lr: 1e-05
sub_9:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2899 - F1: 0.1647
sub_14:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.3235 - F1: 0.2063
sub_5:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2794 - F1: 0.1544
sub_6:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1059
sub_1:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2794 - F1: 0.1392
sub_13:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1059
sub_4:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2754 - F1: 0.1359
sub_10:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2353 - F1: 0.0952
sub_9:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3824 - F1: 0.2972
sub_14:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1125
sub_7:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.1324 - F1: 0.0845
sub_15:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2059 - F1: 0.1304
sub_10:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2464 - F1: 0.1090
sub_2:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2941 - F1: 0.1552
sub_6:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3333 - F1: 0.2257
sub_11:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.1739 - F1: 0.0924
sub_13:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3188 - F1: 0.2407
sub_1:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2464 - F1: 0.1200
sub_8:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3235 - F1: 0.2051
sub_9:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1084
sub_5:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2941 - F1: 0.1767
sub_7:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2609 - F1: 0.1314
sub_11:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.1912 - F1: 0.0878
sub_5:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.3382 - F1: 0.2269
sub_12:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.1739 - F1: 0.1028
sub_10:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2464 - F1: 0.1821
sub_9:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2059 - F1: 0.1735
sub_2:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2319 - F1: 0.0988
sub_7:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1059
sub_8:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.3382 - F1: 0.2310
sub_3:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.3235 - F1: 0.2274
sub_13:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2794 - F1: 0.1405
sub_4:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3382 - F1: 0.2375
sub_5:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2794 - F1: 0.1322
sub_12:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.4412 - F1: 0.3455
sub_6:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2464 - F1: 0.1572
sub_7:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2500 - F1: 0.1500
sub_8:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2941 - F1: 0.1714
sub_1:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1317
sub_13:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.1765 - F1: 0.0759
sub_11:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3043 - F1: 0.2549
sub_4:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2174 - F1: 0.0904
sub_10:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.3043 - F1: 0.2048
sub_9:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.4638 - F1: 0.3087
sub_14:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2754 - F1: 0.1405
sub_10:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2754 - F1: 0.2048
sub_2:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2941 - F1: 0.1696
sub_5:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2059 - F1: 0.0854
sub_1:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2059 - F1: 0.0854
sub_8:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2174 - F1: 0.0893
sub_9:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.3676 - F1: 0.2806
sub_13:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.1912 - F1: 0.0802
sub_3:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2174 - F1: 0.0893
sub_12:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.3188 - F1: 0.2098
sub_7:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.3382 - F1: 0.2467
sub_11:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2174 - F1: 0.0893
sub_3:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2174 - F1: 0.0893
sub_10:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2174 - F1: 0.0893
sub_15:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2174 - F1: 0.0893
sub_14:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.1384
sub_1:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3676 - F1: 0.2806
sub_8:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3235 - F1: 0.2209
sub_2:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3043 - F1: 0.1905
sub_5:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.3824 - F1: 0.2851
sub_3:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3043 - F1: 0.2062
sub_14:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_12:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.3971 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.3088 - F1: 0.1967
sub_10:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2464 - F1: 0.1667
sub_4:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3768 - F1: 0.2878
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3382 - F1: 0.2427
sub_26:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1059
sub_28:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2754 - F1: 0.1359
sub_21:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2754 - F1: 0.1359
sub_22:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1139
sub_26:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3188 - F1: 0.2137
sub_28:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2500 - F1: 0.1000
sub_20:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3043 - F1: 0.2038
sub_19:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2500 - F1: 0.1563
sub_29:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2941 - F1: 0.1933
sub_24:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.3382 - F1: 0.2148
sub_16:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2941 - F1: 0.1916
sub_17:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3043 - F1: 0.2038
sub_26:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.3088 - F1: 0.2181
sub_25:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2500 - F1: 0.1239
sub_18:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2794 - F1: 0.1651
sub_21:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3235 - F1: 0.2214
sub_22:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2500 - F1: 0.2191
sub_28:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2647 - F1: 0.1154
sub_21:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1666
sub_19:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.4118 - F1: 0.3145
sub_27:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2794 - F1: 0.1392
sub_28:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.3088 - F1: 0.1967
sub_23:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2794 - F1: 0.1392
sub_24:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2941 - F1: 0.1764
sub_20:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.0441 - F1: 0.0333
sub_22:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1084
sub_28:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2794 - F1: 0.1381
sub_26:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2353 - F1: 0.1000
sub_16:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1098
sub_29:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2754 - F1: 0.1353
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2464 - F1: 0.0988
sub_19:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1059
sub_27:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3382 - F1: 0.2313
sub_28:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3382 - F1: 0.2313
sub_26:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2206 - F1: 0.1682
sub_24:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3043 - F1: 0.1887
sub_27:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2794 - F1: 0.1322
sub_28:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2059 - F1: 0.0854
sub_23:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3088 - F1: 0.2013
sub_21:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.4412 - F1: 0.2923
sub_27:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2794 - F1: 0.1392
sub_26:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_22:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2464 - F1: 0.1000
sub_17:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2059 - F1: 0.0854
sub_16:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.3382 - F1: 0.2290
sub_20:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.4348 - F1: 0.3104
sub_23:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3676 - F1: 0.2806
sub_21:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.3824 - F1: 0.2972
sub_25:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2794 - F1: 0.2119
sub_22:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_17:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.3824 - F1: 0.2972
sub_29:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2174 - F1: 0.0893
sub_18:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3088 - F1: 0.2295
sub_20:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2174 - F1: 0.0893
sub_21:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2174 - F1: 0.0893
sub_22:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3382 - F1: 0.2427
sub_25:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3382 - F1: 0.2427
sub_21:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.3088 - F1: 0.2182
sub_23:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.3768 - F1: 0.2878
sub_29:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3333 - F1: 0.2348
sub_20:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.3768 - F1: 0.2878

=== Summary Results ===

acc: 26.77 ± 0.94
F1: 12.37 ± 0.96
acc-in: 28.74 ± 1.16
F1-in: 13.75 ± 1.34
runing time: 1161.24 seconds
