lr: 0.0001
sub_14:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.6786 - F1: 0.6571
sub_4:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.4839 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.6905 - F1: 0.6898
sub_11:Test (Best Model) - Loss: 0.4535 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.4155 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.4698 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.8690 - F1: 0.8675
sub_6:Test (Best Model) - Loss: 0.4981 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.3955 - Accuracy: 0.8810 - F1: 0.8799
sub_1:Test (Best Model) - Loss: 0.5147 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.3088 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.4201 - Accuracy: 0.8571 - F1: 0.8551
sub_7:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.7262 - F1: 0.7172
sub_8:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4751 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.5464 - Accuracy: 0.8810 - F1: 0.8803
sub_5:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6429 - F1: 0.6420
sub_14:Test (Best Model) - Loss: 0.5276 - Accuracy: 0.7143 - F1: 0.7061
sub_12:Test (Best Model) - Loss: 0.4530 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.8095 - F1: 0.8041
sub_4:Test (Best Model) - Loss: 0.4788 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 0.3371 - Accuracy: 0.9405 - F1: 0.9405
sub_10:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.8333 - F1: 0.8309
sub_1:Test (Best Model) - Loss: 0.4444 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.4426 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.3365 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.5777 - Accuracy: 0.7262 - F1: 0.7172
sub_6:Test (Best Model) - Loss: 0.4520 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.3930 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.4643 - Accuracy: 0.8571 - F1: 0.8551
sub_12:Test (Best Model) - Loss: 0.4261 - Accuracy: 0.8810 - F1: 0.8792
sub_13:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.9167 - F1: 0.9166
sub_5:Test (Best Model) - Loss: 0.5284 - Accuracy: 0.7262 - F1: 0.7230
sub_3:Test (Best Model) - Loss: 0.4852 - Accuracy: 0.9048 - F1: 0.9047
sub_10:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.4988 - Accuracy: 0.7738 - F1: 0.7699
sub_8:Test (Best Model) - Loss: 0.3942 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.4444 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.4509 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 0.4109 - Accuracy: 0.8690 - F1: 0.8668
sub_6:Test (Best Model) - Loss: 0.4572 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.4589 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.4159 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.4094 - Accuracy: 0.9405 - F1: 0.9405
sub_2:Test (Best Model) - Loss: 0.4548 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 0.5291 - Accuracy: 0.8452 - F1: 0.8447
sub_13:Test (Best Model) - Loss: 0.4692 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.4666 - Accuracy: 0.8929 - F1: 0.8925
sub_5:Test (Best Model) - Loss: 0.5710 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.7381 - F1: 0.7282
sub_6:Test (Best Model) - Loss: 0.4724 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 0.4384 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.4833 - Accuracy: 0.8929 - F1: 0.8928
sub_4:Test (Best Model) - Loss: 0.4436 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.8214 - F1: 0.8155
sub_10:Test (Best Model) - Loss: 0.5327 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.4574 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.4026 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.4717 - Accuracy: 0.9167 - F1: 0.9166
sub_2:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 0.5638 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.7024 - F1: 0.6989
sub_11:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.4263 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.4726 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 0.4988 - Accuracy: 0.8690 - F1: 0.8686
sub_6:Test (Best Model) - Loss: 0.4434 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.5124 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.4405 - Accuracy: 0.8929 - F1: 0.8925
sub_7:Test (Best Model) - Loss: 0.4789 - Accuracy: 0.8452 - F1: 0.8414
sub_4:Test (Best Model) - Loss: 0.5106 - Accuracy: 0.8690 - F1: 0.8690
sub_10:Test (Best Model) - Loss: 0.4210 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.3987 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.3511 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.4519 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.5208 - Accuracy: 0.8690 - F1: 0.8690
sub_4:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.8571 - F1: 0.8571
sub_13:Test (Best Model) - Loss: 0.4641 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.4629 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.5510 - Accuracy: 0.7619 - F1: 0.7551
sub_12:Test (Best Model) - Loss: 0.4590 - Accuracy: 0.8333 - F1: 0.8318
sub_10:Test (Best Model) - Loss: 0.4518 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.4137 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.4221 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.5042 - Accuracy: 0.8452 - F1: 0.8425
sub_6:Test (Best Model) - Loss: 0.4912 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.4609 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.5161 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.3895 - Accuracy: 0.8810 - F1: 0.8792
sub_5:Test (Best Model) - Loss: 0.4664 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.4608 - Accuracy: 0.8929 - F1: 0.8927
sub_13:Test (Best Model) - Loss: 0.5088 - Accuracy: 0.9167 - F1: 0.9167
sub_8:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.3245 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.5264 - Accuracy: 0.8810 - F1: 0.8807
sub_9:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.8333 - F1: 0.8330
sub_7:Test (Best Model) - Loss: 0.4755 - Accuracy: 0.9167 - F1: 0.9167
sub_12:Test (Best Model) - Loss: 0.4989 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 0.3646 - Accuracy: 0.9286 - F1: 0.9285
sub_5:Test (Best Model) - Loss: 0.5085 - Accuracy: 0.8333 - F1: 0.8325
sub_1:Test (Best Model) - Loss: 0.3907 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 0.4112 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.4399 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.3801 - Accuracy: 0.8929 - F1: 0.8916
sub_11:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.4668 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.4849 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 0.5464 - Accuracy: 0.7976 - F1: 0.7890
sub_13:Test (Best Model) - Loss: 0.4281 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.5071 - Accuracy: 0.7500 - F1: 0.7500
sub_10:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.4927 - Accuracy: 0.9286 - F1: 0.9285
sub_4:Test (Best Model) - Loss: 0.5427 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.4790 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.4932 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.4647 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.7857 - F1: 0.7754
sub_8:Test (Best Model) - Loss: 0.4666 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.4813 - Accuracy: 0.8333 - F1: 0.8309
sub_9:Test (Best Model) - Loss: 0.4998 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.9048 - F1: 0.9047
sub_5:Test (Best Model) - Loss: 0.3635 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.5075 - Accuracy: 0.8095 - F1: 0.8041
sub_13:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.4693 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.5025 - Accuracy: 0.8571 - F1: 0.8558
sub_6:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.9286 - F1: 0.9284
sub_3:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.5154 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.3483 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.7262 - F1: 0.7040
sub_13:Test (Best Model) - Loss: 0.4544 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.5229 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.4453 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.7024 - F1: 0.7023
sub_5:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.8929 - F1: 0.8928
sub_7:Test (Best Model) - Loss: 0.5098 - Accuracy: 0.7857 - F1: 0.7776
sub_14:Test (Best Model) - Loss: 0.5327 - Accuracy: 0.8571 - F1: 0.8542
sub_1:Test (Best Model) - Loss: 0.4241 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.7143 - F1: 0.6889
sub_8:Test (Best Model) - Loss: 0.4998 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.5647 - Accuracy: 0.7381 - F1: 0.7282
sub_4:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.8452 - F1: 0.8434
sub_12:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.8690 - F1: 0.8675
sub_13:Test (Best Model) - Loss: 0.3893 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.6548 - F1: 0.6080
sub_11:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.4986 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.5952 - F1: 0.5265
sub_5:Test (Best Model) - Loss: 0.5490 - Accuracy: 0.7738 - F1: 0.7641
sub_6:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.4706 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.4726 - Accuracy: 0.8810 - F1: 0.8809
sub_10:Test (Best Model) - Loss: 0.6237 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 0.5860 - Accuracy: 0.6786 - F1: 0.6415
sub_1:Test (Best Model) - Loss: 0.4540 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.5833 - F1: 0.5073
sub_4:Test (Best Model) - Loss: 0.5033 - Accuracy: 0.8452 - F1: 0.8434
sub_12:Test (Best Model) - Loss: 0.5423 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.5358 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.7738 - F1: 0.7699
sub_2:Test (Best Model) - Loss: 0.5327 - Accuracy: 0.8690 - F1: 0.8689
sub_13:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.5766 - Accuracy: 0.8214 - F1: 0.8183
sub_11:Test (Best Model) - Loss: 0.4076 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.5147 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.4943 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.7381 - F1: 0.7306
sub_10:Test (Best Model) - Loss: 0.5510 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 0.4699 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 0.5350 - Accuracy: 0.7619 - F1: 0.7551
sub_11:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.9286 - F1: 0.9285
sub_1:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.4216 - Accuracy: 0.8810 - F1: 0.8803
sub_4:Test (Best Model) - Loss: 0.5449 - Accuracy: 0.7976 - F1: 0.7941
sub_2:Test (Best Model) - Loss: 0.4173 - Accuracy: 0.9048 - F1: 0.9047
sub_14:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.5714 - F1: 0.4875
sub_10:Test (Best Model) - Loss: 0.6033 - Accuracy: 0.6786 - F1: 0.6415
sub_11:Test (Best Model) - Loss: 0.4602 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.5127 - Accuracy: 0.8095 - F1: 0.8041
sub_6:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.7857 - F1: 0.7812
sub_5:Test (Best Model) - Loss: 0.5415 - Accuracy: 0.7619 - F1: 0.7551
sub_2:Test (Best Model) - Loss: 0.4785 - Accuracy: 0.8452 - F1: 0.8414
sub_4:Test (Best Model) - Loss: 0.5362 - Accuracy: 0.8333 - F1: 0.8309
sub_12:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.8690 - F1: 0.8668
sub_7:Test (Best Model) - Loss: 0.5112 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 0.3265 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5714 - F1: 0.4875
sub_9:Test (Best Model) - Loss: 0.5236 - Accuracy: 0.7976 - F1: 0.7910
sub_1:Test (Best Model) - Loss: 0.4304 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.6271 - Accuracy: 0.6310 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.8214 - F1: 0.8183
sub_13:Test (Best Model) - Loss: 0.3814 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.6190 - F1: 0.5714
sub_1:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.7362 - Accuracy: 0.5714 - F1: 0.4750
sub_7:Test (Best Model) - Loss: 0.4827 - Accuracy: 0.8571 - F1: 0.8571
sub_1:Test (Best Model) - Loss: 0.4758 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.5036 - Accuracy: 0.8095 - F1: 0.8024
sub_7:Test (Best Model) - Loss: 0.5002 - Accuracy: 0.8810 - F1: 0.8810
sub_6:Test (Best Model) - Loss: 0.5716 - Accuracy: 0.7500 - F1: 0.7365
sub_7:Test (Best Model) - Loss: 0.5127 - Accuracy: 0.8690 - F1: 0.8686
sub_7:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.7976 - F1: 0.7962

=== Summary Results ===

acc: 85.88 ± 5.68
F1: 85.36 ± 6.30
acc-in: 92.77 ± 3.84
F1-in: 92.70 ± 3.88
