lr: 0.0001
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5119 - F1: 0.3593
sub_5:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.8214 - F1: 0.8155
sub_9:Test (Best Model) - Loss: 0.5748 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.3676 - Accuracy: 0.8690 - F1: 0.8686
sub_4:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5714 - F1: 0.5179
sub_1:Test (Best Model) - Loss: 0.2018 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6071 - F1: 0.5753
sub_7:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.6071 - F1: 0.5619
sub_5:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.7143 - F1: 0.6971
sub_8:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.2307 - Accuracy: 0.8690 - F1: 0.8689
sub_9:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.7024 - F1: 0.6989
sub_10:Test (Best Model) - Loss: 0.3621 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 0.5549 - Accuracy: 0.7976 - F1: 0.7962
sub_3:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5714 - F1: 0.4750
sub_2:Test (Best Model) - Loss: 0.4365 - Accuracy: 0.7619 - F1: 0.7504
sub_4:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.8810 - F1: 0.8809
sub_7:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.4762 - F1: 0.4296
sub_8:Test (Best Model) - Loss: 0.1193 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5476 - F1: 0.4312
sub_9:Test (Best Model) - Loss: 0.0316 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.2888 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.4412 - Accuracy: 0.8810 - F1: 0.8810
sub_2:Test (Best Model) - Loss: 0.5866 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.4739 - Accuracy: 0.8929 - F1: 0.8927
sub_7:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.4416 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.9081 - Accuracy: 0.6667 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.6548 - F1: 0.6080
sub_5:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6429 - F1: 0.5906
sub_7:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5476 - F1: 0.5435
sub_4:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.9048 - F1: 0.9047
sub_2:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.8214 - F1: 0.8183
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.4940 - Accuracy: 0.7738 - F1: 0.7683
sub_1:Test (Best Model) - Loss: 0.5388 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5595 - F1: 0.4535
sub_7:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.5218 - Accuracy: 0.9524 - F1: 0.9524
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.6071 - F1: 0.5690
sub_9:Test (Best Model) - Loss: 0.0504 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.4842 - Accuracy: 0.8452 - F1: 0.8452
sub_7:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.2487 - Accuracy: 0.9048 - F1: 0.9045
sub_10:Test (Best Model) - Loss: 0.4599 - Accuracy: 0.7738 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5595 - F1: 0.5238
sub_8:Test (Best Model) - Loss: 0.2518 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.5671 - Accuracy: 0.7143 - F1: 0.7083
sub_2:Test (Best Model) - Loss: 0.2962 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.7234 - Accuracy: 0.5119 - F1: 0.4794
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5476 - F1: 0.4312
sub_9:Test (Best Model) - Loss: 0.4655 - Accuracy: 0.8810 - F1: 0.8799
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.8637 - Accuracy: 0.4405 - F1: 0.4220
sub_8:Test (Best Model) - Loss: 0.1915 - Accuracy: 0.9405 - F1: 0.9404
sub_2:Test (Best Model) - Loss: 0.1824 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.6010 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5714 - F1: 0.5592
sub_8:Test (Best Model) - Loss: 0.5382 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 1.1707 - Accuracy: 0.5714 - F1: 0.5712
sub_5:Test (Best Model) - Loss: 1.0326 - Accuracy: 0.5833 - F1: 0.5833
sub_2:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.7381 - F1: 0.7188
sub_7:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5357 - F1: 0.4239
sub_3:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5714 - F1: 0.5457
sub_2:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.8810 - F1: 0.8807
sub_4:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5476 - F1: 0.4312
sub_10:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.7857 - F1: 0.7754
sub_7:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.7381 - F1: 0.7368
sub_5:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.6310 - F1: 0.6284
sub_6:Test (Best Model) - Loss: 0.8522 - Accuracy: 0.4405 - F1: 0.3523
sub_9:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.6310 - F1: 0.6284
sub_10:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.2731 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.2417 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.2922 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.5705 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4881 - F1: 0.3280
sub_3:Test (Best Model) - Loss: 0.7627 - Accuracy: 0.6786 - F1: 0.6782
sub_1:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5595 - F1: 0.5167
sub_9:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3277 - Accuracy: 0.8214 - F1: 0.8183
sub_1:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.4762 - F1: 0.3414
sub_2:Test (Best Model) - Loss: 0.1905 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.6905 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.7381 - F1: 0.7379
sub_5:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4643 - F1: 0.4026
sub_1:Test (Best Model) - Loss: 0.4773 - Accuracy: 0.6905 - F1: 0.6719
sub_8:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.6071 - F1: 0.5452
sub_10:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.4065 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 0.5877 - Accuracy: 0.7024 - F1: 0.6735
sub_4:Test (Best Model) - Loss: 0.5122 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.4849 - Accuracy: 0.6905 - F1: 0.6677
sub_9:Test (Best Model) - Loss: 0.0412 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.5000 - F1: 0.3534
sub_10:Test (Best Model) - Loss: 0.5103 - Accuracy: 0.8571 - F1: 0.8568
sub_4:Test (Best Model) - Loss: 0.5184 - Accuracy: 0.7976 - F1: 0.7910
sub_3:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.7262 - F1: 0.7145
sub_8:Test (Best Model) - Loss: 0.5212 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.2662 - Accuracy: 0.9286 - F1: 0.9285
sub_1:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.7500 - F1: 0.7365
sub_10:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.5238 - F1: 0.3842
sub_9:Test (Best Model) - Loss: 0.2061 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.3586 - Accuracy: 0.8571 - F1: 0.8558
sub_2:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6071 - F1: 0.5540
sub_1:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.6548 - F1: 0.6150
sub_10:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5714 - F1: 0.4875
sub_9:Test (Best Model) - Loss: 0.1213 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.7857 - F1: 0.7846
sub_1:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.5672 - Accuracy: 0.6667 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.6071 - F1: 0.5354
sub_12:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5238 - F1: 0.3842
sub_11:Test (Best Model) - Loss: 0.4926 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.1820 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.8428 - Accuracy: 0.5714 - F1: 0.4750
sub_11:Test (Best Model) - Loss: 0.8579 - Accuracy: 0.6548 - F1: 0.6080
sub_14:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.8690 - F1: 0.8686
sub_13:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.8214 - F1: 0.8155
sub_12:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.1786 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.3783 - Accuracy: 0.8214 - F1: 0.8170
sub_12:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.5952 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.6667 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 0.5362 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7619 - F1: 0.7476
sub_13:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.4724 - Accuracy: 0.7381 - F1: 0.7188
sub_14:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5119 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.7024 - F1: 0.7023
sub_11:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.7976 - F1: 0.7976
sub_14:Test (Best Model) - Loss: 0.5713 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.5595 - F1: 0.4535
sub_13:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6071 - F1: 0.6044
sub_12:Test (Best Model) - Loss: 0.2359 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.8452 - F1: 0.8425
sub_13:Test (Best Model) - Loss: 0.5238 - Accuracy: 0.8810 - F1: 0.8799
sub_14:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.5489 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.0592 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.7619 - F1: 0.7551
sub_14:Test (Best Model) - Loss: 0.4435 - Accuracy: 0.8690 - F1: 0.8690
sub_11:Test (Best Model) - Loss: 0.4720 - Accuracy: 0.7738 - F1: 0.7616
sub_12:Test (Best Model) - Loss: 0.2877 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.7500 - F1: 0.7483
sub_12:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.4556
sub_13:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.3379 - Accuracy: 0.8690 - F1: 0.8668
sub_14:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6786 - F1: 0.6774
sub_12:Test (Best Model) - Loss: 0.4869 - Accuracy: 0.7857 - F1: 0.7796
sub_13:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.8571 - F1: 0.8551
sub_11:Test (Best Model) - Loss: 0.2380 - Accuracy: 0.9048 - F1: 0.9043
sub_12:Test (Best Model) - Loss: 0.2952 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.7615 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.6071 - F1: 0.5354
sub_13:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.6548 - F1: 0.6361
sub_12:Test (Best Model) - Loss: 0.2613 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 1.7555 - Accuracy: 0.5238 - F1: 0.3842
sub_14:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6667 - F1: 0.6659
sub_13:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.5526 - Accuracy: 0.7143 - F1: 0.6889
sub_12:Test (Best Model) - Loss: 0.7837 - Accuracy: 0.7024 - F1: 0.6735
sub_11:Test (Best Model) - Loss: 0.5423 - Accuracy: 0.7143 - F1: 0.7141

=== Summary Results ===

acc: 69.51 ± 9.69
F1: 63.91 ± 12.79
acc-in: 79.19 ± 10.26
F1-in: 75.21 ± 13.31
runing time: 1844.10 seconds
