lr: 0.001
sub_3:Test (Best Model) - Loss: 3.5792 - Accuracy: 0.5882 - F1: 0.5251
sub_12:Test (Best Model) - Loss: 0.9019 - Accuracy: 0.7206 - F1: 0.6728
sub_10:Test (Best Model) - Loss: 1.8327 - Accuracy: 0.5735 - F1: 0.5462
sub_4:Test (Best Model) - Loss: 4.1440 - Accuracy: 0.5797 - F1: 0.5636
sub_5:Test (Best Model) - Loss: 3.0824 - Accuracy: 0.6912 - F1: 0.6279
sub_14:Test (Best Model) - Loss: 1.2835 - Accuracy: 0.4706 - F1: 0.3804
sub_6:Test (Best Model) - Loss: 2.5066 - Accuracy: 0.6324 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.9371 - Accuracy: 0.7941 - F1: 0.8039
sub_11:Test (Best Model) - Loss: 1.8907 - Accuracy: 0.6522 - F1: 0.6435
sub_13:Test (Best Model) - Loss: 1.9131 - Accuracy: 0.5441 - F1: 0.4991
sub_1:Test (Best Model) - Loss: 1.1802 - Accuracy: 0.6765 - F1: 0.6682
sub_8:Test (Best Model) - Loss: 3.1574 - Accuracy: 0.6618 - F1: 0.5937
sub_2:Test (Best Model) - Loss: 1.9822 - Accuracy: 0.4638 - F1: 0.4270
sub_14:Test (Best Model) - Loss: 1.7924 - Accuracy: 0.3971 - F1: 0.3141
sub_5:Test (Best Model) - Loss: 1.7852 - Accuracy: 0.3971 - F1: 0.3303
sub_15:Test (Best Model) - Loss: 1.5206 - Accuracy: 0.4853 - F1: 0.4557
sub_9:Test (Best Model) - Loss: 3.4712 - Accuracy: 0.4265 - F1: 0.4081
sub_6:Test (Best Model) - Loss: 5.4562 - Accuracy: 0.3971 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.7826 - F1: 0.7741
sub_1:Test (Best Model) - Loss: 2.2356 - Accuracy: 0.5000 - F1: 0.4693
sub_7:Test (Best Model) - Loss: 3.6110 - Accuracy: 0.6471 - F1: 0.5929
sub_10:Test (Best Model) - Loss: 6.3230 - Accuracy: 0.3529 - F1: 0.3962
sub_3:Test (Best Model) - Loss: 2.5690 - Accuracy: 0.6912 - F1: 0.6386
sub_4:Test (Best Model) - Loss: 1.1087 - Accuracy: 0.6812 - F1: 0.6224
sub_13:Test (Best Model) - Loss: 4.3861 - Accuracy: 0.4706 - F1: 0.3750
sub_2:Test (Best Model) - Loss: 2.1720 - Accuracy: 0.6087 - F1: 0.5600
sub_12:Test (Best Model) - Loss: 2.1814 - Accuracy: 0.7206 - F1: 0.6536
sub_15:Test (Best Model) - Loss: 2.0374 - Accuracy: 0.6029 - F1: 0.5614
sub_9:Test (Best Model) - Loss: 2.3984 - Accuracy: 0.6618 - F1: 0.6898
sub_6:Test (Best Model) - Loss: 6.4863 - Accuracy: 0.4412 - F1: 0.3612
sub_8:Test (Best Model) - Loss: 3.3795 - Accuracy: 0.5294 - F1: 0.5030
sub_10:Test (Best Model) - Loss: 4.9560 - Accuracy: 0.4118 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 4.0608 - Accuracy: 0.5441 - F1: 0.5223
sub_5:Test (Best Model) - Loss: 4.4474 - Accuracy: 0.6176 - F1: 0.5737
sub_7:Test (Best Model) - Loss: 0.2972 - Accuracy: 0.9265 - F1: 0.9210
sub_2:Test (Best Model) - Loss: 2.8075 - Accuracy: 0.4928 - F1: 0.3534
sub_9:Test (Best Model) - Loss: 3.6403 - Accuracy: 0.5000 - F1: 0.4683
sub_14:Test (Best Model) - Loss: 6.6649 - Accuracy: 0.4706 - F1: 0.3750
sub_11:Test (Best Model) - Loss: 3.1511 - Accuracy: 0.7246 - F1: 0.6642
sub_13:Test (Best Model) - Loss: 1.9937 - Accuracy: 0.6912 - F1: 0.6850
sub_4:Test (Best Model) - Loss: 2.2754 - Accuracy: 0.6522 - F1: 0.6200
sub_3:Test (Best Model) - Loss: 1.6985 - Accuracy: 0.7206 - F1: 0.7271
sub_5:Test (Best Model) - Loss: 5.6721 - Accuracy: 0.4118 - F1: 0.3268
sub_2:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.6087 - F1: 0.5555
sub_8:Test (Best Model) - Loss: 3.3393 - Accuracy: 0.4853 - F1: 0.4707
sub_6:Test (Best Model) - Loss: 4.0974 - Accuracy: 0.4118 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 5.6200 - Accuracy: 0.4706 - F1: 0.3681
sub_4:Test (Best Model) - Loss: 1.5268 - Accuracy: 0.5797 - F1: 0.5390
sub_7:Test (Best Model) - Loss: 2.1521 - Accuracy: 0.7206 - F1: 0.6907
sub_3:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.7647 - F1: 0.7564
sub_12:Test (Best Model) - Loss: 2.8087 - Accuracy: 0.6324 - F1: 0.5798
sub_1:Test (Best Model) - Loss: 3.3889 - Accuracy: 0.5147 - F1: 0.4992
sub_9:Test (Best Model) - Loss: 4.2448 - Accuracy: 0.3824 - F1: 0.4432
sub_10:Test (Best Model) - Loss: 2.5564 - Accuracy: 0.4706 - F1: 0.5210
sub_15:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.7500 - F1: 0.7624
sub_2:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.6087 - F1: 0.5275
sub_14:Test (Best Model) - Loss: 7.2821 - Accuracy: 0.3824 - F1: 0.2968
sub_8:Test (Best Model) - Loss: 5.0925 - Accuracy: 0.5000 - F1: 0.4887
sub_5:Test (Best Model) - Loss: 4.1073 - Accuracy: 0.6765 - F1: 0.6088
sub_11:Test (Best Model) - Loss: 1.8009 - Accuracy: 0.8116 - F1: 0.8117
sub_13:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.6029 - F1: 0.5472
sub_9:Test (Best Model) - Loss: 1.1301 - Accuracy: 0.7206 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 1.8580 - Accuracy: 0.7353 - F1: 0.7437
sub_15:Test (Best Model) - Loss: 1.6601 - Accuracy: 0.5882 - F1: 0.5917
sub_7:Test (Best Model) - Loss: 2.3578 - Accuracy: 0.7353 - F1: 0.6459
sub_1:Test (Best Model) - Loss: 1.9360 - Accuracy: 0.5000 - F1: 0.4483
sub_4:Test (Best Model) - Loss: 1.8595 - Accuracy: 0.6957 - F1: 0.6285
sub_6:Test (Best Model) - Loss: 4.7328 - Accuracy: 0.4853 - F1: 0.4319
sub_2:Test (Best Model) - Loss: 1.2725 - Accuracy: 0.5882 - F1: 0.5443
sub_10:Test (Best Model) - Loss: 4.8304 - Accuracy: 0.4412 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.7284 - Accuracy: 0.8116 - F1: 0.8034
sub_8:Test (Best Model) - Loss: 3.1448 - Accuracy: 0.5147 - F1: 0.5012
sub_5:Test (Best Model) - Loss: 0.7987 - Accuracy: 0.7500 - F1: 0.6984
sub_12:Test (Best Model) - Loss: 2.2770 - Accuracy: 0.6176 - F1: 0.6021
sub_7:Test (Best Model) - Loss: 2.7671 - Accuracy: 0.7059 - F1: 0.6891
sub_1:Test (Best Model) - Loss: 1.6922 - Accuracy: 0.6667 - F1: 0.6068
sub_9:Test (Best Model) - Loss: 5.1251 - Accuracy: 0.5000 - F1: 0.4540
sub_13:Test (Best Model) - Loss: 3.1320 - Accuracy: 0.5217 - F1: 0.4521
sub_3:Test (Best Model) - Loss: 3.2710 - Accuracy: 0.6377 - F1: 0.6169
sub_15:Test (Best Model) - Loss: 1.5521 - Accuracy: 0.6029 - F1: 0.5776
sub_6:Test (Best Model) - Loss: 2.1936 - Accuracy: 0.5942 - F1: 0.5606
sub_7:Test (Best Model) - Loss: 1.9106 - Accuracy: 0.7059 - F1: 0.6438
sub_10:Test (Best Model) - Loss: 2.4154 - Accuracy: 0.5735 - F1: 0.5042
sub_11:Test (Best Model) - Loss: 1.7695 - Accuracy: 0.6957 - F1: 0.6343
sub_4:Test (Best Model) - Loss: 0.9557 - Accuracy: 0.7826 - F1: 0.7677
sub_14:Test (Best Model) - Loss: 4.9423 - Accuracy: 0.4412 - F1: 0.3524
sub_2:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.7353 - F1: 0.6975
sub_12:Test (Best Model) - Loss: 2.4907 - Accuracy: 0.6618 - F1: 0.5975
sub_3:Test (Best Model) - Loss: 2.7866 - Accuracy: 0.6812 - F1: 0.6481
sub_5:Test (Best Model) - Loss: 0.3782 - Accuracy: 0.8088 - F1: 0.7924
sub_15:Test (Best Model) - Loss: 2.9465 - Accuracy: 0.6324 - F1: 0.5719
sub_8:Test (Best Model) - Loss: 2.8451 - Accuracy: 0.6471 - F1: 0.5829
sub_9:Test (Best Model) - Loss: 4.4754 - Accuracy: 0.5588 - F1: 0.4912
sub_7:Test (Best Model) - Loss: 3.2148 - Accuracy: 0.6324 - F1: 0.5606
sub_1:Test (Best Model) - Loss: 1.0945 - Accuracy: 0.7101 - F1: 0.6852
sub_14:Test (Best Model) - Loss: 1.8673 - Accuracy: 0.5735 - F1: 0.5810
sub_11:Test (Best Model) - Loss: 3.2070 - Accuracy: 0.5942 - F1: 0.5184
sub_10:Test (Best Model) - Loss: 4.4150 - Accuracy: 0.4706 - F1: 0.4369
sub_3:Test (Best Model) - Loss: 3.4129 - Accuracy: 0.6087 - F1: 0.5723
sub_15:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.6324 - F1: 0.5481
sub_13:Test (Best Model) - Loss: 2.2030 - Accuracy: 0.4638 - F1: 0.4231
sub_6:Test (Best Model) - Loss: 1.6313 - Accuracy: 0.6232 - F1: 0.5882
sub_4:Test (Best Model) - Loss: 0.4892 - Accuracy: 0.9420 - F1: 0.9443
sub_7:Test (Best Model) - Loss: 2.7718 - Accuracy: 0.6912 - F1: 0.6082
sub_2:Test (Best Model) - Loss: 1.7819 - Accuracy: 0.7059 - F1: 0.6584
sub_12:Test (Best Model) - Loss: 1.7503 - Accuracy: 0.6812 - F1: 0.6760
sub_11:Test (Best Model) - Loss: 1.9349 - Accuracy: 0.6377 - F1: 0.5640
sub_8:Test (Best Model) - Loss: 2.4186 - Accuracy: 0.7206 - F1: 0.6766
sub_9:Test (Best Model) - Loss: 2.8025 - Accuracy: 0.6176 - F1: 0.5434
sub_13:Test (Best Model) - Loss: 3.1632 - Accuracy: 0.5362 - F1: 0.5060
sub_14:Test (Best Model) - Loss: 4.2597 - Accuracy: 0.3529 - F1: 0.3472
sub_5:Test (Best Model) - Loss: 1.6897 - Accuracy: 0.7206 - F1: 0.7249
sub_10:Test (Best Model) - Loss: 3.5209 - Accuracy: 0.5000 - F1: 0.4530
sub_1:Test (Best Model) - Loss: 1.2811 - Accuracy: 0.7826 - F1: 0.7904
sub_7:Test (Best Model) - Loss: 3.2704 - Accuracy: 0.6324 - F1: 0.5592
sub_3:Test (Best Model) - Loss: 3.1363 - Accuracy: 0.6377 - F1: 0.5922
sub_11:Test (Best Model) - Loss: 2.0160 - Accuracy: 0.7246 - F1: 0.6923
sub_15:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.9265 - F1: 0.9267
sub_8:Test (Best Model) - Loss: 2.1740 - Accuracy: 0.7059 - F1: 0.6432
sub_5:Test (Best Model) - Loss: 1.7331 - Accuracy: 0.6029 - F1: 0.5365
sub_6:Test (Best Model) - Loss: 1.0372 - Accuracy: 0.5652 - F1: 0.5651
sub_12:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.7536 - F1: 0.7513
sub_7:Test (Best Model) - Loss: 2.4547 - Accuracy: 0.7059 - F1: 0.6296
sub_2:Test (Best Model) - Loss: 3.1409 - Accuracy: 0.6471 - F1: 0.6136
sub_1:Test (Best Model) - Loss: 0.8240 - Accuracy: 0.7826 - F1: 0.7811
sub_9:Test (Best Model) - Loss: 4.0552 - Accuracy: 0.4559 - F1: 0.4077
sub_13:Test (Best Model) - Loss: 3.4607 - Accuracy: 0.4638 - F1: 0.4329
sub_14:Test (Best Model) - Loss: 4.4567 - Accuracy: 0.3971 - F1: 0.3167
sub_11:Test (Best Model) - Loss: 1.1440 - Accuracy: 0.7391 - F1: 0.6982
sub_10:Test (Best Model) - Loss: 2.2894 - Accuracy: 0.5000 - F1: 0.4113
sub_4:Test (Best Model) - Loss: 0.4086 - Accuracy: 0.8986 - F1: 0.9021
sub_3:Test (Best Model) - Loss: 3.4717 - Accuracy: 0.6377 - F1: 0.5944
sub_5:Test (Best Model) - Loss: 1.8076 - Accuracy: 0.6324 - F1: 0.5897
sub_9:Test (Best Model) - Loss: 2.1198 - Accuracy: 0.6912 - F1: 0.6749
sub_13:Test (Best Model) - Loss: 3.0936 - Accuracy: 0.5797 - F1: 0.5002
sub_7:Test (Best Model) - Loss: 4.9779 - Accuracy: 0.4706 - F1: 0.4311
sub_1:Test (Best Model) - Loss: 2.0290 - Accuracy: 0.5942 - F1: 0.5714
sub_8:Test (Best Model) - Loss: 2.5161 - Accuracy: 0.7353 - F1: 0.6572
sub_3:Test (Best Model) - Loss: 2.4631 - Accuracy: 0.7391 - F1: 0.7323
sub_5:Test (Best Model) - Loss: 3.3858 - Accuracy: 0.4706 - F1: 0.3750
sub_15:Test (Best Model) - Loss: 1.1768 - Accuracy: 0.8088 - F1: 0.8175
sub_12:Test (Best Model) - Loss: 1.6429 - Accuracy: 0.7536 - F1: 0.7289
sub_11:Test (Best Model) - Loss: 3.2927 - Accuracy: 0.5942 - F1: 0.5441
sub_4:Test (Best Model) - Loss: 0.3860 - Accuracy: 0.7391 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 4.3256 - Accuracy: 0.4638 - F1: 0.3384
sub_2:Test (Best Model) - Loss: 1.9398 - Accuracy: 0.7059 - F1: 0.6435
sub_7:Test (Best Model) - Loss: 3.3500 - Accuracy: 0.6912 - F1: 0.6211
sub_10:Test (Best Model) - Loss: 2.4303 - Accuracy: 0.4559 - F1: 0.4202
sub_14:Test (Best Model) - Loss: 3.8146 - Accuracy: 0.4118 - F1: 0.4128
sub_3:Test (Best Model) - Loss: 3.1705 - Accuracy: 0.5362 - F1: 0.4561
sub_1:Test (Best Model) - Loss: 0.8720 - Accuracy: 0.7059 - F1: 0.6317
sub_9:Test (Best Model) - Loss: 3.3851 - Accuracy: 0.5735 - F1: 0.5393
sub_15:Test (Best Model) - Loss: 1.6932 - Accuracy: 0.7206 - F1: 0.6355
sub_7:Test (Best Model) - Loss: 2.9541 - Accuracy: 0.4853 - F1: 0.4982
sub_13:Test (Best Model) - Loss: 3.3919 - Accuracy: 0.4412 - F1: 0.3851
sub_8:Test (Best Model) - Loss: 2.1968 - Accuracy: 0.6324 - F1: 0.6404
sub_6:Test (Best Model) - Loss: 1.4018 - Accuracy: 0.5507 - F1: 0.5247
sub_5:Test (Best Model) - Loss: 2.4899 - Accuracy: 0.3382 - F1: 0.2292
sub_4:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.8841 - F1: 0.8818
sub_10:Test (Best Model) - Loss: 2.7432 - Accuracy: 0.7246 - F1: 0.7111
sub_2:Test (Best Model) - Loss: 3.0750 - Accuracy: 0.6377 - F1: 0.5702
sub_14:Test (Best Model) - Loss: 3.4475 - Accuracy: 0.4853 - F1: 0.5289
sub_11:Test (Best Model) - Loss: 3.2689 - Accuracy: 0.6522 - F1: 0.6322
sub_12:Test (Best Model) - Loss: 1.3400 - Accuracy: 0.7971 - F1: 0.8023
sub_9:Test (Best Model) - Loss: 2.8845 - Accuracy: 0.5147 - F1: 0.5185
sub_4:Test (Best Model) - Loss: 1.5492 - Accuracy: 0.6957 - F1: 0.6493
sub_1:Test (Best Model) - Loss: 2.5407 - Accuracy: 0.7059 - F1: 0.6353
sub_10:Test (Best Model) - Loss: 2.3186 - Accuracy: 0.6812 - F1: 0.6018
sub_13:Test (Best Model) - Loss: 3.3979 - Accuracy: 0.4853 - F1: 0.4559
sub_15:Test (Best Model) - Loss: 4.8879 - Accuracy: 0.5882 - F1: 0.5090
sub_8:Test (Best Model) - Loss: 3.6741 - Accuracy: 0.6176 - F1: 0.5811
sub_7:Test (Best Model) - Loss: 1.7533 - Accuracy: 0.7647 - F1: 0.7319
sub_3:Test (Best Model) - Loss: 6.0913 - Accuracy: 0.5797 - F1: 0.5357
sub_11:Test (Best Model) - Loss: 2.2078 - Accuracy: 0.7391 - F1: 0.7229
sub_5:Test (Best Model) - Loss: 2.4979 - Accuracy: 0.6029 - F1: 0.5446
sub_6:Test (Best Model) - Loss: 2.9858 - Accuracy: 0.6667 - F1: 0.6006
sub_13:Test (Best Model) - Loss: 2.8249 - Accuracy: 0.2794 - F1: 0.2054
sub_2:Test (Best Model) - Loss: 4.1635 - Accuracy: 0.4638 - F1: 0.3170
sub_3:Test (Best Model) - Loss: 2.4025 - Accuracy: 0.7391 - F1: 0.7377
sub_7:Test (Best Model) - Loss: 2.1615 - Accuracy: 0.7206 - F1: 0.6942
sub_12:Test (Best Model) - Loss: 2.8072 - Accuracy: 0.6957 - F1: 0.7036
sub_1:Test (Best Model) - Loss: 2.7095 - Accuracy: 0.7059 - F1: 0.6460
sub_8:Test (Best Model) - Loss: 4.2454 - Accuracy: 0.5882 - F1: 0.5672
sub_14:Test (Best Model) - Loss: 2.5652 - Accuracy: 0.7206 - F1: 0.6752
sub_10:Test (Best Model) - Loss: 2.8741 - Accuracy: 0.4783 - F1: 0.4290
sub_11:Test (Best Model) - Loss: 2.3219 - Accuracy: 0.7101 - F1: 0.6756
sub_9:Test (Best Model) - Loss: 3.0288 - Accuracy: 0.5588 - F1: 0.5265
sub_4:Test (Best Model) - Loss: 1.1641 - Accuracy: 0.7246 - F1: 0.6515
sub_5:Test (Best Model) - Loss: 2.5204 - Accuracy: 0.7353 - F1: 0.6564
sub_1:Test (Best Model) - Loss: 1.4826 - Accuracy: 0.7500 - F1: 0.7011
sub_13:Test (Best Model) - Loss: 2.7637 - Accuracy: 0.4559 - F1: 0.3242
sub_3:Test (Best Model) - Loss: 2.3850 - Accuracy: 0.6232 - F1: 0.5866
sub_12:Test (Best Model) - Loss: 1.2585 - Accuracy: 0.3529 - F1: 0.2685
sub_2:Test (Best Model) - Loss: 1.6436 - Accuracy: 0.8116 - F1: 0.8040
sub_15:Test (Best Model) - Loss: 4.8594 - Accuracy: 0.4853 - F1: 0.3707
sub_11:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.7536 - F1: 0.7608
sub_6:Test (Best Model) - Loss: 3.3226 - Accuracy: 0.4783 - F1: 0.4027
sub_8:Test (Best Model) - Loss: 4.0658 - Accuracy: 0.5000 - F1: 0.5247
sub_10:Test (Best Model) - Loss: 4.0258 - Accuracy: 0.5217 - F1: 0.4720
sub_9:Test (Best Model) - Loss: 2.3591 - Accuracy: 0.6029 - F1: 0.6145
sub_14:Test (Best Model) - Loss: 1.1880 - Accuracy: 0.7647 - F1: 0.7706
sub_4:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.7101 - F1: 0.6591
sub_10:Test (Best Model) - Loss: 2.9823 - Accuracy: 0.6812 - F1: 0.6093
sub_12:Test (Best Model) - Loss: 2.3310 - Accuracy: 0.6471 - F1: 0.6144
sub_6:Test (Best Model) - Loss: 1.4906 - Accuracy: 0.5652 - F1: 0.4786
sub_5:Test (Best Model) - Loss: 2.4866 - Accuracy: 0.7794 - F1: 0.7419
sub_2:Test (Best Model) - Loss: 1.0165 - Accuracy: 0.7826 - F1: 0.7839
sub_8:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.5735 - F1: 0.5617
sub_15:Test (Best Model) - Loss: 6.1510 - Accuracy: 0.4853 - F1: 0.3490
sub_1:Test (Best Model) - Loss: 3.3090 - Accuracy: 0.6176 - F1: 0.5816
sub_4:Test (Best Model) - Loss: 0.9737 - Accuracy: 0.6087 - F1: 0.5642
sub_14:Test (Best Model) - Loss: 1.8501 - Accuracy: 0.7941 - F1: 0.7835
sub_2:Test (Best Model) - Loss: 4.8590 - Accuracy: 0.4493 - F1: 0.3995
sub_13:Test (Best Model) - Loss: 2.2841 - Accuracy: 0.6029 - F1: 0.5657
sub_8:Test (Best Model) - Loss: 3.7104 - Accuracy: 0.4118 - F1: 0.4671
sub_12:Test (Best Model) - Loss: 1.7828 - Accuracy: 0.5294 - F1: 0.4684
sub_4:Test (Best Model) - Loss: 0.3642 - Accuracy: 0.7391 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 1.9791 - Accuracy: 0.7101 - F1: 0.6538
sub_15:Test (Best Model) - Loss: 6.3124 - Accuracy: 0.4706 - F1: 0.3619
sub_14:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.7500 - F1: 0.7136
sub_12:Test (Best Model) - Loss: 2.4888 - Accuracy: 0.6029 - F1: 0.5456
sub_15:Test (Best Model) - Loss: 2.2944 - Accuracy: 0.7353 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 2.8570 - Accuracy: 0.6522 - F1: 0.5843
sub_14:Test (Best Model) - Loss: 1.2244 - Accuracy: 0.7647 - F1: 0.7459
sub_12:Test (Best Model) - Loss: 2.5101 - Accuracy: 0.6029 - F1: 0.5798
sub_25:Test (Best Model) - Loss: 0.0811 - Accuracy: 0.9710 - F1: 0.9694
sub_22:Test (Best Model) - Loss: 2.6220 - Accuracy: 0.5294 - F1: 0.4939
sub_26:Test (Best Model) - Loss: 2.6560 - Accuracy: 0.6377 - F1: 0.6484
sub_20:Test (Best Model) - Loss: 1.1269 - Accuracy: 0.7647 - F1: 0.7321
sub_21:Test (Best Model) - Loss: 0.9713 - Accuracy: 0.5588 - F1: 0.5341
sub_16:Test (Best Model) - Loss: 1.4915 - Accuracy: 0.8088 - F1: 0.8128
sub_29:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.6765 - F1: 0.6261
sub_24:Test (Best Model) - Loss: 3.3862 - Accuracy: 0.5588 - F1: 0.5790
sub_28:Test (Best Model) - Loss: 3.8427 - Accuracy: 0.3676 - F1: 0.2685
sub_19:Test (Best Model) - Loss: 6.5639 - Accuracy: 0.2206 - F1: 0.2818
sub_20:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.6176 - F1: 0.5875
sub_26:Test (Best Model) - Loss: 1.7575 - Accuracy: 0.7101 - F1: 0.7220
sub_21:Test (Best Model) - Loss: 2.4167 - Accuracy: 0.7500 - F1: 0.7393
sub_17:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.8406 - F1: 0.8393
sub_18:Test (Best Model) - Loss: 2.7435 - Accuracy: 0.6522 - F1: 0.6340
sub_23:Test (Best Model) - Loss: 1.9904 - Accuracy: 0.7681 - F1: 0.7168
sub_27:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.8406 - F1: 0.8393
sub_16:Test (Best Model) - Loss: 6.0722 - Accuracy: 0.4853 - F1: 0.4356
sub_25:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.9130 - F1: 0.9136
sub_22:Test (Best Model) - Loss: 5.7284 - Accuracy: 0.5000 - F1: 0.4103
sub_24:Test (Best Model) - Loss: 4.6455 - Accuracy: 0.5441 - F1: 0.5438
sub_16:Test (Best Model) - Loss: 3.4190 - Accuracy: 0.7206 - F1: 0.6434
sub_20:Test (Best Model) - Loss: 2.5443 - Accuracy: 0.5882 - F1: 0.5462
sub_23:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.4783 - F1: 0.3750
sub_18:Test (Best Model) - Loss: 2.2195 - Accuracy: 0.7246 - F1: 0.7187
sub_19:Test (Best Model) - Loss: 7.0021 - Accuracy: 0.2647 - F1: 0.2146
sub_29:Test (Best Model) - Loss: 3.1279 - Accuracy: 0.5735 - F1: 0.5474
sub_26:Test (Best Model) - Loss: 4.0395 - Accuracy: 0.5072 - F1: 0.4658
sub_24:Test (Best Model) - Loss: 4.0840 - Accuracy: 0.5588 - F1: 0.5518
sub_28:Test (Best Model) - Loss: 2.2378 - Accuracy: 0.3824 - F1: 0.3599
sub_21:Test (Best Model) - Loss: 2.0472 - Accuracy: 0.7500 - F1: 0.7512
sub_22:Test (Best Model) - Loss: 6.0727 - Accuracy: 0.4706 - F1: 0.3607
sub_17:Test (Best Model) - Loss: 0.9069 - Accuracy: 0.8551 - F1: 0.8570
sub_25:Test (Best Model) - Loss: 1.5852 - Accuracy: 0.8406 - F1: 0.8404
sub_27:Test (Best Model) - Loss: 0.9069 - Accuracy: 0.8551 - F1: 0.8570
sub_16:Test (Best Model) - Loss: 2.9105 - Accuracy: 0.7206 - F1: 0.6648
sub_28:Test (Best Model) - Loss: 2.9905 - Accuracy: 0.4853 - F1: 0.3873
sub_19:Test (Best Model) - Loss: 9.2812 - Accuracy: 0.2353 - F1: 0.2770
sub_21:Test (Best Model) - Loss: 2.1255 - Accuracy: 0.5735 - F1: 0.5405
sub_29:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.6912 - F1: 0.6329
sub_25:Test (Best Model) - Loss: 0.4806 - Accuracy: 0.9275 - F1: 0.9258
sub_23:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.7971 - F1: 0.7816
sub_24:Test (Best Model) - Loss: 3.0027 - Accuracy: 0.5735 - F1: 0.5893
sub_17:Test (Best Model) - Loss: 0.9389 - Accuracy: 0.8841 - F1: 0.8829
sub_16:Test (Best Model) - Loss: 5.2290 - Accuracy: 0.5588 - F1: 0.5365
sub_26:Test (Best Model) - Loss: 2.1737 - Accuracy: 0.7101 - F1: 0.7037
sub_27:Test (Best Model) - Loss: 0.9389 - Accuracy: 0.8841 - F1: 0.8829
sub_20:Test (Best Model) - Loss: 2.7976 - Accuracy: 0.5441 - F1: 0.5046
sub_18:Test (Best Model) - Loss: 2.2918 - Accuracy: 0.7246 - F1: 0.7426
sub_22:Test (Best Model) - Loss: 3.9667 - Accuracy: 0.3971 - F1: 0.3122
sub_19:Test (Best Model) - Loss: 4.4536 - Accuracy: 0.3382 - F1: 0.3512
sub_29:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.6471 - F1: 0.5918
sub_28:Test (Best Model) - Loss: 3.7808 - Accuracy: 0.6029 - F1: 0.5627
sub_16:Test (Best Model) - Loss: 3.6798 - Accuracy: 0.6618 - F1: 0.6081
sub_23:Test (Best Model) - Loss: 2.9331 - Accuracy: 0.5652 - F1: 0.5322
sub_25:Test (Best Model) - Loss: 1.7367 - Accuracy: 0.8551 - F1: 0.8540
sub_20:Test (Best Model) - Loss: 1.7067 - Accuracy: 0.6176 - F1: 0.6132
sub_21:Test (Best Model) - Loss: 1.9986 - Accuracy: 0.6176 - F1: 0.6206
sub_26:Test (Best Model) - Loss: 1.9068 - Accuracy: 0.6087 - F1: 0.5740
sub_18:Test (Best Model) - Loss: 2.5378 - Accuracy: 0.6812 - F1: 0.6568
sub_22:Test (Best Model) - Loss: 2.8955 - Accuracy: 0.4412 - F1: 0.3922
sub_24:Test (Best Model) - Loss: 4.1632 - Accuracy: 0.6029 - F1: 0.5852
sub_16:Test (Best Model) - Loss: 2.4349 - Accuracy: 0.4853 - F1: 0.3901
sub_17:Test (Best Model) - Loss: 1.0201 - Accuracy: 0.7246 - F1: 0.7095
sub_25:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.7353 - F1: 0.7034
sub_21:Test (Best Model) - Loss: 0.8200 - Accuracy: 0.8824 - F1: 0.8828
sub_27:Test (Best Model) - Loss: 1.0201 - Accuracy: 0.7246 - F1: 0.7095
sub_22:Test (Best Model) - Loss: 1.5541 - Accuracy: 0.5362 - F1: 0.4647
sub_29:Test (Best Model) - Loss: 3.7280 - Accuracy: 0.4853 - F1: 0.5309
sub_16:Test (Best Model) - Loss: 3.2809 - Accuracy: 0.7206 - F1: 0.6716
sub_23:Test (Best Model) - Loss: 1.5605 - Accuracy: 0.4928 - F1: 0.4213
sub_17:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.7101 - F1: 0.6330
sub_25:Test (Best Model) - Loss: 2.6064 - Accuracy: 0.5882 - F1: 0.5792
sub_27:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.7101 - F1: 0.6330
sub_21:Test (Best Model) - Loss: 0.2262 - Accuracy: 0.9412 - F1: 0.9437
sub_28:Test (Best Model) - Loss: 3.0737 - Accuracy: 0.5735 - F1: 0.5051
sub_19:Test (Best Model) - Loss: 3.7884 - Accuracy: 0.3529 - F1: 0.3584
sub_18:Test (Best Model) - Loss: 1.8308 - Accuracy: 0.7246 - F1: 0.7051
sub_20:Test (Best Model) - Loss: 0.5402 - Accuracy: 0.7500 - F1: 0.7136
sub_24:Test (Best Model) - Loss: 2.5321 - Accuracy: 0.6912 - F1: 0.6127
sub_26:Test (Best Model) - Loss: 4.7607 - Accuracy: 0.4706 - F1: 0.4281
sub_22:Test (Best Model) - Loss: 3.6316 - Accuracy: 0.5072 - F1: 0.4348
sub_25:Test (Best Model) - Loss: 2.7558 - Accuracy: 0.6618 - F1: 0.6093
sub_16:Test (Best Model) - Loss: 3.3554 - Accuracy: 0.7059 - F1: 0.6876
sub_29:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.7353 - F1: 0.6631
sub_28:Test (Best Model) - Loss: 4.9369 - Accuracy: 0.2500 - F1: 0.1993
sub_23:Test (Best Model) - Loss: 8.9590 - Accuracy: 0.2647 - F1: 0.1925
sub_21:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.6912 - F1: 0.6272
sub_17:Test (Best Model) - Loss: 5.3550 - Accuracy: 0.4783 - F1: 0.3757
sub_27:Test (Best Model) - Loss: 5.3550 - Accuracy: 0.4783 - F1: 0.3757
sub_19:Test (Best Model) - Loss: 3.0204 - Accuracy: 0.6029 - F1: 0.5658
sub_25:Test (Best Model) - Loss: 2.6845 - Accuracy: 0.7059 - F1: 0.7015
sub_18:Test (Best Model) - Loss: 2.8681 - Accuracy: 0.7059 - F1: 0.6677
sub_29:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.7206 - F1: 0.6473
sub_16:Test (Best Model) - Loss: 8.0842 - Accuracy: 0.2353 - F1: 0.1397
sub_23:Test (Best Model) - Loss: 4.3086 - Accuracy: 0.4265 - F1: 0.3157
sub_22:Test (Best Model) - Loss: 1.6868 - Accuracy: 0.5217 - F1: 0.4568
sub_20:Test (Best Model) - Loss: 1.9910 - Accuracy: 0.6618 - F1: 0.5982
sub_19:Test (Best Model) - Loss: 3.9145 - Accuracy: 0.5882 - F1: 0.5699
sub_25:Test (Best Model) - Loss: 1.4971 - Accuracy: 0.8824 - F1: 0.8846
sub_29:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6912 - F1: 0.6162
sub_24:Test (Best Model) - Loss: 2.0017 - Accuracy: 0.6765 - F1: 0.6337
sub_26:Test (Best Model) - Loss: 3.2371 - Accuracy: 0.5147 - F1: 0.5084
sub_21:Test (Best Model) - Loss: 1.4203 - Accuracy: 0.6912 - F1: 0.6596
sub_16:Test (Best Model) - Loss: 2.6851 - Accuracy: 0.7353 - F1: 0.7332
sub_23:Test (Best Model) - Loss: 3.5814 - Accuracy: 0.3676 - F1: 0.2903
sub_18:Test (Best Model) - Loss: 4.3000 - Accuracy: 0.5147 - F1: 0.5457
sub_17:Test (Best Model) - Loss: 3.3162 - Accuracy: 0.5217 - F1: 0.4971
sub_28:Test (Best Model) - Loss: 4.4129 - Accuracy: 0.3235 - F1: 0.2288
sub_29:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.7206 - F1: 0.6507
sub_27:Test (Best Model) - Loss: 3.3162 - Accuracy: 0.5217 - F1: 0.4971
sub_19:Test (Best Model) - Loss: 2.6438 - Accuracy: 0.7059 - F1: 0.7273
sub_21:Test (Best Model) - Loss: 0.5326 - Accuracy: 0.6471 - F1: 0.5749
sub_16:Test (Best Model) - Loss: 3.8215 - Accuracy: 0.5147 - F1: 0.4737
sub_22:Test (Best Model) - Loss: 4.5584 - Accuracy: 0.5507 - F1: 0.5085
sub_20:Test (Best Model) - Loss: 1.0946 - Accuracy: 0.6912 - F1: 0.6797
sub_25:Test (Best Model) - Loss: 3.7337 - Accuracy: 0.6765 - F1: 0.6266
sub_17:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.5362 - F1: 0.4363
sub_24:Test (Best Model) - Loss: 3.0115 - Accuracy: 0.7500 - F1: 0.7062
sub_27:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.5362 - F1: 0.4363
sub_28:Test (Best Model) - Loss: 5.5842 - Accuracy: 0.3971 - F1: 0.3421
sub_18:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.6765 - F1: 0.6743
sub_26:Test (Best Model) - Loss: 2.3760 - Accuracy: 0.5000 - F1: 0.4893
sub_19:Test (Best Model) - Loss: 2.4507 - Accuracy: 0.6176 - F1: 0.5881
sub_29:Test (Best Model) - Loss: 0.4215 - Accuracy: 0.7206 - F1: 0.6565
sub_16:Test (Best Model) - Loss: 1.8450 - Accuracy: 0.8088 - F1: 0.8089
sub_25:Test (Best Model) - Loss: 1.4926 - Accuracy: 0.7647 - F1: 0.7723
sub_21:Test (Best Model) - Loss: 1.5211 - Accuracy: 0.8235 - F1: 0.8045
sub_23:Test (Best Model) - Loss: 4.1654 - Accuracy: 0.5441 - F1: 0.4707
sub_22:Test (Best Model) - Loss: 4.6541 - Accuracy: 0.4638 - F1: 0.4305
sub_16:Test (Best Model) - Loss: 3.0842 - Accuracy: 0.6765 - F1: 0.6283
sub_20:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.7206 - F1: 0.6410
sub_25:Test (Best Model) - Loss: 5.7848 - Accuracy: 0.4706 - F1: 0.5110
sub_17:Test (Best Model) - Loss: 3.5290 - Accuracy: 0.5797 - F1: 0.5329
sub_28:Test (Best Model) - Loss: 3.7330 - Accuracy: 0.3676 - F1: 0.2551
sub_19:Test (Best Model) - Loss: 4.3662 - Accuracy: 0.4706 - F1: 0.3981
sub_27:Test (Best Model) - Loss: 3.5290 - Accuracy: 0.5797 - F1: 0.5329
sub_24:Test (Best Model) - Loss: 2.6194 - Accuracy: 0.6912 - F1: 0.6053
sub_16:Test (Best Model) - Loss: 1.9412 - Accuracy: 0.7500 - F1: 0.7502
sub_29:Test (Best Model) - Loss: 2.8790 - Accuracy: 0.7101 - F1: 0.6671
sub_18:Test (Best Model) - Loss: 3.3879 - Accuracy: 0.5588 - F1: 0.6014
sub_23:Test (Best Model) - Loss: 2.4745 - Accuracy: 0.5294 - F1: 0.4244
sub_21:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.8382 - F1: 0.8228
sub_26:Test (Best Model) - Loss: 6.2984 - Accuracy: 0.3824 - F1: 0.3573
sub_22:Test (Best Model) - Loss: 4.3917 - Accuracy: 0.5294 - F1: 0.5123
sub_19:Test (Best Model) - Loss: 3.7137 - Accuracy: 0.5441 - F1: 0.4804
sub_17:Test (Best Model) - Loss: 1.0809 - Accuracy: 0.4058 - F1: 0.2614
sub_20:Test (Best Model) - Loss: 1.6424 - Accuracy: 0.5000 - F1: 0.3330
sub_27:Test (Best Model) - Loss: 1.0809 - Accuracy: 0.4058 - F1: 0.2614
sub_24:Test (Best Model) - Loss: 2.2430 - Accuracy: 0.6912 - F1: 0.6518
sub_23:Test (Best Model) - Loss: 1.8625 - Accuracy: 0.6522 - F1: 0.5904
sub_28:Test (Best Model) - Loss: 5.1405 - Accuracy: 0.4559 - F1: 0.3838
sub_25:Test (Best Model) - Loss: 3.9365 - Accuracy: 0.6029 - F1: 0.5632
sub_18:Test (Best Model) - Loss: 4.1378 - Accuracy: 0.5588 - F1: 0.5830
sub_29:Test (Best Model) - Loss: 3.1346 - Accuracy: 0.7101 - F1: 0.6435
sub_22:Test (Best Model) - Loss: 2.8593 - Accuracy: 0.5882 - F1: 0.5612
sub_26:Test (Best Model) - Loss: 3.2903 - Accuracy: 0.3382 - F1: 0.3258
sub_20:Test (Best Model) - Loss: 1.2078 - Accuracy: 0.5942 - F1: 0.5734
sub_19:Test (Best Model) - Loss: 2.5886 - Accuracy: 0.4118 - F1: 0.3118
sub_25:Test (Best Model) - Loss: 0.9004 - Accuracy: 0.7353 - F1: 0.6626
sub_24:Test (Best Model) - Loss: 2.2483 - Accuracy: 0.6176 - F1: 0.6154
sub_17:Test (Best Model) - Loss: 3.4051 - Accuracy: 0.6176 - F1: 0.5854
sub_21:Test (Best Model) - Loss: 1.7025 - Accuracy: 0.7794 - F1: 0.7541
sub_20:Test (Best Model) - Loss: 1.5299 - Accuracy: 0.4638 - F1: 0.3791
sub_27:Test (Best Model) - Loss: 3.4051 - Accuracy: 0.6176 - F1: 0.5854
sub_23:Test (Best Model) - Loss: 4.0675 - Accuracy: 0.5652 - F1: 0.5145
sub_22:Test (Best Model) - Loss: 1.8972 - Accuracy: 0.4853 - F1: 0.4208
sub_28:Test (Best Model) - Loss: 2.2069 - Accuracy: 0.3235 - F1: 0.1985
sub_29:Test (Best Model) - Loss: 3.7373 - Accuracy: 0.6377 - F1: 0.5724
sub_19:Test (Best Model) - Loss: 3.7355 - Accuracy: 0.6029 - F1: 0.5182
sub_26:Test (Best Model) - Loss: 2.0692 - Accuracy: 0.6471 - F1: 0.6186
sub_18:Test (Best Model) - Loss: 0.8144 - Accuracy: 0.7941 - F1: 0.7996
sub_17:Test (Best Model) - Loss: 1.4726 - Accuracy: 0.7206 - F1: 0.6899
sub_27:Test (Best Model) - Loss: 1.4726 - Accuracy: 0.7206 - F1: 0.6899
sub_29:Test (Best Model) - Loss: 0.4941 - Accuracy: 0.7246 - F1: 0.6480
sub_28:Test (Best Model) - Loss: 3.5447 - Accuracy: 0.3529 - F1: 0.3184
sub_21:Test (Best Model) - Loss: 1.2822 - Accuracy: 0.8382 - F1: 0.8474
sub_23:Test (Best Model) - Loss: 4.4015 - Accuracy: 0.6087 - F1: 0.5630
sub_17:Test (Best Model) - Loss: 2.1203 - Accuracy: 0.6029 - F1: 0.5559
sub_20:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.7246 - F1: 0.6891
sub_27:Test (Best Model) - Loss: 2.1203 - Accuracy: 0.6029 - F1: 0.5559
sub_24:Test (Best Model) - Loss: 3.8122 - Accuracy: 0.6324 - F1: 0.5829
sub_28:Test (Best Model) - Loss: 4.6273 - Accuracy: 0.3382 - F1: 0.2834
sub_29:Test (Best Model) - Loss: 1.0146 - Accuracy: 0.6667 - F1: 0.6122
sub_17:Test (Best Model) - Loss: 1.6827 - Accuracy: 0.5735 - F1: 0.5120
sub_22:Test (Best Model) - Loss: 2.1849 - Accuracy: 0.7059 - F1: 0.6920
sub_20:Test (Best Model) - Loss: 1.0459 - Accuracy: 0.6812 - F1: 0.6828
sub_27:Test (Best Model) - Loss: 1.6827 - Accuracy: 0.5735 - F1: 0.5120
sub_26:Test (Best Model) - Loss: 2.3080 - Accuracy: 0.6324 - F1: 0.6274
sub_19:Test (Best Model) - Loss: 1.8740 - Accuracy: 0.6765 - F1: 0.6622
sub_18:Test (Best Model) - Loss: 3.0054 - Accuracy: 0.5147 - F1: 0.4957
sub_21:Test (Best Model) - Loss: 2.0902 - Accuracy: 0.7353 - F1: 0.6964
sub_23:Test (Best Model) - Loss: 2.8717 - Accuracy: 0.5942 - F1: 0.5306
sub_17:Test (Best Model) - Loss: 4.4162 - Accuracy: 0.5000 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 4.4162 - Accuracy: 0.5000 - F1: 0.5038
sub_28:Test (Best Model) - Loss: 3.0632 - Accuracy: 0.2500 - F1: 0.2035
sub_24:Test (Best Model) - Loss: 2.7053 - Accuracy: 0.6765 - F1: 0.6165
sub_19:Test (Best Model) - Loss: 6.7122 - Accuracy: 0.3971 - F1: 0.3250
sub_22:Test (Best Model) - Loss: 3.9680 - Accuracy: 0.5735 - F1: 0.5536
sub_20:Test (Best Model) - Loss: 0.9012 - Accuracy: 0.8406 - F1: 0.8400
sub_18:Test (Best Model) - Loss: 1.6662 - Accuracy: 0.5147 - F1: 0.4710
sub_26:Test (Best Model) - Loss: 3.5838 - Accuracy: 0.3824 - F1: 0.4056
sub_23:Test (Best Model) - Loss: 3.1313 - Accuracy: 0.6522 - F1: 0.5905
sub_28:Test (Best Model) - Loss: 2.9580 - Accuracy: 0.4853 - F1: 0.4160
sub_24:Test (Best Model) - Loss: 1.6563 - Accuracy: 0.8088 - F1: 0.8165
sub_18:Test (Best Model) - Loss: 4.1470 - Accuracy: 0.5441 - F1: 0.4840
sub_26:Test (Best Model) - Loss: 1.4658 - Accuracy: 0.7206 - F1: 0.7297
sub_18:Test (Best Model) - Loss: 1.7177 - Accuracy: 0.4559 - F1: 0.3898
sub_24:Test (Best Model) - Loss: 1.2057 - Accuracy: 0.7794 - F1: 0.7781
sub_26:Test (Best Model) - Loss: 3.1128 - Accuracy: 0.2647 - F1: 0.3015

=== Summary Results ===

acc: 61.11 ± 8.19
F1: 57.18 ± 8.83
acc-in: 95.50 ± 3.45
F1-in: 95.26 ± 3.87
