lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.5470 - Accuracy: 0.7812 - F1: 0.7625
sub_1:Test (Best Model) - Loss: 0.5512 - Accuracy: 0.6875 - F1: 0.6537
sub_1:Test (Best Model) - Loss: 0.4752 - Accuracy: 0.8125 - F1: 0.8057
sub_1:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.7188 - F1: 0.6811
sub_1:Test (Best Model) - Loss: 0.5008 - Accuracy: 0.7812 - F1: 0.7625
sub_1:Test (Best Model) - Loss: 0.4346 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.4704 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.4337 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.5309 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.4226 - Accuracy: 0.7879 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.5107 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.4113 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.3279 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.4897 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.4343 - Accuracy: 0.8750 - F1: 0.8704
sub_2:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.8182 - F1: 0.8139
sub_2:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.6970 - F1: 0.6591
sub_2:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.6070 - Accuracy: 0.7188 - F1: 0.7117
sub_2:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.6875 - F1: 0.6364
sub_2:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6875 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.7273 - F1: 0.7263
sub_2:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.6061 - F1: 0.5926
sub_2:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6003 - Accuracy: 0.7273 - F1: 0.7263
sub_3:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.5938 - F1: 0.5934
sub_3:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5625 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.5758 - F1: 0.5658
sub_3:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.6364 - F1: 0.6333
sub_3:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6061 - F1: 0.4850
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5455 - F1: 0.5171
sub_3:Test (Best Model) - Loss: 0.8283 - Accuracy: 0.5455 - F1: 0.5438
sub_3:Test (Best Model) - Loss: 0.7559 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 0.7733 - Accuracy: 0.5758 - F1: 0.5227
sub_3:Test (Best Model) - Loss: 0.8029 - Accuracy: 0.4848 - F1: 0.4772
sub_4:Test (Best Model) - Loss: 0.5479 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.4446 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 0.5210 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.4349 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.6970 - F1: 0.6591
sub_4:Test (Best Model) - Loss: 0.5562 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.5524 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.5290 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.5264 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.6121 - Accuracy: 0.6667 - F1: 0.6667
sub_4:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.5758 - F1: 0.5722
sub_4:Test (Best Model) - Loss: 0.5426 - Accuracy: 0.7879 - F1: 0.7879
sub_4:Test (Best Model) - Loss: 0.4946 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.4881 - Accuracy: 0.7879 - F1: 0.7879
sub_5:Test (Best Model) - Loss: 0.7912 - Accuracy: 0.4375 - F1: 0.4286
sub_5:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.7935 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6191 - Accuracy: 0.4688 - F1: 0.3976
sub_5:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.4062 - F1: 0.3914
sub_5:Test (Best Model) - Loss: 0.5804 - Accuracy: 0.6250 - F1: 0.6113
sub_5:Test (Best Model) - Loss: 0.5739 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.4688 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 0.6068 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.5625 - F1: 0.5333
sub_6:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6250 - F1: 0.6113
sub_6:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6562 - F1: 0.6102
sub_6:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.7812 - F1: 0.7625
sub_6:Test (Best Model) - Loss: 0.5882 - Accuracy: 0.7812 - F1: 0.7703
sub_6:Test (Best Model) - Loss: 0.8150 - Accuracy: 0.4242 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 0.8890 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 0.8520 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 0.7725 - Accuracy: 0.5758 - F1: 0.4225
sub_6:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.6061 - F1: 0.5662
sub_6:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.6970 - F1: 0.6726
sub_6:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6970 - F1: 0.6726
sub_6:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.7576 - F1: 0.7273
sub_6:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.6667 - F1: 0.6330
sub_7:Test (Best Model) - Loss: 0.6358 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6562 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 0.8466 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.7400 - Accuracy: 0.4688 - F1: 0.4421
sub_7:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4062 - F1: 0.3914
sub_7:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.7730 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.6562 - F1: 0.6476
sub_7:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.5938 - F1: 0.5901
sub_8:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.5608 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.5312 - F1: 0.5195
sub_8:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.6055 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 0.5933 - Accuracy: 0.7500 - F1: 0.7091
sub_8:Test (Best Model) - Loss: 0.6090 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 0.4188 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.4594 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.3548 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.5004 - Accuracy: 0.8438 - F1: 0.8398
sub_9:Test (Best Model) - Loss: 0.5799 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.4959 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.4877 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 0.4314 - Accuracy: 0.8125 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 0.5155 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.4996 - Accuracy: 0.7500 - F1: 0.7229
sub_9:Test (Best Model) - Loss: 0.3408 - Accuracy: 0.9062 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.6250 - F1: 0.6113
sub_10:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.6875 - F1: 0.6863
sub_10:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.6562 - F1: 0.6390
sub_10:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5625 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.7285 - Accuracy: 0.5625 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.5758 - F1: 0.5558
sub_10:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.8707 - Accuracy: 0.4848 - F1: 0.4672
sub_11:Test (Best Model) - Loss: 0.8121 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 0.7285 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.7943 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 0.7436 - Accuracy: 0.4848 - F1: 0.4063
sub_11:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6667 - F1: 0.6553
sub_11:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.7114 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6061 - F1: 0.5196
sub_12:Test (Best Model) - Loss: 0.5280 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.5048 - Accuracy: 0.7812 - F1: 0.7625
sub_12:Test (Best Model) - Loss: 0.5340 - Accuracy: 0.7812 - F1: 0.7625
sub_12:Test (Best Model) - Loss: 0.5229 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.5132 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.5341 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.4807 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.6126 - Accuracy: 0.7188 - F1: 0.7117
sub_12:Test (Best Model) - Loss: 0.5954 - Accuracy: 0.6875 - F1: 0.6135
sub_12:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.6875 - F1: 0.6537
sub_13:Test (Best Model) - Loss: 0.5081 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.4263 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3247 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.4213 - Accuracy: 0.7500 - F1: 0.7490
sub_13:Test (Best Model) - Loss: 0.4453 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.4797 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 0.4509 - Accuracy: 0.8788 - F1: 0.8787
sub_13:Test (Best Model) - Loss: 0.5244 - Accuracy: 0.8182 - F1: 0.8167
sub_13:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.7576 - F1: 0.7462
sub_13:Test (Best Model) - Loss: 0.6017 - Accuracy: 0.6061 - F1: 0.6002
sub_13:Test (Best Model) - Loss: 0.5836 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.4979 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.4959 - Accuracy: 0.7812 - F1: 0.7758
sub_13:Test (Best Model) - Loss: 0.5460 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.5527 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.6562 - F1: 0.6390
sub_14:Test (Best Model) - Loss: 0.5123 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.5360 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.4991 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.5502 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.5271 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5537 - Accuracy: 0.6562 - F1: 0.6102
sub_14:Test (Best Model) - Loss: 0.5533 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.5461 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.5938 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.5421 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.5727 - Accuracy: 0.7812 - F1: 0.7793
sub_15:Test (Best Model) - Loss: 0.6470 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.5218 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.5350 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 0.6327 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.5828 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.5794 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 0.6203 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.5642 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.7416 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.5312 - F1: 0.5077
sub_17:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6667 - F1: 0.6459
sub_17:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.7273 - Accuracy: 0.5455 - F1: 0.5387
sub_17:Test (Best Model) - Loss: 0.7368 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5455 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4848 - F1: 0.4527
sub_17:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5312 - F1: 0.5271
sub_17:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6250 - F1: 0.6113
sub_17:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.5312 - F1: 0.5308
sub_18:Test (Best Model) - Loss: 0.5662 - Accuracy: 0.6364 - F1: 0.6278
sub_18:Test (Best Model) - Loss: 0.5734 - Accuracy: 0.6667 - F1: 0.6553
sub_18:Test (Best Model) - Loss: 0.5850 - Accuracy: 0.6667 - F1: 0.6617
sub_18:Test (Best Model) - Loss: 0.5351 - Accuracy: 0.8182 - F1: 0.8139
sub_18:Test (Best Model) - Loss: 0.5336 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.5609 - Accuracy: 0.7188 - F1: 0.7163
sub_18:Test (Best Model) - Loss: 0.5442 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.5885 - Accuracy: 0.8125 - F1: 0.8118
sub_18:Test (Best Model) - Loss: 0.5579 - Accuracy: 0.6875 - F1: 0.6761
sub_18:Test (Best Model) - Loss: 0.4772 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.8125 - F1: 0.8118
sub_18:Test (Best Model) - Loss: 0.5679 - Accuracy: 0.7188 - F1: 0.7117
sub_18:Test (Best Model) - Loss: 0.4802 - Accuracy: 0.8438 - F1: 0.8359
sub_18:Test (Best Model) - Loss: 0.4739 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.8750 - F1: 0.8730
sub_19:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.5952 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.5625 - F1: 0.4167
sub_19:Test (Best Model) - Loss: 0.6046 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6071 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.7188 - F1: 0.7185
sub_19:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.7188 - F1: 0.6946
sub_19:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 0.6091 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.5799 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.5979 - Accuracy: 0.7188 - F1: 0.6811
sub_20:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.5835 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5455 - F1: 0.5387
sub_20:Test (Best Model) - Loss: 0.7370 - Accuracy: 0.6667 - F1: 0.6459
sub_20:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.6364 - F1: 0.6278
sub_20:Test (Best Model) - Loss: 0.7672 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.7273 - F1: 0.7102
sub_21:Test (Best Model) - Loss: 0.7467 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7958 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 0.7724 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7548 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 0.7658 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7688 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 0.7882 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.7917 - Accuracy: 0.4375 - F1: 0.3766
sub_21:Test (Best Model) - Loss: 0.7567 - Accuracy: 0.5312 - F1: 0.4386
sub_21:Test (Best Model) - Loss: 0.7410 - Accuracy: 0.5938 - F1: 0.5901
sub_21:Test (Best Model) - Loss: 0.7769 - Accuracy: 0.2812 - F1: 0.2805
sub_21:Test (Best Model) - Loss: 0.8213 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 0.8235 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 0.8334 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.7794 - Accuracy: 0.4688 - F1: 0.4231
sub_22:Test (Best Model) - Loss: 0.5085 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.5218 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.5573 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.5467 - Accuracy: 0.6562 - F1: 0.5883
sub_22:Test (Best Model) - Loss: 0.5413 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.7273 - F1: 0.6997
sub_22:Test (Best Model) - Loss: 0.5806 - Accuracy: 0.6667 - F1: 0.6159
sub_22:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.6970 - F1: 0.6591
sub_22:Test (Best Model) - Loss: 0.5688 - Accuracy: 0.6875 - F1: 0.6761
sub_22:Test (Best Model) - Loss: 0.5707 - Accuracy: 0.8125 - F1: 0.8095
sub_22:Test (Best Model) - Loss: 0.6050 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.6006 - Accuracy: 0.6562 - F1: 0.5883
sub_22:Test (Best Model) - Loss: 0.5310 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.4858 - Accuracy: 0.6970 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.5634 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.5186 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.5938 - F1: 0.5934
sub_23:Test (Best Model) - Loss: 0.5887 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.5215 - Accuracy: 0.7812 - F1: 0.7758
sub_23:Test (Best Model) - Loss: 0.5054 - Accuracy: 0.7188 - F1: 0.7185
sub_23:Test (Best Model) - Loss: 0.5746 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.5015 - Accuracy: 0.8485 - F1: 0.8390
sub_23:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.7879 - F1: 0.7746
sub_23:Test (Best Model) - Loss: 0.4691 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.4942 - Accuracy: 0.7273 - F1: 0.6997
sub_24:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.7752 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7541 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.7231 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5938 - F1: 0.5589
sub_24:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.6250 - F1: 0.6250
sub_24:Test (Best Model) - Loss: 0.7349 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7425 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.7836 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.7648 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7380 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.8277 - Accuracy: 0.3939 - F1: 0.3654
sub_25:Test (Best Model) - Loss: 0.7559 - Accuracy: 0.5455 - F1: 0.5438
sub_25:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 0.7689 - Accuracy: 0.4848 - F1: 0.4063
sub_25:Test (Best Model) - Loss: 0.7624 - Accuracy: 0.4545 - F1: 0.4500
sub_25:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 0.6033 - Accuracy: 0.7188 - F1: 0.7046
sub_25:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6562 - F1: 0.6559
sub_25:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.7188 - F1: 0.6811
sub_25:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.5938 - F1: 0.5135
sub_25:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.5625 - F1: 0.4589
sub_25:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6562 - F1: 0.6102
sub_26:Test (Best Model) - Loss: 0.5385 - Accuracy: 0.7273 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 0.5292 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.5243 - Accuracy: 0.7576 - F1: 0.7462
sub_26:Test (Best Model) - Loss: 0.5121 - Accuracy: 0.6970 - F1: 0.6591
sub_26:Test (Best Model) - Loss: 0.4636 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.5808 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.5803 - Accuracy: 0.5938 - F1: 0.5934
sub_26:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.5288 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.5391 - Accuracy: 0.6875 - F1: 0.6825
sub_26:Test (Best Model) - Loss: 0.3282 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.4127 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.3895 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.2985 - Accuracy: 0.8750 - F1: 0.8667
sub_27:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6667 - F1: 0.6459
sub_27:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.7273 - Accuracy: 0.5455 - F1: 0.5387
sub_27:Test (Best Model) - Loss: 0.7368 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5455 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4848 - F1: 0.4527
sub_27:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5312 - F1: 0.5271
sub_27:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.5000 - F1: 0.4667
sub_27:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.5168 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6875 - F1: 0.6875
sub_28:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.8181 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 0.7563 - Accuracy: 0.5000 - F1: 0.4980
sub_28:Test (Best Model) - Loss: 0.7780 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 0.8596 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.5312 - F1: 0.5271
sub_28:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.6250 - F1: 0.5844
sub_28:Test (Best Model) - Loss: 0.9752 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 0.7685 - Accuracy: 0.4375 - F1: 0.3766
sub_28:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.4062 - F1: 0.3914
sub_28:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 0.7502 - Accuracy: 0.4375 - F1: 0.3766
sub_29:Test (Best Model) - Loss: 0.3338 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.3954 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.3993 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.3806 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.3499 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.2854 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2887 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.2486 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.3486 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3242 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.3568 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.3850 - Accuracy: 0.8485 - F1: 0.8433
sub_29:Test (Best Model) - Loss: 0.2901 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.3216 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.3007 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 65.21 ± 10.41
F1: 62.92 ± 11.00
acc-in: 71.70 ± 8.16
F1-in: 69.69 ± 8.53
