lr: 0.001
sub_1:Test (Best Model) - Loss: 5.3783 - Accuracy: 0.6324 - F1: 0.6556
sub_3:Test (Best Model) - Loss: 41.8315 - Accuracy: 0.3824 - F1: 0.2904
sub_2:Test (Best Model) - Loss: 2.7583 - Accuracy: 0.8986 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 13.7608 - Accuracy: 0.5882 - F1: 0.6166
sub_3:Test (Best Model) - Loss: 15.2563 - Accuracy: 0.5441 - F1: 0.4918
sub_2:Test (Best Model) - Loss: 5.1760 - Accuracy: 0.7101 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 2.1025 - Accuracy: 0.7206 - F1: 0.7386
sub_3:Test (Best Model) - Loss: 13.7429 - Accuracy: 0.5882 - F1: 0.5762
sub_2:Test (Best Model) - Loss: 2.7249 - Accuracy: 0.6087 - F1: 0.6085
sub_1:Test (Best Model) - Loss: 46.9586 - Accuracy: 0.5441 - F1: 0.5574
sub_3:Test (Best Model) - Loss: 17.3397 - Accuracy: 0.5000 - F1: 0.4594
sub_2:Test (Best Model) - Loss: 4.7669 - Accuracy: 0.6522 - F1: 0.6159
sub_3:Test (Best Model) - Loss: 24.6064 - Accuracy: 0.5588 - F1: 0.5284
sub_1:Test (Best Model) - Loss: 28.0809 - Accuracy: 0.5000 - F1: 0.5053
sub_3:Test (Best Model) - Loss: 3.2090 - Accuracy: 0.5797 - F1: 0.5649
sub_2:Test (Best Model) - Loss: 4.1819 - Accuracy: 0.6812 - F1: 0.6671
sub_1:Test (Best Model) - Loss: 3.9436 - Accuracy: 0.5362 - F1: 0.5171
sub_2:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.7500 - F1: 0.7587
sub_3:Test (Best Model) - Loss: 13.9106 - Accuracy: 0.5362 - F1: 0.5076
sub_1:Test (Best Model) - Loss: 4.3966 - Accuracy: 0.5072 - F1: 0.4643
sub_2:Test (Best Model) - Loss: 2.7639 - Accuracy: 0.7059 - F1: 0.6890
sub_1:Test (Best Model) - Loss: 4.8757 - Accuracy: 0.5362 - F1: 0.5585
sub_3:Test (Best Model) - Loss: 5.0558 - Accuracy: 0.5507 - F1: 0.5259
sub_2:Test (Best Model) - Loss: 2.4304 - Accuracy: 0.7500 - F1: 0.7452
sub_1:Test (Best Model) - Loss: 21.1015 - Accuracy: 0.4928 - F1: 0.4594
sub_3:Test (Best Model) - Loss: 8.8107 - Accuracy: 0.5942 - F1: 0.5680
sub_2:Test (Best Model) - Loss: 2.0178 - Accuracy: 0.6912 - F1: 0.6870
sub_3:Test (Best Model) - Loss: 5.4209 - Accuracy: 0.5652 - F1: 0.5441
sub_1:Test (Best Model) - Loss: 6.3038 - Accuracy: 0.5217 - F1: 0.4876
sub_1:Test (Best Model) - Loss: 1.8043 - Accuracy: 0.5882 - F1: 0.5446
sub_2:Test (Best Model) - Loss: 2.7080 - Accuracy: 0.7206 - F1: 0.7179
sub_3:Test (Best Model) - Loss: 3.5884 - Accuracy: 0.6667 - F1: 0.6439
sub_2:Test (Best Model) - Loss: 3.5701 - Accuracy: 0.5652 - F1: 0.5401
sub_1:Test (Best Model) - Loss: 1.7502 - Accuracy: 0.5735 - F1: 0.5536
sub_3:Test (Best Model) - Loss: 3.3771 - Accuracy: 0.7826 - F1: 0.7897
sub_3:Test (Best Model) - Loss: 6.0357 - Accuracy: 0.5217 - F1: 0.4693
sub_1:Test (Best Model) - Loss: 1.6688 - Accuracy: 0.6029 - F1: 0.5747
sub_2:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.6957 - F1: 0.6975
sub_1:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.6912 - F1: 0.6499
sub_2:Test (Best Model) - Loss: 7.2605 - Accuracy: 0.5507 - F1: 0.5008
sub_3:Test (Best Model) - Loss: 4.4110 - Accuracy: 0.6667 - F1: 0.6400
sub_2:Test (Best Model) - Loss: 4.2598 - Accuracy: 0.3913 - F1: 0.3729
sub_1:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.6471 - F1: 0.6354
sub_3:Test (Best Model) - Loss: 6.6530 - Accuracy: 0.5942 - F1: 0.5714
sub_2:Test (Best Model) - Loss: 9.2423 - Accuracy: 0.5072 - F1: 0.4422
sub_5:Test (Best Model) - Loss: 55.5043 - Accuracy: 0.6618 - F1: 0.5970
sub_6:Test (Best Model) - Loss: 8.5142 - Accuracy: 0.6029 - F1: 0.5422
sub_4:Test (Best Model) - Loss: 5.9707 - Accuracy: 0.5507 - F1: 0.5181
sub_4:Test (Best Model) - Loss: 5.0099 - Accuracy: 0.6522 - F1: 0.6293
sub_5:Test (Best Model) - Loss: 75.6698 - Accuracy: 0.6618 - F1: 0.6080
sub_6:Test (Best Model) - Loss: 7.1436 - Accuracy: 0.6618 - F1: 0.5829
sub_5:Test (Best Model) - Loss: 19.4739 - Accuracy: 0.6912 - F1: 0.6300
sub_4:Test (Best Model) - Loss: 3.2368 - Accuracy: 0.6087 - F1: 0.5819
sub_6:Test (Best Model) - Loss: 9.9677 - Accuracy: 0.5882 - F1: 0.5303
sub_5:Test (Best Model) - Loss: 58.5247 - Accuracy: 0.6618 - F1: 0.6029
sub_4:Test (Best Model) - Loss: 4.2210 - Accuracy: 0.5507 - F1: 0.5152
sub_6:Test (Best Model) - Loss: 7.9334 - Accuracy: 0.5588 - F1: 0.5099
sub_5:Test (Best Model) - Loss: 38.3242 - Accuracy: 0.6471 - F1: 0.5894
sub_4:Test (Best Model) - Loss: 5.5595 - Accuracy: 0.5652 - F1: 0.5443
sub_4:Test (Best Model) - Loss: 0.8212 - Accuracy: 0.7681 - F1: 0.7750
sub_5:Test (Best Model) - Loss: 1.7941 - Accuracy: 0.7059 - F1: 0.6891
sub_4:Test (Best Model) - Loss: 1.8812 - Accuracy: 0.6957 - F1: 0.7057
sub_6:Test (Best Model) - Loss: 6.0885 - Accuracy: 0.6471 - F1: 0.5743
sub_5:Test (Best Model) - Loss: 3.0804 - Accuracy: 0.5147 - F1: 0.4708
sub_4:Test (Best Model) - Loss: 0.8124 - Accuracy: 0.7971 - F1: 0.7987
sub_6:Test (Best Model) - Loss: 3.0647 - Accuracy: 0.5507 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 10.6727 - Accuracy: 0.4118 - F1: 0.3077
sub_6:Test (Best Model) - Loss: 2.8369 - Accuracy: 0.6087 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 3.5694 - Accuracy: 0.6957 - F1: 0.6676
sub_5:Test (Best Model) - Loss: 1.4895 - Accuracy: 0.7500 - F1: 0.7287
sub_6:Test (Best Model) - Loss: 3.5828 - Accuracy: 0.5942 - F1: 0.6314
sub_4:Test (Best Model) - Loss: 1.6357 - Accuracy: 0.7971 - F1: 0.8023
sub_5:Test (Best Model) - Loss: 2.5991 - Accuracy: 0.6912 - F1: 0.6356
sub_4:Test (Best Model) - Loss: 1.8696 - Accuracy: 0.6957 - F1: 0.6349
sub_6:Test (Best Model) - Loss: 2.0473 - Accuracy: 0.6232 - F1: 0.6428
sub_5:Test (Best Model) - Loss: 5.4878 - Accuracy: 0.4412 - F1: 0.3505
sub_4:Test (Best Model) - Loss: 0.8292 - Accuracy: 0.6957 - F1: 0.7021
sub_5:Test (Best Model) - Loss: 2.7639 - Accuracy: 0.4853 - F1: 0.3923
sub_6:Test (Best Model) - Loss: 1.8121 - Accuracy: 0.6812 - F1: 0.6867
sub_4:Test (Best Model) - Loss: 3.3675 - Accuracy: 0.6812 - F1: 0.6637
sub_5:Test (Best Model) - Loss: 2.9265 - Accuracy: 0.6176 - F1: 0.5424
sub_6:Test (Best Model) - Loss: 4.1332 - Accuracy: 0.7391 - F1: 0.7153
sub_4:Test (Best Model) - Loss: 3.3562 - Accuracy: 0.6957 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 3.7371 - Accuracy: 0.7536 - F1: 0.7217
sub_5:Test (Best Model) - Loss: 3.8248 - Accuracy: 0.6029 - F1: 0.5362
sub_4:Test (Best Model) - Loss: 1.2158 - Accuracy: 0.7101 - F1: 0.6724
sub_6:Test (Best Model) - Loss: 5.0741 - Accuracy: 0.7391 - F1: 0.7064
sub_5:Test (Best Model) - Loss: 2.9925 - Accuracy: 0.7059 - F1: 0.6342
sub_6:Test (Best Model) - Loss: 3.2453 - Accuracy: 0.7536 - F1: 0.7277
sub_6:Test (Best Model) - Loss: 5.0597 - Accuracy: 0.7101 - F1: 0.6750
sub_9:Test (Best Model) - Loss: 1.2142 - Accuracy: 0.4412 - F1: 0.4358
sub_7:Test (Best Model) - Loss: 0.5183 - Accuracy: 0.8529 - F1: 0.8462
sub_8:Test (Best Model) - Loss: 4.0613 - Accuracy: 0.5441 - F1: 0.5237
sub_9:Test (Best Model) - Loss: 3.9009 - Accuracy: 0.4412 - F1: 0.4093
sub_7:Test (Best Model) - Loss: 0.9936 - Accuracy: 0.8676 - F1: 0.8723
sub_9:Test (Best Model) - Loss: 0.9212 - Accuracy: 0.5441 - F1: 0.5517
sub_8:Test (Best Model) - Loss: 4.0443 - Accuracy: 0.5147 - F1: 0.5056
sub_7:Test (Best Model) - Loss: 1.0680 - Accuracy: 0.8971 - F1: 0.8976
sub_8:Test (Best Model) - Loss: 6.4200 - Accuracy: 0.4412 - F1: 0.4380
sub_9:Test (Best Model) - Loss: 6.3741 - Accuracy: 0.4412 - F1: 0.4018
sub_7:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.8824 - F1: 0.8866
sub_8:Test (Best Model) - Loss: 2.0286 - Accuracy: 0.6029 - F1: 0.6110
sub_9:Test (Best Model) - Loss: 5.8756 - Accuracy: 0.6324 - F1: 0.6050
sub_7:Test (Best Model) - Loss: 2.9549 - Accuracy: 0.6176 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 3.8248 - Accuracy: 0.4853 - F1: 0.4776
sub_7:Test (Best Model) - Loss: 3.3806 - Accuracy: 0.5294 - F1: 0.5223
sub_9:Test (Best Model) - Loss: 3.1095 - Accuracy: 0.4706 - F1: 0.4247
sub_8:Test (Best Model) - Loss: 9.3770 - Accuracy: 0.6618 - F1: 0.6211
sub_7:Test (Best Model) - Loss: 2.8064 - Accuracy: 0.5882 - F1: 0.6085
sub_9:Test (Best Model) - Loss: 4.8507 - Accuracy: 0.4118 - F1: 0.3436
sub_8:Test (Best Model) - Loss: 11.6012 - Accuracy: 0.5882 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 2.7102 - Accuracy: 0.6912 - F1: 0.7038
sub_9:Test (Best Model) - Loss: 2.8778 - Accuracy: 0.5000 - F1: 0.4360
sub_8:Test (Best Model) - Loss: 18.3544 - Accuracy: 0.7206 - F1: 0.6716
sub_7:Test (Best Model) - Loss: 2.0358 - Accuracy: 0.6324 - F1: 0.6258
sub_7:Test (Best Model) - Loss: 5.4060 - Accuracy: 0.5000 - F1: 0.4900
sub_9:Test (Best Model) - Loss: 5.3817 - Accuracy: 0.4118 - F1: 0.3492
sub_8:Test (Best Model) - Loss: 5.7404 - Accuracy: 0.7206 - F1: 0.7136
sub_7:Test (Best Model) - Loss: 1.7650 - Accuracy: 0.7794 - F1: 0.7820
sub_7:Test (Best Model) - Loss: 2.6022 - Accuracy: 0.7500 - F1: 0.7484
sub_8:Test (Best Model) - Loss: 14.3775 - Accuracy: 0.7059 - F1: 0.6410
sub_9:Test (Best Model) - Loss: 14.4799 - Accuracy: 0.4118 - F1: 0.3454
sub_8:Test (Best Model) - Loss: 8.0302 - Accuracy: 0.4559 - F1: 0.5012
sub_7:Test (Best Model) - Loss: 2.1297 - Accuracy: 0.8382 - F1: 0.8339
sub_9:Test (Best Model) - Loss: 8.9393 - Accuracy: 0.3971 - F1: 0.3009
sub_7:Test (Best Model) - Loss: 3.8217 - Accuracy: 0.7500 - F1: 0.7609
sub_8:Test (Best Model) - Loss: 10.7587 - Accuracy: 0.4853 - F1: 0.5295
sub_9:Test (Best Model) - Loss: 2.8068 - Accuracy: 0.4853 - F1: 0.4425
sub_8:Test (Best Model) - Loss: 13.0734 - Accuracy: 0.5294 - F1: 0.5391
sub_7:Test (Best Model) - Loss: 6.1848 - Accuracy: 0.7500 - F1: 0.7399
sub_9:Test (Best Model) - Loss: 1.7834 - Accuracy: 0.4706 - F1: 0.4301
sub_8:Test (Best Model) - Loss: 11.6759 - Accuracy: 0.4265 - F1: 0.4780
sub_9:Test (Best Model) - Loss: 5.1117 - Accuracy: 0.4706 - F1: 0.4038
sub_8:Test (Best Model) - Loss: 7.9761 - Accuracy: 0.3971 - F1: 0.4642
sub_9:Test (Best Model) - Loss: 8.2319 - Accuracy: 0.4706 - F1: 0.4196
sub_10:Test (Best Model) - Loss: 15.1134 - Accuracy: 0.5147 - F1: 0.5070
sub_11:Test (Best Model) - Loss: 8.5252 - Accuracy: 0.4638 - F1: 0.4166
sub_12:Test (Best Model) - Loss: 3.4063 - Accuracy: 0.6471 - F1: 0.6439
sub_10:Test (Best Model) - Loss: 5.3822 - Accuracy: 0.4853 - F1: 0.4683
sub_12:Test (Best Model) - Loss: 1.9550 - Accuracy: 0.7059 - F1: 0.7062
sub_11:Test (Best Model) - Loss: 4.4257 - Accuracy: 0.5507 - F1: 0.5300
sub_10:Test (Best Model) - Loss: 5.3830 - Accuracy: 0.5735 - F1: 0.5691
sub_12:Test (Best Model) - Loss: 4.0723 - Accuracy: 0.6618 - F1: 0.6656
sub_11:Test (Best Model) - Loss: 4.8105 - Accuracy: 0.5362 - F1: 0.5408
sub_10:Test (Best Model) - Loss: 6.5990 - Accuracy: 0.4559 - F1: 0.4524
sub_12:Test (Best Model) - Loss: 4.8118 - Accuracy: 0.5588 - F1: 0.5891
sub_10:Test (Best Model) - Loss: 5.1163 - Accuracy: 0.5147 - F1: 0.5166
sub_11:Test (Best Model) - Loss: 12.7845 - Accuracy: 0.4493 - F1: 0.3708
sub_12:Test (Best Model) - Loss: 2.0872 - Accuracy: 0.6324 - F1: 0.6400
sub_12:Test (Best Model) - Loss: 4.3709 - Accuracy: 0.6087 - F1: 0.6072
sub_10:Test (Best Model) - Loss: 20.8101 - Accuracy: 0.6176 - F1: 0.5530
sub_12:Test (Best Model) - Loss: 6.6673 - Accuracy: 0.4493 - F1: 0.4684
sub_11:Test (Best Model) - Loss: 8.6014 - Accuracy: 0.4638 - F1: 0.4406
sub_10:Test (Best Model) - Loss: 54.1212 - Accuracy: 0.5588 - F1: 0.5057
sub_12:Test (Best Model) - Loss: 9.5885 - Accuracy: 0.3768 - F1: 0.3973
sub_11:Test (Best Model) - Loss: 3.3823 - Accuracy: 0.6087 - F1: 0.5831
sub_12:Test (Best Model) - Loss: 5.3247 - Accuracy: 0.4348 - F1: 0.4441
sub_10:Test (Best Model) - Loss: 47.8036 - Accuracy: 0.5294 - F1: 0.4983
sub_11:Test (Best Model) - Loss: 3.5920 - Accuracy: 0.6522 - F1: 0.6277
sub_10:Test (Best Model) - Loss: 49.2120 - Accuracy: 0.5147 - F1: 0.5011
sub_12:Test (Best Model) - Loss: 5.9273 - Accuracy: 0.3913 - F1: 0.4255
sub_12:Test (Best Model) - Loss: 2.6865 - Accuracy: 0.6471 - F1: 0.6417
sub_10:Test (Best Model) - Loss: 35.2725 - Accuracy: 0.5000 - F1: 0.4522
sub_11:Test (Best Model) - Loss: 1.0827 - Accuracy: 0.6812 - F1: 0.6783
sub_10:Test (Best Model) - Loss: 5.7423 - Accuracy: 0.6232 - F1: 0.6059
sub_12:Test (Best Model) - Loss: 1.7617 - Accuracy: 0.6471 - F1: 0.6533
sub_11:Test (Best Model) - Loss: 10.5032 - Accuracy: 0.6232 - F1: 0.5643
sub_10:Test (Best Model) - Loss: 2.5234 - Accuracy: 0.5797 - F1: 0.5131
sub_12:Test (Best Model) - Loss: 3.3334 - Accuracy: 0.5588 - F1: 0.5812
sub_10:Test (Best Model) - Loss: 2.2383 - Accuracy: 0.5507 - F1: 0.4905
sub_11:Test (Best Model) - Loss: 5.0896 - Accuracy: 0.6087 - F1: 0.5819
sub_10:Test (Best Model) - Loss: 4.0624 - Accuracy: 0.6232 - F1: 0.5551
sub_12:Test (Best Model) - Loss: 4.8952 - Accuracy: 0.5735 - F1: 0.5817
sub_11:Test (Best Model) - Loss: 2.4164 - Accuracy: 0.5507 - F1: 0.5129
sub_10:Test (Best Model) - Loss: 4.0254 - Accuracy: 0.6377 - F1: 0.5874
sub_12:Test (Best Model) - Loss: 2.9066 - Accuracy: 0.6471 - F1: 0.6739
sub_11:Test (Best Model) - Loss: 3.1308 - Accuracy: 0.5942 - F1: 0.5659
sub_11:Test (Best Model) - Loss: 3.0033 - Accuracy: 0.6087 - F1: 0.5755
sub_11:Test (Best Model) - Loss: 2.0728 - Accuracy: 0.5942 - F1: 0.5797
sub_11:Test (Best Model) - Loss: 4.5256 - Accuracy: 0.5507 - F1: 0.5445
sub_13:Test (Best Model) - Loss: 3.1545 - Accuracy: 0.3529 - F1: 0.4071
sub_14:Test (Best Model) - Loss: 19.4772 - Accuracy: 0.3529 - F1: 0.2677
sub_15:Test (Best Model) - Loss: 12.1199 - Accuracy: 0.6618 - F1: 0.6622
sub_13:Test (Best Model) - Loss: 3.3555 - Accuracy: 0.4706 - F1: 0.5119
sub_14:Test (Best Model) - Loss: 12.5151 - Accuracy: 0.4118 - F1: 0.3597
sub_15:Test (Best Model) - Loss: 4.3008 - Accuracy: 0.6765 - F1: 0.6507
sub_13:Test (Best Model) - Loss: 6.1012 - Accuracy: 0.3971 - F1: 0.4250
sub_15:Test (Best Model) - Loss: 19.2608 - Accuracy: 0.7794 - F1: 0.7864
sub_14:Test (Best Model) - Loss: 19.0758 - Accuracy: 0.3088 - F1: 0.2031
sub_14:Test (Best Model) - Loss: 15.5564 - Accuracy: 0.3382 - F1: 0.2292
sub_13:Test (Best Model) - Loss: 3.9885 - Accuracy: 0.4118 - F1: 0.4459
sub_15:Test (Best Model) - Loss: 13.7810 - Accuracy: 0.6765 - F1: 0.6582
sub_15:Test (Best Model) - Loss: 9.1134 - Accuracy: 0.6471 - F1: 0.6518
sub_14:Test (Best Model) - Loss: 23.8625 - Accuracy: 0.3971 - F1: 0.3506
sub_13:Test (Best Model) - Loss: 5.0270 - Accuracy: 0.4265 - F1: 0.4504
sub_14:Test (Best Model) - Loss: 9.9361 - Accuracy: 0.6765 - F1: 0.6208
sub_15:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.6618 - F1: 0.6565
sub_15:Test (Best Model) - Loss: 0.8654 - Accuracy: 0.7353 - F1: 0.7356
sub_13:Test (Best Model) - Loss: 12.5075 - Accuracy: 0.5652 - F1: 0.5362
sub_14:Test (Best Model) - Loss: 4.5984 - Accuracy: 0.5441 - F1: 0.5032
sub_15:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.7794 - F1: 0.7897
sub_13:Test (Best Model) - Loss: 12.2587 - Accuracy: 0.4928 - F1: 0.4716
sub_15:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.8235 - F1: 0.8303
sub_14:Test (Best Model) - Loss: 4.0200 - Accuracy: 0.7059 - F1: 0.6471
sub_13:Test (Best Model) - Loss: 11.9376 - Accuracy: 0.4493 - F1: 0.4601
sub_14:Test (Best Model) - Loss: 3.5941 - Accuracy: 0.6176 - F1: 0.5742
sub_15:Test (Best Model) - Loss: 1.0077 - Accuracy: 0.7941 - F1: 0.8026
sub_13:Test (Best Model) - Loss: 21.2277 - Accuracy: 0.4928 - F1: 0.5189
sub_15:Test (Best Model) - Loss: 4.3995 - Accuracy: 0.7206 - F1: 0.7004
sub_14:Test (Best Model) - Loss: 6.2035 - Accuracy: 0.6324 - F1: 0.5691
sub_15:Test (Best Model) - Loss: 2.6862 - Accuracy: 0.6029 - F1: 0.5357
sub_13:Test (Best Model) - Loss: 7.0970 - Accuracy: 0.4928 - F1: 0.5005
sub_14:Test (Best Model) - Loss: 2.0924 - Accuracy: 0.5294 - F1: 0.4805
sub_15:Test (Best Model) - Loss: 7.4555 - Accuracy: 0.5588 - F1: 0.4761
sub_14:Test (Best Model) - Loss: 4.0128 - Accuracy: 0.6471 - F1: 0.6420
sub_13:Test (Best Model) - Loss: 47.3503 - Accuracy: 0.4706 - F1: 0.4199
sub_15:Test (Best Model) - Loss: 4.6743 - Accuracy: 0.7353 - F1: 0.6848
sub_14:Test (Best Model) - Loss: 3.8071 - Accuracy: 0.5294 - F1: 0.4915
sub_13:Test (Best Model) - Loss: 39.8528 - Accuracy: 0.4853 - F1: 0.4394
sub_15:Test (Best Model) - Loss: 5.2267 - Accuracy: 0.6912 - F1: 0.6159
sub_14:Test (Best Model) - Loss: 3.6764 - Accuracy: 0.6029 - F1: 0.5928
sub_13:Test (Best Model) - Loss: 40.6246 - Accuracy: 0.4265 - F1: 0.3905
sub_14:Test (Best Model) - Loss: 5.2297 - Accuracy: 0.4265 - F1: 0.4282
sub_13:Test (Best Model) - Loss: 34.0145 - Accuracy: 0.4559 - F1: 0.4138
sub_13:Test (Best Model) - Loss: 71.3117 - Accuracy: 0.4853 - F1: 0.4446
sub_18:Test (Best Model) - Loss: 11.0053 - Accuracy: 0.5797 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 3.0494 - Accuracy: 0.6324 - F1: 0.6315
sub_17:Test (Best Model) - Loss: 0.9872 - Accuracy: 0.8406 - F1: 0.8403
sub_16:Test (Best Model) - Loss: 2.4295 - Accuracy: 0.5735 - F1: 0.5446
sub_18:Test (Best Model) - Loss: 3.9629 - Accuracy: 0.6667 - F1: 0.5941
sub_17:Test (Best Model) - Loss: 1.5504 - Accuracy: 0.7391 - F1: 0.6798
sub_17:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.6232 - F1: 0.5600
sub_16:Test (Best Model) - Loss: 2.5403 - Accuracy: 0.4412 - F1: 0.4558
sub_18:Test (Best Model) - Loss: 7.8871 - Accuracy: 0.5652 - F1: 0.5242
sub_17:Test (Best Model) - Loss: 4.1390 - Accuracy: 0.7536 - F1: 0.7532
sub_16:Test (Best Model) - Loss: 2.2025 - Accuracy: 0.6176 - F1: 0.5762
sub_18:Test (Best Model) - Loss: 9.2954 - Accuracy: 0.5072 - F1: 0.4715
sub_16:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.6471 - F1: 0.6562
sub_18:Test (Best Model) - Loss: 7.5640 - Accuracy: 0.5652 - F1: 0.5321
sub_17:Test (Best Model) - Loss: 2.4824 - Accuracy: 0.6667 - F1: 0.6128
sub_16:Test (Best Model) - Loss: 6.7758 - Accuracy: 0.4853 - F1: 0.4662
sub_18:Test (Best Model) - Loss: 6.5968 - Accuracy: 0.6765 - F1: 0.6231
sub_17:Test (Best Model) - Loss: 5.8373 - Accuracy: 0.6087 - F1: 0.5746
sub_16:Test (Best Model) - Loss: 9.9829 - Accuracy: 0.4559 - F1: 0.4385
sub_18:Test (Best Model) - Loss: 1.9279 - Accuracy: 0.7206 - F1: 0.7303
sub_17:Test (Best Model) - Loss: 1.9578 - Accuracy: 0.5217 - F1: 0.5015
sub_18:Test (Best Model) - Loss: 2.6995 - Accuracy: 0.6912 - F1: 0.6750
sub_17:Test (Best Model) - Loss: 6.3375 - Accuracy: 0.5362 - F1: 0.5020
sub_16:Test (Best Model) - Loss: 17.7380 - Accuracy: 0.3676 - F1: 0.3477
sub_18:Test (Best Model) - Loss: 3.0638 - Accuracy: 0.6471 - F1: 0.6275
sub_17:Test (Best Model) - Loss: 3.7386 - Accuracy: 0.6232 - F1: 0.6240
sub_16:Test (Best Model) - Loss: 8.5552 - Accuracy: 0.5735 - F1: 0.5477
sub_17:Test (Best Model) - Loss: 3.8752 - Accuracy: 0.4638 - F1: 0.4364
sub_16:Test (Best Model) - Loss: 12.3589 - Accuracy: 0.4118 - F1: 0.4137
sub_18:Test (Best Model) - Loss: 5.1200 - Accuracy: 0.6765 - F1: 0.6422
sub_17:Test (Best Model) - Loss: 2.1993 - Accuracy: 0.6471 - F1: 0.6072
sub_16:Test (Best Model) - Loss: 14.7482 - Accuracy: 0.3971 - F1: 0.3501
sub_18:Test (Best Model) - Loss: 6.2530 - Accuracy: 0.5588 - F1: 0.5893
sub_17:Test (Best Model) - Loss: 3.6459 - Accuracy: 0.7353 - F1: 0.7194
sub_16:Test (Best Model) - Loss: 13.0175 - Accuracy: 0.5294 - F1: 0.5242
sub_18:Test (Best Model) - Loss: 5.1532 - Accuracy: 0.6324 - F1: 0.6518
sub_17:Test (Best Model) - Loss: 7.6701 - Accuracy: 0.6029 - F1: 0.5749
sub_16:Test (Best Model) - Loss: 7.3049 - Accuracy: 0.4706 - F1: 0.4820
sub_18:Test (Best Model) - Loss: 6.8164 - Accuracy: 0.5000 - F1: 0.4919
sub_17:Test (Best Model) - Loss: 7.4840 - Accuracy: 0.6029 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 7.6573 - Accuracy: 0.5294 - F1: 0.4984
sub_17:Test (Best Model) - Loss: 1.4689 - Accuracy: 0.6471 - F1: 0.6276
sub_18:Test (Best Model) - Loss: 4.2411 - Accuracy: 0.6029 - F1: 0.6283
sub_16:Test (Best Model) - Loss: 3.5296 - Accuracy: 0.5882 - F1: 0.5820
sub_18:Test (Best Model) - Loss: 8.0275 - Accuracy: 0.5588 - F1: 0.5442
sub_19:Test (Best Model) - Loss: 12.3522 - Accuracy: 0.4559 - F1: 0.4338
sub_20:Test (Best Model) - Loss: 2.4493 - Accuracy: 0.6029 - F1: 0.5856
sub_21:Test (Best Model) - Loss: 24.8423 - Accuracy: 0.4412 - F1: 0.3850
sub_19:Test (Best Model) - Loss: 7.2557 - Accuracy: 0.3676 - F1: 0.3673
sub_20:Test (Best Model) - Loss: 1.8774 - Accuracy: 0.6029 - F1: 0.5825
sub_21:Test (Best Model) - Loss: 27.6915 - Accuracy: 0.5000 - F1: 0.5104
sub_19:Test (Best Model) - Loss: 5.6512 - Accuracy: 0.3971 - F1: 0.3909
sub_21:Test (Best Model) - Loss: 15.0370 - Accuracy: 0.5000 - F1: 0.5292
sub_19:Test (Best Model) - Loss: 11.2427 - Accuracy: 0.2941 - F1: 0.2581
sub_20:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.6176 - F1: 0.5858
sub_21:Test (Best Model) - Loss: 23.6951 - Accuracy: 0.4706 - F1: 0.4486
sub_20:Test (Best Model) - Loss: 1.1094 - Accuracy: 0.6029 - F1: 0.5849
sub_19:Test (Best Model) - Loss: 8.5311 - Accuracy: 0.3676 - F1: 0.3678
sub_21:Test (Best Model) - Loss: 10.2107 - Accuracy: 0.5147 - F1: 0.5150
sub_19:Test (Best Model) - Loss: 3.5733 - Accuracy: 0.6912 - F1: 0.6944
sub_20:Test (Best Model) - Loss: 2.5266 - Accuracy: 0.5294 - F1: 0.5042
sub_19:Test (Best Model) - Loss: 1.4983 - Accuracy: 0.5588 - F1: 0.5676
sub_21:Test (Best Model) - Loss: 7.2699 - Accuracy: 0.6324 - F1: 0.6132
sub_20:Test (Best Model) - Loss: 1.9152 - Accuracy: 0.7353 - F1: 0.7252
sub_19:Test (Best Model) - Loss: 1.4877 - Accuracy: 0.6324 - F1: 0.5972
sub_21:Test (Best Model) - Loss: 17.4205 - Accuracy: 0.5882 - F1: 0.5795
sub_20:Test (Best Model) - Loss: 1.0991 - Accuracy: 0.7206 - F1: 0.7319
sub_19:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.7647 - F1: 0.7696
sub_20:Test (Best Model) - Loss: 1.2065 - Accuracy: 0.7500 - F1: 0.7660
sub_21:Test (Best Model) - Loss: 7.7675 - Accuracy: 0.6765 - F1: 0.6710
sub_19:Test (Best Model) - Loss: 1.5871 - Accuracy: 0.6471 - F1: 0.6704
sub_20:Test (Best Model) - Loss: 1.5066 - Accuracy: 0.6471 - F1: 0.6551
sub_21:Test (Best Model) - Loss: 24.1464 - Accuracy: 0.5882 - F1: 0.5614
sub_19:Test (Best Model) - Loss: 13.3393 - Accuracy: 0.4559 - F1: 0.4254
sub_20:Test (Best Model) - Loss: 1.2577 - Accuracy: 0.7500 - F1: 0.7546
sub_20:Test (Best Model) - Loss: 1.1955 - Accuracy: 0.6087 - F1: 0.5907
sub_19:Test (Best Model) - Loss: 13.6236 - Accuracy: 0.3971 - F1: 0.3075
sub_21:Test (Best Model) - Loss: 9.9705 - Accuracy: 0.7500 - F1: 0.7352
sub_19:Test (Best Model) - Loss: 13.6203 - Accuracy: 0.3824 - F1: 0.3089
sub_21:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.6765 - F1: 0.6508
sub_20:Test (Best Model) - Loss: 1.2320 - Accuracy: 0.7826 - F1: 0.7945
sub_19:Test (Best Model) - Loss: 13.4551 - Accuracy: 0.4853 - F1: 0.4479
sub_21:Test (Best Model) - Loss: 0.9657 - Accuracy: 0.7500 - F1: 0.7210
sub_20:Test (Best Model) - Loss: 2.0822 - Accuracy: 0.7246 - F1: 0.7288
sub_19:Test (Best Model) - Loss: 4.8906 - Accuracy: 0.5294 - F1: 0.5549
sub_21:Test (Best Model) - Loss: 0.9537 - Accuracy: 0.7647 - F1: 0.7534
sub_20:Test (Best Model) - Loss: 1.7108 - Accuracy: 0.8261 - F1: 0.8321
sub_20:Test (Best Model) - Loss: 0.9131 - Accuracy: 0.7391 - F1: 0.7520
sub_21:Test (Best Model) - Loss: 1.1341 - Accuracy: 0.6324 - F1: 0.6292
sub_21:Test (Best Model) - Loss: 1.5407 - Accuracy: 0.6471 - F1: 0.6109
sub_24:Test (Best Model) - Loss: 3.4638 - Accuracy: 0.5882 - F1: 0.5951
sub_22:Test (Best Model) - Loss: 12.6123 - Accuracy: 0.4706 - F1: 0.3870
sub_23:Test (Best Model) - Loss: 5.3494 - Accuracy: 0.6522 - F1: 0.6086
sub_24:Test (Best Model) - Loss: 3.1971 - Accuracy: 0.6029 - F1: 0.6104
sub_22:Test (Best Model) - Loss: 13.0950 - Accuracy: 0.4412 - F1: 0.3738
sub_23:Test (Best Model) - Loss: 1.7948 - Accuracy: 0.6812 - F1: 0.6907
sub_22:Test (Best Model) - Loss: 13.8664 - Accuracy: 0.4853 - F1: 0.4417
sub_24:Test (Best Model) - Loss: 8.4763 - Accuracy: 0.6176 - F1: 0.6334
sub_23:Test (Best Model) - Loss: 1.6579 - Accuracy: 0.7681 - F1: 0.7676
sub_24:Test (Best Model) - Loss: 2.6225 - Accuracy: 0.5441 - F1: 0.5290
sub_22:Test (Best Model) - Loss: 8.5712 - Accuracy: 0.4706 - F1: 0.4721
sub_24:Test (Best Model) - Loss: 3.2712 - Accuracy: 0.5588 - F1: 0.5379
sub_23:Test (Best Model) - Loss: 2.0864 - Accuracy: 0.5797 - F1: 0.5677
sub_22:Test (Best Model) - Loss: 22.3843 - Accuracy: 0.4118 - F1: 0.3397
sub_23:Test (Best Model) - Loss: 2.3188 - Accuracy: 0.7246 - F1: 0.7395
sub_22:Test (Best Model) - Loss: 3.4789 - Accuracy: 0.4783 - F1: 0.4405
sub_24:Test (Best Model) - Loss: 5.0867 - Accuracy: 0.6029 - F1: 0.6264
sub_23:Test (Best Model) - Loss: 7.2553 - Accuracy: 0.3971 - F1: 0.3341
sub_22:Test (Best Model) - Loss: 2.0345 - Accuracy: 0.5217 - F1: 0.4924
sub_24:Test (Best Model) - Loss: 4.5599 - Accuracy: 0.6618 - F1: 0.6795
sub_23:Test (Best Model) - Loss: 6.4774 - Accuracy: 0.2794 - F1: 0.2014
sub_22:Test (Best Model) - Loss: 2.0692 - Accuracy: 0.5072 - F1: 0.4648
sub_24:Test (Best Model) - Loss: 3.1685 - Accuracy: 0.6176 - F1: 0.6217
sub_23:Test (Best Model) - Loss: 11.2035 - Accuracy: 0.3235 - F1: 0.2499
sub_22:Test (Best Model) - Loss: 2.7430 - Accuracy: 0.5652 - F1: 0.5491
sub_24:Test (Best Model) - Loss: 4.0948 - Accuracy: 0.5588 - F1: 0.5857
sub_23:Test (Best Model) - Loss: 4.4427 - Accuracy: 0.4412 - F1: 0.3842
sub_22:Test (Best Model) - Loss: 4.1159 - Accuracy: 0.4348 - F1: 0.3980
sub_24:Test (Best Model) - Loss: 4.0458 - Accuracy: 0.5441 - F1: 0.5669
sub_23:Test (Best Model) - Loss: 5.7436 - Accuracy: 0.5294 - F1: 0.4693
sub_22:Test (Best Model) - Loss: 13.1445 - Accuracy: 0.4265 - F1: 0.4478
sub_23:Test (Best Model) - Loss: 12.8700 - Accuracy: 0.4058 - F1: 0.3631
sub_24:Test (Best Model) - Loss: 1.1731 - Accuracy: 0.6912 - F1: 0.6928
sub_22:Test (Best Model) - Loss: 11.1558 - Accuracy: 0.6618 - F1: 0.6479
sub_23:Test (Best Model) - Loss: 11.4673 - Accuracy: 0.4638 - F1: 0.4253
sub_24:Test (Best Model) - Loss: 4.5917 - Accuracy: 0.6471 - F1: 0.6539
sub_22:Test (Best Model) - Loss: 7.6396 - Accuracy: 0.5588 - F1: 0.5217
sub_23:Test (Best Model) - Loss: 10.7036 - Accuracy: 0.4203 - F1: 0.3459
sub_24:Test (Best Model) - Loss: 5.0110 - Accuracy: 0.5882 - F1: 0.5600
sub_23:Test (Best Model) - Loss: 9.0171 - Accuracy: 0.4058 - F1: 0.3511
sub_22:Test (Best Model) - Loss: 13.9356 - Accuracy: 0.6324 - F1: 0.5714
sub_24:Test (Best Model) - Loss: 2.8459 - Accuracy: 0.6765 - F1: 0.6679
sub_23:Test (Best Model) - Loss: 21.2130 - Accuracy: 0.4058 - F1: 0.3963
sub_24:Test (Best Model) - Loss: 1.1804 - Accuracy: 0.7500 - F1: 0.7561
sub_22:Test (Best Model) - Loss: 18.1902 - Accuracy: 0.5735 - F1: 0.5801
sub_25:Test (Best Model) - Loss: 4.9754 - Accuracy: 0.8696 - F1: 0.8724
sub_26:Test (Best Model) - Loss: 1.4157 - Accuracy: 0.6812 - F1: 0.6849
sub_27:Test (Best Model) - Loss: 0.9872 - Accuracy: 0.8406 - F1: 0.8403
sub_25:Test (Best Model) - Loss: 3.3490 - Accuracy: 0.7971 - F1: 0.7983
sub_26:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.7101 - F1: 0.7198
sub_27:Test (Best Model) - Loss: 1.5504 - Accuracy: 0.7391 - F1: 0.6798
sub_27:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.6232 - F1: 0.5600
sub_25:Test (Best Model) - Loss: 4.3759 - Accuracy: 0.7536 - F1: 0.7403
sub_26:Test (Best Model) - Loss: 0.8284 - Accuracy: 0.6812 - F1: 0.6967
sub_25:Test (Best Model) - Loss: 7.0634 - Accuracy: 0.7971 - F1: 0.7946
sub_27:Test (Best Model) - Loss: 4.1390 - Accuracy: 0.7536 - F1: 0.7532
sub_26:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.6667 - F1: 0.6747
sub_25:Test (Best Model) - Loss: 6.7655 - Accuracy: 0.7536 - F1: 0.7494
sub_26:Test (Best Model) - Loss: 0.7801 - Accuracy: 0.6522 - F1: 0.6704
sub_27:Test (Best Model) - Loss: 2.4824 - Accuracy: 0.6667 - F1: 0.6128
sub_25:Test (Best Model) - Loss: 1.1958 - Accuracy: 0.7353 - F1: 0.7412
sub_25:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.8088 - F1: 0.8073
sub_26:Test (Best Model) - Loss: 1.1109 - Accuracy: 0.6765 - F1: 0.6532
sub_27:Test (Best Model) - Loss: 5.8373 - Accuracy: 0.6087 - F1: 0.5746
sub_27:Test (Best Model) - Loss: 1.9578 - Accuracy: 0.5217 - F1: 0.5015
sub_25:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.7353 - F1: 0.7258
sub_26:Test (Best Model) - Loss: 2.6721 - Accuracy: 0.6176 - F1: 0.5981
sub_25:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.8529 - F1: 0.8518
sub_27:Test (Best Model) - Loss: 6.3375 - Accuracy: 0.5362 - F1: 0.5020
sub_26:Test (Best Model) - Loss: 2.2969 - Accuracy: 0.5735 - F1: 0.5388
sub_25:Test (Best Model) - Loss: 0.9843 - Accuracy: 0.8382 - F1: 0.8353
sub_27:Test (Best Model) - Loss: 3.7386 - Accuracy: 0.6232 - F1: 0.6240
sub_25:Test (Best Model) - Loss: 9.9768 - Accuracy: 0.6471 - F1: 0.6442
sub_26:Test (Best Model) - Loss: 2.8159 - Accuracy: 0.6176 - F1: 0.5953
sub_27:Test (Best Model) - Loss: 3.8752 - Accuracy: 0.4638 - F1: 0.4364
sub_25:Test (Best Model) - Loss: 4.1878 - Accuracy: 0.6324 - F1: 0.6182
sub_26:Test (Best Model) - Loss: 3.5841 - Accuracy: 0.6029 - F1: 0.5871
sub_27:Test (Best Model) - Loss: 2.1993 - Accuracy: 0.6471 - F1: 0.6072
sub_26:Test (Best Model) - Loss: 2.3562 - Accuracy: 0.5882 - F1: 0.5823
sub_25:Test (Best Model) - Loss: 3.0564 - Accuracy: 0.6912 - F1: 0.6890
sub_27:Test (Best Model) - Loss: 3.6459 - Accuracy: 0.7353 - F1: 0.7194
sub_26:Test (Best Model) - Loss: 3.0445 - Accuracy: 0.7059 - F1: 0.7162
sub_25:Test (Best Model) - Loss: 4.6739 - Accuracy: 0.6324 - F1: 0.6223
sub_27:Test (Best Model) - Loss: 7.6701 - Accuracy: 0.6029 - F1: 0.5749
sub_26:Test (Best Model) - Loss: 16.4890 - Accuracy: 0.4706 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 4.2920 - Accuracy: 0.6618 - F1: 0.6581
sub_27:Test (Best Model) - Loss: 7.4840 - Accuracy: 0.6029 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 5.2950 - Accuracy: 0.7059 - F1: 0.7119
sub_27:Test (Best Model) - Loss: 1.4689 - Accuracy: 0.6471 - F1: 0.6276
sub_26:Test (Best Model) - Loss: 3.9237 - Accuracy: 0.6176 - F1: 0.6199
sub_28:Test (Best Model) - Loss: 5.5944 - Accuracy: 0.5000 - F1: 0.4404
sub_29:Test (Best Model) - Loss: 37.9113 - Accuracy: 0.3971 - F1: 0.4446
sub_28:Test (Best Model) - Loss: 5.7576 - Accuracy: 0.4265 - F1: 0.3694
sub_29:Test (Best Model) - Loss: 25.8508 - Accuracy: 0.4559 - F1: 0.4986
sub_28:Test (Best Model) - Loss: 5.5204 - Accuracy: 0.4559 - F1: 0.4157
sub_29:Test (Best Model) - Loss: 13.2535 - Accuracy: 0.5147 - F1: 0.5181
sub_29:Test (Best Model) - Loss: 26.5199 - Accuracy: 0.5000 - F1: 0.5237
sub_28:Test (Best Model) - Loss: 4.8933 - Accuracy: 0.5147 - F1: 0.4493
sub_28:Test (Best Model) - Loss: 8.8634 - Accuracy: 0.4853 - F1: 0.4388
sub_29:Test (Best Model) - Loss: 20.4564 - Accuracy: 0.3235 - F1: 0.4008
sub_29:Test (Best Model) - Loss: 3.2257 - Accuracy: 0.7941 - F1: 0.8054
sub_28:Test (Best Model) - Loss: 25.1623 - Accuracy: 0.3676 - F1: 0.2620
sub_29:Test (Best Model) - Loss: 3.5617 - Accuracy: 0.6029 - F1: 0.6133
sub_28:Test (Best Model) - Loss: 24.2361 - Accuracy: 0.4118 - F1: 0.3333
sub_29:Test (Best Model) - Loss: 5.6739 - Accuracy: 0.7353 - F1: 0.7397
sub_28:Test (Best Model) - Loss: 14.0936 - Accuracy: 0.3971 - F1: 0.2852
sub_29:Test (Best Model) - Loss: 5.3317 - Accuracy: 0.7059 - F1: 0.6460
sub_28:Test (Best Model) - Loss: 11.6294 - Accuracy: 0.3676 - F1: 0.2982
sub_28:Test (Best Model) - Loss: 21.0883 - Accuracy: 0.3235 - F1: 0.2734
sub_29:Test (Best Model) - Loss: 7.1780 - Accuracy: 0.7206 - F1: 0.7011
sub_29:Test (Best Model) - Loss: 1.1581 - Accuracy: 0.4928 - F1: 0.4961
sub_28:Test (Best Model) - Loss: 36.4495 - Accuracy: 0.4265 - F1: 0.3004
sub_28:Test (Best Model) - Loss: 53.0474 - Accuracy: 0.3676 - F1: 0.3139
sub_29:Test (Best Model) - Loss: 6.6050 - Accuracy: 0.5797 - F1: 0.5354
sub_28:Test (Best Model) - Loss: 24.1263 - Accuracy: 0.4412 - F1: 0.3236
sub_29:Test (Best Model) - Loss: 4.7680 - Accuracy: 0.4348 - F1: 0.4200
sub_28:Test (Best Model) - Loss: 81.2208 - Accuracy: 0.4265 - F1: 0.3169
sub_29:Test (Best Model) - Loss: 5.4207 - Accuracy: 0.5072 - F1: 0.4287
sub_28:Test (Best Model) - Loss: 36.6480 - Accuracy: 0.4118 - F1: 0.2929
sub_29:Test (Best Model) - Loss: 3.3608 - Accuracy: 0.6087 - F1: 0.6057

=== Summary Results ===

acc: 58.82 ± 8.15
F1: 56.70 ± 9.21
acc-in: 87.53 ± 4.31
F1-in: 87.20 ± 4.42
runing time: 2438.81 seconds
