lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.8125 - F1: 0.7922
sub_10:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5938 - F1: 0.4340
sub_3:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.8125 - F1: 0.7922
sub_7:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.8182 - F1: 0.8036
sub_14:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.7812 - F1: 0.7519
sub_10:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.6875 - F1: 0.6135
sub_3:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.7812 - F1: 0.7519
sub_11:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6250 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6562 - F1: 0.5594
sub_3:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5758 - F1: 0.4225
sub_10:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7188 - F1: 0.6632
sub_6:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6667 - F1: 0.5935
sub_9:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7188 - F1: 0.6632
sub_4:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.8182 - F1: 0.8036
sub_8:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6970 - F1: 0.6413
sub_13:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6667 - F1: 0.5935
sub_14:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7879 - F1: 0.7664
sub_13:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.7188 - F1: 0.6632
sub_3:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5758 - F1: 0.4225
sub_9:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.7812 - F1: 0.7519
sub_10:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.5901 - Accuracy: 0.7879 - F1: 0.7664
sub_15:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.7273 - F1: 0.6857
sub_6:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.6667 - F1: 0.5935
sub_9:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.5938 - F1: 0.4340
sub_5:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.7273 - F1: 0.6857
sub_10:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5455 - F1: 0.4058
sub_15:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.8438 - F1: 0.8303
sub_14:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5455 - F1: 0.3529
sub_14:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.6875 - F1: 0.6135
sub_1:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6250 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5312 - F1: 0.3469
sub_17:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.7188 - F1: 0.6632
sub_16:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5938 - F1: 0.4340
sub_27:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.7576 - F1: 0.7273
sub_25:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6250 - F1: 0.5000
sub_26:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6061 - F1: 0.4850
sub_16:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5312 - F1: 0.3469
sub_29:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6364 - F1: 0.5417
sub_18:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6667 - F1: 0.5935
sub_24:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5758 - F1: 0.4225
sub_20:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6250 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.8438 - F1: 0.8303
sub_24:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6364 - F1: 0.5417
sub_21:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.7812 - F1: 0.7519
sub_25:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.8125 - F1: 0.7922
sub_28:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5758 - F1: 0.4225
sub_23:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6875 - F1: 0.6135
sub_16:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.5398 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.7812 - F1: 0.7519
sub_16:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.5812 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5938 - F1: 0.4340
sub_24:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.7188 - F1: 0.6632
sub_16:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.7188 - F1: 0.6632
sub_28:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.8750 - F1: 0.8667
sub_28:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.6364 - F1: 0.5417
sub_25:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.4545 - F1: 0.4288
sub_19:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6875 - F1: 0.6135
sub_27:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5758 - F1: 0.4225
sub_25:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5938 - F1: 0.4340
sub_29:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5938 - F1: 0.4340
sub_20:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6364 - F1: 0.5696
sub_23:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6061 - F1: 0.4850
sub_25:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.5758 - F1: 0.4225

=== Summary Results ===

acc: 58.65 ± 3.22
F1: 41.28 ± 5.91
acc-in: 64.24 ± 6.18
F1-in: 49.74 ± 9.78
runing time: 784.86 seconds
