lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5333
sub_1:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6190 - F1: 0.6111
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1670 - Accuracy: 0.6667 - F1: 0.6370
sub_1:Test (Best Model) - Loss: 0.1747 - Accuracy: 0.4762 - F1: 0.4714
sub_1:Test (Best Model) - Loss: 0.1693 - Accuracy: 0.8095 - F1: 0.8056
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3810 - F1: 0.3576
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_1:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.6667 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_2:Test (Best Model) - Loss: 0.1726 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.1721 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.7143 - F1: 0.6786
sub_2:Test (Best Model) - Loss: 0.1729 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.9524 - F1: 0.9519
sub_2:Test (Best Model) - Loss: 0.1722 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.1723 - Accuracy: 0.8095 - F1: 0.8091
sub_2:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.1707 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.1722 - Accuracy: 0.7143 - F1: 0.6971
sub_2:Test (Best Model) - Loss: 0.1504 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.7143 - F1: 0.7083
sub_2:Test (Best Model) - Loss: 0.1710 - Accuracy: 0.7143 - F1: 0.7083
sub_2:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.7619 - F1: 0.7619
sub_3:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4286 - F1: 0.4167
sub_3:Test (Best Model) - Loss: 0.1722 - Accuracy: 0.5238 - F1: 0.4952
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4286 - F1: 0.3000
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4286 - F1: 0.3571
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.5139
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.6190 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.7143 - F1: 0.6971
sub_4:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.7619 - F1: 0.7407
sub_4:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.7143 - F1: 0.7083
sub_4:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.9524 - F1: 0.9519
sub_4:Test (Best Model) - Loss: 0.1676 - Accuracy: 0.8095 - F1: 0.7981
sub_4:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.8571 - F1: 0.8558
sub_4:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.7143 - F1: 0.6971
sub_4:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.9048 - F1: 0.9045
sub_4:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.7143 - F1: 0.7083
sub_4:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.6667 - F1: 0.6370
sub_4:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6667 - F1: 0.6636
sub_4:Test (Best Model) - Loss: 0.1724 - Accuracy: 0.6190 - F1: 0.6182
sub_4:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.5714 - F1: 0.5675
sub_5:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.6190 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6190 - F1: 0.5714
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_5:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.5714 - F1: 0.5553
sub_5:Test (Best Model) - Loss: 0.1700 - Accuracy: 0.7143 - F1: 0.6786
sub_5:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.6667 - F1: 0.6636
sub_5:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.6190 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.5714 - F1: 0.4987
sub_5:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.6190 - F1: 0.5962
sub_5:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.6190 - F1: 0.5962
sub_5:Test (Best Model) - Loss: 0.1723 - Accuracy: 0.5714 - F1: 0.4987
sub_5:Test (Best Model) - Loss: 0.1713 - Accuracy: 0.6667 - F1: 0.6541
sub_5:Test (Best Model) - Loss: 0.1672 - Accuracy: 0.6667 - F1: 0.6370
sub_6:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6667 - F1: 0.6370
sub_6:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.6667 - F1: 0.6370
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_6:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.7619 - F1: 0.7597
sub_6:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.5238 - F1: 0.4643
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_6:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.7619 - F1: 0.7529
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_6:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.5238 - F1: 0.5227
sub_7:Test (Best Model) - Loss: 0.1668 - Accuracy: 0.7619 - F1: 0.7597
sub_7:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.6190 - F1: 0.5962
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1551 - Accuracy: 0.7143 - F1: 0.7136
sub_7:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.7143 - F1: 0.7083
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6370
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1735 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4457
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1560 - Accuracy: 0.7619 - F1: 0.7597
sub_7:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.7143 - F1: 0.7083
sub_8:Test (Best Model) - Loss: 0.1510 - Accuracy: 0.9048 - F1: 0.9028
sub_8:Test (Best Model) - Loss: 0.1578 - Accuracy: 0.8571 - F1: 0.8518
sub_8:Test (Best Model) - Loss: 0.1698 - Accuracy: 0.9048 - F1: 0.9028
sub_8:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.9048 - F1: 0.9028
sub_8:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.5714 - F1: 0.5553
sub_8:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6190 - F1: 0.5962
sub_8:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.7619 - F1: 0.7407
sub_8:Test (Best Model) - Loss: 0.1589 - Accuracy: 0.9048 - F1: 0.9028
sub_8:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.1590 - Accuracy: 0.9048 - F1: 0.9028
sub_8:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.9048 - F1: 0.9045
sub_8:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.7619 - F1: 0.7619
sub_8:Test (Best Model) - Loss: 0.1679 - Accuracy: 0.8095 - F1: 0.8056
sub_8:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6786
sub_9:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.6667 - F1: 0.6101
sub_9:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.1671 - Accuracy: 0.8571 - F1: 0.8518
sub_9:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.5714 - F1: 0.5553
sub_9:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.7619 - F1: 0.7529
sub_9:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.8571 - F1: 0.8518
sub_9:Test (Best Model) - Loss: 0.1603 - Accuracy: 0.9048 - F1: 0.9028
sub_9:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.5714 - F1: 0.4987
sub_9:Test (Best Model) - Loss: 0.1693 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 0.1650 - Accuracy: 0.7619 - F1: 0.7529
sub_9:Test (Best Model) - Loss: 0.1542 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.6190 - F1: 0.5962
sub_10:Test (Best Model) - Loss: 0.1737 - Accuracy: 0.4286 - F1: 0.4273
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.4643
sub_10:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.6667 - F1: 0.6370
sub_10:Test (Best Model) - Loss: 0.1597 - Accuracy: 0.8095 - F1: 0.8091
sub_10:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6190 - F1: 0.5962
sub_10:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.7619 - F1: 0.7407
sub_10:Test (Best Model) - Loss: 0.1714 - Accuracy: 0.6190 - F1: 0.6111
sub_10:Test (Best Model) - Loss: 0.1683 - Accuracy: 0.6667 - F1: 0.6101
sub_10:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.7143 - F1: 0.6971
sub_10:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.5714 - F1: 0.4987
sub_10:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.8571 - F1: 0.8518
sub_10:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.5238 - F1: 0.3438
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6971
sub_11:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.6190 - F1: 0.6111
sub_11:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4286 - F1: 0.3571
sub_11:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.5714 - F1: 0.5333
sub_11:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6667 - F1: 0.6370
sub_11:Test (Best Model) - Loss: 0.1695 - Accuracy: 0.8095 - F1: 0.8056
sub_11:Test (Best Model) - Loss: 0.1702 - Accuracy: 0.9048 - F1: 0.9045
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_11:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.7143 - F1: 0.6971
sub_11:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.1581 - Accuracy: 0.7143 - F1: 0.7083
sub_11:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.8095 - F1: 0.8091
sub_11:Test (Best Model) - Loss: 0.1726 - Accuracy: 0.7619 - F1: 0.7529
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.5238 - F1: 0.3438
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_12:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.6667 - F1: 0.6101
sub_12:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.6667 - F1: 0.6101
sub_12:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.6667 - F1: 0.6636
sub_12:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.5238 - F1: 0.4167
sub_12:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7143 - F1: 0.6971
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.5227
sub_12:Test (Best Model) - Loss: 0.1675 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5333
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_12:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.9048 - F1: 0.9028
sub_12:Test (Best Model) - Loss: 0.1734 - Accuracy: 0.4762 - F1: 0.3226
sub_13:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.6667 - F1: 0.6370
sub_13:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.4762 - F1: 0.3226
sub_13:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6667 - F1: 0.6541
sub_13:Test (Best Model) - Loss: 0.1728 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1689 - Accuracy: 0.7619 - F1: 0.7407
sub_13:Test (Best Model) - Loss: 0.1636 - Accuracy: 0.6667 - F1: 0.6370
sub_13:Test (Best Model) - Loss: 0.1727 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1725 - Accuracy: 0.6190 - F1: 0.5333
sub_13:Test (Best Model) - Loss: 0.1716 - Accuracy: 0.7619 - F1: 0.7407
sub_13:Test (Best Model) - Loss: 0.1715 - Accuracy: 0.8571 - F1: 0.8518
sub_13:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 0.1525 - Accuracy: 0.8571 - F1: 0.8518
sub_14:Test (Best Model) - Loss: 0.1720 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.5714 - F1: 0.4987
sub_14:Test (Best Model) - Loss: 0.1653 - Accuracy: 0.7143 - F1: 0.6971
sub_14:Test (Best Model) - Loss: 0.1708 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.5714 - F1: 0.4987
sub_14:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.1724 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.1634 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.1705 - Accuracy: 0.8095 - F1: 0.8091
sub_14:Test (Best Model) - Loss: 0.1730 - Accuracy: 0.7619 - F1: 0.7529
sub_14:Test (Best Model) - Loss: 0.1718 - Accuracy: 0.6667 - F1: 0.6101
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6101
sub_14:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.7143 - F1: 0.6971
sub_14:Test (Best Model) - Loss: 0.1719 - Accuracy: 0.6667 - F1: 0.6101
sub_14:Test (Best Model) - Loss: 0.1729 - Accuracy: 0.6667 - F1: 0.6101

=== Summary Results ===

acc:   67.51 ± 9.86
F1:    62.62 ± 13.10
acc‑in:81.43 ± 11.12
F1‑in: 77.56 ± 14.78
