lr: 0.0001
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6924 - 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: 0.6931 - Accuracy: 0.4881 - F1: 0.3474
sub_5:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.4759
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6933 - 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: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.6190 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5119 - F1: 0.3778
sub_6:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4881 - F1: 0.3280
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5238 - F1: 0.3842
sub_7:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4881 - F1: 0.3474
sub_6:Test (Best Model) - Loss: 0.6934 - 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: 0.6923 - 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: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.7024 - F1: 0.7020
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6928 - 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: 0.6932 - 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: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.3645 - Accuracy: 0.8095 - F1: 0.8024
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.3333
sub_5: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_6:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6933 - 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: 0.6910 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4881 - F1: 0.3280
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5714 - F1: 0.5399
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4881 - F1: 0.3806
sub_2:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.8333 - F1: 0.8286
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5357 - F1: 0.4081
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6939 - 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_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4762 - F1: 0.3736
sub_1:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5357 - F1: 0.5107
sub_2:Test (Best Model) - Loss: 0.2713 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4524 - F1: 0.3115
sub_2:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.7262 - F1: 0.7079
sub_2:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4762 - F1: 0.3414
sub_14:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6926 - 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: 0.6933 - 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: 0.6930 - Accuracy: 0.5476 - F1: 0.4708
sub_9:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.6429 - F1: 0.6214
sub_12:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5357 - F1: 0.4081
sub_14:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.6190 - F1: 0.6136
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5833 - F1: 0.5428
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6936 - 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: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5119 - F1: 0.3593
sub_13:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.6667 - F1: 0.6370
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.7500 - F1: 0.7439
sub_10:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.6429 - F1: 0.6396
sub_14:Test (Best Model) - Loss: 0.6935 - 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: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5595 - F1: 0.5450
sub_13:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6929 - 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: 0.6877 - Accuracy: 0.5119 - F1: 0.3593
sub_13:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6786 - F1: 0.6785
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.6310 - F1: 0.5728
sub_11:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6071 - F1: 0.6071
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_9: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_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6940 - 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: 0.6929 - Accuracy: 0.5357 - F1: 0.4822
sub_13:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6914 - 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: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6429 - F1: 0.5982
sub_9:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.4700
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6930 - 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: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.6667 - F1: 0.6466
sub_12:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5952 - F1: 0.5943
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4762 - F1: 0.4565
sub_12:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5952 - F1: 0.5446
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333

=== Summary Results ===

acc: 51.73 ± 2.42
F1: 37.10 ± 3.96
acc-in: 54.45 ± 3.46
F1-in: 39.61 ± 5.14
runing time: 456.85 seconds
