lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.3877 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.4454 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.3699 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3705 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.4110 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.3406 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.3681 - Accuracy: 0.8485 - F1: 0.8462
sub_1:Test (Best Model) - Loss: 0.4878 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.3397 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.3744 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3515 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.2301 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.3326 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.3122 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.7879 - F1: 0.7847
sub_2:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.7576 - F1: 0.7519
sub_2:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.7879 - F1: 0.7746
sub_2:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 0.5875 - Accuracy: 0.6250 - F1: 0.6113
sub_2:Test (Best Model) - Loss: 0.5911 - Accuracy: 0.6875 - F1: 0.6364
sub_2:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.6875 - F1: 0.6537
sub_2:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.6061 - F1: 0.5815
sub_2:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.7576 - F1: 0.7574
sub_2:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.7273 - F1: 0.7179
sub_2:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.6562 - F1: 0.6559
sub_3:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6562 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.6667 - F1: 0.6654
sub_3:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.6061 - F1: 0.5196
sub_3:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6667 - F1: 0.6459
sub_3:Test (Best Model) - Loss: 0.8232 - Accuracy: 0.5758 - F1: 0.5754
sub_3:Test (Best Model) - Loss: 0.7857 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.7396 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.8408 - Accuracy: 0.5455 - F1: 0.4995
sub_3:Test (Best Model) - Loss: 0.9274 - Accuracy: 0.5152 - F1: 0.5147
sub_4:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 0.3314 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4275 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3329 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.3623 - Accuracy: 0.8485 - F1: 0.8390
sub_4:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.7576 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.4673 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.4378 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.6061 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.4659 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.5615 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.5426 - Accuracy: 0.6667 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.5029 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.4624 - Accuracy: 0.8182 - F1: 0.8180
sub_5:Test (Best Model) - Loss: 0.7968 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.8715 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.4375 - F1: 0.3455
sub_5:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.5853 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.5000 - F1: 0.4921
sub_5:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.4375 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.5999 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6562 - F1: 0.6559
sub_6:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.7500 - F1: 0.7333
sub_6:Test (Best Model) - Loss: 0.5895 - Accuracy: 0.7500 - F1: 0.7409
sub_6:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.7812 - F1: 0.7625
sub_6:Test (Best Model) - Loss: 0.9650 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 1.0360 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.9097 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 0.9820 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.8580 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 0.5979 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7273 - F1: 0.6997
sub_6:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.6970 - F1: 0.6591
sub_6:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.6364 - F1: 0.5909
sub_7:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.7500 - F1: 0.7490
sub_7:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5938 - F1: 0.5589
sub_7:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.4375 - F1: 0.4375
sub_7:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7387 - Accuracy: 0.4688 - F1: 0.4421
sub_7:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.7466 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.5722 - Accuracy: 0.7500 - F1: 0.7409
sub_7:Test (Best Model) - Loss: 0.5873 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.5266 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.5586 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.4799 - Accuracy: 0.8438 - F1: 0.8303
sub_8:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.5779 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 0.6327 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.5499 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.5666 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.5026 - Accuracy: 0.7500 - F1: 0.7490
sub_8:Test (Best Model) - Loss: 0.5549 - Accuracy: 0.7500 - F1: 0.7229
sub_8:Test (Best Model) - Loss: 0.4699 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.2854 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3248 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.2997 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.2799 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3188 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.4171 - Accuracy: 0.8438 - F1: 0.8424
sub_9:Test (Best Model) - Loss: 0.4864 - Accuracy: 0.7500 - F1: 0.7490
sub_9:Test (Best Model) - Loss: 0.5459 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.4222 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.4870 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.4924 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.3791 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.4722 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.4685 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.2370 - Accuracy: 0.8438 - F1: 0.8359
sub_10:Test (Best Model) - Loss: 0.5689 - Accuracy: 0.6875 - F1: 0.6537
sub_10:Test (Best Model) - Loss: 0.5406 - Accuracy: 0.7188 - F1: 0.7117
sub_10:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.6562 - F1: 0.6476
sub_10:Test (Best Model) - Loss: 0.5815 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.6295 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.5931 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.7188 - F1: 0.7185
sub_10:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 0.7195 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.7197 - Accuracy: 0.5152 - F1: 0.4923
sub_10:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.6364 - F1: 0.6192
sub_10:Test (Best Model) - Loss: 0.5945 - Accuracy: 0.6667 - F1: 0.6553
sub_10:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.9602 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 0.9208 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.8335 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.8094 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.8803 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.5632 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.7868 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.6667 - F1: 0.6459
sub_11:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.6364 - F1: 0.5909
sub_11:Test (Best Model) - Loss: 0.7366 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5758 - F1: 0.4978
sub_12:Test (Best Model) - Loss: 0.4332 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.4310 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.4057 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.4275 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.4711 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5456 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.4295 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5468 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 0.5146 - Accuracy: 0.7812 - F1: 0.7758
sub_12:Test (Best Model) - Loss: 0.5854 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.3673 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.3864 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.3593 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.3279 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.4075 - Accuracy: 0.8182 - F1: 0.8139
sub_13:Test (Best Model) - Loss: 0.3851 - Accuracy: 0.9394 - F1: 0.9380
sub_13:Test (Best Model) - Loss: 0.4755 - Accuracy: 0.8485 - F1: 0.8485
sub_13:Test (Best Model) - Loss: 0.5550 - Accuracy: 0.6667 - F1: 0.6459
sub_13:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.7879 - F1: 0.7847
sub_13:Test (Best Model) - Loss: 0.5125 - Accuracy: 0.7188 - F1: 0.7163
sub_13:Test (Best Model) - Loss: 0.4589 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.4646 - Accuracy: 0.7500 - F1: 0.7333
sub_13:Test (Best Model) - Loss: 0.3832 - Accuracy: 0.9062 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.4920 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.4904 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.5508 - Accuracy: 0.7812 - F1: 0.7810
sub_14:Test (Best Model) - Loss: 0.4537 - Accuracy: 0.8438 - F1: 0.8359
sub_14:Test (Best Model) - Loss: 0.4498 - Accuracy: 0.9375 - F1: 0.9365
sub_14:Test (Best Model) - Loss: 0.4251 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.4069 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 0.4225 - Accuracy: 0.8125 - F1: 0.8000
sub_14:Test (Best Model) - Loss: 0.3843 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.4564 - Accuracy: 0.7500 - F1: 0.7091
sub_14:Test (Best Model) - Loss: 0.4743 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 0.4155 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.5294 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5040 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.5547 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.5797 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.5194 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 0.5128 - Accuracy: 0.8750 - F1: 0.8667
sub_15:Test (Best Model) - Loss: 0.4221 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.5643 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.4308 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.4600 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5312 - F1: 0.4910
sub_15:Test (Best Model) - Loss: 0.5735 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.5259 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.7366 - Accuracy: 0.4375 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.7339 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.7548 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.8147 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6667 - F1: 0.6459
sub_17:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.5989 - Accuracy: 0.6667 - F1: 0.6459
sub_17:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6970 - F1: 0.6591
sub_17:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.6970 - F1: 0.6898
sub_17:Test (Best Model) - Loss: 0.7232 - Accuracy: 0.4242 - F1: 0.4157
sub_17:Test (Best Model) - Loss: 0.7288 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.8399 - Accuracy: 0.4545 - F1: 0.4417
sub_17:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6364 - F1: 0.6071
sub_17:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4545 - F1: 0.4417
sub_17:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.5608
sub_17:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.5938 - F1: 0.5733
sub_17:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.6250 - F1: 0.6113
sub_17:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.6250 - F1: 0.6190
sub_18:Test (Best Model) - Loss: 0.4521 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.4412 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.4716 - Accuracy: 0.8182 - F1: 0.8167
sub_18:Test (Best Model) - Loss: 0.4098 - Accuracy: 0.9091 - F1: 0.9077
sub_18:Test (Best Model) - Loss: 0.3614 - Accuracy: 0.8182 - F1: 0.8167
sub_18:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.8750 - F1: 0.8704
sub_18:Test (Best Model) - Loss: 0.5069 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.7812 - F1: 0.7810
sub_18:Test (Best Model) - Loss: 0.4333 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.4621 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.4498 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.4424 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.3598 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.3929 - Accuracy: 0.8438 - F1: 0.8424
sub_18:Test (Best Model) - Loss: 0.3838 - Accuracy: 0.8750 - F1: 0.8704
sub_19:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.5961 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.5089 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.5645 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.4688 - F1: 0.4555
sub_19:Test (Best Model) - Loss: 0.7191 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.7188 - F1: 0.6811
sub_19:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 0.5248 - Accuracy: 0.8125 - F1: 0.8057
sub_20:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.8438 - F1: 0.8359
sub_20:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.5290 - Accuracy: 0.7812 - F1: 0.7519
sub_20:Test (Best Model) - Loss: 0.5775 - Accuracy: 0.7812 - F1: 0.7625
sub_20:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.5212 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.5758 - F1: 0.5658
sub_20:Test (Best Model) - Loss: 0.7323 - Accuracy: 0.6970 - F1: 0.6726
sub_20:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6667 - F1: 0.6617
sub_20:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.6970 - F1: 0.6726
sub_20:Test (Best Model) - Loss: 0.5813 - Accuracy: 0.7576 - F1: 0.7462
sub_21:Test (Best Model) - Loss: 0.7919 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.8883 - Accuracy: 0.3750 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 0.8370 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 0.7616 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.8089 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.8201 - Accuracy: 0.5625 - F1: 0.4589
sub_21:Test (Best Model) - Loss: 0.7478 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.3438 - F1: 0.3273
sub_21:Test (Best Model) - Loss: 0.8228 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.8682 - Accuracy: 0.2500 - F1: 0.2381
sub_21:Test (Best Model) - Loss: 0.9449 - Accuracy: 0.3438 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 0.8193 - Accuracy: 0.4375 - F1: 0.3766
sub_22:Test (Best Model) - Loss: 0.4345 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.4532 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4589 - Accuracy: 0.7500 - F1: 0.7333
sub_22:Test (Best Model) - Loss: 0.4499 - Accuracy: 0.6875 - F1: 0.6364
sub_22:Test (Best Model) - Loss: 0.4754 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.5504 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 0.4954 - Accuracy: 0.7576 - F1: 0.7381
sub_22:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.7273 - F1: 0.6997
sub_22:Test (Best Model) - Loss: 0.5498 - Accuracy: 0.6875 - F1: 0.6825
sub_22:Test (Best Model) - Loss: 0.5314 - Accuracy: 0.8125 - F1: 0.8095
sub_22:Test (Best Model) - Loss: 0.4838 - Accuracy: 0.8125 - F1: 0.8000
sub_22:Test (Best Model) - Loss: 0.5269 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 0.4605 - Accuracy: 0.8750 - F1: 0.8730
sub_23:Test (Best Model) - Loss: 0.3683 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 0.4062 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.3987 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.4633 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.3143 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.5346 - Accuracy: 0.6875 - F1: 0.6875
sub_23:Test (Best Model) - Loss: 0.4884 - Accuracy: 0.8125 - F1: 0.8057
sub_23:Test (Best Model) - Loss: 0.4603 - Accuracy: 0.8438 - F1: 0.8424
sub_23:Test (Best Model) - Loss: 0.4506 - Accuracy: 0.8125 - F1: 0.8118
sub_23:Test (Best Model) - Loss: 0.4918 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.3362 - Accuracy: 0.8485 - F1: 0.8433
sub_23:Test (Best Model) - Loss: 0.3739 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.3722 - Accuracy: 0.8182 - F1: 0.8036
sub_24:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7951 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.7734 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.4667
sub_24:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.5312 - F1: 0.5077
sub_24:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5625 - F1: 0.5152
sub_24:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.7462 - Accuracy: 0.5312 - F1: 0.5077
sub_24:Test (Best Model) - Loss: 0.7944 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7640 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.8376 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.8123 - Accuracy: 0.4242 - F1: 0.3883
sub_25:Test (Best Model) - Loss: 0.7605 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.7546 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 0.7633 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 0.8139 - Accuracy: 0.4545 - F1: 0.4107
sub_25:Test (Best Model) - Loss: 0.7365 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 0.5789 - Accuracy: 0.7188 - F1: 0.6946
sub_25:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6875 - F1: 0.6761
sub_25:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7188 - F1: 0.6946
sub_25:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.6250 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6250 - F1: 0.5636
sub_26:Test (Best Model) - Loss: 0.3834 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.4257 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.3395 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.3853 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.3089 - Accuracy: 0.9697 - F1: 0.9692
sub_26:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5336 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.5338 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.8125 - F1: 0.8095
sub_26:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.7812 - F1: 0.7793
sub_26:Test (Best Model) - Loss: 0.2511 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.3188 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.3631 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.3057 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.2526 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6667 - F1: 0.6459
sub_27:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.5989 - Accuracy: 0.6667 - F1: 0.6459
sub_27:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6970 - F1: 0.6591
sub_27:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.6970 - F1: 0.6898
sub_27:Test (Best Model) - Loss: 0.7232 - Accuracy: 0.4242 - F1: 0.4157
sub_27:Test (Best Model) - Loss: 0.7288 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.8399 - Accuracy: 0.4545 - F1: 0.4417
sub_27:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6364 - F1: 0.6071
sub_27:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4545 - F1: 0.4417
sub_27:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.5608
sub_27:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.5938 - F1: 0.5733
sub_27:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.6250 - F1: 0.6190
sub_28:Test (Best Model) - Loss: 0.5660 - Accuracy: 0.7500 - F1: 0.7409
sub_28:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.6562 - F1: 0.6532
sub_28:Test (Best Model) - Loss: 0.7750 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.5625 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.9661 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 1.0791 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.7454 - Accuracy: 0.6250 - F1: 0.5636
sub_28:Test (Best Model) - Loss: 1.1392 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.4062 - F1: 0.3552
sub_28:Test (Best Model) - Loss: 0.7646 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.8351 - Accuracy: 0.4688 - F1: 0.4231
sub_28:Test (Best Model) - Loss: 0.7578 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.8160 - Accuracy: 0.5000 - F1: 0.4667
sub_29:Test (Best Model) - Loss: 0.2591 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.2991 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.2746 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3414 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.2965 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.1872 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.1973 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.2011 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2198 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.1773 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.2240 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.2212 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.1478 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.1972 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.1881 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 68.61 ± 11.91
F1: 66.41 ± 12.79
acc-in: 75.10 ± 8.69
F1-in: 72.78 ± 9.61
