lr: 0.0001
sub_6:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6071 - F1: 0.5540
sub_6:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5403 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4881 - F1: 0.3280
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5476 - F1: 0.4312
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6934 - 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: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.6190 - F1: 0.5852
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.5952 - F1: 0.5932
sub_2:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.5575 - Accuracy: 0.6667 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.6310 - F1: 0.6152
sub_9:Test (Best Model) - Loss: 0.3660 - Accuracy: 0.8690 - F1: 0.8690
sub_8:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.8571 - F1: 0.8571
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.7024 - F1: 0.6783
sub_1:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6906 - 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: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.4920 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.4881 - F1: 0.3649
sub_4:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5476 - F1: 0.4312
sub_9:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5833 - F1: 0.5496
sub_10:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5238 - F1: 0.4013
sub_4:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_9: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_7:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.6786 - F1: 0.6415
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.8571 - F1: 0.8558
sub_5:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3057 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5238 - F1: 0.3842
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5595 - F1: 0.4535
sub_1:Test (Best Model) - Loss: 0.9025 - Accuracy: 0.5000 - F1: 0.3875
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5119 - F1: 0.4911
sub_9:Test (Best Model) - Loss: 0.7231 - Accuracy: 0.5000 - F1: 0.4700
sub_4:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.1306 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6933 - 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: 0.6948 - Accuracy: 0.3810 - F1: 0.2904
sub_5:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.3929 - F1: 0.3921
sub_2:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.5238 - F1: 0.4167
sub_9:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5238 - F1: 0.4167
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.7976 - F1: 0.7974
sub_9:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 1.0555 - Accuracy: 0.6071 - F1: 0.6044
sub_10:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5238 - F1: 0.4013
sub_2:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6548 - F1: 0.6080
sub_10:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.3452 - F1: 0.3173
sub_2:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3928 - Accuracy: 0.8452 - F1: 0.8447
sub_2:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5833 - F1: 0.4958
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.7738 - F1: 0.7730
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.6071 - F1: 0.5904
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5714 - F1: 0.5457
sub_12:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5833 - F1: 0.5270
sub_14:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7381 - F1: 0.7379
sub_12:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5238 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.7390 - Accuracy: 0.5595 - F1: 0.5302
sub_13:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5357 - F1: 0.4081
sub_11:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6936 - 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: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3580 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5357 - F1: 0.4081
sub_12:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4643 - F1: 0.4209
sub_11:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5357 - F1: 0.4729
sub_12:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.9129 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.7262 - F1: 0.7214
sub_14:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5357 - F1: 0.4625
sub_14:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333

=== Summary Results ===

acc: 53.72 ± 5.47
F1: 40.20 ± 7.94
acc-in: 58.87 ± 7.69
F1-in: 48.19 ± 10.45
runing time: 1666.34 seconds
