lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_9: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_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6941 - 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: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6940 - 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: 0.6944 - 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: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6927 - 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: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_2: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_6:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_10: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_2:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4881 - F1: 0.3280
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.4269
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4881 - F1: 0.3280
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3713
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5833 - F1: 0.5428
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5952 - F1: 0.5446
sub_6:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6933 - 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: 0.6933 - 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: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_12: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_14:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6938 - 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: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6935 - 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: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_12: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: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6943 - 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: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6935 - 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_12:Test (Best Model) - Loss: 0.6933 - 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: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3875
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.6667 - F1: 0.6541
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333

=== Summary Results ===

acc: 50.17 ± 0.34
F1: 33.81 ± 0.66
acc-in: 50.70 ± 0.43
F1-in: 34.23 ± 0.87
runing time: 935.93 seconds
