lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.0769
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.1987
sub_1:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2941 - F1: 0.1748
sub_1:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.1471 - F1: 0.0907
sub_1:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2647 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2941 - F1: 0.1598
sub_1:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.2353 - F1: 0.1515
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1587
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.2125
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.2222
sub_2:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1458
sub_2:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1437
sub_2:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.3529 - F1: 0.3231
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.1765 - F1: 0.0789
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.2647 - F1: 0.2698
sub_2:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2059 - F1: 0.1301
sub_2:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.2941 - F1: 0.1935
sub_2:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2941 - F1: 0.2681
sub_2:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.1765 - F1: 0.1132
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2941 - F1: 0.1909
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2059 - F1: 0.1319
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2083
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3529 - F1: 0.2339
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2647 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2941 - F1: 0.1571
sub_3:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.1894
sub_3:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2941 - F1: 0.1882
sub_3:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.1471 - F1: 0.1149
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1765 - F1: 0.1164
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2647 - F1: 0.1417
sub_4:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1098
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2083
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3824 - F1: 0.3241
sub_4:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.3824 - F1: 0.2481
sub_4:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.2647 - F1: 0.1410
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3529 - F1: 0.2471
sub_4:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2941 - F1: 0.2107
sub_4:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4118 - F1: 0.3940
sub_4:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2647 - F1: 0.1781
sub_4:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2647 - F1: 0.1731
sub_4:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.2647 - F1: 0.2011
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2059 - F1: 0.1356
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.4118 - F1: 0.2908
sub_5:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5000 - F1: 0.3694
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.0952
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4118 - F1: 0.2903
sub_5:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.3529 - F1: 0.2321
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.4706 - F1: 0.4136
sub_5:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4706 - F1: 0.4275
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.3824 - F1: 0.2404
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.3529 - F1: 0.2308
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2076
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.3235 - F1: 0.2002
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.2647 - F1: 0.1154
sub_6:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.2941 - F1: 0.1542
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1071
sub_6:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.3529 - F1: 0.2294
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.1282
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.3824 - F1: 0.3119
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2941 - F1: 0.1571
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2498
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4118 - F1: 0.2843
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1986
sub_7:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2941 - F1: 0.1571
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1597
sub_7:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.4412 - F1: 0.4017
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1497
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1410
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3824 - F1: 0.2416
sub_8:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1585
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1843
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2647 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1660
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2007
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2059 - F1: 0.0854
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2941 - F1: 0.1538
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2081
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2941 - F1: 0.1538
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2611
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1654
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2094
sub_9:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2941 - F1: 0.1538
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3529 - F1: 0.3094
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2941 - F1: 0.1863
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1098
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1417
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3529 - F1: 0.2546
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2059 - F1: 0.1029
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2353 - F1: 0.1569
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2353 - F1: 0.1853
sub_10:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1548
sub_10:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.1542
sub_11:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2647 - F1: 0.1917
sub_11:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.4118 - F1: 0.3278
sub_11:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.4412 - F1: 0.3000
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.1146
sub_11:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.3235 - F1: 0.2010
sub_11:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2353 - F1: 0.1518
sub_11:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1732
sub_11:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.1962
sub_11:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2941 - F1: 0.2263
sub_11:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2647 - F1: 0.2010
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.2226
sub_11:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1071
sub_11:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.3824 - F1: 0.2500
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.1471 - F1: 0.0758
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1732
sub_12:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.3235 - F1: 0.2034
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.2182
sub_12:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2081
sub_12:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1410
sub_12:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.2353 - F1: 0.1562
sub_12:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.1218
sub_12:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2333
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.2353 - F1: 0.1278
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.2647 - F1: 0.1410
sub_12:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2353 - F1: 0.1465
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2353 - F1: 0.1081
sub_13:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2059 - F1: 0.1572
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1339
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2059 - F1: 0.0921
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1154
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.1444
sub_13:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1282
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1833
sub_13:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1575
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1863
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.1444
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2941 - F1: 0.2449
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2353 - F1: 0.1843
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1750
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.0952
sub_14:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.2647 - F1: 0.1417
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3824 - F1: 0.3051
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1682
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1021
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3529 - F1: 0.2517
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3529 - F1: 0.2375
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2623
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.0854
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1442
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.3824 - F1: 0.3040
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1098
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1542
sub_15:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2059 - F1: 0.1160
sub_15:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.1471 - F1: 0.0956
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2448
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1779
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1732
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2647 - F1: 0.1742
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2941 - F1: 0.1962
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1141
sub_16:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1414
sub_16:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.2647 - F1: 0.1951
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1471 - F1: 0.0735
sub_17:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.2647 - F1: 0.1594
sub_17:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.3529 - F1: 0.2436
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1726
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.3235 - F1: 0.2158
sub_17:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2059 - F1: 0.1486
sub_17:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1195
sub_17:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.2647 - F1: 0.2288
sub_17:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1435
sub_18:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1548
sub_18:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1125
sub_18:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1121
sub_18:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1471 - F1: 0.1270
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.3235 - F1: 0.3067
sub_18:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1098
sub_18:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1417
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.0897
sub_19:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4118 - F1: 0.2684
sub_19:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4118 - F1: 0.3071
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2124
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.3824 - F1: 0.3182
sub_19:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.3529 - F1: 0.2801
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2176
sub_20:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2941 - F1: 0.1542
sub_20:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.2353 - F1: 0.1811
sub_20:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.3824 - F1: 0.3200
sub_20:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3529 - F1: 0.2809
sub_20:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.3529 - F1: 0.2816
sub_20:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2280
sub_20:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.4118 - F1: 0.2696
sub_20:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.2647 - F1: 0.1154
sub_20:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.3824 - F1: 0.3511
sub_20:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2647 - F1: 0.1682
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.0854
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1079
sub_21:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2353 - F1: 0.1559
sub_21:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.3529 - F1: 0.2540
sub_21:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2116
sub_21:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2059 - F1: 0.1348
sub_21:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.1598
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2941 - F1: 0.1731
sub_21:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.1863
sub_21:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.2647 - F1: 0.1762
sub_22:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.1538
sub_22:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2076
sub_22:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2094
sub_22:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.2941 - F1: 0.2113
sub_22:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2941 - F1: 0.1748
sub_22:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2353 - F1: 0.1438
sub_22:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.3824 - F1: 0.2511
sub_22:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.1471 - F1: 0.0952
sub_23:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2647 - F1: 0.1414
sub_23:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5000 - F1: 0.4111
sub_23:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.2059 - F1: 0.1597
sub_23:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4118 - F1: 0.2719
sub_23:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2417
sub_23:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2941 - F1: 0.1552
sub_23:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1125
sub_23:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.3529 - F1: 0.2814
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2025
sub_23:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.3235 - F1: 0.1898
sub_23:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.3824 - F1: 0.2840
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.4118 - F1: 0.3298
sub_23:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.4412 - F1: 0.3729
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1384
sub_24:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2059 - F1: 0.1798
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1410
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.2353 - F1: 0.1786
sub_24:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2435
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.0946
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2396
sub_24:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.1471 - F1: 0.0956
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2353 - F1: 0.1625
sub_25:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.2647 - F1: 0.1071
sub_25:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.0854
sub_25:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.1765 - F1: 0.1169
sub_25:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.3235 - F1: 0.2821
sub_25:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2941 - F1: 0.1961
sub_25:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2941 - F1: 0.1571
sub_25:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1410
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2121
sub_25:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.2053
sub_26:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.3824 - F1: 0.2406
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2353 - F1: 0.1541
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.2020
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.2231
sub_26:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2941 - F1: 0.1538
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2941 - F1: 0.1580
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1216
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3529 - F1: 0.2622
sub_27:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.3235 - F1: 0.2081
sub_27:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.3235 - F1: 0.1883
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.1765 - F1: 0.1156
sub_27:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1425
sub_27:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.2647 - F1: 0.1699
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1468
sub_27:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.2647 - F1: 0.1699
sub_28:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.2353 - F1: 0.1521
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.0962
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2634
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.1571
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.3529 - F1: 0.3326
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2458
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.1874
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1154
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2473
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2059 - F1: 0.0854
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2941 - F1: 0.1911
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1430
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.3235 - F1: 0.2143
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2141
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.1765 - F1: 0.1015
sub_29:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1687
sub_29:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2353 - F1: 0.1306
sub_29:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.1765 - F1: 0.1101
sub_29:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1985
sub_29:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1716
sub_29:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.2941 - F1: 0.1863

=== Summary Results ===

acc:   27.62 ± 2.20
F1:    15.58 ± 2.47
acc-in:34.97 ± 3.12
F1-in: 21.89 ± 3.70
