lr: 0.0001
sub_1:Test (Best Model) - Loss: 3.5886 - Accuracy: 0.7024 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 3.7178 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 3.0621 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 3.8505 - Accuracy: 0.7143 - F1: 0.6932
sub_1:Test (Best Model) - Loss: 4.0911 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 1.0339 - Accuracy: 0.8452 - F1: 0.8450
sub_1:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.7976 - F1: 0.7941
sub_1:Test (Best Model) - Loss: 1.5057 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 1.5748 - Accuracy: 0.7738 - F1: 0.7738
sub_1:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.8214 - F1: 0.8214
sub_1:Test (Best Model) - Loss: 1.8344 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 1.9291 - Accuracy: 0.7857 - F1: 0.7776
sub_1:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.7738 - F1: 0.7641
sub_1:Test (Best Model) - Loss: 2.1387 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 1.6342 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 1.7641 - Accuracy: 0.7024 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.7738 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.5193 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 1.5165 - Accuracy: 0.6786 - F1: 0.6680
sub_2:Test (Best Model) - Loss: 0.8452 - Accuracy: 0.7619 - F1: 0.7607
sub_2:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.8569 - Accuracy: 0.7381 - F1: 0.7326
sub_2:Test (Best Model) - Loss: 0.9827 - Accuracy: 0.7738 - F1: 0.7699
sub_2:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 0.4267 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 1.1304 - Accuracy: 0.7738 - F1: 0.7722
sub_2:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.8214 - F1: 0.8170
sub_2:Test (Best Model) - Loss: 1.1990 - Accuracy: 0.7976 - F1: 0.7927
sub_2:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 4.4804 - Accuracy: 0.5595 - F1: 0.4901
sub_3:Test (Best Model) - Loss: 3.6473 - Accuracy: 0.6548 - F1: 0.6317
sub_3:Test (Best Model) - Loss: 3.9141 - Accuracy: 0.6190 - F1: 0.5787
sub_3:Test (Best Model) - Loss: 2.0098 - Accuracy: 0.5952 - F1: 0.5593
sub_3:Test (Best Model) - Loss: 6.3646 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 2.2083 - Accuracy: 0.6905 - F1: 0.6889
sub_3:Test (Best Model) - Loss: 1.5729 - Accuracy: 0.7262 - F1: 0.7243
sub_3:Test (Best Model) - Loss: 2.1044 - Accuracy: 0.6905 - F1: 0.6905
sub_3:Test (Best Model) - Loss: 1.8188 - Accuracy: 0.6548 - F1: 0.6547
sub_3:Test (Best Model) - Loss: 1.2687 - Accuracy: 0.6786 - F1: 0.6782
sub_3:Test (Best Model) - Loss: 3.0403 - Accuracy: 0.7381 - F1: 0.7224
sub_3:Test (Best Model) - Loss: 2.6736 - Accuracy: 0.7262 - F1: 0.7079
sub_3:Test (Best Model) - Loss: 2.5909 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 2.8275 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 3.1920 - Accuracy: 0.6667 - F1: 0.6250
sub_4:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.7381 - F1: 0.7375
sub_4:Test (Best Model) - Loss: 1.8170 - Accuracy: 0.6429 - F1: 0.6420
sub_4:Test (Best Model) - Loss: 1.7072 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 2.2711 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 1.5793 - Accuracy: 0.7381 - F1: 0.7343
sub_4:Test (Best Model) - Loss: 1.0877 - Accuracy: 0.7619 - F1: 0.7618
sub_4:Test (Best Model) - Loss: 1.2394 - Accuracy: 0.7976 - F1: 0.7941
sub_4:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.7500 - F1: 0.7491
sub_4:Test (Best Model) - Loss: 2.3313 - Accuracy: 0.6786 - F1: 0.6473
sub_4:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.8571 - F1: 0.8568
sub_4:Test (Best Model) - Loss: 0.7323 - Accuracy: 0.8571 - F1: 0.8558
sub_4:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.8452 - F1: 0.8452
sub_4:Test (Best Model) - Loss: 1.2785 - Accuracy: 0.7738 - F1: 0.7699
sub_4:Test (Best Model) - Loss: 1.1341 - Accuracy: 0.7619 - F1: 0.7607
sub_5:Test (Best Model) - Loss: 1.3576 - Accuracy: 0.8333 - F1: 0.8325
sub_5:Test (Best Model) - Loss: 0.9826 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 0.5747 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 0.9687 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.7514 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 1.1575 - Accuracy: 0.7619 - F1: 0.7504
sub_5:Test (Best Model) - Loss: 1.0698 - Accuracy: 0.7500 - F1: 0.7497
sub_5:Test (Best Model) - Loss: 0.9634 - Accuracy: 0.8810 - F1: 0.8807
sub_5:Test (Best Model) - Loss: 1.1931 - Accuracy: 0.7857 - F1: 0.7846
sub_5:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.9836 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 1.0203 - Accuracy: 0.8214 - F1: 0.8194
sub_6:Test (Best Model) - Loss: 1.8583 - Accuracy: 0.6667 - F1: 0.6659
sub_6:Test (Best Model) - Loss: 2.5888 - Accuracy: 0.6190 - F1: 0.6156
sub_6:Test (Best Model) - Loss: 2.4052 - Accuracy: 0.5833 - F1: 0.5828
sub_6:Test (Best Model) - Loss: 1.6555 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 2.7451 - Accuracy: 0.6190 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.6667 - F1: 0.6619
sub_6:Test (Best Model) - Loss: 1.7627 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 1.3217 - Accuracy: 0.6429 - F1: 0.6377
sub_6:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 3.0731 - Accuracy: 0.6190 - F1: 0.5910
sub_6:Test (Best Model) - Loss: 1.7898 - Accuracy: 0.6548 - F1: 0.6543
sub_6:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.7262 - F1: 0.7252
sub_6:Test (Best Model) - Loss: 1.6906 - Accuracy: 0.7381 - F1: 0.7326
sub_6:Test (Best Model) - Loss: 1.4695 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 1.1759 - Accuracy: 0.7262 - F1: 0.7252
sub_7:Test (Best Model) - Loss: 2.4400 - Accuracy: 0.6667 - F1: 0.6313
sub_7:Test (Best Model) - Loss: 2.5418 - Accuracy: 0.6548 - F1: 0.6463
sub_7:Test (Best Model) - Loss: 2.4345 - Accuracy: 0.6190 - F1: 0.6171
sub_7:Test (Best Model) - Loss: 2.8653 - Accuracy: 0.6310 - F1: 0.6152
sub_7:Test (Best Model) - Loss: 3.5140 - Accuracy: 0.5952 - F1: 0.5524
sub_7:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.6548 - F1: 0.6268
sub_7:Test (Best Model) - Loss: 1.5197 - Accuracy: 0.6310 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 1.7842 - Accuracy: 0.6190 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 2.6781 - Accuracy: 0.5952 - F1: 0.5709
sub_7:Test (Best Model) - Loss: 2.3944 - Accuracy: 0.5714 - F1: 0.5714
sub_7:Test (Best Model) - Loss: 2.7778 - Accuracy: 0.6190 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 2.2838 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 2.5434 - Accuracy: 0.5714 - F1: 0.5592
sub_7:Test (Best Model) - Loss: 1.9967 - Accuracy: 0.6429 - F1: 0.6420
sub_7:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.6310 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 1.6212 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 1.9924 - Accuracy: 0.8095 - F1: 0.8091
sub_8:Test (Best Model) - Loss: 0.9094 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 1.6386 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 1.2195 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 0.9719 - Accuracy: 0.8571 - F1: 0.8564
sub_8:Test (Best Model) - Loss: 1.4388 - Accuracy: 0.7500 - F1: 0.7365
sub_8:Test (Best Model) - Loss: 0.5494 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.8810 - F1: 0.8807
sub_8:Test (Best Model) - Loss: 0.3468 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 1.1250 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.3285 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.8464 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.4429 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.8214 - F1: 0.8155
sub_9:Test (Best Model) - Loss: 1.8087 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.9785 - Accuracy: 0.7976 - F1: 0.7969
sub_9:Test (Best Model) - Loss: 0.9816 - Accuracy: 0.8333 - F1: 0.8299
sub_9:Test (Best Model) - Loss: 1.8690 - Accuracy: 0.7500 - F1: 0.7365
sub_9:Test (Best Model) - Loss: 2.1080 - Accuracy: 0.7143 - F1: 0.7005
sub_9:Test (Best Model) - Loss: 1.2431 - Accuracy: 0.8095 - F1: 0.8078
sub_9:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.7500 - F1: 0.7471
sub_9:Test (Best Model) - Loss: 1.4077 - Accuracy: 0.7857 - F1: 0.7812
sub_9:Test (Best Model) - Loss: 0.9309 - Accuracy: 0.7857 - F1: 0.7846
sub_9:Test (Best Model) - Loss: 0.7252 - Accuracy: 0.8452 - F1: 0.8452
sub_9:Test (Best Model) - Loss: 3.6097 - Accuracy: 0.6310 - F1: 0.5728
sub_9:Test (Best Model) - Loss: 2.0380 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.7923 - Accuracy: 0.8214 - F1: 0.8170
sub_9:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 1.4304 - Accuracy: 0.8095 - F1: 0.8041
sub_10:Test (Best Model) - Loss: 1.1645 - Accuracy: 0.6667 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.7381 - F1: 0.7379
sub_10:Test (Best Model) - Loss: 1.5723 - Accuracy: 0.6548 - F1: 0.6487
sub_10:Test (Best Model) - Loss: 1.7853 - Accuracy: 0.6786 - F1: 0.6707
sub_10:Test (Best Model) - Loss: 1.6718 - Accuracy: 0.6429 - F1: 0.6377
sub_10:Test (Best Model) - Loss: 1.9528 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 1.5695 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 2.4487 - Accuracy: 0.5595 - F1: 0.5590
sub_10:Test (Best Model) - Loss: 1.9611 - Accuracy: 0.6429 - F1: 0.6377
sub_10:Test (Best Model) - Loss: 1.9785 - Accuracy: 0.7024 - F1: 0.7013
sub_10:Test (Best Model) - Loss: 1.7417 - Accuracy: 0.6548 - F1: 0.6361
sub_10:Test (Best Model) - Loss: 1.1661 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 0.8429 - Accuracy: 0.7381 - F1: 0.7375
sub_10:Test (Best Model) - Loss: 1.5048 - Accuracy: 0.6905 - F1: 0.6876
sub_10:Test (Best Model) - Loss: 1.8775 - Accuracy: 0.5714 - F1: 0.5625
sub_11:Test (Best Model) - Loss: 1.7244 - Accuracy: 0.6190 - F1: 0.6136
sub_11:Test (Best Model) - Loss: 1.6294 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 1.4117 - Accuracy: 0.6905 - F1: 0.6840
sub_11:Test (Best Model) - Loss: 2.3329 - Accuracy: 0.6429 - F1: 0.6294
sub_11:Test (Best Model) - Loss: 2.1060 - Accuracy: 0.7143 - F1: 0.7061
sub_11:Test (Best Model) - Loss: 0.8075 - Accuracy: 0.7381 - F1: 0.7375
sub_11:Test (Best Model) - Loss: 1.6503 - Accuracy: 0.6786 - F1: 0.6525
sub_11:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.8371 - Accuracy: 0.7619 - F1: 0.7619
sub_11:Test (Best Model) - Loss: 1.1605 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 1.4770 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.7143 - F1: 0.7102
sub_11:Test (Best Model) - Loss: 0.9356 - Accuracy: 0.7857 - F1: 0.7846
sub_11:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.8452 - F1: 0.8450
sub_11:Test (Best Model) - Loss: 1.0303 - Accuracy: 0.7619 - F1: 0.7607
sub_12:Test (Best Model) - Loss: 0.5364 - Accuracy: 0.8333 - F1: 0.8332
sub_12:Test (Best Model) - Loss: 1.0286 - Accuracy: 0.8333 - F1: 0.8309
sub_12:Test (Best Model) - Loss: 0.4024 - Accuracy: 0.8690 - F1: 0.8681
sub_12:Test (Best Model) - Loss: 0.5126 - Accuracy: 0.8810 - F1: 0.8807
sub_12:Test (Best Model) - Loss: 0.8790 - Accuracy: 0.7976 - F1: 0.7890
sub_12:Test (Best Model) - Loss: 2.5298 - Accuracy: 0.7857 - F1: 0.7796
sub_12:Test (Best Model) - Loss: 1.7041 - Accuracy: 0.7500 - F1: 0.7471
sub_12:Test (Best Model) - Loss: 2.7310 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 2.8847 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 2.1618 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 2.1319 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.8812 - Accuracy: 0.7619 - F1: 0.7476
sub_12:Test (Best Model) - Loss: 1.5029 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.2016 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 1.8575 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.8086 - Accuracy: 0.6905 - F1: 0.6905
sub_13:Test (Best Model) - Loss: 1.5300 - Accuracy: 0.7381 - F1: 0.7357
sub_13:Test (Best Model) - Loss: 1.0852 - Accuracy: 0.7262 - F1: 0.7145
sub_13:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.7857 - F1: 0.7857
sub_13:Test (Best Model) - Loss: 1.0141 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 2.1352 - Accuracy: 0.6310 - F1: 0.6188
sub_13:Test (Best Model) - Loss: 1.2153 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 1.1062 - Accuracy: 0.7976 - F1: 0.7953
sub_13:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.7738 - F1: 0.7712
sub_13:Test (Best Model) - Loss: 0.7621 - Accuracy: 0.7500 - F1: 0.7418
sub_13:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.8165 - Accuracy: 0.7738 - F1: 0.7712
sub_13:Test (Best Model) - Loss: 0.9286 - Accuracy: 0.7381 - F1: 0.7224
sub_13:Test (Best Model) - Loss: 0.8612 - Accuracy: 0.8095 - F1: 0.8091
sub_14:Test (Best Model) - Loss: 0.8086 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 1.5577 - Accuracy: 0.7262 - F1: 0.7172
sub_14:Test (Best Model) - Loss: 0.7805 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.9734 - Accuracy: 0.8214 - F1: 0.8214
sub_14:Test (Best Model) - Loss: 0.4956 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.7953 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.7904 - Accuracy: 0.8214 - F1: 0.8208
sub_14:Test (Best Model) - Loss: 0.7498 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 1.2366 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 0.8564 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.7262 - F1: 0.7114
sub_14:Test (Best Model) - Loss: 1.2957 - Accuracy: 0.7262 - F1: 0.7214
sub_14:Test (Best Model) - Loss: 0.3812 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.8333 - F1: 0.8332
sub_14:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.7857 - F1: 0.7857

=== Summary Results ===

acc: 74.38 ± 6.85
F1: 73.60 ± 7.25
acc-in: 81.83 ± 6.59
F1-in: 81.39 ± 6.97
