lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5312 - F1: 0.4910
sub_1:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6562 - F1: 0.6532
sub_1:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.5938 - F1: 0.5836
sub_1:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5312 - F1: 0.4684
sub_1:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6562 - F1: 0.6476
sub_1:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.7273 - F1: 0.7232
sub_1:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6970 - F1: 0.6944
sub_1:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6061 - F1: 0.5662
sub_1:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.7576 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6875 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6250 - F1: 0.5362
sub_1:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.8438 - F1: 0.8359
sub_2:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4848 - F1: 0.4829
sub_2:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5455 - F1: 0.4762
sub_2:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5938 - F1: 0.5934
sub_2:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5312 - F1: 0.4684
sub_2:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5758 - F1: 0.5658
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5455 - F1: 0.5455
sub_2:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5152 - F1: 0.4923
sub_2:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5312 - F1: 0.5271
sub_3:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5625 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5312 - F1: 0.5195
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5312 - F1: 0.5271
sub_3:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6061 - F1: 0.6046
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6667 - F1: 0.6553
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.6364 - F1: 0.6071
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.6061 - F1: 0.5926
sub_3:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.3636 - F1: 0.3613
sub_3:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.3939 - F1: 0.3797
sub_3:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.5455 - F1: 0.5438
sub_4:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.8485 - F1: 0.8462
sub_4:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.6667 - F1: 0.6159
sub_4:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.7273 - F1: 0.6997
sub_4:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6667 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5152 - F1: 0.4261
sub_4:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.5299
sub_4:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.5758 - F1: 0.5417
sub_4:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.5758 - F1: 0.5754
sub_5:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.7188 - F1: 0.7117
sub_5:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4688 - F1: 0.3976
sub_5:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.5625 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5312 - F1: 0.5271
sub_6:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4688 - F1: 0.4640
sub_6:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.6250 - F1: 0.5844
sub_6:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.5077
sub_6:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5000 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.4848 - F1: 0.4527
sub_6:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.6667 - F1: 0.6459
sub_6:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5455 - F1: 0.4995
sub_6:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5758 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4242 - F1: 0.4242
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.5438
sub_6:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4545 - F1: 0.4540
sub_6:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5758 - F1: 0.5558
sub_6:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.6364 - F1: 0.6278
sub_7:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 0.7126 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.3750 - F1: 0.3651
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6250 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4375 - F1: 0.4000
sub_7:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6875 - F1: 0.6825
sub_7:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4062 - F1: 0.4010
sub_8:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4688 - F1: 0.4555
sub_8:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5625 - F1: 0.5466
sub_8:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4375 - F1: 0.4353
sub_8:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.3750 - F1: 0.3651
sub_8:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5312 - F1: 0.4386
sub_8:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4062 - F1: 0.3764
sub_8:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5938 - F1: 0.5934
sub_8:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6562 - F1: 0.6476
sub_9:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.6250 - F1: 0.6190
sub_9:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.8438 - F1: 0.8398
sub_10:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5000 - F1: 0.4921
sub_10:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5938 - F1: 0.5836
sub_10:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5938 - F1: 0.5836
sub_10:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 0.7234 - Accuracy: 0.3750 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.3750 - F1: 0.3651
sub_10:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4545 - F1: 0.4288
sub_10:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4848 - F1: 0.4527
sub_10:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.3636 - F1: 0.3613
sub_11:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.3939 - F1: 0.3452
sub_11:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5455 - F1: 0.5455
sub_11:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.3939 - F1: 0.3654
sub_11:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5758 - F1: 0.5227
sub_11:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4545 - F1: 0.4417
sub_12:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7188 - F1: 0.7046
sub_12:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6562 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6250 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7576 - F1: 0.7556
sub_12:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6667 - F1: 0.6459
sub_12:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.8182 - F1: 0.8036
sub_12:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.6875 - F1: 0.6761
sub_12:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5000 - F1: 0.4818
sub_12:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5000 - F1: 0.4980
sub_13:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5938 - F1: 0.5589
sub_13:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.6562 - F1: 0.6476
sub_13:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6250 - F1: 0.5636
sub_13:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6061 - F1: 0.6046
sub_13:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.4848 - F1: 0.4848
sub_13:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5758 - F1: 0.5658
sub_13:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6250 - F1: 0.6235
sub_13:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5312 - F1: 0.5271
sub_13:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.6875 - F1: 0.6537
sub_13:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6875 - F1: 0.6875
sub_14:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6250 - F1: 0.6250
sub_14:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.5938 - F1: 0.5733
sub_14:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.5938 - F1: 0.5733
sub_14:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5312 - F1: 0.5077
sub_14:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4375 - F1: 0.4170
sub_15:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5312 - F1: 0.5077
sub_15:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.7500 - F1: 0.7490
sub_15:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.6875 - F1: 0.6863
sub_15:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6250 - F1: 0.5844
sub_15:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4688 - F1: 0.4555
sub_15:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5625 - F1: 0.5333
sub_15:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4375 - F1: 0.4286
sub_16:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.6875 - F1: 0.6667
sub_16:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6250 - F1: 0.5844
sub_16:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5758 - F1: 0.5754
sub_17:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.4242 - F1: 0.4157
sub_17:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4545 - F1: 0.4107
sub_17:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4375 - F1: 0.4000
sub_17:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4375 - F1: 0.4375
sub_17:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6250 - F1: 0.6113
sub_17:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5000 - F1: 0.4921
sub_18:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5152 - F1: 0.4545
sub_18:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.4545 - F1: 0.4107
sub_18:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.5299
sub_18:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.7273 - F1: 0.7273
sub_18:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5625 - F1: 0.5152
sub_18:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.7500 - F1: 0.7500
sub_18:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.7188 - F1: 0.7117
sub_18:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.5625 - F1: 0.5466
sub_18:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6562 - F1: 0.6476
sub_19:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5625 - F1: 0.5152
sub_19:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.4688 - F1: 0.4231
sub_19:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.5938 - F1: 0.5589
sub_19:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5625 - F1: 0.5625
sub_19:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.7188 - F1: 0.7163
sub_19:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.7500 - F1: 0.7333
sub_19:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.5938 - F1: 0.5393
sub_20:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5312 - F1: 0.5195
sub_20:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6562 - F1: 0.6102
sub_20:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.6364 - F1: 0.6333
sub_20:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5455 - F1: 0.5438
sub_20:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6364 - F1: 0.6360
sub_21:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.5312 - F1: 0.5308
sub_21:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.5312 - F1: 0.5271
sub_21:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.7097 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5625 - F1: 0.5152
sub_21:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.5312 - F1: 0.5195
sub_21:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4375 - F1: 0.4375
sub_21:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.5000 - F1: 0.4921
sub_22:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5938 - F1: 0.5589
sub_22:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5312 - F1: 0.5271
sub_22:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.5608
sub_22:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6364 - F1: 0.5909
sub_22:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6667 - F1: 0.6459
sub_22:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4848 - F1: 0.4672
sub_22:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.5758 - F1: 0.5227
sub_22:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5000 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5000 - F1: 0.4459
sub_22:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5625 - F1: 0.5466
sub_23:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.7273 - F1: 0.7179
sub_23:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.6970 - F1: 0.6827
sub_23:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.4848 - F1: 0.4829
sub_23:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.5455 - F1: 0.5387
sub_23:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.5938 - F1: 0.5901
sub_23:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.4980
sub_23:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.7273 - F1: 0.7102
sub_23:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.7273 - F1: 0.6997
sub_23:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.7879 - F1: 0.7746
sub_24:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4375 - F1: 0.4286
sub_24:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6875 - F1: 0.6825
sub_24:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4062 - F1: 0.4010
sub_24:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6562 - F1: 0.6390
sub_24:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.3438 - F1: 0.3379
sub_24:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.5455 - F1: 0.5455
sub_25:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5758 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5758 - F1: 0.5722
sub_25:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5455 - F1: 0.4995
sub_25:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4545 - F1: 0.4540
sub_25:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4375 - F1: 0.4286
sub_25:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5312 - F1: 0.5308
sub_25:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5000 - F1: 0.4459
sub_25:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5000 - F1: 0.4459
sub_25:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4688 - F1: 0.4421
sub_26:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.6970 - F1: 0.6827
sub_26:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.6667 - F1: 0.6667
sub_26:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7273 - F1: 0.7179
sub_26:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.6667 - F1: 0.6159
sub_26:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.6364 - F1: 0.6278
sub_26:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.8125 - F1: 0.8000
sub_26:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.7188 - F1: 0.6811
sub_26:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.6875 - F1: 0.6364
sub_26:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.7812 - F1: 0.7758
sub_27:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4242 - F1: 0.4221
sub_27:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5758 - F1: 0.5754
sub_27:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.4242 - F1: 0.4157
sub_27:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4545 - F1: 0.4107
sub_27:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4375 - F1: 0.4000
sub_27:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4375 - F1: 0.4375
sub_27:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.6562 - F1: 0.6532
sub_28:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.5312 - F1: 0.4684
sub_28:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.6562 - F1: 0.6476
sub_28:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.5625
sub_29:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.5736 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.7812 - F1: 0.7625
sub_29:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.7500 - F1: 0.7333
sub_29:Test (Best Model) - Loss: 0.5830 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.5559 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.8125 - F1: 0.8057
sub_29:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.7812 - F1: 0.7625
sub_29:Test (Best Model) - Loss: 0.6093 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.5395 - Accuracy: 0.8788 - F1: 0.8759
sub_29:Test (Best Model) - Loss: 0.5762 - Accuracy: 0.7879 - F1: 0.7847
sub_29:Test (Best Model) - Loss: 0.6125 - Accuracy: 0.6970 - F1: 0.6944
sub_29:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.8788 - F1: 0.8731
sub_29:Test (Best Model) - Loss: 0.5510 - Accuracy: 0.8788 - F1: 0.8759

=== Summary Results ===

acc: 59.38 ± 7.37
F1: 57.70 ± 7.45
acc-in: 65.19 ± 6.43
F1-in: 63.51 ± 6.60
