lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7500 - F1: 0.7091
sub_7:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.7500 - F1: 0.7091
sub_5:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.7812 - F1: 0.7519
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6061 - F1: 0.4850
sub_13:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6562 - F1: 0.5594
sub_5:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6250 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5938 - F1: 0.4340
sub_14:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6250 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5758 - F1: 0.4225
sub_3:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.8125 - F1: 0.7922
sub_10:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.6667 - F1: 0.6459
sub_4:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.7576 - F1: 0.7273
sub_14:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6562 - F1: 0.5594
sub_9:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.8750 - F1: 0.8667
sub_11:Test (Best Model) - Loss: 0.6313 - Accuracy: 0.8485 - F1: 0.8485
sub_3:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.7273 - F1: 0.6857
sub_8:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.5942 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.7273 - F1: 0.6857
sub_2:Test (Best Model) - Loss: 0.5902 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.9091 - F1: 0.9060
sub_10:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6562 - F1: 0.5594
sub_5:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.7879 - F1: 0.7664
sub_15:Test (Best Model) - Loss: 0.6184 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.4523 - Accuracy: 0.9091 - F1: 0.9060
sub_9:Test (Best Model) - Loss: 0.5711 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.4711 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.8485 - F1: 0.8390
sub_2:Test (Best Model) - Loss: 0.5751 - Accuracy: 0.8125 - F1: 0.7922
sub_13:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.7273 - F1: 0.6857
sub_7:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.5938 - F1: 0.4340
sub_3:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6562 - F1: 0.5594
sub_5:Test (Best Model) - Loss: 0.5979 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6562 - F1: 0.5594
sub_12:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.9697 - F1: 0.9696
sub_10:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.5938 - F1: 0.4340
sub_6:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.7576 - F1: 0.7273
sub_13:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.6875 - F1: 0.6135
sub_7:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.8750 - F1: 0.8667
sub_5:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.6364 - F1: 0.5417
sub_12:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.5455 - F1: 0.3529
sub_10:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.5455 - F1: 0.3529
sub_8:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.9394 - F1: 0.9380
sub_6:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.6250 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.7812 - F1: 0.7519
sub_3:Test (Best Model) - Loss: 0.6180 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.4817 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.7812 - F1: 0.7519
sub_10:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.7188 - F1: 0.6632
sub_3:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5758 - F1: 0.4225
sub_6:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5455 - F1: 0.3529
sub_7:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5455 - F1: 0.3529
sub_3:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5758 - F1: 0.4225
sub_14:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.8182 - F1: 0.8036
sub_6:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5758 - F1: 0.4225
sub_15:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6250 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.5758 - F1: 0.4225
sub_6:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6364 - F1: 0.5417
sub_8:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.6562 - F1: 0.5594
sub_12:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.7812 - F1: 0.7519
sub_19:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5758 - F1: 0.4225
sub_26:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6364 - F1: 0.5417
sub_25:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.7812 - F1: 0.7519
sub_24:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7576 - F1: 0.7273
sub_27:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5758 - F1: 0.4225
sub_25:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7812 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.7188 - F1: 0.6632
sub_16:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5938 - F1: 0.4340
sub_28:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8438 - F1: 0.8303
sub_24:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.9375 - F1: 0.9365
sub_21:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.6067 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6136 - Accuracy: 0.9394 - F1: 0.9380
sub_27:Test (Best Model) - Loss: 0.6136 - Accuracy: 0.9394 - F1: 0.9380
sub_23:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.5875 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.5832 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.5758 - F1: 0.4225
sub_19:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.7188 - F1: 0.6632
sub_18:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.7500 - F1: 0.7091
sub_21:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.8438 - F1: 0.8303
sub_25:Test (Best Model) - Loss: 0.3624 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7879 - F1: 0.7664
sub_28:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.8125 - F1: 0.7922
sub_16:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.8438 - F1: 0.8303
sub_27:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7879 - F1: 0.7664
sub_22:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5455 - F1: 0.3529
sub_21:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6875 - F1: 0.6135
sub_16:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.8125 - F1: 0.7922
sub_21:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.5211 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.5965 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.6562 - F1: 0.5594
sub_17:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5455 - F1: 0.3529
sub_16:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.7812 - F1: 0.7519
sub_19:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5938 - F1: 0.4340
sub_28:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.6562 - F1: 0.5594
sub_17:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6250 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5455 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.7879 - F1: 0.7664
sub_17:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6061 - F1: 0.4850
sub_19:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.7812 - F1: 0.7519
sub_20:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5455 - F1: 0.3529
sub_24:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.3939 - F1: 0.3654
sub_25:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5455 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5455 - F1: 0.3529
sub_29:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.5455 - F1: 0.3529
sub_23:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5455 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.6061 - F1: 0.4850
sub_19:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5625 - F1: 0.3600

=== Summary Results ===

acc: 61.42 ± 2.67
F1: 45.50 ± 4.45
acc-in: 68.85 ± 4.52
F1-in: 56.56 ± 6.99
runing time: 668.95 seconds
