lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.2059 - F1: 0.1154
sub_1:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.2353 - F1: 0.2058
sub_1:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.2941 - F1: 0.1723
sub_1:Test (Best Model) - Loss: 0.7306 - Accuracy: 0.2941 - F1: 0.2885
sub_1:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2941 - F1: 0.1914
sub_1:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.2647 - F1: 0.1927
sub_1:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.2059 - F1: 0.1657
sub_1:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.2353 - F1: 0.1534
sub_1:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.2647 - F1: 0.2048
sub_1:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.2059 - F1: 0.1500
sub_1:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.2647 - F1: 0.1799
sub_1:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.3529 - F1: 0.2976
sub_1:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.5294 - F1: 0.5317
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.3529 - F1: 0.2637
sub_1:Test (Best Model) - Loss: 0.5982 - Accuracy: 0.5000 - F1: 0.4887
sub_2:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.4118 - F1: 0.3139
sub_2:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.4118 - F1: 0.3821
sub_2:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.2353 - F1: 0.1734
sub_2:Test (Best Model) - Loss: 0.6024 - Accuracy: 0.3529 - F1: 0.2981
sub_2:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.2353 - F1: 0.1936
sub_2:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.3824 - F1: 0.3729
sub_2:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.2647 - F1: 0.2056
sub_2:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.2647 - F1: 0.1921
sub_2:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.4118 - F1: 0.3964
sub_2:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.3235 - F1: 0.2866
sub_2:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.2941 - F1: 0.2606
sub_2:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.2059 - F1: 0.1824
sub_2:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.2941 - F1: 0.1833
sub_2:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.3824 - F1: 0.4017
sub_3:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.2059 - F1: 0.1919
sub_3:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.2353 - F1: 0.1938
sub_3:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.5000 - F1: 0.4927
sub_3:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.3824 - F1: 0.3134
sub_3:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.2353 - F1: 0.1682
sub_3:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.2647 - F1: 0.2247
sub_3:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.1471 - F1: 0.0956
sub_3:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.2941 - F1: 0.2740
sub_3:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.1471 - F1: 0.0981
sub_3:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.0882 - F1: 0.0500
sub_3:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.2647 - F1: 0.2680
sub_3:Test (Best Model) - Loss: 0.7195 - Accuracy: 0.1471 - F1: 0.1153
sub_3:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2353 - F1: 0.1861
sub_3:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.2647 - F1: 0.1756
sub_4:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.4118 - F1: 0.3646
sub_4:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.2941 - F1: 0.1765
sub_4:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.3529 - F1: 0.2826
sub_4:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.4118 - F1: 0.3922
sub_4:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.6176 - F1: 0.6429
sub_4:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.3529 - F1: 0.2250
sub_4:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.5882 - F1: 0.5707
sub_4:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.4412 - F1: 0.3881
sub_4:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.2647 - F1: 0.1945
sub_4:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.3824 - F1: 0.3293
sub_4:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.4706 - F1: 0.4741
sub_4:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.3529 - F1: 0.2978
sub_4:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.3824 - F1: 0.3178
sub_4:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.3235 - F1: 0.2928
sub_5:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.2941 - F1: 0.2571
sub_5:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.2647 - F1: 0.1880
sub_5:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.2353 - F1: 0.2242
sub_5:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.5000 - F1: 0.4212
sub_5:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.5588 - F1: 0.5028
sub_5:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.6765 - F1: 0.6811
sub_5:Test (Best Model) - Loss: 0.6222 - Accuracy: 0.3824 - F1: 0.3586
sub_5:Test (Best Model) - Loss: 0.5617 - Accuracy: 0.6176 - F1: 0.5585
sub_5:Test (Best Model) - Loss: 0.5308 - Accuracy: 0.5882 - F1: 0.5464
sub_5:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.5000 - F1: 0.3913
sub_5:Test (Best Model) - Loss: 0.5592 - Accuracy: 0.5000 - F1: 0.4793
sub_5:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.3529 - F1: 0.2923
sub_5:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.4118 - F1: 0.3513
sub_5:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.4412 - F1: 0.3776
sub_5:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.5000 - F1: 0.4401
sub_6:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.2353 - F1: 0.2244
sub_6:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.3529 - F1: 0.3155
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4412 - F1: 0.2917
sub_6:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.3529 - F1: 0.2705
sub_6:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.2647 - F1: 0.2488
sub_6:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.2647 - F1: 0.1184
sub_6:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.2941 - F1: 0.1601
sub_6:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.3529 - F1: 0.2756
sub_6:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.2647 - F1: 0.2271
sub_6:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.4706 - F1: 0.3878
sub_6:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.4412 - F1: 0.3671
sub_6:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.2353 - F1: 0.2066
sub_6:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.3529 - F1: 0.3459
sub_6:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.3235 - F1: 0.2786
sub_7:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.4412 - F1: 0.4300
sub_7:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.5000 - F1: 0.4742
sub_7:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.3235 - F1: 0.2487
sub_7:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.3824 - F1: 0.3095
sub_7:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.3529 - F1: 0.2754
sub_7:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.5588 - F1: 0.5411
sub_7:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.2647 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.3529 - F1: 0.3109
sub_7:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.5294 - F1: 0.4581
sub_7:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.3824 - F1: 0.3332
sub_7:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.2941 - F1: 0.1571
sub_7:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.3235 - F1: 0.2496
sub_7:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.4118 - F1: 0.3853
sub_7:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.5294 - F1: 0.5291
sub_8:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.2941 - F1: 0.2758
sub_8:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.2647 - F1: 0.2424
sub_8:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.3235 - F1: 0.2396
sub_8:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.3235 - F1: 0.2961
sub_8:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.2353 - F1: 0.1330
sub_8:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.3235 - F1: 0.2448
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.1909
sub_8:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.2059 - F1: 0.1266
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2941 - F1: 0.2132
sub_8:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.3235 - F1: 0.2701
sub_8:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.2353 - F1: 0.1507
sub_8:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2353 - F1: 0.1548
sub_8:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.1098
sub_9:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.2941 - F1: 0.1795
sub_9:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.1471 - F1: 0.1106
sub_9:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.1765 - F1: 0.1481
sub_9:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2941 - F1: 0.2195
sub_9:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.2059 - F1: 0.1283
sub_9:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.2941 - F1: 0.2539
sub_9:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.2647 - F1: 0.2009
sub_9:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.4412 - F1: 0.3694
sub_9:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.4118 - F1: 0.2692
sub_9:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.3824 - F1: 0.3288
sub_9:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.2941 - F1: 0.1731
sub_9:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.5882 - F1: 0.5962
sub_9:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.3235 - F1: 0.2200
sub_9:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.3529 - F1: 0.2788
sub_10:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.2059 - F1: 0.1791
sub_10:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.2647 - F1: 0.2048
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.2074
sub_10:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.1176 - F1: 0.0995
sub_10:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.2647 - F1: 0.1938
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1337
sub_10:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.3235 - F1: 0.2479
sub_10:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2353 - F1: 0.0976
sub_10:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.2647 - F1: 0.2121
sub_10:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.2941 - F1: 0.2561
sub_11:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.5000 - F1: 0.3638
sub_11:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.5870 - Accuracy: 0.3824 - F1: 0.3530
sub_11:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.3824 - F1: 0.3781
sub_11:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.3235 - F1: 0.2909
sub_11:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.2941 - F1: 0.2104
sub_11:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.3824 - F1: 0.3459
sub_11:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.2647 - F1: 0.2088
sub_11:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.3529 - F1: 0.3294
sub_11:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.2647 - F1: 0.2235
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.3824 - F1: 0.3023
sub_11:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.4118 - F1: 0.4272
sub_11:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2647 - F1: 0.2393
sub_11:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.2941 - F1: 0.2473
sub_11:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.4118 - F1: 0.3455
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.2941 - F1: 0.2779
sub_12:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.1765 - F1: 0.1131
sub_12:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.1765 - F1: 0.1364
sub_12:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.3529 - F1: 0.3171
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2353 - F1: 0.1680
sub_12:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.1471 - F1: 0.1073
sub_12:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.2353 - F1: 0.2393
sub_12:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.2059 - F1: 0.2065
sub_12:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.7302 - Accuracy: 0.3529 - F1: 0.2411
sub_12:Test (Best Model) - Loss: 0.7718 - Accuracy: 0.1176 - F1: 0.0981
sub_12:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.2647 - F1: 0.2385
sub_12:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.2353 - F1: 0.1865
sub_12:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.1176 - F1: 0.0833
sub_13:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.2059 - F1: 0.1746
sub_13:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.2353 - F1: 0.1455
sub_13:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.2059 - F1: 0.0897
sub_13:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.2647 - F1: 0.2381
sub_13:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.2353 - F1: 0.1894
sub_13:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.3235 - F1: 0.2235
sub_13:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2279
sub_13:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.2941 - F1: 0.1723
sub_13:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.2353 - F1: 0.1625
sub_13:Test (Best Model) - Loss: 0.7430 - Accuracy: 0.3235 - F1: 0.3128
sub_13:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2941 - F1: 0.1598
sub_13:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.3824 - F1: 0.3424
sub_13:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.2059 - F1: 0.1580
sub_14:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.3235 - F1: 0.2494
sub_14:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.3529 - F1: 0.2321
sub_14:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.2941 - F1: 0.2417
sub_14:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.2353 - F1: 0.2048
sub_14:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.4706 - F1: 0.4668
sub_14:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.3529 - F1: 0.2489
sub_14:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.4706 - F1: 0.3077
sub_14:Test (Best Model) - Loss: 0.5764 - Accuracy: 0.5588 - F1: 0.5376
sub_14:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.4412 - F1: 0.3750
sub_14:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.3235 - F1: 0.2114
sub_14:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.3529 - F1: 0.2484
sub_14:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.3235 - F1: 0.2611
sub_14:Test (Best Model) - Loss: 0.6284 - Accuracy: 0.4118 - F1: 0.3475
sub_14:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.3824 - F1: 0.2991
sub_15:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2941 - F1: 0.2742
sub_15:Test (Best Model) - Loss: 0.7847 - Accuracy: 0.2353 - F1: 0.2193
sub_15:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2941 - F1: 0.1863
sub_15:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.3529 - F1: 0.3372
sub_15:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.2647 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2647 - F1: 0.1098
sub_15:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.2059 - F1: 0.1708
sub_15:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.2647 - F1: 0.1732
sub_15:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.8525 - Accuracy: 0.1471 - F1: 0.1107
sub_15:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.2353 - F1: 0.1886
sub_15:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.2353 - F1: 0.1534
sub_16:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.2647 - F1: 0.1759
sub_16:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.2353 - F1: 0.1642
sub_16:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.2941 - F1: 0.2603
sub_16:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.3824 - F1: 0.3274
sub_16:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.2941 - F1: 0.2464
sub_16:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.2941 - F1: 0.2232
sub_16:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.3235 - F1: 0.2408
sub_16:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2647 - F1: 0.1707
sub_16:Test (Best Model) - Loss: 0.7111 - Accuracy: 0.2941 - F1: 0.2795
sub_16:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.2647 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.4706 - F1: 0.4443
sub_16:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.4118 - F1: 0.3683
sub_16:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.4706 - F1: 0.4214
sub_17:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.2941 - F1: 0.2571
sub_17:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.2941 - F1: 0.2306
sub_17:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.2353 - F1: 0.1306
sub_17:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.2059 - F1: 0.1754
sub_17:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.2941 - F1: 0.1552
sub_17:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.3824 - F1: 0.3117
sub_17:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.2353 - F1: 0.1578
sub_17:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.2941 - F1: 0.1552
sub_17:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.4118 - F1: 0.2684
sub_17:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.2353 - F1: 0.1578
sub_17:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.2647 - F1: 0.2219
sub_17:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2647 - F1: 0.2385
sub_17:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.1765 - F1: 0.1346
sub_17:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.3235 - F1: 0.2425
sub_18:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.2647 - F1: 0.1531
sub_18:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.2059 - F1: 0.1406
sub_18:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.2353 - F1: 0.1477
sub_18:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.2941 - F1: 0.2299
sub_18:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.3529 - F1: 0.3097
sub_18:Test (Best Model) - Loss: 0.7804 - Accuracy: 0.2647 - F1: 0.1897
sub_18:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.2353 - F1: 0.1363
sub_18:Test (Best Model) - Loss: 0.8288 - Accuracy: 0.2353 - F1: 0.1695
sub_18:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.3235 - F1: 0.2007
sub_18:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.2647 - F1: 0.1125
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2941 - F1: 0.1598
sub_18:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.3235 - F1: 0.2094
sub_19:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.3235 - F1: 0.2832
sub_19:Test (Best Model) - Loss: 0.7448 - Accuracy: 0.2647 - F1: 0.1850
sub_19:Test (Best Model) - Loss: 0.7420 - Accuracy: 0.2647 - F1: 0.2095
sub_19:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.2647 - F1: 0.1843
sub_19:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.2647 - F1: 0.1715
sub_19:Test (Best Model) - Loss: 0.6126 - Accuracy: 0.4412 - F1: 0.4359
sub_19:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.5000 - F1: 0.4368
sub_19:Test (Best Model) - Loss: 0.4871 - Accuracy: 0.5294 - F1: 0.4875
sub_19:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.3824 - F1: 0.3029
sub_19:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.3824 - F1: 0.3652
sub_19:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.4118 - F1: 0.3736
sub_19:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.5294 - F1: 0.4474
sub_19:Test (Best Model) - Loss: 0.5630 - Accuracy: 0.5588 - F1: 0.5393
sub_19:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.4118 - F1: 0.3747
sub_20:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2647 - F1: 0.2039
sub_20:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.2647 - F1: 0.1588
sub_20:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.2941 - F1: 0.2788
sub_20:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.2059 - F1: 0.1652
sub_20:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.3235 - F1: 0.2826
sub_20:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.3235 - F1: 0.2726
sub_20:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.3235 - F1: 0.2831
sub_20:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.2941 - F1: 0.2730
sub_20:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2941 - F1: 0.2833
sub_20:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2941 - F1: 0.2083
sub_20:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.3235 - F1: 0.2081
sub_20:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.2941 - F1: 0.1601
sub_20:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.2941 - F1: 0.2464
sub_20:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.5000 - F1: 0.4825
sub_20:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.2647 - F1: 0.2560
sub_21:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.2647 - F1: 0.1920
sub_21:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.2647 - F1: 0.2324
sub_21:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.3235 - F1: 0.2663
sub_21:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.5000 - F1: 0.4616
sub_21:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.2059 - F1: 0.1826
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.2353 - F1: 0.1989
sub_21:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.2059 - F1: 0.1348
sub_21:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.2941 - F1: 0.2431
sub_21:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2941 - F1: 0.2425
sub_21:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.3235 - F1: 0.2071
sub_21:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2353 - F1: 0.1515
sub_21:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.2941 - F1: 0.2659
sub_21:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.2941 - F1: 0.1946
sub_21:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.2353 - F1: 0.2095
sub_21:Test (Best Model) - Loss: 0.7502 - Accuracy: 0.2353 - F1: 0.2033
sub_22:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.2941 - F1: 0.2396
sub_22:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1741
sub_22:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.2059 - F1: 0.1712
sub_22:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.2647 - F1: 0.2639
sub_22:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.2941 - F1: 0.1938
sub_22:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.4118 - F1: 0.3703
sub_22:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.3529 - F1: 0.2649
sub_22:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.3235 - F1: 0.2403
sub_22:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.2941 - F1: 0.2214
sub_22:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.2941 - F1: 0.2026
sub_22:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.3235 - F1: 0.3022
sub_22:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.3824 - F1: 0.3193
sub_22:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.4706 - F1: 0.4184
sub_22:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.2353 - F1: 0.1924
sub_23:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.4118 - F1: 0.3506
sub_23:Test (Best Model) - Loss: 0.5463 - Accuracy: 0.5882 - F1: 0.4975
sub_23:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5000 - F1: 0.4215
sub_23:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.2353 - F1: 0.1655
sub_23:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.3824 - F1: 0.3446
sub_23:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.3824 - F1: 0.3817
sub_23:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.2647 - F1: 0.2154
sub_23:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.4118 - F1: 0.3439
sub_23:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.4706 - F1: 0.3918
sub_23:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.4412 - F1: 0.2915
sub_23:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.3824 - F1: 0.2919
sub_23:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.4118 - F1: 0.3350
sub_23:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.4118 - F1: 0.3319
sub_23:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.4706 - F1: 0.3777
sub_24:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.2353 - F1: 0.2088
sub_24:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.3235 - F1: 0.2692
sub_24:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.3235 - F1: 0.2303
sub_24:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.3529 - F1: 0.2785
sub_24:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.2941 - F1: 0.2384
sub_24:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.2941 - F1: 0.1681
sub_24:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.1765 - F1: 0.0811
sub_24:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.2059 - F1: 0.2135
sub_24:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.1765 - F1: 0.1021
sub_24:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.2353 - F1: 0.1786
sub_24:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.3824 - F1: 0.3579
sub_25:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.3824 - F1: 0.3812
sub_25:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.4118 - F1: 0.3468
sub_25:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.4118 - F1: 0.2656
sub_25:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.3529 - F1: 0.3283
sub_25:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.2059 - F1: 0.1170
sub_25:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.4706 - F1: 0.4152
sub_25:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.4118 - F1: 0.3901
sub_25:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.3235 - F1: 0.2462
sub_25:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.3824 - F1: 0.3775
sub_25:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.2353 - F1: 0.2249
sub_25:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.3235 - F1: 0.2523
sub_25:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.3235 - F1: 0.2337
sub_25:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2941 - F1: 0.2361
sub_25:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.2059 - F1: 0.1319
sub_26:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.3235 - F1: 0.2270
sub_26:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.3235 - F1: 0.2835
sub_26:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.3235 - F1: 0.3087
sub_26:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.2647 - F1: 0.2795
sub_26:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.2059 - F1: 0.2143
sub_26:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.4118 - F1: 0.3527
sub_26:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.4118 - F1: 0.3508
sub_26:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.4118 - F1: 0.3371
sub_26:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.3824 - F1: 0.3093
sub_26:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2059 - F1: 0.1371
sub_26:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.3824 - F1: 0.3214
sub_26:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.2941 - F1: 0.2127
sub_26:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.3824 - F1: 0.3139
sub_26:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.2647 - F1: 0.1250
sub_27:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.4118 - F1: 0.3724
sub_27:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.3235 - F1: 0.2225
sub_27:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.3529 - F1: 0.2988
sub_27:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.2647 - F1: 0.1682
sub_27:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.4118 - F1: 0.3862
sub_27:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.2941 - F1: 0.2587
sub_27:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.2941 - F1: 0.2259
sub_27:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2647 - F1: 0.1759
sub_27:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.1699
sub_27:Test (Best Model) - Loss: 0.7411 - Accuracy: 0.1471 - F1: 0.1051
sub_27:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.2059 - F1: 0.1970
sub_28:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.2000
sub_28:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.2059 - F1: 0.1705
sub_28:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.2647 - F1: 0.1732
sub_28:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.2353 - F1: 0.1445
sub_28:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.2647 - F1: 0.2556
sub_28:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.2941 - F1: 0.2534
sub_28:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.3235 - F1: 0.2250
sub_28:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.2647 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.3824 - F1: 0.3364
sub_28:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.4118 - F1: 0.4019
sub_28:Test (Best Model) - Loss: 0.7904 - Accuracy: 0.1471 - F1: 0.0922
sub_28:Test (Best Model) - Loss: 0.8571 - Accuracy: 0.1176 - F1: 0.0826
sub_28:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.2941 - F1: 0.2530
sub_28:Test (Best Model) - Loss: 0.7276 - Accuracy: 0.2059 - F1: 0.1362
sub_28:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.1765 - F1: 0.0769
sub_29:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.3235 - F1: 0.3284
sub_29:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.3235 - F1: 0.3225
sub_29:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.3235 - F1: 0.3206
sub_29:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.2647 - F1: 0.2736
sub_29:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.3824 - F1: 0.3040
sub_29:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.2647 - F1: 0.1857
sub_29:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.4706 - F1: 0.4193
sub_29:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.3235 - F1: 0.2724
sub_29:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.1765 - F1: 0.1340
sub_29:Test (Best Model) - Loss: 0.7953 - Accuracy: 0.1765 - F1: 0.1577
sub_29:Test (Best Model) - Loss: 0.7467 - Accuracy: 0.2353 - F1: 0.2438
sub_29:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.3235 - F1: 0.2466
sub_29:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.2353 - F1: 0.2230

=== Summary Results ===

acc:   31.22 ± 5.37
F1:    24.26 ± 6.03
acc-in:49.05 ± 5.59
F1-in: 41.72 ± 6.54
