lr: 0.0001
sub_10:Test (Best Model) - Loss: 0.5100 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 0.4497 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.4589 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.4128 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.8571 - F1: 0.8551
sub_13:Test (Best Model) - Loss: 0.4506 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 0.4908 - Accuracy: 0.8214 - F1: 0.8155
sub_9:Test (Best Model) - Loss: 0.4063 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.7738 - F1: 0.7664
sub_11:Test (Best Model) - Loss: 0.4539 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.4208 - Accuracy: 0.9524 - F1: 0.9524
sub_6:Test (Best Model) - Loss: 0.4911 - Accuracy: 0.8095 - F1: 0.8024
sub_12:Test (Best Model) - Loss: 0.5191 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.4843 - Accuracy: 0.8095 - F1: 0.8024
sub_3:Test (Best Model) - Loss: 0.5405 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.4985 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.4372 - Accuracy: 0.8690 - F1: 0.8675
sub_9:Test (Best Model) - Loss: 0.4236 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.4561 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.4618 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.4646 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7857 - F1: 0.7826
sub_8:Test (Best Model) - Loss: 0.3327 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.3584 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.4367 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.3929 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.4583 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 0.4734 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.4805 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.3979 - Accuracy: 0.8810 - F1: 0.8792
sub_5:Test (Best Model) - Loss: 0.5287 - Accuracy: 0.8214 - F1: 0.8170
sub_8:Test (Best Model) - Loss: 0.4262 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.4219 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.4191 - Accuracy: 0.9048 - F1: 0.9039
sub_12:Test (Best Model) - Loss: 0.4828 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.4796 - Accuracy: 0.8571 - F1: 0.8551
sub_13:Test (Best Model) - Loss: 0.4170 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.3821 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.4779 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.4712 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.4691 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 0.4817 - Accuracy: 0.8214 - F1: 0.8155
sub_3:Test (Best Model) - Loss: 0.4854 - Accuracy: 0.8571 - F1: 0.8542
sub_1:Test (Best Model) - Loss: 0.4143 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.4399 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.3968 - Accuracy: 0.8810 - F1: 0.8792
sub_5:Test (Best Model) - Loss: 0.5043 - Accuracy: 0.7976 - F1: 0.7941
sub_9:Test (Best Model) - Loss: 0.4164 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.4320 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.4310 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.4045 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.9048 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.4312 - Accuracy: 0.9048 - F1: 0.9043
sub_10:Test (Best Model) - Loss: 0.4980 - Accuracy: 0.7976 - F1: 0.7910
sub_8:Test (Best Model) - Loss: 0.4001 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.4952 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.4635 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.4094 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.4204 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.4581 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.4907 - Accuracy: 0.8929 - F1: 0.8928
sub_6:Test (Best Model) - Loss: 0.3951 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.4750 - Accuracy: 0.8095 - F1: 0.8068
sub_3:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.6667 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 0.3635 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.3783 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.5070 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.3994 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.3738 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.3846 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.4337 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.4030 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.5077 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.4972 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.3792 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.4137 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.4483 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.4128 - Accuracy: 0.9167 - F1: 0.9167
sub_10:Test (Best Model) - Loss: 0.4298 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.3839 - Accuracy: 0.9405 - F1: 0.9405
sub_7:Test (Best Model) - Loss: 0.5363 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.4376 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.4845 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.4292 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.4733 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.3518 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.3710 - Accuracy: 0.9048 - F1: 0.9047
sub_4:Test (Best Model) - Loss: 0.4316 - Accuracy: 0.9286 - F1: 0.9285
sub_7:Test (Best Model) - Loss: 0.5588 - Accuracy: 0.8690 - F1: 0.8681
sub_6:Test (Best Model) - Loss: 0.5166 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.3008 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.4477 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.8452 - F1: 0.8414
sub_8:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4037 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.5131 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.3633 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.4898 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.3558 - Accuracy: 0.9167 - F1: 0.9166
sub_4:Test (Best Model) - Loss: 0.4186 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.4770 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8452 - F1: 0.8414
sub_10:Test (Best Model) - Loss: 0.4316 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.3475 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.3670 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.4145 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.3910 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.4184 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 0.4584 - Accuracy: 0.9048 - F1: 0.9043
sub_7:Test (Best Model) - Loss: 0.3722 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.4528 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.4696 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.4070 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.4170 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.4251 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.3837 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.4622 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.4424 - Accuracy: 0.8571 - F1: 0.8542
sub_1:Test (Best Model) - Loss: 0.4771 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.4654 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.3980 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.4057 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.5549 - Accuracy: 0.7738 - F1: 0.7616
sub_11:Test (Best Model) - Loss: 0.4770 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.4956 - Accuracy: 0.8214 - F1: 0.8194
sub_3:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.3928 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.6667 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 0.4858 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.4256 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.4250 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.3338 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.5511 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.5371 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 0.4126 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5476 - F1: 0.4312
sub_9:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8333 - F1: 0.8332
sub_10:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.6905 - F1: 0.6577
sub_5:Test (Best Model) - Loss: 0.4178 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.4282 - Accuracy: 0.9286 - F1: 0.9284
sub_6:Test (Best Model) - Loss: 0.5049 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.4792 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.4995 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.4361 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.3878 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5476 - F1: 0.4312
sub_4:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.7976 - F1: 0.7890
sub_3:Test (Best Model) - Loss: 0.5484 - Accuracy: 0.8095 - F1: 0.8041
sub_9:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.5460 - Accuracy: 0.8095 - F1: 0.8041
sub_11:Test (Best Model) - Loss: 0.3540 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.4639 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.3771 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.6429 - F1: 0.5906
sub_4:Test (Best Model) - Loss: 0.4813 - Accuracy: 0.8810 - F1: 0.8792
sub_13:Test (Best Model) - Loss: 0.4417 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5833 - F1: 0.4958
sub_5:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.9524 - F1: 0.9524
sub_6:Test (Best Model) - Loss: 0.5649 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.4096 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.5077 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 0.4400 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7024 - F1: 0.6735
sub_14:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5357 - F1: 0.4239
sub_5:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.8929 - F1: 0.8916
sub_11:Test (Best Model) - Loss: 0.4417 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.7738 - F1: 0.7616
sub_9:Test (Best Model) - Loss: 0.5524 - Accuracy: 0.8214 - F1: 0.8155
sub_13:Test (Best Model) - Loss: 0.3792 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.4207 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.5461 - Accuracy: 0.7262 - F1: 0.7040
sub_14:Test (Best Model) - Loss: 0.7421 - Accuracy: 0.5119 - F1: 0.3778
sub_11:Test (Best Model) - Loss: 0.4141 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.5311 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.4361 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.4334 - Accuracy: 0.8452 - F1: 0.8414
sub_7:Test (Best Model) - Loss: 0.5304 - Accuracy: 0.7262 - F1: 0.7214
sub_11:Test (Best Model) - Loss: 0.4286 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.8690 - F1: 0.8668
sub_13:Test (Best Model) - Loss: 0.3250 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.3760 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.3690 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.4541 - Accuracy: 0.8571 - F1: 0.8564
sub_5:Test (Best Model) - Loss: 0.3937 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.4547 - Accuracy: 0.9048 - F1: 0.9047
sub_7:Test (Best Model) - Loss: 0.5667 - Accuracy: 0.8452 - F1: 0.8447

=== Summary Results ===

acc: 88.87 ± 4.54
F1: 88.32 ± 5.33
acc-in: 95.46 ± 2.71
F1-in: 95.42 ± 2.76
