lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4997
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4815
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4997
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.4020
sub_1:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5476 - F1: 0.5143
sub_1:Test (Best Model) - Loss: 0.3465 - 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: 0.5000 - F1: 0.4020
sub_1:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7619 - F1: 0.7529
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4815
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5714 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4312
sub_2:Test (Best Model) - Loss: 0.3434 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7143 - F1: 0.7143
sub_2:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.3141 - Accuracy: 0.9048 - F1: 0.9048
sub_2:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.7381 - F1: 0.7255
sub_2:Test (Best Model) - Loss: 0.3433 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.3416 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.3233 - Accuracy: 0.8571 - F1: 0.8571
sub_2:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.3440 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5894
sub_3:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3713
sub_3:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5411
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.4269
sub_3:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4997
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4048 - F1: 0.2881
sub_3:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5000 - F1: 0.4020
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5474
sub_3:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5705
sub_4:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7857 - F1: 0.7846
sub_4:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7143 - F1: 0.6971
sub_4:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5714 - F1: 0.4750
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: 0.3465 - Accuracy: 0.5952 - F1: 0.5758
sub_4:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.5179
sub_4:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.6905 - F1: 0.6860
sub_4:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.6905 - F1: 0.6816
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.6667 - F1: 0.6659
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5553
sub_4:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3873
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3873
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.3810 - F1: 0.3753
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.6429 - F1: 0.6377
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5159
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4590
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4928
sub_5:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.6429 - F1: 0.6257
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4952
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: 0.4857
sub_5:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4565
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
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: 0.4521
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4952
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4296
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
sub_6:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4997
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5837
sub_6:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.6667 - F1: 0.6541
sub_6:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.6429 - F1: 0.6377
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.3842
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4286 - F1: 0.3942
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.5553
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3713
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4565
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6429 - F1: 0.6050
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4653
sub_7:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5714 - F1: 0.5457
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4269
sub_7:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.6971
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5238 - F1: 0.4167
sub_7:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.7143 - F1: 0.7136
sub_8:Test (Best Model) - Loss: 0.3398 - Accuracy: 0.6190 - F1: 0.5714
sub_8:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.8095 - F1: 0.8056
sub_8:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.7619 - F1: 0.7569
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7381 - F1: 0.7379
sub_8:Test (Best Model) - Loss: 0.3270 - Accuracy: 0.7857 - F1: 0.7754
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6667 - F1: 0.6636
sub_8:Test (Best Model) - Loss: 0.3434 - Accuracy: 0.7619 - F1: 0.7614
sub_8:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.6190 - F1: 0.5544
sub_8:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.7143 - F1: 0.6971
sub_8:Test (Best Model) - Loss: 0.3434 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6667 - F1: 0.6541
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: 0.3464 - Accuracy: 0.5476 - F1: 0.4312
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: 0.3465 - Accuracy: 0.6429 - F1: 0.6427
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5625
sub_9:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.4286 - F1: 0.4286
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.4997
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5333
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5476 - F1: 0.5411
sub_9:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.4987
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5952 - F1: 0.5837
sub_9:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5238 - F1: 0.4167
sub_10:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.6667 - F1: 0.6370
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6190 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5714 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.4447
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4269
sub_10:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.4524 - F1: 0.3944
sub_10:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.6190 - F1: 0.5852
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5654
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5361
sub_10:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5714 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.5476 - F1: 0.4815
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5714 - F1: 0.5457
sub_11:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_11:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.7857 - F1: 0.7796
sub_11:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.7381 - F1: 0.7306
sub_11:Test (Best Model) - Loss: 0.3373 - Accuracy: 0.5952 - F1: 0.5894
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6429 - F1: 0.6257
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5714 - F1: 0.5625
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5894
sub_11:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5476 - F1: 0.5347
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5714 - F1: 0.4987
sub_11:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.7143 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6667 - F1: 0.6370
sub_11:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.7143 - F1: 0.7136
sub_11:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - 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: 0.5238 - F1: 0.5238
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.6667 - F1: 0.6636
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5238 - F1: 0.4430
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3713
sub_12:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5654
sub_12:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5952 - F1: 0.5654
sub_12:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6190 - F1: 0.5714
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: 0.5238 - F1: 0.4430
sub_12:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.6429 - F1: 0.6377
sub_12:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5476 - F1: 0.4997
sub_12:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.4524 - F1: 0.4367
sub_13:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5714 - F1: 0.4750
sub_13:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.6429 - F1: 0.6050
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5952 - F1: 0.5654
sub_13:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.5476 - F1: 0.4590
sub_13:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7857 - F1: 0.7796
sub_13:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.7381 - F1: 0.7306
sub_13:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.3437 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7143 - F1: 0.7136
sub_13:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.4020
sub_13:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.6905 - F1: 0.6903
sub_13:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.7381 - F1: 0.7379
sub_14:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.6190 - F1: 0.6111
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7619 - F1: 0.7569
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.3380 - Accuracy: 0.6905 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.7619 - F1: 0.7476
sub_14:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.7143 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.8095 - F1: 0.8078
sub_14:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.7857 - F1: 0.7796
sub_14:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.8095 - F1: 0.8056
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5000 - F1: 0.4857
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.7143 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6905 - F1: 0.6903
sub_14:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5952 - F1: 0.5894
sub_14:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.7857 - F1: 0.7796

=== Summary Results ===

acc:   60.46 ± 9.57
F1:    54.74 ± 12.35
acc-in:67.09 ± 10.16
F1-in: 61.66 ± 13.13
