lr: 1e-05
sub_3:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.7432 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.4242 - F1: 0.2979
sub_2:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.7879 - F1: 0.7664
sub_3:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5938 - F1: 0.5135
sub_2:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.4242 - F1: 0.4046
sub_1:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.8750 - F1: 0.8745
sub_2:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.9820 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.9062 - F1: 0.9015
sub_2:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.3939 - F1: 0.3182
sub_1:Test (Best Model) - Loss: 0.7530 - Accuracy: 0.4375 - F1: 0.3043
sub_2:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.6023 - Accuracy: 0.9375 - F1: 0.9373
sub_1:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.9394 - F1: 0.9380
sub_2:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5000 - F1: 0.4182
sub_3:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5455 - F1: 0.4995
sub_1:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5758 - F1: 0.4653
sub_2:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.7879 - F1: 0.7871
sub_2:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.7879 - F1: 0.7871
sub_3:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4375 - F1: 0.3043
sub_1:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.8788 - F1: 0.8787
sub_2:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.7576 - F1: 0.7574
sub_3:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6061 - F1: 0.5662
sub_1:Test (Best Model) - Loss: 0.6622 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.7576 - F1: 0.7574
sub_1:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.8750 - F1: 0.8750
sub_3:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.8788 - F1: 0.8731
sub_2:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.5758 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.7698 - Accuracy: 0.4545 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.8750 - F1: 0.8704
sub_3:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.7879 - F1: 0.7664
sub_2:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.7879 - F1: 0.7664
sub_3:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.7576 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.8125 - F1: 0.8118
sub_3:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6061 - F1: 0.5815
sub_1:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5455 - F1: 0.3529
sub_1:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.9062 - F1: 0.9054
sub_6:Test (Best Model) - Loss: 0.8687 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.5152 - F1: 0.4261
sub_5:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5938 - F1: 0.5589
sub_4:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5152 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.9736 - Accuracy: 0.5000 - F1: 0.4182
sub_5:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.6562 - F1: 0.5594
sub_6:Test (Best Model) - Loss: 0.7391 - Accuracy: 0.4688 - F1: 0.3637
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6061 - F1: 0.6002
sub_5:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.8898 - Accuracy: 0.4688 - F1: 0.3976
sub_4:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6667 - F1: 0.6459
sub_6:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.4303 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7517 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.3926 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 0.7575 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.8788 - F1: 0.8731
sub_5:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4062 - F1: 0.3267
sub_4:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5455 - F1: 0.4995
sub_6:Test (Best Model) - Loss: 0.7391 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.8750 - F1: 0.8704
sub_6:Test (Best Model) - Loss: 0.7672 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.4545 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 0.8019 - Accuracy: 0.4242 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6562 - F1: 0.6390
sub_4:Test (Best Model) - Loss: 0.7613 - Accuracy: 0.4545 - F1: 0.4107
sub_6:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5758 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.4688 - F1: 0.3637
sub_4:Test (Best Model) - Loss: 0.7499 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 0.7488 - Accuracy: 0.3636 - F1: 0.2993
sub_4:Test (Best Model) - Loss: 0.9643 - Accuracy: 0.3939 - F1: 0.3182
sub_6:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.4545 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6562 - F1: 0.6390
sub_4:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.5758 - F1: 0.4225
sub_5:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.7500 - F1: 0.7229
sub_5:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.8750 - F1: 0.8750
sub_5:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.8750 - F1: 0.8745
sub_5:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5625 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.3750 - F1: 0.2727
sub_7:Test (Best Model) - Loss: 0.5461 - Accuracy: 0.9375 - F1: 0.9373
sub_9:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.3125 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.6202 - Accuracy: 0.9062 - F1: 0.9062
sub_9:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.3750 - F1: 0.2727
sub_7:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.9688 - F1: 0.9685
sub_9:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.4688 - F1: 0.3637
sub_8:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.3438 - F1: 0.2558
sub_9:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.5312 - F1: 0.4684
sub_7:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.8438 - F1: 0.8436
sub_9:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.6875 - F1: 0.6364
sub_7:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 0.5737 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.7394 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.5000 - F1: 0.4182
sub_7:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.3750 - F1: 0.2727
sub_7:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.9062 - F1: 0.9054
sub_7:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.8125 - F1: 0.8057
sub_8:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.9688 - F1: 0.9685
sub_7:Test (Best Model) - Loss: 0.7716 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6032 - Accuracy: 0.9062 - F1: 0.9054
sub_7:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.8438 - F1: 0.8359
sub_11:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.7226 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.4688 - F1: 0.3637
sub_11:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.3750 - F1: 0.3074
sub_11:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5000 - F1: 0.4459
sub_11:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.4848 - F1: 0.3718
sub_12:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6875 - F1: 0.6761
sub_10:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.9049 - Accuracy: 0.4688 - F1: 0.3637
sub_12:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5152 - F1: 0.4261
sub_12:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.5156 - Accuracy: 0.8125 - F1: 0.8125
sub_11:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5625 - F1: 0.5152
sub_12:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.8332 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.7879 - F1: 0.7847
sub_12:Test (Best Model) - Loss: 0.7482 - Accuracy: 0.4242 - F1: 0.2979
sub_11:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.9620 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7355 - Accuracy: 0.4242 - F1: 0.2979
sub_12:Test (Best Model) - Loss: 0.7206 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.7496 - Accuracy: 0.4848 - F1: 0.3718
sub_12:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4688 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 0.7359 - Accuracy: 0.4545 - F1: 0.3125
sub_12:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.4062 - F1: 0.2889
sub_10:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.4848 - F1: 0.3718
sub_10:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.6364 - F1: 0.5417
sub_14:Test (Best Model) - Loss: 0.9519 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.7919 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.9375 - F1: 0.9365
sub_14:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.7500 - F1: 0.7229
sub_14:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.7500 - F1: 0.7091
sub_14:Test (Best Model) - Loss: 0.7553 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.8485 - F1: 0.8485
sub_14:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.9091 - F1: 0.9060
sub_15:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.5413 - Accuracy: 0.8788 - F1: 0.8731
sub_15:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.8750 - F1: 0.8730
sub_14:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.7500 - F1: 0.7333
sub_13:Test (Best Model) - Loss: 0.5143 - Accuracy: 0.9697 - F1: 0.9692
sub_15:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.7812 - F1: 0.7810
sub_14:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5625 - F1: 0.5152
sub_13:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.8182 - F1: 0.8096
sub_14:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.4375 - F1: 0.3455
sub_13:Test (Best Model) - Loss: 1.8274 - Accuracy: 0.5938 - F1: 0.4340
sub_15:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5938 - F1: 0.5589
sub_13:Test (Best Model) - Loss: 0.7596 - Accuracy: 0.6562 - F1: 0.5594
sub_14:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 0.5929 - Accuracy: 0.7188 - F1: 0.6632
sub_15:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.7812 - F1: 0.7793
sub_14:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.9688 - F1: 0.9685
sub_13:Test (Best Model) - Loss: 0.9291 - Accuracy: 0.7188 - F1: 0.6811
sub_15:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 2.3945 - Accuracy: 0.5938 - F1: 0.4340
sub_15:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.4688 - F1: 0.4555
sub_15:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.5938 - F1: 0.4340
sub_16:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.9640 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5000 - F1: 0.4818
sub_18:Test (Best Model) - Loss: 0.5878 - Accuracy: 0.7576 - F1: 0.7381
sub_17:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.5455 - F1: 0.5171
sub_16:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5625 - F1: 0.5556
sub_18:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.7879 - F1: 0.7847
sub_17:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.6061 - F1: 0.5662
sub_16:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6061 - F1: 0.5926
sub_18:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.6970 - F1: 0.6726
sub_18:Test (Best Model) - Loss: 0.8636 - Accuracy: 0.4848 - F1: 0.3718
sub_17:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4688 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5152 - F1: 0.4261
sub_18:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.7188 - F1: 0.7117
sub_17:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6061 - F1: 0.5662
sub_18:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.8750 - F1: 0.8667
sub_17:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.4242 - F1: 0.2979
sub_16:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5625 - F1: 0.5608
sub_18:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.7879 - F1: 0.7847
sub_18:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.7812 - F1: 0.7793
sub_17:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.5938 - F1: 0.5135
sub_16:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.4459
sub_17:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5625 - F1: 0.5333
sub_18:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.8750 - F1: 0.8704
sub_16:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.6875 - F1: 0.6537
sub_17:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.7812 - F1: 0.7703
sub_17:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5938 - F1: 0.5901
sub_17:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5000 - F1: 0.4667
sub_18:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.5000 - F1: 0.5000
sub_17:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 0.7590 - Accuracy: 0.7188 - F1: 0.6946
sub_19:Test (Best Model) - Loss: 0.7676 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.5000 - F1: 0.4182
sub_20:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.7953 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 0.5693 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.7500 - F1: 0.7500
sub_19:Test (Best Model) - Loss: 0.7492 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.5922 - Accuracy: 0.8438 - F1: 0.8303
sub_20:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 0.7245 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.5312 - F1: 0.3992
sub_21:Test (Best Model) - Loss: 0.5757 - Accuracy: 0.8125 - F1: 0.7922
sub_20:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.8438 - F1: 0.8424
sub_19:Test (Best Model) - Loss: 0.8759 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 0.7873 - Accuracy: 0.7500 - F1: 0.7460
sub_19:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.4688 - F1: 0.3637
sub_20:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.8125 - F1: 0.8125
sub_21:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.7188 - F1: 0.7185
sub_20:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.8438 - F1: 0.8303
sub_19:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.7188 - F1: 0.7117
sub_21:Test (Best Model) - Loss: 0.8124 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.8125 - F1: 0.8118
sub_21:Test (Best Model) - Loss: 0.8334 - Accuracy: 0.7500 - F1: 0.7409
sub_19:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.7449 - Accuracy: 0.4848 - F1: 0.4328
sub_19:Test (Best Model) - Loss: 0.5841 - Accuracy: 0.5312 - F1: 0.4684
sub_21:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.5000 - F1: 0.4921
sub_20:Test (Best Model) - Loss: 0.7855 - Accuracy: 0.4545 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.5837 - Accuracy: 0.8438 - F1: 0.8436
sub_20:Test (Best Model) - Loss: 0.8289 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.5340 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.6667 - F1: 0.5935
sub_21:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.7188 - F1: 0.7117
sub_19:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.4688 - F1: 0.4555
sub_22:Test (Best Model) - Loss: 0.7682 - Accuracy: 0.5312 - F1: 0.4684
sub_23:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4545 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.7500 - F1: 0.7490
sub_22:Test (Best Model) - Loss: 0.7896 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5152 - F1: 0.5147
sub_22:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.3939 - F1: 0.3654
sub_22:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.8610 - Accuracy: 0.4375 - F1: 0.3043
sub_23:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.7273 - F1: 0.6997
sub_23:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.4995
sub_24:Test (Best Model) - Loss: 0.7208 - Accuracy: 0.6875 - F1: 0.6135
sub_23:Test (Best Model) - Loss: 0.8752 - Accuracy: 0.3750 - F1: 0.3333
sub_22:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.7576 - F1: 0.7556
sub_24:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.8438 - F1: 0.8424
sub_23:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.7426 - Accuracy: 0.3750 - F1: 0.3074
sub_22:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6061 - F1: 0.6061
sub_24:Test (Best Model) - Loss: 0.5799 - Accuracy: 0.7812 - F1: 0.7625
sub_23:Test (Best Model) - Loss: 0.8008 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.9394 - F1: 0.9389
sub_23:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.4688 - F1: 0.4231
sub_24:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6970 - F1: 0.6967
sub_23:Test (Best Model) - Loss: 0.7520 - Accuracy: 0.4848 - F1: 0.3718
sub_24:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.9688 - F1: 0.9685
sub_22:Test (Best Model) - Loss: 0.8238 - Accuracy: 0.4062 - F1: 0.2889
sub_23:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.7273 - F1: 0.7232
sub_23:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.7273 - F1: 0.7179
sub_24:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.9375 - F1: 0.9365
sub_22:Test (Best Model) - Loss: 0.7495 - Accuracy: 0.3750 - F1: 0.3333
sub_23:Test (Best Model) - Loss: 0.7980 - Accuracy: 0.4242 - F1: 0.2979
sub_24:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.7664 - Accuracy: 0.4062 - F1: 0.2889
sub_23:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 0.8800 - Accuracy: 0.3438 - F1: 0.2558
sub_24:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.7812 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.5938 - F1: 0.4340
sub_24:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.7812 - F1: 0.7625
sub_24:Test (Best Model) - Loss: 0.5492 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.6667 - F1: 0.6654
sub_25:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.7879 - F1: 0.7871
sub_27:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.5455 - F1: 0.5171
sub_26:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5758 - F1: 0.5227
sub_25:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.8182 - F1: 0.8167
sub_27:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.6061 - F1: 0.5662
sub_26:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.7576 - F1: 0.7462
sub_27:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6061 - F1: 0.5926
sub_25:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.4545 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.4848 - F1: 0.3718
sub_27:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5152 - F1: 0.4261
sub_26:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6562 - F1: 0.6532
sub_25:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6250 - F1: 0.6000
sub_27:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6061 - F1: 0.5662
sub_26:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6875 - F1: 0.6135
sub_27:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.7500 - F1: 0.7229
sub_27:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.7879 - F1: 0.7847
sub_25:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5000 - F1: 0.4182
sub_26:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5938 - F1: 0.5934
sub_27:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.8438 - F1: 0.8436
sub_26:Test (Best Model) - Loss: 0.7742 - Accuracy: 0.6562 - F1: 0.6532
sub_27:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.3750 - F1: 0.3651
sub_25:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.7812 - F1: 0.7793
sub_25:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.8438 - F1: 0.8436
sub_27:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5836
sub_26:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.7500 - F1: 0.7490
sub_27:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5000 - F1: 0.4667
sub_25:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.8438 - F1: 0.8424
sub_26:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.7188 - F1: 0.7117
sub_25:Test (Best Model) - Loss: 0.7811 - Accuracy: 0.4062 - F1: 0.2889
sub_27:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5938 - F1: 0.5733
sub_26:Test (Best Model) - Loss: 0.8842 - Accuracy: 0.4062 - F1: 0.3552
sub_25:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.7500 - F1: 0.7091
sub_28:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.8125 - F1: 0.8057
sub_29:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6250 - F1: 0.6113
sub_29:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.7188 - F1: 0.7117
sub_29:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.4688 - F1: 0.3637
sub_28:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.8750 - F1: 0.8745
sub_29:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.7378 - Accuracy: 0.4848 - F1: 0.3718
sub_28:Test (Best Model) - Loss: 0.5740 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7459 - Accuracy: 0.7879 - F1: 0.7847
sub_29:Test (Best Model) - Loss: 0.7774 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.4686 - Accuracy: 0.6562 - F1: 0.5594
sub_29:Test (Best Model) - Loss: 0.7343 - Accuracy: 0.4545 - F1: 0.3125
sub_28:Test (Best Model) - Loss: 0.4459 - Accuracy: 0.6562 - F1: 0.5594
sub_29:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.9091 - F1: 0.9077
sub_28:Test (Best Model) - Loss: 1.2898 - Accuracy: 0.3750 - F1: 0.2727
sub_28:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.5625 - F1: 0.3600

=== Summary Results ===

acc: 61.48 ± 9.90
F1: 55.43 ± 12.11
acc-in: 66.30 ± 9.79
F1-in: 61.32 ± 11.58
runing time: 1139.08 seconds
