lr: 0.001
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.2353 - F1: 0.1026
sub_1:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.2941 - F1: 0.1767
sub_1:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.3529 - F1: 0.2296
sub_1:Test (Best Model) - Loss: 0.9270 - Accuracy: 0.2059 - F1: 0.1521
sub_1:Test (Best Model) - Loss: 1.2518 - Accuracy: 0.2059 - F1: 0.1701
sub_1:Test (Best Model) - Loss: 0.9500 - Accuracy: 0.2353 - F1: 0.1679
sub_1:Test (Best Model) - Loss: 1.1012 - Accuracy: 0.2647 - F1: 0.1909
sub_1:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.2941 - F1: 0.1981
sub_1:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.2647 - F1: 0.1410
sub_1:Test (Best Model) - Loss: 0.7303 - Accuracy: 0.3235 - F1: 0.3179
sub_1:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.3529 - F1: 0.2676
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.3529 - F1: 0.3555
sub_2:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.3529 - F1: 0.3269
sub_2:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.2941 - F1: 0.1571
sub_2:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.3529 - F1: 0.2256
sub_2:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.2059 - F1: 0.1919
sub_2:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.2941 - F1: 0.3096
sub_2:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.2353 - F1: 0.1026
sub_2:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.4118 - F1: 0.3558
sub_2:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.4118 - F1: 0.2869
sub_2:Test (Best Model) - Loss: 0.5486 - Accuracy: 0.3529 - F1: 0.3954
sub_2:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.2941 - F1: 0.1571
sub_2:Test (Best Model) - Loss: 0.5954 - Accuracy: 0.4412 - F1: 0.3611
sub_2:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.3824 - F1: 0.3396
sub_2:Test (Best Model) - Loss: 0.7656 - Accuracy: 0.2059 - F1: 0.2097
sub_2:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.3235 - F1: 0.3026
sub_2:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.2353 - F1: 0.2033
sub_3:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.2353 - F1: 0.2424
sub_3:Test (Best Model) - Loss: 0.7088 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.2647 - F1: 0.2198
sub_3:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.2059 - F1: 0.1722
sub_3:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.1765 - F1: 0.1101
sub_3:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.2941 - F1: 0.1709
sub_3:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.2353 - F1: 0.1521
sub_3:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.2647 - F1: 0.2481
sub_3:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.1471 - F1: 0.0903
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.2353 - F1: 0.1598
sub_3:Test (Best Model) - Loss: 0.7576 - Accuracy: 0.2353 - F1: 0.1903
sub_3:Test (Best Model) - Loss: 0.7745 - Accuracy: 0.2353 - F1: 0.1584
sub_3:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.2941 - F1: 0.1850
sub_4:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.3824 - F1: 0.2500
sub_4:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.3529 - F1: 0.2292
sub_4:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.5294 - F1: 0.4711
sub_4:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.2941 - F1: 0.1633
sub_4:Test (Best Model) - Loss: 0.5901 - Accuracy: 0.4412 - F1: 0.4481
sub_4:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.4706 - F1: 0.3734
sub_4:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.3824 - F1: 0.3083
sub_4:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.3235 - F1: 0.2250
sub_4:Test (Best Model) - Loss: 0.5309 - Accuracy: 0.5294 - F1: 0.5089
sub_4:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.2647 - F1: 0.1098
sub_4:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.3529 - F1: 0.2294
sub_4:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.3824 - F1: 0.3528
sub_4:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.3529 - F1: 0.3185
sub_4:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.2941 - F1: 0.2087
sub_4:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.2647 - F1: 0.1831
sub_5:Test (Best Model) - Loss: 0.7735 - Accuracy: 0.2941 - F1: 0.1885
sub_5:Test (Best Model) - Loss: 0.7298 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.5294 - F1: 0.5185
sub_5:Test (Best Model) - Loss: 0.5143 - Accuracy: 0.5294 - F1: 0.4038
sub_5:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.3235 - F1: 0.2500
sub_5:Test (Best Model) - Loss: 0.5693 - Accuracy: 0.4706 - F1: 0.5048
sub_5:Test (Best Model) - Loss: 0.5746 - Accuracy: 0.4412 - F1: 0.3832
sub_5:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.5000 - F1: 0.4254
sub_5:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.3824 - F1: 0.3002
sub_5:Test (Best Model) - Loss: 0.7626 - Accuracy: 0.2941 - F1: 0.2167
sub_5:Test (Best Model) - Loss: 1.2238 - Accuracy: 0.4118 - F1: 0.3191
sub_5:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.2353 - F1: 0.0976
sub_5:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.3824 - F1: 0.3986
sub_5:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.3235 - F1: 0.3107
sub_6:Test (Best Model) - Loss: 0.7145 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.2353 - F1: 0.1282
sub_6:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.7435 - Accuracy: 0.3529 - F1: 0.3083
sub_6:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.2647 - F1: 0.1364
sub_6:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.3235 - F1: 0.2110
sub_6:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.3529 - F1: 0.2674
sub_6:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.3235 - F1: 0.2115
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.5000 - F1: 0.3304
sub_6:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.4118 - F1: 0.2738
sub_6:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.2941 - F1: 0.2514
sub_6:Test (Best Model) - Loss: 0.7673 - Accuracy: 0.2059 - F1: 0.1310
sub_6:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.3529 - F1: 0.2216
sub_7:Test (Best Model) - Loss: 0.5552 - Accuracy: 0.4118 - F1: 0.3934
sub_7:Test (Best Model) - Loss: 0.5875 - Accuracy: 0.4412 - F1: 0.2881
sub_7:Test (Best Model) - Loss: 0.7819 - Accuracy: 0.3529 - F1: 0.2989
sub_7:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.3529 - F1: 0.2520
sub_7:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.4118 - F1: 0.3500
sub_7:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.4118 - F1: 0.3705
sub_7:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.2647 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.4118 - F1: 0.3923
sub_7:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.3235 - F1: 0.2834
sub_7:Test (Best Model) - Loss: 0.5322 - Accuracy: 0.5294 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.3529 - F1: 0.2361
sub_7:Test (Best Model) - Loss: 0.7204 - Accuracy: 0.2941 - F1: 0.1569
sub_7:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.3529 - F1: 0.2943
sub_7:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.5294 - F1: 0.5181
sub_7:Test (Best Model) - Loss: 0.5367 - Accuracy: 0.5294 - F1: 0.5256
sub_8:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.2647 - F1: 0.1699
sub_8:Test (Best Model) - Loss: 0.8443 - Accuracy: 0.2353 - F1: 0.2087
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1715
sub_8:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.3235 - F1: 0.2254
sub_8:Test (Best Model) - Loss: 0.8335 - Accuracy: 0.2353 - F1: 0.1946
sub_8:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.2941 - F1: 0.1569
sub_8:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.2059 - F1: 0.0875
sub_8:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.2647 - F1: 0.1635
sub_8:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.3235 - F1: 0.2136
sub_8:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2353 - F1: 0.1722
sub_8:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.3824 - F1: 0.2481
sub_8:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.2647 - F1: 0.1834
sub_9:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.2941 - F1: 0.1882
sub_9:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.2647 - F1: 0.1699
sub_9:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.2941 - F1: 0.2154
sub_9:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.3529 - F1: 0.2338
sub_9:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.2353 - F1: 0.1810
sub_9:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.3824 - F1: 0.3169
sub_9:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.5136 - Accuracy: 0.4118 - F1: 0.2879
sub_9:Test (Best Model) - Loss: 0.5532 - Accuracy: 0.3235 - F1: 0.2758
sub_9:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.3824 - F1: 0.3294
sub_9:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.3824 - F1: 0.3328
sub_9:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.3529 - F1: 0.2303
sub_9:Test (Best Model) - Loss: 0.7636 - Accuracy: 0.3235 - F1: 0.2005
sub_9:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.3235 - F1: 0.2094
sub_10:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.3235 - F1: 0.2491
sub_10:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.2941 - F1: 0.2708
sub_10:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.2353 - F1: 0.1000
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6857 - 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: 0.6845 - Accuracy: 0.2647 - F1: 0.2065
sub_10:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.8967 - Accuracy: 0.4412 - F1: 0.3543
sub_11:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.4118 - F1: 0.3637
sub_11:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.3529 - F1: 0.2445
sub_11:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2059 - F1: 0.1810
sub_11:Test (Best Model) - Loss: 0.7270 - Accuracy: 0.2647 - F1: 0.2245
sub_11:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.2353 - F1: 0.1521
sub_11:Test (Best Model) - Loss: 0.8605 - Accuracy: 0.2353 - F1: 0.1904
sub_11:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.2647 - F1: 0.1782
sub_11:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.4412 - F1: 0.3739
sub_11:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.4706 - F1: 0.3197
sub_11:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.2353 - F1: 0.1478
sub_11:Test (Best Model) - Loss: 0.7449 - Accuracy: 0.2647 - F1: 0.2057
sub_11:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.2353 - F1: 0.1081
sub_11:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.2647 - F1: 0.1875
sub_12:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.1765 - F1: 0.1171
sub_12:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.2647 - F1: 0.2093
sub_12:Test (Best Model) - Loss: 0.7675 - Accuracy: 0.2941 - F1: 0.2723
sub_12:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.1471 - F1: 0.1235
sub_12:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.2647 - F1: 0.1469
sub_12:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.1765 - F1: 0.1278
sub_12:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.0099 - Accuracy: 0.0294 - F1: 0.0357
sub_12:Test (Best Model) - Loss: 0.7169 - Accuracy: 0.1765 - F1: 0.1282
sub_12:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.2941 - F1: 0.1850
sub_12:Test (Best Model) - Loss: 0.7296 - Accuracy: 0.2647 - F1: 0.1597
sub_12:Test (Best Model) - Loss: 1.2478 - Accuracy: 0.2941 - F1: 0.2274
sub_12:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.1765 - F1: 0.1145
sub_13:Test (Best Model) - Loss: 0.7114 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.9629 - Accuracy: 0.2353 - F1: 0.0976
sub_13:Test (Best Model) - Loss: 0.8948 - Accuracy: 0.1471 - F1: 0.0900
sub_13:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.3529 - F1: 0.2928
sub_13:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.2059 - F1: 0.0854
sub_13:Test (Best Model) - Loss: 0.9170 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.7707 - Accuracy: 0.2647 - F1: 0.2026
sub_13:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.1765 - F1: 0.1182
sub_13:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.2353 - F1: 0.0952
sub_13:Test (Best Model) - Loss: 0.7919 - Accuracy: 0.1176 - F1: 0.0769
sub_13:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.2941 - F1: 0.1571
sub_13:Test (Best Model) - Loss: 0.7937 - Accuracy: 0.1765 - F1: 0.0789
sub_14:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.4118 - F1: 0.2755
sub_14:Test (Best Model) - Loss: 0.5840 - Accuracy: 0.4412 - F1: 0.3493
sub_14:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.3235 - F1: 0.2836
sub_14:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.2941 - F1: 0.1580
sub_14:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.3824 - F1: 0.2907
sub_14:Test (Best Model) - Loss: 0.8099 - Accuracy: 0.1765 - F1: 0.1500
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.3529 - F1: 0.2288
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1577
sub_14:Test (Best Model) - Loss: 0.6076 - Accuracy: 0.3824 - F1: 0.2841
sub_14:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.4118 - F1: 0.3460
sub_14:Test (Best Model) - Loss: 0.7874 - Accuracy: 0.2353 - F1: 0.1899
sub_14:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.2941 - F1: 0.2352
sub_14:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.3529 - F1: 0.2490
sub_14:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.2647 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 1.0924 - Accuracy: 0.1765 - F1: 0.1357
sub_15:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.2647 - F1: 0.1687
sub_15:Test (Best Model) - Loss: 0.7370 - Accuracy: 0.1176 - F1: 0.1088
sub_15:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.3235 - F1: 0.2522
sub_15:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.2647 - F1: 0.2061
sub_15:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1716
sub_15:Test (Best Model) - Loss: 0.7859 - Accuracy: 0.2353 - F1: 0.1731
sub_15:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.2941 - F1: 0.1552
sub_15:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.2059 - F1: 0.0854
sub_15:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.2941 - F1: 0.2109
sub_15:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.2941 - F1: 0.1538
sub_16:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.3235 - F1: 0.2179
sub_16:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.3824 - F1: 0.2952
sub_16:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.7747 - Accuracy: 0.3824 - F1: 0.3137
sub_16:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.8318 - Accuracy: 0.1765 - F1: 0.1664
sub_16:Test (Best Model) - Loss: 0.7752 - Accuracy: 0.2353 - F1: 0.1987
sub_16:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.3824 - F1: 0.2614
sub_16:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.3529 - F1: 0.2343
sub_16:Test (Best Model) - Loss: 0.7375 - Accuracy: 0.1765 - F1: 0.1007
sub_16:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.5722 - Accuracy: 0.4706 - F1: 0.4563
sub_16:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.7591 - Accuracy: 0.2059 - F1: 0.2012
sub_17:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.2647 - F1: 0.1430
sub_17:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.2941 - F1: 0.1905
sub_17:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.2647 - F1: 0.2203
sub_17:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.2059 - F1: 0.1369
sub_17:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.4118 - F1: 0.2844
sub_17:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.4118 - F1: 0.3226
sub_17:Test (Best Model) - Loss: 0.7987 - Accuracy: 0.2941 - F1: 0.2539
sub_17:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.2353 - F1: 0.1444
sub_17:Test (Best Model) - Loss: 0.7126 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.7609 - Accuracy: 0.2647 - F1: 0.1682
sub_17:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.2353 - F1: 0.1709
sub_17:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.2059 - F1: 0.1172
sub_17:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.2353 - F1: 0.1538
sub_18:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.2941 - F1: 0.1748
sub_18:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.2059 - F1: 0.1000
sub_18:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.2941 - F1: 0.2509
sub_18:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.2647 - F1: 0.1417
sub_18:Test (Best Model) - Loss: 0.7216 - Accuracy: 0.2059 - F1: 0.1339
sub_18:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.2353 - F1: 0.1903
sub_18:Test (Best Model) - Loss: 0.7349 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.7783 - Accuracy: 0.2647 - F1: 0.1583
sub_19:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.2647 - F1: 0.2270
sub_19:Test (Best Model) - Loss: 0.9804 - Accuracy: 0.2059 - F1: 0.0875
sub_19:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.1176 - F1: 0.1008
sub_19:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.3235 - F1: 0.1883
sub_19:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.2059 - F1: 0.1160
sub_19:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.4118 - F1: 0.2772
sub_19:Test (Best Model) - Loss: 0.4516 - Accuracy: 0.5294 - F1: 0.5060
sub_19:Test (Best Model) - Loss: 0.5951 - Accuracy: 0.4706 - F1: 0.4520
sub_19:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.3529 - F1: 0.3497
sub_19:Test (Best Model) - Loss: 0.8717 - Accuracy: 0.2059 - F1: 0.1688
sub_19:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.3529 - F1: 0.2188
sub_19:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.4706 - F1: 0.4152
sub_19:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3235 - F1: 0.1898
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.2941 - F1: 0.1750
sub_20:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.3529 - F1: 0.2261
sub_20:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.2941 - F1: 0.1927
sub_20:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.2941 - F1: 0.2248
sub_20:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.3824 - F1: 0.2964
sub_20:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.3235 - F1: 0.2455
sub_20:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.2647 - F1: 0.2076
sub_20:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.2647 - F1: 0.1154
sub_20:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.4706 - F1: 0.4499
sub_20:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.3824 - F1: 0.3993
sub_20:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.2353 - F1: 0.0976
sub_21:Test (Best Model) - Loss: 0.9829 - Accuracy: 0.2941 - F1: 0.1946
sub_21:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.2647 - F1: 0.3268
sub_21:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.3529 - F1: 0.2838
sub_21:Test (Best Model) - Loss: 0.9631 - Accuracy: 0.3824 - F1: 0.3640
sub_21:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.1765 - F1: 0.1151
sub_21:Test (Best Model) - Loss: 0.8293 - Accuracy: 0.2647 - F1: 0.1792
sub_21:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.3529 - F1: 0.2321
sub_21:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2647 - F1: 0.1726
sub_21:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.2647 - F1: 0.1560
sub_21:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.2647 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.2647 - F1: 0.1507
sub_21:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.3235 - F1: 0.2141
sub_21:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.1471 - F1: 0.1000
sub_21:Test (Best Model) - Loss: 0.7757 - Accuracy: 0.2353 - F1: 0.1445
sub_22:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.2353 - F1: 0.1524
sub_22:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2941 - F1: 0.2000
sub_22:Test (Best Model) - Loss: 0.7347 - Accuracy: 0.2059 - F1: 0.1754
sub_22:Test (Best Model) - Loss: 0.7575 - Accuracy: 0.2059 - F1: 0.1747
sub_22:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.2059 - F1: 0.1633
sub_22:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.3235 - F1: 0.1883
sub_22:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.3529 - F1: 0.3004
sub_22:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.2647 - F1: 0.1594
sub_22:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.3235 - F1: 0.1923
sub_22:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.2647 - F1: 0.1688
sub_22:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.3235 - F1: 0.2209
sub_22:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.4412 - F1: 0.4207
sub_22:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.2647 - F1: 0.1667
sub_23:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.2647 - F1: 0.1759
sub_23:Test (Best Model) - Loss: 0.7327 - Accuracy: 0.2941 - F1: 0.1981
sub_23:Test (Best Model) - Loss: 0.4588 - Accuracy: 0.5882 - F1: 0.5081
sub_23:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.2941 - F1: 0.1625
sub_23:Test (Best Model) - Loss: 0.8817 - Accuracy: 0.3529 - F1: 0.2256
sub_23:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.2647 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.2941 - F1: 0.1696
sub_23:Test (Best Model) - Loss: 0.8225 - Accuracy: 0.2647 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 0.7590 - Accuracy: 0.4412 - F1: 0.3489
sub_23:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4118 - F1: 0.2679
sub_23:Test (Best Model) - Loss: 0.5712 - Accuracy: 0.4412 - F1: 0.3390
sub_23:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.1765 - F1: 0.0750
sub_23:Test (Best Model) - Loss: 0.7257 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.2647 - F1: 0.1654
sub_24:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.2941 - F1: 0.2609
sub_24:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.2353 - F1: 0.1279
sub_24:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.2941 - F1: 0.1833
sub_24:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.3529 - F1: 0.2822
sub_24:Test (Best Model) - Loss: 0.7115 - Accuracy: 0.2941 - F1: 0.1542
sub_24:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.3824 - F1: 0.2797
sub_24:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.1765 - F1: 0.1124
sub_24:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.2941 - F1: 0.1571
sub_24:Test (Best Model) - Loss: 0.7623 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.2647 - F1: 0.1098
sub_24:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.2647 - F1: 0.2221
sub_24:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.1765 - F1: 0.0750
sub_24:Test (Best Model) - Loss: 0.7297 - Accuracy: 0.1765 - F1: 0.1486
sub_24:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.2647 - F1: 0.1071
sub_25:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.3824 - F1: 0.2550
sub_25:Test (Best Model) - Loss: 0.7480 - Accuracy: 0.2647 - F1: 0.1098
sub_25:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.3824 - F1: 0.3094
sub_25:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.3235 - F1: 0.1958
sub_25:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.1765 - F1: 0.1190
sub_25:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.2647 - F1: 0.1928
sub_25:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.4706 - F1: 0.4028
sub_25:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.3235 - F1: 0.2632
sub_25:Test (Best Model) - Loss: 0.7261 - Accuracy: 0.2353 - F1: 0.0976
sub_25:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.2941 - F1: 0.1980
sub_25:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.1765 - F1: 0.1031
sub_25:Test (Best Model) - Loss: 0.7946 - Accuracy: 0.3235 - F1: 0.2575
sub_25:Test (Best Model) - Loss: 0.7856 - Accuracy: 0.3235 - F1: 0.2393
sub_25:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.2353 - F1: 0.1342
sub_25:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.9461 - Accuracy: 0.2353 - F1: 0.2251
sub_26:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.3235 - F1: 0.3137
sub_26:Test (Best Model) - Loss: 0.7871 - Accuracy: 0.2353 - F1: 0.1889
sub_26:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.3529 - F1: 0.2403
sub_26:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.2941 - F1: 0.1926
sub_26:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.4412 - F1: 0.4138
sub_26:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.2941 - F1: 0.2013
sub_26:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2353 - F1: 0.1518
sub_26:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4118 - F1: 0.4272
sub_26:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.2647 - F1: 0.1098
sub_26:Test (Best Model) - Loss: 0.7683 - Accuracy: 0.2647 - F1: 0.2124
sub_26:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.2941 - F1: 0.1736
sub_26:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.3529 - F1: 0.3264
sub_27:Test (Best Model) - Loss: 0.7951 - Accuracy: 0.3235 - F1: 0.2523
sub_27:Test (Best Model) - Loss: 0.7474 - Accuracy: 0.1471 - F1: 0.0758
sub_27:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.2941 - F1: 0.2604
sub_27:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.5000 - F1: 0.4239
sub_27:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.2941 - F1: 0.1882
sub_27:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.2941 - F1: 0.1538
sub_27:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.2059 - F1: 0.1342
sub_27:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.2353 - F1: 0.1913
sub_27:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.2647 - F1: 0.2140
sub_27:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.2941 - F1: 0.1732
sub_27:Test (Best Model) - Loss: 0.9808 - Accuracy: 0.2059 - F1: 0.1960
sub_28:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.1176 - F1: 0.1024
sub_28:Test (Best Model) - Loss: 1.1508 - Accuracy: 0.2941 - F1: 0.2978
sub_28:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.3529 - F1: 0.2949
sub_28:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.2353 - F1: 0.1668
sub_28:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.2941 - F1: 0.2667
sub_28:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4118 - F1: 0.3141
sub_28:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.4118 - F1: 0.4033
sub_28:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.2059 - F1: 0.0875
sub_28:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.2941 - F1: 0.1923
sub_28:Test (Best Model) - Loss: 1.5392 - Accuracy: 0.1176 - F1: 0.0556
sub_28:Test (Best Model) - Loss: 0.7881 - Accuracy: 0.2059 - F1: 0.1381
sub_28:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.1176 - F1: 0.0788
sub_28:Test (Best Model) - Loss: 0.8253 - Accuracy: 0.1176 - F1: 0.1030
sub_28:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.2647 - F1: 0.1364
sub_29:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.3235 - F1: 0.2076
sub_29:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.2647 - F1: 0.2100
sub_29:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.2941 - F1: 0.1970
sub_29:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.3529 - F1: 0.2625
sub_29:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.2647 - F1: 0.1417
sub_29:Test (Best Model) - Loss: 0.7458 - Accuracy: 0.2059 - F1: 0.2099
sub_29:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.3824 - F1: 0.2470
sub_29:Test (Best Model) - Loss: 0.7130 - Accuracy: 0.2647 - F1: 0.1754
sub_29:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.2647 - F1: 0.1699
sub_29:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.1765 - F1: 0.1021
sub_29:Test (Best Model) - Loss: 0.7908 - Accuracy: 0.2059 - F1: 0.1736
sub_29:Test (Best Model) - Loss: 0.8755 - Accuracy: 0.2353 - F1: 0.1488
sub_29:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.2647 - F1: 0.1727
sub_29:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.2941 - F1: 0.1843

=== Summary Results ===

acc:   29.30 ± 4.13
F1:    19.91 ± 4.92
acc-in:43.40 ± 4.89
F1-in: 32.31 ± 6.06
