/sec, CrossEntropy=1.591572, SmoothL1=0.689476, accuracy=0.863858
[Epoch 154] Training cost: 194.478071, CrossEntropy=1.592259, SmoothL1=0.690542, accuracy=0.863803
[Epoch 154] Validation:
aeroplane=0.798716
bicycle=0.841560
bird=0.743015
boat=0.677032
bottle=0.455305
bus=0.829026
car=0.854063
cat=0.871601
chair=0.577322
cow=0.798851
diningtable=0.744202
dog=0.823790
horse=0.839011
motorbike=0.834016
person=0.776659
pottedplant=0.480710
sheep=0.737434
sofa=0.783696
train=0.862228
tvmonitor=0.755003
mAP=0.754162
[Epoch 155][Batch 99], Speed: 91.498903 samples/sec, CrossEntropy=1.571993, SmoothL1=0.670074, accuracy=0.865220
[Epoch 155][Batch 199], Speed: 93.437299 samples/sec, CrossEntropy=1.601229, SmoothL1=0.703027, accuracy=0.863498
[Epoch 155][Batch 299], Speed: 95.085621 samples/sec, CrossEntropy=1.600565, SmoothL1=0.699489, accuracy=0.863041
[Epoch 155][Batch 399], Speed: 82.451881 samples/sec, CrossEntropy=1.611790, SmoothL1=0.702198, accuracy=0.862503
[Epoch 155][Batch 499], Speed: 94.715494 samples/sec, CrossEntropy=1.603180, SmoothL1=0.698247, accuracy=0.863124
[Epoch 155] Training cost: 194.570693, CrossEntropy=1.600889, SmoothL1=0.695726, accuracy=0.863280
[Epoch 155] Validation:
aeroplane=0.804018
bicycle=0.826462
bird=0.740610
boat=0.680783
bottle=0.469396
bus=0.831750
car=0.854605
cat=0.868239
chair=0.568649
cow=0.797284
diningtable=0.758611
dog=0.826442
horse=0.861155
motorbike=0.830084
person=0.766598
pottedplant=0.488976
sheep=0.774995
sofa=0.787075
train=0.836244
tvmonitor=0.735081
mAP=0.755353
[Epoch 156][Batch 99], Speed: 93.274963 samples/sec, CrossEntropy=1.549752, SmoothL1=0.684508, accuracy=0.867472
[Epoch 156][Batch 199], Speed: 80.997849 samples/sec, CrossEntropy=1.569818, SmoothL1=0.688809, accuracy=0.865140
[Epoch 156][Batch 299], Speed: 88.825323 samples/sec, CrossEntropy=1.582065, SmoothL1=0.689929, accuracy=0.864318
[Epoch 156][Batch 399], Speed: 87.336301 samples/sec, CrossEntropy=1.581898, SmoothL1=0.682397, accuracy=0.864398
[Epoch 156][Batch 499], Speed: 86.155358 samples/sec, CrossEntropy=1.585239, SmoothL1=0.683136, accuracy=0.864320
[Epoch 156] Training cost: 194.179025, CrossEntropy=1.588001, SmoothL1=0.685224, accuracy=0.864075
[Epoch 156] Validation:
aeroplane=0.798084
bicycle=0.836877
bird=0.739102
boat=0.663133
bottle=0.473467
bus=0.818766
car=0.847764
cat=0.868344
chair=0.586809
cow=0.812326
diningtable=0.742431
dog=0.824593
horse=0.848523
motorbike=0.831472
person=0.768361
pottedplant=0.478010
sheep=0.740220
sofa=0.785883
train=0.851876
tvmonitor=0.749596
mAP=0.753282
[Epoch 157][Batch 99], Speed: 89.512619 samples/sec, CrossEntropy=1.572790, SmoothL1=0.681572, accuracy=0.865676
[Epoch 157][Batch 199], Speed: 88.581392 samples/sec, CrossEntropy=1.577982, SmoothL1=0.692630, accuracy=0.864602
[Epoch 157][Batch 299], Speed: 85.832822 samples/sec, CrossEntropy=1.587546, SmoothL1=0.693740, accuracy=0.863861
[Epoch 157][Batch 399], Speed: 86.642000 samples/sec, CrossEntropy=1.590155, SmoothL1=0.690475, accuracy=0.863884
[Epoch 157][Batch 499], Speed: 92.227226 samples/sec, CrossEntropy=1.589069, SmoothL1=0.689388, accuracy=0.864060
[Epoch 157] Training cost: 194.667371, CrossEntropy=1.591949, SmoothL1=0.690190, accuracy=0.863862
[Epoch 157] Validation:
aeroplane=0.790215
bicycle=0.836363
bird=0.746182
boat=0.691634
bottle=0.457367
bus=0.842920
car=0.854739
cat=0.867231
chair=0.571042
cow=0.797751
diningtable=0.731326
dog=0.824253
horse=0.861374
motorbike=0.819827
person=0.780039
pottedplant=0.479115
sheep=0.740539
sofa=0.766896
train=0.855203
tvmonitor=0.750446
mAP=0.753223
[Epoch 158][Batch 99], Speed: 89.515485 samples/sec, CrossEntropy=1.568229, SmoothL1=0.670962, accuracy=0.866179
[Epoch 158][Batch 199], Speed: 88.409031 samples/sec, CrossEntropy=1.564038, SmoothL1=0.679164, accuracy=0.866065
[Epoch 158][Batch 299], Speed: 90.491142 samples/sec, CrossEntropy=1.578408, SmoothL1=0.686322, accuracy=0.864769
[Epoch 158][Batch 399], Speed: 83.357903 samples/sec, CrossEntropy=1.579210, SmoothL1=0.679762, accuracy=0.864807
[Epoch 158][Batch 499], Speed: 88.796469 samples/sec, CrossEntropy=1.583206, SmoothL1=0.683672, accuracy=0.864706
[Epoch 158] Training cost: 194.614120, CrossEntropy=1.581363, SmoothL1=0.683754, accuracy=0.864810
[Epoch 158] Validation:
aeroplane=0.800924
bicycle=0.828309
bird=0.729806
boat=0.692698
bottle=0.465956
bus=0.828741
car=0.856753
cat=0.856386
chair=0.545328
cow=0.803434
diningtable=0.740351
dog=0.818870
horse=0.846118
motorbike=0.818598
person=0.773504
pottedplant=0.478585
sheep=0.754922
sofa=0.775889
train=0.846536
tvmonitor=0.765332
mAP=0.751352
[Epoch 159][Batch 99], Speed: 85.551609 samples/sec, CrossEntropy=1.563640, SmoothL1=0.679891, accuracy=0.865440
[Epoch 159][Batch 199], Speed: 89.057185 samples/sec, CrossEntropy=1.578085, SmoothL1=0.687170, accuracy=0.864570
[Epoch 159][Batch 299], Speed: 90.596017 samples/sec, CrossEntropy=1.573171, SmoothL1=0.684471, accuracy=0.864990
[Epoch 159][Batch 399], Speed: 84.968633 samples/sec, CrossEntropy=1.584919, SmoothL1=0.684215, accuracy=0.864285
[Epoch 159][Batch 499], Speed: 92.950947 samples/sec, CrossEntropy=1.580975, SmoothL1=0.682253, accuracy=0.864666
[Epoch 159] Training cost: 194.685547, CrossEntropy=1.579900, SmoothL1=0.682075, accuracy=0.864836
[Epoch 159] Validation:
aeroplane=0.801302
bicycle=0.826733
bird=0.725543
boat=0.679782
bottle=0.416943
bus=0.821670
car=0.846602
cat=0.856292
chair=0.581259
cow=0.790638
diningtable=0.763052
dog=0.809587
horse=0.862622
motorbike=0.839391
person=0.770582
pottedplant=0.481596
sheep=0.739916
sofa=0.784403
train=0.841504
tvmonitor=0.759356
mAP=0.749939
[Epoch 160] Set learning rate to 0.0001
[Epoch 160][Batch 99], Speed: 92.204353 samples/sec, CrossEntropy=1.557201, SmoothL1=0.681681, accuracy=0.866053
[Epoch 160][Batch 199], Speed: 82.954603 samples/sec, CrossEntropy=1.537446, SmoothL1=0.673657, accuracy=0.868189
[Epoch 160][Batch 299], Speed: 87.409673 samples/sec, CrossEntropy=1.520007, SmoothL1=0.665578, accuracy=0.869853
[Epoch 160][Batch 399], Speed: 95.514424 samples/sec, CrossEntropy=1.502009, SmoothL1=0.651573, accuracy=0.871102
[Epoch 160][Batch 499], Speed: 93.502587 samples/sec, CrossEntropy=1.496311, SmoothL1=0.650819, accuracy=0.871693
[Epoch 160] Training cost: 194.197299, CrossEntropy=1.494207, SmoothL1=0.648254, accuracy=0.871820
[Epoch 160] Validation:
aeroplane=0.809156
bicycle=0.830810
bird=0.758986
boat=0.702672
bottle=0.471006
bus=0.841587
car=0.857992
cat=0.885720
chair=0.591955
cow=0.829987
diningtable=0.758556
dog=0.837634
horse=0.851370
motorbike=0.854627
person=0.780557
pottedplant=0.500694
sheep=0.778299
sofa=0.805057
train=0.860140
tvmonitor=0.768529
mAP=0.768767
[Epoch 161][Batch 99], Speed: 88.263335 samples/sec, CrossEntropy=1.455325, SmoothL1=0.624319, accuracy=0.875965
[Epoch 161][Batch 199], Speed: 94.227620 samples/sec, CrossEntropy=1.475077, SmoothL1=0.637990, accuracy=0.873762
[Epoch 161][Batch 299], Speed: 95.587005 samples/sec, CrossEntropy=1.466907, SmoothL1=0.634628, accuracy=0.874477
[Epoch 161][Batch 399], Speed: 84.098429 samples/sec, CrossEntropy=1.463585, SmoothL1=0.629824, accuracy=0.874744
[Epoch 161][Batch 499], Speed: 83.133153 samples/sec, CrossEntropy=1.461795, SmoothL1=0.628903, accuracy=0.874665
[Epoch 161] Training cost: 194.153271, CrossEntropy=1.461423, SmoothL1=0.628621, accuracy=0.874722
[Epoch 161] Validation:
aeroplane=0.805330
bicycle=0.828179
bird=0.763421
boat=0.695098
bottle=0.474377
bus=0.842931
car=0.860203
cat=0.877791
chair=0.588819
cow=0.832961
diningtable=0.771405
dog=0.841266
horse=0.867830
motorbike=0.850910
person=0.780328
pottedplant=0.497610
sheep=0.778867
sofa=0.794949
train=0.868511
tvmonitor=0.768572
mAP=0.769468
[Epoch 162][Batch 99], Speed: 84.968633 samples/sec, CrossEntropy=1.434458, SmoothL1=0.637548, accuracy=0.876407
[Epoch 162][Batch 199], Speed: 93.332041 samples/sec, CrossEntropy=1.445079, SmoothL1=0.636208, accuracy=0.875729
[Epoch 162][Batch 299], Speed: 88.269894 samples/sec, CrossEntropy=1.441688, SmoothL1=0.629076, accuracy=0.876405
[Epoch 162][Batch 399], Speed: 87.567071 samples/sec, CrossEntropy=1.438808, SmoothL1=0.622347, accuracy=0.876415
[Epoch 162][Batch 499], Speed: 99.074732 samples/sec, CrossEntropy=1.431317, SmoothL1=0.616904, accuracy=0.876953
[Epoch 162] Training cost: 194.071274, CrossEntropy=1.432595, SmoothL1=0.617522, accuracy=0.876793
[Epoch 162] Validation:
aeroplane=0.801632
bicycle=0.832300
bird=0.758406
boat=0.707893
bottle=0.470684
bus=0.845416
car=0.863000
cat=0.880473
chair=0.595016
cow=0.836587
diningtable=0.767776
dog=0.845151
horse=0.863705
motorbike=0.852865
person=0.784354
pottedplant=0.499951
sheep=0.776855
sofa=0.802991
train=0.867481
tvmonitor=0.768016
mAP=0.771028
[Epoch 163][Batch 99], Speed: 90.091165 samples/sec, CrossEntropy=1.439358, SmoothL1=0.630279, accuracy=0.876205
[Epoch 163][Batch 199], Speed: 88.479376 samples/sec, CrossEntropy=1.429855, SmoothL1=0.621005, accuracy=0.876722
[Epoch 163][Batch 299], Speed: 89.983352 samples/sec, CrossEntropy=1.425037, SmoothL1=0.616439, accuracy=0.877426
[Epoch 163][Batch 399], Speed: 88.057010 samples/sec, CrossEntropy=1.422459, SmoothL1=0.610484, accuracy=0.877517
[Epoch 163][Batch 499], Speed: 95.787018 samples/sec, CrossEntropy=1.421788, SmoothL1=0.609180, accuracy=0.877706
[Epoch 163] Training cost: 194.093745, CrossEntropy=1.419967, SmoothL1=0.609398, accuracy=0.877752
[Epoch 163] Validation:
aeroplane=0.810535
bicycle=0.830664
bird=0.753346
boat=0.711732
bottle=0.478385
bus=0.849527
car=0.862504
cat=0.877813
chair=0.605238
cow=0.832432
diningtable=0.751743
dog=0.845900
horse=0.865999
motorbike=0.856511
person=0.785759
pottedplant=0.506429
sheep=0.785025
sofa=0.794730
train=0.859763
tvmonitor=0.769950
mAP=0.771699
[Epoch 164][Batch 99], Speed: 87.747462 samples/sec, CrossEntropy=1.393048, SmoothL1=0.594498, accuracy=0.880295
[Epoch 164][Batch 199], Speed: 91.804317 samples/sec, CrossEntropy=1.411972, SmoothL1=0.611823, accuracy=0.878493
[Epoch 164][Batch 299], Speed: 87.891689 samples/sec, CrossEntropy=1.418049, SmoothL1=0.617749, accuracy=0.877810
[Epoch 164][Batch 399], Speed: 96.474147 samples/sec, CrossEntropy=1.417709, SmoothL1=0.613352, accuracy=0.878183
[Epoch 164][Batch 499], Speed: 96.440111 samples/sec, CrossEntropy=1.408501, SmoothL1=0.606023, accuracy=0.878691
[Epoch 164] Training cost: 194.531503, CrossEntropy=1.404517, SmoothL1=0.603704, accuracy=0.879017
[Epoch 164] Validation:
aeroplane=0.807501
bicycle=0.831004
bird=0.758844
boat=0.709612
bottle=0.483535
bus=0.843937
car=0.863162
cat=0.877264
chair=0.603943
cow=0.838158
diningtable=0.770163
dog=0.846458
horse=0.865883
motorbike=0.853979
person=0.784628
pottedplant=0.507539
sheep=0.779983
sofa=0.802336
train=0.873029
tvmonitor=0.759711
mAP=0.773033
[Epoch 165][Batch 99], Speed: 83.197465 samples/sec, CrossEntropy=1.399199, SmoothL1=0.603102, accuracy=0.879039
[Epoch 165][Batch 199], Speed: 87.049457 samples/sec, CrossEntropy=1.418022, SmoothL1=0.620076, accuracy=0.877445
[Epoch 165][Batch 299], Speed: 82.622574 samples/sec, CrossEntropy=1.417825, SmoothL1=0.618556, accuracy=0.877842
[Epoch 165][Batch 399], Speed: 75.158825 samples/sec, CrossEntropy=1.418261, SmoothL1=0.615740, accuracy=0.877849
[Epoch 165][Batch 499], Speed: 91.018766 samples/sec, CrossEntropy=1.415294, SmoothL1=0.613428, accuracy=0.878252
[Epoch 165] Training cost: 193.892016, CrossEntropy=1.415294, SmoothL1=0.611590, accuracy=0.878266
[Epoch 165] Validation:
aeroplane=0.807342
bicycle=0.832332
bird=0.770153
boat=0.703478
bottle=0.481149
bus=0.846214
car=0.861309
cat=0.878382
chair=0.607721
cow=0.832485
diningtable=0.769253
dog=0.854258
horse=0.862812
motorbike=0.851455
person=0.783517
pottedplant=0.510442
sheep=0.782820
sofa=0.794645
train=0.874119
tvmonitor=0.769829
mAP=0.773686
[Epoch 166][Batch 99], Speed: 90.657088 samples/sec, CrossEntropy=1.397239, SmoothL1=0.611958, accuracy=0.879865
[Epoch 166][Batch 199], Speed: 91.984196 samples/sec, CrossEntropy=1.403261, SmoothL1=0.612087, accuracy=0.879380
[Epoch 166][Batch 299], Speed: 84.515988 samples/sec, CrossEntropy=1.404612, SmoothL1=0.610833, accuracy=0.879448
[Epoch 166][Batch 399], Speed: 88.255616 samples/sec, CrossEntropy=1.407457, SmoothL1=0.610013, accuracy=0.878918
[Epoch 166][Batch 499], Speed: 84.308042 samples/sec, CrossEntropy=1.403716, SmoothL1=0.606449, accuracy=0.879421
[Epoch 166] Training cost: 193.824702, CrossEntropy=1.403520, SmoothL1=0.605399, accuracy=0.879457
[Epoch 166] Validation:
aeroplane=0.806262
bicycle=0.832873
bird=0.749561
boat=0.706445
bottle=0.476354
bus=0.844538
car=0.862593
cat=0.883067
chair=0.598931
cow=0.831615
diningtable=0.765785
dog=0.851076
horse=0.866772
motorbike=0.850267
person=0.785374
pottedplant=0.503919
sheep=0.786222
sofa=0.808141
train=0.872876
tvmonitor=0.775129
mAP=0.772890
[Epoch 167][Batch 99], Speed: 91.896717 samples/sec, CrossEntropy=1.406098, SmoothL1=0.603323, accuracy=0.879480
[Epoch 167][Batch 199], Speed: 92.270974 samples/sec, CrossEntropy=1.419695, SmoothL1=0.613574, accuracy=0.878301
[Epoch 167][Batch 299], Speed: 90.230284 samples/sec, CrossEntropy=1.417184, SmoothL1=0.611619, accuracy=0.878153
[Epoch 167][Batch 399], Speed: 88.302357 samples/sec, CrossEntropy=1.410078, SmoothL1=0.606912, accuracy=0.878799
[Epoch 167][Batch 499], Speed: 95.890628 samples/sec, CrossEntropy=1.403925, SmoothL1=0.604355, accuracy=0.879058
[Epoch 167] Training cost: 194.963415, CrossEntropy=1.407276, SmoothL1=0.606723, accuracy=0.878890
[Epoch 167] Validation:
aeroplane=0.806343
bicycle=0.842180
bird=0.756338
boat=0.705382
bottle=0.477670
bus=0.848820
car=0.862445
cat=0.883701
chair=0.598166
cow=0.839736
diningtable=0.772773
dog=0.846624
horse=0.865439
motorbike=0.845675
person=0.784151
pottedplant=0.498443
sheep=0.786708
sofa=0.798718
train=0.873587
tvmonitor=0.770490
mAP=0.773169
[Epoch 168][Batch 99], Speed: 90.288068 samples/sec, CrossEntropy=1.391612, SmoothL1=0.587914, accuracy=0.880691
[Epoch 168][Batch 199], Speed: 95.604163 samples/sec, CrossEntropy=1.391500, SmoothL1=0.591739, accuracy=0.880096
[Epoch 168][Batch 299], Speed: 88.152495 samples/sec, CrossEntropy=1.395101, SmoothL1=0.600592, accuracy=0.879876
[Epoch 168][Batch 399], Speed: 84.317734 samples/sec, CrossEntropy=1.400178, SmoothL1=0.602264, accuracy=0.879329
[Epoch 168][Batch 499], Speed: 92.779839 samples/sec, CrossEntropy=1.398799, SmoothL1=0.599455, accuracy=0.879507
[Epoch 168] Training cost: 194.276813, CrossEntropy=1.399602, SmoothL1=0.599288, accuracy=0.879499
[Epoch 168] Validation:
aeroplane=0.808753
bicycle=0.832524
bird=0.756018
boat=0.705560
bottle=0.477231
bus=0.851142
car=0.862688
cat=0.883206
chair=0.608255
cow=0.836121
diningtable=0.764932
dog=0.849532
horse=0.869008
motorbike=0.850679
person=0.781895
pottedplant=0.501018
sheep=0.794770
sofa=0.795904
train=0.874515
tvmonitor=0.772000
mAP=0.773788
[Epoch 169][Batch 99], Speed: 88.389934 samples/sec, CrossEntropy=1.373899, SmoothL1=0.591320, accuracy=0.882771
[Epoch 169][Batch 199], Speed: 86.194033 samples/sec, CrossEntropy=1.394101, SmoothL1=0.601405, accuracy=0.880741
[Epoch 169][Batch 299], Speed: 89.244071 samples/sec, CrossEntropy=1.402374, SmoothL1=0.609795, accuracy=0.879348
[Epoch 169][Batch 399], Speed: 87.482884 samples/sec, CrossEntropy=1.402958, SmoothL1=0.606785, accuracy=0.879428
[Epoch 169][Batch 499], Speed: 98.469326 samples/sec, CrossEntropy=1.396937, SmoothL1=0.601899, accuracy=0.879714
[Epoch 169] Training cost: 194.672653, CrossEntropy=1.396100, SmoothL1=0.601922, accuracy=0.879767
[Epoch 169] Validation:
aeroplane=0.809915
bicycle=0.831305
bird=0.758913
boat=0.709336
bottle=0.474202
bus=0.842542
car=0.860637
cat=0.878646
chair=0.601223
cow=0.824134
diningtable=0.777218
dog=0.848473
horse=0.861737
motorbike=0.848267
person=0.782988
pottedplant=0.505232
sheep=0.789270
sofa=0.797231
train=0.871172
tvmonitor=0.772448
mAP=0.772244
[Epoch 170][Batch 99], Speed: 90.099814 samples/sec, CrossEntropy=1.376246, SmoothL1=0.579297, accuracy=0.881958
[Epoch 170][Batch 199], Speed: 89.391656 samples/sec, CrossEntropy=1.390171, SmoothL1=0.599680, accuracy=0.880613
[Epoch 170][Batch 299], Speed: 84.750054 samples/sec, CrossEntropy=1.388608, SmoothL1=0.600154, accuracy=0.880334
[Epoch 170][Batch 399], Speed: 87.903489 samples/sec, CrossEntropy=1.382093, SmoothL1=0.593867, accuracy=0.880840
[Epoch 170][Batch 499], Speed: 92.408004 samples/sec, CrossEntropy=1.381299, SmoothL1=0.595964, accuracy=0.880864
[Epoch 170] Training cost: 194.332178, CrossEntropy=1.380667, SmoothL1=0.595473, accuracy=0.880960
[Epoch 170] Validation:
aeroplane=0.806114
bicycle=0.829556
bird=0.761234
boat=0.719071
bottle=0.482219
bus=0.848497
car=0.860004
cat=0.882827
chair=0.602182
cow=0.833762
diningtable=0.772157
dog=0.846671
horse=0.862868
motorbike=0.851035
person=0.785270
pottedplant=0.502553
sheep=0.784598
sofa=0.802309
train=0.870103
tvmonitor=0.766402
mAP=0.773472
[Epoch 171][Batch 99], Speed: 83.405352 samples/sec, CrossEntropy=1.335691, SmoothL1=0.570213, accuracy=0.883499
[Epoch 171][Batch 199], Speed: 89.308323 samples/sec, CrossEntropy=1.371016, SmoothL1=0.588606, accuracy=0.880886
[Epoch 171][Batch 299], Speed: 95.898712 samples/sec, CrossEntropy=1.383685, SmoothL1=0.595461, accuracy=0.880599
[Epoch 171][Batch 399], Speed: 89.750369 samples/sec, CrossEntropy=1.380965, SmoothL1=0.591333, accuracy=0.880854
[Epoch 171][Batch 499], Speed: 90.358091 samples/sec, CrossEntropy=1.383542, SmoothL1=0.590792, accuracy=0.880736
[Epoch 171] Training cost: 194.984488, CrossEntropy=1.385128, SmoothL1=0.590956, accuracy=0.880665
[Epoch 171] Validation:
aeroplane=0.808009
bicycle=0.832154
bird=0.762974
boat=0.710374
bottle=0.485756
bus=0.844983
car=0.862192
cat=0.884512
chair=0.600432
cow=0.836606
diningtable=0.776577
dog=0.847022
horse=0.866562
motorbike=0.856638
person=0.782827
pottedplant=0.499582
sheep=0.790088
sofa=0.803620
train=0.858588
tvmonitor=0.770119
mAP=0.773981
[Epoch 172][Batch 99], Speed: 86.563768 samples/sec, CrossEntropy=1.372594, SmoothL1=0.576204, accuracy=0.882264
[Epoch 172][Batch 199], Speed: 94.394155 samples/sec, CrossEntropy=1.395361, SmoothL1=0.598965, accuracy=0.880414
[Epoch 172][Batch 299], Speed: 88.229798 samples/sec, CrossEntropy=1.397272, SmoothL1=0.600335, accuracy=0.880182
[Epoch 172][Batch 399], Speed: 83.067862 samples/sec, CrossEntropy=1.398605, SmoothL1=0.598048, accuracy=0.880054
[Epoch 172][Batch 499], Speed: 96.046875 samples/sec, CrossEntropy=1.393890, SmoothL1=0.594005, accuracy=0.880301
[Epoch 172] Training cost: 194.356796, CrossEntropy=1.394445, SmoothL1=0.593873, accuracy=0.880304
[Epoch 172] Validation:
aeroplane=0.810226
bicycle=0.828593
bird=0.749398
boat=0.707966
bottle=0.481555
bus=0.850274
car=0.859655
cat=0.875070
chair=0.596650
cow=0.834137
diningtable=0.775780
dog=0.845259
horse=0.864957
motorbike=0.855357
person=0.779244
pottedplant=0.503863
sheep=0.805429
sofa=0.796580
train=0.867089
tvmonitor=0.772811
mAP=0.772995
[Epoch 173][Batch 99], Speed: 88.674445 samples/sec, CrossEntropy=1.358975, SmoothL1=0.575827, accuracy=0.883509
[Epoch 173][Batch 199], Speed: 94.043811 samples/sec, CrossEntropy=1.377660, SmoothL1=0.591319, accuracy=0.881738
[Epoch 173][Batch 299], Speed: 90.985447 samples/sec, CrossEntropy=1.373808, SmoothL1=0.588935, accuracy=0.881986
[Epoch 173][Batch 399], Speed: 87.563072 samples/sec, CrossEntropy=1.374484, SmoothL1=0.589949, accuracy=0.881920
[Epoch 173][Batch 499], Speed: 88.547380 samples/sec, CrossEntropy=1.378190, SmoothL1=0.594050, accuracy=0.881460
[Epoch 173] Training cost: 194.749094, CrossEntropy=1.378038, SmoothL1=0.594235, accuracy=0.881469
[Epoch 173] Validation:
aeroplane=0.810763
bicycle=0.828681
bird=0.749860
boat=0.717274
bottle=0.476124
bus=0.844039
car=0.863133
cat=0.879036
chair=0.598478
cow=0.836030
diningtable=0.765692
dog=0.849316
horse=0.862874
motorbike=0.842673
person=0.783663
pottedplant=0.504645
sheep=0.797868
sofa=0.795847
train=0.871332
tvmonitor=0.771404
mAP=0.772437
[Epoch 174][Batch 99], Speed: 91.083622 samples/sec, CrossEntropy=1.367799, SmoothL1=0.603429, accuracy=0.883226
[Epoch 174][Batch 199], Speed: 80.158509 samples/sec, CrossEntropy=1.385427, SmoothL1=0.611561, accuracy=0.881682
[Epoch 174][Batch 299], Speed: 92.429131 samples/sec, CrossEntropy=1.384961, SmoothL1=0.604325, accuracy=0.881290
[Epoch 174][Batch 399], Speed: 88.911232 samples/sec, CrossEntropy=1.389685, SmoothL1=0.603538, accuracy=0.880817
[Epoch 174][Batch 499], Speed: 92.432314 samples/sec, CrossEntropy=1.389395, SmoothL1=0.601805, accuracy=0.880596
[Epoch 174] Training cost: 194.028416, CrossEntropy=1.391204, SmoothL1=0.601923, accuracy=0.880424
[Epoch 174] Validation:
aeroplane=0.810768
bicycle=0.832671
bird=0.752560
boat=0.711491
bottle=0.475561
bus=0.847876
car=0.863380
cat=0.880984
chair=0.598675
cow=0.833366
diningtable=0.777686
dog=0.853293
horse=0.869886
motorbike=0.833904
person=0.782913
pottedplant=0.497610
sheep=0.792446
sofa=0.799367
train=0.870030
tvmonitor=0.769693
mAP=0.772708
[Epoch 175][Batch 99], Speed: 83.324990 samples/sec, CrossEntropy=1.380512, SmoothL1=0.603593, accuracy=0.881110
[Epoch 175][Batch 199], Speed: 92.814036 samples/sec, CrossEntropy=1.398466, SmoothL1=0.610472, accuracy=0.879408
[Epoch 175][Batch 299], Speed: 82.908280 samples/sec, CrossEntropy=1.402238, SmoothL1=0.608344, accuracy=0.878934
[Epoch 175][Batch 399], Speed: 88.833319 samples/sec, CrossEntropy=1.393788, SmoothL1=0.601382, accuracy=0.879866
[Epoch 175][Batch 499], Speed: 86.050078 samples/sec, CrossEntropy=1.394937, SmoothL1=0.600272, accuracy=0.879874
[Epoch 175] Training cost: 194.106759, CrossEntropy=1.394084, SmoothL1=0.600646, accuracy=0.879955
[Epoch 175] Validation:
aeroplane=0.804656
bicycle=0.826582
bird=0.740674
boat=0.709720
bottle=0.479572
bus=0.850312
car=0.860709
cat=0.876633
chair=0.597909
cow=0.840255
diningtable=0.779334
dog=0.846627
horse=0.869645
motorbike=0.842481
person=0.783083
pottedplant=0.508277
sheep=0.800784
sofa=0.798284
train=0.862449
tvmonitor=0.771086
mAP=0.772454
[Epoch 176][Batch 99], Speed: 94.594136 samples/sec, CrossEntropy=1.365646, SmoothL1=0.587690, accuracy=0.881882
[Epoch 176][Batch 199], Speed: 89.049859 samples/sec, CrossEntropy=1.384866, SmoothL1=0.600300, accuracy=0.880568
[Epoch 176][Batch 299], Speed: 85.261237 samples/sec, CrossEntropy=1.380929, SmoothL1=0.598886, accuracy=0.880884
[Epoch 176][Batch 399], Speed: 80.201857 samples/sec, CrossEntropy=1.381564, SmoothL1=0.592921, accuracy=0.881148
[Epoch 176][Batch 499], Speed: 90.296086 samples/sec, CrossEntropy=1.384464, SmoothL1=0.595286, accuracy=0.880883
[Epoch 176] Training cost: 194.522851, CrossEntropy=1.383018, SmoothL1=0.594033, accuracy=0.881087
[Epoch 176] Validation:
aeroplane=0.809621
bicycle=0.845659
bird=0.749962
boat=0.716980
bottle=0.473365
bus=0.851830
car=0.863254
cat=0.879043
chair=0.600652
cow=0.837705
diningtable=0.766133
dog=0.844796
horse=0.869365
motorbike=0.844225
person=0.781269
pottedplant=0.506589
sheep=0.792087
sofa=0.805855
train=0.868849
tvmonitor=0.772505
mAP=0.773987
[Epoch 177][Batch 99], Speed: 69.785559 samples/sec, CrossEntropy=1.347794, SmoothL1=0.585216, accuracy=0.884315
[Epoch 177][Batch 199], Speed: 79.986250 samples/sec, CrossEntropy=1.365309, SmoothL1=0.594921, accuracy=0.882037
[Epoch 177][Batch 299], Speed: 94.284744 samples/sec, CrossEntropy=1.368326, SmoothL1=0.592808, accuracy=0.881852
[Epoch 177][Batch 399], Speed: 87.433702 samples/sec, CrossEntropy=1.375578, SmoothL1=0.593918, accuracy=0.881515
[Epoch 177][Batch 499], Speed: 87.448457 samples/sec, CrossEntropy=1.375092, SmoothL1=0.593112, accuracy=0.881662
[Epoch 177] Training cost: 194.877591, CrossEntropy=1.375348, SmoothL1=0.592418, accuracy=0.881650
[Epoch 177] Validation:
aeroplane=0.814403
bicycle=0.846143
bird=0.754424
boat=0.713353
bottle=0.481339
bus=0.845105
car=0.861634
cat=0.880467
chair=0.601284
cow=0.837791
diningtable=0.772136
dog=0.850250
horse=0.871397
motorbike=0.843601
person=0.785154
pottedplant=0.508171
sheep=0.790823
sofa=0.802602
train=0.868154
tvmonitor=0.765122
mAP=0.774668
[Epoch 178][Batch 99], Speed: 85.728766 samples/sec, CrossEntropy=1.361797, SmoothL1=0.587075, accuracy=0.883664
[Epoch 178][Batch 199], Speed: 85.284533 samples/sec, CrossEntropy=1.371179, SmoothL1=0.590519, accuracy=0.882724
[Epoch 178][Batch 299], Speed: 88.353393 samples/sec, CrossEntropy=1.362324, SmoothL1=0.588619, accuracy=0.883349
[Epoch 178][Batch 399], Speed: 87.879604 samples/sec, CrossEntropy=1.362248, SmoothL1=0.587111, accuracy=0.883059
[Epoch 178][Batch 499], Speed: 98.315473 samples/sec, CrossEntropy=1.362002, SmoothL1=0.584892, accuracy=0.883159
[Epoch 178] Training cost: 195.160872, CrossEntropy=1.363623, SmoothL1=0.585795, accuracy=0.882962
[Epoch 178] Validation:
aeroplane=0.806854
bicycle=0.831535
bird=0.757934
boat=0.716180
bottle=0.473728
bus=0.850933
car=0.862969
cat=0.882780
chair=0.601254
cow=0.839236
diningtable=0.767058
dog=0.849361
horse=0.867310
motorbike=0.845842
person=0.783254
pottedplant=0.509227
sheep=0.786346
sofa=0.789851
train=0.871622
tvmonitor=0.773624
mAP=0.773345
[Epoch 179][Batch 99], Speed: 86.446518 samples/sec, CrossEntropy=1.349452, SmoothL1=0.583956, accuracy=0.883931
[Epoch 179][Batch 199], Speed: 82.019771 samples/sec, CrossEntropy=1.361268, SmoothL1=0.591121, accuracy=0.882869
[Epoch 179][Batch 299], Speed: 89.496862 samples/sec, CrossEntropy=1.367255, SmoothL1=0.595290, accuracy=0.882220
[Epoch 179][Batch 399], Speed: 85.555481 samples/sec, CrossEntropy=1.365999, SmoothL1=0.593019, accuracy=0.882400
[Epoch 179][Batch 499], Speed: 89.610930 samples/sec, CrossEntropy=1.372859, SmoothL1=0.594232, accuracy=0.881791
[Epoch 179] Training cost: 194.713340, CrossEntropy=1.374349, SmoothL1=0.593610, accuracy=0.881661
[Epoch 179] Validation:
aeroplane=0.810383
bicycle=0.829202
bird=0.760346
boat=0.711116
bottle=0.476681
bus=0.845247
car=0.863519
cat=0.878207
chair=0.600234
cow=0.838073
diningtable=0.769997
dog=0.845849
horse=0.868142
motorbike=0.842772
person=0.782374
pottedplant=0.504570
sheep=0.792014
sofa=0.808010
train=0.868066
tvmonitor=0.766978
mAP=0.773089
[Epoch 180][Batch 99], Speed: 94.764379 samples/sec, CrossEntropy=1.348521, SmoothL1=0.575779, accuracy=0.884917
[Epoch 180][Batch 199], Speed: 83.545944 samples/sec, CrossEntropy=1.376975, SmoothL1=0.600850, accuracy=0.881799
[Epoch 180][Batch 299], Speed: 78.618724 samples/sec, CrossEntropy=1.386033, SmoothL1=0.603442, accuracy=0.880927
[Epoch 180][Batch 399], Speed: 88.333274 samples/sec, CrossEntropy=1.376566, SmoothL1=0.596146, accuracy=0.881704
[Epoch 180][Batch 499], Speed: 87.525557 samples/sec, CrossEntropy=1.371827, SmoothL1=0.592061, accuracy=0.882181
[Epoch 180] Training cost: 193.957999, CrossEntropy=1.372526, SmoothL1=0.591379, accuracy=0.882166
[Epoch 180] Validation:
aeroplane=0.808625
bicycle=0.830373
bird=0.760034
boat=0.713967
bottle=0.480255
bus=0.849098
car=0.863766
cat=0.877842
chair=0.601545
cow=0.837675
diningtable=0.773750
dog=0.848494
horse=0.868157
motorbike=0.846061
person=0.786669
pottedplant=0.504164
sheep=0.767030
sofa=0.802233
train=0.870893
tvmonitor=0.769096
mAP=0.772986
[Epoch 181][Batch 99], Speed: 85.535471 samples/sec, CrossEntropy=1.364976, SmoothL1=0.591264, accuracy=0.881912
[Epoch 181][Batch 199], Speed: 86.867031 samples/sec, CrossEntropy=1.369388, SmoothL1=0.596756, accuracy=0.882039
[Epoch 181][Batch 299], Speed: 95.672925 samples/sec, CrossEntropy=1.374975, SmoothL1=0.601346, accuracy=0.881510
[Epoch 181][Batch 399], Speed: 87.007699 samples/sec, CrossEntropy=1.376581, SmoothL1=0.599292, accuracy=0.881062
[Epoch 181][Batch 499], Speed: 91.971149 samples/sec, CrossEntropy=1.377596, SmoothL1=0.600104, accuracy=0.881031
[Epoch 181] Training cost: 194.273026, CrossEntropy=1.378534, SmoothL1=0.599502, accuracy=0.880953
[Epoch 181] Validation:
aeroplane=0.812270
bicycle=0.827766
bird=0.745152
boat=0.710037
bottle=0.490628
bus=0.845700
car=0.864014
cat=0.876936
chair=0.604169
cow=0.824264
diningtable=0.766092
dog=0.850415
horse=0.864143
motorbike=0.840522
person=0.785086
pottedplant=0.508123
sheep=0.787124
sofa=0.810113
train=0.870614
tvmonitor=0.770011
mAP=0.772659
[Epoch 182][Batch 99], Speed: 91.341051 samples/sec, CrossEntropy=1.325923, SmoothL1=0.558411, accuracy=0.885023
[Epoch 182][Batch 199], Speed: 83.971311 samples/sec, CrossEntropy=1.361707, SmoothL1=0.581357, accuracy=0.882383
[Epoch 182][Batch 299], Speed: 91.917989 samples/sec, CrossEntropy=1.361594, SmoothL1=0.585840, accuracy=0.882554
[Epoch 182][Batch 399], Speed: 80.980939 samples/sec, CrossEntropy=1.367994, SmoothL1=0.587946, accuracy=0.882176
[Epoch 182][Batch 499], Speed: 90.786599 samples/sec, CrossEntropy=1.360521, SmoothL1=0.584088, accuracy=0.883060
[Epoch 182] Training cost: 194.644398, CrossEntropy=1.361424, SmoothL1=0.584888, accuracy=0.882979
[Epoch 182] Validation:
aeroplane=0.808639
bicycle=0.834965
bird=0.753442
boat=0.709086
bottle=0.481073
bus=0.853794
car=0.863408
cat=0.872877
chair=0.601487
cow=0.834802
diningtable=0.766966
dog=0.847271
horse=0.868163
motorbike=0.849741
person=0.781653
pottedplant=0.502461
sheep=0.780788
sofa=0.791958
train=0.869615
tvmonitor=0.768625
mAP=0.772041
[Epoch 183][Batch 99], Speed: 83.985445 samples/sec, CrossEntropy=1.349807, SmoothL1=0.585421, accuracy=0.883597
[Epoch 183][Batch 199], Speed: 81.583389 samples/sec, CrossEntropy=1.360936, SmoothL1=0.590956, accuracy=0.882048
[Epoch 183][Batch 299], Speed: 95.029474 samples/sec, CrossEntropy=1.361081, SmoothL1=0.589049, accuracy=0.882256
[Epoch 183][Batch 399], Speed: 84.278396 samples/sec, CrossEntropy=1.362993, SmoothL1=0.588194, accuracy=0.882021
[Epoch 183][Batch 499], Speed: 90.995748 samples/sec, CrossEntropy=1.362689, SmoothL1=0.585564, accuracy=0.882274
[Epoch 183] Training cost: 194.611991, CrossEntropy=1.362163, SmoothL1=0.583977, accuracy=0.882374
[Epoch 183] Validation:
aeroplane=0.815014
bicycle=0.834972
bird=0.762301
boat=0.719150
bottle=0.483112
bus=0.850776
car=0.863831
cat=0.877915
chair=0.591376
cow=0.837049
diningtable=0.767411
dog=0.848157
horse=0.868584
motorbike=0.841913
person=0.781418
pottedplant=0.501844
sheep=0.787349
sofa=0.802667
train=0.872432
tvmonitor=0.770452
mAP=0.773886
[Epoch 184][Batch 99], Speed: 88.431515 samples/sec, CrossEntropy=1.358470, SmoothL1=0.594743, accuracy=0.882308
[Epoch 184][Batch 199], Speed: 95.205476 samples/sec, CrossEntropy=1.356664, SmoothL1=0.593027, accuracy=0.883060
[Epoch 184][Batch 299], Speed: 88.301427 samples/sec, CrossEntropy=1.359141, SmoothL1=0.590530, accuracy=0.882745
[Epoch 184][Batch 399], Speed: 85.222150 samples/sec, CrossEntropy=1.354958, SmoothL1=0.583671, accuracy=0.883014
[Epoch 184][Batch 499], Speed: 96.894535 samples/sec, CrossEntropy=1.356940, SmoothL1=0.581327, accuracy=0.882863
[Epoch 184] Training cost: 194.264554, CrossEntropy=1.357337, SmoothL1=0.580529, accuracy=0.882876
[Epoch 184] Validation:
aeroplane=0.818761
bicycle=0.834252
bird=0.758801
boat=0.714801
bottle=0.486542
bus=0.850961
car=0.859693
cat=0.883135
chair=0.599128
cow=0.827654
diningtable=0.769699
dog=0.845218
horse=0.871798
motorbike=0.842742
person=0.783121
pottedplant=0.499328
sheep=0.778934
sofa=0.800951
train=0.870798
tvmonitor=0.771530
mAP=0.773392
[Epoch 185][Batch 99], Speed: 83.019153 samples/sec, CrossEntropy=1.355703, SmoothL1=0.592856, accuracy=0.884215
[Epoch 185][Batch 199], Speed: 75.918225 samples/sec, CrossEntropy=1.353490, SmoothL1=0.585576, accuracy=0.884196
[Epoch 185][Batch 299], Speed: 90.195722 samples/sec, CrossEntropy=1.353524, SmoothL1=0.582846, accuracy=0.883794
[Epoch 185][Batch 399], Speed: 90.617854 samples/sec, CrossEntropy=1.358826, SmoothL1=0.578988, accuracy=0.883545
[Epoch 185][Batch 499], Speed: 94.359448 samples/sec, CrossEntropy=1.361776, SmoothL1=0.581473, accuracy=0.883132
[Epoch 185] Training cost: 194.315655, CrossEntropy=1.362952, SmoothL1=0.581841, accuracy=0.883061
[Epoch 185] Validation:
aeroplane=0.816204
bicycle=0.833682
bird=0.757955
boat=0.713642
bottle=0.479517
bus=0.845203
car=0.864293
cat=0.880185
chair=0.603412
cow=0.839683
diningtable=0.754812
dog=0.851133
horse=0.866904
motorbike=0.849352
person=0.785800
pottedplant=0.511225
sheep=0.773311
sofa=0.793766
train=0.872972
tvmonitor=0.771284
mAP=0.773217
[Epoch 186][Batch 99], Speed: 84.616426 samples/sec, CrossEntropy=1.327472, SmoothL1=0.578795, accuracy=0.884740
[Epoch 186][Batch 199], Speed: 85.795074 samples/sec, CrossEntropy=1.360250, SmoothL1=0.591510, accuracy=0.882649
[Epoch 186][Batch 299], Speed: 94.355601 samples/sec, CrossEntropy=1.370553, SmoothL1=0.590118, accuracy=0.882208
[Epoch 186][Batch 399], Speed: 74.668156 samples/sec, CrossEntropy=1.372878, SmoothL1=0.586364, accuracy=0.882233
[Epoch 186][Batch 499], Speed: 92.715236 samples/sec, CrossEntropy=1.368360, SmoothL1=0.586563, accuracy=0.882430
[Epoch 186] Training cost: 194.182360, CrossEntropy=1.370254, SmoothL1=0.585721, accuracy=0.882350
[Epoch 186] Validation:
aeroplane=0.816569
bicycle=0.836017
bird=0.761634
boat=0.714414
bottle=0.486515
bus=0.853159
car=0.864074
cat=0.880081
chair=0.603965
cow=0.840683
diningtable=0.776876
dog=0.853383
horse=0.867725
motorbike=0.861652
person=0.784589
pottedplant=0.504108
sheep=0.782979
sofa=0.801143
train=0.871608
tvmonitor=0.771567
mAP=0.776637
[Epoch 187][Batch 99], Speed: 94.092004 samples/sec, CrossEntropy=1.326456, SmoothL1=0.567372, accuracy=0.885477
[Epoch 187][Batch 199], Speed: 88.590279 samples/sec, CrossEntropy=1.356463, SmoothL1=0.584156, accuracy=0.883339
[Epoch 187][Batch 299], Speed: 89.212750 samples/sec, CrossEntropy=1.354910, SmoothL1=0.586123, accuracy=0.883169
[Epoch 187][Batch 399], Speed: 93.916740 samples/sec, CrossEntropy=1.361048, SmoothL1=0.586944, accuracy=0.882485
[Epoch 187][Batch 499], Speed: 86.402054 samples/sec, CrossEntropy=1.366130, SmoothL1=0.588462, accuracy=0.882182
[Epoch 187] Training cost: 194.882833, CrossEntropy=1.364826, SmoothL1=0.587346, accuracy=0.882323
[Epoch 187] Validation:
aeroplane=0.819328
bicycle=0.834498
bird=0.750231
boat=0.717469
bottle=0.486365
bus=0.852349
car=0.859672
cat=0.879123
chair=0.601402
cow=0.843035
diningtable=0.768804
dog=0.853573
horse=0.866891
motorbike=0.853716
person=0.784681
pottedplant=0.498149
sheep=0.788115
sofa=0.791922
train=0.872701
tvmonitor=0.772786
mAP=0.774741
[Epoch 188][Batch 99], Speed: 92.069253 samples/sec, CrossEntropy=1.331256, SmoothL1=0.575492, accuracy=0.885554
[Epoch 188][Batch 199], Speed: 90.012560 samples/sec, CrossEntropy=1.346624, SmoothL1=0.585366, accuracy=0.883810
[Epoch 188][Batch 299], Speed: 85.207813 samples/sec, CrossEntropy=1.356958, SmoothL1=0.588562, accuracy=0.883144
[Epoch 188][Batch 399], Speed: 83.954135 samples/sec, CrossEntropy=1.359859, SmoothL1=0.588132, accuracy=0.883023
[Epoch 188][Batch 499], Speed: 92.476002 samples/sec, CrossEntropy=1.360383, SmoothL1=0.587937, accuracy=0.882998
[Epoch 188] Training cost: 194.476023, CrossEntropy=1.359740, SmoothL1=0.587389, accuracy=0.882934
[Epoch 188] Validation:
aeroplane=0.818527
bicycle=0.830645
bird=0.758574
boat=0.722951
bottle=0.481014
bus=0.847994
car=0.864145
cat=0.876647
chair=0.598658
cow=0.835371
diningtable=0.760336
dog=0.849560
horse=0.872104
motorbike=0.852433
person=0.780834
pottedplant=0.497589
sheep=0.785187
sofa=0.797688
train=0.866942
tvmonitor=0.772875
mAP=0.773504
[Epoch 189][Batch 99], Speed: 84.183722 samples/sec, CrossEntropy=1.334845, SmoothL1=0.577338, accuracy=0.886246
[Epoch 189][Batch 199], Speed: 90.775547 samples/sec, CrossEntropy=1.356905, SmoothL1=0.589801, accuracy=0.883778
[Epoch 189][Batch 299], Speed: 92.976123 samples/sec, CrossEntropy=1.364832, SmoothL1=0.590624, accuracy=0.883523
[Epoch 189][Batch 399], Speed: 94.143879 samples/sec, CrossEntropy=1.366833, SmoothL1=0.590794, accuracy=0.883007
[Epoch 189][Batch 499], Speed: 92.796261 samples/sec, CrossEntropy=1.364016, SmoothL1=0.587050, accuracy=0.883247
[Epoch 189] Training cost: 194.276327, CrossEntropy=1.366137, SmoothL1=0.587030, accuracy=0.883098
[Epoch 189] Validation:
aeroplane=0.818998
bicycle=0.830739
bird=0.753317
boat=0.718460
bottle=0.486730
bus=0.845657
car=0.864187
cat=0.878422
chair=0.606096
cow=0.834070
diningtable=0.777520
dog=0.846057
horse=0.870642
motorbike=0.852484
person=0.783866
pottedplant=0.501339
sheep=0.778651
sofa=0.787794
train=0.866780
tvmonitor=0.771138
mAP=0.773647
[Epoch 190][Batch 99], Speed: 87.673693 samples/sec, CrossEntropy=1.320262, SmoothL1=0.574899, accuracy=0.885652
[Epoch 190][Batch 199], Speed: 84.235499 samples/sec, CrossEntropy=1.326120, SmoothL1=0.578551, accuracy=0.885213
[Epoch 190][Batch 299], Speed: 92.391529 samples/sec, CrossEntropy=1.342976, SmoothL1=0.584598, accuracy=0.883774
[Epoch 190][Batch 399], Speed: 84.198773 samples/sec, CrossEntropy=1.341421, SmoothL1=0.580939, accuracy=0.883983
[Epoch 190][Batch 499], Speed: 92.614984 samples/sec, CrossEntropy=1.339690, SmoothL1=0.578823, accuracy=0.884200
[Epoch 190] Training cost: 194.023608, CrossEntropy=1.339283, SmoothL1=0.578955, accuracy=0.884281
[Epoch 190] Validation:
aeroplane=0.818567
bicycle=0.834861
bird=0.760213
boat=0.713865
bottle=0.482274
bus=0.848724
car=0.860067
cat=0.881843
chair=0.594595
cow=0.837019
diningtable=0.766576
dog=0.852271
horse=0.866852
motorbike=0.863165
person=0.785717
pottedplant=0.500127
sheep=0.789889
sofa=0.803607
train=0.869954
tvmonitor=0.769199
mAP=0.774969
[Epoch 191][Batch 99], Speed: 84.281148 samples/sec, CrossEntropy=1.359758, SmoothL1=0.585055, accuracy=0.883411
[Epoch 191][Batch 199], Speed: 96.171785 samples/sec, CrossEntropy=1.347265, SmoothL1=0.586452, accuracy=0.883831
[Epoch 191][Batch 299], Speed: 71.139711 samples/sec, CrossEntropy=1.349648, SmoothL1=0.590492, accuracy=0.883359
[Epoch 191][Batch 399], Speed: 87.925660 samples/sec, CrossEntropy=1.361764, SmoothL1=0.591815, accuracy=0.882506
[Epoch 191][Batch 499], Speed: 87.093912 samples/sec, CrossEntropy=1.356323, SmoothL1=0.587654, accuracy=0.882972
[Epoch 191] Training cost: 195.057792, CrossEntropy=1.354304, SmoothL1=0.586170, accuracy=0.883133
[Epoch 191] Validation:
aeroplane=0.809897
bicycle=0.834390
bird=0.753734
boat=0.725698
bottle=0.476954
bus=0.850808
car=0.859545
cat=0.875134
chair=0.597609
cow=0.840761
diningtable=0.768901
dog=0.850243
horse=0.877401
motorbike=0.844503
person=0.784643
pottedplant=0.500060
sheep=0.783275
sofa=0.802958
train=0.872799
tvmonitor=0.770931
mAP=0.774012
[Epoch 192][Batch 99], Speed: 88.778262 samples/sec, CrossEntropy=1.309198, SmoothL1=0.560700, accuracy=0.886763
[Epoch 192][Batch 199], Speed: 88.400063 samples/sec, CrossEntropy=1.337376, SmoothL1=0.573231, accuracy=0.884184
[Epoch 192][Batch 299], Speed: 79.362985 samples/sec, CrossEntropy=1.343734, SmoothL1=0.578389, accuracy=0.883932
[Epoch 192][Batch 399], Speed: 87.563929 samples/sec, CrossEntropy=1.343465, SmoothL1=0.576153, accuracy=0.883868
[Epoch 192][Batch 499], Speed: 97.802808 samples/sec, CrossEntropy=1.348829, SmoothL1=0.576239, accuracy=0.883547
[Epoch 192] Training cost: 194.032416, CrossEntropy=1.348341, SmoothL1=0.575576, accuracy=0.883513
[Epoch 192] Validation:
aeroplane=0.805445
bicycle=0.832135
bird=0.751393
boat=0.717005
bottle=0.488362
bus=0.849495
car=0.861503
cat=0.870317
chair=0.602722
cow=0.828340
diningtable=0.766617
dog=0.849757
horse=0.859387
motorbike=0.847438
person=0.783545
pottedplant=0.495638
sheep=0.766990
sofa=0.799610
train=0.866327
tvmonitor=0.768064
mAP=0.770505
[Epoch 193][Batch 99], Speed: 93.471396 samples/sec, CrossEntropy=1.307992, SmoothL1=0.569386, accuracy=0.887498
[Epoch 193][Batch 199], Speed: 96.343402 samples/sec, CrossEntropy=1.324626, SmoothL1=0.570253, accuracy=0.885646
[Epoch 193][Batch 299], Speed: 95.216214 samples/sec, CrossEntropy=1.334698, SmoothL1=0.576561, accuracy=0.885256
[Epoch 193][Batch 399], Speed: 89.944880 samples/sec, CrossEntropy=1.350266, SmoothL1=0.583303, accuracy=0.884302
[Epoch 193][Batch 499], Speed: 89.554906 samples/sec, CrossEntropy=1.345541, SmoothL1=0.576838, accuracy=0.884677
[Epoch 193] Training cost: 193.603563, CrossEntropy=1.345909, SmoothL1=0.577613, accuracy=0.884643
[Epoch 193] Validation:
aeroplane=0.815156
bicycle=0.836849
bird=0.758039
boat=0.717973
bottle=0.485509
bus=0.845649
car=0.860167
cat=0.875703
chair=0.597452
cow=0.829374
diningtable=0.767929
dog=0.844869
horse=0.868747
motorbike=0.851451
person=0.782283
pottedplant=0.493324
sheep=0.779902
sofa=0.798893
train=0.870254
tvmonitor=0.770593
mAP=0.772506
[Epoch 194][Batch 99], Speed: 89.377013 samples/sec, CrossEntropy=1.333234, SmoothL1=0.571951, accuracy=0.884714
[Epoch 194][Batch 199], Speed: 89.308799 samples/sec, CrossEntropy=1.340651, SmoothL1=0.583750, accuracy=0.884971
[Epoch 194][Batch 299], Speed: 86.992980 samples/sec, CrossEntropy=1.350085, SmoothL1=0.584330, accuracy=0.884272
[Epoch 194][Batch 399], Speed: 92.696154 samples/sec, CrossEntropy=1.352768, SmoothL1=0.581604, accuracy=0.884055
[Epoch 194][Batch 499], Speed: 98.234809 samples/sec, CrossEntropy=1.348323, SmoothL1=0.580273, accuracy=0.884536
[Epoch 194] Training cost: 193.671362, CrossEntropy=1.350749, SmoothL1=0.581201, accuracy=0.884327
[Epoch 194] Validation:
aeroplane=0.814918
bicycle=0.851288
bird=0.739442
boat=0.714050
bottle=0.489259
bus=0.848201
car=0.857556
cat=0.872455
chair=0.607571
cow=0.835339
diningtable=0.767800
dog=0.850827
horse=0.864287
motorbike=0.845782
person=0.780797
pottedplant=0.488053
sheep=0.766713
sofa=0.790145
train=0.868269
tvmonitor=0.765082
mAP=0.770892
[Epoch 195][Batch 99], Speed: 93.924035 samples/sec, CrossEntropy=1.314148, SmoothL1=0.568190, accuracy=0.886144
[Epoch 195][Batch 199], Speed: 90.116813 samples/sec, CrossEntropy=1.342094, SmoothL1=0.584580, accuracy=0.884134
[Epoch 195][Batch 299], Speed: 91.144856 samples/sec, CrossEntropy=1.343257, SmoothL1=0.585423, accuracy=0.884378
[Epoch 195][Batch 399], Speed: 80.222135 samples/sec, CrossEntropy=1.345357, SmoothL1=0.583904, accuracy=0.884192
[Epoch 195][Batch 499], Speed: 98.114454 samples/sec, CrossEntropy=1.351138, SmoothL1=0.586667, accuracy=0.883772
[Epoch 195] Training cost: 194.853769, CrossEntropy=1.349800, SmoothL1=0.586212, accuracy=0.883797
[Epoch 195] Validation:
aeroplane=0.809195
bicycle=0.834213
bird=0.755346
boat=0.721922
bottle=0.485143
bus=0.847993
car=0.859061
cat=0.875384
chair=0.604775
cow=0.828725
diningtable=0.766058
dog=0.852441
horse=0.864551
motorbike=0.845437
person=0.781335
pottedplant=0.491685
sheep=0.778284
sofa=0.793647
train=0.873855
tvmonitor=0.767477
mAP=0.771826
[Epoch 196][Batch 99], Speed: 93.700636 samples/sec, CrossEntropy=1.347153, SmoothL1=0.571334, accuracy=0.884529
[Epoch 196][Batch 199], Speed: 87.722056 samples/sec, CrossEntropy=1.356698, SmoothL1=0.584310, accuracy=0.883646
[Epoch 196][Batch 299], Speed: 85.602572 samples/sec, CrossEntropy=1.359907, SmoothL1=0.585210, accuracy=0.883428
[Epoch 196][Batch 399], Speed: 73.634703 samples/sec, CrossEntropy=1.351124, SmoothL1=0.576300, accuracy=0.883817
[Epoch 196][Batch 499], Speed: 93.234985 samples/sec, CrossEntropy=1.346385, SmoothL1=0.576156, accuracy=0.884298
[Epoch 196] Training cost: 194.728095, CrossEntropy=1.346157, SmoothL1=0.576347, accuracy=0.884310
[Epoch 196] Validation:
aeroplane=0.816829
bicycle=0.826181
bird=0.756438
boat=0.717794
bottle=0.487676
bus=0.849677
car=0.863555
cat=0.876428
chair=0.604330
cow=0.832218
diningtable=0.767932
dog=0.847977
horse=0.871593
motorbike=0.848750
person=0.786480
pottedplant=0.499413
sheep=0.776786
sofa=0.803045
train=0.872618
tvmonitor=0.765332
mAP=0.773553
[Epoch 197][Batch 99], Speed: 82.259804 samples/sec, CrossEntropy=1.326780, SmoothL1=0.584021, accuracy=0.885449
[Epoch 197][Batch 199], Speed: 89.056004 samples/sec, CrossEntropy=1.348528, SmoothL1=0.585996, accuracy=0.883641
[Epoch 197][Batch 299], Speed: 90.236957 samples/sec, CrossEntropy=1.348991, SmoothL1=0.581470, accuracy=0.883695
[Epoch 197][Batch 399], Speed: 89.681225 samples/sec, CrossEntropy=1.350780, SmoothL1=0.581249, accuracy=0.883735
[Epoch 197][Batch 499], Speed: 96.887960 samples/sec, CrossEntropy=1.352770, SmoothL1=0.582400, accuracy=0.883486
[Epoch 197] Training cost: 194.571537, CrossEntropy=1.352836, SmoothL1=0.582263, accuracy=0.883377
[Epoch 197] Validation:
aeroplane=0.809553
bicycle=0.839268
bird=0.755565
boat=0.722884
bottle=0.482397
bus=0.852360
car=0.862473
cat=0.875397
chair=0.603895
cow=0.829732
diningtable=0.770673
dog=0.848780
horse=0.866202
motorbike=0.845357
person=0.785171
pottedplant=0.489821
sheep=0.769057
sofa=0.794034
train=0.872474
tvmonitor=0.765299
mAP=0.772020
[Epoch 198][Batch 99], Speed: 89.905838 samples/sec, CrossEntropy=1.339724, SmoothL1=0.587359, accuracy=0.884957
[Epoch 198][Batch 199], Speed: 83.706477 samples/sec, CrossEntropy=1.360794, SmoothL1=0.590211, accuracy=0.883195
[Epoch 198][Batch 299], Speed: 92.205177 samples/sec, CrossEntropy=1.355029, SmoothL1=0.584608, accuracy=0.883298
[Epoch 198][Batch 399], Speed: 89.951209 samples/sec, CrossEntropy=1.350810, SmoothL1=0.582494, accuracy=0.883595
[Epoch 198][Batch 499], Speed: 93.208244 samples/sec, CrossEntropy=1.351821, SmoothL1=0.581976, accuracy=0.883764
[Epoch 198] Training cost: 193.797566, CrossEntropy=1.352169, SmoothL1=0.582571, accuracy=0.883799
[Epoch 198] Validation:
aeroplane=0.811177
bicycle=0.834338
bird=0.745402
boat=0.713302
bottle=0.472682
bus=0.843697
car=0.862632
cat=0.878348
chair=0.603936
cow=0.820896
diningtable=0.758891
dog=0.846069
horse=0.873997
motorbike=0.848082
person=0.785519
pottedplant=0.500664
sheep=0.776464
sofa=0.803708
train=0.875040
tvmonitor=0.762675
mAP=0.770876
[Epoch 199][Batch 99], Speed: 88.838375 samples/sec, CrossEntropy=1.345844, SmoothL1=0.579611, accuracy=0.884170
[Epoch 199][Batch 199], Speed: 90.419511 samples/sec, CrossEntropy=1.358975, SmoothL1=0.589678, accuracy=0.883386
[Epoch 199][Batch 299], Speed: 84.984881 samples/sec, CrossEntropy=1.348140, SmoothL1=0.584600, accuracy=0.884140
[Epoch 199][Batch 399], Speed: 93.165995 samples/sec, CrossEntropy=1.350587, SmoothL1=0.585152, accuracy=0.884053
[Epoch 199][Batch 499], Speed: 92.231979 samples/sec, CrossEntropy=1.348822, SmoothL1=0.582941, accuracy=0.884115
[Epoch 199] Training cost: 194.579072, CrossEntropy=1.349857, SmoothL1=0.583121, accuracy=0.884094
[Epoch 199] Validation:
aeroplane=0.803249
bicycle=0.833874
bird=0.753322
boat=0.712049
bottle=0.479490
bus=0.840865
car=0.860978
cat=0.880208
chair=0.601748
cow=0.841761
diningtable=0.764492
dog=0.848199
horse=0.863543
motorbike=0.855016
person=0.783345
pottedplant=0.495289
sheep=0.779504
sofa=0.797289
train=0.873957
tvmonitor=0.768756
mAP=0.771847
[Epoch 200] Set learning rate to 0.0001
[Epoch 200] Set learning rate to 1e-05
[Epoch 200][Batch 99], Speed: 89.198521 samples/sec, CrossEntropy=1.323460, SmoothL1=0.577564, accuracy=0.885249
[Epoch 200][Batch 199], Speed: 72.387350 samples/sec, CrossEntropy=1.332237, SmoothL1=0.577082, accuracy=0.885101
[Epoch 200][Batch 299], Speed: 69.140025 samples/sec, CrossEntropy=1.344505, SmoothL1=0.585191, accuracy=0.884418
[Epoch 200][Batch 399], Speed: 93.215818 samples/sec, CrossEntropy=1.350174, SmoothL1=0.587377, accuracy=0.884003
[Epoch 200][Batch 499], Speed: 79.223715 samples/sec, CrossEntropy=1.340852, SmoothL1=0.580532, accuracy=0.884754
[Epoch 200] Training cost: 200.528353, CrossEntropy=1.339229, SmoothL1=0.580137, accuracy=0.884827
[Epoch 200] Validation:
aeroplane=0.805433
bicycle=0.828694
bird=0.757924
boat=0.718303
bottle=0.480956
bus=0.843721
car=0.862622
cat=0.882060
chair=0.607238
cow=0.841265
diningtable=0.763313
dog=0.848044
horse=0.865849
motorbike=0.851879
person=0.785341
pottedplant=0.495945
sheep=0.780146
sofa=0.799079
train=0.876394
tvmonitor=0.765506
mAP=0.772986
[Epoch 201][Batch 99], Speed: 89.939033 samples/sec, CrossEntropy=1.343042, SmoothL1=0.568781, accuracy=0.884653
[Epoch 201][Batch 199], Speed: 89.896083 samples/sec, CrossEntropy=1.334320, SmoothL1=0.571592, accuracy=0.884962
[Epoch 201][Batch 299], Speed: 87.381220 samples/sec, CrossEntropy=1.337712, SmoothL1=0.576472, accuracy=0.885158
[Epoch 201][Batch 399], Speed: 91.975624 samples/sec, CrossEntropy=1.337719, SmoothL1=0.575956, accuracy=0.884965
[Epoch 201][Batch 499], Speed: 89.536087 samples/sec, CrossEntropy=1.338060, SmoothL1=0.575781, accuracy=0.884970
[Epoch 201] Training cost: 190.248801, CrossEntropy=1.338519, SmoothL1=0.576255, accuracy=0.884913
[Epoch 201] Validation:
aeroplane=0.806742
bicycle=0.827373
bird=0.753152
boat=0.716360
bottle=0.480541
bus=0.843524
car=0.863192
cat=0.879191
chair=0.610481
cow=0.838425
diningtable=0.770262
dog=0.849583
horse=0.869035
motorbike=0.853016
person=0.784597
pottedplant=0.495054
sheep=0.773836
sofa=0.799545
train=0.876108
tvmonitor=0.764799
mAP=0.772741
[Epoch 202][Batch 99], Speed: 92.557631 samples/sec, CrossEntropy=1.330773, SmoothL1=0.564367, accuracy=0.886227
[Epoch 202][Batch 199], Speed: 91.771425 samples/sec, CrossEntropy=1.336276, SmoothL1=0.574849, accuracy=0.885499
[Epoch 202][Batch 299], Speed: 82.924467 samples/sec, CrossEntropy=1.349433, SmoothL1=0.580602, accuracy=0.884586
[Epoch 202][Batch 399], Speed: 90.398257 samples/sec, CrossEntropy=1.353455, SmoothL1=0.582983, accuracy=0.884143
[Epoch 202][Batch 499], Speed: 87.864876 samples/sec, CrossEntropy=1.351439, SmoothL1=0.581934, accuracy=0.884082
[Epoch 202] Training cost: 190.780574, CrossEntropy=1.350795, SmoothL1=0.581196, accuracy=0.884151
[Epoch 202] Validation:
aeroplane=0.808625
bicycle=0.833366
bird=0.755607
boat=0.718439
bottle=0.480507
bus=0.844238
car=0.863318
cat=0.879262
chair=0.609971
cow=0.836534
diningtable=0.766167
dog=0.848855
horse=0.867424
motorbike=0.850602
person=0.786686
pottedplant=0.493376
sheep=0.781644
sofa=0.801041
train=0.873950
tvmonitor=0.766073
mAP=0.773284
[Epoch 203][Batch 99], Speed: 88.726088 samples/sec, CrossEntropy=1.345051, SmoothL1=0.582915, accuracy=0.884629
[Epoch 203][Batch 199], Speed: 90.289890 samples/sec, CrossEntropy=1.360722, SmoothL1=0.587523, accuracy=0.883825
[Epoch 203][Batch 299], Speed: 91.598690 samples/sec, CrossEntropy=1.355064, SmoothL1=0.586789, accuracy=0.883931
[Epoch 203][Batch 399], Speed: 91.420127 samples/sec, CrossEntropy=1.355075, SmoothL1=0.586043, accuracy=0.884022
[Epoch 203][Batch 499], Speed: 81.467760 samples/sec, CrossEntropy=1.349359, SmoothL1=0.581134, accuracy=0.884403
[Epoch 203] Training cost: 191.149424, CrossEntropy=1.347986, SmoothL1=0.580049, accuracy=0.884574
[Epoch 203] Validation:
aeroplane=0.809735
bicycle=0.831039
bird=0.753830
boat=0.716022
bottle=0.481203
bus=0.845643
car=0.863025
cat=0.882683
chair=0.608284
cow=0.833064
diningtable=0.764634
dog=0.850015
horse=0.865871
motorbike=0.850420
person=0.786334
pottedplant=0.497455
sheep=0.781507
sofa=0.795555
train=0.875516
tvmonitor=0.764921
mAP=0.772838
[Epoch 204][Batch 99], Speed: 90.136603 samples/sec, CrossEntropy=1.323610, SmoothL1=0.568693, accuracy=0.886318
[Epoch 204][Batch 199], Speed: 86.068398 samples/sec, CrossEntropy=1.312885, SmoothL1=0.558293, accuracy=0.887151
[Epoch 204][Batch 299], Speed: 83.463857 samples/sec, CrossEntropy=1.324778, SmoothL1=0.564461, accuracy=0.886126
[Epoch 204][Batch 399], Speed: 89.466855 samples/sec, CrossEntropy=1.333459, SmoothL1=0.573317, accuracy=0.885612
[Epoch 204][Batch 499], Speed: 86.860397 samples/sec, CrossEntropy=1.337634, SmoothL1=0.575298, accuracy=0.885451
[Epoch 204] Training cost: 192.274545, CrossEntropy=1.334794, SmoothL1=0.573997, accuracy=0.885607
[Epoch 204] Validation:
aeroplane=0.810542
bicycle=0.832615
bird=0.754756
boat=0.714396
bottle=0.480008
bus=0.845473
car=0.862164
cat=0.878851
chair=0.607339
cow=0.836427
diningtable=0.769470
dog=0.849641
horse=0.868245
motorbike=0.848824
person=0.785073
pottedplant=0.503351
sheep=0.781991
sofa=0.797558
train=0.875846
tvmonitor=0.765589
mAP=0.773408
[Epoch 205][Batch 99], Speed: 86.655257 samples/sec, CrossEntropy=1.308364, SmoothL1=0.562267, accuracy=0.887173
[Epoch 205][Batch 199], Speed: 88.919891 samples/sec, CrossEntropy=1.306394, SmoothL1=0.555492, accuracy=0.887806
[Epoch 205][Batch 299], Speed: 94.974535 samples/sec, CrossEntropy=1.314679, SmoothL1=0.559494, accuracy=0.887130
[Epoch 205][Batch 399], Speed: 90.528923 samples/sec, CrossEntropy=1.322192, SmoothL1=0.568230, accuracy=0.886407
[Epoch 205][Batch 499], Speed: 88.474069 samples/sec, CrossEntropy=1.323313, SmoothL1=0.568970, accuracy=0.886272
[Epoch 205] Training cost: 191.347872, CrossEntropy=1.321452, SmoothL1=0.567586, accuracy=0.886468
[Epoch 205] Validation:
aeroplane=0.809512
bicycle=0.831637
bird=0.756216
boat=0.717122
bottle=0.482527
bus=0.845565
car=0.862714
cat=0.881419
chair=0.607881
cow=0.838337
diningtable=0.770229
dog=0.849587
horse=0.869021
motorbike=0.847563
person=0.783328
pottedplant=0.497750
sheep=0.784464
sofa=0.798727
train=0.875894
tvmonitor=0.766160
mAP=0.773783
[Epoch 206][Batch 99], Speed: 92.293689 samples/sec, CrossEntropy=1.338395, SmoothL1=0.573929, accuracy=0.885102
[Epoch 206][Batch 199], Speed: 88.665423 samples/sec, CrossEntropy=1.321018, SmoothL1=0.566429, accuracy=0.886790
[Epoch 206][Batch 299], Speed: 86.191321 samples/sec, CrossEntropy=1.323643, SmoothL1=0.565362, accuracy=0.886511
[Epoch 206][Batch 399], Speed: 84.923043 samples/sec, CrossEntropy=1.329749, SmoothL1=0.572793, accuracy=0.885801
[Epoch 206][Batch 499], Speed: 81.203473 samples/sec, CrossEntropy=1.328518, SmoothL1=0.571668, accuracy=0.885897
[Epoch 206] Training cost: 191.195163, CrossEntropy=1.326555, SmoothL1=0.571275, accuracy=0.886019
[Epoch 206] Validation:
aeroplane=0.808550
bicycle=0.831283
bird=0.755792
boat=0.718171
bottle=0.479501
bus=0.844890
car=0.861247
cat=0.879913
chair=0.606442
cow=0.836777
diningtable=0.770077
dog=0.848679
horse=0.866466
motorbike=0.850069
person=0.785107
pottedplant=0.498447
sheep=0.780015
sofa=0.798054
train=0.874350
tvmonitor=0.765739
mAP=0.772979
[Epoch 207][Batch 99], Speed: 82.598321 samples/sec, CrossEntropy=1.338799, SmoothL1=0.582179, accuracy=0.885978
[Epoch 207][Batch 199], Speed: 88.357465 samples/sec, CrossEntropy=1.340240, SmoothL1=0.586308, accuracy=0.885923
[Epoch 207][Batch 299], Speed: 89.355651 samples/sec, CrossEntropy=1.335736, SmoothL1=0.581638, accuracy=0.885798
[Epoch 207][Batch 399], Speed: 86.763539 samples/sec, CrossEntropy=1.339922, SmoothL1=0.582663, accuracy=0.885035
[Epoch 207][Batch 499], Speed: 81.986103 samples/sec, CrossEntropy=1.334838, SmoothL1=0.578058, accuracy=0.885489
[Epoch 207] Training cost: 192.381054, CrossEntropy=1.333750, SmoothL1=0.576975, accuracy=0.885538
[Epoch 207] Validation:
aeroplane=0.812195
bicycle=0.832083
bird=0.753185
boat=0.720638
bottle=0.479734
bus=0.845337
car=0.862285
cat=0.881505
chair=0.608963
cow=0.835089
diningtable=0.766862
dog=0.848138
horse=0.868056
motorbike=0.849135
person=0.784943
pottedplant=0.495088
sheep=0.784961
sofa=0.798345
train=0.876423
tvmonitor=0.766246
mAP=0.773461
[Epoch 208][Batch 99], Speed: 91.263043 samples/sec, CrossEntropy=1.323285, SmoothL1=0.574552, accuracy=0.886613
[Epoch 208][Batch 199], Speed: 90.096245 samples/sec, CrossEntropy=1.335094, SmoothL1=0.572884, accuracy=0.885230
[Epoch 208][Batch 299], Speed: 90.245391 samples/sec, CrossEntropy=1.351111, SmoothL1=0.587410, accuracy=0.883787
[Epoch 208][Batch 399], Speed: 90.240779 samples/sec, CrossEntropy=1.345590, SmoothL1=0.583998, accuracy=0.884291
[Epoch 208][Batch 499], Speed: 85.948302 samples/sec, CrossEntropy=1.339944, SmoothL1=0.577099, accuracy=0.884644
[Epoch 208] Training cost: 191.370203, CrossEntropy=1.339007, SmoothL1=0.576228, accuracy=0.884749
[Epoch 208] Validation:
aeroplane=0.812331
bicycle=0.831343
bird=0.757464
boat=0.720212
bottle=0.478669
bus=0.846469
car=0.862938
cat=0.881820
chair=0.606206
cow=0.842295
diningtable=0.772082
dog=0.848086
horse=0.867984
motorbike=0.852743
person=0.784549
pottedplant=0.499708
sheep=0.780341
sofa=0.796218
train=0.876702
tvmonitor=0.765687
mAP=0.774192
[Epoch 209][Batch 99], Speed: 85.330241 samples/sec, CrossEntropy=1.311205, SmoothL1=0.568661, accuracy=0.886418
[Epoch 209][Batch 199], Speed: 93.538362 samples/sec, CrossEntropy=1.330958, SmoothL1=0.574457, accuracy=0.885633
[Epoch 209][Batch 299], Speed: 93.660227 samples/sec, CrossEntropy=1.337167, SmoothL1=0.583975, accuracy=0.884824
[Epoch 209][Batch 399], Speed: 87.879431 samples/sec, CrossEntropy=1.331919, SmoothL1=0.579711, accuracy=0.885490
[Epoch 209][Batch 499], Speed: 91.278249 samples/sec, CrossEntropy=1.328519, SmoothL1=0.575115, accuracy=0.885642
[Epoch 209] Training cost: 191.464335, CrossEntropy=1.329679, SmoothL1=0.575508, accuracy=0.885616
[Epoch 209] Validation:
aeroplane=0.810484
bicycle=0.835593
bird=0.758226
boat=0.718261
bottle=0.482024
bus=0.844611
car=0.862881
cat=0.882039
chair=0.606255
cow=0.837311
diningtable=0.769185
dog=0.848978
horse=0.868085
motorbike=0.853968
person=0.785083
pottedplant=0.505951
sheep=0.786162
sofa=0.794550
train=0.874580
tvmonitor=0.765118
mAP=0.774467
[Epoch 210][Batch 99], Speed: 82.888568 samples/sec, CrossEntropy=1.353798, SmoothL1=0.584422, accuracy=0.883467
[Epoch 210][Batch 199], Speed: 91.907729 samples/sec, CrossEntropy=1.325431, SmoothL1=0.578075, accuracy=0.885751
[Epoch 210][Batch 299], Speed: 94.143483 samples/sec, CrossEntropy=1.327244, SmoothL1=0.573661, accuracy=0.885355
[Epoch 210][Batch 399], Speed: 85.833261 samples/sec, CrossEntropy=1.328966, SmoothL1=0.572424, accuracy=0.885385
[Epoch 210][Batch 499], Speed: 92.612109 samples/sec, CrossEntropy=1.327101, SmoothL1=0.571987, accuracy=0.885576
[Epoch 210] Training cost: 191.789860, CrossEntropy=1.326282, SmoothL1=0.571463, accuracy=0.885702
[Epoch 210] Validation:
aeroplane=0.812148
bicycle=0.834423
bird=0.755470
boat=0.719981
bottle=0.482746
bus=0.846550
car=0.863743
cat=0.876326
chair=0.604966
cow=0.837031
diningtable=0.767497
dog=0.849897
horse=0.866517
motorbike=0.852765
person=0.786007
pottedplant=0.504858
sheep=0.773701
sofa=0.799903
train=0.876213
tvmonitor=0.765727
mAP=0.773823
[Epoch 211][Batch 99], Speed: 88.608059 samples/sec, CrossEntropy=1.340043, SmoothL1=0.592114, accuracy=0.885999
[Epoch 211][Batch 199], Speed: 88.056202 samples/sec, CrossEntropy=1.334027, SmoothL1=0.579057, accuracy=0.885833
[Epoch 211][Batch 299], Speed: 90.015216 samples/sec, CrossEntropy=1.338838, SmoothL1=0.576886, accuracy=0.885353
[Epoch 211][Batch 399], Speed: 91.319362 samples/sec, CrossEntropy=1.341695, SmoothL1=0.578747, accuracy=0.885231
[Epoch 211][Batch 499], Speed: 86.277254 samples/sec, CrossEntropy=1.335024, SmoothL1=0.575899, accuracy=0.885554
[Epoch 211] Training cost: 190.200181, CrossEntropy=1.336714, SmoothL1=0.577518, accuracy=0.885381
[Epoch 211] Validation:
aeroplane=0.813714
bicycle=0.835280
bird=0.758036
boat=0.720731
bottle=0.482040
bus=0.845851
car=0.863728
cat=0.881621
chair=0.605359
cow=0.836019
diningtable=0.767520
dog=0.847857
horse=0.863986
motorbike=0.851726
person=0.784828
pottedplant=0.502049
sheep=0.776013
sofa=0.797412
train=0.875087
tvmonitor=0.766290
mAP=0.773757
[Epoch 212][Batch 99], Speed: 85.526423 samples/sec, CrossEntropy=1.336646, SmoothL1=0.577854, accuracy=0.885634
[Epoch 212][Batch 199], Speed: 88.625202 samples/sec, CrossEntropy=1.333892, SmoothL1=0.570239, accuracy=0.885108
[Epoch 212][Batch 299], Speed: 84.403261 samples/sec, CrossEntropy=1.340443, SmoothL1=0.576929, accuracy=0.884671
[Epoch 212][Batch 399], Speed: 89.470254 samples/sec, CrossEntropy=1.340643, SmoothL1=0.575446, accuracy=0.884849
[Epoch 212][Batch 499], Speed: 83.423289 samples/sec, CrossEntropy=1.332726, SmoothL1=0.573412, accuracy=0.885357
[Epoch 212] Training cost: 189.990647, CrossEntropy=1.330121, SmoothL1=0.571824, accuracy=0.885558
[Epoch 212] Validation:
aeroplane=0.813387
bicycle=0.832688
bird=0.756948
boat=0.720030
bottle=0.481077
bus=0.847527
car=0.863516
cat=0.880585
chair=0.604829
cow=0.835941
diningtable=0.771578
dog=0.848100
horse=0.865021
motorbike=0.853459
person=0.785099
pottedplant=0.500701
sheep=0.784389
sofa=0.797684
train=0.874893
tvmonitor=0.766413
mAP=0.774193
[Epoch 213][Batch 99], Speed: 87.602507 samples/sec, CrossEntropy=1.355457, SmoothL1=0.587927, accuracy=0.884195
[Epoch 213][Batch 199], Speed: 85.601316 samples/sec, CrossEntropy=1.350040, SmoothL1=0.593490, accuracy=0.884327
[Epoch 213][Batch 299], Speed: 90.343190 samples/sec, CrossEntropy=1.345536, SmoothL1=0.585972, accuracy=0.884736
[Epoch 213][Batch 399], Speed: 86.361414 samples/sec, CrossEntropy=1.336788, SmoothL1=0.580629, accuracy=0.885428
[Epoch 213][Batch 499], Speed: 89.469061 samples/sec, CrossEntropy=1.329264, SmoothL1=0.574202, accuracy=0.886015
[Epoch 213] Training cost: 190.864789, CrossEntropy=1.330696, SmoothL1=0.574282, accuracy=0.885819
[Epoch 213] Validation:
aeroplane=0.812690
bicycle=0.830540
bird=0.753174
boat=0.716989
bottle=0.480692
bus=0.847509
car=0.862159
cat=0.879706
chair=0.607440
cow=0.839669
diningtable=0.768809
dog=0.848094
horse=0.864652
motorbike=0.852946
person=0.784537
pottedplant=0.501212
sheep=0.783783
sofa=0.795174
train=0.874531
tvmonitor=0.765534
mAP=0.773492
[Epoch 214][Batch 99], Speed: 92.735030 samples/sec, CrossEntropy=1.331143, SmoothL1=0.564790, accuracy=0.885498
[Epoch 214][Batch 199], Speed: 93.226113 samples/sec, CrossEntropy=1.329501, SmoothL1=0.569681, accuracy=0.885905
[Epoch 214][Batch 299], Speed: 92.626042 samples/sec, CrossEntropy=1.338035, SmoothL1=0.574281, accuracy=0.885235
[Epoch 214][Batch 399], Speed: 85.541032 samples/sec, CrossEntropy=1.333140, SmoothL1=0.569939, accuracy=0.885604
[Epoch 214][Batch 499], Speed: 85.753031 samples/sec, CrossEntropy=1.333835, SmoothL1=0.571882, accuracy=0.885372
[Epoch 214] Training cost: 191.249453, CrossEntropy=1.335783, SmoothL1=0.574251, accuracy=0.885179
[Epoch 214] Validation:
aeroplane=0.811273
bicycle=0.829509
bird=0.754260
boat=0.719721
bottle=0.477819
bus=0.847196
car=0.863237
cat=0.877727
chair=0.607900
cow=0.839310
diningtable=0.768359
dog=0.849737
horse=0.863038
motorbike=0.852399
person=0.785970
pottedplant=0.498938
sheep=0.774691
sofa=0.797889
train=0.873243
tvmonitor=0.764924
mAP=0.772857
[Epoch 215][Batch 99], Speed: 88.171258 samples/sec, CrossEntropy=1.317265, SmoothL1=0.571184, accuracy=0.887024
[Epoch 215][Batch 199], Speed: 87.758937 samples/sec, CrossEntropy=1.323761, SmoothL1=0.574377, accuracy=0.886559
[Epoch 215][Batch 299], Speed: 87.937239 samples/sec, CrossEntropy=1.339535, SmoothL1=0.581843, accuracy=0.885550
[Epoch 215][Batch 399], Speed: 86.617006 samples/sec, CrossEntropy=1.339941, SmoothL1=0.584353, accuracy=0.885371
[Epoch 215][Batch 499], Speed: 81.277233 samples/sec, CrossEntropy=1.338537, SmoothL1=0.584213, accuracy=0.885278
[Epoch 215] Training cost: 191.796728, CrossEntropy=1.336696, SmoothL1=0.583146, accuracy=0.885330
[Epoch 215] Validation:
aeroplane=0.808933
bicycle=0.828656
bird=0.754979
boat=0.717539
bottle=0.485531
bus=0.848084
car=0.862758
cat=0.881850
chair=0.608658
cow=0.840302
diningtable=0.769640
dog=0.849709
horse=0.866019
motorbike=0.852901
person=0.784201
pottedplant=0.502717
sheep=0.783510
sofa=0.794788
train=0.874830
tvmonitor=0.764827
mAP=0.774022
[Epoch 216][Batch 99], Speed: 81.806059 samples/sec, CrossEntropy=1.306021, SmoothL1=0.577288, accuracy=0.887363
[Epoch 216][Batch 199], Speed: 84.959382 samples/sec, CrossEntropy=1.304302, SmoothL1=0.571121, accuracy=0.887445
[Epoch 216][Batch 299], Speed: 82.992151 samples/sec, CrossEntropy=1.321262, SmoothL1=0.578851, accuracy=0.886071
[Epoch 216][Batch 399], Speed: 87.498682 samples/sec, CrossEntropy=1.322580, SmoothL1=0.577571, accuracy=0.885887
[Epoch 216][Batch 499], Speed: 89.460057 samples/sec, CrossEntropy=1.324454, SmoothL1=0.578131, accuracy=0.885718
[Epoch 216] Training cost: 191.961976, CrossEntropy=1.325671, SmoothL1=0.578249, accuracy=0.885697
[Epoch 216] Validation:
aeroplane=0.810245
bicycle=0.829057
bird=0.752749
boat=0.718010
bottle=0.479058
bus=0.849434
car=0.862357
cat=0.883079
chair=0.607467
cow=0.838984
diningtable=0.772965
dog=0.847882
horse=0.863089
motorbike=0.854337
person=0.785105
pottedplant=0.498369
sheep=0.777350
sofa=0.796070
train=0.875516
tvmonitor=0.766607
mAP=0.773387
[Epoch 217][Batch 99], Speed: 88.917122 samples/sec, CrossEntropy=1.328273, SmoothL1=0.577955, accuracy=0.885716
[Epoch 217][Batch 199], Speed: 89.504561 samples/sec, CrossEntropy=1.315882, SmoothL1=0.570315, accuracy=0.887272
[Epoch 217][Batch 299], Speed: 92.113989 samples/sec, CrossEntropy=1.331506, SmoothL1=0.577440, accuracy=0.885791
[Epoch 217][Batch 399], Speed: 90.491508 samples/sec, CrossEntropy=1.335134, SmoothL1=0.578827, accuracy=0.885705
[Epoch 217][Batch 499], Speed: 83.311232 samples/sec, CrossEntropy=1.337240, SmoothL1=0.580053, accuracy=0.885610
[Epoch 217] Training cost: 192.287199, CrossEntropy=1.337634, SmoothL1=0.580361, accuracy=0.885654
[Epoch 217] Validation:
aeroplane=0.812225
bicycle=0.832050
bird=0.755681
boat=0.718765
bottle=0.479197
bus=0.846992
car=0.862681
cat=0.883091
chair=0.605305
cow=0.838878
diningtable=0.769936
dog=0.847091
horse=0.867780
motorbike=0.853398
person=0.786335
pottedplant=0.505707
sheep=0.771775
sofa=0.796533
train=0.874730
tvmonitor=0.771499
mAP=0.773983
[Epoch 218][Batch 99], Speed: 88.254571 samples/sec, CrossEntropy=1.320100, SmoothL1=0.569651, accuracy=0.886751
[Epoch 218][Batch 199], Speed: 82.042383 samples/sec, CrossEntropy=1.318334, SmoothL1=0.558748, accuracy=0.886891
[Epoch 218][Batch 299], Speed: 92.556673 samples/sec, CrossEntropy=1.330408, SmoothL1=0.567909, accuracy=0.885800
[Epoch 218][Batch 399], Speed: 85.373174 samples/sec, CrossEntropy=1.338132, SmoothL1=0.572965, accuracy=0.885498
[Epoch 218][Batch 499], Speed: 90.256921 samples/sec, CrossEntropy=1.334620, SmoothL1=0.570434, accuracy=0.885918
[Epoch 218] Training cost: 191.083295, CrossEntropy=1.332714, SmoothL1=0.569767, accuracy=0.886090
[Epoch 218] Validation:
aeroplane=0.808708
bicycle=0.830613
bird=0.750675
boat=0.717900
bottle=0.482160
bus=0.849080
car=0.862406
cat=0.883544
chair=0.606732
cow=0.839200
diningtable=0.767998
dog=0.846664
horse=0.869780
motorbike=0.853636
person=0.784234
pottedplant=0.503981
sheep=0.774854
sofa=0.796073
train=0.872845
tvmonitor=0.768943
mAP=0.773501
[Epoch 219][Batch 99], Speed: 89.278561 samples/sec, CrossEntropy=1.346268, SmoothL1=0.590045, accuracy=0.884893
[Epoch 219][Batch 199], Speed: 76.140368 samples/sec, CrossEntropy=1.336337, SmoothL1=0.584050, accuracy=0.885758
[Epoch 219][Batch 299], Speed: 77.966521 samples/sec, CrossEntropy=1.335816, SmoothL1=0.582336, accuracy=0.885364
[Epoch 219][Batch 399], Speed: 86.673388 samples/sec, CrossEntropy=1.335330, SmoothL1=0.578625, accuracy=0.885226
[Epoch 219][Batch 499], Speed: 88.494019 samples/sec, CrossEntropy=1.336705, SmoothL1=0.577848, accuracy=0.884963
[Epoch 219] Training cost: 191.718783, CrossEntropy=1.335122, SmoothL1=0.577065, accuracy=0.885195
[Epoch 219] Validation:
aeroplane=0.813484
bicycle=0.831023
bird=0.755027
boat=0.718982
bottle=0.483750
bus=0.848297
car=0.860969
cat=0.882112
chair=0.606864
cow=0.839631
diningtable=0.770269
dog=0.847359
horse=0.864980
motorbike=0.854595
person=0.786144
pottedplant=0.503667
sheep=0.776767
sofa=0.795585
train=0.873550
tvmonitor=0.768492
mAP=0.774077
[Epoch 220][Batch 99], Speed: 91.594877 samples/sec, CrossEntropy=1.343467, SmoothL1=0.588982, accuracy=0.884889
[Epoch 220][Batch 199], Speed: 87.608397 samples/sec, CrossEntropy=1.338849, SmoothL1=0.580714, accuracy=0.885495
[Epoch 220][Batch 299], Speed: 78.449207 samples/sec, CrossEntropy=1.339666, SmoothL1=0.583299, accuracy=0.885219
[Epoch 220][Batch 399], Speed: 90.619077 samples/sec, CrossEntropy=1.339078, SmoothL1=0.584021, accuracy=0.885080
[Epoch 220][Batch 499], Speed: 88.523611 samples/sec, CrossEntropy=1.335950, SmoothL1=0.577657, accuracy=0.885493
[Epoch 220] Training cost: 190.808184, CrossEntropy=1.336518, SmoothL1=0.577992, accuracy=0.885420
[Epoch 220] Validation:
aeroplane=0.812077
bicycle=0.830993
bird=0.752804
boat=0.718264
bottle=0.481542
bus=0.851726
car=0.862149
cat=0.882512
chair=0.605724
cow=0.833431
diningtable=0.767347
dog=0.847542
horse=0.865012
motorbike=0.851486
person=0.786810
pottedplant=0.501537
sheep=0.781113
sofa=0.798495
train=0.872407
tvmonitor=0.768011
mAP=0.773549
[Epoch 221][Batch 99], Speed: 90.763208 samples/sec, CrossEntropy=1.353757, SmoothL1=0.591357, accuracy=0.883488
[Epoch 221][Batch 199], Speed: 92.314701 samples/sec, CrossEntropy=1.329088, SmoothL1=0.581449, accuracy=0.885562
[Epoch 221][Batch 299], Speed: 86.004864 samples/sec, CrossEntropy=1.337694, SmoothL1=0.585990, accuracy=0.885345
[Epoch 221][Batch 399], Speed: 92.349445 samples/sec, CrossEntropy=1.338515, SmoothL1=0.586843, accuracy=0.885509
[Epoch 221][Batch 499], Speed: 91.979027 samples/sec, CrossEntropy=1.336061, SmoothL1=0.585274, accuracy=0.885479
[Epoch 221] Training cost: 191.355473, CrossEntropy=1.338775, SmoothL1=0.586021, accuracy=0.885293
[Epoch 221] Validation:
aeroplane=0.810746
bicycle=0.831258
bird=0.758240
boat=0.718683
bottle=0.483329
bus=0.852274
car=0.863316
cat=0.882118
chair=0.607429
cow=0.835515
diningtable=0.766872
dog=0.847838
horse=0.866420
motorbike=0.853880
person=0.786149
pottedplant=0.501554
sheep=0.775441
sofa=0.798084
train=0.875289
tvmonitor=0.766119
mAP=0.774028
[Epoch 222][Batch 99], Speed: 89.174815 samples/sec, CrossEntropy=1.350039, SmoothL1=0.588774, accuracy=0.883737
[Epoch 222][Batch 199], Speed: 87.024849 samples/sec, CrossEntropy=1.336727, SmoothL1=0.575698, accuracy=0.884494
[Epoch 222][Batch 299], Speed: 80.337473 samples/sec, CrossEntropy=1.336320, SmoothL1=0.579951, accuracy=0.885282
[Epoch 222][Batch 399], Speed: 93.330873 samples/sec, CrossEntropy=1.336339, SmoothL1=0.580200, accuracy=0.885089
[Epoch 222][Batch 499], Speed: 89.869899 samples/sec, CrossEntropy=1.333111, SmoothL1=0.575964, accuracy=0.885079
[Epoch 222] Training cost: 192.209622, CrossEntropy=1.333825, SmoothL1=0.575858, accuracy=0.885114
[Epoch 222] Validation:
aeroplane=0.813053
bicycle=0.830851
bird=0.752930
boat=0.719564
bottle=0.483867
bus=0.852396
car=0.862645
cat=0.881297
chair=0.607583
cow=0.834699
diningtable=0.769039
dog=0.847386
horse=0.867036
motorbike=0.852322
person=0.784889
pottedplant=0.498434
sheep=0.772941
sofa=0.797430
train=0.874191
tvmonitor=0.768460
mAP=0.773551
[Epoch 223][Batch 99], Speed: 90.422801 samples/sec, CrossEntropy=1.374446, SmoothL1=0.601399, accuracy=0.882424
[Epoch 223][Batch 199], Speed: 87.679764 samples/sec, CrossEntropy=1.341764, SmoothL1=0.577163, accuracy=0.884673
[Epoch 223][Batch 299], Speed: 85.649113 samples/sec, CrossEntropy=1.347056, SmoothL1=0.578876, accuracy=0.884131
[Epoch 223][Batch 399], Speed: 87.324084 samples/sec, CrossEntropy=1.343975, SmoothL1=0.578766, accuracy=0.884272
[Epoch 223][Batch 499], Speed: 87.468859 samples/sec, CrossEntropy=1.341599, SmoothL1=0.578383, accuracy=0.884559
[Epoch 223] Training cost: 191.841173, CrossEntropy=1.341032, SmoothL1=0.578490, accuracy=0.884580
[Epoch 223] Validation:
aeroplane=0.813451
bicycle=0.832099
bird=0.754699
boat=0.721195
bottle=0.481404
bus=0.850242
car=0.861707
cat=0.882382
chair=0.605671
cow=0.833727
diningtable=0.768827
dog=0.847300
horse=0.866744
motorbike=0.851760
person=0.786078
pottedplant=0.502033
sheep=0.771306
sofa=0.795984
train=0.872456
tvmonitor=0.769774
mAP=0.773442
[Epoch 224][Batch 99], Speed: 91.380665 samples/sec, CrossEntropy=1.317378, SmoothL1=0.561405, accuracy=0.886451
[Epoch 224][Batch 199], Speed: 91.684412 samples/sec, CrossEntropy=1.327355, SmoothL1=0.563795, accuracy=0.886689
[Epoch 224][Batch 299], Speed: 82.857456 samples/sec, CrossEntropy=1.330705, SmoothL1=0.571183, accuracy=0.886162
[Epoch 224][Batch 399], Speed: 88.232988 samples/sec, CrossEntropy=1.327470, SmoothL1=0.572147, accuracy=0.886180
[Epoch 224][Batch 499], Speed: 88.302008 samples/sec, CrossEntropy=1.332443, SmoothL1=0.571028, accuracy=0.885900
[Epoch 224] Training cost: 190.772687, CrossEntropy=1.332209, SmoothL1=0.570374, accuracy=0.885991
[Epoch 224] Validation:
aeroplane=0.814378
bicycle=0.830273
bird=0.753035
boat=0.716992
bottle=0.483399
bus=0.848112
car=0.861346
cat=0.881548
chair=0.606949
cow=0.834422
diningtable=0.770502
dog=0.849030
horse=0.864883
motorbike=0.850945
person=0.786627
pottedplant=0.499638
sheep=0.775300
sofa=0.795473
train=0.874815
tvmonitor=0.774180
mAP=0.773592
[Epoch 225][Batch 99], Speed: 85.557826 samples/sec, CrossEntropy=1.341185, SmoothL1=0.578583, accuracy=0.885980
[Epoch 225][Batch 199], Speed: 92.346840 samples/sec, CrossEntropy=1.348681, SmoothL1=0.586283, accuracy=0.884720
[Epoch 225][Batch 299], Speed: 90.913587 samples/sec, CrossEntropy=1.346169, SmoothL1=0.583607, accuracy=0.885104
[Epoch 225][Batch 399], Speed: 86.227036 samples/sec, CrossEntropy=1.348043, SmoothL1=0.583673, accuracy=0.884478
[Epoch 225][Batch 499], Speed: 83.477821 samples/sec, CrossEntropy=1.344342, SmoothL1=0.579234, accuracy=0.884766
[Epoch 225] Training cost: 192.518392, CrossEntropy=1.342389, SmoothL1=0.578136, accuracy=0.884866
[Epoch 225] Validation:
aeroplane=0.812842
bicycle=0.830968
bird=0.753519
boat=0.715706
bottle=0.482725
bus=0.847739
car=0.861900
cat=0.882440
chair=0.607578
cow=0.838928
diningtable=0.767991
dog=0.846727
horse=0.863219
motorbike=0.851464
person=0.786458
pottedplant=0.501055
sheep=0.770969
sofa=0.794937
train=0.875029
tvmonitor=0.768487
mAP=0.773034
[Epoch 226][Batch 99], Speed: 84.865320 samples/sec, CrossEntropy=1.321823, SmoothL1=0.580598, accuracy=0.886355
[Epoch 226][Batch 199], Speed: 89.653190 samples/sec, CrossEntropy=1.323732, SmoothL1=0.575736, accuracy=0.885947
[Epoch 226][Batch 299], Speed: 90.431513 samples/sec, CrossEntropy=1.329883, SmoothL1=0.577474, accuracy=0.885297
[Epoch 226][Batch 399], Speed: 90.926828 samples/sec, CrossEntropy=1.331763, SmoothL1=0.576048, accuracy=0.885189
[Epoch 226][Batch 499], Speed: 87.280188 samples/sec, CrossEntropy=1.334428, SmoothL1=0.575915, accuracy=0.885026
[Epoch 226] Training cost: 191.907221, CrossEntropy=1.335336, SmoothL1=0.575816, accuracy=0.885046
[Epoch 226] Validation:
aeroplane=0.811355
bicycle=0.830344
bird=0.756913
boat=0.715749
bottle=0.481746
bus=0.850106
car=0.862859
cat=0.881841
chair=0.606155
cow=0.839620
diningtable=0.768593
dog=0.848361
horse=0.863505
motorbike=0.852839
person=0.783763
pottedplant=0.504522
sheep=0.772874
sofa=0.796727
train=0.874761
tvmonitor=0.767163
mAP=0.773490
[Epoch 227][Batch 99], Speed: 85.769416 samples/sec, CrossEntropy=1.314700, SmoothL1=0.572697, accuracy=0.886767
[Epoch 227][Batch 199], Speed: 89.780327 samples/sec, CrossEntropy=1.333418, SmoothL1=0.574953, accuracy=0.885727
[Epoch 227][Batch 299], Speed: 87.629674 samples/sec, CrossEntropy=1.339586, SmoothL1=0.582063, accuracy=0.885119
[Epoch 227][Batch 399], Speed: 86.308157 samples/sec, CrossEntropy=1.343090, SmoothL1=0.584316, accuracy=0.884638
[Epoch 227][Batch 499], Speed: 88.635678 samples/sec, CrossEntropy=1.336218, SmoothL1=0.580012, accuracy=0.884947
[Epoch 227] Training cost: 191.226644, CrossEntropy=1.337438, SmoothL1=0.580363, accuracy=0.884865
[Epoch 227] Validation:
aeroplane=0.812171
bicycle=0.831058
bird=0.751424
boat=0.715198
bottle=0.481948
bus=0.850011
car=0.862506
cat=0.881506
chair=0.605927
cow=0.838908
diningtable=0.768200
dog=0.848461
horse=0.864082
motorbike=0.850615
person=0.786345
pottedplant=0.501079
sheep=0.767946
sofa=0.801033
train=0.874265
tvmonitor=0.766381
mAP=0.772953
[Epoch 228][Batch 99], Speed: 89.458089 samples/sec, CrossEntropy=1.318475, SmoothL1=0.564429, accuracy=0.887249
[Epoch 228][Batch 199], Speed: 91.826426 samples/sec, CrossEntropy=1.329510, SmoothL1=0.578310, accuracy=0.886348
[Epoch 228][Batch 299], Speed: 92.940970 samples/sec, CrossEntropy=1.334113, SmoothL1=0.582128, accuracy=0.885613
[Epoch 228][Batch 399], Speed: 91.662184 samples/sec, CrossEntropy=1.336691, SmoothL1=0.579506, accuracy=0.885417
[Epoch 228][Batch 499], Speed: 83.737603 samples/sec, CrossEntropy=1.329527, SmoothL1=0.577095, accuracy=0.885884
[Epoch 228] Training cost: 192.063438, CrossEntropy=1.330212, SmoothL1=0.577220, accuracy=0.885908
[Epoch 228] Validation:
aeroplane=0.817422
bicycle=0.830685
bird=0.756832
boat=0.717103
bottle=0.481359
bus=0.849031
car=0.862235
cat=0.881133
chair=0.606341
cow=0.843266
diningtable=0.769242
dog=0.847274
horse=0.863700
motorbike=0.848043
person=0.785863
pottedplant=0.503854
sheep=0.766676
sofa=0.797939
train=0.874014
tvmonitor=0.767950
mAP=0.773498
[Epoch 229][Batch 99], Speed: 88.061401 samples/sec, CrossEntropy=1.334564, SmoothL1=0.575473, accuracy=0.884818
[Epoch 229][Batch 199], Speed: 89.324312 samples/sec, CrossEntropy=1.336319, SmoothL1=0.571574, accuracy=0.885276
[Epoch 229][Batch 299], Speed: 92.894720 samples/sec, CrossEntropy=1.333791, SmoothL1=0.572949, accuracy=0.885294
[Epoch 229][Batch 399], Speed: 76.323994 samples/sec, CrossEntropy=1.340699, SmoothL1=0.578460, accuracy=0.884836
[Epoch 229][Batch 499], Speed: 88.577826 samples/sec, CrossEntropy=1.336976, SmoothL1=0.576821, accuracy=0.885159
[Epoch 229] Training cost: 191.010679, CrossEntropy=1.336431, SmoothL1=0.575636, accuracy=0.885217
[Epoch 229] Validation:
aeroplane=0.813145
bicycle=0.832976
bird=0.754027
boat=0.714854
bottle=0.482628
bus=0.849180
car=0.862511
cat=0.882807
chair=0.606613
cow=0.843051
diningtable=0.770774
dog=0.847825
horse=0.867395
motorbike=0.853934
person=0.786673
pottedplant=0.504204
sheep=0.773963
sofa=0.794755
train=0.872764
tvmonitor=0.766732
mAP=0.774041
[Epoch 230][Batch 99], Speed: 92.212589 samples/sec, CrossEntropy=1.313478, SmoothL1=0.565495, accuracy=0.887478
[Epoch 230][Batch 199], Speed: 87.998988 samples/sec, CrossEntropy=1.314960, SmoothL1=0.563694, accuracy=0.886962
[Epoch 230][Batch 299], Speed: 64.491106 samples/sec, CrossEntropy=1.327551, SmoothL1=0.571731, accuracy=0.886080
[Epoch 230][Batch 399], Speed: 84.909183 samples/sec, CrossEntropy=1.331834, SmoothL1=0.573825, accuracy=0.885943
[Epoch 230][Batch 499], Speed: 87.796940 samples/sec, CrossEntropy=1.334359, SmoothL1=0.577433, accuracy=0.885569
[Epoch 230] Training cost: 190.602376, CrossEntropy=1.332687, SmoothL1=0.576681, accuracy=0.885573
[Epoch 230] Validation:
aeroplane=0.812447
bicycle=0.831006
bird=0.751789
boat=0.715684
bottle=0.482722
bus=0.850000
car=0.862209
cat=0.881948
chair=0.607498
cow=0.838246
diningtable=0.769217
dog=0.848940
horse=0.863188
motorbike=0.849756
person=0.784681
pottedplant=0.504905
sheep=0.773425
sofa=0.795235
train=0.873679
tvmonitor=0.767829
mAP=0.773220
[Epoch 231][Batch 99], Speed: 90.846636 samples/sec, CrossEntropy=1.317458, SmoothL1=0.568463, accuracy=0.885567
[Epoch 231][Batch 199], Speed: 87.825148 samples/sec, CrossEntropy=1.326747, SmoothL1=0.581125, accuracy=0.885312
[Epoch 231][Batch 299], Speed: 89.051631 samples/sec, CrossEntropy=1.337440, SmoothL1=0.584219, accuracy=0.884667
[Epoch 231][Batch 399], Speed: 80.419931 samples/sec, CrossEntropy=1.331826, SmoothL1=0.576113, accuracy=0.884973
[Epoch 231][Batch 499], Speed: 88.964979 samples/sec, CrossEntropy=1.330380, SmoothL1=0.574805, accuracy=0.885222
[Epoch 231] Training cost: 191.693099, CrossEntropy=1.329236, SmoothL1=0.573601, accuracy=0.885432
[Epoch 231] Validation:
aeroplane=0.809481
bicycle=0.831299
bird=0.752038
boat=0.717889
bottle=0.485684
bus=0.848161
car=0.862011
cat=0.882377
chair=0.606054
cow=0.837006
diningtable=0.770774
dog=0.846580
horse=0.866256
motorbike=0.856018
person=0.786692
pottedplant=0.503505
sheep=0.764926
sofa=0.795840
train=0.872277
tvmonitor=0.769348
mAP=0.773211
[Epoch 232][Batch 99], Speed: 89.110518 samples/sec, CrossEntropy=1.323614, SmoothL1=0.562738, accuracy=0.886735
[Epoch 232][Batch 199], Speed: 85.599733 samples/sec, CrossEntropy=1.327058, SmoothL1=0.569284, accuracy=0.886446
[Epoch 232][Batch 299], Speed: 79.494600 samples/sec, CrossEntropy=1.335928, SmoothL1=0.572465, accuracy=0.885938
[Epoch 232][Batch 399], Speed: 75.383059 samples/sec, CrossEntropy=1.337764, SmoothL1=0.577959, accuracy=0.885595
[Epoch 232][Batch 499], Speed: 93.775399 samples/sec, CrossEntropy=1.334183, SmoothL1=0.573331, accuracy=0.885655
[Epoch 232] Training cost: 191.977933, CrossEntropy=1.335468, SmoothL1=0.573971, accuracy=0.885530
[Epoch 232] Validation:
aeroplane=0.809983
bicycle=0.833296
bird=0.755764
boat=0.716982
bottle=0.481837
bus=0.849031
car=0.861879
cat=0.881976
chair=0.606700
cow=0.838412
diningtable=0.768873
dog=0.849388
horse=0.866059
motorbike=0.854838
person=0.786351
pottedplant=0.501042
sheep=0.768662
sofa=0.793813
train=0.873211
tvmonitor=0.769632
mAP=0.773387
[Epoch 233][Batch 99], Speed: 87.663844 samples/sec, CrossEntropy=1.331672, SmoothL1=0.582532, accuracy=0.884351
[Epoch 233][Batch 199], Speed: 91.512753 samples/sec, CrossEntropy=1.328769, SmoothL1=0.581257, accuracy=0.885544
[Epoch 233][Batch 299], Speed: 82.658294 samples/sec, CrossEntropy=1.338110, SmoothL1=0.582352, accuracy=0.884634
[Epoch 233][Batch 399], Speed: 81.415378 samples/sec, CrossEntropy=1.334027, SmoothL1=0.578387, accuracy=0.884684
[Epoch 233][Batch 499], Speed: 86.992360 samples/sec, CrossEntropy=1.329668, SmoothL1=0.572772, accuracy=0.885097
[Epoch 233] Training cost: 191.292289, CrossEntropy=1.328818, SmoothL1=0.572251, accuracy=0.885201
[Epoch 233] Validation:
aeroplane=0.812317
bicycle=0.829160
bird=0.754637
boat=0.718290
bottle=0.483597
bus=0.847592
car=0.860917
cat=0.883088
chair=0.604856
cow=0.831865
diningtable=0.768811
dog=0.848831
horse=0.867707
motorbike=0.854159
person=0.785132
pottedplant=0.503396
sheep=0.775142
sofa=0.796264
train=0.874341
tvmonitor=0.765311
mAP=0.773271
[Epoch 234][Batch 99], Speed: 87.949628 samples/sec, CrossEntropy=1.307873, SmoothL1=0.566047, accuracy=0.887498
[Epoch 234][Batch 199], Speed: 83.727051 samples/sec, CrossEntropy=1.314421, SmoothL1=0.569030, accuracy=0.887204
[Epoch 234][Batch 299], Speed: 82.715246 samples/sec, CrossEntropy=1.325877, SmoothL1=0.573439, accuracy=0.886277
[Epoch 234][Batch 399], Speed: 75.841094 samples/sec, CrossEntropy=1.329402, SmoothL1=0.575414, accuracy=0.885804
[Epoch 234][Batch 499], Speed: 87.408478 samples/sec, CrossEntropy=1.328018, SmoothL1=0.571914, accuracy=0.886034
[Epoch 234] Training cost: 190.934453, CrossEntropy=1.327363, SmoothL1=0.571366, accuracy=0.886026
[Epoch 234] Validation:
aeroplane=0.811650
bicycle=0.833454
bird=0.754610
boat=0.718552
bottle=0.484640
bus=0.847227
car=0.862177
cat=0.883024
chair=0.607201
cow=0.837688
diningtable=0.771538
dog=0.849984
horse=0.867293
motorbike=0.853584
person=0.785370
pottedplant=0.503442
sheep=0.768905
sofa=0.796475
train=0.871484
tvmonitor=0.768909
mAP=0.773860
[Epoch 235][Batch 99], Speed: 91.996680 samples/sec, CrossEntropy=1.330320, SmoothL1=0.577287, accuracy=0.886248
[Epoch 235][Batch 199], Speed: 88.300963 samples/sec, CrossEntropy=1.333094, SmoothL1=0.575925, accuracy=0.885372
[Epoch 235][Batch 299], Speed: 86.309433 samples/sec, CrossEntropy=1.345098, SmoothL1=0.579202, accuracy=0.884829
[Epoch 235][Batch 399], Speed: 86.448467 samples/sec, CrossEntropy=1.336206, SmoothL1=0.572812, accuracy=0.885593
[Epoch 235][Batch 499], Speed: 91.291225 samples/sec, CrossEntropy=1.338955, SmoothL1=0.577347, accuracy=0.885363
[Epoch 235] Training cost: 191.257925, CrossEntropy=1.338215, SmoothL1=0.577746, accuracy=0.885459
[Epoch 235] Validation:
aeroplane=0.816256
bicycle=0.830723
bird=0.754950
boat=0.717928
bottle=0.480422
bus=0.846938
car=0.861589
cat=0.883226
chair=0.607313
cow=0.835826
diningtable=0.770539
dog=0.850549
horse=0.868100
motorbike=0.853277
person=0.783680
pottedplant=0.499299
sheep=0.767214
sofa=0.795210
train=0.875088
tvmonitor=0.765963
mAP=0.773205
[Epoch 236][Batch 99], Speed: 90.765111 samples/sec, CrossEntropy=1.334698, SmoothL1=0.578086, accuracy=0.884757
[Epoch 236][Batch 199], Speed: 90.414517 samples/sec, CrossEntropy=1.327486, SmoothL1=0.568340, accuracy=0.885916
[Epoch 236][Batch 299], Speed: 81.692981 samples/sec, CrossEntropy=1.339277, SmoothL1=0.572173, accuracy=0.885111
[Epoch 236][Batch 399], Speed: 73.176793 samples/sec, CrossEntropy=1.339620, SmoothL1=0.572473, accuracy=0.884915
[Epoch 236][Batch 499], Speed: 91.905526 samples/sec, CrossEntropy=1.342954, SmoothL1=0.575470, accuracy=0.884712
[Epoch 236] Training cost: 192.520715, CrossEntropy=1.341797, SmoothL1=0.573972, accuracy=0.884804
[Epoch 236] Validation:
aeroplane=0.809975
bicycle=0.832053
bird=0.752879
boat=0.717324
bottle=0.483248
bus=0.846798
car=0.861449
cat=0.883408
chair=0.605047
cow=0.836824
diningtable=0.772369
dog=0.849512
horse=0.865720
motorbike=0.854134
person=0.783055
pottedplant=0.497582
sheep=0.771243
sofa=0.796077
train=0.873254
tvmonitor=0.768808
mAP=0.773038
[Epoch 237][Batch 99], Speed: 85.292500 samples/sec, CrossEntropy=1.301783, SmoothL1=0.565044, accuracy=0.887974
[Epoch 237][Batch 199], Speed: 88.453661 samples/sec, CrossEntropy=1.310438, SmoothL1=0.566539, accuracy=0.887788
[Epoch 237][Batch 299], Speed: 86.534802 samples/sec, CrossEntropy=1.308656, SmoothL1=0.567324, accuracy=0.887496
[Epoch 237][Batch 399], Speed: 86.082143 samples/sec, CrossEntropy=1.316046, SmoothL1=0.570218, accuracy=0.886793
[Epoch 237][Batch 499], Speed: 88.569409 samples/sec, CrossEntropy=1.317174, SmoothL1=0.573721, accuracy=0.886728
[Epoch 237] Training cost: 191.907645, CrossEntropy=1.316535, SmoothL1=0.574339, accuracy=0.886733
[Epoch 237] Validation:
aeroplane=0.811410
bicycle=0.834327
bird=0.750868
boat=0.718761
bottle=0.485813
bus=0.849647
car=0.862532
cat=0.883722
chair=0.607135
cow=0.836822
diningtable=0.772184
dog=0.850184
horse=0.866172
motorbike=0.854823
person=0.783656
pottedplant=0.497879
sheep=0.774469
sofa=0.796472
train=0.875171
tvmonitor=0.770661
mAP=0.774135
[Epoch 238][Batch 99], Speed: 91.621950 samples/sec, CrossEntropy=1.309808, SmoothL1=0.562575, accuracy=0.887994
[Epoch 238][Batch 199], Speed: 87.135414 samples/sec, CrossEntropy=1.309355, SmoothL1=0.560924, accuracy=0.887566
[Epoch 238][Batch 299], Speed: 83.645234 samples/sec, CrossEntropy=1.326279, SmoothL1=0.572838, accuracy=0.885993
[Epoch 238][Batch 399], Speed: 95.709834 samples/sec, CrossEntropy=1.326445, SmoothL1=0.570541, accuracy=0.886219
[Epoch 238][Batch 499], Speed: 80.832481 samples/sec, CrossEntropy=1.330693, SmoothL1=0.573321, accuracy=0.885752
[Epoch 238] Training cost: 190.686025, CrossEntropy=1.330952, SmoothL1=0.572823, accuracy=0.885712
[Epoch 238] Validation:
aeroplane=0.810581
bicycle=0.830526
bird=0.755541
boat=0.717014
bottle=0.486691
bus=0.849654
car=0.860661
cat=0.883526
chair=0.603802
cow=0.834511
diningtable=0.773167
dog=0.849058
horse=0.865022
motorbike=0.855664
person=0.784332
pottedplant=0.503258
sheep=0.776095
sofa=0.795003
train=0.873430
tvmonitor=0.769308
mAP=0.773842
[Epoch 239][Batch 99], Speed: 83.546776 samples/sec, CrossEntropy=1.338197, SmoothL1=0.585984, accuracy=0.885827
[Epoch 239][Batch 199], Speed: 90.612042 samples/sec, CrossEntropy=1.328345, SmoothL1=0.576357, accuracy=0.885816
[Epoch 239][Batch 299], Speed: 88.467362 samples/sec, CrossEntropy=1.331581, SmoothL1=0.579917, accuracy=0.885679
[Epoch 239][Batch 399], Speed: 84.391373 samples/sec, CrossEntropy=1.338085, SmoothL1=0.579676, accuracy=0.885289
[Epoch 239][Batch 499], Speed: 90.159066 samples/sec, CrossEntropy=1.334377, SmoothL1=0.578073, accuracy=0.885514
[Epoch 239] Training cost: 191.401617, CrossEntropy=1.334460, SmoothL1=0.578227, accuracy=0.885542
[Epoch 239] Validation:
aeroplane=0.810234
bicycle=0.834462
bird=0.757103
boat=0.716375
bottle=0.485639
bus=0.848930
car=0.860086
cat=0.884054
chair=0.606559
cow=0.835521
diningtable=0.771451
dog=0.848035
horse=0.864384
motorbike=0.855329
person=0.784376
pottedplant=0.500545
sheep=0.775001
sofa=0.793523
train=0.872579
tvmonitor=0.769007
mAP=0.773660