lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.2190 - F1: 0.1817
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1029
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1111
sub_1:Test (Best Model) - Loss: 0.8030 - Accuracy: 0.2762 - F1: 0.2130
sub_1:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2190 - F1: 0.1311
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1016
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.1982
sub_1:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2190 - F1: 0.0982
sub_1:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.0849
sub_1:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.3810 - F1: 0.2695
sub_1:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.2381 - F1: 0.1910
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1866
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1766
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1286
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1578
sub_2:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.3333 - F1: 0.2470
sub_2:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.4381 - F1: 0.3260
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1375
sub_2:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2190 - F1: 0.1087
sub_2:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.2571 - F1: 0.1594
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3429 - F1: 0.2501
sub_2:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.3238 - F1: 0.2668
sub_2:Test (Best Model) - Loss: 0.8029 - Accuracy: 0.3714 - F1: 0.3240
sub_2:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.3524 - F1: 0.2419
sub_2:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.3810 - F1: 0.3280
sub_2:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.1061
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1946
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.1979
sub_2:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2952 - F1: 0.2205
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0833
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0842
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1744
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0905
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1541
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0991
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.1068
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1493
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2095 - F1: 0.1311
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.1333 - F1: 0.0718
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0876
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.1498
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1359
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1593
sub_4:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.3048 - F1: 0.1857
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1389
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3238 - F1: 0.2871
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0943
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3429 - F1: 0.2037
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1067
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3429 - F1: 0.2867
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3048 - F1: 0.2307
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.2124
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1646
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1361
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1336
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1483
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1700
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1438
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0911
sub_5:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2190 - F1: 0.1149
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0645
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1616
sub_5:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2762 - F1: 0.1626
sub_5:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2476 - F1: 0.1858
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1675
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1188
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1533
sub_5:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2667 - F1: 0.1655
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1363
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0607
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1159
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0677
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.1086
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1429 - F1: 0.0821
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1374
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0850
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0967
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1333 - F1: 0.0694
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1813
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1243
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.1310
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1202
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1039
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1551
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1070
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1061
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1603
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1527
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0849
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1003
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1143
sub_7:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.2476 - F1: 0.1833
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.0988
sub_8:Test (Best Model) - Loss: 0.8009 - Accuracy: 0.3429 - F1: 0.2847
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.2257
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2952 - F1: 0.1862
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8015 - Accuracy: 0.3429 - F1: 0.2987
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1333 - F1: 0.0884
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2952 - F1: 0.2292
sub_8:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.4000 - F1: 0.3031
sub_8:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.3905 - F1: 0.3334
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.2056
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0689
sub_8:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.4000 - F1: 0.3232
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3524 - F1: 0.2073
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.2054
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1061
sub_9:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2952 - F1: 0.2002
sub_9:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3524 - F1: 0.2095
sub_9:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.4190 - F1: 0.3655
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1196
sub_9:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3143 - F1: 0.2076
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3143 - F1: 0.1979
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0850
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1563
sub_9:Test (Best Model) - Loss: 0.7995 - Accuracy: 0.4000 - F1: 0.3285
sub_9:Test (Best Model) - Loss: 0.8033 - Accuracy: 0.3619 - F1: 0.2989
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3333 - F1: 0.2312
sub_10:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2571 - F1: 0.1880
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0789
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1532
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1198
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1385
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1524
sub_10:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.3429 - F1: 0.2610
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1661
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1714 - F1: 0.0955
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0925
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1329
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1033
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1646
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1649
sub_11:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2000 - F1: 0.1224
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0650
sub_11:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2857 - F1: 0.1941
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1366
sub_11:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2762 - F1: 0.1966
sub_11:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.3238 - F1: 0.2427
sub_11:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1698
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2952 - F1: 0.1699
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1642
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1068
sub_11:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2762 - F1: 0.1557
sub_11:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1686
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.1102
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2571 - F1: 0.1987
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2571 - F1: 0.2060
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1295
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2857 - F1: 0.2071
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1181
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1350
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1343
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1068
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2762 - F1: 0.1795
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1839
sub_12:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1179
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.3238 - F1: 0.2614
sub_13:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.3238 - F1: 0.2042
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1504
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1668
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1222
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.1956
sub_13:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2952 - F1: 0.1776
sub_13:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2857 - F1: 0.1668
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1091
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1302
sub_13:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.3429 - F1: 0.2089
sub_13:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.3429 - F1: 0.2558
sub_13:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2857 - F1: 0.1616
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0683
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1571
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1512
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1801
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1409
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1631
sub_14:Test (Best Model) - Loss: 0.7993 - Accuracy: 0.2952 - F1: 0.2027
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2952 - F1: 0.1989
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.1625
sub_14:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2571 - F1: 0.1933
sub_14:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.3429 - F1: 0.2565
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0916
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1173
sub_14:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2571 - F1: 0.1486
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0956
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1288

=== Summary Results ===

acc:   24.98 ± 3.28
F1:    15.08 ± 3.38
acc‑in:28.76 ± 3.36
F1‑in: 18.36 ± 3.64
