lr: 1e-06
sub_9:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4062 - F1: 0.2889
sub_10:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6981 - 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: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5312 - F1: 0.3469
sub_5:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5758 - F1: 0.4225
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5152 - F1: 0.3400
sub_14:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.4058
sub_1:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5152 - F1: 0.3400
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_18:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5312 - F1: 0.3469
sub_17:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5938 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.3043

=== Summary Results ===

acc: 48.74 ± 0.39
F1: 32.74 ± 0.29
acc-in: 49.04 ± 0.40
F1-in: 32.81 ± 0.45
runing time: 522.88 seconds
