lr: 0.001
sub_1:Test (Best Model) - Loss: 0.8832 - Accuracy: 0.4706 - F1: 0.3750
sub_6:Test (Best Model) - Loss: 1.4548 - Accuracy: 0.5000 - F1: 0.4896
sub_9:Test (Best Model) - Loss: 1.0877 - Accuracy: 0.4412 - F1: 0.3786
sub_4:Test (Best Model) - Loss: 1.7689 - Accuracy: 0.6522 - F1: 0.6294
sub_3:Test (Best Model) - Loss: 0.8760 - Accuracy: 0.4559 - F1: 0.3697
sub_5:Test (Best Model) - Loss: 0.9718 - Accuracy: 0.5588 - F1: 0.5243
sub_8:Test (Best Model) - Loss: 1.5503 - Accuracy: 0.5147 - F1: 0.5139
sub_10:Test (Best Model) - Loss: 2.3504 - Accuracy: 0.3824 - F1: 0.3415
sub_2:Test (Best Model) - Loss: 0.7526 - Accuracy: 0.7101 - F1: 0.6917
sub_6:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.6471 - F1: 0.6134
sub_8:Test (Best Model) - Loss: 0.8114 - Accuracy: 0.6176 - F1: 0.5723
sub_2:Test (Best Model) - Loss: 0.8959 - Accuracy: 0.5507 - F1: 0.4621
sub_7:Test (Best Model) - Loss: 0.4641 - Accuracy: 0.7647 - F1: 0.7692
sub_4:Test (Best Model) - Loss: 2.7790 - Accuracy: 0.3188 - F1: 0.2150
sub_1:Test (Best Model) - Loss: 0.9102 - Accuracy: 0.5882 - F1: 0.5965
sub_8:Test (Best Model) - Loss: 0.8924 - Accuracy: 0.4706 - F1: 0.3681
sub_10:Test (Best Model) - Loss: 2.6950 - Accuracy: 0.5000 - F1: 0.4451
sub_3:Test (Best Model) - Loss: 0.9062 - Accuracy: 0.6618 - F1: 0.6660
sub_5:Test (Best Model) - Loss: 1.8992 - Accuracy: 0.5147 - F1: 0.4931
sub_9:Test (Best Model) - Loss: 1.7053 - Accuracy: 0.4412 - F1: 0.4860
sub_10:Test (Best Model) - Loss: 0.9300 - Accuracy: 0.4412 - F1: 0.3643
sub_6:Test (Best Model) - Loss: 1.6673 - Accuracy: 0.5441 - F1: 0.4996
sub_4:Test (Best Model) - Loss: 0.9584 - Accuracy: 0.5652 - F1: 0.4945
sub_2:Test (Best Model) - Loss: 0.8490 - Accuracy: 0.5507 - F1: 0.4791
sub_8:Test (Best Model) - Loss: 0.9571 - Accuracy: 0.4706 - F1: 0.4063
sub_7:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6471 - F1: 0.6520
sub_3:Test (Best Model) - Loss: 0.8765 - Accuracy: 0.4706 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.3529 - F1: 0.2649
sub_4:Test (Best Model) - Loss: 1.7470 - Accuracy: 0.4058 - F1: 0.3958
sub_8:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.3529 - F1: 0.2741
sub_2:Test (Best Model) - Loss: 0.8972 - Accuracy: 0.6087 - F1: 0.5844
sub_1:Test (Best Model) - Loss: 0.4827 - Accuracy: 0.7941 - F1: 0.8079
sub_7:Test (Best Model) - Loss: 0.8882 - Accuracy: 0.4706 - F1: 0.3768
sub_6:Test (Best Model) - Loss: 3.1605 - Accuracy: 0.4265 - F1: 0.3568
sub_2:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3768 - F1: 0.2893
sub_5:Test (Best Model) - Loss: 1.5331 - Accuracy: 0.4706 - F1: 0.3938
sub_10:Test (Best Model) - Loss: 3.1831 - Accuracy: 0.2647 - F1: 0.1452
sub_4:Test (Best Model) - Loss: 1.0425 - Accuracy: 0.5942 - F1: 0.5630
sub_9:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6471 - F1: 0.6315
sub_3:Test (Best Model) - Loss: 1.0142 - Accuracy: 0.6765 - F1: 0.6975
sub_8:Test (Best Model) - Loss: 0.9061 - Accuracy: 0.5735 - F1: 0.5694
sub_7:Test (Best Model) - Loss: 0.8697 - Accuracy: 0.4853 - F1: 0.4208
sub_6:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.3824 - F1: 0.3018
sub_5:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6471 - F1: 0.6414
sub_2:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.4706 - F1: 0.4134
sub_10:Test (Best Model) - Loss: 2.9518 - Accuracy: 0.3971 - F1: 0.3261
sub_1:Test (Best Model) - Loss: 0.8110 - Accuracy: 0.6176 - F1: 0.6277
sub_8:Test (Best Model) - Loss: 0.9182 - Accuracy: 0.5000 - F1: 0.4394
sub_4:Test (Best Model) - Loss: 1.5859 - Accuracy: 0.5942 - F1: 0.5652
sub_6:Test (Best Model) - Loss: 1.2474 - Accuracy: 0.5217 - F1: 0.4754
sub_9:Test (Best Model) - Loss: 1.0186 - Accuracy: 0.4706 - F1: 0.4188
sub_8:Test (Best Model) - Loss: 0.7894 - Accuracy: 0.5588 - F1: 0.5298
sub_5:Test (Best Model) - Loss: 0.5908 - Accuracy: 0.6471 - F1: 0.6045
sub_1:Test (Best Model) - Loss: 1.3096 - Accuracy: 0.4559 - F1: 0.4174
sub_2:Test (Best Model) - Loss: 0.4888 - Accuracy: 0.7206 - F1: 0.7255
sub_7:Test (Best Model) - Loss: 1.6444 - Accuracy: 0.2500 - F1: 0.2149
sub_3:Test (Best Model) - Loss: 1.4441 - Accuracy: 0.4706 - F1: 0.4646
sub_10:Test (Best Model) - Loss: 1.2168 - Accuracy: 0.6471 - F1: 0.6396
sub_8:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.5294 - F1: 0.4966
sub_6:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6667 - F1: 0.6161
sub_4:Test (Best Model) - Loss: 0.8577 - Accuracy: 0.5072 - F1: 0.4286
sub_5:Test (Best Model) - Loss: 0.5532 - Accuracy: 0.7206 - F1: 0.6528
sub_4:Test (Best Model) - Loss: 0.7636 - Accuracy: 0.5362 - F1: 0.4415
sub_9:Test (Best Model) - Loss: 1.9193 - Accuracy: 0.4265 - F1: 0.3789
sub_3:Test (Best Model) - Loss: 0.9426 - Accuracy: 0.6812 - F1: 0.6256
sub_2:Test (Best Model) - Loss: 0.5445 - Accuracy: 0.7059 - F1: 0.6469
sub_10:Test (Best Model) - Loss: 1.9415 - Accuracy: 0.4853 - F1: 0.3916
sub_8:Test (Best Model) - Loss: 0.5876 - Accuracy: 0.7794 - F1: 0.7898
sub_6:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.4783 - F1: 0.3995
sub_5:Test (Best Model) - Loss: 0.8894 - Accuracy: 0.4706 - F1: 0.3733
sub_7:Test (Best Model) - Loss: 5.3907 - Accuracy: 0.4412 - F1: 0.3683
sub_9:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.4559 - F1: 0.3150
sub_1:Test (Best Model) - Loss: 3.1779 - Accuracy: 0.4203 - F1: 0.3510
sub_4:Test (Best Model) - Loss: 0.8626 - Accuracy: 0.5797 - F1: 0.5298
sub_2:Test (Best Model) - Loss: 0.9242 - Accuracy: 0.5000 - F1: 0.4505
sub_8:Test (Best Model) - Loss: 0.8936 - Accuracy: 0.7206 - F1: 0.6954
sub_3:Test (Best Model) - Loss: 1.5328 - Accuracy: 0.6087 - F1: 0.5442
sub_6:Test (Best Model) - Loss: 1.1345 - Accuracy: 0.4348 - F1: 0.3687
sub_9:Test (Best Model) - Loss: 1.2855 - Accuracy: 0.4706 - F1: 0.3690
sub_10:Test (Best Model) - Loss: 4.3932 - Accuracy: 0.3824 - F1: 0.3124
sub_1:Test (Best Model) - Loss: 1.7847 - Accuracy: 0.3333 - F1: 0.3208
sub_4:Test (Best Model) - Loss: 1.2558 - Accuracy: 0.3333 - F1: 0.2830
sub_6:Test (Best Model) - Loss: 0.8318 - Accuracy: 0.4783 - F1: 0.4711
sub_7:Test (Best Model) - Loss: 2.9919 - Accuracy: 0.4265 - F1: 0.3726
sub_5:Test (Best Model) - Loss: 3.1323 - Accuracy: 0.4265 - F1: 0.3480
sub_9:Test (Best Model) - Loss: 1.4605 - Accuracy: 0.4412 - F1: 0.3051
sub_3:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.5217 - F1: 0.5001
sub_2:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.7353 - F1: 0.7446
sub_8:Test (Best Model) - Loss: 0.8997 - Accuracy: 0.7206 - F1: 0.7225
sub_4:Test (Best Model) - Loss: 0.9718 - Accuracy: 0.4348 - F1: 0.3472
sub_10:Test (Best Model) - Loss: 1.1501 - Accuracy: 0.5147 - F1: 0.4969
sub_1:Test (Best Model) - Loss: 1.9907 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 0.8513 - Accuracy: 0.5000 - F1: 0.3599
sub_2:Test (Best Model) - Loss: 1.2261 - Accuracy: 0.3913 - F1: 0.2716
sub_9:Test (Best Model) - Loss: 1.2552 - Accuracy: 0.2353 - F1: 0.1833
sub_4:Test (Best Model) - Loss: 0.9076 - Accuracy: 0.5797 - F1: 0.5205
sub_6:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.5362 - F1: 0.4668
sub_8:Test (Best Model) - Loss: 0.9121 - Accuracy: 0.6618 - F1: 0.5678
sub_2:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.6377 - F1: 0.5611
sub_1:Test (Best Model) - Loss: 0.9559 - Accuracy: 0.4493 - F1: 0.3538
sub_7:Test (Best Model) - Loss: 4.5335 - Accuracy: 0.3529 - F1: 0.2700
sub_4:Test (Best Model) - Loss: 1.9404 - Accuracy: 0.3913 - F1: 0.2736
sub_5:Test (Best Model) - Loss: 1.0303 - Accuracy: 0.4118 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 1.8712 - Accuracy: 0.3333 - F1: 0.2309
sub_3:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.7101 - F1: 0.6422
sub_10:Test (Best Model) - Loss: 2.2255 - Accuracy: 0.4853 - F1: 0.4644
sub_6:Test (Best Model) - Loss: 2.0819 - Accuracy: 0.3043 - F1: 0.1700
sub_9:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.4853 - F1: 0.3866
sub_8:Test (Best Model) - Loss: 0.2739 - Accuracy: 0.8824 - F1: 0.8871
sub_10:Test (Best Model) - Loss: 0.9840 - Accuracy: 0.4493 - F1: 0.3571
sub_3:Test (Best Model) - Loss: 1.9742 - Accuracy: 0.4348 - F1: 0.3391
sub_6:Test (Best Model) - Loss: 1.1463 - Accuracy: 0.3913 - F1: 0.2969
sub_2:Test (Best Model) - Loss: 1.9033 - Accuracy: 0.3478 - F1: 0.3186
sub_4:Test (Best Model) - Loss: 0.4979 - Accuracy: 0.6812 - F1: 0.6400
sub_5:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.6029 - F1: 0.5558
sub_7:Test (Best Model) - Loss: 1.9178 - Accuracy: 0.4706 - F1: 0.4772
sub_1:Test (Best Model) - Loss: 3.0449 - Accuracy: 0.3043 - F1: 0.2745
sub_6:Test (Best Model) - Loss: 1.4043 - Accuracy: 0.2754 - F1: 0.1437
sub_10:Test (Best Model) - Loss: 1.0681 - Accuracy: 0.4638 - F1: 0.3893
sub_8:Test (Best Model) - Loss: 1.2374 - Accuracy: 0.5294 - F1: 0.4966
sub_2:Test (Best Model) - Loss: 1.1056 - Accuracy: 0.5217 - F1: 0.4607
sub_3:Test (Best Model) - Loss: 0.8631 - Accuracy: 0.4638 - F1: 0.4226
sub_4:Test (Best Model) - Loss: 0.9299 - Accuracy: 0.6667 - F1: 0.5841
sub_5:Test (Best Model) - Loss: 0.7988 - Accuracy: 0.6176 - F1: 0.6308
sub_1:Test (Best Model) - Loss: 0.8805 - Accuracy: 0.4853 - F1: 0.4042
sub_2:Test (Best Model) - Loss: 2.1588 - Accuracy: 0.3623 - F1: 0.3308
sub_9:Test (Best Model) - Loss: 1.1748 - Accuracy: 0.5882 - F1: 0.5367
sub_10:Test (Best Model) - Loss: 1.8417 - Accuracy: 0.5362 - F1: 0.5009
sub_7:Test (Best Model) - Loss: 3.6203 - Accuracy: 0.3382 - F1: 0.2639
sub_3:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.5072 - F1: 0.4454
sub_10:Test (Best Model) - Loss: 0.9817 - Accuracy: 0.7246 - F1: 0.7108
sub_9:Test (Best Model) - Loss: 2.0155 - Accuracy: 0.3971 - F1: 0.2545
sub_5:Test (Best Model) - Loss: 0.8196 - Accuracy: 0.7647 - F1: 0.7495
sub_7:Test (Best Model) - Loss: 1.1513 - Accuracy: 0.3971 - F1: 0.3659
sub_1:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.7206 - F1: 0.7014
sub_9:Test (Best Model) - Loss: 1.1661 - Accuracy: 0.3382 - F1: 0.2026
sub_10:Test (Best Model) - Loss: 1.5331 - Accuracy: 0.5072 - F1: 0.5190
sub_5:Test (Best Model) - Loss: 2.0852 - Accuracy: 0.4412 - F1: 0.3965
sub_7:Test (Best Model) - Loss: 2.0479 - Accuracy: 0.6765 - F1: 0.6037
sub_3:Test (Best Model) - Loss: 1.7536 - Accuracy: 0.6522 - F1: 0.5739
sub_1:Test (Best Model) - Loss: 0.9462 - Accuracy: 0.7059 - F1: 0.6992
sub_9:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.6618 - F1: 0.6575
sub_3:Test (Best Model) - Loss: 1.4524 - Accuracy: 0.6377 - F1: 0.5794
sub_9:Test (Best Model) - Loss: 1.7650 - Accuracy: 0.3235 - F1: 0.2069
sub_1:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.8676 - F1: 0.8695
sub_7:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.7206 - F1: 0.6698
sub_3:Test (Best Model) - Loss: 0.9770 - Accuracy: 0.7101 - F1: 0.6876
sub_7:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.5000 - F1: 0.4830
sub_1:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.7647 - F1: 0.7678
sub_7:Test (Best Model) - Loss: 1.3566 - Accuracy: 0.3971 - F1: 0.4181
sub_18:Test (Best Model) - Loss: 0.8682 - Accuracy: 0.4348 - F1: 0.3587
sub_12:Test (Best Model) - Loss: 1.0473 - Accuracy: 0.4265 - F1: 0.3596
sub_20:Test (Best Model) - Loss: 1.4387 - Accuracy: 0.6324 - F1: 0.5959
sub_14:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.7647 - F1: 0.7461
sub_15:Test (Best Model) - Loss: 0.9798 - Accuracy: 0.4412 - F1: 0.3524
sub_16:Test (Best Model) - Loss: 1.8212 - Accuracy: 0.4559 - F1: 0.4011
sub_19:Test (Best Model) - Loss: 1.8511 - Accuracy: 0.3382 - F1: 0.2111
sub_18:Test (Best Model) - Loss: 0.8580 - Accuracy: 0.4783 - F1: 0.3750
sub_11:Test (Best Model) - Loss: 0.9037 - Accuracy: 0.5652 - F1: 0.5129
sub_12:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.6618 - F1: 0.6870
sub_17:Test (Best Model) - Loss: 0.8740 - Accuracy: 0.4783 - F1: 0.3970
sub_20:Test (Best Model) - Loss: 0.5005 - Accuracy: 0.8235 - F1: 0.8203
sub_15:Test (Best Model) - Loss: 0.5823 - Accuracy: 0.7059 - F1: 0.7261
sub_18:Test (Best Model) - Loss: 0.8630 - Accuracy: 0.4783 - F1: 0.3750
sub_14:Test (Best Model) - Loss: 2.1644 - Accuracy: 0.3529 - F1: 0.2885
sub_13:Test (Best Model) - Loss: 4.4366 - Accuracy: 0.2206 - F1: 0.1125
sub_16:Test (Best Model) - Loss: 2.4233 - Accuracy: 0.4265 - F1: 0.3775
sub_12:Test (Best Model) - Loss: 0.9087 - Accuracy: 0.4559 - F1: 0.3657
sub_20:Test (Best Model) - Loss: 1.0008 - Accuracy: 0.4412 - F1: 0.3524
sub_17:Test (Best Model) - Loss: 0.5202 - Accuracy: 0.8406 - F1: 0.8421
sub_18:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.4783 - F1: 0.3750
sub_19:Test (Best Model) - Loss: 1.2550 - Accuracy: 0.5588 - F1: 0.5297
sub_11:Test (Best Model) - Loss: 0.9036 - Accuracy: 0.5072 - F1: 0.4377
sub_13:Test (Best Model) - Loss: 4.3848 - Accuracy: 0.3382 - F1: 0.2301
sub_12:Test (Best Model) - Loss: 0.9386 - Accuracy: 0.4559 - F1: 0.3640
sub_14:Test (Best Model) - Loss: 2.9194 - Accuracy: 0.4118 - F1: 0.3609
sub_16:Test (Best Model) - Loss: 0.8277 - Accuracy: 0.5441 - F1: 0.5066
sub_15:Test (Best Model) - Loss: 0.7530 - Accuracy: 0.6765 - F1: 0.6677
sub_18:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.6377 - F1: 0.5986
sub_20:Test (Best Model) - Loss: 0.8993 - Accuracy: 0.5735 - F1: 0.5934
sub_17:Test (Best Model) - Loss: 0.8751 - Accuracy: 0.5072 - F1: 0.4224
sub_14:Test (Best Model) - Loss: 1.5464 - Accuracy: 0.3382 - F1: 0.2441
sub_19:Test (Best Model) - Loss: 2.1294 - Accuracy: 0.4118 - F1: 0.3268
sub_13:Test (Best Model) - Loss: 2.1397 - Accuracy: 0.2941 - F1: 0.2096
sub_12:Test (Best Model) - Loss: 1.2343 - Accuracy: 0.3824 - F1: 0.2972
sub_18:Test (Best Model) - Loss: 0.8600 - Accuracy: 0.4706 - F1: 0.3750
sub_16:Test (Best Model) - Loss: 1.9823 - Accuracy: 0.3676 - F1: 0.3233
sub_11:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.7826 - F1: 0.7799
sub_15:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.6618 - F1: 0.6874
sub_14:Test (Best Model) - Loss: 2.4817 - Accuracy: 0.4118 - F1: 0.3951
sub_19:Test (Best Model) - Loss: 2.9270 - Accuracy: 0.4265 - F1: 0.3419
sub_20:Test (Best Model) - Loss: 3.2529 - Accuracy: 0.4412 - F1: 0.3847
sub_12:Test (Best Model) - Loss: 0.8923 - Accuracy: 0.4783 - F1: 0.3964
sub_17:Test (Best Model) - Loss: 1.0817 - Accuracy: 0.6377 - F1: 0.5998
sub_16:Test (Best Model) - Loss: 1.8530 - Accuracy: 0.3676 - F1: 0.2806
sub_13:Test (Best Model) - Loss: 8.3291 - Accuracy: 0.2206 - F1: 0.1151
sub_18:Test (Best Model) - Loss: 0.9603 - Accuracy: 0.4412 - F1: 0.3558
sub_11:Test (Best Model) - Loss: 0.8724 - Accuracy: 0.5362 - F1: 0.5033
sub_12:Test (Best Model) - Loss: 1.1347 - Accuracy: 0.4203 - F1: 0.3300
sub_19:Test (Best Model) - Loss: 1.1076 - Accuracy: 0.4265 - F1: 0.3561
sub_15:Test (Best Model) - Loss: 1.1124 - Accuracy: 0.6471 - F1: 0.6578
sub_14:Test (Best Model) - Loss: 1.5333 - Accuracy: 0.5294 - F1: 0.4855
sub_16:Test (Best Model) - Loss: 1.1215 - Accuracy: 0.4118 - F1: 0.3932
sub_13:Test (Best Model) - Loss: 2.6140 - Accuracy: 0.4559 - F1: 0.3548
sub_17:Test (Best Model) - Loss: 0.9603 - Accuracy: 0.5362 - F1: 0.4636
sub_20:Test (Best Model) - Loss: 1.2837 - Accuracy: 0.7059 - F1: 0.6726
sub_11:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.6377 - F1: 0.6003
sub_19:Test (Best Model) - Loss: 0.9747 - Accuracy: 0.4559 - F1: 0.3565
sub_18:Test (Best Model) - Loss: 2.2700 - Accuracy: 0.4559 - F1: 0.3814
sub_15:Test (Best Model) - Loss: 0.8761 - Accuracy: 0.4706 - F1: 0.3750
sub_12:Test (Best Model) - Loss: 1.1589 - Accuracy: 0.4348 - F1: 0.3633
sub_17:Test (Best Model) - Loss: 0.8829 - Accuracy: 0.4928 - F1: 0.4031
sub_16:Test (Best Model) - Loss: 1.2616 - Accuracy: 0.2353 - F1: 0.2653
sub_13:Test (Best Model) - Loss: 1.6669 - Accuracy: 0.4493 - F1: 0.4398
sub_15:Test (Best Model) - Loss: 0.8652 - Accuracy: 0.4853 - F1: 0.4208
sub_12:Test (Best Model) - Loss: 1.1704 - Accuracy: 0.4203 - F1: 0.3300
sub_18:Test (Best Model) - Loss: 0.9054 - Accuracy: 0.4706 - F1: 0.3750
sub_16:Test (Best Model) - Loss: 1.2230 - Accuracy: 0.3676 - F1: 0.3003
sub_20:Test (Best Model) - Loss: 0.5187 - Accuracy: 0.7647 - F1: 0.7737
sub_19:Test (Best Model) - Loss: 1.7715 - Accuracy: 0.5588 - F1: 0.5288
sub_17:Test (Best Model) - Loss: 2.8513 - Accuracy: 0.3478 - F1: 0.3010
sub_14:Test (Best Model) - Loss: 1.9485 - Accuracy: 0.6176 - F1: 0.5586
sub_11:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.7246 - F1: 0.7367
sub_12:Test (Best Model) - Loss: 1.4839 - Accuracy: 0.5942 - F1: 0.5878
sub_16:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.3971 - F1: 0.3161
sub_19:Test (Best Model) - Loss: 0.9448 - Accuracy: 0.4559 - F1: 0.3953
sub_15:Test (Best Model) - Loss: 0.5695 - Accuracy: 0.7353 - F1: 0.7543
sub_17:Test (Best Model) - Loss: 0.8470 - Accuracy: 0.4638 - F1: 0.3801
sub_13:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.2464 - F1: 0.1701
sub_18:Test (Best Model) - Loss: 0.9120 - Accuracy: 0.5147 - F1: 0.4519
sub_12:Test (Best Model) - Loss: 0.9687 - Accuracy: 0.3676 - F1: 0.3769
sub_14:Test (Best Model) - Loss: 0.3161 - Accuracy: 0.9118 - F1: 0.9132
sub_17:Test (Best Model) - Loss: 1.0676 - Accuracy: 0.4638 - F1: 0.3647
sub_11:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.5797 - F1: 0.5569
sub_18:Test (Best Model) - Loss: 0.9195 - Accuracy: 0.4559 - F1: 0.3657
sub_13:Test (Best Model) - Loss: 1.4768 - Accuracy: 0.3043 - F1: 0.2561
sub_19:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.5147 - F1: 0.4952
sub_15:Test (Best Model) - Loss: 0.8529 - Accuracy: 0.6029 - F1: 0.5772
sub_16:Test (Best Model) - Loss: 3.4043 - Accuracy: 0.2206 - F1: 0.2621
sub_12:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.5147 - F1: 0.4505
sub_14:Test (Best Model) - Loss: 1.5090 - Accuracy: 0.3529 - F1: 0.2729
sub_20:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.7794 - F1: 0.7936
sub_13:Test (Best Model) - Loss: 0.8954 - Accuracy: 0.5362 - F1: 0.4876
sub_17:Test (Best Model) - Loss: 3.6491 - Accuracy: 0.4058 - F1: 0.3670
sub_16:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.3676 - F1: 0.2645
sub_11:Test (Best Model) - Loss: 1.2264 - Accuracy: 0.4783 - F1: 0.3996
sub_15:Test (Best Model) - Loss: 0.9949 - Accuracy: 0.6324 - F1: 0.6353
sub_18:Test (Best Model) - Loss: 0.8984 - Accuracy: 0.5294 - F1: 0.5545
sub_19:Test (Best Model) - Loss: 1.2146 - Accuracy: 0.4559 - F1: 0.4623
sub_20:Test (Best Model) - Loss: 0.8886 - Accuracy: 0.4559 - F1: 0.3714
sub_12:Test (Best Model) - Loss: 0.8880 - Accuracy: 0.4706 - F1: 0.4514
sub_17:Test (Best Model) - Loss: 1.0908 - Accuracy: 0.4118 - F1: 0.3268
sub_14:Test (Best Model) - Loss: 0.7897 - Accuracy: 0.7059 - F1: 0.6069
sub_15:Test (Best Model) - Loss: 1.0288 - Accuracy: 0.4412 - F1: 0.3541
sub_11:Test (Best Model) - Loss: 0.9233 - Accuracy: 0.4783 - F1: 0.4166
sub_18:Test (Best Model) - Loss: 1.0645 - Accuracy: 0.5147 - F1: 0.4707
sub_16:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.4559 - F1: 0.4274
sub_17:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.4118 - F1: 0.3300
sub_19:Test (Best Model) - Loss: 2.6738 - Accuracy: 0.3529 - F1: 0.3790
sub_13:Test (Best Model) - Loss: 3.5542 - Accuracy: 0.3623 - F1: 0.2717
sub_16:Test (Best Model) - Loss: 2.6511 - Accuracy: 0.2647 - F1: 0.1154
sub_12:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.5000 - F1: 0.4432
sub_18:Test (Best Model) - Loss: 1.0374 - Accuracy: 0.5000 - F1: 0.4812
sub_11:Test (Best Model) - Loss: 1.5030 - Accuracy: 0.5072 - F1: 0.4839
sub_15:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.7647 - F1: 0.7826
sub_12:Test (Best Model) - Loss: 0.8770 - Accuracy: 0.4706 - F1: 0.3750
sub_14:Test (Best Model) - Loss: 1.2634 - Accuracy: 0.6618 - F1: 0.6570
sub_19:Test (Best Model) - Loss: 1.1288 - Accuracy: 0.5294 - F1: 0.5506
sub_20:Test (Best Model) - Loss: 0.8517 - Accuracy: 0.7500 - F1: 0.7339
sub_13:Test (Best Model) - Loss: 1.4337 - Accuracy: 0.3529 - F1: 0.2940
sub_17:Test (Best Model) - Loss: 0.7685 - Accuracy: 0.6471 - F1: 0.5782
sub_16:Test (Best Model) - Loss: 1.6274 - Accuracy: 0.2794 - F1: 0.2813
sub_14:Test (Best Model) - Loss: 1.8352 - Accuracy: 0.5735 - F1: 0.5220
sub_18:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.4412 - F1: 0.3869
sub_17:Test (Best Model) - Loss: 1.0111 - Accuracy: 0.4412 - F1: 0.3524
sub_11:Test (Best Model) - Loss: 1.2692 - Accuracy: 0.6667 - F1: 0.6439
sub_15:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.7941 - F1: 0.7957
sub_19:Test (Best Model) - Loss: 1.1955 - Accuracy: 0.5147 - F1: 0.5221
sub_13:Test (Best Model) - Loss: 1.0329 - Accuracy: 0.4853 - F1: 0.4482
sub_20:Test (Best Model) - Loss: 0.9002 - Accuracy: 0.6232 - F1: 0.5738
sub_16:Test (Best Model) - Loss: 4.4456 - Accuracy: 0.2941 - F1: 0.1961
sub_17:Test (Best Model) - Loss: 0.9666 - Accuracy: 0.4412 - F1: 0.3524
sub_14:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.6176 - F1: 0.5935
sub_15:Test (Best Model) - Loss: 0.8775 - Accuracy: 0.4706 - F1: 0.3750
sub_19:Test (Best Model) - Loss: 1.1930 - Accuracy: 0.5000 - F1: 0.4538
sub_11:Test (Best Model) - Loss: 0.9794 - Accuracy: 0.5362 - F1: 0.5137
sub_20:Test (Best Model) - Loss: 1.0400 - Accuracy: 0.5652 - F1: 0.5784
sub_19:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.5588 - F1: 0.5667
sub_14:Test (Best Model) - Loss: 0.8360 - Accuracy: 0.7794 - F1: 0.7840
sub_13:Test (Best Model) - Loss: 1.5413 - Accuracy: 0.5294 - F1: 0.4785
sub_15:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.7794 - F1: 0.7802
sub_20:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.7101 - F1: 0.6846
sub_13:Test (Best Model) - Loss: 0.8235 - Accuracy: 0.5882 - F1: 0.5283
sub_11:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.4493 - F1: 0.4536
sub_14:Test (Best Model) - Loss: 2.7210 - Accuracy: 0.4265 - F1: 0.3864
sub_20:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.7101 - F1: 0.7138
sub_13:Test (Best Model) - Loss: 1.8976 - Accuracy: 0.4706 - F1: 0.3768
sub_11:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.6667 - F1: 0.6480
sub_20:Test (Best Model) - Loss: 0.8692 - Accuracy: 0.7246 - F1: 0.7330
sub_11:Test (Best Model) - Loss: 1.6680 - Accuracy: 0.5217 - F1: 0.5071
sub_25:Test (Best Model) - Loss: 1.2375 - Accuracy: 0.4493 - F1: 0.4092
sub_23:Test (Best Model) - Loss: 0.9416 - Accuracy: 0.4638 - F1: 0.3647
sub_26:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.4058 - F1: 0.3109
sub_29:Test (Best Model) - Loss: 1.0066 - Accuracy: 0.4265 - F1: 0.3416
sub_21:Test (Best Model) - Loss: 1.1752 - Accuracy: 0.5000 - F1: 0.4716
sub_22:Test (Best Model) - Loss: 1.0236 - Accuracy: 0.4265 - F1: 0.3827
sub_24:Test (Best Model) - Loss: 0.9172 - Accuracy: 0.5588 - F1: 0.5214
sub_27:Test (Best Model) - Loss: 0.8740 - Accuracy: 0.4783 - F1: 0.3970
sub_28:Test (Best Model) - Loss: 0.9734 - Accuracy: 0.6029 - F1: 0.5856
sub_29:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.6324 - F1: 0.6589
sub_26:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6957 - F1: 0.7089
sub_21:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.6029 - F1: 0.5020
sub_25:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.7101 - F1: 0.7154
sub_24:Test (Best Model) - Loss: 0.7531 - Accuracy: 0.6029 - F1: 0.5584
sub_23:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.4928 - F1: 0.4419
sub_27:Test (Best Model) - Loss: 0.5202 - Accuracy: 0.8406 - F1: 0.8421
sub_29:Test (Best Model) - Loss: 0.8656 - Accuracy: 0.5000 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 1.0826 - Accuracy: 0.4265 - F1: 0.3400
sub_26:Test (Best Model) - Loss: 0.9834 - Accuracy: 0.5507 - F1: 0.5224
sub_22:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.6029 - F1: 0.5875
sub_28:Test (Best Model) - Loss: 0.9813 - Accuracy: 0.6029 - F1: 0.5891
sub_25:Test (Best Model) - Loss: 0.9387 - Accuracy: 0.4058 - F1: 0.3923
sub_23:Test (Best Model) - Loss: 0.9229 - Accuracy: 0.4638 - F1: 0.3700
sub_24:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.6324 - F1: 0.5826
sub_22:Test (Best Model) - Loss: 0.9996 - Accuracy: 0.4412 - F1: 0.3541
sub_29:Test (Best Model) - Loss: 0.8779 - Accuracy: 0.5147 - F1: 0.4555
sub_27:Test (Best Model) - Loss: 0.8751 - Accuracy: 0.5072 - F1: 0.4224
sub_28:Test (Best Model) - Loss: 1.0585 - Accuracy: 0.5147 - F1: 0.4359
sub_25:Test (Best Model) - Loss: 0.9184 - Accuracy: 0.6232 - F1: 0.5517
sub_21:Test (Best Model) - Loss: 1.2004 - Accuracy: 0.7647 - F1: 0.7632
sub_22:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6912 - F1: 0.6710
sub_29:Test (Best Model) - Loss: 0.9985 - Accuracy: 0.5147 - F1: 0.5527
sub_25:Test (Best Model) - Loss: 1.4399 - Accuracy: 0.3768 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 1.0844 - Accuracy: 0.4348 - F1: 0.3653
sub_26:Test (Best Model) - Loss: 0.8403 - Accuracy: 0.7391 - F1: 0.7245
sub_24:Test (Best Model) - Loss: 0.8495 - Accuracy: 0.5588 - F1: 0.5147
sub_28:Test (Best Model) - Loss: 1.0140 - Accuracy: 0.4706 - F1: 0.3960
sub_22:Test (Best Model) - Loss: 1.0985 - Accuracy: 0.3676 - F1: 0.3717
sub_27:Test (Best Model) - Loss: 1.0817 - Accuracy: 0.6377 - F1: 0.5998
sub_23:Test (Best Model) - Loss: 1.0460 - Accuracy: 0.4058 - F1: 0.3296
sub_21:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.3088 - F1: 0.2375
sub_25:Test (Best Model) - Loss: 1.5737 - Accuracy: 0.2941 - F1: 0.1918
sub_29:Test (Best Model) - Loss: 1.2999 - Accuracy: 0.5000 - F1: 0.4278
sub_22:Test (Best Model) - Loss: 0.9131 - Accuracy: 0.5217 - F1: 0.4638
sub_26:Test (Best Model) - Loss: 0.9224 - Accuracy: 0.5362 - F1: 0.4824
sub_23:Test (Best Model) - Loss: 1.7768 - Accuracy: 0.4412 - F1: 0.3208
sub_25:Test (Best Model) - Loss: 2.0015 - Accuracy: 0.2794 - F1: 0.1636
sub_27:Test (Best Model) - Loss: 0.9603 - Accuracy: 0.5362 - F1: 0.4636
sub_29:Test (Best Model) - Loss: 0.8931 - Accuracy: 0.4706 - F1: 0.3681
sub_28:Test (Best Model) - Loss: 3.3578 - Accuracy: 0.3824 - F1: 0.2972
sub_22:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.4928 - F1: 0.4398
sub_24:Test (Best Model) - Loss: 0.8901 - Accuracy: 0.6176 - F1: 0.5463
sub_21:Test (Best Model) - Loss: 1.5826 - Accuracy: 0.3235 - F1: 0.2454
sub_23:Test (Best Model) - Loss: 0.9748 - Accuracy: 0.4559 - F1: 0.3471
sub_27:Test (Best Model) - Loss: 0.8829 - Accuracy: 0.4928 - F1: 0.4031
sub_26:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.3235 - F1: 0.2317
sub_28:Test (Best Model) - Loss: 3.8025 - Accuracy: 0.2647 - F1: 0.2294
sub_29:Test (Best Model) - Loss: 0.4824 - Accuracy: 0.7059 - F1: 0.6422
sub_25:Test (Best Model) - Loss: 1.3075 - Accuracy: 0.5588 - F1: 0.5436
sub_24:Test (Best Model) - Loss: 0.8369 - Accuracy: 0.6765 - F1: 0.6670
sub_26:Test (Best Model) - Loss: 0.9937 - Accuracy: 0.4559 - F1: 0.3548
sub_22:Test (Best Model) - Loss: 2.8568 - Accuracy: 0.2609 - F1: 0.1084
sub_27:Test (Best Model) - Loss: 2.8513 - Accuracy: 0.3478 - F1: 0.3010
sub_21:Test (Best Model) - Loss: 0.9405 - Accuracy: 0.7647 - F1: 0.7441
sub_23:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.2500 - F1: 0.2645
sub_29:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.7206 - F1: 0.7012
sub_25:Test (Best Model) - Loss: 0.9298 - Accuracy: 0.6324 - F1: 0.6360
sub_27:Test (Best Model) - Loss: 0.8470 - Accuracy: 0.4638 - F1: 0.3801
sub_26:Test (Best Model) - Loss: 0.8603 - Accuracy: 0.5147 - F1: 0.4568
sub_23:Test (Best Model) - Loss: 0.9876 - Accuracy: 0.4412 - F1: 0.4208
sub_28:Test (Best Model) - Loss: 2.1619 - Accuracy: 0.3971 - F1: 0.3065
sub_24:Test (Best Model) - Loss: 0.9132 - Accuracy: 0.5588 - F1: 0.5528
sub_22:Test (Best Model) - Loss: 1.9238 - Accuracy: 0.4348 - F1: 0.3664
sub_26:Test (Best Model) - Loss: 0.8766 - Accuracy: 0.4853 - F1: 0.4031
sub_21:Test (Best Model) - Loss: 0.7423 - Accuracy: 0.6029 - F1: 0.5633
sub_27:Test (Best Model) - Loss: 1.0676 - Accuracy: 0.4638 - F1: 0.3647
sub_24:Test (Best Model) - Loss: 1.1847 - Accuracy: 0.4265 - F1: 0.3618
sub_28:Test (Best Model) - Loss: 2.5996 - Accuracy: 0.3676 - F1: 0.2717
sub_29:Test (Best Model) - Loss: 0.5228 - Accuracy: 0.7353 - F1: 0.6599
sub_21:Test (Best Model) - Loss: 1.0880 - Accuracy: 0.4265 - F1: 0.3400
sub_22:Test (Best Model) - Loss: 2.7242 - Accuracy: 0.3768 - F1: 0.2989
sub_23:Test (Best Model) - Loss: 1.8577 - Accuracy: 0.4265 - F1: 0.3803
sub_24:Test (Best Model) - Loss: 0.9326 - Accuracy: 0.4853 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 0.9167 - Accuracy: 0.6471 - F1: 0.6372
sub_28:Test (Best Model) - Loss: 1.1308 - Accuracy: 0.3824 - F1: 0.3337
sub_29:Test (Best Model) - Loss: 0.8575 - Accuracy: 0.6812 - F1: 0.6239
sub_21:Test (Best Model) - Loss: 0.5895 - Accuracy: 0.6765 - F1: 0.6365
sub_27:Test (Best Model) - Loss: 3.6491 - Accuracy: 0.4058 - F1: 0.3670
sub_26:Test (Best Model) - Loss: 4.0413 - Accuracy: 0.4706 - F1: 0.4015
sub_23:Test (Best Model) - Loss: 1.1389 - Accuracy: 0.3623 - F1: 0.3521
sub_29:Test (Best Model) - Loss: 0.8954 - Accuracy: 0.5507 - F1: 0.4769
sub_22:Test (Best Model) - Loss: 1.7317 - Accuracy: 0.6471 - F1: 0.6664
sub_23:Test (Best Model) - Loss: 1.9025 - Accuracy: 0.2754 - F1: 0.1397
sub_24:Test (Best Model) - Loss: 0.9973 - Accuracy: 0.6912 - F1: 0.6915
sub_27:Test (Best Model) - Loss: 1.0908 - Accuracy: 0.4118 - F1: 0.3268
sub_26:Test (Best Model) - Loss: 0.9073 - Accuracy: 0.4559 - F1: 0.3640
sub_25:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.7353 - F1: 0.7249
sub_28:Test (Best Model) - Loss: 2.9466 - Accuracy: 0.2500 - F1: 0.1278
sub_23:Test (Best Model) - Loss: 1.4410 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 2.1284 - Accuracy: 0.3478 - F1: 0.3062
sub_22:Test (Best Model) - Loss: 1.3304 - Accuracy: 0.4265 - F1: 0.3433
sub_27:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.4118 - F1: 0.3300
sub_21:Test (Best Model) - Loss: 1.0729 - Accuracy: 0.7500 - F1: 0.7467
sub_24:Test (Best Model) - Loss: 0.9871 - Accuracy: 0.6029 - F1: 0.5797
sub_26:Test (Best Model) - Loss: 1.1218 - Accuracy: 0.3824 - F1: 0.3301
sub_28:Test (Best Model) - Loss: 1.3478 - Accuracy: 0.4265 - F1: 0.3867
sub_29:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.2754 - F1: 0.2049
sub_25:Test (Best Model) - Loss: 1.3237 - Accuracy: 0.6471 - F1: 0.5857
sub_23:Test (Best Model) - Loss: 1.8713 - Accuracy: 0.5072 - F1: 0.4726
sub_28:Test (Best Model) - Loss: 2.3823 - Accuracy: 0.1765 - F1: 0.1072
sub_21:Test (Best Model) - Loss: 1.0228 - Accuracy: 0.5000 - F1: 0.4228
sub_27:Test (Best Model) - Loss: 0.7685 - Accuracy: 0.6471 - F1: 0.5782
sub_22:Test (Best Model) - Loss: 3.6202 - Accuracy: 0.2647 - F1: 0.2819
sub_26:Test (Best Model) - Loss: 1.9400 - Accuracy: 0.5147 - F1: 0.4911
sub_29:Test (Best Model) - Loss: 0.8830 - Accuracy: 0.4783 - F1: 0.3750
sub_23:Test (Best Model) - Loss: 1.1158 - Accuracy: 0.4493 - F1: 0.4256
sub_28:Test (Best Model) - Loss: 2.1342 - Accuracy: 0.4412 - F1: 0.3503
sub_24:Test (Best Model) - Loss: 2.9191 - Accuracy: 0.3235 - F1: 0.2070
sub_27:Test (Best Model) - Loss: 1.0111 - Accuracy: 0.4412 - F1: 0.3524
sub_21:Test (Best Model) - Loss: 1.8696 - Accuracy: 0.4118 - F1: 0.2900
sub_25:Test (Best Model) - Loss: 1.0660 - Accuracy: 0.4265 - F1: 0.3703
sub_26:Test (Best Model) - Loss: 0.9502 - Accuracy: 0.4559 - F1: 0.3657
sub_21:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.3676 - F1: 0.2806
sub_22:Test (Best Model) - Loss: 0.7922 - Accuracy: 0.6765 - F1: 0.6697
sub_24:Test (Best Model) - Loss: 1.8204 - Accuracy: 0.2647 - F1: 0.1200
sub_27:Test (Best Model) - Loss: 0.9666 - Accuracy: 0.4412 - F1: 0.3524
sub_28:Test (Best Model) - Loss: 1.6327 - Accuracy: 0.2794 - F1: 0.2483
sub_25:Test (Best Model) - Loss: 0.7900 - Accuracy: 0.7206 - F1: 0.7291
sub_28:Test (Best Model) - Loss: 3.8547 - Accuracy: 0.2206 - F1: 0.1172
sub_26:Test (Best Model) - Loss: 1.5279 - Accuracy: 0.6765 - F1: 0.6207
sub_24:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.5588 - F1: 0.5169
sub_22:Test (Best Model) - Loss: 0.9383 - Accuracy: 0.4706 - F1: 0.4093
sub_21:Test (Best Model) - Loss: 4.6725 - Accuracy: 0.4265 - F1: 0.3177
sub_24:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.3382 - F1: 0.2411
sub_25:Test (Best Model) - Loss: 1.9159 - Accuracy: 0.3824 - F1: 0.3786

=== Summary Results ===

acc: 50.68 ± 6.65
F1: 45.45 ± 7.69
acc-in: 67.68 ± 6.68
F1-in: 63.40 ± 8.07
runing time: 1117.37 seconds
