lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1292
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2403
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1176 - F1: 0.0819
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1844
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2984
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2076
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1471 - F1: 0.0970
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1166
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2103
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1837
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2856
sub_2:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.1571
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1410
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1538
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1880
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1169
sub_2:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2753
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.1395
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1571
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1172
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1529
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2842
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1625
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1990
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2007
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1864
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1632
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1552
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1515
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1732
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1894
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.2209
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3529 - F1: 0.2807
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1111
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.4706 - F1: 0.3971
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1125
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.2409
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2880
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2271
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1925
sub_4:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1430
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1833
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1699
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2412
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2363
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2546
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1850
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1791
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1576
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1288
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2896
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2256
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1476
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4706 - F1: 0.3206
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2308
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1844
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6831 - 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: 0.6831 - Accuracy: 0.2647 - F1: 0.1620
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1542
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2124
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5294 - F1: 0.4392
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1731
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1417
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.1923
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1771
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2676
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1946
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2500
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2265
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1844
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4118 - F1: 0.2684
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1682
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2641
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1782
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1667
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1552
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: 0.1949
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1542
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1538
sub_8:Test (Best Model) - Loss: 0.6931 - 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: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1562
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2141
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2692
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1667
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.2107
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1098
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.3583
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.2247
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.1501
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.0694
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1889
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1962
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1526
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.1765 - F1: 0.1346
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1748
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1435
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.2106
sub_10:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.1898
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.0952
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1071
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3824 - F1: 0.2692
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1850
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.2303
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2250
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.2058
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2010
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1531
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.2171
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1515
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.0833
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.3246
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4118 - F1: 0.2743
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1580
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.1653
sub_12:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1944
sub_12:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1847
sub_12:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2941 - F1: 0.1920
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1208
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2216
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1616
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.0882
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1400
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1541
sub_13:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2353 - F1: 0.2030
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1515
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.0955
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1538
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.4118 - F1: 0.3558
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1098
sub_13:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2542
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1346
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1331
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1731
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1306
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1348
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1654
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2948
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1682
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.1923
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2081
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1552
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1147
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1623
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1552
sub_15:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1518
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1612
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1053
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1594
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2242
sub_15:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.0857
sub_16:Test (Best Model) - Loss: 0.6931 - 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: 0.6931 - Accuracy: 0.2647 - F1: 0.1731
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1552
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1762
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1471 - F1: 0.0908
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.3241
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1438
sub_16:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.3235 - F1: 0.2141
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2843
sub_16:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2511
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1352
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1410
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1285
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1585
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1542
sub_17:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2353 - F1: 0.1397
sub_17:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1507
sub_17:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1491
sub_17:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2574
sub_17:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2689
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1098
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1765 - F1: 0.1238
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1410
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1477
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2007
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1333
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1471 - F1: 0.1354
sub_18:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1904
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2423
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1098
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2530
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.0875
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3529 - F1: 0.2376
sub_19:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.0897
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.3235 - F1: 0.2664
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0976
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1510
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1909
sub_19:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.3235 - F1: 0.2205
sub_19:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1125
sub_19:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3235 - F1: 0.2025
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1962
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1538
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4118 - F1: 0.2959
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1880
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4412 - F1: 0.3340
sub_20:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.2011
sub_20:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1195
sub_20:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.3529 - F1: 0.2243
sub_20:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.2020
sub_20:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1696
sub_20:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.3095
sub_20:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1514
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1307
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1367
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1559
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1981
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2081
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1845
sub_21:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1348
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.2041
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2000
sub_21:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.2647 - F1: 0.1585
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1342
sub_21:Test (Best Model) - Loss: 0.6931 - 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: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0952
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1905
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1410
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2059 - F1: 0.1440
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2499
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1625
sub_22:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2353 - F1: 0.1837
sub_22:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.2647 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2701
sub_22:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1759
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.0976
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1031
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1894
sub_22:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2059 - F1: 0.0875
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2647 - F1: 0.1410
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2197
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1098
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1765 - F1: 0.1198
sub_23:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.4118 - F1: 0.2692
sub_23:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.1911
sub_23:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2702
sub_23:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1125
sub_23:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.1912
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2025
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2188
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2060
sub_23:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3235 - F1: 0.2098
sub_23:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2096
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.2164
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.2439
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1633
sub_24:Test (Best Model) - Loss: 0.6931 - 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: 0.3235 - F1: 0.2588
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1742
sub_24:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1902
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2059 - F1: 0.1414
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2353 - F1: 0.1053
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1471 - F1: 0.0952
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.0857
sub_24:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1176 - F1: 0.0942
sub_25:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3529 - F1: 0.2308
sub_25:Test (Best Model) - Loss: 0.6831 - 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: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1471 - F1: 0.1010
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1556
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1958
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1455
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.2019
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1904
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1748
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1282
sub_25:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1471 - F1: 0.0981
sub_26:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.3235 - F1: 0.2166
sub_26:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.3824 - F1: 0.2462
sub_26:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1071
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.1765 - F1: 0.1008
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1552
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1667
sub_26:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1471 - F1: 0.0979
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1081
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1184
sub_27:Test (Best Model) - Loss: 0.6831 - 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: 0.6831 - Accuracy: 0.2647 - F1: 0.1417
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.4412 - F1: 0.3651
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1176 - F1: 0.0977
sub_27:Test (Best Model) - Loss: 0.6830 - 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: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.1552
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2353 - F1: 0.1458
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1437
sub_27:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2647 - F1: 0.1699
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1632
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1805
sub_27:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1306
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1937
sub_28:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.1765 - F1: 0.1454
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1776
sub_28:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.3529 - F1: 0.2410
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1585
sub_28:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2647 - F1: 0.1909
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.3241
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1844
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.1879
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1154
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3235 - F1: 0.2049
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1941
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.3824 - F1: 0.2416
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: 0.6931 - Accuracy: 0.2647 - F1: 0.1635
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1871
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1571
sub_29:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.2353 - F1: 0.0952
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2353 - F1: 0.1488
sub_29:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.2941 - F1: 0.1924
sub_29:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1765 - F1: 0.1044
sub_29:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.1765 - F1: 0.1013
sub_29:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.2059 - F1: 0.2053
sub_29:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.2941 - F1: 0.2222

=== Summary Results ===

acc:   27.10 ± 1.69
F1:    15.76 ± 1.67
acc-in:33.68 ± 2.43
F1-in: 20.87 ± 2.68
