lr: 0.001
sub_1:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1234 - Accuracy: 0.8750 - F1: 0.8545
sub_1:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1536 - Accuracy: 0.8750 - F1: 0.8545
sub_1:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1694 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1694 - Accuracy: 0.6250 - F1: 0.3846
sub_1:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1645 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1680 - Accuracy: 0.5000 - F1: 0.4667
sub_2:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1670 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1642 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1645 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_2:Test (Best Model) - Loss: 0.1652 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1642 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1647 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1652 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1668 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_3:Test (Best Model) - Loss: 0.1647 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1324 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.1652 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1639 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.8750 - F1: 0.8545
sub_4:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1647 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.7500 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_4:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.7500 - F1: 0.6667
sub_5:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1459 - Accuracy: 0.8750 - F1: 0.8545
sub_5:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_5:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1692 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1646 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1646 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1649 - Accuracy: 0.6250 - F1: 0.3846
sub_6:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1723 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.6250 - F1: 0.3846
sub_7:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1687 - Accuracy: 0.6250 - F1: 0.3846
sub_8:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1513 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1694 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1685 - Accuracy: 0.7500 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1710 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_9:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1641 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1639 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_10:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1650 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1654 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1664 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1647 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1662 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1627 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_11:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.5000 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1666 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1689 - Accuracy: 0.6250 - F1: 0.3846
sub_12:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1688 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1692 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1692 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1641 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1689 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_13:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1726 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1722 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_14:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_15:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1722 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_16:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1650 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1649 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1646 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1649 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1494 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1514 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1686 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1548 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1374 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1654 - Accuracy: 0.8750 - F1: 0.8545
sub_18:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.6250 - F1: 0.3846
sub_18:Test (Best Model) - Loss: 0.1728 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1726 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1597 - Accuracy: 0.7500 - F1: 0.7333
sub_19:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1686 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 0.1724 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1689 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1694 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1662 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.7500 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_20:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1688 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1687 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1639 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1652 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1687 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_22:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1650 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1649 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1710 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1710 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1655 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846
sub_23:Test (Best Model) - Loss: 0.1649 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1692 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_24:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1668 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1784 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1679 - Accuracy: 0.7500 - F1: 0.7500
sub_25:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1690 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1710 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.6250 - F1: 0.3846
sub_25:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1639 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1660 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1648 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1507 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1851 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.6250 - F1: 0.3846
sub_26:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1655 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1661 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1654 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1637 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1663 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1646 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1658 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1646 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.6250 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1697 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1701 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1683 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_28:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1722 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1174 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1688 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1675 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.6250 - F1: 0.3846
sub_29:Test (Best Model) - Loss: 0.1120 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1651 - Accuracy: 0.6250 - F1: 0.3846

=== Summary Results ===

acc:   63.82 ± 3.13
F1:    41.16 ± 5.34
acc‑in:68.74 ± 3.45
F1‑in: 43.72 ± 6.21
