lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.4343 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.4835 - Accuracy: 0.8438 - F1: 0.8424
sub_1:Test (Best Model) - Loss: 0.4238 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.4017 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.4166 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.4056 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.3940 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.4536 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4016 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3065 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4011 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.3925 - Accuracy: 0.8438 - F1: 0.8398
sub_2:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6090 - Accuracy: 0.8182 - F1: 0.8139
sub_2:Test (Best Model) - Loss: 0.6202 - Accuracy: 0.7576 - F1: 0.7462
sub_2:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.5938 - F1: 0.5589
sub_2:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.6875 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 0.5833 - Accuracy: 0.7188 - F1: 0.6811
sub_2:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.7500 - F1: 0.7091
sub_2:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.5674 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.6970 - F1: 0.6967
sub_3:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6250 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.6562 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6667 - F1: 0.6617
sub_3:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5455 - F1: 0.4457
sub_3:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.8307 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.7585 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 0.7585 - Accuracy: 0.5152 - F1: 0.4923
sub_3:Test (Best Model) - Loss: 0.7645 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.4242 - F1: 0.4157
sub_4:Test (Best Model) - Loss: 0.5212 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.3977 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4077 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.3772 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4135 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.7273 - F1: 0.6997
sub_4:Test (Best Model) - Loss: 0.4913 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.4690 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.5281 - Accuracy: 0.7879 - F1: 0.7879
sub_4:Test (Best Model) - Loss: 0.4744 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.4668 - Accuracy: 0.7576 - F1: 0.7574
sub_5:Test (Best Model) - Loss: 0.8571 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.7801 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.5862 - Accuracy: 0.5312 - F1: 0.4684
sub_5:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.5312 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.5744 - Accuracy: 0.4688 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.5000 - F1: 0.4818
sub_5:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5938 - F1: 0.5836
sub_6:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.6562 - F1: 0.6476
sub_6:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 0.6228 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.6875 - F1: 0.6761
sub_6:Test (Best Model) - Loss: 0.5757 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 0.8707 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.9633 - Accuracy: 0.3939 - F1: 0.2826
sub_6:Test (Best Model) - Loss: 0.8650 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.9491 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.7877 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5152 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6970 - F1: 0.6726
sub_6:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.6667 - F1: 0.6459
sub_6:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.7273 - F1: 0.6857
sub_6:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6667 - F1: 0.6553
sub_7:Test (Best Model) - Loss: 0.5921 - Accuracy: 0.7188 - F1: 0.7046
sub_7:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 0.7297 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.8312 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 0.7417 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.7465 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.7689 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.7500 - F1: 0.7460
sub_8:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.7812 - F1: 0.7625
sub_8:Test (Best Model) - Loss: 0.6202 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.5008 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.5664 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.5325 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.5672 - Accuracy: 0.7188 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.5449 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.3359 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4090 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.3533 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.3531 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.3736 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.4967 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.5637 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.4742 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4936 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.5892 - Accuracy: 0.5938 - F1: 0.5589
sub_9:Test (Best Model) - Loss: 0.4030 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.5039 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.4924 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.2895 - Accuracy: 0.8750 - F1: 0.8704
sub_10:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.7188 - F1: 0.7163
sub_10:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.7322 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5938 - F1: 0.5901
sub_10:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5625 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 0.7407 - Accuracy: 0.5455 - F1: 0.5455
sub_10:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.5758 - F1: 0.5722
sub_10:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6061 - F1: 0.5926
sub_10:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.8752 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.8004 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.8203 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.7257 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.8957 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.6364 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.6364 - F1: 0.6360
sub_11:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6667 - F1: 0.6330
sub_11:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5758 - F1: 0.4978
sub_12:Test (Best Model) - Loss: 0.4761 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.4437 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.5087 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.4633 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.4888 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5154 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.5344 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.4657 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.5846 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 0.6085 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.7188 - F1: 0.6811
sub_13:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.3730 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3114 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.3154 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.4255 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7576 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.4576 - Accuracy: 0.8485 - F1: 0.8485
sub_13:Test (Best Model) - Loss: 0.5364 - Accuracy: 0.8182 - F1: 0.8180
sub_13:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.6970 - F1: 0.6827
sub_13:Test (Best Model) - Loss: 0.5342 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 0.5482 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.4671 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.4356 - Accuracy: 0.8438 - F1: 0.8398
sub_13:Test (Best Model) - Loss: 0.5214 - Accuracy: 0.7188 - F1: 0.6811
sub_13:Test (Best Model) - Loss: 0.4562 - Accuracy: 0.8750 - F1: 0.8704
sub_14:Test (Best Model) - Loss: 0.5446 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.4972 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.5409 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.5066 - Accuracy: 0.8438 - F1: 0.8424
sub_14:Test (Best Model) - Loss: 0.4742 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 0.5018 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 0.4802 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 0.4955 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.5019 - Accuracy: 0.7500 - F1: 0.7229
sub_14:Test (Best Model) - Loss: 0.5411 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.5774 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.5938 - F1: 0.5733
sub_14:Test (Best Model) - Loss: 0.4854 - Accuracy: 0.7812 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.5405 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.7812 - F1: 0.7703
sub_15:Test (Best Model) - Loss: 0.5222 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.5117 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.4839 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.5174 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6006 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.6562 - F1: 0.6390
sub_15:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6562 - F1: 0.6559
sub_16:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.5453 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.6271 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.7272 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.6250 - F1: 0.5844
sub_16:Test (Best Model) - Loss: 0.7627 - Accuracy: 0.4062 - F1: 0.3914
sub_17:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6364 - F1: 0.5909
sub_17:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6667 - F1: 0.6553
sub_17:Test (Best Model) - Loss: 0.7335 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.4545 - F1: 0.4500
sub_17:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.6061 - F1: 0.6046
sub_17:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.6250 - F1: 0.6000
sub_17:Test (Best Model) - Loss: 0.7933 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.5312 - F1: 0.4910
sub_17:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.5140 - Accuracy: 0.7879 - F1: 0.7871
sub_18:Test (Best Model) - Loss: 0.5494 - Accuracy: 0.7273 - F1: 0.7179
sub_18:Test (Best Model) - Loss: 0.5116 - Accuracy: 0.7879 - F1: 0.7871
sub_18:Test (Best Model) - Loss: 0.5037 - Accuracy: 0.8788 - F1: 0.8759
sub_18:Test (Best Model) - Loss: 0.4719 - Accuracy: 0.7879 - F1: 0.7847
sub_18:Test (Best Model) - Loss: 0.5133 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.4824 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.5142 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.4510 - Accuracy: 0.8750 - F1: 0.8704
sub_18:Test (Best Model) - Loss: 0.4239 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.4726 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.4150 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.4591 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.4636 - Accuracy: 0.8125 - F1: 0.8095
sub_19:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.5617 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.5925 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6562 - F1: 0.6559
sub_19:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.7812 - F1: 0.7625
sub_19:Test (Best Model) - Loss: 0.6072 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.6053 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.5523 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.8125 - F1: 0.8057
sub_20:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.6250 - F1: 0.6235
sub_20:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.6278 - Accuracy: 0.6875 - F1: 0.6825
sub_20:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.5859 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.7447 - Accuracy: 0.5152 - F1: 0.5038
sub_20:Test (Best Model) - Loss: 0.7816 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 0.8150 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.7273 - F1: 0.7102
sub_21:Test (Best Model) - Loss: 0.7354 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 0.8312 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 0.8222 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.7771 - Accuracy: 0.4688 - F1: 0.3976
sub_21:Test (Best Model) - Loss: 0.7495 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.7762 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 0.7680 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.7807 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 0.7608 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.7776 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.8623 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7997 - Accuracy: 0.3750 - F1: 0.3651
sub_22:Test (Best Model) - Loss: 0.4756 - Accuracy: 0.7812 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.5065 - Accuracy: 0.8438 - F1: 0.8359
sub_22:Test (Best Model) - Loss: 0.5046 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4812 - Accuracy: 0.6562 - F1: 0.5883
sub_22:Test (Best Model) - Loss: 0.5138 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.5832 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5448 - Accuracy: 0.7273 - F1: 0.6857
sub_22:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.5615 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.5602 - Accuracy: 0.8125 - F1: 0.8118
sub_22:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7500 - F1: 0.7091
sub_22:Test (Best Model) - Loss: 0.5112 - Accuracy: 0.8438 - F1: 0.8398
sub_23:Test (Best Model) - Loss: 0.4524 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.4227 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4984 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.3531 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.5401 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 0.4976 - Accuracy: 0.7500 - F1: 0.7460
sub_23:Test (Best Model) - Loss: 0.4608 - Accuracy: 0.7500 - F1: 0.7490
sub_23:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.4160 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4697 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4386 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4527 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.7273 - F1: 0.6857
sub_24:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.7444 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.7316 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6562 - F1: 0.6390
sub_24:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.6875 - F1: 0.6875
sub_24:Test (Best Model) - Loss: 0.7522 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.7608 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 0.7582 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 0.7600 - Accuracy: 0.5938 - F1: 0.5901
sub_25:Test (Best Model) - Loss: 0.8084 - Accuracy: 0.3939 - F1: 0.3654
sub_25:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.5455 - F1: 0.5455
sub_25:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.8140 - Accuracy: 0.3939 - F1: 0.2826
sub_25:Test (Best Model) - Loss: 0.8201 - Accuracy: 0.4848 - F1: 0.4527
sub_25:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.5000 - F1: 0.4818
sub_25:Test (Best Model) - Loss: 0.6327 - Accuracy: 0.6875 - F1: 0.6761
sub_25:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6562 - F1: 0.6476
sub_25:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.6562 - F1: 0.6102
sub_25:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.5938 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.6875 - F1: 0.6364
sub_26:Test (Best Model) - Loss: 0.4799 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.4357 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.4106 - Accuracy: 0.8788 - F1: 0.8731
sub_26:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.7500 - F1: 0.7490
sub_26:Test (Best Model) - Loss: 0.5463 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5684 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5007 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.3769 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.4009 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.3977 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.3688 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.2814 - Accuracy: 0.9062 - F1: 0.9015
sub_27:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6232 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.6364 - F1: 0.5909
sub_27:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.7335 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.4545 - F1: 0.4500
sub_27:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.6061 - F1: 0.6046
sub_27:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.6250 - F1: 0.6000
sub_27:Test (Best Model) - Loss: 0.7933 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.5312 - F1: 0.4910
sub_27:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.7188 - F1: 0.7117
sub_28:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.7188 - F1: 0.7117
sub_28:Test (Best Model) - Loss: 0.7711 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 0.8703 - Accuracy: 0.5938 - F1: 0.5135
sub_28:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.8158 - Accuracy: 0.5938 - F1: 0.5733
sub_28:Test (Best Model) - Loss: 0.8681 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.8723 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.5938 - F1: 0.5393
sub_28:Test (Best Model) - Loss: 0.9935 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.8028 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.7748 - Accuracy: 0.4062 - F1: 0.3914
sub_28:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.4062 - F1: 0.3764
sub_28:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 0.7603 - Accuracy: 0.4688 - F1: 0.3976
sub_29:Test (Best Model) - Loss: 0.2761 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3386 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3224 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3273 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3336 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3128 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.2568 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.1843 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2382 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.2585 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.3128 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2627 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.2063 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2855 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2575 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 66.80 ± 11.44
F1: 64.54 ± 12.22
acc-in: 72.86 ± 8.68
F1-in: 70.64 ± 9.25
