lr: 1e-05
sub_13:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.3750 - F1: 0.3074
sub_8:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.4182
sub_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.3125 - F1: 0.2381
sub_6:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.3636 - F1: 0.2667
sub_10:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6562 - F1: 0.6102
sub_7:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.4182
sub_29:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.3438 - F1: 0.2558
sub_19:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4688 - F1: 0.3637
sub_16:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.6250 - F1: 0.6235
sub_27:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043

=== Summary Results ===

acc: 49.04 ± 0.52
F1: 32.96 ± 0.55
acc-in: 49.32 ± 0.69
F1-in: 33.08 ± 0.85
runing time: 528.63 seconds
