lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.7143 - F1: 0.7061
sub_1:Test (Best Model) - Loss: 0.6153 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.5559 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.4950 - Accuracy: 0.8214 - F1: 0.8202
sub_1:Test (Best Model) - Loss: 0.4049 - Accuracy: 0.8571 - F1: 0.8564
sub_1:Test (Best Model) - Loss: 0.4619 - Accuracy: 0.8214 - F1: 0.8202
sub_1:Test (Best Model) - Loss: 0.4557 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.7976 - F1: 0.7974
sub_1:Test (Best Model) - Loss: 0.5449 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.4887 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.7857 - F1: 0.7846
sub_2:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.7381 - F1: 0.7375
sub_2:Test (Best Model) - Loss: 0.5421 - Accuracy: 0.7619 - F1: 0.7618
sub_2:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.8214 - F1: 0.8202
sub_2:Test (Best Model) - Loss: 0.5206 - Accuracy: 0.7738 - F1: 0.7699
sub_2:Test (Best Model) - Loss: 0.4763 - Accuracy: 0.7381 - F1: 0.7255
sub_2:Test (Best Model) - Loss: 0.4676 - Accuracy: 0.7262 - F1: 0.7079
sub_2:Test (Best Model) - Loss: 0.3850 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.4034 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.4771 - Accuracy: 0.7381 - F1: 0.7224
sub_2:Test (Best Model) - Loss: 0.4327 - Accuracy: 0.8095 - F1: 0.8085
sub_2:Test (Best Model) - Loss: 0.3987 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.7976 - F1: 0.7953
sub_2:Test (Best Model) - Loss: 0.3651 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.4221 - Accuracy: 0.7857 - F1: 0.7856
sub_3:Test (Best Model) - Loss: 0.6173 - Accuracy: 0.6190 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5952 - F1: 0.5265
sub_3:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.5952 - F1: 0.5265
sub_3:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5833 - F1: 0.5073
sub_3:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.7619 - F1: 0.7618
sub_3:Test (Best Model) - Loss: 0.5286 - Accuracy: 0.7381 - F1: 0.7379
sub_3:Test (Best Model) - Loss: 0.5153 - Accuracy: 0.6786 - F1: 0.6782
sub_3:Test (Best Model) - Loss: 0.5177 - Accuracy: 0.7381 - F1: 0.7375
sub_3:Test (Best Model) - Loss: 0.4867 - Accuracy: 0.7500 - F1: 0.7483
sub_3:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6071 - F1: 0.5354
sub_3:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.7262 - F1: 0.7040
sub_3:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.6548 - F1: 0.6080
sub_4:Test (Best Model) - Loss: 0.5351 - Accuracy: 0.7500 - F1: 0.7500
sub_4:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.6667 - F1: 0.6659
sub_4:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5952 - F1: 0.5950
sub_4:Test (Best Model) - Loss: 0.5945 - Accuracy: 0.6905 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.7262 - F1: 0.7214
sub_4:Test (Best Model) - Loss: 0.5654 - Accuracy: 0.6548 - F1: 0.6400
sub_4:Test (Best Model) - Loss: 0.5181 - Accuracy: 0.7500 - F1: 0.7491
sub_4:Test (Best Model) - Loss: 0.5116 - Accuracy: 0.8095 - F1: 0.8078
sub_4:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.5670 - Accuracy: 0.7024 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.7381 - F1: 0.7306
sub_4:Test (Best Model) - Loss: 0.4828 - Accuracy: 0.7857 - F1: 0.7838
sub_4:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.6786 - F1: 0.6648
sub_4:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.7024 - F1: 0.6926
sub_5:Test (Best Model) - Loss: 0.4477 - Accuracy: 0.8214 - F1: 0.8208
sub_5:Test (Best Model) - Loss: 0.4179 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.3639 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.4552 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.7738 - F1: 0.7722
sub_5:Test (Best Model) - Loss: 0.5230 - Accuracy: 0.7738 - F1: 0.7641
sub_5:Test (Best Model) - Loss: 0.4706 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 0.4654 - Accuracy: 0.7381 - F1: 0.7379
sub_5:Test (Best Model) - Loss: 0.4812 - Accuracy: 0.8333 - F1: 0.8318
sub_5:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.4435 - Accuracy: 0.7619 - F1: 0.7569
sub_5:Test (Best Model) - Loss: 0.3866 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 0.4302 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.4630 - Accuracy: 0.7976 - F1: 0.7941
sub_5:Test (Best Model) - Loss: 0.4879 - Accuracy: 0.7738 - F1: 0.7712
sub_6:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.6429 - F1: 0.6410
sub_6:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5833 - F1: 0.5833
sub_6:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.6190 - F1: 0.6171
sub_6:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.6667 - F1: 0.6665
sub_6:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.6190 - F1: 0.6182
sub_6:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6905 - F1: 0.6876
sub_6:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6310 - F1: 0.6309
sub_7:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5000 - F1: 0.4989
sub_7:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5476 - F1: 0.5143
sub_7:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.5952 - F1: 0.5654
sub_7:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5833 - F1: 0.5655
sub_7:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5357 - F1: 0.5303
sub_7:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.6429 - F1: 0.6166
sub_7:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5714 - F1: 0.5712
sub_7:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.6071 - F1: 0.6071
sub_7:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6429 - F1: 0.6257
sub_8:Test (Best Model) - Loss: 0.3695 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3673 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.3718 - Accuracy: 0.8452 - F1: 0.8450
sub_8:Test (Best Model) - Loss: 0.3698 - Accuracy: 0.8333 - F1: 0.8333
sub_8:Test (Best Model) - Loss: 0.3859 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.3713 - Accuracy: 0.8690 - F1: 0.8689
sub_8:Test (Best Model) - Loss: 0.4109 - Accuracy: 0.8095 - F1: 0.8056
sub_8:Test (Best Model) - Loss: 0.3587 - Accuracy: 0.8690 - F1: 0.8689
sub_8:Test (Best Model) - Loss: 0.3398 - Accuracy: 0.8690 - F1: 0.8681
sub_8:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.3599 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.3551 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.3554 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.3745 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.4364 - Accuracy: 0.7857 - F1: 0.7826
sub_9:Test (Best Model) - Loss: 0.5103 - Accuracy: 0.7143 - F1: 0.7128
sub_9:Test (Best Model) - Loss: 0.4418 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.5268 - Accuracy: 0.7143 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.7500 - F1: 0.7471
sub_9:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.7976 - F1: 0.7953
sub_9:Test (Best Model) - Loss: 0.4864 - Accuracy: 0.7619 - F1: 0.7597
sub_9:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.8333 - F1: 0.8333
sub_9:Test (Best Model) - Loss: 0.4933 - Accuracy: 0.8095 - F1: 0.8094
sub_9:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.8333 - F1: 0.8333
sub_9:Test (Best Model) - Loss: 0.5813 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5328 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5209 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.4717 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.4873 - Accuracy: 0.7143 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.6429 - F1: 0.6429
sub_10:Test (Best Model) - Loss: 0.6032 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.6429 - F1: 0.6396
sub_10:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6429 - F1: 0.6377
sub_10:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.5828 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.7143 - F1: 0.7141
sub_10:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.5577 - Accuracy: 0.7500 - F1: 0.7491
sub_10:Test (Best Model) - Loss: 0.6087 - Accuracy: 0.6667 - F1: 0.6597
sub_10:Test (Best Model) - Loss: 0.5547 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.6310 - F1: 0.6305
sub_11:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5833 - F1: 0.5833
sub_11:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.6310 - F1: 0.6305
sub_11:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6071 - F1: 0.6066
sub_11:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 0.4993 - Accuracy: 0.8095 - F1: 0.8085
sub_11:Test (Best Model) - Loss: 0.5344 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.4884 - Accuracy: 0.7857 - F1: 0.7856
sub_11:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.7976 - F1: 0.7974
sub_11:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.7143 - F1: 0.7128
sub_11:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.7024 - F1: 0.7003
sub_11:Test (Best Model) - Loss: 0.5368 - Accuracy: 0.7619 - F1: 0.7607
sub_11:Test (Best Model) - Loss: 0.5336 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.5666 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 0.4540 - Accuracy: 0.7857 - F1: 0.7846
sub_12:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 0.3943 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.4172 - Accuracy: 0.8214 - F1: 0.8183
sub_12:Test (Best Model) - Loss: 0.5335 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.5209 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.7381 - F1: 0.7224
sub_12:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.7381 - F1: 0.7306
sub_12:Test (Best Model) - Loss: 0.5443 - Accuracy: 0.7381 - F1: 0.7306
sub_12:Test (Best Model) - Loss: 0.5043 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.4838 - Accuracy: 0.7857 - F1: 0.7796
sub_12:Test (Best Model) - Loss: 0.4790 - Accuracy: 0.7738 - F1: 0.7641
sub_12:Test (Best Model) - Loss: 0.4722 - Accuracy: 0.7619 - F1: 0.7569
sub_12:Test (Best Model) - Loss: 0.5377 - Accuracy: 0.7024 - F1: 0.6926
sub_13:Test (Best Model) - Loss: 0.5391 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.7381 - F1: 0.7381
sub_13:Test (Best Model) - Loss: 0.5604 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.5366 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 0.5179 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.6786 - F1: 0.6680
sub_13:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.5474 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.7143 - F1: 0.7128
sub_13:Test (Best Model) - Loss: 0.4892 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.5261 - Accuracy: 0.7976 - F1: 0.7962
sub_13:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7976 - F1: 0.7953
sub_13:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.7976 - F1: 0.7927
sub_13:Test (Best Model) - Loss: 0.5261 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.4760 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 0.5240 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.4505 - Accuracy: 0.7857 - F1: 0.7846
sub_14:Test (Best Model) - Loss: 0.4107 - Accuracy: 0.8214 - F1: 0.8214
sub_14:Test (Best Model) - Loss: 0.4630 - Accuracy: 0.8333 - F1: 0.8333
sub_14:Test (Best Model) - Loss: 0.3823 - Accuracy: 0.8214 - F1: 0.8183
sub_14:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.7619 - F1: 0.7569
sub_14:Test (Best Model) - Loss: 0.5156 - Accuracy: 0.7262 - F1: 0.7172
sub_14:Test (Best Model) - Loss: 0.4078 - Accuracy: 0.8333 - F1: 0.8332
sub_14:Test (Best Model) - Loss: 0.3706 - Accuracy: 0.8095 - F1: 0.8056
sub_14:Test (Best Model) - Loss: 0.5248 - Accuracy: 0.7619 - F1: 0.7607
sub_14:Test (Best Model) - Loss: 0.4853 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 0.4862 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.7857 - F1: 0.7852

=== Summary Results ===

acc: 73.00 ± 7.10
F1: 72.27 ± 7.42
acc-in: 78.13 ± 7.09
F1-in: 77.68 ± 7.27
