lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5407 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.6562 - F1: 0.6476
sub_1:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.7500 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.7500 - F1: 0.7229
sub_1:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.5287 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.5642 - Accuracy: 0.6970 - F1: 0.6413
sub_1:Test (Best Model) - Loss: 0.4994 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.8438 - F1: 0.8398
sub_1:Test (Best Model) - Loss: 0.5308 - Accuracy: 0.8125 - F1: 0.8095
sub_1:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.4771 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.8438 - F1: 0.8398
sub_2:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.6364 - F1: 0.6071
sub_2:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7576 - F1: 0.7556
sub_2:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.4909
sub_2:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5938 - F1: 0.5836
sub_2:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.6875 - F1: 0.6364
sub_2:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6250 - F1: 0.5844
sub_2:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.6061 - F1: 0.6061
sub_2:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5758 - F1: 0.5558
sub_2:Test (Best Model) - Loss: 0.5683 - Accuracy: 0.7273 - F1: 0.7263
sub_2:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.7273 - F1: 0.7263
sub_3:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5312 - F1: 0.5271
sub_3:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5312 - F1: 0.5308
sub_3:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.5000
sub_3:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5152 - F1: 0.4923
sub_3:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.3939 - F1: 0.3889
sub_3:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.5758 - F1: 0.5658
sub_3:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.5758 - F1: 0.4225
sub_3:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.7650 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.7438 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 0.7489 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.7453 - Accuracy: 0.5455 - F1: 0.4995
sub_3:Test (Best Model) - Loss: 0.8351 - Accuracy: 0.3939 - F1: 0.3934
sub_4:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.5547 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.5855 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.4981 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.6364 - F1: 0.5696
sub_4:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.6970 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.5877 - Accuracy: 0.6667 - F1: 0.6459
sub_4:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6667 - F1: 0.6617
sub_4:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.7879 - F1: 0.7879
sub_4:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.6061 - F1: 0.5815
sub_5:Test (Best Model) - Loss: 0.7555 - Accuracy: 0.4375 - F1: 0.4286
sub_5:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.7784 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.4688 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.5938 - F1: 0.5733
sub_5:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5312 - F1: 0.4910
sub_6:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.5938 - F1: 0.5901
sub_6:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.6875 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.6106 - Accuracy: 0.7812 - F1: 0.7625
sub_6:Test (Best Model) - Loss: 0.8002 - Accuracy: 0.4242 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 0.9122 - Accuracy: 0.4848 - F1: 0.3718
sub_6:Test (Best Model) - Loss: 0.7903 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.8353 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6364 - F1: 0.6192
sub_6:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.7273 - F1: 0.6997
sub_6:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6061 - F1: 0.5815
sub_7:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5625 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.6562 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.7463 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.7193 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7425 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.7198 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.6562 - F1: 0.6559
sub_7:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.6875 - F1: 0.6825
sub_7:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5312 - F1: 0.4684
sub_8:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.5312 - F1: 0.4910
sub_8:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.6250 - F1: 0.6235
sub_8:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6250 - F1: 0.5844
sub_8:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4688 - F1: 0.4640
sub_8:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.4797 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.5211 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 0.4365 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.4981 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.5965 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.5673 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.5771 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5312 - F1: 0.4910
sub_9:Test (Best Model) - Loss: 0.4991 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.6099 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.5782 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.7500 - F1: 0.7460
sub_10:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.5000 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.5938 - F1: 0.5589
sub_10:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5625 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.3438 - F1: 0.3431
sub_10:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.5152 - F1: 0.4923
sub_10:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.7423 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.7549 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.7525 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6364 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.5152 - F1: 0.4545
sub_11:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6364 - F1: 0.6333
sub_11:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.6364 - F1: 0.5909
sub_11:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5758 - F1: 0.5227
sub_12:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.5914 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.5718 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.5513 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6562 - F1: 0.6267
sub_13:Test (Best Model) - Loss: 0.4709 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.5559 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.5612 - Accuracy: 0.7500 - F1: 0.7500
sub_13:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.8125 - F1: 0.8000
sub_13:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.6970 - F1: 0.6967
sub_13:Test (Best Model) - Loss: 0.5721 - Accuracy: 0.8485 - F1: 0.8479
sub_13:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.6667 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6061 - F1: 0.6002
sub_13:Test (Best Model) - Loss: 0.6121 - Accuracy: 0.6667 - F1: 0.6553
sub_13:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.5097 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.6875 - F1: 0.6537
sub_13:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5625 - F1: 0.5608
sub_14:Test (Best Model) - Loss: 0.6003 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.6250 - F1: 0.6235
sub_14:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6562 - F1: 0.6390
sub_14:Test (Best Model) - Loss: 0.6072 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.5763 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.5906 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5895 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.7500 - F1: 0.7490
sub_15:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.5724 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6047 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.5625 - F1: 0.5625
sub_15:Test (Best Model) - Loss: 0.5965 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.5961 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4688 - F1: 0.4231
sub_16:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6283 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4375 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 0.7273 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.7284 - Accuracy: 0.3750 - F1: 0.3651
sub_17:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.5758 - F1: 0.5754
sub_17:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.6061 - F1: 0.5460
sub_17:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.5455 - F1: 0.5455
sub_17:Test (Best Model) - Loss: 0.7530 - Accuracy: 0.5758 - F1: 0.5722
sub_17:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4848 - F1: 0.4328
sub_17:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.4545 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5312 - F1: 0.5271
sub_17:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.5938 - F1: 0.5836
sub_17:Test (Best Model) - Loss: 0.7221 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.6250 - F1: 0.6000
sub_17:Test (Best Model) - Loss: 0.7282 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.6364 - F1: 0.6278
sub_18:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.6970 - F1: 0.6898
sub_18:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.7273 - F1: 0.7232
sub_18:Test (Best Model) - Loss: 0.5691 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.5992 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.6161 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6021 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.5313 - Accuracy: 0.7812 - F1: 0.7758
sub_18:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.5292 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 0.6143 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6235 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.5000 - F1: 0.4667
sub_19:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6875 - F1: 0.6667
sub_19:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.5312 - F1: 0.5271
sub_20:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 0.5963 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.6250 - F1: 0.5636
sub_20:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6470 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.5758 - F1: 0.5658
sub_20:Test (Best Model) - Loss: 0.7529 - Accuracy: 0.6061 - F1: 0.5926
sub_20:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6061 - F1: 0.5926
sub_20:Test (Best Model) - Loss: 0.7751 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 0.6121 - Accuracy: 0.6970 - F1: 0.6827
sub_21:Test (Best Model) - Loss: 0.7242 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 0.7631 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 0.7206 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.4688 - F1: 0.3976
sub_21:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.7466 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7590 - Accuracy: 0.5000 - F1: 0.4182
sub_21:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.5000 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.7629 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 0.7899 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.8172 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.7831 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.7600 - Accuracy: 0.4688 - F1: 0.4421
sub_22:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.6562 - F1: 0.6390
sub_22:Test (Best Model) - Loss: 0.5952 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.5881 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.6875 - F1: 0.6364
sub_22:Test (Best Model) - Loss: 0.6050 - Accuracy: 0.6562 - F1: 0.6102
sub_22:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5758 - F1: 0.4653
sub_22:Test (Best Model) - Loss: 0.6203 - Accuracy: 0.6364 - F1: 0.5696
sub_22:Test (Best Model) - Loss: 0.6082 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6667 - F1: 0.6330
sub_22:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5938 - F1: 0.5901
sub_22:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.5938 - F1: 0.5733
sub_22:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.6875 - F1: 0.6364
sub_22:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.6562 - F1: 0.6532
sub_23:Test (Best Model) - Loss: 0.5664 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.5606 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.6061 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 0.5352 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.6053 - Accuracy: 0.6875 - F1: 0.6761
sub_23:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.5293 - Accuracy: 0.8125 - F1: 0.8118
sub_23:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.6250 - F1: 0.6190
sub_23:Test (Best Model) - Loss: 0.5718 - Accuracy: 0.7273 - F1: 0.7102
sub_23:Test (Best Model) - Loss: 0.5534 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.5283 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.7273 - F1: 0.6857
sub_24:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.7613 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7311 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.7175 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.6562 - F1: 0.6532
sub_24:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.7433 - Accuracy: 0.4062 - F1: 0.4010
sub_24:Test (Best Model) - Loss: 0.7369 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 0.7486 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.7484 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.7893 - Accuracy: 0.4242 - F1: 0.3883
sub_25:Test (Best Model) - Loss: 0.7316 - Accuracy: 0.4545 - F1: 0.4540
sub_25:Test (Best Model) - Loss: 0.7175 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.4848 - F1: 0.4063
sub_25:Test (Best Model) - Loss: 0.7382 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.5312 - F1: 0.5271
sub_25:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.6562 - F1: 0.6532
sub_25:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.6875 - F1: 0.6667
sub_25:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6562 - F1: 0.6390
sub_26:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.7273 - F1: 0.7179
sub_26:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.7273 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 0.5665 - Accuracy: 0.7273 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.6667 - F1: 0.6159
sub_26:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7273 - F1: 0.6857
sub_26:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5813 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.5735 - Accuracy: 0.7188 - F1: 0.7117
sub_26:Test (Best Model) - Loss: 0.5956 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.4906 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.4713 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.4934 - Accuracy: 0.7812 - F1: 0.7625
sub_26:Test (Best Model) - Loss: 0.4832 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.4602 - Accuracy: 0.9375 - F1: 0.9352
sub_27:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.5758 - F1: 0.5754
sub_27:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.6061 - F1: 0.5460
sub_27:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.4242 - F1: 0.4221
sub_27:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.5455 - F1: 0.5455
sub_27:Test (Best Model) - Loss: 0.7530 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4848 - F1: 0.4328
sub_27:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.4545 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5312 - F1: 0.5271
sub_27:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.5938 - F1: 0.5836
sub_27:Test (Best Model) - Loss: 0.7221 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.6250 - F1: 0.6000
sub_27:Test (Best Model) - Loss: 0.7282 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.6875 - F1: 0.6863
sub_28:Test (Best Model) - Loss: 0.7370 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 0.7616 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 0.7571 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 0.7307 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.7887 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.7765 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.6250 - F1: 0.5844
sub_28:Test (Best Model) - Loss: 1.0142 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.7367 - Accuracy: 0.4375 - F1: 0.4375
sub_28:Test (Best Model) - Loss: 0.7304 - Accuracy: 0.4688 - F1: 0.3976
sub_28:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.7257 - Accuracy: 0.4375 - F1: 0.3766
sub_29:Test (Best Model) - Loss: 0.3799 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.4799 - Accuracy: 0.7188 - F1: 0.7046
sub_29:Test (Best Model) - Loss: 0.4576 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.4376 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.4578 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.4570 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.3587 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.4260 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3621 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.4419 - Accuracy: 0.8788 - F1: 0.8759
sub_29:Test (Best Model) - Loss: 0.4672 - Accuracy: 0.7879 - F1: 0.7806
sub_29:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.3789 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 62.56 ± 9.46
F1: 60.29 ± 9.84
acc-in: 69.01 ± 6.97
F1-in: 66.83 ± 7.43
