lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.3934 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.4093 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.3357 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4425 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.8485 - F1: 0.8462
sub_1:Test (Best Model) - Loss: 0.4765 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.4034 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.3519 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3540 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.2577 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.3401 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3395 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.6309 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.7576 - F1: 0.7462
sub_2:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.7576 - F1: 0.7519
sub_2:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 0.6276 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6562 - F1: 0.6390
sub_2:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.6562 - F1: 0.6532
sub_2:Test (Best Model) - Loss: 0.5600 - Accuracy: 0.7500 - F1: 0.7229
sub_2:Test (Best Model) - Loss: 0.6023 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.5522 - Accuracy: 0.7273 - F1: 0.7263
sub_2:Test (Best Model) - Loss: 0.5756 - Accuracy: 0.7273 - F1: 0.7232
sub_2:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.6667 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6562 - F1: 0.6559
sub_3:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6562 - F1: 0.6476
sub_3:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.6364 - F1: 0.6192
sub_3:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.6364 - F1: 0.6192
sub_3:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.5455 - F1: 0.4457
sub_3:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6061 - F1: 0.5460
sub_3:Test (Best Model) - Loss: 0.9015 - Accuracy: 0.5758 - F1: 0.5658
sub_3:Test (Best Model) - Loss: 0.8172 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.7903 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 0.7887 - Accuracy: 0.5152 - F1: 0.4261
sub_3:Test (Best Model) - Loss: 0.8496 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 0.4457 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.3676 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4277 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3166 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.4715 - Accuracy: 0.7273 - F1: 0.6997
sub_4:Test (Best Model) - Loss: 0.4957 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.4781 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.5215 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.5211 - Accuracy: 0.7273 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.6970 - F1: 0.6944
sub_4:Test (Best Model) - Loss: 0.4706 - Accuracy: 0.8485 - F1: 0.8485
sub_4:Test (Best Model) - Loss: 0.4660 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.4226 - Accuracy: 0.8182 - F1: 0.8167
sub_5:Test (Best Model) - Loss: 0.7650 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.5998 - Accuracy: 0.5312 - F1: 0.4684
sub_5:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.5414 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.5490 - Accuracy: 0.6250 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.4062 - F1: 0.3552
sub_5:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6250 - F1: 0.6113
sub_6:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.8125 - F1: 0.8000
sub_6:Test (Best Model) - Loss: 0.5368 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 0.9410 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 1.0653 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.9099 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.9721 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.8672 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6364 - F1: 0.5909
sub_6:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.6970 - F1: 0.6591
sub_6:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.6061 - F1: 0.5815
sub_7:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6562 - F1: 0.6476
sub_7:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5312 - F1: 0.4684
sub_7:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.7500 - F1: 0.7091
sub_7:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.8652 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 0.7270 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.7381 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.7188 - F1: 0.7163
sub_7:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.7432 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.5761 - Accuracy: 0.7500 - F1: 0.7409
sub_7:Test (Best Model) - Loss: 0.5579 - Accuracy: 0.7188 - F1: 0.7117
sub_8:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.7188 - F1: 0.7163
sub_8:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.5097 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.5718 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.5311 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.7500 - F1: 0.7460
sub_8:Test (Best Model) - Loss: 0.5437 - Accuracy: 0.7500 - F1: 0.7229
sub_8:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.2860 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3644 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.3003 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.3341 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.3480 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4388 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.4707 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 0.5409 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.3946 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.4351 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.5159 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.4179 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.4707 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.2431 - Accuracy: 0.8438 - F1: 0.8359
sub_10:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.6875 - F1: 0.6667
sub_10:Test (Best Model) - Loss: 0.5508 - Accuracy: 0.7188 - F1: 0.7163
sub_10:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.6562 - F1: 0.6102
sub_10:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.5938 - F1: 0.5901
sub_10:Test (Best Model) - Loss: 0.7050 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.5000 - F1: 0.4459
sub_10:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.5000 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5758 - F1: 0.5722
sub_10:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6061 - F1: 0.5815
sub_10:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.6061 - F1: 0.6002
sub_10:Test (Best Model) - Loss: 0.7488 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 1.0152 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 0.8410 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.8228 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.8096 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.8988 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 0.5860 - Accuracy: 0.7273 - F1: 0.6997
sub_11:Test (Best Model) - Loss: 0.8022 - Accuracy: 0.4848 - F1: 0.4063
sub_11:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.7146 - Accuracy: 0.6667 - F1: 0.6654
sub_11:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.6364 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 0.7307 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.7144 - Accuracy: 0.5758 - F1: 0.4978
sub_12:Test (Best Model) - Loss: 0.4382 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.4281 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 0.4523 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.4142 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.4631 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.4692 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.4688 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5078 - Accuracy: 0.7812 - F1: 0.7625
sub_12:Test (Best Model) - Loss: 0.6155 - Accuracy: 0.6875 - F1: 0.6863
sub_12:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.8125 - F1: 0.8057
sub_12:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.3595 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3009 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.3260 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.3732 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.8182 - F1: 0.8139
sub_13:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.9091 - F1: 0.9091
sub_13:Test (Best Model) - Loss: 0.4873 - Accuracy: 0.8485 - F1: 0.8485
sub_13:Test (Best Model) - Loss: 0.5428 - Accuracy: 0.7273 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 0.4551 - Accuracy: 0.8182 - F1: 0.8167
sub_13:Test (Best Model) - Loss: 0.4313 - Accuracy: 0.8125 - F1: 0.8118
sub_13:Test (Best Model) - Loss: 0.4886 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.4735 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.5445 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.5019 - Accuracy: 0.8125 - F1: 0.8125
sub_14:Test (Best Model) - Loss: 0.4948 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 0.4610 - Accuracy: 0.9062 - F1: 0.9054
sub_14:Test (Best Model) - Loss: 0.4451 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.4168 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.4269 - Accuracy: 0.7812 - F1: 0.7519
sub_14:Test (Best Model) - Loss: 0.4539 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.4985 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.5538 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.4424 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.5732 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.5406 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5296 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.5206 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.5067 - Accuracy: 0.8438 - F1: 0.8303
sub_15:Test (Best Model) - Loss: 0.4766 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.4566 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.5030 - Accuracy: 0.7188 - F1: 0.6811
sub_15:Test (Best Model) - Loss: 0.5701 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.6250 - F1: 0.6235
sub_15:Test (Best Model) - Loss: 0.5794 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.5265 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.5509 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.5597 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.7918 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6250 - F1: 0.5362
sub_16:Test (Best Model) - Loss: 0.7290 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.7568 - Accuracy: 0.4375 - F1: 0.4375
sub_17:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.6667 - F1: 0.6330
sub_17:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.6667 - F1: 0.6617
sub_17:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.6364 - F1: 0.5696
sub_17:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 0.7876 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 0.7818 - Accuracy: 0.3333 - F1: 0.3278
sub_17:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.5000 - F1: 0.4921
sub_17:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 0.7979 - Accuracy: 0.5938 - F1: 0.5836
sub_17:Test (Best Model) - Loss: 0.7381 - Accuracy: 0.6250 - F1: 0.6113
sub_17:Test (Best Model) - Loss: 0.7157 - Accuracy: 0.6562 - F1: 0.6267
sub_18:Test (Best Model) - Loss: 0.4798 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.5044 - Accuracy: 0.7273 - F1: 0.7179
sub_18:Test (Best Model) - Loss: 0.4841 - Accuracy: 0.7273 - F1: 0.7263
sub_18:Test (Best Model) - Loss: 0.4448 - Accuracy: 0.8788 - F1: 0.8759
sub_18:Test (Best Model) - Loss: 0.3710 - Accuracy: 0.9091 - F1: 0.9077
sub_18:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.5399 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.5528 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.4482 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.4132 - Accuracy: 0.8438 - F1: 0.8303
sub_18:Test (Best Model) - Loss: 0.4656 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.4431 - Accuracy: 0.8750 - F1: 0.8730
sub_18:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.4135 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 0.3766 - Accuracy: 0.8438 - F1: 0.8398
sub_19:Test (Best Model) - Loss: 0.5880 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 0.5394 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.5954 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5749 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.5574 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.5487 - Accuracy: 0.6875 - F1: 0.6364
sub_19:Test (Best Model) - Loss: 0.6201 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.6875 - F1: 0.6537
sub_19:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.5000 - F1: 0.4667
sub_19:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.6250 - F1: 0.6250
sub_19:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.7188 - F1: 0.7163
sub_20:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.5294 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 0.5709 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.7518 - Accuracy: 0.6562 - F1: 0.6102
sub_20:Test (Best Model) - Loss: 0.5448 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.6667 - F1: 0.6617
sub_20:Test (Best Model) - Loss: 0.8239 - Accuracy: 0.6667 - F1: 0.6459
sub_20:Test (Best Model) - Loss: 0.5824 - Accuracy: 0.7879 - F1: 0.7664
sub_21:Test (Best Model) - Loss: 0.7252 - Accuracy: 0.5312 - F1: 0.5077
sub_21:Test (Best Model) - Loss: 0.8462 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 0.8157 - Accuracy: 0.4375 - F1: 0.4000
sub_21:Test (Best Model) - Loss: 0.7777 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.8136 - Accuracy: 0.5312 - F1: 0.4910
sub_21:Test (Best Model) - Loss: 0.7828 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.7690 - Accuracy: 0.5000 - F1: 0.3816
sub_21:Test (Best Model) - Loss: 0.8117 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.9515 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.9562 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.8948 - Accuracy: 0.3438 - F1: 0.3273
sub_21:Test (Best Model) - Loss: 0.8402 - Accuracy: 0.4062 - F1: 0.3552
sub_22:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.4442 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4655 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4761 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 0.5095 - Accuracy: 0.7812 - F1: 0.7519
sub_22:Test (Best Model) - Loss: 0.5638 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 0.5701 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5312 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5602 - Accuracy: 0.6970 - F1: 0.6591
sub_22:Test (Best Model) - Loss: 0.5834 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.5573 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 0.5134 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4965 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.4138 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.4109 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4680 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.3051 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.5928 - Accuracy: 0.6250 - F1: 0.6235
sub_23:Test (Best Model) - Loss: 0.5272 - Accuracy: 0.7188 - F1: 0.7185
sub_23:Test (Best Model) - Loss: 0.4677 - Accuracy: 0.8125 - F1: 0.8095
sub_23:Test (Best Model) - Loss: 0.4457 - Accuracy: 0.7812 - F1: 0.7793
sub_23:Test (Best Model) - Loss: 0.5098 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.3890 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.3409 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 0.3513 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.3887 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.3985 - Accuracy: 0.7879 - F1: 0.7664
sub_24:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.8385 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.7117 - Accuracy: 0.6562 - F1: 0.6559
sub_24:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.5938 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.7604 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.7446 - Accuracy: 0.3750 - F1: 0.3651
sub_24:Test (Best Model) - Loss: 0.7848 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7856 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.5938 - F1: 0.5901
sub_25:Test (Best Model) - Loss: 0.7839 - Accuracy: 0.5152 - F1: 0.4762
sub_25:Test (Best Model) - Loss: 0.7987 - Accuracy: 0.5152 - F1: 0.5111
sub_25:Test (Best Model) - Loss: 0.7577 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.8163 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 0.7893 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4688 - F1: 0.4231
sub_25:Test (Best Model) - Loss: 0.5747 - Accuracy: 0.7188 - F1: 0.7046
sub_25:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.5625 - F1: 0.5608
sub_25:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6030 - Accuracy: 0.7812 - F1: 0.7625
sub_25:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.6250 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5625 - F1: 0.4589
sub_25:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6250 - F1: 0.5844
sub_26:Test (Best Model) - Loss: 0.4177 - Accuracy: 0.7879 - F1: 0.7806
sub_26:Test (Best Model) - Loss: 0.4107 - Accuracy: 0.8485 - F1: 0.8390
sub_26:Test (Best Model) - Loss: 0.3656 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.3915 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.3161 - Accuracy: 0.9091 - F1: 0.9060
sub_26:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.6875 - F1: 0.6875
sub_26:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.5467 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.4376 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.4356 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 0.2908 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3372 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.3502 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.2754 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.2544 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.6667 - F1: 0.6330
sub_27:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6223 - Accuracy: 0.6667 - F1: 0.6617
sub_27:Test (Best Model) - Loss: 0.5867 - Accuracy: 0.6364 - F1: 0.5696
sub_27:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 0.7876 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 0.7818 - Accuracy: 0.3333 - F1: 0.3278
sub_27:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.5000 - F1: 0.4921
sub_27:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 0.7979 - Accuracy: 0.5938 - F1: 0.5836
sub_27:Test (Best Model) - Loss: 0.7381 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.7157 - Accuracy: 0.6562 - F1: 0.6267
sub_28:Test (Best Model) - Loss: 0.5447 - Accuracy: 0.7812 - F1: 0.7758
sub_28:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.7500 - F1: 0.7409
sub_28:Test (Best Model) - Loss: 0.7760 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.9182 - Accuracy: 0.5938 - F1: 0.5393
sub_28:Test (Best Model) - Loss: 0.8359 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.8778 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.9784 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 1.0114 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.7882 - Accuracy: 0.6250 - F1: 0.5844
sub_28:Test (Best Model) - Loss: 1.1830 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.8660 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.7610 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 0.8010 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 0.7928 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.7929 - Accuracy: 0.4688 - F1: 0.3976
sub_29:Test (Best Model) - Loss: 0.2685 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3054 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3062 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.3081 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.2832 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.1758 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2201 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.1835 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.1766 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1709 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.2419 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2453 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.2057 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1935 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.2123 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 68.39 ± 11.68
F1: 66.24 ± 12.61
acc-in: 75.07 ± 8.49
F1-in: 72.90 ± 9.23
