lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.1912 - F1: 0.1160
sub_1:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2353 - F1: 0.1471
sub_1:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2319 - F1: 0.1469
sub_1:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2754 - F1: 0.1309
sub_1:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2029 - F1: 0.1214
sub_1:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2319 - F1: 0.1492
sub_1:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2647 - F1: 0.1111
sub_1:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1059
sub_1:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.3188 - F1: 0.2149
sub_2:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.1594 - F1: 0.1038
sub_2:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2609 - F1: 0.1084
sub_2:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2174 - F1: 0.0915
sub_2:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.1594 - F1: 0.0864
sub_3:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.1111
sub_3:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2941 - F1: 0.1676
sub_3:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.3088 - F1: 0.1823
sub_3:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2319 - F1: 0.1162
sub_3:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2609 - F1: 0.1608
sub_3:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2754 - F1: 0.1778
sub_3:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2899 - F1: 0.1753
sub_3:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.1739 - F1: 0.1002
sub_3:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2029 - F1: 0.1373
sub_3:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.1884 - F1: 0.1566
sub_3:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2464 - F1: 0.1024
sub_3:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2609 - F1: 0.1059
sub_4:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3188 - F1: 0.1980
sub_4:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2609 - F1: 0.1059
sub_4:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3333 - F1: 0.2139
sub_4:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3333 - F1: 0.2176
sub_4:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.4058 - F1: 0.3354
sub_4:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2319 - F1: 0.1142
sub_4:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2609 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3188 - F1: 0.2321
sub_5:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3382 - F1: 0.2215
sub_5:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.3971 - F1: 0.2834
sub_5:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2353 - F1: 0.1111
sub_5:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2941 - F1: 0.1561
sub_5:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.2500 - F1: 0.1049
sub_5:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.2647 - F1: 0.1059
sub_5:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3088 - F1: 0.1779
sub_5:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2647 - F1: 0.1084
sub_6:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2941 - F1: 0.1676
sub_6:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2794 - F1: 0.1765
sub_6:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3529 - F1: 0.2242
sub_6:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2899 - F1: 0.1559
sub_6:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2609 - F1: 0.1396
sub_6:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.2754 - F1: 0.1612
sub_6:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2609 - F1: 0.1059
sub_6:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2899 - F1: 0.1867
sub_6:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2754 - F1: 0.1842
sub_6:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2754 - F1: 0.1854
sub_6:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2609 - F1: 0.1071
sub_6:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3188 - F1: 0.2565
sub_7:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.3235 - F1: 0.2079
sub_7:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.3088 - F1: 0.1799
sub_7:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2941 - F1: 0.2399
sub_7:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2500 - F1: 0.1012
sub_7:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2941 - F1: 0.1552
sub_7:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1059
sub_7:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2206 - F1: 0.1337
sub_8:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3382 - F1: 0.2187
sub_8:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2941 - F1: 0.1571
sub_8:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3088 - F1: 0.2096
sub_8:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.1912 - F1: 0.1286
sub_8:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2500 - F1: 0.1208
sub_8:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2206 - F1: 0.1765
sub_8:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2941 - F1: 0.1748
sub_8:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2941 - F1: 0.1885
sub_8:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2794 - F1: 0.1322
sub_8:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3235 - F1: 0.2027
sub_8:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.3235 - F1: 0.2087
sub_9:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.3088 - F1: 0.1930
sub_9:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2206 - F1: 0.1265
sub_9:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2500 - F1: 0.1213
sub_9:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.1765 - F1: 0.1131
sub_9:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2206 - F1: 0.1212
sub_9:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2941 - F1: 0.1539
sub_9:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.3088 - F1: 0.1987
sub_10:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2899 - F1: 0.1717
sub_10:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.3043 - F1: 0.2225
sub_10:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2609 - F1: 0.1404
sub_10:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2319 - F1: 0.1357
sub_11:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2754 - F1: 0.1310
sub_11:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2754 - F1: 0.1310
sub_11:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2899 - F1: 0.1539
sub_11:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2754 - F1: 0.1309
sub_11:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2174 - F1: 0.1203
sub_11:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2754 - F1: 0.1956
sub_11:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2794 - F1: 0.1826
sub_12:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2794 - F1: 0.1830
sub_12:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2319 - F1: 0.1111
sub_12:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2174 - F1: 0.1800
sub_12:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.1449 - F1: 0.1223
sub_12:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2319 - F1: 0.1000
sub_12:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1264
sub_12:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3382 - F1: 0.2225
sub_12:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2647 - F1: 0.1098
sub_13:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.3088 - F1: 0.2236
sub_13:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2647 - F1: 0.1267
sub_13:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2794 - F1: 0.1321
sub_13:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2794 - F1: 0.1854
sub_13:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3043 - F1: 0.1984
sub_13:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2941 - F1: 0.1607
sub_13:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2206 - F1: 0.0915
sub_13:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.3088 - F1: 0.2159
sub_13:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2059 - F1: 0.1201
sub_13:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3529 - F1: 0.2216
sub_14:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3235 - F1: 0.2120
sub_14:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.3235 - F1: 0.2087
sub_14:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2647 - F1: 0.1059
sub_14:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3529 - F1: 0.2307
sub_14:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2500 - F1: 0.1446
sub_14:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3529 - F1: 0.2311
sub_15:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1325
sub_15:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2941 - F1: 0.1808
sub_15:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.3382 - F1: 0.2212
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2500 - F1: 0.1451
sub_15:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1059
sub_15:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1702
sub_15:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2206 - F1: 0.1448
sub_16:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2794 - F1: 0.1321
sub_16:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2941 - F1: 0.1748
sub_16:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2500 - F1: 0.1562
sub_16:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2059 - F1: 0.0897
sub_16:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2647 - F1: 0.1059
sub_16:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2353 - F1: 0.1514
sub_16:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2206 - F1: 0.1082
sub_16:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2206 - F1: 0.1759
sub_16:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2794 - F1: 0.1581
sub_16:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2500 - F1: 0.1012
sub_16:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.3235 - F1: 0.2051
sub_17:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2319 - F1: 0.1512
sub_17:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2754 - F1: 0.1657
sub_17:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2464 - F1: 0.1598
sub_17:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2319 - F1: 0.0941
sub_17:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2464 - F1: 0.1635
sub_17:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2319 - F1: 0.1138
sub_17:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2500 - F1: 0.1224
sub_17:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1262
sub_17:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2794 - F1: 0.1322
sub_17:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3235 - F1: 0.1910
sub_18:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.1884 - F1: 0.1527
sub_18:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2754 - F1: 0.1479
sub_18:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2609 - F1: 0.1713
sub_18:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2174 - F1: 0.1455
sub_18:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2500 - F1: 0.1599
sub_18:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2353 - F1: 0.1333
sub_18:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3088 - F1: 0.1823
sub_18:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2206 - F1: 0.1479
sub_18:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.1765 - F1: 0.1026
sub_18:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2500 - F1: 0.1443
sub_18:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1765 - F1: 0.1210
sub_18:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2500 - F1: 0.1640
sub_19:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2500 - F1: 0.1443
sub_19:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2794 - F1: 0.1484
sub_19:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.1912 - F1: 0.1508
sub_19:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2647 - F1: 0.1687
sub_19:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.3088 - F1: 0.2014
sub_19:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2059 - F1: 0.1340
sub_20:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2059 - F1: 0.0875
sub_20:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2353 - F1: 0.1970
sub_20:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2794 - F1: 0.1728
sub_20:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2500 - F1: 0.1525
sub_20:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2500 - F1: 0.1630
sub_20:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.3088 - F1: 0.2129
sub_20:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2941 - F1: 0.2080
sub_20:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2941 - F1: 0.1571
sub_20:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3529 - F1: 0.2505
sub_20:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2206 - F1: 0.1102
sub_20:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3333 - F1: 0.2364
sub_20:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2754 - F1: 0.1760
sub_21:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3088 - F1: 0.2077
sub_21:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2500 - F1: 0.1012
sub_21:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2500 - F1: 0.1392
sub_21:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2941 - F1: 0.2031
sub_21:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2500 - F1: 0.1321
sub_21:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.1059
sub_21:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2794 - F1: 0.1719
sub_21:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.3235 - F1: 0.2020
sub_21:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2059 - F1: 0.1045
sub_21:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2353 - F1: 0.1519
sub_21:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1625
sub_21:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2353 - F1: 0.1503
sub_21:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2353 - F1: 0.0964
sub_22:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2609 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2899 - F1: 0.1956
sub_22:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2500 - F1: 0.1104
sub_22:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.2794 - F1: 0.1321
sub_23:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2609 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3188 - F1: 0.1925
sub_23:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2464 - F1: 0.1918
sub_23:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.2206 - F1: 0.1694
sub_23:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2500 - F1: 0.1118
sub_23:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2794 - F1: 0.1478
sub_23:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2899 - F1: 0.1559
sub_23:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2464 - F1: 0.1221
sub_23:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.1263
sub_23:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2174 - F1: 0.1394
sub_23:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2029 - F1: 0.1270
sub_24:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2941 - F1: 0.1571
sub_24:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3088 - F1: 0.1995
sub_24:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2500 - F1: 0.1000
sub_24:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2941 - F1: 0.1968
sub_24:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2500 - F1: 0.1000
sub_24:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2206 - F1: 0.1443
sub_24:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2794 - F1: 0.1321
sub_24:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3382 - F1: 0.2204
sub_24:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2059 - F1: 0.1412
sub_24:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2941 - F1: 0.2054
sub_24:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2500 - F1: 0.1716
sub_24:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2941 - F1: 0.2267
sub_24:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.2941 - F1: 0.2407
sub_25:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2464 - F1: 0.1620
sub_25:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3676 - F1: 0.2304
sub_25:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.1912 - F1: 0.1012
sub_25:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2794 - F1: 0.1321
sub_25:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2500 - F1: 0.1000
sub_25:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2500 - F1: 0.1000
sub_25:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2059 - F1: 0.1023
sub_26:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2174 - F1: 0.1418
sub_26:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2794 - F1: 0.1322
sub_26:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3235 - F1: 0.1910
sub_26:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2941 - F1: 0.1539
sub_26:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2794 - F1: 0.1662
sub_26:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2647 - F1: 0.1514
sub_26:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2353 - F1: 0.1279
sub_26:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3088 - F1: 0.2112
sub_27:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2319 - F1: 0.1512
sub_27:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2754 - F1: 0.1657
sub_27:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2464 - F1: 0.1598
sub_27:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2319 - F1: 0.0941
sub_27:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2464 - F1: 0.1635
sub_27:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2319 - F1: 0.1138
sub_27:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2500 - F1: 0.1224
sub_27:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1262
sub_27:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2794 - F1: 0.1322
sub_27:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3235 - F1: 0.1910
sub_28:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2647 - F1: 0.1262
sub_28:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2500 - F1: 0.1565
sub_28:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2794 - F1: 0.1580
sub_28:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2206 - F1: 0.1228
sub_28:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2353 - F1: 0.1149
sub_28:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.1618 - F1: 0.0797
sub_28:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2353 - F1: 0.0952
sub_28:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2059 - F1: 0.0864
sub_29:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2500 - F1: 0.1664
sub_29:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2206 - F1: 0.1403
sub_29:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2941 - F1: 0.1552
sub_29:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2794 - F1: 0.1845
sub_29:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2609 - F1: 0.1804
sub_29:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.2174 - F1: 0.1574
sub_29:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.1739 - F1: 0.0944
sub_29:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2609 - F1: 0.1034
sub_29:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.1159 - F1: 0.0654

=== Summary Results ===

acc: 26.37 ± 1.19
F1: 13.30 ± 1.43
acc-in: 29.65 ± 2.34
F1-in: 17.70 ± 2.60
