lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.4312 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.4445 - Accuracy: 0.8125 - F1: 0.8057
sub_1:Test (Best Model) - Loss: 0.4647 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.3513 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.3864 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.4268 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.3771 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.3720 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.4823 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.3965 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.3897 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3244 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.2981 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.3905 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3117 - Accuracy: 0.8750 - F1: 0.8704
sub_2:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.7879 - F1: 0.7746
sub_2:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.7576 - F1: 0.7462
sub_2:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.7879 - F1: 0.7746
sub_2:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5938 - F1: 0.5836
sub_2:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.6562 - F1: 0.6476
sub_2:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.7500 - F1: 0.7091
sub_2:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.6562 - F1: 0.5883
sub_2:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.7273 - F1: 0.7273
sub_2:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.5721 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.6120 - Accuracy: 0.6667 - F1: 0.6617
sub_3:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6250 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.5312 - F1: 0.5271
sub_3:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.6250 - F1: 0.6235
sub_3:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6061 - F1: 0.5926
sub_3:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5455 - F1: 0.4457
sub_3:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.5758 - F1: 0.5417
sub_3:Test (Best Model) - Loss: 0.8684 - Accuracy: 0.5455 - F1: 0.5438
sub_3:Test (Best Model) - Loss: 0.7759 - Accuracy: 0.5152 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.7736 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.8886 - Accuracy: 0.4242 - F1: 0.4046
sub_4:Test (Best Model) - Loss: 0.4746 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.3656 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4368 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.8788 - F1: 0.8731
sub_4:Test (Best Model) - Loss: 0.4226 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.5247 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.4770 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.4657 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.5965 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.5170 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.5487 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.4720 - Accuracy: 0.7576 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.7576 - F1: 0.7574
sub_5:Test (Best Model) - Loss: 0.7533 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.8317 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.4062 - F1: 0.3552
sub_5:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.5816 - Accuracy: 0.5938 - F1: 0.5733
sub_5:Test (Best Model) - Loss: 0.5729 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.5349 - Accuracy: 0.7188 - F1: 0.7117
sub_5:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4062 - F1: 0.3552
sub_5:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.5625 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.6875 - F1: 0.6761
sub_6:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6875 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.5839 - Accuracy: 0.6875 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 0.9235 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.9612 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.5455 - F1: 0.4058
sub_6:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.7726 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6667 - F1: 0.6159
sub_6:Test (Best Model) - Loss: 0.6191 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6041 - Accuracy: 0.7576 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.6061 - F1: 0.5460
sub_7:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.4375 - F1: 0.4286
sub_7:Test (Best Model) - Loss: 0.6001 - Accuracy: 0.6562 - F1: 0.6102
sub_7:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.7245 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 0.7285 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.7500 - F1: 0.7460
sub_7:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6250 - F1: 0.5362
sub_8:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.4979 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.6250 - F1: 0.6000
sub_8:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.7500 - F1: 0.7229
sub_8:Test (Best Model) - Loss: 0.5392 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.7812 - F1: 0.7758
sub_8:Test (Best Model) - Loss: 0.5394 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.2952 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.3814 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.3272 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.3207 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.3804 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4589 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.4792 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.7188 - F1: 0.7163
sub_9:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4296 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5118 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 0.4093 - Accuracy: 0.8438 - F1: 0.8398
sub_9:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.2668 - Accuracy: 0.8438 - F1: 0.8359
sub_10:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.6250 - F1: 0.5844
sub_10:Test (Best Model) - Loss: 0.5484 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.5952 - Accuracy: 0.5938 - F1: 0.5901
sub_10:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.6250 - F1: 0.5844
sub_10:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6875 - F1: 0.6875
sub_10:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.3750 - F1: 0.3725
sub_10:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.6364 - F1: 0.6333
sub_10:Test (Best Model) - Loss: 0.7437 - Accuracy: 0.5152 - F1: 0.5038
sub_10:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6364 - F1: 0.6192
sub_10:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.8953 - Accuracy: 0.4242 - F1: 0.3883
sub_11:Test (Best Model) - Loss: 0.8815 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.8663 - Accuracy: 0.4242 - F1: 0.4157
sub_11:Test (Best Model) - Loss: 0.7629 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.8407 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.7565 - Accuracy: 0.5455 - F1: 0.4058
sub_11:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6364 - F1: 0.6278
sub_11:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6364 - F1: 0.5909
sub_12:Test (Best Model) - Loss: 0.4773 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.4226 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.4733 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.4679 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.4411 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5318 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.4747 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.5072 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.4403 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.3860 - Accuracy: 0.8125 - F1: 0.7922
sub_13:Test (Best Model) - Loss: 0.3997 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.3272 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.3840 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.7879 - F1: 0.7806
sub_13:Test (Best Model) - Loss: 0.4309 - Accuracy: 0.9091 - F1: 0.9091
sub_13:Test (Best Model) - Loss: 0.4455 - Accuracy: 0.9091 - F1: 0.9088
sub_13:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.7273 - F1: 0.7179
sub_13:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.8182 - F1: 0.8096
sub_13:Test (Best Model) - Loss: 0.4719 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.5046 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.4585 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8750 - F1: 0.8730
sub_14:Test (Best Model) - Loss: 0.4838 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.4633 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.5076 - Accuracy: 0.7812 - F1: 0.7810
sub_14:Test (Best Model) - Loss: 0.4741 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.4716 - Accuracy: 0.9062 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.4392 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.8750 - F1: 0.8704
sub_14:Test (Best Model) - Loss: 0.4206 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.4928 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 0.4711 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.5765 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6153 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.4523 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.5354 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.5083 - Accuracy: 0.7812 - F1: 0.7703
sub_15:Test (Best Model) - Loss: 0.5120 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.4602 - Accuracy: 0.8438 - F1: 0.8424
sub_15:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.5771 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.5658 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6562 - F1: 0.6559
sub_16:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.5419 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 0.7088 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.8177 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.7530 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6667 - F1: 0.6459
sub_17:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.6364 - F1: 0.5909
sub_17:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.6667 - F1: 0.6617
sub_17:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.6061 - F1: 0.6046
sub_17:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.8180 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5901
sub_17:Test (Best Model) - Loss: 0.7304 - Accuracy: 0.5938 - F1: 0.5836
sub_17:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.5000 - F1: 0.4980
sub_17:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5938 - F1: 0.5836
sub_18:Test (Best Model) - Loss: 0.5148 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.4852 - Accuracy: 0.8182 - F1: 0.8180
sub_18:Test (Best Model) - Loss: 0.5017 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.4785 - Accuracy: 0.8485 - F1: 0.8433
sub_18:Test (Best Model) - Loss: 0.4403 - Accuracy: 0.8182 - F1: 0.8167
sub_18:Test (Best Model) - Loss: 0.4757 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.5197 - Accuracy: 0.7500 - F1: 0.7500
sub_18:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.7500 - F1: 0.7500
sub_18:Test (Best Model) - Loss: 0.4816 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.4720 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.4368 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.4571 - Accuracy: 0.8750 - F1: 0.8730
sub_18:Test (Best Model) - Loss: 0.4081 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.4234 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.4198 - Accuracy: 0.8438 - F1: 0.8398
sub_19:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.5758 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 0.5655 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5947 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.5828 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6250 - F1: 0.6250
sub_19:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.7500 - F1: 0.7333
sub_19:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.5767 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8438 - F1: 0.8398
sub_20:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.5870 - Accuracy: 0.7500 - F1: 0.7229
sub_20:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.5304 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.7286 - Accuracy: 0.5758 - F1: 0.5658
sub_20:Test (Best Model) - Loss: 0.7546 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 0.7881 - Accuracy: 0.6667 - F1: 0.6459
sub_20:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.7879 - F1: 0.7664
sub_21:Test (Best Model) - Loss: 0.7583 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7859 - Accuracy: 0.2812 - F1: 0.2749
sub_21:Test (Best Model) - Loss: 0.7709 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.7579 - Accuracy: 0.5312 - F1: 0.4386
sub_21:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.7815 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.8389 - Accuracy: 0.5938 - F1: 0.5393
sub_21:Test (Best Model) - Loss: 0.7447 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.8319 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 0.8223 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.8550 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.9171 - Accuracy: 0.3438 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.7684 - Accuracy: 0.5000 - F1: 0.4667
sub_22:Test (Best Model) - Loss: 0.4904 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4936 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.4660 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4789 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 0.5347 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5342 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.5413 - Accuracy: 0.7576 - F1: 0.7381
sub_22:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.8125 - F1: 0.8095
sub_22:Test (Best Model) - Loss: 0.5571 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.5177 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 0.5653 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.4231 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.3341 - Accuracy: 0.9091 - F1: 0.9060
sub_23:Test (Best Model) - Loss: 0.5729 - Accuracy: 0.6875 - F1: 0.6875
sub_23:Test (Best Model) - Loss: 0.5366 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8438 - F1: 0.8398
sub_23:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.7500 - F1: 0.7490
sub_23:Test (Best Model) - Loss: 0.5124 - Accuracy: 0.7500 - F1: 0.7500
sub_23:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.3785 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4040 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4515 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.7576 - F1: 0.7273
sub_24:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 0.8093 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 0.7257 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7739 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6250 - F1: 0.6250
sub_24:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6250 - F1: 0.5844
sub_24:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 0.7435 - Accuracy: 0.5938 - F1: 0.5733
sub_24:Test (Best Model) - Loss: 0.7455 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7686 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.7986 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.7672 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 0.7913 - Accuracy: 0.3636 - F1: 0.2993
sub_25:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.5758 - F1: 0.5722
sub_25:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.8261 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.7761 - Accuracy: 0.4848 - F1: 0.4328
sub_25:Test (Best Model) - Loss: 0.7262 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.7500 - F1: 0.7333
sub_25:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6583 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6059 - Accuracy: 0.6250 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.6250 - F1: 0.5362
sub_26:Test (Best Model) - Loss: 0.4341 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.4675 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.4027 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.4632 - Accuracy: 0.7576 - F1: 0.7273
sub_26:Test (Best Model) - Loss: 0.3641 - Accuracy: 0.9091 - F1: 0.9060
sub_26:Test (Best Model) - Loss: 0.5268 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 0.5552 - Accuracy: 0.6875 - F1: 0.6875
sub_26:Test (Best Model) - Loss: 0.5103 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 0.4739 - Accuracy: 0.7500 - F1: 0.7409
sub_26:Test (Best Model) - Loss: 0.4459 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.3027 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.3668 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.3763 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.3278 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.3093 - Accuracy: 0.8438 - F1: 0.8303
sub_27:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6667 - F1: 0.6459
sub_27:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.6364 - F1: 0.5909
sub_27:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.6667 - F1: 0.6617
sub_27:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.6061 - F1: 0.6046
sub_27:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.8180 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5901
sub_27:Test (Best Model) - Loss: 0.7304 - Accuracy: 0.5938 - F1: 0.5836
sub_27:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.5000 - F1: 0.4980
sub_27:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.5625 - F1: 0.5333
sub_27:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.5225 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.6562 - F1: 0.6559
sub_28:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.9396 - Accuracy: 0.5312 - F1: 0.4684
sub_28:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.9005 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.9697 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.9251 - Accuracy: 0.5000 - F1: 0.4980
sub_28:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 1.1620 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.8464 - Accuracy: 0.4062 - F1: 0.3552
sub_28:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.3438 - F1: 0.3431
sub_28:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.5938 - F1: 0.5934
sub_28:Test (Best Model) - Loss: 0.7424 - Accuracy: 0.4375 - F1: 0.3766
sub_29:Test (Best Model) - Loss: 0.2825 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3206 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3275 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3324 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.2913 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.1944 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.2558 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1784 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2339 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.2169 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.2498 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2760 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.1757 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2431 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.2177 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 67.68 ± 11.77
F1: 65.42 ± 12.65
acc-in: 74.24 ± 8.47
F1-in: 72.04 ± 9.07
