lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.1404
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0815
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.1540
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0732
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0749
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2143 - F1: 0.0947
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1190 - F1: 0.0439
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2143 - F1: 0.1242
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1714 - F1: 0.0716
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1292
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.1021
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0762
sub_2:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2810 - F1: 0.2108
sub_2:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2190 - F1: 0.1125
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.3476 - F1: 0.2041
sub_2:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.3286 - F1: 0.2113
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.3429 - F1: 0.2722
sub_2:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2190 - F1: 0.1119
sub_2:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.3190 - F1: 0.2585
sub_2:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.3381 - F1: 0.2281
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.3381 - F1: 0.2256
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.3333 - F1: 0.2053
sub_2:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.3048 - F1: 0.1813
sub_2:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.3048 - F1: 0.2485
sub_2:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2905 - F1: 0.1861
sub_2:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.3000 - F1: 0.2057
sub_2:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.3048 - F1: 0.2168
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2333 - F1: 0.1346
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2429 - F1: 0.1577
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1619 - F1: 0.0911
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.0820
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.1287
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0848
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0822
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.1076
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0836
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.1235
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0764
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1234
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0855
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0680
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1762 - F1: 0.1040
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2762 - F1: 0.1833
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1701
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0764
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2143 - F1: 0.1079
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1203
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2143 - F1: 0.0982
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0863
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1267
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1358
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.1135
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2524 - F1: 0.1788
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.0640
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.0719
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0851
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0762
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0677
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0859
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.0854
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.1120
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2333 - F1: 0.1744
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1278
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.1527
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2095 - F1: 0.1009
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.1187
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2619 - F1: 0.1985
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2667 - F1: 0.1520
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1225
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2905 - F1: 0.1719
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1178
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0672
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2619 - F1: 0.1517
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2905 - F1: 0.1901
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.0942
sub_6:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2095 - F1: 0.1546
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0653
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2667 - F1: 0.1676
sub_6:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0675
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1476 - F1: 0.0648
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1238 - F1: 0.0800
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.0857
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1476 - F1: 0.0559
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1476 - F1: 0.0566
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2238 - F1: 0.1697
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2238 - F1: 0.1543
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.0766
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0867
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1905 - F1: 0.0758
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2190 - F1: 0.1175
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2143 - F1: 0.1138
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1810 - F1: 0.0981
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2333 - F1: 0.1349
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0669
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1524
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2524 - F1: 0.1374
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0675
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2476 - F1: 0.1375
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0771
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.0941
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2143 - F1: 0.1060
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2571 - F1: 0.1701
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.1222
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2524 - F1: 0.1802
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2429 - F1: 0.1436
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.1204
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2762 - F1: 0.1830
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2667 - F1: 0.1608
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2381 - F1: 0.1365
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0653
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0672
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2524 - F1: 0.1523
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0659
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0818
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1571 - F1: 0.1221
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.1540
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0748
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.0645
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.1092
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0798
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1020
sub_10:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1762 - F1: 0.0999
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.0988
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0686
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2381 - F1: 0.1555
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2857 - F1: 0.1749
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0765
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0762
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2381 - F1: 0.1400
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.1127
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0763
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2381 - F1: 0.1325
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2429 - F1: 0.1327
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0771
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2381 - F1: 0.1329
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1762 - F1: 0.1028
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.1150
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.1120
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.1222
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1714 - F1: 0.0718
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1571 - F1: 0.1070
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2190 - F1: 0.1489
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.0778
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.1054
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1090
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1013
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2238 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2143 - F1: 0.1079
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.0963
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0689
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0859
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2429 - F1: 0.1748
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1667 - F1: 0.0976
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1667 - F1: 0.1257
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1619 - F1: 0.0641
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.1483
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1857 - F1: 0.1029
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1810 - F1: 0.0906
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2286 - F1: 0.1812
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1293
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2381 - F1: 0.1631
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2571 - F1: 0.1919
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2286 - F1: 0.1282
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.1138
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.1100
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2333 - F1: 0.1328
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2619 - F1: 0.1553
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2476 - F1: 0.1734
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2286 - F1: 0.1534
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2571 - F1: 0.1827
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2476 - F1: 0.1772
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2952 - F1: 0.1946
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2714 - F1: 0.1822
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.3095 - F1: 0.2290
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1810 - F1: 0.1285
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1230
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.1212
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0683
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0669
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1321
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1857 - F1: 0.0979
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1085
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2238 - F1: 0.1132
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1571 - F1: 0.0819
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0686
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1857 - F1: 0.1235
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.1121
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0852

=== Summary Results ===

acc: 21.71 ± 2.89
F1: 11.56 ± 3.09
acc-in: 24.25 ± 2.78
F1-in: 13.51 ± 3.48
