lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.3095 - F1: 0.2898
sub_2:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5714 - F1: 0.5088
sub_1:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.7262 - F1: 0.7258
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3534
sub_2:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5595 - F1: 0.5238
sub_3:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.4167 - F1: 0.3247
sub_2:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4881 - F1: 0.3280
sub_2:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6071 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5476 - F1: 0.5204
sub_1:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6786 - F1: 0.6785
sub_3:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5595 - F1: 0.5595
sub_2:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5714 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.7262 - F1: 0.7258
sub_3:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6190 - F1: 0.5714
sub_1:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5833 - F1: 0.5731
sub_3:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5000 - F1: 0.3534
sub_1:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.7738 - F1: 0.7664
sub_3:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4762 - F1: 0.3583
sub_1:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5000 - F1: 0.3534
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.4643 - F1: 0.4209
sub_3:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4643 - F1: 0.3171
sub_1:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.7143 - F1: 0.7061
sub_2:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5476 - F1: 0.4312
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.6071 - F1: 0.6044
sub_1:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6190 - F1: 0.6082
sub_2:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5238 - F1: 0.4734
sub_3:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5595 - F1: 0.4791
sub_3:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5476 - F1: 0.5306
sub_1:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6786 - F1: 0.6730
sub_1:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.6190 - F1: 0.6082
sub_1:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.5119 - F1: 0.3778
sub_2:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6310 - F1: 0.6063
sub_2:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.4524 - F1: 0.3594
sub_2:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5476 - F1: 0.4312
sub_5:Test (Best Model) - Loss: 0.7192 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5714 - F1: 0.5675
sub_4:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.7143 - F1: 0.7102
sub_5:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5119 - F1: 0.3944
sub_5:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5119 - F1: 0.4094
sub_4:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.4269
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4643 - F1: 0.4414
sub_5:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.6905 - F1: 0.6840
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5238 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5952 - F1: 0.5593
sub_4:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5476 - F1: 0.4458
sub_4:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5357 - F1: 0.5107
sub_5:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.7381 - F1: 0.7224
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5595 - F1: 0.5358
sub_5:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.7024 - F1: 0.6989
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5952 - F1: 0.5943
sub_5:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.6429 - F1: 0.6396
sub_4:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.7024 - F1: 0.6825
sub_5:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.7262 - F1: 0.7258
sub_6:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.3571 - F1: 0.3568
sub_6:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5000 - F1: 0.3713
sub_5:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4762 - F1: 0.3873
sub_4:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.3690 - F1: 0.3270
sub_5:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5595 - F1: 0.4670
sub_4:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6786 - F1: 0.6730
sub_6:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.3929 - F1: 0.3107
sub_4:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5833 - F1: 0.5353
sub_5:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5714 - F1: 0.5592
sub_4:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.6548 - F1: 0.6508
sub_4:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4643 - F1: 0.4026
sub_5:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4762 - F1: 0.4750
sub_6:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.5119 - F1: 0.5062
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5238 - F1: 0.4430
sub_5:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5952 - F1: 0.5524
sub_6:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5000 - F1: 0.3713
sub_6:Test (Best Model) - Loss: 0.7115 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4881 - F1: 0.3280
sub_7:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.6190 - F1: 0.6182
sub_7:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5119 - F1: 0.3778
sub_9:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4643 - F1: 0.3517
sub_8:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.7143 - F1: 0.6971
sub_7:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4881 - F1: 0.3474
sub_9:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5357 - F1: 0.4081
sub_7:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5714 - F1: 0.4875
sub_9:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6548 - F1: 0.6523
sub_8:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6190 - F1: 0.6156
sub_9:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6667 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5714 - F1: 0.4875
sub_8:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5595 - F1: 0.5487
sub_9:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.7619 - F1: 0.7585
sub_7:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5119 - F1: 0.3778
sub_8:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.7976 - F1: 0.7890
sub_9:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5833 - F1: 0.5073
sub_7:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5952 - F1: 0.5593
sub_8:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5000 - F1: 0.4896
sub_7:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5000 - F1: 0.3713
sub_9:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.3534
sub_7:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4881 - F1: 0.3806
sub_9:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.4762 - F1: 0.3226
sub_7:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6548 - F1: 0.6543
sub_9:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4643 - F1: 0.4636
sub_7:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5000 - F1: 0.4151
sub_8:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.9048 - F1: 0.9045
sub_7:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4048 - F1: 0.3417
sub_9:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.2024 - F1: 0.2023
sub_8:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6429 - F1: 0.6377
sub_8:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5714 - F1: 0.4875
sub_9:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5000 - F1: 0.4974
sub_9:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.7381 - F1: 0.7255
sub_8:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5476 - F1: 0.5074
sub_8:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4762 - F1: 0.4612
sub_10:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5595 - F1: 0.5595
sub_12:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6071 - F1: 0.5540
sub_10:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6429 - F1: 0.5982
sub_11:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6071 - F1: 0.5452
sub_10:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.5357 - F1: 0.4510
sub_12:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6071 - F1: 0.5354
sub_10:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.5119 - F1: 0.3593
sub_11:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5595 - F1: 0.4901
sub_10:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.7738 - F1: 0.7738
sub_11:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.6667 - F1: 0.6597
sub_12:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.6190 - F1: 0.5787
sub_11:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5238 - F1: 0.3842
sub_12:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.7738 - F1: 0.7738
sub_11:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5119 - F1: 0.3778
sub_12:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.6071 - F1: 0.5452
sub_10:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5238 - F1: 0.4013
sub_12:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.7857 - F1: 0.7856
sub_10:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5000 - F1: 0.4020
sub_12:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5000 - F1: 0.3534
sub_11:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6429 - F1: 0.6166
sub_12:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.3810 - F1: 0.3354
sub_10:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4048 - F1: 0.3761
sub_10:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.7262 - F1: 0.7214
sub_11:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.4881 - F1: 0.4074
sub_12:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5119 - F1: 0.4094
sub_10:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6071 - F1: 0.5354
sub_12:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5952 - F1: 0.5265
sub_11:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.4405 - F1: 0.4267
sub_12:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.7976 - F1: 0.7969
sub_10:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5238 - F1: 0.3842
sub_11:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5000 - F1: 0.4997
sub_12:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.8095 - F1: 0.8056
sub_11:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5000 - F1: 0.4151
sub_10:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5357 - F1: 0.5341
sub_12:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5952 - F1: 0.5950
sub_13:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.6190 - F1: 0.5714
sub_14:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5952 - F1: 0.5265
sub_13:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.7381 - F1: 0.7282
sub_13:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.6310 - F1: 0.5951
sub_14:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5595 - F1: 0.4999
sub_13:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.8333 - F1: 0.8332
sub_14:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5714 - F1: 0.4987
sub_14:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5238 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.8333 - F1: 0.8332
sub_14:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.6071 - F1: 0.5354
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3534
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5476 - F1: 0.4997
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4881 - F1: 0.3474
sub_13:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.8690 - F1: 0.8689
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5357 - F1: 0.4906
sub_13:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.9048 - F1: 0.9047
sub_14:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.4762 - F1: 0.4447
sub_13:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5357 - F1: 0.4382
sub_14:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.8452 - F1: 0.8442
sub_13:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.8810 - F1: 0.8809
sub_13:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.5119 - F1: 0.3593

=== Summary Results ===

acc: 57.32 ± 5.20
F1: 49.98 ± 5.83
acc-in: 62.80 ± 5.98
F1-in: 56.56 ± 7.39
runing time: 1162.75 seconds
