lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.7024 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.4855 - Accuracy: 0.8452 - F1: 0.8442
sub_1:Test (Best Model) - Loss: 0.4255 - Accuracy: 0.8452 - F1: 0.8447
sub_1:Test (Best Model) - Loss: 0.4090 - Accuracy: 0.8810 - F1: 0.8803
sub_1:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.8214 - F1: 0.8208
sub_1:Test (Best Model) - Loss: 0.4190 - Accuracy: 0.8333 - F1: 0.8325
sub_1:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.5578 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 0.5402 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 0.4108 - Accuracy: 0.8810 - F1: 0.8810
sub_2:Test (Best Model) - Loss: 0.4271 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.4345 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.4721 - Accuracy: 0.7738 - F1: 0.7699
sub_2:Test (Best Model) - Loss: 0.4071 - Accuracy: 0.7976 - F1: 0.7910
sub_2:Test (Best Model) - Loss: 0.4044 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.3754 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.3904 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.8095 - F1: 0.8078
sub_2:Test (Best Model) - Loss: 0.3901 - Accuracy: 0.8452 - F1: 0.8442
sub_2:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.8333 - F1: 0.8318
sub_2:Test (Best Model) - Loss: 0.2832 - Accuracy: 0.8929 - F1: 0.8916
sub_2:Test (Best Model) - Loss: 0.3965 - Accuracy: 0.8333 - F1: 0.8330
sub_3:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.5952 - F1: 0.5265
sub_3:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.8675 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 0.4325 - Accuracy: 0.7619 - F1: 0.7619
sub_3:Test (Best Model) - Loss: 0.5135 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 0.5522 - Accuracy: 0.6667 - F1: 0.6665
sub_3:Test (Best Model) - Loss: 0.5292 - Accuracy: 0.7500 - F1: 0.7483
sub_3:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.6786 - F1: 0.6774
sub_3:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.7381 - F1: 0.7188
sub_3:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.7024 - F1: 0.6735
sub_4:Test (Best Model) - Loss: 0.4717 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.7500 - F1: 0.7497
sub_4:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.7619 - F1: 0.7618
sub_4:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 0.4864 - Accuracy: 0.7976 - F1: 0.7969
sub_4:Test (Best Model) - Loss: 0.4754 - Accuracy: 0.7738 - F1: 0.7712
sub_4:Test (Best Model) - Loss: 0.4826 - Accuracy: 0.7381 - F1: 0.7306
sub_4:Test (Best Model) - Loss: 0.4347 - Accuracy: 0.8214 - F1: 0.8212
sub_4:Test (Best Model) - Loss: 0.4038 - Accuracy: 0.8333 - F1: 0.8318
sub_4:Test (Best Model) - Loss: 0.4675 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 0.4621 - Accuracy: 0.7976 - F1: 0.7927
sub_4:Test (Best Model) - Loss: 0.4900 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.4630 - Accuracy: 0.7381 - F1: 0.7224
sub_4:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.6905 - F1: 0.6719
sub_4:Test (Best Model) - Loss: 0.4304 - Accuracy: 0.7857 - F1: 0.7796
sub_5:Test (Best Model) - Loss: 0.3555 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.3903 - Accuracy: 0.8452 - F1: 0.8447
sub_5:Test (Best Model) - Loss: 0.3617 - Accuracy: 0.8571 - F1: 0.8564
sub_5:Test (Best Model) - Loss: 0.3587 - Accuracy: 0.8333 - F1: 0.8330
sub_5:Test (Best Model) - Loss: 0.3855 - Accuracy: 0.8214 - F1: 0.8214
sub_5:Test (Best Model) - Loss: 0.4494 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.7857 - F1: 0.7796
sub_5:Test (Best Model) - Loss: 0.4074 - Accuracy: 0.7976 - F1: 0.7941
sub_5:Test (Best Model) - Loss: 0.3953 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.3800 - Accuracy: 0.8571 - F1: 0.8551
sub_5:Test (Best Model) - Loss: 0.3768 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.3629 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.3591 - Accuracy: 0.8214 - F1: 0.8194
sub_5:Test (Best Model) - Loss: 0.3815 - Accuracy: 0.8571 - F1: 0.8558
sub_5:Test (Best Model) - Loss: 0.3542 - Accuracy: 0.8929 - F1: 0.8925
sub_6:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6429 - F1: 0.6429
sub_6:Test (Best Model) - Loss: 0.5945 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.7143 - F1: 0.7143
sub_6:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6310 - F1: 0.6245
sub_6:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.6905 - F1: 0.6860
sub_6:Test (Best Model) - Loss: 0.6135 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 0.5648 - Accuracy: 0.7381 - F1: 0.7375
sub_6:Test (Best Model) - Loss: 0.5461 - Accuracy: 0.7500 - F1: 0.7497
sub_6:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.6667 - F1: 0.6619
sub_6:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.6071 - F1: 0.6044
sub_7:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6667 - F1: 0.6571
sub_7:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.5357 - F1: 0.5356
sub_7:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.6667 - F1: 0.6597
sub_7:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.6190 - F1: 0.5852
sub_7:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.6310 - F1: 0.5951
sub_7:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.6190 - F1: 0.6047
sub_7:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.5833 - F1: 0.5785
sub_7:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.6429 - F1: 0.6050
sub_7:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.6071 - F1: 0.6071
sub_7:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.5714 - F1: 0.5692
sub_7:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.6190 - F1: 0.6188
sub_7:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6190 - F1: 0.6182
sub_7:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6190 - F1: 0.6082
sub_8:Test (Best Model) - Loss: 0.3739 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 0.3490 - Accuracy: 0.8333 - F1: 0.8330
sub_8:Test (Best Model) - Loss: 0.3576 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.3550 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.3029 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.3072 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.2984 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 0.3003 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.2790 - Accuracy: 0.9048 - F1: 0.9043
sub_8:Test (Best Model) - Loss: 0.2977 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.2689 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.2486 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.2851 - Accuracy: 0.8571 - F1: 0.8558
sub_9:Test (Best Model) - Loss: 0.4120 - Accuracy: 0.8333 - F1: 0.8318
sub_9:Test (Best Model) - Loss: 0.4347 - Accuracy: 0.7500 - F1: 0.7483
sub_9:Test (Best Model) - Loss: 0.3895 - Accuracy: 0.7857 - F1: 0.7826
sub_9:Test (Best Model) - Loss: 0.4766 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 0.4936 - Accuracy: 0.7619 - F1: 0.7529
sub_9:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.7857 - F1: 0.7838
sub_9:Test (Best Model) - Loss: 0.4856 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.4653 - Accuracy: 0.7619 - F1: 0.7619
sub_9:Test (Best Model) - Loss: 0.4722 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 0.4459 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.6786 - F1: 0.6415
sub_9:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.4685 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.4796 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.6028 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.6310 - F1: 0.6284
sub_10:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.7381 - F1: 0.7381
sub_10:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.6786 - F1: 0.6730
sub_10:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.6548 - F1: 0.6487
sub_10:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.6905 - F1: 0.6905
sub_10:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6429 - F1: 0.6420
sub_10:Test (Best Model) - Loss: 0.5286 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 0.4993 - Accuracy: 0.7619 - F1: 0.7614
sub_10:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7024 - F1: 0.6989
sub_10:Test (Best Model) - Loss: 0.5155 - Accuracy: 0.7381 - F1: 0.7375
sub_11:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 0.6077 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.7024 - F1: 0.7003
sub_11:Test (Best Model) - Loss: 0.4068 - Accuracy: 0.8214 - F1: 0.8212
sub_11:Test (Best Model) - Loss: 0.4588 - Accuracy: 0.7500 - F1: 0.7497
sub_11:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.7738 - F1: 0.7730
sub_11:Test (Best Model) - Loss: 0.4716 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.4773 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.5781 - Accuracy: 0.6905 - F1: 0.6840
sub_11:Test (Best Model) - Loss: 0.4891 - Accuracy: 0.7619 - F1: 0.7585
sub_11:Test (Best Model) - Loss: 0.4618 - Accuracy: 0.7381 - F1: 0.7343
sub_11:Test (Best Model) - Loss: 0.4753 - Accuracy: 0.7381 - F1: 0.7357
sub_12:Test (Best Model) - Loss: 0.4282 - Accuracy: 0.8095 - F1: 0.8091
sub_12:Test (Best Model) - Loss: 0.3185 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.3059 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 0.3029 - Accuracy: 0.9048 - F1: 0.9045
sub_12:Test (Best Model) - Loss: 0.3854 - Accuracy: 0.8333 - F1: 0.8318
sub_12:Test (Best Model) - Loss: 0.5259 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.4736 - Accuracy: 0.7500 - F1: 0.7418
sub_12:Test (Best Model) - Loss: 0.5393 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.5056 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.7619 - F1: 0.7529
sub_12:Test (Best Model) - Loss: 0.4940 - Accuracy: 0.7619 - F1: 0.7504
sub_12:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.8095 - F1: 0.8041
sub_12:Test (Best Model) - Loss: 0.3980 - Accuracy: 0.7976 - F1: 0.7910
sub_12:Test (Best Model) - Loss: 0.4217 - Accuracy: 0.8095 - F1: 0.8078
sub_12:Test (Best Model) - Loss: 0.4901 - Accuracy: 0.7619 - F1: 0.7504
sub_13:Test (Best Model) - Loss: 0.5573 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.7381 - F1: 0.7379
sub_13:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.5247 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.5478 - Accuracy: 0.7738 - F1: 0.7738
sub_13:Test (Best Model) - Loss: 0.5606 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 0.5053 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.4876 - Accuracy: 0.7381 - F1: 0.7357
sub_13:Test (Best Model) - Loss: 0.4735 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 0.4548 - Accuracy: 0.7738 - F1: 0.7712
sub_13:Test (Best Model) - Loss: 0.4558 - Accuracy: 0.7619 - F1: 0.7551
sub_13:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 0.4874 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.4701 - Accuracy: 0.8214 - F1: 0.8170
sub_13:Test (Best Model) - Loss: 0.5060 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 0.3158 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.3693 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.3416 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.3509 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.3556 - Accuracy: 0.8929 - F1: 0.8928
sub_14:Test (Best Model) - Loss: 0.3517 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.4106 - Accuracy: 0.7738 - F1: 0.7699
sub_14:Test (Best Model) - Loss: 0.3707 - Accuracy: 0.8095 - F1: 0.8041
sub_14:Test (Best Model) - Loss: 0.3690 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.3197 - Accuracy: 0.8452 - F1: 0.8425
sub_14:Test (Best Model) - Loss: 0.3826 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 0.3527 - Accuracy: 0.9286 - F1: 0.9286
sub_14:Test (Best Model) - Loss: 0.3753 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.3554 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.3795 - Accuracy: 0.8571 - F1: 0.8568

=== Summary Results ===

acc: 75.63 ± 7.52
F1: 74.92 ± 7.93
acc-in: 80.94 ± 7.15
F1-in: 80.63 ± 7.32
