lr: 0.0001
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6310 - F1: 0.5728
sub_6:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5238 - F1: 0.4013
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4405 - F1: 0.4404
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.7738 - F1: 0.7683
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.6071 - F1: 0.5619
sub_5:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.5833 - F1: 0.4958
sub_1:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6916 - 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: 0.6670 - Accuracy: 0.6071 - F1: 0.5354
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5119 - F1: 0.3944
sub_1:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5119 - F1: 0.3593
sub_4:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5119 - F1: 0.3593
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.7266 - Accuracy: 0.4167 - F1: 0.4126
sub_2:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5714 - F1: 0.5675
sub_1:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5595 - F1: 0.4999
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5119 - F1: 0.3593
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5476 - F1: 0.4312
sub_6:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.3929 - F1: 0.2971
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4762 - F1: 0.3226
sub_2:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.7296 - Accuracy: 0.4881 - F1: 0.4874
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4762 - F1: 0.4296
sub_2:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3534
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4881 - F1: 0.3280
sub_1:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5714 - F1: 0.4750
sub_2:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5357 - F1: 0.4625
sub_5:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.4643 - F1: 0.3353
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3875
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4881 - F1: 0.3280
sub_1:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.8571 - F1: 0.8551
sub_3:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5595 - F1: 0.4791
sub_1:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4643 - F1: 0.3171
sub_5:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4881 - F1: 0.3280
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5833 - F1: 0.5819
sub_3:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4643 - F1: 0.4122
sub_1:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6071 - F1: 0.5452
sub_5:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6190 - F1: 0.6156
sub_9:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5595 - F1: 0.4670
sub_10:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6548 - F1: 0.6080
sub_9:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.9167 - F1: 0.9164
sub_13:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.4745 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4167 - F1: 0.3495
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.7738 - F1: 0.7664
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.3978 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.7738 - F1: 0.7641
sub_11:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.7738 - F1: 0.7730
sub_10:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.6071 - F1: 0.5540
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.4759
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4762 - F1: 0.3996
sub_14:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5357 - F1: 0.4081
sub_13:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6429 - F1: 0.6257
sub_11:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.5833 - F1: 0.4958
sub_9:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5952 - F1: 0.5265
sub_8:Test (Best Model) - Loss: 0.5729 - Accuracy: 0.8333 - F1: 0.8318
sub_12:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5833 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.6905 - F1: 0.6577
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.4564 - Accuracy: 0.8690 - F1: 0.8689
sub_11:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6548 - F1: 0.6317
sub_12:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5476 - F1: 0.4708
sub_14:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.7381 - F1: 0.7326
sub_13:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4405 - F1: 0.3861
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.7976 - F1: 0.7910
sub_13:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.6071 - F1: 0.5975
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.6310 - F1: 0.5951
sub_11:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.5119 - F1: 0.3593
sub_10:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5238 - F1: 0.3842
sub_12:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.6071 - F1: 0.5860
sub_9:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5357 - F1: 0.4625
sub_10:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5119 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3706 - Accuracy: 0.8333 - F1: 0.8286
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.6310 - F1: 0.6296
sub_8:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4643 - F1: 0.3171
sub_10:Test (Best Model) - Loss: 0.4921 - Accuracy: 0.8452 - F1: 0.8442
sub_8:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.6905 - F1: 0.6719
sub_12:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.5526 - Accuracy: 0.8333 - F1: 0.8330
sub_12:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6548 - F1: 0.6463
sub_8:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.5111 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.5252 - Accuracy: 0.8095 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 0.2181 - Accuracy: 0.9643 - F1: 0.9642

=== Summary Results ===

acc: 54.90 ± 5.42
F1: 42.60 ± 7.55
acc-in: 60.74 ± 6.87
F1-in: 48.50 ± 9.44
runing time: 643.58 seconds
