lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3713
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4121
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.5906
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4286 - F1: 0.4167
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4590
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4750
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7306
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.5852
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.6971
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7379
sub_2:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8095 - F1: 0.8091
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7857 - F1: 0.7796
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4952
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5411
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5758
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5179
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4312
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4997
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4260
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4565
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4590
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7343
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4296
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4020
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5333
sub_4:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4590
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5894
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.7035
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4643
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4286 - F1: 0.4167
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3583
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.3571 - F1: 0.2632
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.5962
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5705
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4269
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4447
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4286 - F1: 0.3000
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4367
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4048 - F1: 0.4017
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3583
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4590
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4928
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.3451
sub_6:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.5714
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4312
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5457
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5258
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.5962
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4296
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4987
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4643
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4987
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7857 - F1: 0.7826
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6667 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4590
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4286 - F1: 0.4273
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6905 - F1: 0.6677
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6327
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6190 - F1: 0.5544
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7597
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6257
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3583
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5361
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.5962
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4952
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3873
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5333
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5524
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4296
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4367
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4815
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6667 - F1: 0.6541
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6327
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.7143 - F1: 0.7035
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4750
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5361
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.6182
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5474
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5238 - F1: 0.4167
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5258
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6905 - F1: 0.6577
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6327
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.5179
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.7143 - F1: 0.7083
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.3115
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4815
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4714
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4815
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.3115
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5950
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4107
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4750
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5159
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6257
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4312
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.8095 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.5544
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7619
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6667 - F1: 0.6659
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7619
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3713
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6190 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7368
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7343
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.7143 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4260
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.3115
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5333

=== Summary Results ===

acc:   56.26 ± 6.55
F1:    47.81 ± 8.96
acc-in:61.73 ± 6.30
F1-in: 53.98 ± 8.95
