lr: 1e-06
sub_2:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5238 - F1: 0.5009
sub_3:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4286 - F1: 0.4233
sub_1:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6310 - F1: 0.6296
sub_2:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.5238 - F1: 0.5102
sub_3:Test (Best Model) - Loss: 0.7518 - Accuracy: 0.4881 - F1: 0.3474
sub_1:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4643 - F1: 0.3353
sub_3:Test (Best Model) - Loss: 0.7481 - Accuracy: 0.3810 - F1: 0.2759
sub_2:Test (Best Model) - Loss: 0.7843 - Accuracy: 0.5000 - F1: 0.3534
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5952 - F1: 0.5446
sub_3:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5000 - F1: 0.3713
sub_2:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4881 - F1: 0.3280
sub_2:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6905 - F1: 0.6898
sub_1:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.6786 - F1: 0.6730
sub_3:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.4989
sub_2:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.4524 - F1: 0.3451
sub_3:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5357 - F1: 0.4510
sub_2:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5952 - F1: 0.5868
sub_2:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.3713
sub_1:Test (Best Model) - Loss: 0.7409 - Accuracy: 0.4762 - F1: 0.3414
sub_3:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.4286 - F1: 0.4071
sub_2:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4762 - F1: 0.3583
sub_1:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.5595 - F1: 0.5544
sub_3:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.6071 - F1: 0.6003
sub_2:Test (Best Model) - Loss: 0.7476 - Accuracy: 0.5714 - F1: 0.4875
sub_1:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4167 - F1: 0.3247
sub_2:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4762 - F1: 0.4687
sub_3:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4405 - F1: 0.3384
sub_1:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5238 - F1: 0.4430
sub_2:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5952 - F1: 0.5894
sub_3:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5000 - F1: 0.4928
sub_2:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.5119 - F1: 0.3944
sub_3:Test (Best Model) - Loss: 0.7338 - Accuracy: 0.4167 - F1: 0.3247
sub_1:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6548 - F1: 0.6434
sub_2:Test (Best Model) - Loss: 0.7768 - Accuracy: 0.5238 - F1: 0.3842
sub_3:Test (Best Model) - Loss: 0.7989 - Accuracy: 0.4762 - F1: 0.4207
sub_1:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.5119 - F1: 0.4794
sub_3:Test (Best Model) - Loss: 0.8301 - Accuracy: 0.6190 - F1: 0.5544
sub_3:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.6429 - F1: 0.6410
sub_1:Test (Best Model) - Loss: 0.7520 - Accuracy: 0.6667 - F1: 0.6370
sub_1:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5119 - F1: 0.3593
sub_5:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.6786 - F1: 0.6648
sub_4:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5714 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.5119 - F1: 0.5118
sub_4:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5357 - F1: 0.4510
sub_6:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5238 - F1: 0.5139
sub_5:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.5000 - F1: 0.4020
sub_4:Test (Best Model) - Loss: 0.7409 - Accuracy: 0.5357 - F1: 0.5159
sub_5:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.5595 - F1: 0.4999
sub_5:Test (Best Model) - Loss: 0.7894 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.7967 - Accuracy: 0.5119 - F1: 0.4794
sub_6:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5476 - F1: 0.5347
sub_6:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5476 - F1: 0.4911
sub_5:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5952 - F1: 0.5709
sub_6:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5119 - F1: 0.3944
sub_5:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5476 - F1: 0.5435
sub_4:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5357 - F1: 0.5204
sub_6:Test (Best Model) - Loss: 0.7526 - Accuracy: 0.3929 - F1: 0.3229
sub_5:Test (Best Model) - Loss: 0.7497 - Accuracy: 0.4286 - F1: 0.3166
sub_4:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5238 - F1: 0.4542
sub_6:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5000 - F1: 0.4812
sub_5:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6548 - F1: 0.6361
sub_4:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.3571 - F1: 0.3388
sub_6:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.5000 - F1: 0.3534
sub_4:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4524 - F1: 0.3594
sub_5:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.4762 - F1: 0.3226
sub_4:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4286 - F1: 0.3000
sub_5:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5119 - F1: 0.3944
sub_4:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6667 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 2.0492 - Accuracy: 0.5595 - F1: 0.5564
sub_4:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5238 - F1: 0.4734
sub_5:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.4167 - F1: 0.3975
sub_4:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.6071 - F1: 0.5619
sub_5:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.3452 - F1: 0.3237
sub_4:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.4405 - F1: 0.3523
sub_5:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.5119 - F1: 0.4094
sub_6:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.5238 - F1: 0.4167
sub_4:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.5714 - F1: 0.5457
sub_6:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5000 - F1: 0.3713
sub_6:Test (Best Model) - Loss: 2.8973 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5476 - F1: 0.4911
sub_7:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5952 - F1: 0.5915
sub_9:Test (Best Model) - Loss: 0.7698 - Accuracy: 0.4524 - F1: 0.3115
sub_7:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5238 - F1: 0.4013
sub_8:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4762 - F1: 0.3996
sub_7:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5119 - F1: 0.3778
sub_9:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5595 - F1: 0.4535
sub_8:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4762 - F1: 0.4296
sub_7:Test (Best Model) - Loss: 0.7368 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7251 - Accuracy: 0.5833 - F1: 0.5819
sub_9:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.5357 - F1: 0.4510
sub_9:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5833 - F1: 0.5073
sub_8:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.7143 - F1: 0.7128
sub_9:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6190 - F1: 0.6111
sub_8:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5714 - F1: 0.5088
sub_7:Test (Best Model) - Loss: 0.7380 - Accuracy: 0.4524 - F1: 0.4474
sub_7:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.4286 - F1: 0.3316
sub_9:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5238 - F1: 0.4167
sub_7:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.4524 - F1: 0.3292
sub_8:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.8929 - F1: 0.8925
sub_7:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5476 - F1: 0.4815
sub_8:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5119 - F1: 0.3944
sub_9:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5119 - F1: 0.5118
sub_7:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4405 - F1: 0.3861
sub_9:Test (Best Model) - Loss: 0.8000 - Accuracy: 0.4881 - F1: 0.3280
sub_7:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5952 - F1: 0.5952
sub_9:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.7143 - F1: 0.7102
sub_7:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.4643 - F1: 0.3665
sub_9:Test (Best Model) - Loss: 0.8469 - Accuracy: 0.2738 - F1: 0.2560
sub_7:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.7303 - Accuracy: 0.5119 - F1: 0.3593
sub_9:Test (Best Model) - Loss: 0.9893 - Accuracy: 0.3810 - F1: 0.2904
sub_8:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6071 - F1: 0.5690
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6667 - F1: 0.6659
sub_9:Test (Best Model) - Loss: 0.7890 - Accuracy: 0.2262 - F1: 0.2172
sub_9:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.4762 - F1: 0.4714
sub_8:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.5119 - F1: 0.3593
sub_11:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7383 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6071 - F1: 0.6057
sub_11:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5357 - F1: 0.5204
sub_10:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.6310 - F1: 0.6010
sub_10:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5119 - F1: 0.4794
sub_12:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5476 - F1: 0.4458
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5476 - F1: 0.4458
sub_10:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6071 - F1: 0.5975
sub_12:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5238 - F1: 0.4430
sub_10:Test (Best Model) - Loss: 0.7242 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5595 - F1: 0.4535
sub_10:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.7024 - F1: 0.6926
sub_12:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5952 - F1: 0.5915
sub_11:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.4881 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.6667 - F1: 0.6466
sub_10:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.6310 - F1: 0.6309
sub_12:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6548 - F1: 0.6268
sub_11:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.4881 - F1: 0.3280
sub_10:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5000 - F1: 0.3713
sub_11:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.7024 - F1: 0.7003
sub_10:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.5119 - F1: 0.3778
sub_12:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.6190 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5119 - F1: 0.3593
sub_10:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.4643 - F1: 0.4624
sub_11:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5238 - F1: 0.3842
sub_12:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.5476 - F1: 0.5074
sub_12:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.5000 - F1: 0.4151
sub_10:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7262 - F1: 0.7195
sub_11:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.7143 - F1: 0.7005
sub_10:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5714 - F1: 0.4750
sub_12:Test (Best Model) - Loss: 0.8778 - Accuracy: 0.4881 - F1: 0.3280
sub_12:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.5476 - F1: 0.4997
sub_11:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.4643 - F1: 0.4026
sub_10:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.4762 - F1: 0.3226
sub_10:Test (Best Model) - Loss: 0.7384 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.4881 - F1: 0.4466
sub_12:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.6071 - F1: 0.5354
sub_11:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5595 - F1: 0.5238
sub_12:Test (Best Model) - Loss: 0.9535 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5238 - F1: 0.4013
sub_13:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.5000 - F1: 0.3534
sub_14:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.5714 - F1: 0.5692
sub_13:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4881 - F1: 0.3280
sub_14:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.5119 - F1: 0.4645
sub_13:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.7738 - F1: 0.7699
sub_14:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.5476 - F1: 0.4911
sub_13:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.6667 - F1: 0.6506
sub_13:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.6071 - F1: 0.5753
sub_14:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.4643 - F1: 0.3665
sub_13:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5119 - F1: 0.3778
sub_14:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5357 - F1: 0.5341
sub_13:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.7381 - F1: 0.7375
sub_14:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.5119 - F1: 0.3778
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5714 - F1: 0.5260
sub_14:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.3810 - F1: 0.3512
sub_13:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.7500 - F1: 0.7483
sub_14:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5357 - F1: 0.4510
sub_13:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5595 - F1: 0.4791
sub_14:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4167 - F1: 0.4099
sub_13:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.8095 - F1: 0.8078
sub_13:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6071 - F1: 0.5690
sub_14:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4881 - F1: 0.4822
sub_14:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5238 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.7976 - F1: 0.7969
sub_13:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.6786 - F1: 0.6415
sub_13:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.5119 - F1: 0.3593

=== Summary Results ===

acc: 53.57 ± 3.61
F1: 45.88 ± 3.93
acc-in: 57.20 ± 2.68
F1-in: 50.36 ± 3.15
runing time: 976.47 seconds
