lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.7262 - F1: 0.7114
sub_1:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.6093 - Accuracy: 0.7143 - F1: 0.6971
sub_1:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 0.4104 - Accuracy: 0.8333 - F1: 0.8318
sub_1:Test (Best Model) - Loss: 0.4241 - Accuracy: 0.8214 - F1: 0.8208
sub_1:Test (Best Model) - Loss: 0.4412 - Accuracy: 0.8095 - F1: 0.8085
sub_1:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.8333 - F1: 0.8330
sub_1:Test (Best Model) - Loss: 0.5913 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5051 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.5312 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.5305 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.7738 - F1: 0.7722
sub_2:Test (Best Model) - Loss: 0.4552 - Accuracy: 0.8214 - F1: 0.8214
sub_2:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.4989 - Accuracy: 0.7619 - F1: 0.7614
sub_2:Test (Best Model) - Loss: 0.4563 - Accuracy: 0.7976 - F1: 0.7910
sub_2:Test (Best Model) - Loss: 0.4378 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.3868 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 0.4007 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.4298 - Accuracy: 0.8452 - F1: 0.8442
sub_2:Test (Best Model) - Loss: 0.4526 - Accuracy: 0.8214 - F1: 0.8194
sub_2:Test (Best Model) - Loss: 0.3286 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.8095 - F1: 0.8091
sub_3:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 0.7403 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.8815 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 0.4250 - Accuracy: 0.7976 - F1: 0.7974
sub_3:Test (Best Model) - Loss: 0.5183 - Accuracy: 0.7619 - F1: 0.7614
sub_3:Test (Best Model) - Loss: 0.5078 - Accuracy: 0.6786 - F1: 0.6782
sub_3:Test (Best Model) - Loss: 0.4920 - Accuracy: 0.7381 - F1: 0.7375
sub_3:Test (Best Model) - Loss: 0.4845 - Accuracy: 0.7143 - F1: 0.7136
sub_3:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.6429 - F1: 0.5906
sub_3:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.6429 - F1: 0.5906
sub_3:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.5941 - Accuracy: 0.6905 - F1: 0.6577
sub_4:Test (Best Model) - Loss: 0.5484 - Accuracy: 0.7024 - F1: 0.7023
sub_4:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.6905 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.5753 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 0.5522 - Accuracy: 0.7381 - F1: 0.7368
sub_4:Test (Best Model) - Loss: 0.5363 - Accuracy: 0.7143 - F1: 0.7083
sub_4:Test (Best Model) - Loss: 0.5390 - Accuracy: 0.7024 - F1: 0.6926
sub_4:Test (Best Model) - Loss: 0.4599 - Accuracy: 0.7738 - F1: 0.7722
sub_4:Test (Best Model) - Loss: 0.4490 - Accuracy: 0.8095 - F1: 0.8078
sub_4:Test (Best Model) - Loss: 0.5007 - Accuracy: 0.7143 - F1: 0.7083
sub_4:Test (Best Model) - Loss: 0.4971 - Accuracy: 0.7976 - F1: 0.7910
sub_4:Test (Best Model) - Loss: 0.4952 - Accuracy: 0.7619 - F1: 0.7551
sub_4:Test (Best Model) - Loss: 0.4813 - Accuracy: 0.7500 - F1: 0.7456
sub_4:Test (Best Model) - Loss: 0.6024 - Accuracy: 0.6548 - F1: 0.6361
sub_4:Test (Best Model) - Loss: 0.4807 - Accuracy: 0.7738 - F1: 0.7683
sub_5:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.4270 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 0.3774 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.4099 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.4783 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4991 - Accuracy: 0.7619 - F1: 0.7529
sub_5:Test (Best Model) - Loss: 0.4303 - Accuracy: 0.7738 - F1: 0.7712
sub_5:Test (Best Model) - Loss: 0.4317 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.8214 - F1: 0.8183
sub_5:Test (Best Model) - Loss: 0.4167 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.3816 - Accuracy: 0.8214 - F1: 0.8183
sub_5:Test (Best Model) - Loss: 0.3659 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.4252 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.4303 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 0.6255 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.6071 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.6190 - F1: 0.6182
sub_6:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.6786 - F1: 0.6782
sub_6:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.6786 - F1: 0.6782
sub_6:Test (Best Model) - Loss: 0.6120 - Accuracy: 0.6905 - F1: 0.6889
sub_6:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.7262 - F1: 0.7262
sub_6:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.7024 - F1: 0.7020
sub_6:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.6190 - F1: 0.6188
sub_7:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6667 - F1: 0.6659
sub_7:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.5714 - F1: 0.5705
sub_7:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.5952 - F1: 0.5654
sub_7:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.5952 - F1: 0.5524
sub_7:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.5952 - F1: 0.5709
sub_7:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5595 - F1: 0.5580
sub_7:Test (Best Model) - Loss: 0.6295 - Accuracy: 0.6310 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6429 - F1: 0.6377
sub_7:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.5833 - F1: 0.5828
sub_7:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6190 - F1: 0.6007
sub_8:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3701 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.3380 - Accuracy: 0.8810 - F1: 0.8807
sub_8:Test (Best Model) - Loss: 0.3713 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 0.3473 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.3570 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.3234 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.3173 - Accuracy: 0.9167 - F1: 0.9167
sub_8:Test (Best Model) - Loss: 0.3096 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.2875 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.3286 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.2548 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.3325 - Accuracy: 0.8333 - F1: 0.8309
sub_9:Test (Best Model) - Loss: 0.4054 - Accuracy: 0.7976 - F1: 0.7941
sub_9:Test (Best Model) - Loss: 0.4409 - Accuracy: 0.7857 - F1: 0.7838
sub_9:Test (Best Model) - Loss: 0.4319 - Accuracy: 0.7857 - F1: 0.7812
sub_9:Test (Best Model) - Loss: 0.4894 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 0.4703 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 0.3998 - Accuracy: 0.8333 - F1: 0.8325
sub_9:Test (Best Model) - Loss: 0.4450 - Accuracy: 0.7619 - F1: 0.7607
sub_9:Test (Best Model) - Loss: 0.4562 - Accuracy: 0.7857 - F1: 0.7852
sub_9:Test (Best Model) - Loss: 0.4177 - Accuracy: 0.8095 - F1: 0.8091
sub_9:Test (Best Model) - Loss: 0.4203 - Accuracy: 0.8214 - F1: 0.8214
sub_9:Test (Best Model) - Loss: 0.6052 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5130 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.5095 - Accuracy: 0.7143 - F1: 0.6932
sub_9:Test (Best Model) - Loss: 0.4958 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 0.4937 - Accuracy: 0.6905 - F1: 0.6577
sub_10:Test (Best Model) - Loss: 0.5956 - Accuracy: 0.6667 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.5772 - Accuracy: 0.6786 - F1: 0.6774
sub_10:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6667 - F1: 0.6659
sub_10:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.6667 - F1: 0.6659
sub_10:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.6548 - F1: 0.6508
sub_10:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.6905 - F1: 0.6903
sub_10:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.7143 - F1: 0.7143
sub_10:Test (Best Model) - Loss: 0.5565 - Accuracy: 0.6905 - F1: 0.6876
sub_10:Test (Best Model) - Loss: 0.5430 - Accuracy: 0.7500 - F1: 0.7497
sub_10:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.6667 - F1: 0.6636
sub_10:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.7500 - F1: 0.7491
sub_11:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6190 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.6786 - F1: 0.6748
sub_11:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6429 - F1: 0.6420
sub_11:Test (Best Model) - Loss: 0.5462 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 0.4202 - Accuracy: 0.8690 - F1: 0.8689
sub_11:Test (Best Model) - Loss: 0.4209 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.7738 - F1: 0.7738
sub_11:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.7976 - F1: 0.7976
sub_11:Test (Best Model) - Loss: 0.4761 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.6786 - F1: 0.6748
sub_11:Test (Best Model) - Loss: 0.4672 - Accuracy: 0.7976 - F1: 0.7962
sub_11:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.7143 - F1: 0.7136
sub_11:Test (Best Model) - Loss: 0.5269 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7381 - F1: 0.7375
sub_12:Test (Best Model) - Loss: 0.3894 - Accuracy: 0.8571 - F1: 0.8568
sub_12:Test (Best Model) - Loss: 0.3753 - Accuracy: 0.8810 - F1: 0.8807
sub_12:Test (Best Model) - Loss: 0.3899 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.4192 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 0.5265 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.4932 - Accuracy: 0.7262 - F1: 0.7114
sub_12:Test (Best Model) - Loss: 0.5391 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 0.5439 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.7738 - F1: 0.7641
sub_12:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.4580 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.3997 - Accuracy: 0.8095 - F1: 0.8056
sub_12:Test (Best Model) - Loss: 0.4929 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.7024 - F1: 0.7013
sub_13:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.7024 - F1: 0.7013
sub_13:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.5211 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.5313 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.5005 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.7857 - F1: 0.7838
sub_13:Test (Best Model) - Loss: 0.4998 - Accuracy: 0.7976 - F1: 0.7962
sub_13:Test (Best Model) - Loss: 0.5312 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.8214 - F1: 0.8212
sub_13:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.4938 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.3565 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.4335 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 0.4103 - Accuracy: 0.8214 - F1: 0.8202
sub_14:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 0.3741 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.4751 - Accuracy: 0.7500 - F1: 0.7439
sub_14:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.8214 - F1: 0.8183
sub_14:Test (Best Model) - Loss: 0.3818 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.3019 - Accuracy: 0.8333 - F1: 0.8299
sub_14:Test (Best Model) - Loss: 0.4806 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.4088 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.4524 - Accuracy: 0.8095 - F1: 0.8094
sub_14:Test (Best Model) - Loss: 0.4793 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.7857 - F1: 0.7857

=== Summary Results ===

acc: 74.46 ± 7.23
F1: 73.72 ± 7.66
acc-in: 79.74 ± 6.99
F1-in: 79.37 ± 7.22
