lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2941 - F1: 0.1696
sub_12:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2500 - F1: 0.1000
sub_1:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_5: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: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2464 - F1: 0.0988
sub_1:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2609 - F1: 0.1611
sub_3:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3188 - F1: 0.2194
sub_9:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2353 - F1: 0.1533
sub_8:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3235 - F1: 0.2024
sub_2:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2647 - F1: 0.1471
sub_14:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.1324 - F1: 0.0845
sub_11:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.3043 - F1: 0.2010
sub_13:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2319 - F1: 0.1531
sub_12:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2464 - F1: 0.1090
sub_10:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.1912 - F1: 0.1310
sub_5:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1139
sub_15:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3676 - F1: 0.2515
sub_4:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3043 - F1: 0.1786
sub_1:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2029 - F1: 0.1063
sub_2:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1233
sub_11:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2174 - F1: 0.0893
sub_9:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2059 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2174 - F1: 0.0893
sub_14:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2174 - F1: 0.0893
sub_12:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2059 - F1: 0.0854
sub_10:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2174 - F1: 0.0893
sub_5:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2059 - F1: 0.0854
sub_15:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2174 - F1: 0.0893
sub_1:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2174 - F1: 0.0893
sub_14:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2059 - F1: 0.0864
sub_11:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2174 - F1: 0.0904
sub_9:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.1912 - F1: 0.0823
sub_8:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2059 - F1: 0.0933
sub_3:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2174 - F1: 0.0915
sub_7:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.4058 - F1: 0.2746
sub_12:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.0735 - F1: 0.0352
sub_13:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.1912 - F1: 0.0813
sub_10:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.1739 - F1: 0.0750
sub_5:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2206 - F1: 0.1126
sub_15:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2353 - F1: 0.1352
sub_4:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2174 - F1: 0.0893
sub_11:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2319 - F1: 0.1340
sub_9:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2059 - F1: 0.0864
sub_12:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2174 - F1: 0.0893
sub_8:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2059 - F1: 0.0854
sub_1:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2059 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2174 - F1: 0.0893
sub_12:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2059 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2174 - F1: 0.0893
sub_10:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2059 - F1: 0.0854
sub_5:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2059 - F1: 0.0854
sub_15:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2059 - F1: 0.0854
sub_14:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2174 - F1: 0.0893
sub_1:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2059 - F1: 0.0854
sub_9:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2174 - F1: 0.0893
sub_8:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2174 - F1: 0.0893
sub_12:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2059 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2174 - F1: 0.0893
sub_2:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2174 - F1: 0.0893
sub_10:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2059 - F1: 0.0854
sub_5:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2059 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2174 - F1: 0.0893
sub_15:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_4:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2174 - F1: 0.0893
sub_7:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3862 - 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: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2353 - F1: 0.0952
sub_27:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.0294 - F1: 0.0161
sub_18:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.1268
sub_21:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2500 - F1: 0.1000
sub_17:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2754 - F1: 0.1558
sub_23:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2059 - F1: 0.1333
sub_27:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2754 - F1: 0.1558
sub_26:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2059 - F1: 0.1340
sub_22:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.1529
sub_16:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2500 - F1: 0.1049
sub_20:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2500 - F1: 0.1308
sub_18:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1139
sub_19:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3235 - F1: 0.1910
sub_28:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1154
sub_24:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2794 - F1: 0.1551
sub_25:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3235 - F1: 0.1928
sub_29:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2174 - F1: 0.0893
sub_21:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2059 - F1: 0.0854
sub_23:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2059 - F1: 0.0854
sub_22:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_27:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2059 - F1: 0.0854
sub_20:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2174 - F1: 0.0893
sub_16:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2059 - F1: 0.0854
sub_21:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2206 - F1: 0.1127
sub_23:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.1884 - F1: 0.1389
sub_27:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2206 - F1: 0.1127
sub_26:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2206 - F1: 0.1151
sub_22:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2206 - F1: 0.1159
sub_20:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2029 - F1: 0.0972
sub_16:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.1912 - F1: 0.0802
sub_25:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2059 - F1: 0.1014
sub_19:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.0882 - F1: 0.0423
sub_28:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2941 - F1: 0.1917
sub_24:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2059 - F1: 0.0864
sub_21:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.1912 - F1: 0.0813
sub_29:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2174 - F1: 0.0893
sub_27:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2059 - F1: 0.0854
sub_17:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2059 - F1: 0.0854
sub_23:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2174 - F1: 0.0893
sub_26:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2059 - F1: 0.0854
sub_16:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2059 - F1: 0.0854
sub_20:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2174 - F1: 0.0893
sub_22:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2174 - F1: 0.0893
sub_21:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2059 - F1: 0.0854
sub_23:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2174 - F1: 0.0893
sub_27:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.0854
sub_17:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.0854
sub_26:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.0854
sub_20:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2174 - F1: 0.0893
sub_16:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2059 - F1: 0.0854
sub_22:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2059 - F1: 0.0854
sub_28:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2059 - F1: 0.0854
sub_19:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2059 - F1: 0.0854
sub_24:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2059 - F1: 0.0854
sub_18:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2059 - F1: 0.0854

=== Summary Results ===

acc: 24.84 ± 0.57
F1: 10.35 ± 0.41
acc-in: 26.37 ± 0.52
F1-in: 10.88 ± 0.42
runing time: 886.25 seconds
