lr: 1e-05
sub_7:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2647 - F1: 0.1047
sub_8: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_13:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3860 - 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: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3860 - 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: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_8: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_5:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3333 - F1: 0.2162
sub_5:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2059 - F1: 0.1346
sub_1:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1268
sub_3:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2899 - F1: 0.1753
sub_8:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2206 - F1: 0.1360
sub_10:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2353 - F1: 0.1521
sub_2:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.3235 - F1: 0.1923
sub_9:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2353 - F1: 0.1278
sub_11:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1591
sub_4:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2174 - F1: 0.1659
sub_7:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2206 - F1: 0.1361
sub_13:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1780
sub_12:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2464 - F1: 0.1396
sub_8:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2353 - F1: 0.0988
sub_11:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.4118 - F1: 0.2692
sub_6:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.1449 - F1: 0.0986
sub_4:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2029 - F1: 0.0875
sub_12:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2029 - F1: 0.1251
sub_7:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.1739 - F1: 0.1103
sub_6:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2754 - F1: 0.1567
sub_15:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2941 - F1: 0.1653
sub_5:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2500 - F1: 0.1625
sub_11:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2500 - F1: 0.1024
sub_4:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2319 - F1: 0.0941
sub_8:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2899 - F1: 0.1548
sub_11:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2174 - F1: 0.0893
sub_6:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_8:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_12:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2941 - F1: 0.1652
sub_10:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2174 - F1: 0.0893
sub_14:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1059
sub_1:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2059 - F1: 0.0854
sub_5:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.1765 - F1: 0.1146
sub_4:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2174 - F1: 0.0893
sub_11:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2059 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2609 - F1: 0.1404
sub_6:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2174 - F1: 0.0893
sub_9:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2794 - F1: 0.1885
sub_10:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.1765 - F1: 0.0936
sub_13:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2174 - F1: 0.0893
sub_12:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2647 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.1912 - F1: 0.0802
sub_15:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.1884 - F1: 0.1100
sub_3:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2174 - F1: 0.0893
sub_2:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2941 - F1: 0.1673
sub_14:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2174 - F1: 0.1131
sub_15:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2500 - F1: 0.1652
sub_17:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2029 - F1: 0.1423
sub_24:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2941 - F1: 0.1871
sub_22:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1714
sub_26:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2059 - F1: 0.1292
sub_29:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2353 - F1: 0.1387
sub_16:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2059 - F1: 0.1291
sub_21:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2353 - F1: 0.1172
sub_20:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2206 - F1: 0.1212
sub_19:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1711
sub_27:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2029 - F1: 0.1423
sub_23:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2353 - F1: 0.0964
sub_28:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.3235 - F1: 0.1997
sub_24:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.4412 - F1: 0.3468
sub_20:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.1392
sub_26:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.1392
sub_18:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1084
sub_17:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2353 - F1: 0.1158
sub_25:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2319 - F1: 0.1511
sub_26:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.1618 - F1: 0.1081
sub_22:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1275
sub_21:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2353 - F1: 0.1189
sub_24:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1274
sub_27:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2353 - F1: 0.1158
sub_25:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2609 - F1: 0.1720
sub_17:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_21:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2794 - F1: 0.1839
sub_25:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2059 - F1: 0.0854
sub_23:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2174 - F1: 0.0893
sub_20:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2059 - F1: 0.0854
sub_21:Test (Best Model) - Loss: 1.3900 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2059 - F1: 0.0854
sub_27:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2500 - F1: 0.1012
sub_23:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2206 - F1: 0.1127
sub_20:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2174 - F1: 0.0893
sub_22:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.3088 - F1: 0.1931
sub_21:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2794 - F1: 0.1392
sub_16:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2206 - F1: 0.1127
sub_18:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2500 - F1: 0.1644
sub_28:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2609 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2647 - F1: 0.1664

=== Summary Results ===

acc: 25.77 ± 0.68
F1: 10.93 ± 0.52
acc-in: 27.39 ± 0.69
F1-in: 12.10 ± 0.78
runing time: 969.29 seconds
