lr: 0.0001
sub_6:Test (Best Model) - Loss: 0.5171 - Accuracy: 0.7976 - F1: 0.7976
sub_10:Test (Best Model) - Loss: 0.5098 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.8571 - F1: 0.8571
sub_2:Test (Best Model) - Loss: 0.4026 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.5048 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.5343 - Accuracy: 0.9048 - F1: 0.9048
sub_5:Test (Best Model) - Loss: 0.5205 - Accuracy: 0.8571 - F1: 0.8558
sub_4:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.3486 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.5714 - Accuracy: 0.7262 - F1: 0.7145
sub_6:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.8214 - F1: 0.8170
sub_2:Test (Best Model) - Loss: 0.4676 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 0.5111 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.8095 - F1: 0.8041
sub_1:Test (Best Model) - Loss: 0.5047 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.4860 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.8571 - F1: 0.8564
sub_10:Test (Best Model) - Loss: 0.5494 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.5289 - Accuracy: 0.7738 - F1: 0.7664
sub_8:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.9286 - F1: 0.9286
sub_13:Test (Best Model) - Loss: 0.4195 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 0.5296 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.8690 - F1: 0.8689
sub_4:Test (Best Model) - Loss: 0.4623 - Accuracy: 0.8214 - F1: 0.8212
sub_2:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 0.4532 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.4989 - Accuracy: 0.7857 - F1: 0.7846
sub_1:Test (Best Model) - Loss: 0.4193 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.5238 - Accuracy: 0.7619 - F1: 0.7504
sub_11:Test (Best Model) - Loss: 0.5201 - Accuracy: 0.8452 - F1: 0.8442
sub_5:Test (Best Model) - Loss: 0.5030 - Accuracy: 0.7500 - F1: 0.7365
sub_8:Test (Best Model) - Loss: 0.3916 - Accuracy: 0.9405 - F1: 0.9405
sub_10:Test (Best Model) - Loss: 0.5121 - Accuracy: 0.8214 - F1: 0.8183
sub_13:Test (Best Model) - Loss: 0.4079 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.4984 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.5536 - Accuracy: 0.8452 - F1: 0.8452
sub_2:Test (Best Model) - Loss: 0.4330 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.4949 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.7619 - F1: 0.7569
sub_4:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7976 - F1: 0.7962
sub_6:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.5490 - Accuracy: 0.7976 - F1: 0.7927
sub_1:Test (Best Model) - Loss: 0.4169 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.5021 - Accuracy: 0.9167 - F1: 0.9166
sub_11:Test (Best Model) - Loss: 0.4727 - Accuracy: 0.8571 - F1: 0.8568
sub_13:Test (Best Model) - Loss: 0.5526 - Accuracy: 0.8333 - F1: 0.8325
sub_12:Test (Best Model) - Loss: 0.5234 - Accuracy: 0.8214 - F1: 0.8194
sub_3:Test (Best Model) - Loss: 0.5128 - Accuracy: 0.7738 - F1: 0.7699
sub_14:Test (Best Model) - Loss: 0.5216 - Accuracy: 0.8571 - F1: 0.8571
sub_10:Test (Best Model) - Loss: 0.5240 - Accuracy: 0.7976 - F1: 0.7927
sub_2:Test (Best Model) - Loss: 0.3743 - Accuracy: 0.9405 - F1: 0.9404
sub_6:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.8333 - F1: 0.8332
sub_9:Test (Best Model) - Loss: 0.4540 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.7024 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.4846 - Accuracy: 0.9286 - F1: 0.9286
sub_1:Test (Best Model) - Loss: 0.4500 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.5273 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.5132 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.8452 - F1: 0.8442
sub_12:Test (Best Model) - Loss: 0.5746 - Accuracy: 0.7976 - F1: 0.7962
sub_11:Test (Best Model) - Loss: 0.4724 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.9048 - F1: 0.9047
sub_10:Test (Best Model) - Loss: 0.5260 - Accuracy: 0.7857 - F1: 0.7754
sub_3:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6786 - F1: 0.6525
sub_7:Test (Best Model) - Loss: 0.5774 - Accuracy: 0.7262 - F1: 0.7114
sub_8:Test (Best Model) - Loss: 0.5453 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.4954 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.3645 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 0.4544 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.7262 - F1: 0.7214
sub_4:Test (Best Model) - Loss: 0.4901 - Accuracy: 0.7857 - F1: 0.7856
sub_5:Test (Best Model) - Loss: 0.5338 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.7024 - F1: 0.6926
sub_3:Test (Best Model) - Loss: 0.5291 - Accuracy: 0.7738 - F1: 0.7641
sub_10:Test (Best Model) - Loss: 0.4253 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.8929 - F1: 0.8925
sub_1:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.4131 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.4897 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 0.5490 - Accuracy: 0.8095 - F1: 0.8091
sub_8:Test (Best Model) - Loss: 0.3780 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.5611 - Accuracy: 0.8214 - F1: 0.8212
sub_7:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.5477 - Accuracy: 0.7738 - F1: 0.7641
sub_6:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.7143 - F1: 0.7035
sub_12:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.7976 - F1: 0.7974
sub_10:Test (Best Model) - Loss: 0.4942 - Accuracy: 0.9286 - F1: 0.9285
sub_13:Test (Best Model) - Loss: 0.5513 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 0.4455 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.4403 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.5266 - Accuracy: 0.7857 - F1: 0.7852
sub_9:Test (Best Model) - Loss: 0.4007 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.4602 - Accuracy: 0.8214 - F1: 0.8155
sub_6:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.7143 - F1: 0.7005
sub_2:Test (Best Model) - Loss: 0.3632 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 0.5156 - Accuracy: 0.7976 - F1: 0.7962
sub_4:Test (Best Model) - Loss: 0.4947 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.5181 - Accuracy: 0.8452 - F1: 0.8452
sub_7:Test (Best Model) - Loss: 0.3950 - Accuracy: 0.8690 - F1: 0.8686
sub_10:Test (Best Model) - Loss: 0.3907 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.4873 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.6905 - F1: 0.6788
sub_8:Test (Best Model) - Loss: 0.4872 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.3606 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.4267 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.8571 - F1: 0.8568
sub_3:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 0.5105 - Accuracy: 0.8452 - F1: 0.8434
sub_6:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7381 - F1: 0.7255
sub_1:Test (Best Model) - Loss: 0.4769 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.4477 - Accuracy: 0.9048 - F1: 0.9045
sub_4:Test (Best Model) - Loss: 0.4632 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 0.4823 - Accuracy: 0.9048 - F1: 0.9043
sub_10:Test (Best Model) - Loss: 0.4161 - Accuracy: 0.9286 - F1: 0.9286
sub_8:Test (Best Model) - Loss: 0.5008 - Accuracy: 0.8452 - F1: 0.8414
sub_12:Test (Best Model) - Loss: 0.5011 - Accuracy: 0.8810 - F1: 0.8809
sub_7:Test (Best Model) - Loss: 0.4818 - Accuracy: 0.8690 - F1: 0.8686
sub_3:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.8690 - F1: 0.8686
sub_14:Test (Best Model) - Loss: 0.4696 - Accuracy: 0.9524 - F1: 0.9523
sub_5:Test (Best Model) - Loss: 0.5823 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.7738 - F1: 0.7738
sub_9:Test (Best Model) - Loss: 0.5438 - Accuracy: 0.7738 - F1: 0.7616
sub_2:Test (Best Model) - Loss: 0.4426 - Accuracy: 0.9167 - F1: 0.9167
sub_10:Test (Best Model) - Loss: 0.5266 - Accuracy: 0.9167 - F1: 0.9166
sub_12:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.7857 - F1: 0.7857
sub_8:Test (Best Model) - Loss: 0.3707 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.3876 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.7976 - F1: 0.7969
sub_4:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.6905 - F1: 0.6905
sub_14:Test (Best Model) - Loss: 0.4262 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.5787 - Accuracy: 0.7381 - F1: 0.7306
sub_5:Test (Best Model) - Loss: 0.4834 - Accuracy: 0.8690 - F1: 0.8681
sub_9:Test (Best Model) - Loss: 0.5127 - Accuracy: 0.7619 - F1: 0.7476
sub_13:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.9048 - F1: 0.9045
sub_7:Test (Best Model) - Loss: 0.5432 - Accuracy: 0.8452 - F1: 0.8450
sub_2:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.8929 - F1: 0.8927
sub_6:Test (Best Model) - Loss: 0.4084 - Accuracy: 0.9405 - F1: 0.9404
sub_8:Test (Best Model) - Loss: 0.4426 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7619 - F1: 0.7504
sub_3:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.6905 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.7619 - F1: 0.7569
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5595 - F1: 0.5088
sub_9:Test (Best Model) - Loss: 0.5870 - Accuracy: 0.7262 - F1: 0.7040
sub_11:Test (Best Model) - Loss: 0.3399 - Accuracy: 0.9524 - F1: 0.9523
sub_5:Test (Best Model) - Loss: 0.4812 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 0.4077 - Accuracy: 0.9048 - F1: 0.9048
sub_7:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.8929 - F1: 0.8928
sub_13:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6548 - F1: 0.6080
sub_12:Test (Best Model) - Loss: 0.5366 - Accuracy: 0.8333 - F1: 0.8309
sub_6:Test (Best Model) - Loss: 0.4742 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.6190 - F1: 0.5634
sub_9:Test (Best Model) - Loss: 0.5655 - Accuracy: 0.7381 - F1: 0.7188
sub_8:Test (Best Model) - Loss: 0.3943 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.3781 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.7024 - F1: 0.6926
sub_1:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.7262 - F1: 0.7214
sub_5:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.8452 - F1: 0.8425
sub_10:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.6429 - F1: 0.6050
sub_11:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.7262 - F1: 0.7079
sub_13:Test (Best Model) - Loss: 0.4754 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.5306 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.3887 - Accuracy: 0.9286 - F1: 0.9285
sub_7:Test (Best Model) - Loss: 0.5507 - Accuracy: 0.7976 - F1: 0.7941
sub_8:Test (Best Model) - Loss: 0.4152 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.4532 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.5440 - Accuracy: 0.7976 - F1: 0.7962
sub_6:Test (Best Model) - Loss: 0.3974 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.7143 - F1: 0.7035
sub_10:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.5952 - F1: 0.5446
sub_3:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.7262 - F1: 0.7079
sub_2:Test (Best Model) - Loss: 0.4710 - Accuracy: 0.8690 - F1: 0.8681
sub_13:Test (Best Model) - Loss: 0.4734 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.4360 - Accuracy: 0.9405 - F1: 0.9405
sub_5:Test (Best Model) - Loss: 0.4734 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.4343 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.5228 - Accuracy: 0.8214 - F1: 0.8194
sub_14:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.8929 - F1: 0.8921
sub_4:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.7262 - F1: 0.7114
sub_10:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.5952 - F1: 0.5446
sub_6:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 0.5486 - Accuracy: 0.7738 - F1: 0.7664
sub_7:Test (Best Model) - Loss: 0.5751 - Accuracy: 0.7500 - F1: 0.7471
sub_4:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.8095 - F1: 0.8041
sub_12:Test (Best Model) - Loss: 0.5403 - Accuracy: 0.7976 - F1: 0.7941
sub_11:Test (Best Model) - Loss: 0.3814 - Accuracy: 0.9405 - F1: 0.9404
sub_14:Test (Best Model) - Loss: 0.4555 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.9167 - F1: 0.9164
sub_3:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.7381 - F1: 0.7188
sub_14:Test (Best Model) - Loss: 0.4898 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.5574 - Accuracy: 0.7619 - F1: 0.7569
sub_7:Test (Best Model) - Loss: 0.4642 - Accuracy: 0.8333 - F1: 0.8325
sub_11:Test (Best Model) - Loss: 0.3498 - Accuracy: 0.9405 - F1: 0.9404
sub_7:Test (Best Model) - Loss: 0.5773 - Accuracy: 0.7857 - F1: 0.7826

=== Summary Results ===

acc: 84.79 ± 5.45
F1: 84.37 ± 5.81
acc-in: 92.06 ± 3.85
F1-in: 91.95 ± 3.93
