lr: 1e-05
sub_8:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4545 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4545 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_20:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529

=== Summary Results ===

acc: 52.67 ± 0.26
F1: 34.42 ± 0.10
acc-in: 53.88 ± 0.32
F1-in: 34.86 ± 0.13
runing time: 425.31 seconds
