lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.6875 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5938 - F1: 0.5901
sub_1:Test (Best Model) - Loss: 0.5996 - Accuracy: 0.7188 - F1: 0.6632
sub_1:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.7879 - F1: 0.7847
sub_1:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.6364 - F1: 0.5696
sub_1:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7879 - F1: 0.7746
sub_1:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.6562 - F1: 0.6532
sub_1:Test (Best Model) - Loss: 0.5996 - Accuracy: 0.8750 - F1: 0.8745
sub_1:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.6875 - F1: 0.6667
sub_1:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6562 - F1: 0.6476
sub_1:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.8438 - F1: 0.8436
sub_2:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.6667 - F1: 0.6459
sub_2:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.4848 - F1: 0.4672
sub_2:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6061 - F1: 0.5460
sub_2:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4375 - F1: 0.4170
sub_2:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5312 - F1: 0.5195
sub_2:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5625 - F1: 0.5333
sub_2:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.5312 - F1: 0.5195
sub_2:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.4545 - F1: 0.4540
sub_2:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4242 - F1: 0.4157
sub_2:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.5000 - F1: 0.5000
sub_3:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5625 - F1: 0.5333
sub_3:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5000 - F1: 0.4921
sub_3:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5152 - F1: 0.4545
sub_3:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.4107
sub_3:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.5455 - F1: 0.5455
sub_3:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.4242 - F1: 0.4242
sub_4:Test (Best Model) - Loss: 0.6126 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.5527 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5704 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.7879 - F1: 0.7847
sub_4:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.5152 - F1: 0.5038
sub_4:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.4545 - F1: 0.4107
sub_4:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4545 - F1: 0.4540
sub_4:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.6364 - F1: 0.6333
sub_5:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.7169 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.7188 - F1: 0.7185
sub_5:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.4375 - F1: 0.4286
sub_5:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.4688 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.6875 - F1: 0.6875
sub_5:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5938 - F1: 0.5733
sub_6:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5000 - F1: 0.4921
sub_6:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.5312 - F1: 0.4910
sub_6:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5938 - F1: 0.5393
sub_6:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 0.7631 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 0.7377 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.7243 - Accuracy: 0.4242 - F1: 0.3365
sub_6:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5152 - F1: 0.5147
sub_6:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.5152 - F1: 0.5147
sub_6:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.6061 - F1: 0.5926
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6667 - F1: 0.6654
sub_6:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5758 - F1: 0.5722
sub_6:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.4545 - F1: 0.4500
sub_7:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5625 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.7306 - Accuracy: 0.2812 - F1: 0.2749
sub_7:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6250 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.3438 - F1: 0.3431
sub_8:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5938 - F1: 0.5135
sub_8:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.7232 - Accuracy: 0.3438 - F1: 0.2874
sub_8:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.7812 - F1: 0.7703
sub_8:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7188 - F1: 0.7163
sub_8:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5938 - F1: 0.5393
sub_8:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.7183 - Accuracy: 0.3438 - F1: 0.3108
sub_8:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.4375 - F1: 0.4353
sub_8:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.5420 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5439 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.5585 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.5565 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7188 - F1: 0.7185
sub_9:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.7188 - F1: 0.7163
sub_9:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6074 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.4353 - Accuracy: 0.8438 - F1: 0.8398
sub_9:Test (Best Model) - Loss: 0.5178 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.5625 - F1: 0.5152
sub_9:Test (Best Model) - Loss: 0.4721 - Accuracy: 0.8438 - F1: 0.8359
sub_10:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6562 - F1: 0.6102
sub_10:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.8125 - F1: 0.8095
sub_10:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5938 - F1: 0.5836
sub_10:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5938 - F1: 0.5589
sub_10:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 0.7316 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.6875 - F1: 0.6875
sub_10:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4688 - F1: 0.4640
sub_10:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.3750 - F1: 0.3651
sub_10:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.6061 - F1: 0.6061
sub_10:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4848 - F1: 0.4672
sub_10:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6364 - F1: 0.6071
sub_10:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.3939 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 0.7336 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5152 - F1: 0.5147
sub_11:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6364 - F1: 0.6333
sub_11:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6061 - F1: 0.6061
sub_11:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.6667 - F1: 0.6159
sub_11:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6970 - F1: 0.6827
sub_11:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5758 - F1: 0.5558
sub_12:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.6250 - F1: 0.5636
sub_12:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.7273 - F1: 0.7179
sub_12:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6061 - F1: 0.5662
sub_12:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6061 - F1: 0.5662
sub_12:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.5312 - F1: 0.5195
sub_12:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.6562 - F1: 0.6390
sub_12:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.4688 - F1: 0.4231
sub_13:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6562 - F1: 0.5883
sub_13:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.8125 - F1: 0.8000
sub_13:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7500 - F1: 0.7229
sub_13:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.7576 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6970 - F1: 0.6944
sub_13:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5455 - F1: 0.5299
sub_13:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7188 - F1: 0.7185
sub_13:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.7188 - F1: 0.7185
sub_13:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.5938 - F1: 0.5393
sub_13:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.5625 - F1: 0.5625
sub_14:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6010 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 0.5828 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.7500 - F1: 0.7229
sub_14:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5938 - F1: 0.5589
sub_14:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.6250 - F1: 0.6235
sub_14:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.7812 - F1: 0.7703
sub_15:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6030 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 0.6393 - Accuracy: 0.7188 - F1: 0.6946
sub_15:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.7812 - F1: 0.7758
sub_15:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7500 - F1: 0.7490
sub_16:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.8125 - F1: 0.8000
sub_16:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.4375 - F1: 0.4353
sub_16:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6562 - F1: 0.6102
sub_16:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.5312 - F1: 0.4910
sub_16:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5938 - F1: 0.5901
sub_17:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6061 - F1: 0.5460
sub_17:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5758 - F1: 0.5754
sub_17:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5758 - F1: 0.5722
sub_17:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4545 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4848 - F1: 0.4527
sub_17:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5312 - F1: 0.5308
sub_17:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4688 - F1: 0.4640
sub_18:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.7879 - F1: 0.7847
sub_18:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.5455 - F1: 0.5455
sub_18:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.6364 - F1: 0.6360
sub_18:Test (Best Model) - Loss: 0.6139 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.6050 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5938 - F1: 0.5836
sub_18:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6562 - F1: 0.6476
sub_18:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.7188 - F1: 0.7117
sub_18:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6222 - Accuracy: 0.6562 - F1: 0.6390
sub_18:Test (Best Model) - Loss: 0.5720 - Accuracy: 0.8750 - F1: 0.8704
sub_18:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.7812 - F1: 0.7810
sub_19:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6250 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.5312 - F1: 0.3469
sub_19:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6562 - F1: 0.6390
sub_19:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6875 - F1: 0.6364
sub_19:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.6562 - F1: 0.6476
sub_19:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5938 - F1: 0.5934
sub_20:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4688 - F1: 0.4640
sub_20:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6875 - F1: 0.6364
sub_20:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.4848 - F1: 0.4772
sub_20:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5758 - F1: 0.5658
sub_20:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.5152 - F1: 0.5147
sub_20:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.6364 - F1: 0.6192
sub_21:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5312 - F1: 0.5271
sub_21:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.6250 - F1: 0.6235
sub_21:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 0.7280 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5312 - F1: 0.5271
sub_21:Test (Best Model) - Loss: 0.7105 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6562 - F1: 0.6559
sub_21:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5000 - F1: 0.4818
sub_22:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6250 - F1: 0.5844
sub_22:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5152 - F1: 0.5111
sub_22:Test (Best Model) - Loss: 0.6477 - Accuracy: 0.6364 - F1: 0.6192
sub_22:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6667 - F1: 0.6330
sub_22:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.7273 - F1: 0.7179
sub_22:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.6875 - F1: 0.6667
sub_22:Test (Best Model) - Loss: 0.6620 - Accuracy: 0.7188 - F1: 0.7163
sub_22:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5625 - F1: 0.5333
sub_23:Test (Best Model) - Loss: 0.5812 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.7576 - F1: 0.7462
sub_23:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6061 - F1: 0.5662
sub_23:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6667 - F1: 0.6159
sub_23:Test (Best Model) - Loss: 0.5765 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6250 - F1: 0.6113
sub_23:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.7500 - F1: 0.7500
sub_23:Test (Best Model) - Loss: 0.5887 - Accuracy: 0.8485 - F1: 0.8479
sub_23:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.7576 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.6667 - F1: 0.6553
sub_23:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.7273 - F1: 0.6997
sub_24:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.3766
sub_24:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6250 - F1: 0.6250
sub_24:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5625 - F1: 0.4909
sub_24:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.5466
sub_25:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.4545 - F1: 0.4288
sub_25:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5758 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5758 - F1: 0.5558
sub_25:Test (Best Model) - Loss: 0.7409 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4545 - F1: 0.4500
sub_25:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.3750 - F1: 0.3750
sub_25:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.5556
sub_25:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.5625 - F1: 0.5608
sub_25:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5312 - F1: 0.4910
sub_25:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.7146 - Accuracy: 0.3438 - F1: 0.3379
sub_25:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6250 - F1: 0.6000
sub_25:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.7188 - F1: 0.7046
sub_26:Test (Best Model) - Loss: 0.5903 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.6667 - F1: 0.6617
sub_26:Test (Best Model) - Loss: 0.5827 - Accuracy: 0.7879 - F1: 0.7746
sub_26:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.6667 - F1: 0.6159
sub_26:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.8485 - F1: 0.8462
sub_26:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.6875 - F1: 0.6875
sub_26:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.6250 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6562 - F1: 0.6390
sub_26:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5217 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.5524 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.8125 - F1: 0.8000
sub_27:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6061 - F1: 0.5460
sub_27:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.5758 - F1: 0.5754
sub_27:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.4545 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4848 - F1: 0.4527
sub_27:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5312 - F1: 0.5308
sub_27:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5000 - F1: 0.4667
sub_27:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.7405 - Accuracy: 0.5625 - F1: 0.4589
sub_28:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.6562 - F1: 0.6102
sub_28:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.7512 - Accuracy: 0.5000 - F1: 0.4980
sub_28:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.7194 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5938 - F1: 0.5733
sub_28:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.5534 - Accuracy: 0.8125 - F1: 0.8095
sub_29:Test (Best Model) - Loss: 0.5095 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.5063 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.4535 - Accuracy: 0.8125 - F1: 0.8000
sub_29:Test (Best Model) - Loss: 0.5512 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.5344 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.8125 - F1: 0.8095
sub_29:Test (Best Model) - Loss: 0.5332 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.5002 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.5512 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.5425 - Accuracy: 0.9091 - F1: 0.9088
sub_29:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.4930 - Accuracy: 0.9091 - F1: 0.9077

=== Summary Results ===

acc: 62.20 ± 8.65
F1: 60.39 ± 8.88
acc-in: 67.54 ± 7.52
F1-in: 65.67 ± 7.85
