lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2174 - F1: 0.1394
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2464 - F1: 0.1205
sub_1:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2029 - F1: 0.1313
sub_1:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1769
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2464 - F1: 0.1000
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.2094
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1322
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.1402
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3088 - F1: 0.1799
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1442
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2319 - F1: 0.0988
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1575
sub_3:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1884 - F1: 0.1245
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1322
sub_3:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1304 - F1: 0.0833
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1716
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3043 - F1: 0.1716
sub_4:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3188 - F1: 0.1997
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3043 - F1: 0.1929
sub_4:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3188 - F1: 0.2011
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3188 - F1: 0.2267
sub_4:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1059
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3088 - F1: 0.1799
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1000
sub_5:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3088 - F1: 0.1806
sub_5:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2206 - F1: 0.1311
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1000
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1322
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1118
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1275
sub_5:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1059
sub_5:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1322
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3088 - F1: 0.2018
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1372
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3824 - F1: 0.2550
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3529 - F1: 0.2282
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3333 - F1: 0.2046
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3478 - F1: 0.2742
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3043 - F1: 0.1957
sub_6:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3333 - F1: 0.2008
sub_6:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1808
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2059 - F1: 0.0933
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.0926
sub_7:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2794 - F1: 0.1797
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1059
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2941 - F1: 0.1914
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.3529 - F1: 0.2484
sub_8:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2941 - F1: 0.1538
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1205
sub_9:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1765 - F1: 0.1127
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2941 - F1: 0.1571
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2941 - F1: 0.1541
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1322
sub_10:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2464 - F1: 0.1024
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2319 - F1: 0.1147
sub_10:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2754 - F1: 0.1786
sub_10:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.1739 - F1: 0.1151
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1322
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1410
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2319 - F1: 0.1440
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1712
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3235 - F1: 0.2116
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3088 - F1: 0.1834
sub_13:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.1765 - F1: 0.0906
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1906
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.0938
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1059
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3088 - F1: 0.2585
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3529 - F1: 0.2311
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3382 - F1: 0.2211
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1417
sub_14:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1820
sub_15:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3382 - F1: 0.2187
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1322
sub_15:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2353 - F1: 0.1154
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2353 - F1: 0.1918
sub_15:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1625
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.1113
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1370
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1849
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1514
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.1083
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3235 - F1: 0.2117
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2059 - F1: 0.1052
sub_16:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1208
sub_16:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2899 - F1: 0.2183
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1309
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1742
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1037
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3382 - F1: 0.2535
sub_17:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1590
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1332
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2464 - F1: 0.1428
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2353 - F1: 0.1373
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1326
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.1304
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1792
sub_18:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2794 - F1: 0.1322
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1000
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1024
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1536
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1000
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1012
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1012
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1641
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1333
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2059 - F1: 0.1318
sub_19:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1912 - F1: 0.1248
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.2036
sub_20:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2941 - F1: 0.1654
sub_20:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1449
sub_20:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1000
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1262
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2899 - F1: 0.1840
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2464 - F1: 0.1000
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3478 - F1: 0.2496
sub_20:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1012
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.0915
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1059
sub_21:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2794 - F1: 0.1346
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.1912 - F1: 0.0997
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2059 - F1: 0.0875
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1658
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1712
sub_21:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.1444
sub_21:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1271
sub_21:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1912 - F1: 0.1019
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1059
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1059
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1332
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2754 - F1: 0.1659
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2899 - F1: 0.1934
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1350
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3235 - F1: 0.2113
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3333 - F1: 0.2478
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.0915
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1346
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2319 - F1: 0.1000
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1823
sub_23:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2754 - F1: 0.1581
sub_23:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1537
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3088 - F1: 0.2515
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2941 - F1: 0.1561
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3088 - F1: 0.1888
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1663
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.1304
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3088 - F1: 0.1969
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2500 - F1: 0.1000
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2206 - F1: 0.1689
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2941 - F1: 0.1667
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.2021
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.1459
sub_24:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3088 - F1: 0.2575
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1581
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.1034
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3382 - F1: 0.2149
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.0964
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2353 - F1: 0.0964
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1524
sub_25:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.1448
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1059
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2353 - F1: 0.0988
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1754
sub_26:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2899 - F1: 0.2183
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1309
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2754 - F1: 0.1742
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2174 - F1: 0.0893
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2500 - F1: 0.1037
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.3382 - F1: 0.2535
sub_27:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1590
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1264
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2794 - F1: 0.1321
sub_28:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.1084
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1618 - F1: 0.1058
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1322
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2794 - F1: 0.1822
sub_29:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2609 - F1: 0.1084
sub_29:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2754 - F1: 0.1826
sub_29:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.1739 - F1: 0.0944
sub_29:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.1159 - F1: 0.0758
sub_29:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2464 - F1: 0.1037

=== Summary Results ===

acc: 26.36 ± 1.03
F1: 12.33 ± 1.48
acc-in: 29.44 ± 1.51
F1-in: 17.34 ± 2.16
