lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7500 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.5636
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.5636
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.3750 - F1: 0.2727
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.8750 - F1: 0.8545
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.8750 - F1: 0.8545
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3750 - F1: 0.2727
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7500 - F1: 0.6667
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.5636
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7500 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3750 - F1: 0.2727
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.2500 - F1: 0.2000
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.4667
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3750 - F1: 0.3651
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.2500 - F1: 0.2000
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.3333
sub_17:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.7500 - F1: 0.6667
sub_18:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8750 - F1: 0.8545
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7500 - F1: 0.6667
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8750 - F1: 0.8730
sub_22:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8750 - F1: 0.8730
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.2500 - F1: 0.2000
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.2500 - F1: 0.2500
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.3750 - F1: 0.3651
sub_26:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.7500 - F1: 0.6667
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5000 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.6250 - F1: 0.3846

=== Summary Results ===

acc:   62.16 ± 1.49
F1:    39.63 ± 2.09
acc‑in:67.13 ± 0.90
F1‑in: 41.44 ± 1.93
