lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.5352 - Accuracy: 0.7619 - F1: 0.7585
sub_1:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.6548 - F1: 0.6361
sub_1:Test (Best Model) - Loss: 0.5791 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.6429 - F1: 0.6427
sub_1:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.6548 - F1: 0.6508
sub_1:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.7500 - F1: 0.7393
sub_1:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 0.5173 - Accuracy: 0.7976 - F1: 0.7974
sub_1:Test (Best Model) - Loss: 0.5218 - Accuracy: 0.7619 - F1: 0.7607
sub_1:Test (Best Model) - Loss: 0.4994 - Accuracy: 0.7500 - F1: 0.7483
sub_1:Test (Best Model) - Loss: 0.5262 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.5340 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.6905 - F1: 0.6788
sub_1:Test (Best Model) - Loss: 0.5860 - Accuracy: 0.6786 - F1: 0.6525
sub_1:Test (Best Model) - Loss: 0.5518 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.6071 - F1: 0.5619
sub_2:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.5833 - F1: 0.5073
sub_2:Test (Best Model) - Loss: 0.5345 - Accuracy: 0.7857 - F1: 0.7812
sub_2:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.7024 - F1: 0.6897
sub_2:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.6429 - F1: 0.6294
sub_2:Test (Best Model) - Loss: 0.5324 - Accuracy: 0.6190 - F1: 0.5544
sub_2:Test (Best Model) - Loss: 0.5264 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.5479 - Accuracy: 0.6310 - F1: 0.5728
sub_2:Test (Best Model) - Loss: 0.5495 - Accuracy: 0.5357 - F1: 0.4081
sub_2:Test (Best Model) - Loss: 0.5294 - Accuracy: 0.6190 - F1: 0.5634
sub_2:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.5117 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.5302 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.4801 - Accuracy: 0.8333 - F1: 0.8299
sub_2:Test (Best Model) - Loss: 0.4936 - Accuracy: 0.8214 - F1: 0.8194
sub_3:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.6667 - F1: 0.6466
sub_3:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.6548 - F1: 0.6150
sub_3:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.5595 - F1: 0.4901
sub_3:Test (Best Model) - Loss: 0.6393 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.7738 - F1: 0.7730
sub_3:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.7500 - F1: 0.7471
sub_3:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.6548 - F1: 0.6543
sub_3:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.6786 - F1: 0.6707
sub_3:Test (Best Model) - Loss: 0.5458 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.7024 - F1: 0.6863
sub_3:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.7024 - F1: 0.6897
sub_3:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.7024 - F1: 0.6989
sub_3:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.6548 - F1: 0.6434
sub_4:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.5952 - F1: 0.5800
sub_4:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5357 - F1: 0.5303
sub_4:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.5595 - F1: 0.5580
sub_4:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.5714 - F1: 0.5692
sub_4:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.5714 - F1: 0.5457
sub_4:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.6429 - F1: 0.6111
sub_4:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.7619 - F1: 0.7614
sub_4:Test (Best Model) - Loss: 0.5614 - Accuracy: 0.7500 - F1: 0.7483
sub_4:Test (Best Model) - Loss: 0.6007 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.5714 - F1: 0.4875
sub_4:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.5595 - F1: 0.4535
sub_4:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.5714 - F1: 0.4750
sub_4:Test (Best Model) - Loss: 0.6325 - Accuracy: 0.5714 - F1: 0.4750
sub_4:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.5952 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.6905 - F1: 0.6677
sub_5:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.6310 - F1: 0.5728
sub_5:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.7500 - F1: 0.7393
sub_5:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.6905 - F1: 0.6903
sub_5:Test (Best Model) - Loss: 0.5480 - Accuracy: 0.7500 - F1: 0.7456
sub_5:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.6190 - F1: 0.5714
sub_5:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.6190 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.7024 - F1: 0.6951
sub_5:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.6010 - Accuracy: 0.6190 - F1: 0.5714
sub_5:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.6190 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.5357 - F1: 0.4510
sub_5:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6548 - F1: 0.6361
sub_5:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.6190 - F1: 0.5787
sub_5:Test (Best Model) - Loss: 0.5647 - Accuracy: 0.7381 - F1: 0.7306
sub_6:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.5833 - F1: 0.5609
sub_6:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6548 - F1: 0.6535
sub_6:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5238 - F1: 0.5235
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5476 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5476 - F1: 0.5347
sub_6:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.5714 - F1: 0.5553
sub_6:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.6786 - F1: 0.6763
sub_6:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6071 - F1: 0.6003
sub_6:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.7381 - F1: 0.7357
sub_6:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5833 - F1: 0.5785
sub_6:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5833 - F1: 0.5655
sub_6:Test (Best Model) - Loss: 0.6470 - Accuracy: 0.6429 - F1: 0.6354
sub_6:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.6310 - F1: 0.6296
sub_6:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5357 - F1: 0.5276
sub_7:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6310 - F1: 0.6309
sub_7:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5119 - F1: 0.5034
sub_7:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.6310 - F1: 0.6305
sub_7:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5476 - F1: 0.5411
sub_7:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.5714 - F1: 0.5399
sub_7:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6429 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5357 - F1: 0.5276
sub_7:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5595 - F1: 0.5450
sub_7:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6190 - F1: 0.5910
sub_7:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5833 - F1: 0.5731
sub_7:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5238 - F1: 0.4952
sub_7:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7024 - F1: 0.7013
sub_7:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5476 - F1: 0.5411
sub_7:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5238 - F1: 0.4952
sub_8:Test (Best Model) - Loss: 0.4911 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4357 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4655 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.7976 - F1: 0.7974
sub_8:Test (Best Model) - Loss: 0.4658 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 0.4493 - Accuracy: 0.8452 - F1: 0.8442
sub_8:Test (Best Model) - Loss: 0.4960 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 0.5094 - Accuracy: 0.8095 - F1: 0.8078
sub_8:Test (Best Model) - Loss: 0.4394 - Accuracy: 0.8690 - F1: 0.8681
sub_8:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.7381 - F1: 0.7188
sub_8:Test (Best Model) - Loss: 0.5573 - Accuracy: 0.6548 - F1: 0.6080
sub_8:Test (Best Model) - Loss: 0.4431 - Accuracy: 0.7857 - F1: 0.7776
sub_8:Test (Best Model) - Loss: 0.4482 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.5238 - Accuracy: 0.7857 - F1: 0.7796
sub_9:Test (Best Model) - Loss: 0.5285 - Accuracy: 0.8452 - F1: 0.8452
sub_9:Test (Best Model) - Loss: 0.5290 - Accuracy: 0.8095 - F1: 0.8091
sub_9:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.7262 - F1: 0.7214
sub_9:Test (Best Model) - Loss: 0.5639 - Accuracy: 0.7619 - F1: 0.7597
sub_9:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.7738 - F1: 0.7730
sub_9:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.6310 - F1: 0.6111
sub_9:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7024 - F1: 0.6972
sub_9:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.6905 - F1: 0.6876
sub_9:Test (Best Model) - Loss: 0.6017 - Accuracy: 0.6667 - F1: 0.6597
sub_9:Test (Best Model) - Loss: 0.6188 - Accuracy: 0.7024 - F1: 0.6926
sub_9:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.6905 - F1: 0.6630
sub_9:Test (Best Model) - Loss: 0.5624 - Accuracy: 0.6905 - F1: 0.6630
sub_9:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.6071 - F1: 0.5860
sub_9:Test (Best Model) - Loss: 0.5775 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.5665 - Accuracy: 0.6310 - F1: 0.5810
sub_10:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.5119 - F1: 0.5118
sub_10:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6667 - F1: 0.6597
sub_10:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5595 - F1: 0.5564
sub_10:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5833 - F1: 0.5804
sub_10:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.5714 - F1: 0.5675
sub_10:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.6786 - F1: 0.6782
sub_10:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5595 - F1: 0.5580
sub_10:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.5714 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5119 - F1: 0.5118
sub_10:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6190 - F1: 0.5962
sub_11:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5833 - F1: 0.5556
sub_11:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.5714 - F1: 0.5508
sub_11:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.5833 - F1: 0.5655
sub_11:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.6548 - F1: 0.6212
sub_11:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.5833 - F1: 0.5556
sub_11:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.6786 - F1: 0.6612
sub_11:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.6429 - F1: 0.6294
sub_11:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.6190 - F1: 0.6007
sub_11:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.5595 - F1: 0.5302
sub_11:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.6548 - F1: 0.6434
sub_11:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.6786 - F1: 0.6730
sub_11:Test (Best Model) - Loss: 0.5762 - Accuracy: 0.6786 - F1: 0.6730
sub_11:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6667 - F1: 0.6597
sub_12:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 0.6215 - Accuracy: 0.6429 - F1: 0.6410
sub_12:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.8452 - F1: 0.8442
sub_12:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.8214 - F1: 0.8212
sub_12:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.6786 - F1: 0.6763
sub_12:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.6905 - F1: 0.6816
sub_12:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.7381 - F1: 0.7326
sub_12:Test (Best Model) - Loss: 0.5984 - Accuracy: 0.6905 - F1: 0.6719
sub_12:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.7976 - F1: 0.7962
sub_12:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.7619 - F1: 0.7551
sub_12:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.5952 - F1: 0.5524
sub_12:Test (Best Model) - Loss: 0.5522 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 0.5390 - Accuracy: 0.7738 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.7500 - F1: 0.7497
sub_12:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7381 - F1: 0.7224
sub_13:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6548 - F1: 0.6547
sub_13:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6310 - F1: 0.6111
sub_13:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.7143 - F1: 0.7141
sub_13:Test (Best Model) - Loss: 0.5821 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.4167 - F1: 0.4166
sub_13:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7262 - F1: 0.7262
sub_13:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.6667 - F1: 0.6571
sub_13:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6786 - F1: 0.6707
sub_13:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.6310 - F1: 0.6219
sub_14:Test (Best Model) - Loss: 0.4898 - Accuracy: 0.7500 - F1: 0.7418
sub_14:Test (Best Model) - Loss: 0.5666 - Accuracy: 0.6548 - F1: 0.6400
sub_14:Test (Best Model) - Loss: 0.5739 - Accuracy: 0.6548 - F1: 0.6268
sub_14:Test (Best Model) - Loss: 0.5125 - Accuracy: 0.7500 - F1: 0.7483
sub_14:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.7143 - F1: 0.7005
sub_14:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.7262 - F1: 0.7114
sub_14:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.6786 - F1: 0.6571
sub_14:Test (Best Model) - Loss: 0.5777 - Accuracy: 0.6190 - F1: 0.5634
sub_14:Test (Best Model) - Loss: 0.4967 - Accuracy: 0.7738 - F1: 0.7712
sub_14:Test (Best Model) - Loss: 0.5029 - Accuracy: 0.7381 - F1: 0.7224
sub_14:Test (Best Model) - Loss: 0.5567 - Accuracy: 0.7619 - F1: 0.7607
sub_14:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6548 - F1: 0.6361
sub_14:Test (Best Model) - Loss: 0.6082 - Accuracy: 0.7024 - F1: 0.6926
sub_14:Test (Best Model) - Loss: 0.5659 - Accuracy: 0.7381 - F1: 0.7357
sub_14:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.6667 - F1: 0.6506

=== Summary Results ===

acc: 67.00 ± 5.94
F1: 65.39 ± 6.18
acc-in: 71.36 ± 6.89
F1-in: 70.32 ± 7.20
