lr: 1e-06
sub_2:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.6364 - F1: 0.6192
sub_1:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.4848 - F1: 0.4772
sub_1:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.3333 - F1: 0.3177
sub_3:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.4170
sub_1:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.4421
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5938 - F1: 0.4793
sub_1:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5938 - F1: 0.5733
sub_2:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4688 - F1: 0.4421
sub_3:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.2500 - F1: 0.2471
sub_1:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.3939 - F1: 0.3452
sub_2:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.2500 - F1: 0.2000
sub_2:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5152 - F1: 0.3889
sub_3:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4848 - F1: 0.4063
sub_2:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4062 - F1: 0.3267
sub_1:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.3333 - F1: 0.3327
sub_3:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5152 - F1: 0.3400
sub_2:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.2727 - F1: 0.2667
sub_2:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.3333 - F1: 0.3177
sub_1:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4545 - F1: 0.3125
sub_2:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4848 - F1: 0.4063
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.7188 - F1: 0.6811
sub_2:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5000 - F1: 0.4459
sub_2:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6061 - F1: 0.4850
sub_1:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5758 - F1: 0.5754
sub_1:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5312 - F1: 0.3469
sub_3:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4545 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5152 - F1: 0.5147
sub_5:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.5135
sub_6:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6875 - F1: 0.6875
sub_4:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4848 - F1: 0.4772
sub_5:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.9375 - F1: 0.9365
sub_5:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5312 - F1: 0.3469
sub_4:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.3125 - F1: 0.2667
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.6562 - F1: 0.5883
sub_5:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.3125 - F1: 0.2667
sub_6:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.3636 - F1: 0.2993
sub_5:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4242 - F1: 0.3365
sub_4:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4688 - F1: 0.3976
sub_6:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.3939 - F1: 0.3182
sub_4:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.6364 - F1: 0.6071
sub_5:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.3333 - F1: 0.2500
sub_4:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4848 - F1: 0.3718
sub_4:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5152 - F1: 0.4261
sub_5:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4242 - F1: 0.2979
sub_4:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5455 - F1: 0.4995
sub_4:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.6364 - F1: 0.6071
sub_5:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6667 - F1: 0.6617
sub_5:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5938 - F1: 0.4793
sub_6:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4848 - F1: 0.4063
sub_4:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5455 - F1: 0.3529
sub_5:Test (Best Model) - Loss: 0.6756 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.7169 - Accuracy: 0.5152 - F1: 0.3400
sub_5:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4062 - F1: 0.2889
sub_5:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.8125 - F1: 0.8125
sub_9:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.9062 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.2812 - F1: 0.2805
sub_9:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.2812 - F1: 0.2451
sub_7:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.7500 - F1: 0.7409
sub_8:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.5312 - F1: 0.3469
sub_9:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.0938 - F1: 0.0857
sub_8:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4062 - F1: 0.3552
sub_9:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6562 - F1: 0.5594
sub_7:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4688 - F1: 0.4682
sub_9:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.2500 - F1: 0.2227
sub_9:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.4062 - F1: 0.2889
sub_7:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5625 - F1: 0.4909
sub_8:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5625 - F1: 0.5466
sub_9:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.3750 - F1: 0.2727
sub_8:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4062 - F1: 0.2889
sub_7:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.4688 - F1: 0.3637
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.7188 - F1: 0.6811
sub_7:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4688 - F1: 0.3976
sub_9:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.8125 - F1: 0.8000
sub_7:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5938 - F1: 0.5901
sub_8:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.9688 - F1: 0.9685
sub_7:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4062 - F1: 0.2889
sub_8:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5938 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.7191 - Accuracy: 0.5312 - F1: 0.3469
sub_8:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.4688 - F1: 0.3976
sub_7:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.3438 - F1: 0.2558
sub_11:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4242 - F1: 0.3660
sub_12:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.7812 - F1: 0.7625
sub_11:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.5152 - F1: 0.4545
sub_12:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5312 - F1: 0.5308
sub_11:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.1212 - F1: 0.1212
sub_10:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.4921
sub_11:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.3750 - F1: 0.3725
sub_10:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.3816
sub_11:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.3939 - F1: 0.2826
sub_12:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5938 - F1: 0.4340
sub_10:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.3939 - F1: 0.3654
sub_10:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.8438 - F1: 0.8398
sub_12:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4545 - F1: 0.3543
sub_10:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.3939 - F1: 0.3452
sub_12:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.3030 - F1: 0.2792
sub_11:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.3939 - F1: 0.2826
sub_11:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.4848 - F1: 0.3718
sub_10:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.7500 - F1: 0.7460
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5152 - F1: 0.4545
sub_12:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4242 - F1: 0.2979
sub_12:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4688 - F1: 0.4231
sub_11:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6061 - F1: 0.4850
sub_10:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6667 - F1: 0.6330
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.4459
sub_10:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.7273 - F1: 0.6997
sub_11:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.6061 - F1: 0.5926
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.4459
sub_11:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7115 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.4688 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.4688 - F1: 0.3191
sub_15:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.3438 - F1: 0.3273
sub_15:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.3750 - F1: 0.3750
sub_14:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4062 - F1: 0.3914
sub_13:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5938 - F1: 0.5589
sub_15:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.4688 - F1: 0.3637
sub_14:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4375 - F1: 0.4000
sub_15:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.4688 - F1: 0.4231
sub_13:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4688 - F1: 0.3191
sub_15:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.4182
sub_14:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.3750 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5758 - F1: 0.5558
sub_15:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.4375 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.4589
sub_13:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5455 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.6667 - F1: 0.6330
sub_15:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4545 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.6061 - F1: 0.5815
sub_15:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4062 - F1: 0.2889
sub_14:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6562 - F1: 0.5883
sub_14:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5938 - F1: 0.4340
sub_14:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4688 - F1: 0.3637
sub_13:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6970 - F1: 0.6944
sub_16:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5152 - F1: 0.5147
sub_18:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.5455
sub_16:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.3750 - F1: 0.3333
sub_17:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.6364 - F1: 0.6071
sub_18:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5455 - F1: 0.5387
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4545 - F1: 0.3864
sub_16:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.4818
sub_18:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4375 - F1: 0.4170
sub_17:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.2727 - F1: 0.2385
sub_16:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5000 - F1: 0.3816
sub_18:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.6250 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.3750 - F1: 0.3074
sub_17:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.3636 - F1: 0.2993
sub_18:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.6875 - F1: 0.6825
sub_17:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5152 - F1: 0.4261
sub_18:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.6562 - F1: 0.5594
sub_17:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.6562 - F1: 0.6532
sub_17:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6250 - F1: 0.5362
sub_18:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5000 - F1: 0.4182
sub_17:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5312 - F1: 0.3469
sub_19:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.8125 - F1: 0.8000
sub_20:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.8125 - F1: 0.8000
sub_19:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4062 - F1: 0.3914
sub_19:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5938 - F1: 0.4793
sub_20:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.5625 - F1: 0.4167
sub_21:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.7188 - F1: 0.6632
sub_19:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.0312 - F1: 0.0303
sub_20:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4375 - F1: 0.3766
sub_20:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.6875 - F1: 0.6875
sub_20:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.3750 - F1: 0.3074
sub_19:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.9062 - F1: 0.9062
sub_21:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.3438 - F1: 0.3273
sub_20:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5000 - F1: 0.4182
sub_21:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.3125 - F1: 0.2874
sub_19:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5000 - F1: 0.4182
sub_20:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5758 - F1: 0.5417
sub_21:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.3438 - F1: 0.2558
sub_21:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.3438 - F1: 0.2558
sub_20:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.6061 - F1: 0.5196
sub_19:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.8125 - F1: 0.8000
sub_20:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6364 - F1: 0.6192
sub_19:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5312 - F1: 0.5195
sub_21:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3750 - F1: 0.3074
sub_19:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.7500 - F1: 0.7091
sub_20:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5455 - F1: 0.4058
sub_19:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 0.7311 - Accuracy: 0.4688 - F1: 0.3637
sub_22:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.7576 - F1: 0.7381
sub_22:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5625 - F1: 0.4909
sub_24:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4242 - F1: 0.3660
sub_23:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.3030 - F1: 0.2326
sub_24:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4375 - F1: 0.4286
sub_22:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.3939 - F1: 0.3452
sub_23:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.7273 - F1: 0.6997
sub_24:Test (Best Model) - Loss: 0.7135 - Accuracy: 0.2812 - F1: 0.2195
sub_22:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.4545 - F1: 0.4417
sub_23:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4545 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.4545 - F1: 0.4107
sub_23:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.3125 - F1: 0.3016
sub_22:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5938 - F1: 0.5733
sub_23:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.4921
sub_22:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.6250 - F1: 0.5362
sub_23:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5312 - F1: 0.4684
sub_24:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.3438 - F1: 0.3108
sub_23:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4688 - F1: 0.3637
sub_23:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.4688 - F1: 0.3637
sub_24:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5312 - F1: 0.4910
sub_22:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.5455 - F1: 0.5171
sub_24:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.8438 - F1: 0.8303
sub_23:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6364 - F1: 0.5696
sub_24:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4375 - F1: 0.3455
sub_24:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.7812 - F1: 0.7703
sub_23:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5758 - F1: 0.5722
sub_24:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4062 - F1: 0.2889
sub_23:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.4848 - F1: 0.3718
sub_24:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5312 - F1: 0.3469
sub_23:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6970 - F1: 0.6944
sub_25:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.8182 - F1: 0.8036
sub_27:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5152 - F1: 0.5147
sub_26:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.8485 - F1: 0.8479
sub_27:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.6364 - F1: 0.6071
sub_25:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.7273 - F1: 0.7263
sub_26:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.3636 - F1: 0.3419
sub_27:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5758 - F1: 0.4225
sub_26:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4545 - F1: 0.3864
sub_26:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.2727 - F1: 0.2385
sub_26:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.3750 - F1: 0.3333
sub_25:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5938 - F1: 0.5589
sub_27:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.3636 - F1: 0.2993
sub_25:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.3750 - F1: 0.3333
sub_26:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.2812 - F1: 0.2749
sub_27:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.3125 - F1: 0.2381
sub_26:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.2812 - F1: 0.2805
sub_27:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5152 - F1: 0.4261
sub_25:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6250 - F1: 0.5362
sub_26:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5000 - F1: 0.4182
sub_25:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.6250 - F1: 0.5000
sub_27:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.4667
sub_26:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6250 - F1: 0.5844
sub_27:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.7812 - F1: 0.7625
sub_26:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.7500 - F1: 0.7091
sub_27:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5312 - F1: 0.3469
sub_25:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.9375 - F1: 0.9373
sub_26:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.9375 - F1: 0.9373
sub_25:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4062 - F1: 0.2889
sub_26:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.7812 - F1: 0.7758
sub_28:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.4375 - F1: 0.4353
sub_29:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.4818
sub_29:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.3438 - F1: 0.3273
sub_28:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.3125 - F1: 0.3016
sub_29:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.4375 - F1: 0.4170
sub_29:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4062 - F1: 0.2889
sub_28:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4688 - F1: 0.3637
sub_29:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4688 - F1: 0.3637
sub_28:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.6250 - F1: 0.6190
sub_29:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.7188 - F1: 0.7163
sub_28:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.7188 - F1: 0.6632
sub_29:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.6364 - F1: 0.6360
sub_28:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6250 - F1: 0.6190
sub_28:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.9091 - F1: 0.9077
sub_28:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.4848 - F1: 0.3718
sub_28:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.5455 - F1: 0.3529

=== Summary Results ===

acc: 51.56 ± 3.47
F1: 43.60 ± 3.47
acc-in: 49.43 ± 2.75
F1-in: 41.72 ± 3.11
runing time: 1089.61 seconds
