lr: 0.0001
sub_3:Test (Best Model) - Loss: 3.0608 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.9062 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 0.9624 - Accuracy: 0.6364 - F1: 0.6278
sub_3:Test (Best Model) - Loss: 2.4070 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.9053 - Accuracy: 0.7273 - F1: 0.7263
sub_3:Test (Best Model) - Loss: 5.8314 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 1.1738 - Accuracy: 0.6364 - F1: 0.6333
sub_1:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.8438 - F1: 0.8398
sub_3:Test (Best Model) - Loss: 2.8121 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6667 - F1: 0.6617
sub_1:Test (Best Model) - Loss: 0.5430 - Accuracy: 0.8750 - F1: 0.8704
sub_3:Test (Best Model) - Loss: 3.9788 - Accuracy: 0.9062 - F1: 0.9015
sub_2:Test (Best Model) - Loss: 1.2173 - Accuracy: 0.6364 - F1: 0.6278
sub_1:Test (Best Model) - Loss: 0.4392 - Accuracy: 0.9062 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.7481 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.3355 - Accuracy: 0.9062 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.5367 - Accuracy: 0.7576 - F1: 0.7574
sub_1:Test (Best Model) - Loss: 0.4279 - Accuracy: 0.9697 - F1: 0.9692
sub_3:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.6667 - F1: 0.6617
sub_1:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.7879 - F1: 0.7847
sub_2:Test (Best Model) - Loss: 0.4226 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.7576 - F1: 0.7519
sub_3:Test (Best Model) - Loss: 0.1974 - Accuracy: 0.9394 - F1: 0.9389
sub_3:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.6667 - F1: 0.6553
sub_1:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.8788 - F1: 0.8759
sub_2:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.9062 - F1: 0.9062
sub_3:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.9697 - F1: 0.9692
sub_3:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.7879 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.3702 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.8750 - F1: 0.8750
sub_3:Test (Best Model) - Loss: 0.8448 - Accuracy: 0.7273 - F1: 0.6857
sub_2:Test (Best Model) - Loss: 0.3507 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4338 - Accuracy: 0.9062 - F1: 0.9015
sub_3:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.7879 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.5758 - F1: 0.5227
sub_1:Test (Best Model) - Loss: 0.4108 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.9724 - Accuracy: 0.8182 - F1: 0.8036
sub_2:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.5420 - Accuracy: 0.8438 - F1: 0.8436
sub_1:Test (Best Model) - Loss: 0.5091 - Accuracy: 0.9688 - F1: 0.9685
sub_2:Test (Best Model) - Loss: 0.3258 - Accuracy: 0.9091 - F1: 0.9060
sub_2:Test (Best Model) - Loss: 0.7595 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.5009 - Accuracy: 0.6970 - F1: 0.6967
sub_5:Test (Best Model) - Loss: 0.1674 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.3731 - Accuracy: 0.9394 - F1: 0.9389
sub_6:Test (Best Model) - Loss: 0.3714 - Accuracy: 0.7812 - F1: 0.7810
sub_5:Test (Best Model) - Loss: 0.2822 - Accuracy: 0.8438 - F1: 0.8303
sub_4:Test (Best Model) - Loss: 0.3747 - Accuracy: 0.8182 - F1: 0.8096
sub_6:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.6875 - F1: 0.6863
sub_5:Test (Best Model) - Loss: 0.2073 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.8485 - F1: 0.8433
sub_5:Test (Best Model) - Loss: 0.2685 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.9572 - Accuracy: 0.7812 - F1: 0.7810
sub_4:Test (Best Model) - Loss: 0.4909 - Accuracy: 0.7879 - F1: 0.7806
sub_5:Test (Best Model) - Loss: 0.1796 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.6120 - Accuracy: 0.6970 - F1: 0.6944
sub_6:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.8438 - F1: 0.8436
sub_5:Test (Best Model) - Loss: 0.4526 - Accuracy: 0.8125 - F1: 0.8095
sub_6:Test (Best Model) - Loss: 1.6524 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 1.6523 - Accuracy: 0.4242 - F1: 0.3660
sub_5:Test (Best Model) - Loss: 0.3782 - Accuracy: 0.8125 - F1: 0.8095
sub_4:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.6061 - F1: 0.6046
sub_6:Test (Best Model) - Loss: 1.6584 - Accuracy: 0.4848 - F1: 0.4848
sub_5:Test (Best Model) - Loss: 0.3395 - Accuracy: 0.9062 - F1: 0.9062
sub_4:Test (Best Model) - Loss: 0.8153 - Accuracy: 0.4545 - F1: 0.4107
sub_6:Test (Best Model) - Loss: 0.9995 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.4144 - Accuracy: 0.9062 - F1: 0.9062
sub_4:Test (Best Model) - Loss: 0.7901 - Accuracy: 0.4545 - F1: 0.4288
sub_5:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.7812 - F1: 0.7793
sub_4:Test (Best Model) - Loss: 0.7726 - Accuracy: 0.4545 - F1: 0.4107
sub_6:Test (Best Model) - Loss: 1.2735 - Accuracy: 0.6667 - F1: 0.6654
sub_5:Test (Best Model) - Loss: 0.3649 - Accuracy: 0.8438 - F1: 0.8359
sub_6:Test (Best Model) - Loss: 1.4453 - Accuracy: 0.2424 - F1: 0.2165
sub_5:Test (Best Model) - Loss: 0.5164 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 3.8973 - Accuracy: 0.5455 - F1: 0.5387
sub_5:Test (Best Model) - Loss: 0.3376 - Accuracy: 0.8438 - F1: 0.8359
sub_6:Test (Best Model) - Loss: 1.2877 - Accuracy: 0.2727 - F1: 0.2556
sub_4:Test (Best Model) - Loss: 1.1672 - Accuracy: 0.6364 - F1: 0.6360
sub_5:Test (Best Model) - Loss: 0.5560 - Accuracy: 0.9688 - F1: 0.9680
sub_6:Test (Best Model) - Loss: 0.3484 - Accuracy: 0.8182 - F1: 0.8139
sub_5:Test (Best Model) - Loss: 0.4955 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 1.1077 - Accuracy: 0.6061 - F1: 0.6046
sub_6:Test (Best Model) - Loss: 0.7301 - Accuracy: 0.7879 - F1: 0.7847
sub_4:Test (Best Model) - Loss: 1.6510 - Accuracy: 0.4545 - F1: 0.4500
sub_6:Test (Best Model) - Loss: 0.9975 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7622 - Accuracy: 0.5152 - F1: 0.5147
sub_6:Test (Best Model) - Loss: 1.0303 - Accuracy: 0.3939 - F1: 0.3654
sub_6:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.6061 - F1: 0.5926
sub_7:Test (Best Model) - Loss: 0.0668 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.4507 - Accuracy: 0.8438 - F1: 0.8436
sub_9:Test (Best Model) - Loss: 0.3825 - Accuracy: 0.7812 - F1: 0.7793
sub_7:Test (Best Model) - Loss: 0.1919 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5000 - F1: 0.4667
sub_7:Test (Best Model) - Loss: 0.0528 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.7668 - Accuracy: 0.4062 - F1: 0.4057
sub_9:Test (Best Model) - Loss: 0.4483 - Accuracy: 0.7812 - F1: 0.7703
sub_7:Test (Best Model) - Loss: 0.1663 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.8106 - Accuracy: 0.4375 - F1: 0.4000
sub_9:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.6875 - F1: 0.6875
sub_8:Test (Best Model) - Loss: 1.2081 - Accuracy: 0.3125 - F1: 0.2874
sub_7:Test (Best Model) - Loss: 0.0076 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.8125 - F1: 0.7922
sub_7:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.7812 - F1: 0.7519
sub_7:Test (Best Model) - Loss: 0.3327 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.5641 - Accuracy: 0.7812 - F1: 0.7703
sub_8:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.8750 - F1: 0.8745
sub_7:Test (Best Model) - Loss: 0.3069 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.1791 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.8876 - Accuracy: 0.7500 - F1: 0.7500
sub_7:Test (Best Model) - Loss: 0.3164 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.1988 - Accuracy: 0.9062 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.7500 - F1: 0.7500
sub_7:Test (Best Model) - Loss: 0.4892 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.1828 - Accuracy: 0.9688 - F1: 0.9685
sub_7:Test (Best Model) - Loss: 0.4222 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.3752 - Accuracy: 0.8750 - F1: 0.8667
sub_7:Test (Best Model) - Loss: 0.3611 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.3624 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.4358 - Accuracy: 0.8438 - F1: 0.8359
sub_8:Test (Best Model) - Loss: 0.2922 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3491 - Accuracy: 0.9062 - F1: 0.9062
sub_7:Test (Best Model) - Loss: 0.2755 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.3749 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.2538 - Accuracy: 0.8125 - F1: 0.8095
sub_7:Test (Best Model) - Loss: 0.2792 - Accuracy: 0.9062 - F1: 0.9015
sub_8:Test (Best Model) - Loss: 0.4709 - Accuracy: 0.8750 - F1: 0.8730
sub_9:Test (Best Model) - Loss: 0.3355 - Accuracy: 0.8125 - F1: 0.8000
sub_8:Test (Best Model) - Loss: 0.4571 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 1.1096 - Accuracy: 0.3750 - F1: 0.3074
sub_9:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.5938 - F1: 0.5934
sub_11:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.5455 - F1: 0.4995
sub_10:Test (Best Model) - Loss: 0.2316 - Accuracy: 0.9062 - F1: 0.9062
sub_12:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4688 - F1: 0.3637
sub_11:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.6061 - F1: 0.5815
sub_10:Test (Best Model) - Loss: 0.2946 - Accuracy: 0.9062 - F1: 0.9054
sub_11:Test (Best Model) - Loss: 0.8980 - Accuracy: 0.4848 - F1: 0.4063
sub_12:Test (Best Model) - Loss: 0.4084 - Accuracy: 0.7812 - F1: 0.7810
sub_11:Test (Best Model) - Loss: 0.9862 - Accuracy: 0.6061 - F1: 0.5926
sub_12:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7130 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.6562 - F1: 0.6532
sub_10:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.8125 - F1: 0.8095
sub_12:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.5938 - F1: 0.5934
sub_11:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.6970 - F1: 0.6827
sub_12:Test (Best Model) - Loss: 0.9990 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.4779 - Accuracy: 0.9062 - F1: 0.9062
sub_11:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.6364 - F1: 0.6071
sub_12:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.3043 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.9162 - Accuracy: 0.8485 - F1: 0.8462
sub_11:Test (Best Model) - Loss: 0.4751 - Accuracy: 0.8182 - F1: 0.8180
sub_11:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6667 - F1: 0.6459
sub_10:Test (Best Model) - Loss: 1.6776 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.8640 - Accuracy: 0.6970 - F1: 0.6726
sub_12:Test (Best Model) - Loss: 0.8834 - Accuracy: 0.6667 - F1: 0.6617
sub_10:Test (Best Model) - Loss: 0.4184 - Accuracy: 0.9062 - F1: 0.9015
sub_12:Test (Best Model) - Loss: 1.5652 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.8182 - F1: 0.8167
sub_10:Test (Best Model) - Loss: 1.8910 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.7420 - Accuracy: 0.7188 - F1: 0.7117
sub_11:Test (Best Model) - Loss: 0.9285 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 1.8064 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.7564 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.3761 - Accuracy: 0.9091 - F1: 0.9088
sub_10:Test (Best Model) - Loss: 0.3878 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 1.0598 - Accuracy: 0.5000 - F1: 0.4667
sub_10:Test (Best Model) - Loss: 1.3309 - Accuracy: 0.4848 - F1: 0.3718
sub_11:Test (Best Model) - Loss: 0.4671 - Accuracy: 0.8485 - F1: 0.8479
sub_12:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.7188 - F1: 0.7185
sub_10:Test (Best Model) - Loss: 0.2547 - Accuracy: 0.8485 - F1: 0.8390
sub_11:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.1603 - Accuracy: 0.9091 - F1: 0.9077
sub_11:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.6970 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 0.5610 - Accuracy: 0.8788 - F1: 0.8787
sub_10:Test (Best Model) - Loss: 0.3175 - Accuracy: 0.9091 - F1: 0.9060
sub_13:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 2.3297 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.9062 - F1: 0.9015
sub_15:Test (Best Model) - Loss: 0.4852 - Accuracy: 0.8438 - F1: 0.8398
sub_14:Test (Best Model) - Loss: 1.1231 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 0.3365 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.7812 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 0.5802 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 3.5438 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.4083 - Accuracy: 0.8438 - F1: 0.8303
sub_14:Test (Best Model) - Loss: 2.2290 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.5848 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 2.3697 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.4800 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.2536 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.7188 - F1: 0.7163
sub_13:Test (Best Model) - Loss: 0.3503 - Accuracy: 0.8182 - F1: 0.8036
sub_15:Test (Best Model) - Loss: 0.3084 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.6055 - Accuracy: 0.7812 - F1: 0.7810
sub_13:Test (Best Model) - Loss: 0.1609 - Accuracy: 0.9394 - F1: 0.9380
sub_14:Test (Best Model) - Loss: 0.5050 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.4423 - Accuracy: 0.9375 - F1: 0.9365
sub_13:Test (Best Model) - Loss: 0.2821 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.1987 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 15.8887 - Accuracy: 0.7812 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.2769 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 7.4240 - Accuracy: 0.7188 - F1: 0.6632
sub_15:Test (Best Model) - Loss: 0.4130 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 0.4231 - Accuracy: 0.9375 - F1: 0.9365
sub_13:Test (Best Model) - Loss: 4.9248 - Accuracy: 0.6250 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.9688 - F1: 0.9685
sub_13:Test (Best Model) - Loss: 7.5649 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.4120 - Accuracy: 0.9062 - F1: 0.9062
sub_15:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.9062 - F1: 0.9054
sub_13:Test (Best Model) - Loss: 12.4932 - Accuracy: 0.6562 - F1: 0.5594
sub_15:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.2431 - Accuracy: 0.9062 - F1: 0.9062
sub_15:Test (Best Model) - Loss: 0.5826 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.5396 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.9338 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 1.9481 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.3180 - Accuracy: 0.8788 - F1: 0.8731
sub_16:Test (Best Model) - Loss: 0.5109 - Accuracy: 0.8125 - F1: 0.8000
sub_17:Test (Best Model) - Loss: 0.3631 - Accuracy: 0.8788 - F1: 0.8778
sub_18:Test (Best Model) - Loss: 0.3600 - Accuracy: 0.8182 - F1: 0.8036
sub_16:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.9062 - F1: 0.9039
sub_17:Test (Best Model) - Loss: 0.5390 - Accuracy: 0.8182 - F1: 0.8180
sub_17:Test (Best Model) - Loss: 0.7717 - Accuracy: 0.8485 - F1: 0.8479
sub_16:Test (Best Model) - Loss: 0.4320 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.8788 - F1: 0.8787
sub_17:Test (Best Model) - Loss: 0.5335 - Accuracy: 0.7576 - F1: 0.7462
sub_18:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.7273 - F1: 0.7102
sub_16:Test (Best Model) - Loss: 0.5271 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.5042 - Accuracy: 0.7273 - F1: 0.7102
sub_17:Test (Best Model) - Loss: 0.4156 - Accuracy: 0.8485 - F1: 0.8485
sub_16:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.7812 - F1: 0.7758
sub_18:Test (Best Model) - Loss: 0.5797 - Accuracy: 0.7500 - F1: 0.7490
sub_17:Test (Best Model) - Loss: 0.2203 - Accuracy: 0.9697 - F1: 0.9696
sub_16:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.4823 - Accuracy: 0.8438 - F1: 0.8436
sub_16:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.6562 - F1: 0.6476
sub_17:Test (Best Model) - Loss: 0.2239 - Accuracy: 0.9697 - F1: 0.9696
sub_17:Test (Best Model) - Loss: 0.2866 - Accuracy: 0.9394 - F1: 0.9389
sub_18:Test (Best Model) - Loss: 0.2783 - Accuracy: 0.8750 - F1: 0.8745
sub_16:Test (Best Model) - Loss: 2.1376 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.7273 - F1: 0.7179
sub_18:Test (Best Model) - Loss: 0.5068 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.7188 - F1: 0.7163
sub_18:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.7188 - F1: 0.6946
sub_17:Test (Best Model) - Loss: 0.5445 - Accuracy: 0.7273 - F1: 0.7179
sub_18:Test (Best Model) - Loss: 0.3315 - Accuracy: 0.9375 - F1: 0.9352
sub_16:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.7500 - F1: 0.7229
sub_17:Test (Best Model) - Loss: 0.9396 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.5938 - F1: 0.5836
sub_18:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.5938 - F1: 0.5733
sub_17:Test (Best Model) - Loss: 0.8189 - Accuracy: 0.5938 - F1: 0.5733
sub_18:Test (Best Model) - Loss: 0.4387 - Accuracy: 0.8750 - F1: 0.8667
sub_16:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6250 - F1: 0.6235
sub_17:Test (Best Model) - Loss: 0.8912 - Accuracy: 0.8125 - F1: 0.8095
sub_16:Test (Best Model) - Loss: 0.8855 - Accuracy: 0.4688 - F1: 0.4640
sub_18:Test (Best Model) - Loss: 0.5349 - Accuracy: 0.7188 - F1: 0.7117
sub_17:Test (Best Model) - Loss: 0.8558 - Accuracy: 0.6875 - F1: 0.6537
sub_16:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.5344 - Accuracy: 0.7812 - F1: 0.7625
sub_16:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.7188 - F1: 0.7163
sub_20:Test (Best Model) - Loss: 0.7539 - Accuracy: 0.4688 - F1: 0.4421
sub_19:Test (Best Model) - Loss: 6.8054 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.1308 - Accuracy: 0.9375 - F1: 0.9352
sub_21:Test (Best Model) - Loss: 0.3556 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.5938 - F1: 0.5589
sub_19:Test (Best Model) - Loss: 4.6927 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.8125 - F1: 0.7922
sub_21:Test (Best Model) - Loss: 0.4705 - Accuracy: 0.7812 - F1: 0.7519
sub_19:Test (Best Model) - Loss: 3.5026 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 0.2885 - Accuracy: 0.8125 - F1: 0.7922
sub_19:Test (Best Model) - Loss: 1.9018 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 0.8142 - Accuracy: 0.6250 - F1: 0.6250
sub_21:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.8125 - F1: 0.8057
sub_19:Test (Best Model) - Loss: 2.3877 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.6875 - F1: 0.6761
sub_19:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 2.7943 - Accuracy: 0.7188 - F1: 0.7117
sub_21:Test (Best Model) - Loss: 1.1248 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.4650 - Accuracy: 0.9375 - F1: 0.9373
sub_19:Test (Best Model) - Loss: 0.8227 - Accuracy: 0.6875 - F1: 0.6761
sub_21:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.8438 - F1: 0.8303
sub_20:Test (Best Model) - Loss: 0.3994 - Accuracy: 0.9062 - F1: 0.9015
sub_19:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.7500 - F1: 0.7460
sub_21:Test (Best Model) - Loss: 1.0083 - Accuracy: 0.7812 - F1: 0.7625
sub_20:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.6562 - F1: 0.6390
sub_21:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.6250 - F1: 0.6113
sub_19:Test (Best Model) - Loss: 0.3311 - Accuracy: 0.9062 - F1: 0.9062
sub_20:Test (Best Model) - Loss: 0.5278 - Accuracy: 0.8438 - F1: 0.8303
sub_21:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.5000 - F1: 0.4818
sub_19:Test (Best Model) - Loss: 0.5779 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.5612 - Accuracy: 0.8125 - F1: 0.7922
sub_21:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5312 - F1: 0.5271
sub_20:Test (Best Model) - Loss: 2.5183 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.7812 - F1: 0.7793
sub_21:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.7812 - F1: 0.7793
sub_20:Test (Best Model) - Loss: 1.6667 - Accuracy: 0.4848 - F1: 0.4063
sub_21:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.5938 - F1: 0.5836
sub_19:Test (Best Model) - Loss: 0.3653 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.8125 - F1: 0.8118
sub_20:Test (Best Model) - Loss: 3.5365 - Accuracy: 0.6061 - F1: 0.6002
sub_20:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.4242 - F1: 0.4046
sub_19:Test (Best Model) - Loss: 0.2014 - Accuracy: 0.9062 - F1: 0.9062
sub_20:Test (Best Model) - Loss: 0.9822 - Accuracy: 0.3636 - F1: 0.3541
sub_24:Test (Best Model) - Loss: 1.1642 - Accuracy: 0.8125 - F1: 0.8000
sub_22:Test (Best Model) - Loss: 0.3518 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.4988 - Accuracy: 0.8788 - F1: 0.8787
sub_24:Test (Best Model) - Loss: 1.9624 - Accuracy: 0.7500 - F1: 0.7229
sub_24:Test (Best Model) - Loss: 2.3714 - Accuracy: 0.7500 - F1: 0.7333
sub_22:Test (Best Model) - Loss: 0.3017 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.4721 - Accuracy: 0.6970 - F1: 0.6726
sub_22:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.4688 - F1: 0.3637
sub_24:Test (Best Model) - Loss: 2.2292 - Accuracy: 0.7812 - F1: 0.7625
sub_23:Test (Best Model) - Loss: 0.5064 - Accuracy: 0.6667 - F1: 0.6459
sub_24:Test (Best Model) - Loss: 1.5005 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.2812 - F1: 0.2633
sub_23:Test (Best Model) - Loss: 0.5745 - Accuracy: 0.7576 - F1: 0.7273
sub_24:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.9062 - F1: 0.9039
sub_22:Test (Best Model) - Loss: 1.1482 - Accuracy: 0.4688 - F1: 0.4640
sub_23:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7273 - F1: 0.6997
sub_24:Test (Best Model) - Loss: 0.3805 - Accuracy: 0.9062 - F1: 0.9039
sub_22:Test (Best Model) - Loss: 0.5847 - Accuracy: 0.6970 - F1: 0.6898
sub_24:Test (Best Model) - Loss: 0.4597 - Accuracy: 0.8750 - F1: 0.8704
sub_23:Test (Best Model) - Loss: 2.4764 - Accuracy: 0.8125 - F1: 0.8118
sub_22:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.8182 - F1: 0.8036
sub_24:Test (Best Model) - Loss: 0.3950 - Accuracy: 0.8750 - F1: 0.8704
sub_24:Test (Best Model) - Loss: 0.3426 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 1.6478 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.7568 - Accuracy: 0.7576 - F1: 0.7462
sub_22:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.8182 - F1: 0.8096
sub_24:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.5951 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 3.3005 - Accuracy: 0.9062 - F1: 0.9054
sub_24:Test (Best Model) - Loss: 0.7930 - Accuracy: 0.8438 - F1: 0.8303
sub_23:Test (Best Model) - Loss: 2.0352 - Accuracy: 0.4375 - F1: 0.4353
sub_22:Test (Best Model) - Loss: 1.6621 - Accuracy: 0.4062 - F1: 0.3552
sub_23:Test (Best Model) - Loss: 1.8920 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 1.1939 - Accuracy: 0.4375 - F1: 0.4000
sub_24:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7812 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 1.1687 - Accuracy: 0.7576 - F1: 0.7462
sub_22:Test (Best Model) - Loss: 1.1475 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.7576 - F1: 0.7381
sub_22:Test (Best Model) - Loss: 2.1144 - Accuracy: 0.3438 - F1: 0.2558
sub_22:Test (Best Model) - Loss: 0.8246 - Accuracy: 0.4688 - F1: 0.4640
sub_23:Test (Best Model) - Loss: 0.7544 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 1.1227 - Accuracy: 0.6364 - F1: 0.6278
sub_23:Test (Best Model) - Loss: 0.5838 - Accuracy: 0.7576 - F1: 0.7273
sub_25:Test (Best Model) - Loss: 0.5060 - Accuracy: 0.8182 - F1: 0.8180
sub_26:Test (Best Model) - Loss: 0.3040 - Accuracy: 0.8788 - F1: 0.8787
sub_27:Test (Best Model) - Loss: 0.3631 - Accuracy: 0.8788 - F1: 0.8778
sub_25:Test (Best Model) - Loss: 0.4566 - Accuracy: 0.8788 - F1: 0.8787
sub_26:Test (Best Model) - Loss: 0.3359 - Accuracy: 0.8182 - F1: 0.8167
sub_27:Test (Best Model) - Loss: 0.5390 - Accuracy: 0.8182 - F1: 0.8180
sub_25:Test (Best Model) - Loss: 0.3093 - Accuracy: 0.8788 - F1: 0.8759
sub_27:Test (Best Model) - Loss: 0.7717 - Accuracy: 0.8485 - F1: 0.8479
sub_26:Test (Best Model) - Loss: 0.3571 - Accuracy: 0.8485 - F1: 0.8479
sub_25:Test (Best Model) - Loss: 0.4311 - Accuracy: 0.8788 - F1: 0.8731
sub_26:Test (Best Model) - Loss: 0.5606 - Accuracy: 0.7879 - F1: 0.7806
sub_27:Test (Best Model) - Loss: 0.5335 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.8031 - Accuracy: 0.6970 - F1: 0.6944
sub_25:Test (Best Model) - Loss: 0.4145 - Accuracy: 0.8788 - F1: 0.8787
sub_26:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.8438 - F1: 0.8398
sub_27:Test (Best Model) - Loss: 0.4156 - Accuracy: 0.8485 - F1: 0.8485
sub_25:Test (Best Model) - Loss: 0.3334 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.7812 - F1: 0.7758
sub_25:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.8438 - F1: 0.8303
sub_27:Test (Best Model) - Loss: 0.2203 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.9079 - Accuracy: 0.6562 - F1: 0.6476
sub_25:Test (Best Model) - Loss: 0.1836 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.9468 - Accuracy: 0.6875 - F1: 0.6761
sub_27:Test (Best Model) - Loss: 0.2239 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.9772 - Accuracy: 0.6562 - F1: 0.6390
sub_25:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.2866 - Accuracy: 0.9394 - F1: 0.9389
sub_25:Test (Best Model) - Loss: 0.4762 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.7273 - F1: 0.7179
sub_26:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.8125 - F1: 0.8095
sub_25:Test (Best Model) - Loss: 0.2355 - Accuracy: 0.9375 - F1: 0.9352
sub_27:Test (Best Model) - Loss: 0.5445 - Accuracy: 0.7273 - F1: 0.7179
sub_25:Test (Best Model) - Loss: 0.0989 - Accuracy: 0.9688 - F1: 0.9685
sub_26:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.8125 - F1: 0.8057
sub_27:Test (Best Model) - Loss: 0.9396 - Accuracy: 0.6875 - F1: 0.6761
sub_25:Test (Best Model) - Loss: 0.2508 - Accuracy: 0.9375 - F1: 0.9352
sub_27:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.5938 - F1: 0.5733
sub_26:Test (Best Model) - Loss: 0.3872 - Accuracy: 0.8750 - F1: 0.8704
sub_25:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.8125 - F1: 0.8125
sub_26:Test (Best Model) - Loss: 1.1674 - Accuracy: 0.3750 - F1: 0.3651
sub_27:Test (Best Model) - Loss: 0.8189 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.2662 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.6562 - F1: 0.6390
sub_27:Test (Best Model) - Loss: 0.8912 - Accuracy: 0.8125 - F1: 0.8095
sub_27:Test (Best Model) - Loss: 0.8558 - Accuracy: 0.6875 - F1: 0.6537
sub_29:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.3868 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.3716 - Accuracy: 0.9375 - F1: 0.9365
sub_28:Test (Best Model) - Loss: 0.5759 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.3836 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.4686 - Accuracy: 0.8125 - F1: 0.8125
sub_28:Test (Best Model) - Loss: 0.4735 - Accuracy: 0.7500 - F1: 0.7460
sub_29:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.8750 - F1: 0.8704
sub_28:Test (Best Model) - Loss: 0.2853 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.4185 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.4437 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.1864 - Accuracy: 0.9062 - F1: 0.9039
sub_29:Test (Best Model) - Loss: 0.3272 - Accuracy: 0.8750 - F1: 0.8704
sub_28:Test (Best Model) - Loss: 0.1755 - Accuracy: 0.9375 - F1: 0.9365
sub_28:Test (Best Model) - Loss: 0.3981 - Accuracy: 0.9062 - F1: 0.9062
sub_29:Test (Best Model) - Loss: 0.4545 - Accuracy: 0.8438 - F1: 0.8303
sub_28:Test (Best Model) - Loss: 0.8602 - Accuracy: 0.6875 - F1: 0.6135
sub_29:Test (Best Model) - Loss: 0.1921 - Accuracy: 0.8788 - F1: 0.8759
sub_28:Test (Best Model) - Loss: 2.3781 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 1.8549 - Accuracy: 0.5938 - F1: 0.4340
sub_29:Test (Best Model) - Loss: 0.2246 - Accuracy: 0.9394 - F1: 0.9380
sub_28:Test (Best Model) - Loss: 1.0840 - Accuracy: 0.7812 - F1: 0.7625
sub_29:Test (Best Model) - Loss: 0.2040 - Accuracy: 0.9394 - F1: 0.9380
sub_28:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.5938 - F1: 0.4340
sub_29:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.7879 - F1: 0.7746
sub_29:Test (Best Model) - Loss: 0.3189 - Accuracy: 0.9091 - F1: 0.9060

=== Summary Results ===

acc: 76.29 ± 9.64
F1: 74.48 ± 10.61
acc-in: 83.21 ± 7.11
F1-in: 81.36 ± 8.31
runing time: 1078.35 seconds
