lr: 1e-05
sub_2:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.8182 - F1: 0.8096
sub_1:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.4545 - F1: 0.4107
sub_3:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.4688 - F1: 0.3976
sub_3:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.9375 - F1: 0.9373
sub_2:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.4848 - F1: 0.4527
sub_1:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.8125 - F1: 0.8118
sub_2:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.3939 - F1: 0.2826
sub_1:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.9062 - F1: 0.9062
sub_2:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.5625 - F1: 0.5152
sub_1:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.6364 - F1: 0.6071
sub_3:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.5000 - F1: 0.4182
sub_2:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.4688 - F1: 0.3637
sub_1:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6061 - F1: 0.5662
sub_3:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.4848 - F1: 0.3718
sub_2:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5455 - F1: 0.4762
sub_1:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6104 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5625 - F1: 0.5152
sub_3:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5152 - F1: 0.4261
sub_2:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.9697 - F1: 0.9696
sub_1:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.7500 - F1: 0.7460
sub_3:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.5758 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.8182 - F1: 0.8167
sub_1:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5312 - F1: 0.4684
sub_1:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.8485 - F1: 0.8462
sub_1:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.7812 - F1: 0.7793
sub_3:Test (Best Model) - Loss: 0.6271 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.9697 - F1: 0.9696
sub_3:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.8788 - F1: 0.8787
sub_3:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6667 - F1: 0.6459
sub_3:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.9697 - F1: 0.9692
sub_6:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.9375 - F1: 0.9373
sub_4:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6325 - Accuracy: 0.5000 - F1: 0.4182
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.4848 - F1: 0.3718
sub_4:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6364 - F1: 0.6333
sub_5:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.4242 - F1: 0.2979
sub_4:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4848 - F1: 0.3718
sub_4:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5152 - F1: 0.4261
sub_4:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5758 - F1: 0.5227
sub_5:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6061 - F1: 0.5662
sub_5:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6061 - F1: 0.5196
sub_6:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4242 - F1: 0.3660
sub_5:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.3636 - F1: 0.3541
sub_5:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.6068 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.7500 - F1: 0.7091
sub_7:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6218 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.4688 - F1: 0.3637
sub_9:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.5312 - F1: 0.4684
sub_8:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.9062 - F1: 0.9062
sub_9:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.4688 - F1: 0.3191
sub_9:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4688 - F1: 0.3637
sub_9:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.9062 - F1: 0.9062
sub_8:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.4688 - F1: 0.3637
sub_7:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7812 - F1: 0.7793
sub_9:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.4688 - F1: 0.3637
sub_9:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.4688 - F1: 0.3637
sub_9:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.4062 - F1: 0.2889
sub_7:Test (Best Model) - Loss: 0.6423 - Accuracy: 0.8750 - F1: 0.8750
sub_8:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.5000 - F1: 0.4182
sub_9:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.7188 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.8125 - F1: 0.8118
sub_7:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.4688 - F1: 0.3637
sub_8:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.8125 - F1: 0.8125
sub_8:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6875 - F1: 0.6135
sub_9:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.5312 - F1: 0.4684
sub_7:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5625 - F1: 0.5152
sub_11:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5312 - F1: 0.4684
sub_12:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5758 - F1: 0.5227
sub_10:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.4182
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4062 - F1: 0.2889
sub_11:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.4242 - F1: 0.3883
sub_10:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5312 - F1: 0.4684
sub_11:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4848 - F1: 0.4672
sub_10:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6189 - Accuracy: 0.5000 - F1: 0.4182
sub_12:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.7188 - F1: 0.7117
sub_12:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.5000 - F1: 0.4182
sub_12:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.4545 - F1: 0.3543
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.6562 - F1: 0.6390
sub_11:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4242 - F1: 0.2979
sub_10:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.4242 - F1: 0.2979
sub_11:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5152 - F1: 0.4261
sub_12:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.6364 - F1: 0.5696
sub_12:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5000 - F1: 0.4980
sub_11:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6012 - Accuracy: 0.8125 - F1: 0.8118
sub_14:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.9062 - F1: 0.9062
sub_14:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6562 - F1: 0.5883
sub_13:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.9062 - F1: 0.9015
sub_15:Test (Best Model) - Loss: 0.5911 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.6097 - Accuracy: 0.8125 - F1: 0.8118
sub_14:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4688 - F1: 0.3637
sub_15:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.5152
sub_13:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.4848 - F1: 0.3718
sub_15:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6562 - F1: 0.6390
sub_14:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5000 - F1: 0.4182
sub_15:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6970 - F1: 0.6827
sub_14:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6970 - F1: 0.6944
sub_15:Test (Best Model) - Loss: 0.5929 - Accuracy: 0.9375 - F1: 0.9373
sub_14:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5152 - F1: 0.4261
sub_15:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.8750 - F1: 0.8750
sub_14:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.8438 - F1: 0.8436
sub_13:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.6364 - F1: 0.6071
sub_15:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.8438 - F1: 0.8436
sub_13:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.8125 - F1: 0.8000
sub_14:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.9062 - F1: 0.9062
sub_15:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6875 - F1: 0.6135
sub_15:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.9688 - F1: 0.9685
sub_13:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.8125 - F1: 0.8125
sub_13:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.7500 - F1: 0.7333
sub_16:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.7188 - F1: 0.7117
sub_17:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6970 - F1: 0.6944
sub_16:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5758 - F1: 0.5227
sub_18:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5758 - F1: 0.5417
sub_16:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5625 - F1: 0.5608
sub_17:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4242 - F1: 0.4046
sub_16:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6667 - F1: 0.6553
sub_16:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5312 - F1: 0.4684
sub_18:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4062 - F1: 0.3267
sub_18:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5625 - F1: 0.5152
sub_17:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.4688 - F1: 0.3637
sub_16:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.6250 - F1: 0.6000
sub_17:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.4375 - F1: 0.3766
sub_17:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.4375 - F1: 0.4000
sub_18:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5938 - F1: 0.5589
sub_18:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5938 - F1: 0.4340
sub_17:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4688 - F1: 0.3637
sub_16:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.4182
sub_21:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.7188 - F1: 0.7117
sub_21:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.7500 - F1: 0.7490
sub_21:Test (Best Model) - Loss: 0.6096 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5312 - F1: 0.4386
sub_21:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.8438 - F1: 0.8303
sub_20:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5312 - F1: 0.3992
sub_21:Test (Best Model) - Loss: 0.5628 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7812 - F1: 0.7793
sub_19:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4688 - F1: 0.3637
sub_20:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.9375 - F1: 0.9373
sub_21:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.8438 - F1: 0.8424
sub_20:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.7812 - F1: 0.7793
sub_20:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6875 - F1: 0.6761
sub_19:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.8750 - F1: 0.8745
sub_20:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.6667 - F1: 0.6553
sub_19:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8125 - F1: 0.8118
sub_20:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.5312 - F1: 0.4684
sub_20:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.6364 - F1: 0.5909
sub_19:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.7812 - F1: 0.7793
sub_21:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 0.6047 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 0.5655 - Accuracy: 0.8438 - F1: 0.8436
sub_23:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.4242 - F1: 0.4046
sub_22:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4375 - F1: 0.4286
sub_23:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6875 - F1: 0.6825
sub_22:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5152 - F1: 0.4261
sub_24:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.8750 - F1: 0.8704
sub_22:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4848 - F1: 0.3718
sub_23:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.4375 - F1: 0.3455
sub_24:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.5938 - F1: 0.5589
sub_24:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.9375 - F1: 0.9373
sub_23:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.4688 - F1: 0.3637
sub_22:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.9062 - F1: 0.9062
sub_23:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.4848 - F1: 0.4672
sub_24:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.9062 - F1: 0.9062
sub_22:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.7500 - F1: 0.7490
sub_22:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.8438 - F1: 0.8436
sub_22:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6061 - F1: 0.6002
sub_22:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5455 - F1: 0.4762
sub_24:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.8750 - F1: 0.8750
sub_22:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5938 - F1: 0.5393
sub_23:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5455 - F1: 0.4762
sub_24:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.8125 - F1: 0.7922
sub_23:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.7576 - F1: 0.7273
sub_24:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.8750 - F1: 0.8667
sub_24:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.9062 - F1: 0.9015
sub_27:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5758 - F1: 0.5227
sub_26:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.7273 - F1: 0.7179
sub_25:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.9697 - F1: 0.9696
sub_27:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5152 - F1: 0.4261
sub_25:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6970 - F1: 0.6827
sub_27:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7273 - F1: 0.7179
sub_25:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.9091 - F1: 0.9091
sub_27:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6562 - F1: 0.6390
sub_26:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.3125 - F1: 0.2667
sub_27:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5625 - F1: 0.5333
sub_26:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6250 - F1: 0.6190
sub_25:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.4375 - F1: 0.4000
sub_25:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.8125 - F1: 0.8118
sub_26:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5000 - F1: 0.4182
sub_27:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5938 - F1: 0.5589
sub_25:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.7812 - F1: 0.7793
sub_26:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6250 - F1: 0.6000
sub_25:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.7812 - F1: 0.7793
sub_27:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5312 - F1: 0.4684
sub_26:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.7812 - F1: 0.7519
sub_25:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.9375 - F1: 0.9373
sub_27:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4688 - F1: 0.3637
sub_28:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.4688 - F1: 0.3637
sub_28:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.5000 - F1: 0.4459
sub_29:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.5312 - F1: 0.4910
sub_29:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5312 - F1: 0.4910
sub_28:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.4688 - F1: 0.3637
sub_29:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.5312 - F1: 0.4684
sub_29:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.4688 - F1: 0.3637
sub_29:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.4688 - F1: 0.3637
sub_29:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.7273 - F1: 0.7179
sub_28:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.4848 - F1: 0.3718
sub_28:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.9091 - F1: 0.9088
sub_28:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.8438 - F1: 0.8398
sub_28:Test (Best Model) - Loss: 0.5766 - Accuracy: 0.9375 - F1: 0.9352
sub_28:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.5947 - Accuracy: 0.8125 - F1: 0.7922

=== Summary Results ===

acc: 58.31 ± 10.71
F1: 50.74 ± 13.71
acc-in: 65.40 ± 12.64
F1-in: 59.98 ± 15.16
runing time: 1323.80 seconds
