lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_1: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_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_3: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_3:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_6: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_6:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_8: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_8:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_9: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_9:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529

=== Summary Results ===

acc: 55.70 ± 0.53
F1: 35.77 ± 0.22
acc-in: 56.41 ± 0.94
F1-in: 36.96 ± 1.71
