lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5238 - F1: 0.5102
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.7738 - F1: 0.7641
sub_1:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5595 - F1: 0.4535
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5357 - F1: 0.4510
sub_2:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.8214 - F1: 0.8212
sub_2:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.8214 - F1: 0.8183
sub_2:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.8571 - F1: 0.8551
sub_2:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.7976 - F1: 0.7974
sub_2:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.6071 - F1: 0.5619
sub_2:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.7738 - F1: 0.7735
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_3: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_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.5341
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5476 - F1: 0.4458
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_3: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: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5357 - F1: 0.4081
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.7143 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5119 - F1: 0.3593
sub_4:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.7024 - F1: 0.6825
sub_4: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_4:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5119 - F1: 0.4094
sub_4:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5119 - F1: 0.4459
sub_4:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5238 - F1: 0.4542
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5238 - F1: 0.4430
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4643 - F1: 0.3665
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5119 - F1: 0.3778
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.4556
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4881 - F1: 0.3649
sub_6:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5476 - F1: 0.4312
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5357 - F1: 0.4239
sub_6:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6786 - F1: 0.6680
sub_6:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5476 - F1: 0.4458
sub_6:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5714 - F1: 0.5508
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5833 - F1: 0.5353
sub_6:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.6190 - F1: 0.5787
sub_6:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5476 - F1: 0.4312
sub_6:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5476 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4881 - F1: 0.3649
sub_6:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5476 - F1: 0.4312
sub_7:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.6071 - F1: 0.5619
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.4762 - F1: 0.3583
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.6071 - F1: 0.5354
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5476 - F1: 0.4997
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.7143 - F1: 0.7136
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5357 - F1: 0.4081
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5476 - F1: 0.4911
sub_8:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5714 - F1: 0.5592
sub_8:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5952 - F1: 0.5159
sub_8:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6310 - F1: 0.5728
sub_8:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5833 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.6905 - F1: 0.6630
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9: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_9:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4405 - F1: 0.3523
sub_9:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5119 - F1: 0.4349
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5714 - F1: 0.5088
sub_9:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.4524 - F1: 0.4410
sub_9:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5357 - F1: 0.5243
sub_9: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_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.4405 - F1: 0.3058
sub_10: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_10:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5833 - F1: 0.5428
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5357 - F1: 0.4382
sub_10:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3875
sub_10:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5119 - F1: 0.4911
sub_10:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6071 - F1: 0.5452
sub_11:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.4928
sub_11:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3534
sub_11:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.3571 - F1: 0.3513
sub_11:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4524 - F1: 0.4445
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.6071 - F1: 0.5904
sub_11:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_11: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: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4048 - F1: 0.3519
sub_12:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.4405 - F1: 0.3384
sub_12:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5714 - F1: 0.4987
sub_12:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4881 - F1: 0.4291
sub_12:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.3810 - F1: 0.2759
sub_13:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5238 - F1: 0.4013
sub_13:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5833 - F1: 0.5353
sub_13:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6190 - F1: 0.5910
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.6071 - F1: 0.5942
sub_13:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.7024 - F1: 0.7020
sub_13:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6905 - F1: 0.6903
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.6429 - F1: 0.6429
sub_14:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5238 - F1: 0.3842
sub_14:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5476 - F1: 0.4312

=== Summary Results ===

acc: 52.90 ± 3.84
F1: 40.49 ± 5.65
acc-in: 59.09 ± 7.26
F1-in: 49.42 ± 11.01
