lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.6875 - F1: 0.6761
sub_1:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.7188 - F1: 0.7046
sub_1:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7500 - F1: 0.7409
sub_1:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.7500 - F1: 0.7409
sub_1:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.8125 - F1: 0.8000
sub_1:Test (Best Model) - Loss: 0.6283 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.7273 - F1: 0.7263
sub_1:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.6364 - F1: 0.6071
sub_1:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.7576 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7188 - F1: 0.7185
sub_1:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.7812 - F1: 0.7810
sub_1:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.7188 - F1: 0.7046
sub_1:Test (Best Model) - Loss: 0.6272 - Accuracy: 0.7812 - F1: 0.7758
sub_2:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4545 - F1: 0.4288
sub_2:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5758 - F1: 0.5417
sub_2:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.4062 - F1: 0.4010
sub_2:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.4688 - F1: 0.4682
sub_2:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.6250 - F1: 0.6235
sub_2:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5312 - F1: 0.5271
sub_2:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.5455 - F1: 0.5438
sub_2:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4545 - F1: 0.4417
sub_2:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6061 - F1: 0.6046
sub_3:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4375 - F1: 0.4375
sub_3:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.3750 - F1: 0.3651
sub_3:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6667 - F1: 0.6617
sub_3:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6364 - F1: 0.6278
sub_3:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4848 - F1: 0.4527
sub_3:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.6970 - F1: 0.6827
sub_4:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.5422 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.6970 - F1: 0.6827
sub_4:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6364 - F1: 0.6278
sub_4:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5455 - F1: 0.5299
sub_4:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.4545 - F1: 0.4288
sub_4:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5758 - F1: 0.5658
sub_5:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.4688 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.7500 - F1: 0.7490
sub_5:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6875 - F1: 0.6825
sub_5:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5000 - F1: 0.4921
sub_5:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.4688 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.4688 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.5938 - F1: 0.5901
sub_6:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5938 - F1: 0.5901
sub_6:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.4688 - F1: 0.4555
sub_6:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5625 - F1: 0.5625
sub_6:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.5938 - F1: 0.5901
sub_6:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.5758 - F1: 0.4978
sub_6:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.4242 - F1: 0.4046
sub_6:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.5758 - F1: 0.4653
sub_6:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 0.7135 - Accuracy: 0.4545 - F1: 0.4540
sub_6:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4848 - F1: 0.4772
sub_6:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6364 - F1: 0.6360
sub_6:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.5455 - F1: 0.5438
sub_6:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4848 - F1: 0.4848
sub_7:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.7188 - F1: 0.7185
sub_7:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.3750 - F1: 0.3651
sub_7:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4062 - F1: 0.3764
sub_7:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.6875 - F1: 0.6875
sub_8:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5312 - F1: 0.4684
sub_8:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.6250 - F1: 0.5844
sub_8:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5312 - F1: 0.5077
sub_8:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.4921
sub_8:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5934
sub_8:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5312 - F1: 0.5077
sub_8:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 0.5357 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.5758 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.5848 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.6028 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.5723 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7812 - F1: 0.7810
sub_9:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.5938 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.6562 - F1: 0.6476
sub_9:Test (Best Model) - Loss: 0.5782 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.8438 - F1: 0.8398
sub_10:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.7254 - Accuracy: 0.3438 - F1: 0.3431
sub_10:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.3438 - F1: 0.3379
sub_10:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4242 - F1: 0.4221
sub_10:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5455 - F1: 0.5387
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4545 - F1: 0.4107
sub_10:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6061 - F1: 0.6046
sub_10:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 0.7254 - Accuracy: 0.3939 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6364 - F1: 0.6278
sub_11:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6061 - F1: 0.5926
sub_11:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6970 - F1: 0.6898
sub_11:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4848 - F1: 0.4063
sub_11:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.3636 - F1: 0.3239
sub_11:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.7273 - F1: 0.7102
sub_11:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5455 - F1: 0.5387
sub_12:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.5758 - F1: 0.4978
sub_12:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6970 - F1: 0.6726
sub_12:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6667 - F1: 0.6330
sub_12:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.5988 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6630 - Accuracy: 0.6250 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5938 - F1: 0.5836
sub_12:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4688 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5625 - F1: 0.5333
sub_13:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5312 - F1: 0.5195
sub_13:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.7188 - F1: 0.7163
sub_13:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5938 - F1: 0.5836
sub_13:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5938 - F1: 0.5733
sub_13:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5000 - F1: 0.4667
sub_14:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.5312 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.5832 - Accuracy: 0.8125 - F1: 0.8000
sub_14:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.4688 - F1: 0.4640
sub_14:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.6875 - F1: 0.6537
sub_15:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.7812 - F1: 0.7758
sub_15:Test (Best Model) - Loss: 0.6199 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.7500 - F1: 0.7500
sub_15:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.7500 - F1: 0.7490
sub_15:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.6123 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.7500 - F1: 0.7490
sub_16:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5000 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7500 - F1: 0.7490
sub_16:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4688 - F1: 0.4555
sub_16:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.4375 - F1: 0.4286
sub_17:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5455 - F1: 0.5299
sub_17:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6061 - F1: 0.6046
sub_17:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4848 - F1: 0.4672
sub_17:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4848 - F1: 0.4829
sub_17:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.4062 - F1: 0.4057
sub_17:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6250 - F1: 0.6235
sub_17:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.4688 - F1: 0.4555
sub_17:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.4818
sub_18:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.7273 - F1: 0.7273
sub_18:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.5455 - F1: 0.5299
sub_18:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.6667 - F1: 0.6553
sub_18:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.7273 - F1: 0.7273
sub_18:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.6364 - F1: 0.6360
sub_18:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5000 - F1: 0.4980
sub_18:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.6875 - F1: 0.6875
sub_18:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5312 - F1: 0.5271
sub_18:Test (Best Model) - Loss: 0.5952 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.5000 - F1: 0.4980
sub_18:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6562 - F1: 0.6559
sub_19:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5312 - F1: 0.4910
sub_19:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4688 - F1: 0.4231
sub_19:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6594 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6250 - F1: 0.6250
sub_20:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5938 - F1: 0.5934
sub_20:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.5938 - F1: 0.5836
sub_20:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.4688 - F1: 0.4640
sub_20:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6250 - F1: 0.6190
sub_20:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5455 - F1: 0.5455
sub_20:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.5758 - F1: 0.5754
sub_20:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.6970 - F1: 0.6898
sub_21:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.6250 - F1: 0.6190
sub_21:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.7109 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.5625 - F1: 0.5625
sub_21:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.6250 - F1: 0.6190
sub_21:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5625 - F1: 0.5608
sub_21:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.5608
sub_22:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5312 - F1: 0.5195
sub_22:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6562 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5152 - F1: 0.4762
sub_22:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.6970 - F1: 0.6591
sub_22:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.4545 - F1: 0.4417
sub_22:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.5625 - F1: 0.5625
sub_22:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5000 - F1: 0.4818
sub_22:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5312 - F1: 0.5308
sub_22:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6875 - F1: 0.6364
sub_22:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6250 - F1: 0.6000
sub_23:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7273 - F1: 0.7102
sub_23:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6970 - F1: 0.6944
sub_23:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6970 - F1: 0.6827
sub_23:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.5938 - F1: 0.5836
sub_23:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6250 - F1: 0.6235
sub_23:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5938 - F1: 0.5934
sub_23:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.5625 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.6970 - F1: 0.6944
sub_23:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.7576 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.7576 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.6114 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.7273 - F1: 0.6997
sub_24:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.4170
sub_24:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4375 - F1: 0.4170
sub_24:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.3438 - F1: 0.3431
sub_24:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 0.7327 - Accuracy: 0.3939 - F1: 0.3452
sub_25:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4242 - F1: 0.4221
sub_25:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.5438
sub_25:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.4242 - F1: 0.4242
sub_25:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.4921
sub_25:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.5312 - F1: 0.5271
sub_25:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4688 - F1: 0.4421
sub_25:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.5466
sub_25:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4375 - F1: 0.4375
sub_25:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5000 - F1: 0.4459
sub_25:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.5466
sub_26:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.6364 - F1: 0.6278
sub_26:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7273 - F1: 0.6997
sub_26:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.7273 - F1: 0.7179
sub_26:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.7576 - F1: 0.7273
sub_26:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.8182 - F1: 0.8167
sub_26:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6250 - F1: 0.6190
sub_26:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6875 - F1: 0.6825
sub_26:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.5625 - F1: 0.5625
sub_26:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.8438 - F1: 0.8359
sub_26:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.7812 - F1: 0.7810
sub_26:Test (Best Model) - Loss: 0.5802 - Accuracy: 0.7188 - F1: 0.7046
sub_26:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.9062 - F1: 0.9054
sub_27:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5455 - F1: 0.5299
sub_27:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6061 - F1: 0.6046
sub_27:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4848 - F1: 0.4672
sub_27:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4848 - F1: 0.4829
sub_27:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.4062 - F1: 0.4057
sub_27:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6250 - F1: 0.6235
sub_27:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.4688 - F1: 0.4555
sub_27:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.7302 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.7188 - F1: 0.6632
sub_28:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.4688 - F1: 0.3976
sub_28:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6562 - F1: 0.6476
sub_28:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.7214 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.6250 - F1: 0.6250
sub_28:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5000 - F1: 0.4980
sub_29:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.5681 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.5409 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.5161 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.5695 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.5404 - Accuracy: 0.8438 - F1: 0.8436
sub_29:Test (Best Model) - Loss: 0.5316 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.5368 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.5326 - Accuracy: 0.8125 - F1: 0.8057
sub_29:Test (Best Model) - Loss: 0.5070 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.4926 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.5340 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.8182 - F1: 0.8180
sub_29:Test (Best Model) - Loss: 0.5011 - Accuracy: 0.8788 - F1: 0.8759
sub_29:Test (Best Model) - Loss: 0.5688 - Accuracy: 0.9091 - F1: 0.9060

=== Summary Results ===

acc: 60.78 ± 8.71
F1: 59.47 ± 8.86
acc-in: 66.48 ± 7.76
F1-in: 64.90 ± 7.90
