lr: 0.0001
sub_4:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6667 - F1: 0.6506
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6313 - Accuracy: 0.7738 - F1: 0.7730
sub_2:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.7381 - F1: 0.7188
sub_6:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.6786 - F1: 0.6473
sub_7:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.7024 - F1: 0.6972
sub_3:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5952 - F1: 0.5932
sub_5:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.5595 - F1: 0.5450
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.3911 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 0.3792 - Accuracy: 0.7976 - F1: 0.7890
sub_7:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5119 - F1: 0.3778
sub_4:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5238 - F1: 0.3842
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.7738 - F1: 0.7722
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.8452 - F1: 0.8434
sub_3:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5952 - F1: 0.5524
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.8333 - F1: 0.8299
sub_4:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.6667 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.4881 - F1: 0.3280
sub_4:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5833 - F1: 0.4958
sub_2:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5714 - F1: 0.5399
sub_5:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.6071 - F1: 0.5540
sub_4:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.3929 - F1: 0.3780
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4881 - F1: 0.4291
sub_3:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3582 - Accuracy: 0.7976 - F1: 0.7910
sub_1:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.5262 - Accuracy: 0.8452 - F1: 0.8447
sub_5:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5627 - Accuracy: 0.8095 - F1: 0.8078
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.6310 - F1: 0.5810
sub_2:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6310 - F1: 0.5884
sub_5:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.4048 - F1: 0.3037
sub_1:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5238 - F1: 0.4887
sub_3:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6429 - F1: 0.6410
sub_1:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.9048 - F1: 0.9043
sub_5:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.5388 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.7143 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5357 - F1: 0.4081
sub_14:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5119 - F1: 0.3593
sub_13:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.4868 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.7976 - F1: 0.7890
sub_8:Test (Best Model) - Loss: 0.2151 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.8571 - F1: 0.8564
sub_11:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.5714 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.9048 - F1: 0.9047
sub_12:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.5952 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.4535 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6190 - F1: 0.5787
sub_13:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6429 - F1: 0.6257
sub_11:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.5217 - Accuracy: 0.9048 - F1: 0.9047
sub_14:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7024 - F1: 0.6735
sub_13:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.3816 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5357 - F1: 0.4239
sub_12:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6071 - F1: 0.5619
sub_11:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.5033 - Accuracy: 0.8333 - F1: 0.8286
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.6310 - F1: 0.5728
sub_8:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.9048 - F1: 0.9045
sub_13:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5714 - F1: 0.4750
sub_11:Test (Best Model) - Loss: 0.5678 - Accuracy: 0.7500 - F1: 0.7393
sub_14:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5119 - F1: 0.3593
sub_10:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.8929 - F1: 0.8927
sub_12:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5952 - F1: 0.5361
sub_11:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.8929 - F1: 0.8921
sub_10:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.6786 - F1: 0.6748
sub_8:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.7976 - F1: 0.7890
sub_14:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.7619 - F1: 0.7476
sub_10:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5476 - F1: 0.4590
sub_12:Test (Best Model) - Loss: 0.5486 - Accuracy: 0.7024 - F1: 0.6735
sub_11:Test (Best Model) - Loss: 0.2900 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4643 - F1: 0.3665
sub_8:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.8214 - F1: 0.8208
sub_9:Test (Best Model) - Loss: 0.4364 - Accuracy: 0.7738 - F1: 0.7616
sub_8:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.6548 - F1: 0.6463
sub_10:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.4039 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.4780 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.5540 - Accuracy: 0.7857 - F1: 0.7796
sub_8:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.8333 - F1: 0.8309
sub_12:Test (Best Model) - Loss: 0.3837 - Accuracy: 0.8452 - F1: 0.8447

=== Summary Results ===

acc: 58.99 ± 6.02
F1: 47.84 ± 8.24
acc-in: 63.80 ± 7.20
F1-in: 52.59 ± 9.69
runing time: 656.53 seconds
