lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.3961 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.3975 - Accuracy: 0.9062 - F1: 0.9054
sub_1:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8438 - F1: 0.8398
sub_1:Test (Best Model) - Loss: 0.3600 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3542 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3770 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.3476 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.3277 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.4131 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.3097 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.2638 - Accuracy: 0.9062 - F1: 0.9054
sub_1:Test (Best Model) - Loss: 0.2426 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.2762 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.3050 - Accuracy: 0.8438 - F1: 0.8398
sub_2:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.7273 - F1: 0.7179
sub_2:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.7273 - F1: 0.7179
sub_2:Test (Best Model) - Loss: 0.6260 - Accuracy: 0.7273 - F1: 0.7232
sub_2:Test (Best Model) - Loss: 0.6019 - Accuracy: 0.6970 - F1: 0.6591
sub_2:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.7879 - F1: 0.7806
sub_2:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5625 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.6562 - F1: 0.6559
sub_2:Test (Best Model) - Loss: 0.5749 - Accuracy: 0.7500 - F1: 0.7409
sub_2:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.7188 - F1: 0.6811
sub_2:Test (Best Model) - Loss: 0.5164 - Accuracy: 0.8485 - F1: 0.8462
sub_2:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.6061 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.7273 - F1: 0.7232
sub_2:Test (Best Model) - Loss: 0.6068 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.6667 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.6250 - F1: 0.6235
sub_3:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.5455 - F1: 0.5171
sub_3:Test (Best Model) - Loss: 0.7383 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5758 - F1: 0.4225
sub_3:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.6364 - F1: 0.5909
sub_3:Test (Best Model) - Loss: 0.8575 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.7732 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 0.7945 - Accuracy: 0.4848 - F1: 0.4527
sub_3:Test (Best Model) - Loss: 0.8133 - Accuracy: 0.5758 - F1: 0.4978
sub_3:Test (Best Model) - Loss: 0.8818 - Accuracy: 0.5152 - F1: 0.5038
sub_4:Test (Best Model) - Loss: 0.4547 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.3914 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 0.3877 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3388 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3729 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4565 - Accuracy: 0.6970 - F1: 0.6827
sub_4:Test (Best Model) - Loss: 0.4657 - Accuracy: 0.8485 - F1: 0.8462
sub_4:Test (Best Model) - Loss: 0.4164 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.5284 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.5101 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.5658 - Accuracy: 0.6364 - F1: 0.6360
sub_4:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.8485 - F1: 0.8485
sub_4:Test (Best Model) - Loss: 0.4745 - Accuracy: 0.8485 - F1: 0.8462
sub_4:Test (Best Model) - Loss: 0.4745 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.4110 - Accuracy: 0.8182 - F1: 0.8167
sub_5:Test (Best Model) - Loss: 0.7887 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.7672 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.4688 - F1: 0.3637
sub_5:Test (Best Model) - Loss: 0.6028 - Accuracy: 0.5000 - F1: 0.4182
sub_5:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.5265 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.5370 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6026 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6007 - Accuracy: 0.6250 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.6875 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.7188 - F1: 0.7117
sub_6:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.7812 - F1: 0.7703
sub_6:Test (Best Model) - Loss: 0.5243 - Accuracy: 0.7812 - F1: 0.7625
sub_6:Test (Best Model) - Loss: 0.9107 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 0.9312 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.9078 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.9506 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.8932 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6061 - F1: 0.5460
sub_6:Test (Best Model) - Loss: 0.5846 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 0.5388 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.6061 - F1: 0.5196
sub_7:Test (Best Model) - Loss: 0.6001 - Accuracy: 0.6875 - F1: 0.6761
sub_7:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6250 - F1: 0.5844
sub_7:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.5000 - F1: 0.4667
sub_7:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7500 - F1: 0.7490
sub_7:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.6562 - F1: 0.6532
sub_7:Test (Best Model) - Loss: 0.7528 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.8125 - F1: 0.8118
sub_7:Test (Best Model) - Loss: 0.5475 - Accuracy: 0.7812 - F1: 0.7758
sub_8:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.7812 - F1: 0.7758
sub_8:Test (Best Model) - Loss: 0.5663 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.5398 - Accuracy: 0.7500 - F1: 0.7229
sub_8:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 0.5144 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.5645 - Accuracy: 0.7188 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.5038 - Accuracy: 0.8438 - F1: 0.8359
sub_8:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.4848 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.2682 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3411 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.2531 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.3507 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.3408 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 0.4416 - Accuracy: 0.8438 - F1: 0.8424
sub_9:Test (Best Model) - Loss: 0.5617 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.3952 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4371 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.5680 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.3952 - Accuracy: 0.8438 - F1: 0.8398
sub_9:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.4863 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.1973 - Accuracy: 0.9062 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.6250 - F1: 0.5844
sub_10:Test (Best Model) - Loss: 0.5208 - Accuracy: 0.7500 - F1: 0.7460
sub_10:Test (Best Model) - Loss: 0.5503 - Accuracy: 0.6875 - F1: 0.6761
sub_10:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.7188 - F1: 0.6811
sub_10:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.5625 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6250 - F1: 0.6250
sub_10:Test (Best Model) - Loss: 0.5982 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4375 - F1: 0.4286
sub_10:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.6667 - F1: 0.6553
sub_10:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.5758 - F1: 0.5558
sub_11:Test (Best Model) - Loss: 0.9913 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.9162 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 0.9609 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.7856 - Accuracy: 0.6061 - F1: 0.5926
sub_11:Test (Best Model) - Loss: 0.8845 - Accuracy: 0.4242 - F1: 0.3660
sub_11:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5455 - F1: 0.4058
sub_11:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.5152 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 0.5807 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 0.8074 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 0.7298 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.7307 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.4435 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.3828 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.3802 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.3842 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.3784 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.4209 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.4144 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.5091 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.5200 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.4357 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.5485 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.7500 - F1: 0.7409
sub_12:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.5444 - Accuracy: 0.8125 - F1: 0.8000
sub_13:Test (Best Model) - Loss: 0.3420 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.4032 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3288 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.3878 - Accuracy: 0.7812 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.3608 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.4331 - Accuracy: 0.8788 - F1: 0.8787
sub_13:Test (Best Model) - Loss: 0.4503 - Accuracy: 0.8485 - F1: 0.8485
sub_13:Test (Best Model) - Loss: 0.4931 - Accuracy: 0.7273 - F1: 0.7179
sub_13:Test (Best Model) - Loss: 0.4861 - Accuracy: 0.8182 - F1: 0.8167
sub_13:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.4753 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.4538 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.4134 - Accuracy: 0.8125 - F1: 0.8000
sub_13:Test (Best Model) - Loss: 0.4657 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.4770 - Accuracy: 0.7812 - F1: 0.7793
sub_14:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 0.4119 - Accuracy: 0.8750 - F1: 0.8730
sub_14:Test (Best Model) - Loss: 0.4077 - Accuracy: 0.8438 - F1: 0.8303
sub_14:Test (Best Model) - Loss: 0.4414 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.3916 - Accuracy: 0.8750 - F1: 0.8704
sub_14:Test (Best Model) - Loss: 0.4025 - Accuracy: 0.7500 - F1: 0.7229
sub_14:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.4725 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.4597 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.3886 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.5792 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.4886 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.5663 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.5207 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.4704 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.4209 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.3943 - Accuracy: 0.8750 - F1: 0.8745
sub_15:Test (Best Model) - Loss: 0.4428 - Accuracy: 0.7188 - F1: 0.6811
sub_15:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.5545 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.5162 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6093 - Accuracy: 0.7812 - F1: 0.7703
sub_16:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6250 - F1: 0.5844
sub_16:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.7499 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6562 - F1: 0.6102
sub_16:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.7457 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.6970 - F1: 0.6726
sub_17:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.6061 - F1: 0.6002
sub_17:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.6970 - F1: 0.6898
sub_17:Test (Best Model) - Loss: 0.5151 - Accuracy: 0.7273 - F1: 0.6857
sub_17:Test (Best Model) - Loss: 0.6103 - Accuracy: 0.6667 - F1: 0.6159
sub_17:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.7380 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 0.7779 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.5938 - F1: 0.5934
sub_17:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.6562 - F1: 0.6476
sub_17:Test (Best Model) - Loss: 0.8258 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6562 - F1: 0.6267
sub_17:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.5938 - F1: 0.5901
sub_18:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.7879 - F1: 0.7871
sub_18:Test (Best Model) - Loss: 0.4702 - Accuracy: 0.8182 - F1: 0.8180
sub_18:Test (Best Model) - Loss: 0.4524 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.4575 - Accuracy: 0.8182 - F1: 0.8096
sub_18:Test (Best Model) - Loss: 0.3920 - Accuracy: 0.8788 - F1: 0.8778
sub_18:Test (Best Model) - Loss: 0.4714 - Accuracy: 0.8750 - F1: 0.8704
sub_18:Test (Best Model) - Loss: 0.4594 - Accuracy: 0.8438 - F1: 0.8424
sub_18:Test (Best Model) - Loss: 0.4345 - Accuracy: 0.9062 - F1: 0.9054
sub_18:Test (Best Model) - Loss: 0.4395 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.4189 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.3861 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.4293 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.3956 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.3648 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.3683 - Accuracy: 0.8750 - F1: 0.8730
sub_19:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.5634 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.5331 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.5244 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.7188 - F1: 0.6632
sub_19:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.5625 - F1: 0.5625
sub_19:Test (Best Model) - Loss: 0.6314 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6159 - Accuracy: 0.7500 - F1: 0.7409
sub_19:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.5408 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 0.4493 - Accuracy: 0.8438 - F1: 0.8398
sub_20:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.5760 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.5788 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7188 - F1: 0.6811
sub_20:Test (Best Model) - Loss: 0.4735 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.6061 - F1: 0.5926
sub_20:Test (Best Model) - Loss: 0.7639 - Accuracy: 0.6970 - F1: 0.6726
sub_20:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6364 - F1: 0.6333
sub_20:Test (Best Model) - Loss: 0.7996 - Accuracy: 0.6970 - F1: 0.6726
sub_20:Test (Best Model) - Loss: 0.5660 - Accuracy: 0.7273 - F1: 0.7179
sub_21:Test (Best Model) - Loss: 0.7755 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.8364 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.8344 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.8007 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.5938 - F1: 0.5135
sub_21:Test (Best Model) - Loss: 0.8850 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.8010 - Accuracy: 0.5000 - F1: 0.4459
sub_21:Test (Best Model) - Loss: 0.8247 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.8596 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.7695 - Accuracy: 0.5625 - F1: 0.5556
sub_21:Test (Best Model) - Loss: 0.8324 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 0.8175 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.9912 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.9795 - Accuracy: 0.3750 - F1: 0.3074
sub_21:Test (Best Model) - Loss: 0.8020 - Accuracy: 0.5312 - F1: 0.4684
sub_22:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4465 - Accuracy: 0.7500 - F1: 0.7333
sub_22:Test (Best Model) - Loss: 0.4336 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.4702 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.5809 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5425 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.4960 - Accuracy: 0.8182 - F1: 0.8036
sub_22:Test (Best Model) - Loss: 0.6129 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 0.5380 - Accuracy: 0.8438 - F1: 0.8398
sub_22:Test (Best Model) - Loss: 0.5769 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.5199 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.4802 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4623 - Accuracy: 0.8750 - F1: 0.8730
sub_23:Test (Best Model) - Loss: 0.4024 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.3889 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4080 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4462 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.7188 - F1: 0.7046
sub_23:Test (Best Model) - Loss: 0.4694 - Accuracy: 0.8438 - F1: 0.8424
sub_23:Test (Best Model) - Loss: 0.4715 - Accuracy: 0.8125 - F1: 0.8095
sub_23:Test (Best Model) - Loss: 0.4822 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.3380 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.3222 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.3785 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.3784 - Accuracy: 0.7879 - F1: 0.7664
sub_24:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.8178 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.7847 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.7262 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 0.8094 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.8147 - Accuracy: 0.4375 - F1: 0.4000
sub_24:Test (Best Model) - Loss: 0.7477 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 0.8395 - Accuracy: 0.5152 - F1: 0.4261
sub_25:Test (Best Model) - Loss: 0.7652 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 0.7503 - Accuracy: 0.5152 - F1: 0.5038
sub_25:Test (Best Model) - Loss: 0.8379 - Accuracy: 0.4848 - F1: 0.3718
sub_25:Test (Best Model) - Loss: 0.7875 - Accuracy: 0.4242 - F1: 0.3883
sub_25:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.6250 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 0.5941 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6562 - F1: 0.5594
sub_25:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.7188 - F1: 0.6946
sub_25:Test (Best Model) - Loss: 0.5761 - Accuracy: 0.6562 - F1: 0.5594
sub_25:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.6250 - F1: 0.5636
sub_26:Test (Best Model) - Loss: 0.3545 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.3763 - Accuracy: 0.8788 - F1: 0.8731
sub_26:Test (Best Model) - Loss: 0.3198 - Accuracy: 0.8485 - F1: 0.8390
sub_26:Test (Best Model) - Loss: 0.3791 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.2916 - Accuracy: 0.9394 - F1: 0.9380
sub_26:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.4705 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.4310 - Accuracy: 0.8750 - F1: 0.8704
sub_26:Test (Best Model) - Loss: 0.4436 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 0.2746 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.3009 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.3362 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.3177 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.2585 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.6970 - F1: 0.6726
sub_27:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.6061 - F1: 0.6002
sub_27:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.6970 - F1: 0.6898
sub_27:Test (Best Model) - Loss: 0.5151 - Accuracy: 0.7273 - F1: 0.6857
sub_27:Test (Best Model) - Loss: 0.6103 - Accuracy: 0.6667 - F1: 0.6159
sub_27:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.7380 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 0.7779 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.5938 - F1: 0.5934
sub_27:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.6562 - F1: 0.6476
sub_27:Test (Best Model) - Loss: 0.8258 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6562 - F1: 0.6267
sub_27:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.5213 - Accuracy: 0.7812 - F1: 0.7703
sub_28:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.7188 - F1: 0.7046
sub_28:Test (Best Model) - Loss: 0.7573 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.9929 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 0.8097 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 1.1031 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 1.1935 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.8621 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.8252 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.8377 - Accuracy: 0.2500 - F1: 0.2471
sub_28:Test (Best Model) - Loss: 0.8289 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.7825 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.8453 - Accuracy: 0.4375 - F1: 0.3455
sub_29:Test (Best Model) - Loss: 0.2457 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.2672 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.3103 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.3385 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3072 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.1778 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.1832 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1637 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.1624 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.1626 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.2186 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.2004 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.1825 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2013 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.1976 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 69.34 ± 11.71
F1: 67.09 ± 12.85
acc-in: 75.47 ± 8.27
F1-in: 73.28 ± 8.87
