File size: 4,615 Bytes
9e14838 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | Train images: 141230 Validation images: 8070
__TRAINING STATS__
Counter({1.0: 88531, 0.0: 52699})
Weights 0.5952604172549728
__VALIDATION STATS__
Counter({0: 4198, 1: 3872})
#0/300 loss:0.5136975361087457 accuracy:0.5732563902853501 val_loss:0.5364688427299703 val_accuracy:0.6002478314745973 val_0s:4678/4198 val_1s:3392/3872
#1/300 loss:0.4748700084961793 accuracy:0.6409332294838207 val_loss:0.5375074183976265 val_accuracy:0.6192069392812887 val_0s:4395/4198 val_1s:3675/3872
#2/300 loss:0.4591452846219224 accuracy:0.6621114494087659 val_loss:0.5839169139465875 val_accuracy:0.614002478314746 val_0s:2867/4198 val_1s:5203/3872
#3/300 loss:0.4471282922684823 accuracy:0.6749203427033916 val_loss:0.5183086053412465 val_accuracy:0.628004956629492 val_0s:4636/4198 val_1s:3434/3872
#4/300 loss:0.4380730671197989 accuracy:0.6847766055370672 val_loss:0.5090801186943618 val_accuracy:0.5711276332094176 val_0s:7007/4198 val_1s:1063/3872
#5/300 loss:0.4327000849617695 accuracy:0.6904552857041705 val_loss:0.5188724035608308 val_accuracy:0.6338289962825279 val_0s:4449/4198 val_1s:3621/3872
#6/300 loss:0.42427017841971437 accuracy:0.6993769029243079 val_loss:0.527833827893175 val_accuracy:0.6415117719950434 val_0s:4149/4198 val_1s:3921/3872
#7/300 loss:0.4212744265080735 accuracy:0.7030163562982369 val_loss:0.5026112759643917 val_accuracy:0.6396530359355638 val_0s:5058/4198 val_1s:3012/3872
#8/300 loss:0.4154885301614286 accuracy:0.7076683424201657 val_loss:0.5432640949554897 val_accuracy:0.6465923172242874 val_0s:4044/4198 val_1s:4026/3872
#9/300 loss:0.4123908241291415 accuracy:0.710812150392976 val_loss:0.5210385756676557 val_accuracy:0.6503097893432466 val_0s:4164/4198 val_1s:3906/3872
#10/300 loss:0.40723704333050326 accuracy:0.7136939743680522 val_loss:0.5589614243323435 val_accuracy:0.6472118959107807 val_0s:3179/4198 val_1s:4891/3872
#11/300 loss:0.402232795242142 accuracy:0.7185654605961906 val_loss:0.5192581602373888 val_accuracy:0.6350681536555143 val_0s:4991/4198 val_1s:3079/3872
#12/300 loss:0.39900764655904725 accuracy:0.7225235431565531 val_loss:0.5632047477744805 val_accuracy:0.6503097893432466 val_0s:3448/4198 val_1s:4622/3872
#14/300 loss:0.5343504934649247 accuracy:0.7136664258322681 val_loss:0.9343544303797466 val_accuracy:0.57053852
#15/300 loss:0.525838890370766 accuracy:0.7187906408047574 val_loss:0.8023291139240499 val_accuracy:0.614572332
#16/300 loss:0.5172125900240065 accuracy:0.7257766909353638 val_loss:0.6720759493670888 val_accuracy:0.64656812
#17/300 loss:0.5092864763937068 accuracy:0.7304396154059912 val_loss:0.679392405063291 val_accuracy:0.6568109820485745 val_0s:37742
#18/300 loss:0.5029607895438754 accuracy:0.7338798421608403 val_loss:1.3394683544303796 val_accuracy:0.50200632
#19/300 loss:0.49735662843424994 accuracy:0.7380870338464959 val_loss:0.8208860759493672 val_accuracy:0.5971482
#20/300 loss:0.4908455588156868 accuracy:0.7425498805090869 val_loss:0.668025316455696 val_accuracy:0.640232312
#21/300 loss:0.48448919711923205 accuracy:0.745934530095037 val_loss:0.8548101265822788 val_accuracy:0.586272439281943 val_0s:71562
#22/300 loss:0.4819138436916507 accuracy:0.7464736286333574 val_loss:0.8362784810126573 val_accuracy:0.6214361140443506 val_0s:1512
#23/300 loss:0.4766591090957589 accuracy:0.7510865336519758 val_loss:0.8313924050632903 val_accuracy:0.6175290390707497 val_0s:5592
Train images: 324636 Validation images: 9470
__TRAINING STATS__
Counter({1.0: 184165, 0.0: 140471})
Weights 0.7627453642114408
__VALIDATION STATS__
Counter({1: 5272, 0.0: 4198})
#0/300 loss:0.577774820728925 accuracy:0.5991941743984032 val_loss:0.6628860759493668 val_accuracy:0.5971488912354804 val_0s:2313/4198 val_1s:7157/5272
#1/300 loss:0.5315613218008431 accuracy:0.661925972473786 val_loss:0.6108101265822785 val_accuracy:0.5901795142555438 val_0s:3371/4198 val_1s:6099/5272
#2/300 loss:0.5131625637613617 accuracy:0.6794471346369473 val_loss:0.6132911392405063 val_accuracy:0.5706441393875396 val_0s:6406/4198 val_1s:3064/5272
#3/300 loss:0.49969690249131055 accuracy:0.6905796030015156 val_loss:0.5810126582278485 val_accuracy:0.6125659978880675 val_0s:5133/4198 val_1s:4337/5272
#4/300 loss:0.4878531825238368 accuracy:0.7005754136941066 val_loss:0.5803544303797468 val_accuracy:0.6221752903907075 val_0s:4904/4198 val_1s:4566/5272
#5/300 loss:0.47785761809713456 accuracy:0.7076171465887948 val_loss:0.599493670886076 val_accuracy:0.6082365364308342 val_0s:4704/4198 val_1s:4766/5272
#6/300 loss:0.4679618540696333 accuracy:0.7164331743860817 val_loss:0.5943291139240504 val_accuracy:0.6158394931362197 val_0s:5984/4198 val_1s:3486/5272 |