lr: 0.0001
sub_8:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2941 - F1: 0.1571
sub_7:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.4559 - F1: 0.2974
sub_6:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2500 - F1: 0.1345
sub_5:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.4412 - F1: 0.2917
sub_12:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2500 - F1: 0.1213
sub_11:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.3043 - F1: 0.1725
sub_13:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2941 - F1: 0.1561
sub_3:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2941 - F1: 0.1539
sub_10:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.4265 - F1: 0.3163
sub_8:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2206 - F1: 0.0915
sub_7:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.4348 - F1: 0.2848
sub_6:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.3676 - F1: 0.2282
sub_2:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3623 - F1: 0.2716
sub_13:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2500 - F1: 0.1600
sub_11:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.4118 - F1: 0.2883
sub_14:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3235 - F1: 0.1995
sub_4:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.1618 - F1: 0.0833
sub_12:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2754 - F1: 0.1310
sub_7:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.1059
sub_10:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1262
sub_8:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2647 - F1: 0.1111
sub_12:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.1765 - F1: 0.0857
sub_4:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2174 - F1: 0.0904
sub_11:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2899 - F1: 0.1721
sub_7:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2464 - F1: 0.1333
sub_1:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3088 - F1: 0.1731
sub_3:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2464 - F1: 0.1049
sub_9:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2754 - F1: 0.1310
sub_11:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.4058 - F1: 0.3095
sub_8:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.1618 - F1: 0.1319
sub_12:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3623 - F1: 0.2277
sub_2:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2899 - F1: 0.1821
sub_5:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2206 - F1: 0.1223
sub_13:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2464 - F1: 0.1193
sub_11:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2464 - F1: 0.0988
sub_8:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3043 - F1: 0.1981
sub_14:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2794 - F1: 0.1322
sub_9:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2609 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.1059
sub_10:Test (Best Model) - Loss: 1.1666 - Accuracy: 0.4118 - F1: 0.3469
sub_13:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2609 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3676 - F1: 0.2482
sub_12:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2647 - F1: 0.1429
sub_8:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2647 - F1: 0.1452
sub_4:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2941 - F1: 0.1552
sub_2:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2794 - F1: 0.1640
sub_13:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2464 - F1: 0.1624
sub_14:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2941 - F1: 0.1542
sub_8:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2899 - F1: 0.1756
sub_4:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2500 - F1: 0.1000
sub_13:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2941 - F1: 0.1970
sub_11:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2647 - F1: 0.1059
sub_5:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3382 - F1: 0.2283
sub_8:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2647 - F1: 0.1084
sub_6:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.5147 - F1: 0.3387
sub_13:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2500 - F1: 0.1024
sub_1:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2647 - F1: 0.1590
sub_11:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3913 - F1: 0.2601
sub_10:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2754 - F1: 0.1310
sub_4:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.4348 - F1: 0.2855
sub_15:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3228 - Accuracy: 0.2754 - F1: 0.1338
sub_9:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3529 - F1: 0.2222
sub_2:Test (Best Model) - Loss: 1.3690 - Accuracy: 0.4638 - F1: 0.3050
sub_1:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.4348 - F1: 0.2981
sub_15:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.3088 - F1: 0.1763
sub_14:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3088 - F1: 0.1749
sub_1:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.5147 - F1: 0.3432
sub_7:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.4265 - F1: 0.2788
sub_1:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.3088 - F1: 0.1727
sub_17:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.3623 - F1: 0.2337
sub_27:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.3623 - F1: 0.2337
sub_23:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2029 - F1: 0.1230
sub_25:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1250
sub_28:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2941 - F1: 0.1546
sub_19:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.4559 - F1: 0.3044
sub_20:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3382 - F1: 0.2172
sub_29:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2647 - F1: 0.1098
sub_26:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.4348 - F1: 0.2845
sub_16:Test (Best Model) - Loss: 1.3692 - Accuracy: 0.4412 - F1: 0.2918
sub_17:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3073 - Accuracy: 0.3676 - F1: 0.2676
sub_21:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.4706 - F1: 0.3076
sub_25:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1059
sub_28:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.4348 - F1: 0.2857
sub_20:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1262
sub_19:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1684
sub_16:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2609 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1059
sub_22:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.5882 - F1: 0.5272
sub_28:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2609 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2794 - F1: 0.1322
sub_17:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.2647 - F1: 0.1277
sub_19:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3768 - F1: 0.2429
sub_16:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1410
sub_26:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3088 - F1: 0.1779
sub_29:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2353 - F1: 0.1281
sub_18:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2206 - F1: 0.1128
sub_17:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3235 - F1: 0.1958
sub_17:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2500 - F1: 0.1000
sub_27:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2899 - F1: 0.1559
sub_28:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3235 - F1: 0.2623
sub_21:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2941 - F1: 0.1733
sub_29:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2754 - F1: 0.1309
sub_26:Test (Best Model) - Loss: 1.3070 - Accuracy: 0.3676 - F1: 0.2303
sub_19:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.4265 - F1: 0.3268
sub_20:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3043 - F1: 0.1700
sub_25:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2500 - F1: 0.1049
sub_27:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3043 - F1: 0.1700
sub_16:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2794 - F1: 0.1322
sub_24:Test (Best Model) - Loss: 1.2533 - Accuracy: 0.4118 - F1: 0.3211
sub_28:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3234 - Accuracy: 0.3676 - F1: 0.3194
sub_26:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2754 - F1: 0.1310
sub_25:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2794 - F1: 0.1321
sub_27:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.4118 - F1: 0.2847
sub_28:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3824 - F1: 0.2649
sub_17:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2794 - F1: 0.1322
sub_19:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2500 - F1: 0.1000
sub_21:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.3382 - F1: 0.2225
sub_28:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.1912 - F1: 0.1117
sub_21:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.3235 - F1: 0.2005
sub_16:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3824 - F1: 0.2534
sub_22:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3824 - F1: 0.2534
sub_16:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.3235 - F1: 0.1958
sub_28:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2941 - F1: 0.1571
sub_29:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2941 - F1: 0.1542
sub_19:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2500 - F1: 0.1037
sub_16:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.4706 - F1: 0.3152
sub_18:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.3971 - F1: 0.2631
sub_24:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3529 - F1: 0.2336

=== Summary Results ===

acc: 27.90 ± 1.53
F1: 12.87 ± 1.84
acc-in: 30.94 ± 1.97
F1-in: 15.87 ± 2.38
runing time: 1124.04 seconds
