lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6250 - F1: 0.6000
sub_1:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.5938 - F1: 0.5733
sub_1:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.5625 - F1: 0.5466
sub_1:Test (Best Model) - Loss: 0.6024 - Accuracy: 0.6562 - F1: 0.5594
sub_1:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7188 - F1: 0.6946
sub_1:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6667 - F1: 0.6330
sub_1:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.5758 - F1: 0.5658
sub_1:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.6667 - F1: 0.5935
sub_1:Test (Best Model) - Loss: 0.5917 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.8438 - F1: 0.8398
sub_1:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.8125 - F1: 0.8118
sub_1:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.6667 - F1: 0.6330
sub_2:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6667 - F1: 0.6459
sub_2:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5938 - F1: 0.5135
sub_2:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5312 - F1: 0.5077
sub_2:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5938 - F1: 0.5901
sub_2:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6562 - F1: 0.6102
sub_2:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6250 - F1: 0.6113
sub_2:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6364 - F1: 0.6360
sub_2:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.6061 - F1: 0.6061
sub_2:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6364 - F1: 0.6360
sub_2:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5312 - F1: 0.5308
sub_3:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5312 - F1: 0.5308
sub_3:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4688 - F1: 0.4555
sub_3:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5758 - F1: 0.4653
sub_3:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.3636 - F1: 0.3636
sub_3:Test (Best Model) - Loss: 0.7630 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 0.7564 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 0.7538 - Accuracy: 0.4848 - F1: 0.4772
sub_4:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6061 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.5758 - F1: 0.4978
sub_4:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.6970 - F1: 0.6413
sub_4:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6364 - F1: 0.6278
sub_4:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6364 - F1: 0.6360
sub_4:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5152 - F1: 0.4261
sub_4:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6061 - F1: 0.5926
sub_4:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6061 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.6364 - F1: 0.6278
sub_5:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 0.7317 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.7317 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.4375 - F1: 0.3455
sub_5:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4375 - F1: 0.3455
sub_5:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4062 - F1: 0.3552
sub_5:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.4688 - F1: 0.4421
sub_6:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6250 - F1: 0.6000
sub_6:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.5625 - F1: 0.5556
sub_6:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6562 - F1: 0.5883
sub_6:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 0.7725 - Accuracy: 0.4242 - F1: 0.3660
sub_6:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.4242 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 0.7683 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.7803 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.7500 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5758 - F1: 0.5658
sub_6:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.5758 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5455 - F1: 0.5299
sub_6:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6667 - F1: 0.6330
sub_6:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4545 - F1: 0.4417
sub_7:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5312 - F1: 0.4910
sub_7:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5938 - F1: 0.5393
sub_7:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.7340 - Accuracy: 0.2812 - F1: 0.2749
sub_7:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.5000 - F1: 0.4667
sub_7:Test (Best Model) - Loss: 0.7286 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.5625
sub_8:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4688 - F1: 0.4421
sub_8:Test (Best Model) - Loss: 0.7257 - Accuracy: 0.4062 - F1: 0.3764
sub_8:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.6250 - F1: 0.6235
sub_8:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.4921
sub_8:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.7338 - Accuracy: 0.3750 - F1: 0.3725
sub_8:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5625 - F1: 0.5466
sub_8:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5312 - F1: 0.5308
sub_9:Test (Best Model) - Loss: 0.5785 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 0.5969 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6875 - F1: 0.6364
sub_9:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.6875 - F1: 0.6537
sub_9:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.4062 - F1: 0.3764
sub_9:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6250 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.5625 - F1: 0.5556
sub_9:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.4688 - F1: 0.4421
sub_9:Test (Best Model) - Loss: 0.5762 - Accuracy: 0.7500 - F1: 0.7490
sub_10:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6562 - F1: 0.6532
sub_10:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5000 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.4688 - F1: 0.4555
sub_10:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5312 - F1: 0.4910
sub_10:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4062 - F1: 0.3914
sub_10:Test (Best Model) - Loss: 0.7232 - Accuracy: 0.4242 - F1: 0.4221
sub_10:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.5152 - F1: 0.4923
sub_10:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5152 - F1: 0.4762
sub_10:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5455 - F1: 0.5387
sub_10:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.7597 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.7512 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.7342 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.7252 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5152 - F1: 0.4545
sub_11:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.4545 - F1: 0.3864
sub_11:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.3939 - F1: 0.3452
sub_11:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5152 - F1: 0.4762
sub_12:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6562 - F1: 0.6476
sub_12:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6250 - F1: 0.5844
sub_12:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6364 - F1: 0.6192
sub_12:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6364 - F1: 0.6192
sub_12:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6061 - F1: 0.5196
sub_12:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5455 - F1: 0.4058
sub_12:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.6970 - F1: 0.6726
sub_12:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5312 - F1: 0.5271
sub_12:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.5000 - F1: 0.4980
sub_12:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.5000 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6250 - F1: 0.6113
sub_13:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.6875 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7188 - F1: 0.7185
sub_13:Test (Best Model) - Loss: 0.6054 - Accuracy: 0.6875 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6061 - F1: 0.6061
sub_13:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.6667 - F1: 0.6459
sub_13:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.6364 - F1: 0.6333
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.4848 - F1: 0.4829
sub_13:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.4848 - F1: 0.4848
sub_13:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6250 - F1: 0.6235
sub_13:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.6250 - F1: 0.6235
sub_14:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5625 - F1: 0.5608
sub_14:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5312 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.4688 - F1: 0.4682
sub_14:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6250 - F1: 0.6250
sub_14:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.6562 - F1: 0.6390
sub_14:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.7296 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.7290 - Accuracy: 0.4062 - F1: 0.4010
sub_14:Test (Best Model) - Loss: 0.7551 - Accuracy: 0.4688 - F1: 0.4640
sub_14:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.6562 - F1: 0.6267
sub_15:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.6562 - F1: 0.6267
sub_15:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.6875 - F1: 0.6667
sub_16:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4688 - F1: 0.3976
sub_16:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5312 - F1: 0.4910
sub_16:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4062 - F1: 0.3764
sub_17:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5455 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.5758 - F1: 0.5754
sub_17:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.3939 - F1: 0.3452
sub_17:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.5312 - F1: 0.5077
sub_17:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.5000 - F1: 0.4921
sub_17:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 0.7179 - Accuracy: 0.4375 - F1: 0.4286
sub_18:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.5455 - F1: 0.5438
sub_18:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.5455 - F1: 0.5171
sub_18:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5455 - F1: 0.5387
sub_18:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.6667 - F1: 0.6553
sub_18:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5000 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6250 - F1: 0.6190
sub_18:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.5938 - F1: 0.5901
sub_18:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.6250 - F1: 0.6113
sub_18:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6562 - F1: 0.6390
sub_18:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.5938 - F1: 0.5589
sub_18:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5000 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4688 - F1: 0.4231
sub_19:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5000 - F1: 0.4667
sub_19:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4375 - F1: 0.3455
sub_19:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4688 - F1: 0.4421
sub_19:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.7188 - F1: 0.6946
sub_19:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.5938 - F1: 0.5733
sub_20:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5938 - F1: 0.5393
sub_20:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6875 - F1: 0.6825
sub_20:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.5938 - F1: 0.5733
sub_20:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.5625 - F1: 0.5556
sub_20:Test (Best Model) - Loss: 0.7302 - Accuracy: 0.5455 - F1: 0.5438
sub_20:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.6061 - F1: 0.6002
sub_20:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6364 - F1: 0.6278
sub_21:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7393 - Accuracy: 0.3750 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.3438 - F1: 0.3273
sub_21:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7380 - Accuracy: 0.3438 - F1: 0.3273
sub_21:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.7440 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.5312 - F1: 0.4386
sub_21:Test (Best Model) - Loss: 0.7231 - Accuracy: 0.4375 - F1: 0.4375
sub_21:Test (Best Model) - Loss: 0.7312 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 0.7646 - Accuracy: 0.2812 - F1: 0.2749
sub_21:Test (Best Model) - Loss: 0.7355 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.4688 - F1: 0.4421
sub_22:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.6562 - F1: 0.6532
sub_22:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6250 - F1: 0.5844
sub_22:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6562 - F1: 0.6559
sub_22:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.5455 - F1: 0.4457
sub_22:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5758 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5758 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.6061 - F1: 0.5815
sub_22:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5625 - F1: 0.5556
sub_22:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4688 - F1: 0.4640
sub_22:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.4589
sub_22:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.5556
sub_23:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.5758 - F1: 0.4978
sub_23:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6364 - F1: 0.5696
sub_23:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6061 - F1: 0.5815
sub_23:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.5758 - F1: 0.4653
sub_23:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.6970 - F1: 0.6827
sub_23:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5625 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6562 - F1: 0.6390
sub_23:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.5455 - F1: 0.5299
sub_23:Test (Best Model) - Loss: 0.6314 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.6085 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6364 - F1: 0.5417
sub_23:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.6667 - F1: 0.6159
sub_24:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.6562 - F1: 0.6559
sub_24:Test (Best Model) - Loss: 0.7583 - Accuracy: 0.4062 - F1: 0.4010
sub_24:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.4375 - F1: 0.4170
sub_24:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7127 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.7212 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.5312 - F1: 0.5308
sub_25:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.4545 - F1: 0.4417
sub_25:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.4848 - F1: 0.4848
sub_25:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.3636 - F1: 0.2667
sub_25:Test (Best Model) - Loss: 0.7283 - Accuracy: 0.5152 - F1: 0.5147
sub_25:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.5466
sub_25:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6875 - F1: 0.6863
sub_25:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5312 - F1: 0.3992
sub_25:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.7812 - F1: 0.7625
sub_25:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.5625 - F1: 0.4909
sub_25:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.5625 - F1: 0.4909
sub_25:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.6364 - F1: 0.6278
sub_26:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6061 - F1: 0.5662
sub_26:Test (Best Model) - Loss: 0.6295 - Accuracy: 0.6667 - F1: 0.6459
sub_26:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6364 - F1: 0.5909
sub_26:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.6364 - F1: 0.6192
sub_26:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.6250 - F1: 0.6250
sub_26:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.7188 - F1: 0.7046
sub_26:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5800 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.5866 - Accuracy: 0.7500 - F1: 0.7229
sub_26:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.6875 - F1: 0.6667
sub_26:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.7500 - F1: 0.7229
sub_26:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.7812 - F1: 0.7758
sub_27:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5455 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4242 - F1: 0.4221
sub_27:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.4242 - F1: 0.4221
sub_27:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.5758 - F1: 0.5754
sub_27:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.3939 - F1: 0.3452
sub_27:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.5312 - F1: 0.5077
sub_27:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.5000 - F1: 0.4921
sub_27:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5000 - F1: 0.4667
sub_27:Test (Best Model) - Loss: 0.7179 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6250 - F1: 0.6250
sub_28:Test (Best Model) - Loss: 0.7206 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.5312 - F1: 0.4684
sub_28:Test (Best Model) - Loss: 0.7449 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 0.7455 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 0.8103 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.4688 - F1: 0.4231
sub_28:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.7121 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4688 - F1: 0.4231
sub_29:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.7500 - F1: 0.7460
sub_29:Test (Best Model) - Loss: 0.5838 - Accuracy: 0.6875 - F1: 0.6761
sub_29:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.7500 - F1: 0.7229
sub_29:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.8125 - F1: 0.8000
sub_29:Test (Best Model) - Loss: 0.5758 - Accuracy: 0.6562 - F1: 0.6559
sub_29:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.7812 - F1: 0.7758
sub_29:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.7812 - F1: 0.7758
sub_29:Test (Best Model) - Loss: 0.5553 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.5436 - Accuracy: 0.8485 - F1: 0.8462
sub_29:Test (Best Model) - Loss: 0.5754 - Accuracy: 0.7273 - F1: 0.7179
sub_29:Test (Best Model) - Loss: 0.5898 - Accuracy: 0.7273 - F1: 0.7263
sub_29:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.7879 - F1: 0.7871

=== Summary Results ===

acc: 58.00 ± 7.45
F1: 55.78 ± 7.66
acc-in: 64.98 ± 5.58
F1-in: 62.84 ± 5.78
