lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.7188 - F1: 0.6946
sub_1:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6562 - F1: 0.6102
sub_1:Test (Best Model) - Loss: 0.6023 - Accuracy: 0.7812 - F1: 0.7793
sub_1:Test (Best Model) - Loss: 0.5619 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.6875 - F1: 0.6537
sub_1:Test (Best Model) - Loss: 0.5791 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.5405 - Accuracy: 0.8485 - F1: 0.8433
sub_1:Test (Best Model) - Loss: 0.5799 - Accuracy: 0.7273 - F1: 0.7232
sub_1:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.6364 - F1: 0.5909
sub_1:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.7879 - F1: 0.7806
sub_1:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.5881 - Accuracy: 0.8438 - F1: 0.8424
sub_1:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.7812 - F1: 0.7810
sub_1:Test (Best Model) - Loss: 0.6054 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.5674 - Accuracy: 0.7812 - F1: 0.7703
sub_2:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6061 - F1: 0.5662
sub_2:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.3438 - F1: 0.3379
sub_2:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5312 - F1: 0.5195
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5938 - F1: 0.5733
sub_2:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5625 - F1: 0.5466
sub_2:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.4848 - F1: 0.4672
sub_2:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5152 - F1: 0.5111
sub_2:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7273 - F1: 0.7179
sub_2:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.5758 - F1: 0.5754
sub_3:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.5000 - F1: 0.4921
sub_3:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4688 - F1: 0.4640
sub_3:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5312 - F1: 0.5077
sub_3:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.5625 - F1: 0.5466
sub_3:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5455 - F1: 0.5455
sub_3:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5455 - F1: 0.5438
sub_3:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.6061 - F1: 0.5815
sub_3:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.7209 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 0.7214 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6667 - F1: 0.6617
sub_3:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.4242 - F1: 0.4221
sub_4:Test (Best Model) - Loss: 0.5763 - Accuracy: 0.8485 - F1: 0.8433
sub_4:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.5866 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.5428 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.6970 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.5692 - Accuracy: 0.8182 - F1: 0.8167
sub_4:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.5455 - F1: 0.4995
sub_4:Test (Best Model) - Loss: 0.5871 - Accuracy: 0.7576 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.5152 - F1: 0.5038
sub_4:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.7576 - F1: 0.7574
sub_4:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5758 - F1: 0.5417
sub_5:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.6124 - Accuracy: 0.6875 - F1: 0.6875
sub_5:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.4375 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.4688 - F1: 0.4555
sub_6:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.7500 - F1: 0.7333
sub_6:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5625 - F1: 0.5556
sub_6:Test (Best Model) - Loss: 0.7539 - Accuracy: 0.4848 - F1: 0.4527
sub_6:Test (Best Model) - Loss: 0.7721 - Accuracy: 0.4545 - F1: 0.3864
sub_6:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.5455 - F1: 0.5171
sub_6:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.6061 - F1: 0.5662
sub_6:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.4848 - F1: 0.4527
sub_6:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5152 - F1: 0.5111
sub_6:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5455 - F1: 0.5438
sub_6:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.5758 - F1: 0.5558
sub_7:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5625 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5625 - F1: 0.5152
sub_8:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.6643 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5000 - F1: 0.4921
sub_8:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.7500 - F1: 0.7409
sub_8:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.5032 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5324 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.4998 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.5316 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.6875 - F1: 0.6875
sub_9:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.5938 - F1: 0.5934
sub_9:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.6250 - F1: 0.6190
sub_9:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.6250 - F1: 0.5844
sub_9:Test (Best Model) - Loss: 0.4416 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.5408 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.6103 - Accuracy: 0.5938 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.8750 - F1: 0.8704
sub_10:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5000 - F1: 0.4667
sub_10:Test (Best Model) - Loss: 0.6314 - Accuracy: 0.7188 - F1: 0.7117
sub_10:Test (Best Model) - Loss: 0.6201 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6562 - F1: 0.6476
sub_10:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5000 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.7500 - F1: 0.7460
sub_10:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5312 - F1: 0.4910
sub_10:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.5758 - F1: 0.5558
sub_10:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6667 - F1: 0.6617
sub_10:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.6970 - F1: 0.6726
sub_10:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5758 - F1: 0.5722
sub_11:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.5152 - F1: 0.5147
sub_11:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6667 - F1: 0.6553
sub_11:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.6061 - F1: 0.6061
sub_11:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6364 - F1: 0.6278
sub_11:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5152 - F1: 0.4923
sub_12:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.5873 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.5938 - F1: 0.5393
sub_12:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.5971 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.7576 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.5882 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.6250 - F1: 0.6113
sub_12:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6250 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.5938 - F1: 0.4340
sub_12:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6562 - F1: 0.6390
sub_13:Test (Best Model) - Loss: 0.5683 - Accuracy: 0.7500 - F1: 0.7229
sub_13:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.6562 - F1: 0.5883
sub_13:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6562 - F1: 0.6267
sub_13:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.7500 - F1: 0.7333
sub_13:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.7188 - F1: 0.6632
sub_13:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.6970 - F1: 0.6944
sub_13:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.8485 - F1: 0.8390
sub_13:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.6358 - Accuracy: 0.5758 - F1: 0.5658
sub_13:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.6250 - F1: 0.6235
sub_13:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6284 - Accuracy: 0.6562 - F1: 0.6102
sub_13:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.5000 - F1: 0.4667
sub_14:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.5000 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.6562 - F1: 0.6102
sub_14:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5881 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5869 - Accuracy: 0.7812 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.5870 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.6284 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4375 - F1: 0.4000
sub_15:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.7500 - F1: 0.7500
sub_15:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.4688 - F1: 0.4682
sub_15:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6004 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4062 - F1: 0.3914
sub_16:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5938 - F1: 0.5589
sub_16:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4688 - F1: 0.3976
sub_16:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.4062 - F1: 0.4057
sub_17:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.7416 - Accuracy: 0.4848 - F1: 0.4848
sub_17:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.6061 - F1: 0.6002
sub_17:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4375 - F1: 0.4286
sub_17:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5312 - F1: 0.5077
sub_17:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.5312 - F1: 0.5271
sub_17:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5000 - F1: 0.4459
sub_17:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.5818 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.8182 - F1: 0.8180
sub_18:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.8485 - F1: 0.8485
sub_18:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.5312 - F1: 0.4910
sub_18:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.4688 - F1: 0.4555
sub_18:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.5714 - Accuracy: 0.7188 - F1: 0.7163
sub_18:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.7812 - F1: 0.7810
sub_18:Test (Best Model) - Loss: 0.5956 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5625 - F1: 0.5152
sub_19:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.6126 - Accuracy: 0.6875 - F1: 0.6667
sub_19:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5938 - F1: 0.5733
sub_19:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6875 - F1: 0.6364
sub_19:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.4688 - F1: 0.4682
sub_19:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5938 - F1: 0.5393
sub_19:Test (Best Model) - Loss: 0.7213 - Accuracy: 0.4375 - F1: 0.4353
sub_20:Test (Best Model) - Loss: 0.6123 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.5968 - Accuracy: 0.8125 - F1: 0.8057
sub_20:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.5625 - F1: 0.5333
sub_20:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.7812 - F1: 0.7625
sub_20:Test (Best Model) - Loss: 0.6110 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.6667 - F1: 0.6654
sub_20:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6667 - F1: 0.6553
sub_20:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5758 - F1: 0.5754
sub_20:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6667 - F1: 0.6459
sub_20:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6061 - F1: 0.6046
sub_21:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5938 - F1: 0.5393
sub_21:Test (Best Model) - Loss: 0.7330 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 0.7258 - Accuracy: 0.3750 - F1: 0.2727
sub_21:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5312 - F1: 0.4910
sub_21:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 0.7192 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6562 - F1: 0.6267
sub_21:Test (Best Model) - Loss: 0.7364 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.5312 - F1: 0.5195
sub_21:Test (Best Model) - Loss: 0.7864 - Accuracy: 0.3438 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4062 - F1: 0.3914
sub_22:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5312 - F1: 0.4684
sub_22:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.6562 - F1: 0.5883
sub_22:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.6970 - F1: 0.6726
sub_22:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.5758 - F1: 0.5658
sub_22:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.7576 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.5841 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.6875 - F1: 0.6863
sub_22:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5625 - F1: 0.5556
sub_22:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6250 - F1: 0.5844
sub_22:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.8438 - F1: 0.8436
sub_23:Test (Best Model) - Loss: 0.5164 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 0.5618 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.6076 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.8182 - F1: 0.8139
sub_23:Test (Best Model) - Loss: 0.4730 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.7188 - F1: 0.7185
sub_23:Test (Best Model) - Loss: 0.5920 - Accuracy: 0.7812 - F1: 0.7793
sub_23:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.5132 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 0.6061 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.5224 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.6970 - F1: 0.6898
sub_23:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7879 - F1: 0.7746
sub_24:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6875 - F1: 0.6667
sub_24:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.4688 - F1: 0.3976
sub_24:Test (Best Model) - Loss: 0.7363 - Accuracy: 0.3438 - F1: 0.3273
sub_24:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.7146 - Accuracy: 0.4375 - F1: 0.3766
sub_24:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.4062 - F1: 0.3914
sub_24:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.7438 - Accuracy: 0.3125 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6061 - F1: 0.5926
sub_25:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.6061 - F1: 0.6061
sub_25:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4242 - F1: 0.3660
sub_25:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.4545 - F1: 0.4417
sub_25:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4688 - F1: 0.4640
sub_25:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5625 - F1: 0.5608
sub_25:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4688 - F1: 0.4640
sub_25:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6875 - F1: 0.6761
sub_25:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5625 - F1: 0.5556
sub_25:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6250 - F1: 0.5636
sub_25:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5312 - F1: 0.5077
sub_26:Test (Best Model) - Loss: 0.5463 - Accuracy: 0.8182 - F1: 0.8139
sub_26:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.6364 - F1: 0.6192
sub_26:Test (Best Model) - Loss: 0.5724 - Accuracy: 0.7576 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.6667 - F1: 0.6459
sub_26:Test (Best Model) - Loss: 0.5600 - Accuracy: 0.8182 - F1: 0.8139
sub_26:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.6208 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.6875 - F1: 0.6825
sub_26:Test (Best Model) - Loss: 0.6001 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 0.4303 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.7812 - F1: 0.7703
sub_26:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.8125 - F1: 0.8000
sub_26:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.8438 - F1: 0.8303
sub_27:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.7416 - Accuracy: 0.4848 - F1: 0.4848
sub_27:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.6061 - F1: 0.6002
sub_27:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4375 - F1: 0.4286
sub_27:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5312 - F1: 0.5077
sub_27:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.5312 - F1: 0.5271
sub_27:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5000 - F1: 0.4459
sub_27:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6875 - F1: 0.6863
sub_28:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.6562 - F1: 0.6267
sub_28:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.7522 - Accuracy: 0.5625 - F1: 0.4167
sub_28:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.4375 - F1: 0.3455
sub_28:Test (Best Model) - Loss: 0.7802 - Accuracy: 0.3438 - F1: 0.3431
sub_28:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.6250 - F1: 0.6250
sub_28:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.7188 - F1: 0.7046
sub_28:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5312 - F1: 0.4910
sub_28:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.5938 - F1: 0.5934
sub_28:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.5000 - F1: 0.4818
sub_29:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.5016 - Accuracy: 0.8438 - F1: 0.8436
sub_29:Test (Best Model) - Loss: 0.5104 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.4760 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.4451 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.4672 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.3803 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.4845 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.4992 - Accuracy: 0.8485 - F1: 0.8485
sub_29:Test (Best Model) - Loss: 0.4849 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.4620 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 62.93 ± 9.80
F1: 61.26 ± 10.10
acc-in: 67.76 ± 8.67
F1-in: 65.89 ± 8.96
