lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6310 - F1: 0.6305
sub_1:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5476 - F1: 0.5258
sub_1:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5952 - F1: 0.5932
sub_1:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5714 - F1: 0.5675
sub_1:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5833 - F1: 0.5804
sub_1:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6667 - F1: 0.6619
sub_1:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6429 - F1: 0.6396
sub_1:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6429 - F1: 0.6429
sub_1:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6310 - F1: 0.6296
sub_1:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5595 - F1: 0.5407
sub_1:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6310 - F1: 0.6063
sub_1:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6429 - F1: 0.6354
sub_1:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.5952 - F1: 0.5709
sub_1:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.5833 - F1: 0.5428
sub_2:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.6548 - F1: 0.6535
sub_2:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.5952 - F1: 0.5654
sub_2:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6667 - F1: 0.6650
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5952 - F1: 0.5894
sub_2:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5952 - F1: 0.5837
sub_2:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6310 - F1: 0.6152
sub_2:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.7024 - F1: 0.7003
sub_2:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.5833 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.5833 - F1: 0.5353
sub_2:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.6310 - F1: 0.6111
sub_2:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6310 - F1: 0.6309
sub_2:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.6429 - F1: 0.6410
sub_2:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.5357 - F1: 0.5351
sub_2:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6310 - F1: 0.6309
sub_2:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6190 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5714 - F1: 0.5260
sub_3:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6190 - F1: 0.6136
sub_3:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5595 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5476 - F1: 0.5204
sub_3:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5595 - F1: 0.5358
sub_3:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6786 - F1: 0.6785
sub_3:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5357 - F1: 0.5351
sub_3:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5714 - F1: 0.5705
sub_3:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5833 - F1: 0.5655
sub_3:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5714 - F1: 0.5712
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5357 - F1: 0.5351
sub_3:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.4643 - F1: 0.4624
sub_3:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5357 - F1: 0.5356
sub_3:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5714 - F1: 0.5712
sub_3:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6310 - F1: 0.6284
sub_4:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.4997
sub_4:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.4405 - F1: 0.4404
sub_4:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4762 - F1: 0.4687
sub_4:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4762 - F1: 0.4687
sub_4:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.5000 - F1: 0.4928
sub_4:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5476 - F1: 0.5347
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.4857
sub_4:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4643 - F1: 0.4414
sub_4:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6310 - F1: 0.6305
sub_4:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5476 - F1: 0.5411
sub_4:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5000 - F1: 0.4700
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.4643 - F1: 0.4414
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5952 - F1: 0.5709
sub_4:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5714 - F1: 0.5333
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5119 - F1: 0.4794
sub_5:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.6071 - F1: 0.6026
sub_5:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5714 - F1: 0.5692
sub_5:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5714 - F1: 0.5088
sub_5:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.4405 - F1: 0.4307
sub_5:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4762 - F1: 0.4612
sub_5:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5238 - F1: 0.5214
sub_5:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6190 - F1: 0.6171
sub_5:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5595 - F1: 0.5088
sub_5:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5357 - F1: 0.5325
sub_5:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6190 - F1: 0.5910
sub_5:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4762 - F1: 0.4714
sub_5:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5119 - F1: 0.4856
sub_5:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5476 - F1: 0.5474
sub_6:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4167 - F1: 0.4166
sub_6:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5238 - F1: 0.5102
sub_6:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.6071 - F1: 0.5942
sub_6:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.4928
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5595 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5238 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5714 - F1: 0.5705
sub_6:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4643 - F1: 0.4354
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4762 - F1: 0.4612
sub_6:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5476 - F1: 0.5453
sub_6:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5357 - F1: 0.5325
sub_6:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4881 - F1: 0.4863
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5119 - F1: 0.5085
sub_6:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4405 - F1: 0.4385
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.4928
sub_7:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6310 - F1: 0.6245
sub_7:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5714 - F1: 0.5675
sub_7:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5357 - F1: 0.5325
sub_7:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5476 - F1: 0.5435
sub_7:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5595 - F1: 0.5487
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5119 - F1: 0.5034
sub_7:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.4896
sub_7:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4762 - F1: 0.4447
sub_7:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.4524 - F1: 0.4410
sub_7:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5238 - F1: 0.4643
sub_7:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5595 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5119 - F1: 0.5062
sub_7:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6429 - F1: 0.6420
sub_7:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5238 - F1: 0.5102
sub_7:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5119 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6667 - F1: 0.6659
sub_8:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6429 - F1: 0.6396
sub_8:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.7024 - F1: 0.7020
sub_8:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6905 - F1: 0.6905
sub_8:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6667 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.7143 - F1: 0.7141
sub_8:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6548 - F1: 0.6547
sub_8:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6667 - F1: 0.6619
sub_8:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6786 - F1: 0.6730
sub_8:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.7024 - F1: 0.7013
sub_8:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.5714 - F1: 0.5508
sub_8:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6548 - F1: 0.6361
sub_8:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.6071 - F1: 0.5860
sub_8:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6190 - F1: 0.6047
sub_8:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6071 - F1: 0.6044
sub_9:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6071 - F1: 0.6066
sub_9:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.5595 - F1: 0.5518
sub_9:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6071 - F1: 0.6057
sub_9:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5714 - F1: 0.5625
sub_9:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6190 - F1: 0.6182
sub_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5476 - F1: 0.5382
sub_9:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5238 - F1: 0.5235
sub_9:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4405 - F1: 0.4166
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4762 - F1: 0.4735
sub_9:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4881 - F1: 0.4845
sub_9:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4762 - F1: 0.4653
sub_9:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5714 - F1: 0.5712
sub_9:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5357 - F1: 0.5276
sub_9:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5238 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6310 - F1: 0.6111
sub_10:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4762 - F1: 0.4759
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5476 - F1: 0.5474
sub_10:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5357 - F1: 0.5351
sub_10:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5238 - F1: 0.5235
sub_10:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5833 - F1: 0.5731
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4881 - F1: 0.4792
sub_10:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5238 - F1: 0.5170
sub_10:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5952 - F1: 0.5837
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5595 - F1: 0.5544
sub_10:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5833 - F1: 0.5761
sub_10:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6071 - F1: 0.6057
sub_10:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5595 - F1: 0.5564
sub_10:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4286 - F1: 0.3942
sub_11:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5357 - F1: 0.5356
sub_11:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.4167 - F1: 0.4166
sub_11:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5119 - F1: 0.4911
sub_11:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5714 - F1: 0.5653
sub_11:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5595 - F1: 0.5564
sub_11:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5952 - F1: 0.5950
sub_11:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6190 - F1: 0.6136
sub_11:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5119 - F1: 0.5062
sub_11:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.4643 - F1: 0.4636
sub_11:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5000 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4762 - F1: 0.4687
sub_11:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4405 - F1: 0.4385
sub_12:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5357 - F1: 0.5243
sub_12:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5714 - F1: 0.5692
sub_12:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5595 - F1: 0.5088
sub_12:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6786 - F1: 0.6763
sub_12:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6667 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6310 - F1: 0.6296
sub_12:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5476 - F1: 0.5411
sub_12:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6310 - F1: 0.6305
sub_12:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.6786 - F1: 0.6707
sub_12:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.6429 - F1: 0.6410
sub_12:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.5357 - F1: 0.5204
sub_12:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6071 - F1: 0.5942
sub_12:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5714 - F1: 0.5625
sub_12:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5357 - F1: 0.5107
sub_12:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5714 - F1: 0.5625
sub_13:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5595 - F1: 0.5358
sub_13:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.6071 - F1: 0.5619
sub_13:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5952 - F1: 0.5800
sub_13:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.6190 - F1: 0.6182
sub_13:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5714 - F1: 0.5625
sub_13:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5833 - F1: 0.5833
sub_13:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.6786 - F1: 0.6730
sub_13:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.6190 - F1: 0.6082
sub_13:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6548 - F1: 0.6487
sub_13:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5119 - F1: 0.5102
sub_13:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6190 - F1: 0.6136
sub_13:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6786 - F1: 0.6707
sub_13:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6548 - F1: 0.6535
sub_14:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6071 - F1: 0.6044
sub_14:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5952 - F1: 0.5894
sub_14:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.6190 - F1: 0.6156
sub_14:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5952 - F1: 0.5952
sub_14:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5952 - F1: 0.5932
sub_14:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5476 - F1: 0.5074
sub_14:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6190 - F1: 0.6082
sub_14:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5595 - F1: 0.5358
sub_14:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.6429 - F1: 0.6410
sub_14:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.5833 - F1: 0.5496
sub_14:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5714 - F1: 0.5712
sub_14:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6429 - F1: 0.6396
sub_14:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5833 - F1: 0.5731
sub_14:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6310 - F1: 0.6309
sub_14:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5833 - F1: 0.5785

=== Summary Results ===

acc: 57.18 ± 4.45
F1: 56.19 ± 4.52
acc-in: 61.28 ± 3.75
F1-in: 60.35 ± 4.00
