lr: 0.0001
sub_7:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.9375 - F1: 0.9365
sub_4:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.9394 - F1: 0.9389
sub_10:Test (Best Model) - Loss: 0.5358 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.7879 - F1: 0.7847
sub_2:Test (Best Model) - Loss: 0.5740 - Accuracy: 0.8485 - F1: 0.8390
sub_5:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.5771 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.9375 - F1: 0.9373
sub_8:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.8750 - F1: 0.8667
sub_14:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.9091 - F1: 0.9088
sub_16:Test (Best Model) - Loss: 0.5735 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.5846 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.5601 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5692 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.5361 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.5398 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.8182 - F1: 0.8180
sub_27:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.9091 - F1: 0.9088
sub_9:Test (Best Model) - Loss: 0.5160 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6325 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.5938 - Accuracy: 0.9091 - F1: 0.9088
sub_20:Test (Best Model) - Loss: 0.5265 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.5911 - Accuracy: 0.8750 - F1: 0.8704
sub_28:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.9375 - F1: 0.9373
sub_10:Test (Best Model) - Loss: 0.5506 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.8438 - F1: 0.8359
sub_7:Test (Best Model) - Loss: 0.5605 - Accuracy: 0.8438 - F1: 0.8303
sub_5:Test (Best Model) - Loss: 0.5359 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.9062 - F1: 0.9054
sub_11:Test (Best Model) - Loss: 0.5758 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 0.5547 - Accuracy: 0.8788 - F1: 0.8731
sub_14:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.5293 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.4604 - Accuracy: 0.9394 - F1: 0.9380
sub_26:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.9394 - F1: 0.9393
sub_19:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.8438 - F1: 0.8436
sub_18:Test (Best Model) - Loss: 0.5310 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4827 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.5147 - Accuracy: 0.9062 - F1: 0.9015
sub_16:Test (Best Model) - Loss: 0.5434 - Accuracy: 0.9375 - F1: 0.9365
sub_3:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.8750 - F1: 0.8704
sub_22:Test (Best Model) - Loss: 0.4931 - Accuracy: 0.9688 - F1: 0.9680
sub_17:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.9394 - F1: 0.9389
sub_24:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.8750 - F1: 0.8704
sub_8:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.9062 - F1: 0.9039
sub_15:Test (Best Model) - Loss: 0.5154 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.9394 - F1: 0.9389
sub_23:Test (Best Model) - Loss: 0.5777 - Accuracy: 0.8485 - F1: 0.8485
sub_6:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.6562 - F1: 0.6559
sub_21:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.8750 - F1: 0.8667
sub_20:Test (Best Model) - Loss: 0.5283 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.5060 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.4841 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5546 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.4695 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.4860 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.7568 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.5613 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.5713 - Accuracy: 0.8485 - F1: 0.8479
sub_29:Test (Best Model) - Loss: 0.5279 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.9091 - F1: 0.9077
sub_13:Test (Best Model) - Loss: 0.5852 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.5621 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.4789 - Accuracy: 0.9091 - F1: 0.9077
sub_18:Test (Best Model) - Loss: 0.5076 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5743 - Accuracy: 0.9062 - F1: 0.9054
sub_25:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.8788 - F1: 0.8778
sub_16:Test (Best Model) - Loss: 0.5588 - Accuracy: 0.9375 - F1: 0.9373
sub_26:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.9697 - F1: 0.9692
sub_15:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.8788 - F1: 0.8759
sub_8:Test (Best Model) - Loss: 0.5789 - Accuracy: 0.8125 - F1: 0.8095
sub_24:Test (Best Model) - Loss: 0.5185 - Accuracy: 0.9688 - F1: 0.9685
sub_6:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6250 - F1: 0.6250
sub_27:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.8788 - F1: 0.8759
sub_21:Test (Best Model) - Loss: 0.5796 - Accuracy: 0.7812 - F1: 0.7793
sub_10:Test (Best Model) - Loss: 0.4667 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.5454 - Accuracy: 0.9375 - F1: 0.9352
sub_20:Test (Best Model) - Loss: 0.4888 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5394 - Accuracy: 0.8750 - F1: 0.8745
sub_16:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.8438 - F1: 0.8436
sub_11:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.7273 - F1: 0.7263
sub_7:Test (Best Model) - Loss: 0.5195 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.5354 - Accuracy: 0.9375 - F1: 0.9352
sub_5:Test (Best Model) - Loss: 0.5408 - Accuracy: 0.8438 - F1: 0.8359
sub_14:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.9062 - F1: 0.9015
sub_19:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.7188 - F1: 0.7117
sub_23:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.8182 - F1: 0.8167
sub_25:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.9091 - F1: 0.9088
sub_9:Test (Best Model) - Loss: 0.4123 - Accuracy: 0.9688 - F1: 0.9680
sub_2:Test (Best Model) - Loss: 0.5590 - Accuracy: 0.9091 - F1: 0.9088
sub_3:Test (Best Model) - Loss: 0.5553 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.5095 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.8750 - F1: 0.8745
sub_26:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.9697 - F1: 0.9696
sub_4:Test (Best Model) - Loss: 0.5059 - Accuracy: 0.9697 - F1: 0.9692
sub_28:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.5460 - Accuracy: 0.8125 - F1: 0.8125
sub_17:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.9091 - F1: 0.9077
sub_15:Test (Best Model) - Loss: 0.4947 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.8750 - F1: 0.8667
sub_12:Test (Best Model) - Loss: 0.4825 - Accuracy: 0.9375 - F1: 0.9365
sub_21:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.8125 - F1: 0.8057
sub_6:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.6875 - F1: 0.6863
sub_11:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.7273 - F1: 0.7273
sub_27:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.9091 - F1: 0.9077
sub_14:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.5104 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5471 - Accuracy: 0.9688 - F1: 0.9685
sub_24:Test (Best Model) - Loss: 0.4948 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.5366 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.9688 - F1: 0.9685
sub_2:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.8788 - F1: 0.8731
sub_3:Test (Best Model) - Loss: 0.5848 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.4788 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.5146 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.5667 - Accuracy: 0.8438 - F1: 0.8436
sub_25:Test (Best Model) - Loss: 0.5641 - Accuracy: 0.8485 - F1: 0.8479
sub_8:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 0.5456 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.7879 - F1: 0.7871
sub_23:Test (Best Model) - Loss: 0.5026 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.7879 - F1: 0.7871
sub_26:Test (Best Model) - Loss: 0.5177 - Accuracy: 0.9697 - F1: 0.9696
sub_6:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.8125 - F1: 0.8095
sub_22:Test (Best Model) - Loss: 0.4904 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.4701 - Accuracy: 0.9697 - F1: 0.9692
sub_13:Test (Best Model) - Loss: 0.5299 - Accuracy: 0.9062 - F1: 0.9062
sub_18:Test (Best Model) - Loss: 0.4569 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.4841 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.9091 - F1: 0.9060
sub_12:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.5199 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.5632 - Accuracy: 0.8125 - F1: 0.8118
sub_21:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.7500 - F1: 0.7409
sub_10:Test (Best Model) - Loss: 0.5403 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.4523 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.5456 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.5073 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5695 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.5463 - Accuracy: 0.9062 - F1: 0.9015
sub_2:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.8750 - F1: 0.8745
sub_25:Test (Best Model) - Loss: 0.6023 - Accuracy: 0.8182 - F1: 0.8167
sub_1:Test (Best Model) - Loss: 0.5000 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.6061 - F1: 0.5926
sub_3:Test (Best Model) - Loss: 0.5089 - Accuracy: 0.9697 - F1: 0.9692
sub_8:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.8438 - F1: 0.8436
sub_19:Test (Best Model) - Loss: 0.4552 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.6061 - F1: 0.5926
sub_16:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.5625 - F1: 0.5333
sub_26:Test (Best Model) - Loss: 0.5645 - Accuracy: 0.9394 - F1: 0.9393
sub_15:Test (Best Model) - Loss: 0.5726 - Accuracy: 0.8750 - F1: 0.8750
sub_28:Test (Best Model) - Loss: 0.5578 - Accuracy: 0.8438 - F1: 0.8303
sub_5:Test (Best Model) - Loss: 0.4976 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.5211 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4786 - Accuracy: 0.9697 - F1: 0.9696
sub_12:Test (Best Model) - Loss: 0.5610 - Accuracy: 0.9091 - F1: 0.9077
sub_6:Test (Best Model) - Loss: 0.5140 - Accuracy: 0.8788 - F1: 0.8731
sub_20:Test (Best Model) - Loss: 0.4870 - Accuracy: 0.9688 - F1: 0.9685
sub_10:Test (Best Model) - Loss: 0.5590 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.5784 - Accuracy: 0.8788 - F1: 0.8778
sub_7:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.8438 - F1: 0.8359
sub_23:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.5938 - F1: 0.5589
sub_11:Test (Best Model) - Loss: 0.5297 - Accuracy: 0.8485 - F1: 0.8390
sub_29:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.9688 - F1: 0.9680
sub_25:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6562 - F1: 0.6476
sub_17:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.9062 - F1: 0.9062
sub_14:Test (Best Model) - Loss: 0.4584 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.5000 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.5647 - Accuracy: 0.9091 - F1: 0.9091
sub_28:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.5674 - Accuracy: 0.8750 - F1: 0.8745
sub_3:Test (Best Model) - Loss: 0.5478 - Accuracy: 0.9697 - F1: 0.9696
sub_18:Test (Best Model) - Loss: 0.5384 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6667 - F1: 0.6553
sub_16:Test (Best Model) - Loss: 0.5604 - Accuracy: 0.9062 - F1: 0.9062
sub_4:Test (Best Model) - Loss: 0.5452 - Accuracy: 0.9091 - F1: 0.9091
sub_7:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.5788 - Accuracy: 0.9091 - F1: 0.9088
sub_9:Test (Best Model) - Loss: 0.4793 - Accuracy: 0.9062 - F1: 0.9015
sub_11:Test (Best Model) - Loss: 0.5592 - Accuracy: 0.8485 - F1: 0.8390
sub_5:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.8438 - F1: 0.8436
sub_15:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.9062 - F1: 0.9054
sub_23:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.4123 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.4261 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.5994 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.5035 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.6133 - Accuracy: 0.8788 - F1: 0.8787
sub_10:Test (Best Model) - Loss: 0.5654 - Accuracy: 0.8750 - F1: 0.8667
sub_20:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.5883 - Accuracy: 0.7576 - F1: 0.7556
sub_25:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.7812 - F1: 0.7519
sub_3:Test (Best Model) - Loss: 0.5770 - Accuracy: 0.9091 - F1: 0.9077
sub_17:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6061 - F1: 0.6046
sub_14:Test (Best Model) - Loss: 0.5432 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.5623 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.4688 - F1: 0.3976
sub_21:Test (Best Model) - Loss: 0.5434 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.5063 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.4521 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5428 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.4945 - Accuracy: 0.9394 - F1: 0.9380
sub_27:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6061 - F1: 0.6046
sub_19:Test (Best Model) - Loss: 0.5376 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.5747 - Accuracy: 0.9375 - F1: 0.9365
sub_11:Test (Best Model) - Loss: 0.5292 - Accuracy: 0.8485 - F1: 0.8390
sub_15:Test (Best Model) - Loss: 0.5736 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.4884 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.4742 - Accuracy: 0.9375 - F1: 0.9365
sub_7:Test (Best Model) - Loss: 0.5699 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.5901 - Accuracy: 0.8485 - F1: 0.8462
sub_8:Test (Best Model) - Loss: 0.5249 - Accuracy: 0.8750 - F1: 0.8745
sub_22:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.9091 - F1: 0.9088
sub_28:Test (Best Model) - Loss: 0.5876 - Accuracy: 0.7188 - F1: 0.6632
sub_20:Test (Best Model) - Loss: 0.5542 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.8182 - F1: 0.8036
sub_10:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.8750 - F1: 0.8667
sub_5:Test (Best Model) - Loss: 0.5464 - Accuracy: 0.8750 - F1: 0.8750
sub_23:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.5094 - Accuracy: 0.9375 - F1: 0.9365
sub_3:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.9697 - F1: 0.9692
sub_17:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6061 - F1: 0.6061
sub_2:Test (Best Model) - Loss: 0.5993 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.4517 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.5722 - Accuracy: 0.9091 - F1: 0.9077
sub_21:Test (Best Model) - Loss: 0.5560 - Accuracy: 0.9375 - F1: 0.9352
sub_7:Test (Best Model) - Loss: 0.5735 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.7576 - F1: 0.7519
sub_11:Test (Best Model) - Loss: 0.5002 - Accuracy: 0.9394 - F1: 0.9380
sub_4:Test (Best Model) - Loss: 0.5479 - Accuracy: 0.9697 - F1: 0.9696
sub_24:Test (Best Model) - Loss: 0.5261 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6061 - F1: 0.6061
sub_19:Test (Best Model) - Loss: 0.5427 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.5502 - Accuracy: 0.7812 - F1: 0.7793
sub_14:Test (Best Model) - Loss: 0.4689 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.5111 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.7576 - F1: 0.7574
sub_16:Test (Best Model) - Loss: 0.5515 - Accuracy: 0.9062 - F1: 0.9062
sub_28:Test (Best Model) - Loss: 0.5801 - Accuracy: 0.7812 - F1: 0.7519
sub_10:Test (Best Model) - Loss: 0.5282 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.9375 - F1: 0.9365
sub_13:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.9697 - F1: 0.9696
sub_15:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.8438 - F1: 0.8436
sub_20:Test (Best Model) - Loss: 0.5350 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.8438 - F1: 0.8436
sub_25:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.8485 - F1: 0.8462
sub_9:Test (Best Model) - Loss: 0.5205 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.5140 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.8182 - F1: 0.8036
sub_21:Test (Best Model) - Loss: 0.5390 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.7576 - F1: 0.7574
sub_3:Test (Best Model) - Loss: 0.5226 - Accuracy: 0.9394 - F1: 0.9380
sub_6:Test (Best Model) - Loss: 0.5667 - Accuracy: 0.8788 - F1: 0.8731
sub_7:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.9394 - F1: 0.9389
sub_2:Test (Best Model) - Loss: 0.4853 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5312 - F1: 0.4684
sub_5:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.7500 - F1: 0.7460
sub_24:Test (Best Model) - Loss: 0.5684 - Accuracy: 0.9375 - F1: 0.9365
sub_28:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.4688 - F1: 0.4555
sub_29:Test (Best Model) - Loss: 0.4584 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.8485 - F1: 0.8479
sub_14:Test (Best Model) - Loss: 0.5077 - Accuracy: 0.9688 - F1: 0.9685
sub_4:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.9697 - F1: 0.9696
sub_19:Test (Best Model) - Loss: 0.4343 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.4919 - Accuracy: 0.9091 - F1: 0.9060
sub_10:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.8788 - F1: 0.8731
sub_18:Test (Best Model) - Loss: 0.5166 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.5382 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6970 - F1: 0.6967
sub_9:Test (Best Model) - Loss: 0.5178 - Accuracy: 0.9375 - F1: 0.9373
sub_17:Test (Best Model) - Loss: 0.5710 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.9394 - F1: 0.9393
sub_12:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.8182 - F1: 0.8139
sub_25:Test (Best Model) - Loss: 0.5754 - Accuracy: 0.9062 - F1: 0.9062
sub_26:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.8125 - F1: 0.8118
sub_3:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.9091 - F1: 0.9088
sub_2:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.7879 - F1: 0.7664
sub_6:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7879 - F1: 0.7871
sub_21:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.9375 - F1: 0.9352
sub_28:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.8750 - F1: 0.8750
sub_23:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.8788 - F1: 0.8731
sub_18:Test (Best Model) - Loss: 0.5480 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.5710 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.5407 - Accuracy: 0.9394 - F1: 0.9389
sub_13:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6250 - F1: 0.6250
sub_29:Test (Best Model) - Loss: 0.5305 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.9062 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.5399 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 0.4414 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.5532 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.5427 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.5383 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.5847 - Accuracy: 0.9091 - F1: 0.9060
sub_22:Test (Best Model) - Loss: 0.5519 - Accuracy: 0.9375 - F1: 0.9373
sub_11:Test (Best Model) - Loss: 0.5672 - Accuracy: 0.8788 - F1: 0.8759
sub_8:Test (Best Model) - Loss: 0.5083 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.8750 - F1: 0.8750
sub_24:Test (Best Model) - Loss: 0.4732 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.8438 - F1: 0.8303
sub_17:Test (Best Model) - Loss: 0.5654 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.4741 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.5649 - Accuracy: 0.9697 - F1: 0.9696
sub_25:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.8125 - F1: 0.8118
sub_28:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6875 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 0.4947 - Accuracy: 0.9688 - F1: 0.9685
sub_2:Test (Best Model) - Loss: 0.5618 - Accuracy: 0.8788 - F1: 0.8731
sub_15:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.6875 - F1: 0.6761
sub_21:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.7812 - F1: 0.7810
sub_4:Test (Best Model) - Loss: 0.5402 - Accuracy: 0.9394 - F1: 0.9389
sub_18:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.9375 - F1: 0.9373
sub_16:Test (Best Model) - Loss: 0.5872 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.5607 - Accuracy: 0.9091 - F1: 0.9060
sub_10:Test (Best Model) - Loss: 0.4979 - Accuracy: 0.9394 - F1: 0.9380
sub_5:Test (Best Model) - Loss: 0.5665 - Accuracy: 0.8750 - F1: 0.8750
sub_6:Test (Best Model) - Loss: 0.5335 - Accuracy: 0.8788 - F1: 0.8787
sub_29:Test (Best Model) - Loss: 0.5100 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.5654 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6875 - F1: 0.6875
sub_22:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.8750 - F1: 0.8750
sub_19:Test (Best Model) - Loss: 0.5300 - Accuracy: 0.8750 - F1: 0.8667
sub_20:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.8485 - F1: 0.8433
sub_8:Test (Best Model) - Loss: 0.5122 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.9062 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.5724 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.4953 - Accuracy: 0.9375 - F1: 0.9365
sub_12:Test (Best Model) - Loss: 0.5499 - Accuracy: 0.9375 - F1: 0.9352
sub_16:Test (Best Model) - Loss: 0.5759 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.5142 - Accuracy: 0.9375 - F1: 0.9352
sub_21:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7500 - F1: 0.7460
sub_24:Test (Best Model) - Loss: 0.5388 - Accuracy: 0.9375 - F1: 0.9365
sub_2:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.9091 - F1: 0.9077
sub_3:Test (Best Model) - Loss: 0.5394 - Accuracy: 0.9394 - F1: 0.9393
sub_10:Test (Best Model) - Loss: 0.5181 - Accuracy: 0.9091 - F1: 0.9060
sub_18:Test (Best Model) - Loss: 0.4723 - Accuracy: 0.9688 - F1: 0.9685
sub_28:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.7500 - F1: 0.7490
sub_23:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.8182 - F1: 0.8096
sub_1:Test (Best Model) - Loss: 0.4830 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.5036 - Accuracy: 0.9091 - F1: 0.9060
sub_17:Test (Best Model) - Loss: 0.5150 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.4904 - Accuracy: 0.9697 - F1: 0.9696
sub_5:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.9375 - F1: 0.9373
sub_4:Test (Best Model) - Loss: 0.4882 - Accuracy: 0.9697 - F1: 0.9696
sub_25:Test (Best Model) - Loss: 0.5141 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.5931 - Accuracy: 0.8182 - F1: 0.8167
sub_22:Test (Best Model) - Loss: 0.5121 - Accuracy: 0.9688 - F1: 0.9685
sub_8:Test (Best Model) - Loss: 0.4813 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4688 - F1: 0.3976
sub_20:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.9091 - F1: 0.9060
sub_13:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6250 - F1: 0.6235
sub_7:Test (Best Model) - Loss: 0.5398 - Accuracy: 0.9375 - F1: 0.9352
sub_19:Test (Best Model) - Loss: 0.5113 - Accuracy: 0.8750 - F1: 0.8667
sub_15:Test (Best Model) - Loss: 0.5077 - Accuracy: 0.9062 - F1: 0.9054
sub_27:Test (Best Model) - Loss: 0.5150 - Accuracy: 0.9062 - F1: 0.9015
sub_21:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.5515 - Accuracy: 0.9062 - F1: 0.9015
sub_16:Test (Best Model) - Loss: 0.5298 - Accuracy: 0.9375 - F1: 0.9352
sub_12:Test (Best Model) - Loss: 0.5273 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.5721 - Accuracy: 0.9697 - F1: 0.9692
sub_18:Test (Best Model) - Loss: 0.5018 - Accuracy: 0.9688 - F1: 0.9685
sub_5:Test (Best Model) - Loss: 0.5530 - Accuracy: 0.8438 - F1: 0.8436
sub_26:Test (Best Model) - Loss: 0.4992 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.5905 - Accuracy: 0.8788 - F1: 0.8759
sub_1:Test (Best Model) - Loss: 0.5065 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.9697 - F1: 0.9696
sub_2:Test (Best Model) - Loss: 0.5467 - Accuracy: 0.9394 - F1: 0.9380
sub_11:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.9091 - F1: 0.9077
sub_10:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.9091 - F1: 0.9060
sub_23:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.8788 - F1: 0.8731
sub_22:Test (Best Model) - Loss: 0.5500 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.8438 - F1: 0.8398
sub_25:Test (Best Model) - Loss: 0.5298 - Accuracy: 0.9375 - F1: 0.9352
sub_24:Test (Best Model) - Loss: 0.5618 - Accuracy: 0.9062 - F1: 0.9062
sub_8:Test (Best Model) - Loss: 0.5022 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4710 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.5611 - Accuracy: 0.8788 - F1: 0.8731
sub_13:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6562 - F1: 0.6559
sub_4:Test (Best Model) - Loss: 0.5675 - Accuracy: 0.9697 - F1: 0.9692
sub_19:Test (Best Model) - Loss: 0.5672 - Accuracy: 0.9062 - F1: 0.9015
sub_21:Test (Best Model) - Loss: 0.6115 - Accuracy: 0.7500 - F1: 0.7490
sub_7:Test (Best Model) - Loss: 0.5019 - Accuracy: 0.9375 - F1: 0.9352
sub_12:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.8438 - F1: 0.8398
sub_2:Test (Best Model) - Loss: 0.5381 - Accuracy: 0.9091 - F1: 0.9060
sub_6:Test (Best Model) - Loss: 0.5594 - Accuracy: 0.8788 - F1: 0.8778
sub_1:Test (Best Model) - Loss: 0.4871 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5553 - Accuracy: 0.8788 - F1: 0.8731
sub_14:Test (Best Model) - Loss: 0.5649 - Accuracy: 0.8750 - F1: 0.8667
sub_15:Test (Best Model) - Loss: 0.5779 - Accuracy: 0.7812 - F1: 0.7793
sub_11:Test (Best Model) - Loss: 0.4961 - Accuracy: 0.9697 - F1: 0.9692
sub_18:Test (Best Model) - Loss: 0.4759 - Accuracy: 0.9375 - F1: 0.9373
sub_22:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.8750 - F1: 0.8750
sub_3:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.9394 - F1: 0.9389
sub_24:Test (Best Model) - Loss: 0.5521 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 0.4534 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.5116 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.5858 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.5070 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.5521 - Accuracy: 0.8438 - F1: 0.8359
sub_20:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.8788 - F1: 0.8731
sub_8:Test (Best Model) - Loss: 0.5047 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.6015 - Accuracy: 0.7812 - F1: 0.7758
sub_12:Test (Best Model) - Loss: 0.5412 - Accuracy: 0.9062 - F1: 0.9015
sub_21:Test (Best Model) - Loss: 0.5603 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.8750 - F1: 0.8750
sub_24:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.9062 - F1: 0.9062
sub_27:Test (Best Model) - Loss: 0.5521 - Accuracy: 0.8438 - F1: 0.8359
sub_25:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4044 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.5122 - Accuracy: 0.9062 - F1: 0.9015
sub_14:Test (Best Model) - Loss: 0.5489 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 0.5984 - Accuracy: 0.7812 - F1: 0.7793
sub_24:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.9375 - F1: 0.9373
sub_26:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.5096 - Accuracy: 0.9062 - F1: 0.9015

=== Summary Results ===

acc: 88.12 ± 6.50
F1: 87.61 ± 7.06
acc-in: 93.05 ± 3.83
F1-in: 92.75 ± 4.05
