lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5714
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.1905 - F1: 0.1831
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8095 - F1: 0.8091
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.6111
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6190 - F1: 0.5714
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7143 - F1: 0.7083
sub_2:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_2:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.5139
sub_2:Test (Best Model) - Loss: 0.1733 - 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: 0.1733 - Accuracy: 0.6667 - F1: 0.6636
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3810 - F1: 0.2759
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
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: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.4167
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_3:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5962
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.7083
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7619 - F1: 0.7407
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8571 - F1: 0.8518
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7619 - F1: 0.7597
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_4:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.6111
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: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_5:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6370
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: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.7136
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.4167
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5714
sub_6:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4286 - F1: 0.3000
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6636
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3810 - F1: 0.3576
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.4643
sub_7:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6667 - F1: 0.6636
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4457
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5675
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8571 - F1: 0.8518
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.4296
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7619 - F1: 0.7597
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6190 - F1: 0.5714
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_8:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.4762 - F1: 0.3226
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6786
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6786
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5962
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.7136
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_9:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.4762 - F1: 0.3226
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_9:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.7083
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4286 - F1: 0.4273
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.9048 - F1: 0.9028
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5333
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8095 - F1: 0.8091
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.4714
sub_10:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.5714
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6667
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_11:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.8571 - F1: 0.8558
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.3333 - F1: 0.3318
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5333
sub_11:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
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: 0.1733 - Accuracy: 0.5238 - F1: 0.4952
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
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: 0.1733 - 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: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
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: 0.1733 - Accuracy: 0.6190 - F1: 0.5714
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.4167
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5714 - F1: 0.4987
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5333
sub_13:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.6971
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_14:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6190 - F1: 0.5714
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.7143 - F1: 0.7136
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.7143 - F1: 0.7083
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6636
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_14:Test (Best Model) - Loss: 0.1732 - Accuracy: 0.6667 - F1: 0.6101
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.6667 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.5238 - F1: 0.3438
sub_14:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.4762 - F1: 0.3226

=== Summary Results ===

acc:   56.08 ± 4.94
F1:    45.16 ± 7.15
acc‑in:61.55 ± 6.21
F1‑in: 51.38 ± 8.16
