lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.6562 - F1: 0.6532
sub_1:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.6562 - F1: 0.6559
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.4818
sub_1:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5938 - F1: 0.5135
sub_1:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.7576 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.6970 - F1: 0.6827
sub_1:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.6061 - F1: 0.5662
sub_1:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.7273 - F1: 0.7179
sub_1:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5938 - F1: 0.5901
sub_1:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6562 - F1: 0.6532
sub_1:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6562 - F1: 0.6559
sub_2:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5455 - F1: 0.5387
sub_2:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.7273 - F1: 0.7232
sub_2:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6667 - F1: 0.6459
sub_2:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4688 - F1: 0.4421
sub_2:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4688 - F1: 0.4555
sub_2:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5312 - F1: 0.5195
sub_2:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.5000 - F1: 0.4921
sub_2:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5455 - F1: 0.5438
sub_2:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.4995
sub_2:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6667 - F1: 0.6654
sub_3:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5000 - F1: 0.4921
sub_3:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.4688 - F1: 0.4640
sub_3:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5758 - F1: 0.5417
sub_3:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6970 - F1: 0.6726
sub_3:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.3333 - F1: 0.3278
sub_3:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4242 - F1: 0.4242
sub_3:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.3939 - F1: 0.3889
sub_3:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.3333 - F1: 0.3327
sub_4:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6364 - F1: 0.6278
sub_4:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6061 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5758 - F1: 0.5722
sub_4:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.6667 - F1: 0.6617
sub_4:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.6061 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.5299
sub_4:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4848 - F1: 0.4527
sub_4:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5758 - F1: 0.5558
sub_4:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5455 - F1: 0.5387
sub_5:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4062 - F1: 0.4010
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.7500 - F1: 0.7500
sub_5:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4375 - F1: 0.4375
sub_5:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.4688 - F1: 0.3976
sub_6:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4375 - F1: 0.4170
sub_6:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5625 - F1: 0.5556
sub_6:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5938 - F1: 0.5836
sub_6:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6875 - F1: 0.6825
sub_6:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6667 - F1: 0.6330
sub_6:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4545 - F1: 0.3543
sub_6:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.4242 - F1: 0.4046
sub_6:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6667 - F1: 0.6617
sub_6:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.4848 - F1: 0.4328
sub_6:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4545 - F1: 0.4417
sub_6:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6061 - F1: 0.6002
sub_6:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5455 - F1: 0.5455
sub_7:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5938 - F1: 0.5393
sub_7:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6875 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6562 - F1: 0.6559
sub_7:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6250 - F1: 0.6235
sub_7:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4062 - F1: 0.4057
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5312 - F1: 0.5077
sub_8:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5625 - F1: 0.5608
sub_8:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5312 - F1: 0.4910
sub_8:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5625 - F1: 0.5625
sub_8:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4688 - F1: 0.4640
sub_9:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6875 - F1: 0.6135
sub_9:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5312 - F1: 0.5271
sub_9:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5000 - F1: 0.4980
sub_9:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5625 - F1: 0.5466
sub_9:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.7500 - F1: 0.7460
sub_10:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.4909
sub_10:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5312 - F1: 0.4910
sub_10:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4375 - F1: 0.4286
sub_10:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5455 - F1: 0.5455
sub_10:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4848 - F1: 0.4672
sub_10:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4545 - F1: 0.4500
sub_11:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5758 - F1: 0.5722
sub_11:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4545 - F1: 0.3864
sub_11:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5758 - F1: 0.5722
sub_11:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.7273 - F1: 0.7102
sub_11:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6061 - F1: 0.6046
sub_11:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5758 - F1: 0.5754
sub_12:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.7188 - F1: 0.7046
sub_12:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5938 - F1: 0.5393
sub_12:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5938 - F1: 0.5393
sub_12:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.7576 - F1: 0.7381
sub_12:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6061 - F1: 0.5815
sub_12:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.5758 - F1: 0.4225
sub_12:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.7576 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6250 - F1: 0.6113
sub_12:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5312 - F1: 0.5271
sub_12:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5625 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5625 - F1: 0.5333
sub_12:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4688 - F1: 0.4231
sub_13:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.5608
sub_13:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5312 - F1: 0.5271
sub_13:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.5556
sub_13:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5938 - F1: 0.5934
sub_13:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6667 - F1: 0.6654
sub_13:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.4848 - F1: 0.4772
sub_13:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5455 - F1: 0.5455
sub_13:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5152 - F1: 0.5038
sub_13:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.5333
sub_13:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.8438 - F1: 0.8398
sub_13:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5312 - F1: 0.5271
sub_14:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.8125 - F1: 0.8125
sub_14:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5938 - F1: 0.5393
sub_14:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.4688 - F1: 0.4555
sub_14:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5312 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4062 - F1: 0.4010
sub_15:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5312 - F1: 0.5195
sub_15:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5625 - F1: 0.5625
sub_16:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4688 - F1: 0.4640
sub_16:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4375 - F1: 0.4353
sub_16:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4375 - F1: 0.4170
sub_16:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.3750 - F1: 0.3651
sub_16:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.2812 - F1: 0.2451
sub_17:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.3939 - F1: 0.3654
sub_17:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4242 - F1: 0.4046
sub_17:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5455 - F1: 0.5455
sub_17:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.3636 - F1: 0.3541
sub_17:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5758 - F1: 0.5754
sub_17:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.4909
sub_17:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5312 - F1: 0.5308
sub_17:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5625 - F1: 0.5625
sub_18:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5152 - F1: 0.5111
sub_18:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4545 - F1: 0.4417
sub_18:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5152 - F1: 0.5147
sub_18:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6061 - F1: 0.6002
sub_18:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.7879 - F1: 0.7847
sub_18:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5938 - F1: 0.5589
sub_18:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6250 - F1: 0.6190
sub_18:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5938 - F1: 0.5901
sub_18:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5625 - F1: 0.5556
sub_18:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.5556
sub_18:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4688 - F1: 0.4682
sub_19:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6562 - F1: 0.6390
sub_19:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6250 - F1: 0.6113
sub_19:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.5152
sub_19:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.4375 - F1: 0.3455
sub_19:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.5938 - F1: 0.5393
sub_19:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.4688 - F1: 0.4555
sub_19:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6562 - F1: 0.6390
sub_19:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5312 - F1: 0.4910
sub_19:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5312 - F1: 0.5195
sub_20:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.6250 - F1: 0.6190
sub_20:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5000 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.5333
sub_20:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5938 - F1: 0.5393
sub_20:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5455 - F1: 0.5455
sub_20:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6061 - F1: 0.6061
sub_20:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.3636 - F1: 0.3613
sub_20:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6364 - F1: 0.6333
sub_21:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4688 - F1: 0.4682
sub_21:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5312 - F1: 0.4910
sub_21:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4688 - F1: 0.4640
sub_21:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5312 - F1: 0.5308
sub_21:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.4688 - F1: 0.4555
sub_22:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6250 - F1: 0.6235
sub_22:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6250 - F1: 0.6235
sub_22:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6562 - F1: 0.6476
sub_22:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5312 - F1: 0.4684
sub_22:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5455 - F1: 0.4762
sub_22:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6061 - F1: 0.5815
sub_22:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5455 - F1: 0.4762
sub_22:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.6061 - F1: 0.6002
sub_22:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5152 - F1: 0.5147
sub_22:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5625 - F1: 0.5556
sub_22:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4062 - F1: 0.3552
sub_22:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4375 - F1: 0.4353
sub_22:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5312 - F1: 0.4684
sub_22:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6667 - F1: 0.6553
sub_23:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6364 - F1: 0.6192
sub_23:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5455 - F1: 0.5455
sub_23:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6364 - F1: 0.5909
sub_23:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.7273 - F1: 0.6997
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.5901
sub_23:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.7188 - F1: 0.7185
sub_23:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6875 - F1: 0.6667
sub_23:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.4818
sub_23:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6061 - F1: 0.6046
sub_23:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.6364 - F1: 0.5909
sub_23:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5152 - F1: 0.4762
sub_24:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.3766
sub_24:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.3750 - F1: 0.3522
sub_24:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4375 - F1: 0.4286
sub_24:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.5625 - F1: 0.5625
sub_25:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.5152 - F1: 0.5038
sub_25:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5455 - F1: 0.5438
sub_25:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.6061 - F1: 0.6002
sub_25:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.5171
sub_25:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5455 - F1: 0.5438
sub_25:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4688 - F1: 0.4640
sub_25:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.5556
sub_25:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.4818
sub_25:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5938 - F1: 0.5589
sub_25:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.3750 - F1: 0.3651
sub_25:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5625 - F1: 0.5625
sub_26:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.7273 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6667 - F1: 0.6617
sub_26:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.6364 - F1: 0.6278
sub_26:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6061 - F1: 0.5460
sub_26:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6970 - F1: 0.6827
sub_26:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.7500 - F1: 0.7409
sub_26:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7188 - F1: 0.7117
sub_26:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.8125 - F1: 0.8095
sub_26:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.7500 - F1: 0.7409
sub_27:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.3939 - F1: 0.3654
sub_27:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4242 - F1: 0.4046
sub_27:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5455 - F1: 0.5455
sub_27:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.3636 - F1: 0.3541
sub_27:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5758 - F1: 0.5754
sub_27:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.4909
sub_27:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5312 - F1: 0.5308
sub_27:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5625 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6562 - F1: 0.6532
sub_28:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.3750 - F1: 0.3725
sub_28:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.5000 - F1: 0.4980
sub_28:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4688 - F1: 0.4231
sub_28:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.4980
sub_28:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5000 - F1: 0.4459
sub_29:Test (Best Model) - Loss: 0.6393 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.6562 - F1: 0.6532
sub_29:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.8125 - F1: 0.8000
sub_29:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.7188 - F1: 0.7185
sub_29:Test (Best Model) - Loss: 0.5961 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.7812 - F1: 0.7703
sub_29:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7879 - F1: 0.7806
sub_29:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.8485 - F1: 0.8485
sub_29:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.7879 - F1: 0.7847
sub_29:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6061 - F1: 0.5815

=== Summary Results ===

acc: 57.98 ± 6.62
F1: 56.39 ± 6.73
acc-in: 63.73 ± 6.03
F1-in: 61.71 ± 6.23
