lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1429 - F1: 0.1056
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0748
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1714 - F1: 0.0804
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1084
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1092
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2952 - F1: 0.1678
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1335
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1025
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1514
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1745
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1937
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0851
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3429 - F1: 0.2422
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.3714 - F1: 0.2773
sub_2:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.3619 - F1: 0.2505
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.1716
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.2273
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0992
sub_2:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0645
sub_2:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3619 - F1: 0.2772
sub_2:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1270
sub_2:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2762 - F1: 0.2037
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1429 - F1: 0.0815
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0817
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1206
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0815
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1270
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: 0.1618
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1190
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0876
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0677
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0817
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0943
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: 0.1126
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1377
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1009
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1038
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0876
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1524 - F1: 0.0830
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0849
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1101
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1106
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1143
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1433
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1188
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0871
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1111
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1290
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
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: 0.2571 - F1: 0.1385
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1331
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1234
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1235
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1438
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1586
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1714 - F1: 0.0987
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0796
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1078
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0848
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0677
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1524 - F1: 0.1330
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: 0.1238 - F1: 0.0721
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1116
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1714 - F1: 0.0931
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.0816
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0976
sub_8:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2286 - F1: 0.1539
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1291
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1052
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0623
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0930
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0911
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0859
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1140
sub_8:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2476 - F1: 0.1429
sub_8:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2667 - F1: 0.1987
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0782
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3714 - F1: 0.2713
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1242
sub_8:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.1996
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1358
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1648
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1581
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.0997
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1057
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1170
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1145
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0661
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1127
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1803
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1346
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0851
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1037
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0788
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0994
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0718
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2857 - F1: 0.2033
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0677
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1471
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1115
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1212
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0918
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3238 - F1: 0.2409
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0800
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1265
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1883
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0851
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1382
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1855
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1124
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0787
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1584
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: 0.8047 - 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: 0.8047 - Accuracy: 0.2286 - F1: 0.1183
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: 0.8047 - Accuracy: 0.2095 - F1: 0.1181
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1007
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.1018
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1730
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1650
sub_13:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2476 - F1: 0.1519
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1092
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1368
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1388
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1689
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1392
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.0996
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1755
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2762 - F1: 0.1584
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.1778
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1207
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1058
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1302
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3048 - F1: 0.2523
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1122
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0645
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0849
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1403
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1110
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667

=== Summary Results ===

acc:   21.61 ± 1.90
F1:    10.62 ± 2.25
acc-in:23.73 ± 1.74
F1-in: 12.35 ± 2.25
