lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.7188 - F1: 0.6946
sub_1:Test (Best Model) - Loss: 0.5557 - Accuracy: 0.7500 - F1: 0.7409
sub_1:Test (Best Model) - Loss: 0.7279 - Accuracy: 0.7500 - F1: 0.7460
sub_1:Test (Best Model) - Loss: 0.5310 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.5683 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.5748 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.7576 - F1: 0.7462
sub_1:Test (Best Model) - Loss: 0.9554 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.7576 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.5067 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.3901 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.2397 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.4585 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.5266 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.6061 - F1: 0.5926
sub_2:Test (Best Model) - Loss: 0.9762 - Accuracy: 0.7273 - F1: 0.7232
sub_2:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.7576 - F1: 0.7381
sub_2:Test (Best Model) - Loss: 1.2203 - Accuracy: 0.6667 - F1: 0.6330
sub_2:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.0538 - Accuracy: 0.5938 - F1: 0.5393
sub_2:Test (Best Model) - Loss: 0.9882 - Accuracy: 0.5625 - F1: 0.4909
sub_2:Test (Best Model) - Loss: 0.8324 - Accuracy: 0.5938 - F1: 0.5733
sub_2:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.6562 - F1: 0.5883
sub_2:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.7188 - F1: 0.6632
sub_2:Test (Best Model) - Loss: 1.0006 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 1.2766 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.6970 - F1: 0.6944
sub_2:Test (Best Model) - Loss: 0.7437 - Accuracy: 0.6970 - F1: 0.6944
sub_2:Test (Best Model) - Loss: 0.9984 - Accuracy: 0.6970 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 1.4152 - Accuracy: 0.5938 - F1: 0.5901
sub_3:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 1.2381 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 1.1242 - Accuracy: 0.5625 - F1: 0.5556
sub_3:Test (Best Model) - Loss: 0.9054 - Accuracy: 0.5758 - F1: 0.5754
sub_3:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.4242 - F1: 0.4221
sub_3:Test (Best Model) - Loss: 0.9795 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 1.4737 - Accuracy: 0.4545 - F1: 0.3864
sub_3:Test (Best Model) - Loss: 1.3245 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 1.8731 - Accuracy: 0.5152 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.4545 - F1: 0.3543
sub_3:Test (Best Model) - Loss: 1.7702 - Accuracy: 0.4848 - F1: 0.4063
sub_3:Test (Best Model) - Loss: 1.9307 - Accuracy: 0.3636 - F1: 0.2993
sub_4:Test (Best Model) - Loss: 0.9366 - Accuracy: 0.6970 - F1: 0.6591
sub_4:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.7537 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.6970 - F1: 0.6413
sub_4:Test (Best Model) - Loss: 0.8448 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 1.0890 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 0.7711 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.4784 - Accuracy: 0.8182 - F1: 0.8167
sub_4:Test (Best Model) - Loss: 0.4948 - Accuracy: 0.7273 - F1: 0.7232
sub_4:Test (Best Model) - Loss: 0.4237 - Accuracy: 0.8182 - F1: 0.8036
sub_5:Test (Best Model) - Loss: 1.8652 - Accuracy: 0.3438 - F1: 0.3431
sub_5:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.5000 - F1: 0.4921
sub_5:Test (Best Model) - Loss: 2.8222 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 1.2267 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.7483 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.7589 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 0.9019 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.7188 - F1: 0.7046
sub_5:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.6875 - F1: 0.6761
sub_5:Test (Best Model) - Loss: 1.0579 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 1.0547 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 1.0677 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.9002 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 1.0945 - Accuracy: 0.6562 - F1: 0.6559
sub_6:Test (Best Model) - Loss: 1.2539 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 0.9023 - Accuracy: 0.7812 - F1: 0.7758
sub_6:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.6250 - F1: 0.5844
sub_6:Test (Best Model) - Loss: 1.0491 - Accuracy: 0.5938 - F1: 0.5836
sub_6:Test (Best Model) - Loss: 0.8896 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.9203 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 2.6396 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 2.2983 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 2.6520 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 2.3304 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.6364 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 1.2502 - Accuracy: 0.6364 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 1.0134 - Accuracy: 0.6667 - F1: 0.6159
sub_6:Test (Best Model) - Loss: 1.1872 - Accuracy: 0.6970 - F1: 0.6591
sub_6:Test (Best Model) - Loss: 1.0276 - Accuracy: 0.6364 - F1: 0.5417
sub_7:Test (Best Model) - Loss: 0.9300 - Accuracy: 0.6250 - F1: 0.5636
sub_7:Test (Best Model) - Loss: 1.1592 - Accuracy: 0.5312 - F1: 0.4910
sub_7:Test (Best Model) - Loss: 1.4860 - Accuracy: 0.5000 - F1: 0.4667
sub_7:Test (Best Model) - Loss: 1.0824 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 1.4287 - Accuracy: 0.5000 - F1: 0.4459
sub_7:Test (Best Model) - Loss: 1.8382 - Accuracy: 0.3125 - F1: 0.3098
sub_7:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.2589 - Accuracy: 0.3750 - F1: 0.3725
sub_7:Test (Best Model) - Loss: 1.7883 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 1.0548 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 1.6424 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.9963 - Accuracy: 0.6562 - F1: 0.6559
sub_7:Test (Best Model) - Loss: 0.8636 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 1.3148 - Accuracy: 0.5625 - F1: 0.4909
sub_8:Test (Best Model) - Loss: 1.5158 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 1.2898 - Accuracy: 0.6250 - F1: 0.6235
sub_8:Test (Best Model) - Loss: 1.0927 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 1.6402 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 1.0068 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 1.6830 - Accuracy: 0.5312 - F1: 0.4910
sub_8:Test (Best Model) - Loss: 1.1641 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.4375 - F1: 0.4286
sub_8:Test (Best Model) - Loss: 1.1643 - Accuracy: 0.5625 - F1: 0.5556
sub_8:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.9846 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.5585 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.4649 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.6004 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.7388 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 1.0441 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.9696 - Accuracy: 0.6250 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 1.5278 - Accuracy: 0.5625 - F1: 0.5466
sub_9:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.6562 - F1: 0.6532
sub_9:Test (Best Model) - Loss: 1.0185 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 1.0547 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 1.0181 - Accuracy: 0.7812 - F1: 0.7758
sub_10:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.5625 - F1: 0.5152
sub_10:Test (Best Model) - Loss: 1.0330 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 1.0814 - Accuracy: 0.5000 - F1: 0.4921
sub_10:Test (Best Model) - Loss: 1.2316 - Accuracy: 0.5000 - F1: 0.4459
sub_10:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 1.5503 - Accuracy: 0.4688 - F1: 0.4555
sub_10:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 1.2114 - Accuracy: 0.4062 - F1: 0.3914
sub_10:Test (Best Model) - Loss: 1.5100 - Accuracy: 0.4688 - F1: 0.4640
sub_10:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 0.9280 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.1333 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.2509 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 2.1729 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 1.9655 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.7042 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 1.4252 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 1.9557 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.5339 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 1.0250 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 1.6949 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 1.2110 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.5455 - F1: 0.4058
sub_11:Test (Best Model) - Loss: 1.0244 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 1.4044 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.8364 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 1.0238 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 0.9474 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 1.5025 - Accuracy: 0.5312 - F1: 0.4386
sub_12:Test (Best Model) - Loss: 1.1987 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.6061 - F1: 0.5196
sub_12:Test (Best Model) - Loss: 0.7629 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.7212 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 1.1249 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 1.2571 - Accuracy: 0.5938 - F1: 0.5733
sub_12:Test (Best Model) - Loss: 1.0768 - Accuracy: 0.6250 - F1: 0.6113
sub_12:Test (Best Model) - Loss: 1.5141 - Accuracy: 0.7188 - F1: 0.6811
sub_12:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.5938 - F1: 0.5393
sub_13:Test (Best Model) - Loss: 0.4141 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.5264 - Accuracy: 0.7812 - F1: 0.7810
sub_13:Test (Best Model) - Loss: 0.3755 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.6667 - F1: 0.6459
sub_13:Test (Best Model) - Loss: 0.4282 - Accuracy: 0.8182 - F1: 0.8180
sub_13:Test (Best Model) - Loss: 0.4290 - Accuracy: 0.8182 - F1: 0.8167
sub_13:Test (Best Model) - Loss: 1.1887 - Accuracy: 0.5455 - F1: 0.5455
sub_13:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.7302 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.5070 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.3630 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.4367 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6170 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 1.0414 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.7471 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.5338 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.5569 - Accuracy: 0.6250 - F1: 0.5844
sub_14:Test (Best Model) - Loss: 0.7798 - Accuracy: 0.5938 - F1: 0.5393
sub_14:Test (Best Model) - Loss: 0.7219 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.7789 - Accuracy: 0.6562 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 0.9683 - Accuracy: 0.5938 - F1: 0.5393
sub_14:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.7500 - F1: 0.7091
sub_14:Test (Best Model) - Loss: 0.9426 - Accuracy: 0.6250 - F1: 0.5844
sub_14:Test (Best Model) - Loss: 1.1841 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 1.1308 - Accuracy: 0.5625 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 1.6229 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 1.0801 - Accuracy: 0.5625 - F1: 0.5625
sub_15:Test (Best Model) - Loss: 1.1728 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 1.1109 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 1.1569 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 1.4517 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 1.9784 - Accuracy: 0.5625 - F1: 0.5608
sub_15:Test (Best Model) - Loss: 0.9573 - Accuracy: 0.6250 - F1: 0.6250
sub_15:Test (Best Model) - Loss: 1.4569 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 1.4666 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 1.0694 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 1.1482 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 1.4282 - Accuracy: 0.4688 - F1: 0.4640
sub_15:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 1.1231 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 1.0349 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.8516 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 1.0572 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 0.9277 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 1.0110 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 1.3197 - Accuracy: 0.7812 - F1: 0.7758
sub_16:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 1.2045 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 1.5712 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.5625 - F1: 0.4589
sub_16:Test (Best Model) - Loss: 1.4852 - Accuracy: 0.6250 - F1: 0.5844
sub_16:Test (Best Model) - Loss: 1.3047 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 1.7643 - Accuracy: 0.4688 - F1: 0.3976
sub_17:Test (Best Model) - Loss: 1.1180 - Accuracy: 0.6364 - F1: 0.6071
sub_17:Test (Best Model) - Loss: 0.9165 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.9338 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 1.1456 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 0.9509 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.4545 - F1: 0.4500
sub_17:Test (Best Model) - Loss: 1.2394 - Accuracy: 0.5152 - F1: 0.5038
sub_17:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.5758 - F1: 0.5722
sub_17:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.5455 - F1: 0.4995
sub_17:Test (Best Model) - Loss: 1.0164 - Accuracy: 0.5152 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 0.9112 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 1.0897 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.5312 - F1: 0.5077
sub_17:Test (Best Model) - Loss: 1.1244 - Accuracy: 0.6562 - F1: 0.6390
sub_17:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.5312 - F1: 0.5195
sub_18:Test (Best Model) - Loss: 0.6007 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.4927 - Accuracy: 0.7576 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.6667 - F1: 0.6617
sub_18:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.3939 - Accuracy: 0.8485 - F1: 0.8462
sub_18:Test (Best Model) - Loss: 0.7882 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.6875 - F1: 0.6825
sub_18:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.6875 - F1: 0.6875
sub_18:Test (Best Model) - Loss: 0.7621 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.5328 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.5576 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.8671 - Accuracy: 0.6875 - F1: 0.6667
sub_18:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.7812 - F1: 0.7703
sub_19:Test (Best Model) - Loss: 1.9797 - Accuracy: 0.5000 - F1: 0.3333
sub_19:Test (Best Model) - Loss: 1.3190 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.2010 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 2.3187 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 1.1466 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 1.1511 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.4688 - F1: 0.3976
sub_19:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.5000 - F1: 0.4667
sub_19:Test (Best Model) - Loss: 1.4664 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 1.2511 - Accuracy: 0.4688 - F1: 0.4682
sub_19:Test (Best Model) - Loss: 0.9388 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.7357 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.6562 - F1: 0.6102
sub_20:Test (Best Model) - Loss: 1.7069 - Accuracy: 0.6562 - F1: 0.5883
sub_20:Test (Best Model) - Loss: 1.3027 - Accuracy: 0.5938 - F1: 0.5135
sub_20:Test (Best Model) - Loss: 1.9911 - Accuracy: 0.5625 - F1: 0.4909
sub_20:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 1.1909 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 1.7016 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 1.1853 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 2.2611 - Accuracy: 0.4848 - F1: 0.4672
sub_20:Test (Best Model) - Loss: 1.9046 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 1.9959 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 2.5533 - Accuracy: 0.5758 - F1: 0.5417
sub_20:Test (Best Model) - Loss: 1.6008 - Accuracy: 0.7273 - F1: 0.6997
sub_21:Test (Best Model) - Loss: 1.5454 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 1.7455 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 1.7405 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 1.6857 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 1.7470 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 1.4108 - Accuracy: 0.4688 - F1: 0.3637
sub_21:Test (Best Model) - Loss: 1.1366 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.2812 - F1: 0.2749
sub_21:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.5625 - F1: 0.4909
sub_21:Test (Best Model) - Loss: 1.2218 - Accuracy: 0.5000 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 1.4443 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 1.4295 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 1.9617 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 2.1058 - Accuracy: 0.3438 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 1.4364 - Accuracy: 0.5000 - F1: 0.4182
sub_22:Test (Best Model) - Loss: 0.8798 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.8114 - Accuracy: 0.6562 - F1: 0.5883
sub_22:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.8522 - Accuracy: 0.5938 - F1: 0.4340
sub_22:Test (Best Model) - Loss: 0.8508 - Accuracy: 0.7812 - F1: 0.7625
sub_22:Test (Best Model) - Loss: 1.1809 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 1.1401 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 1.2171 - Accuracy: 0.6061 - F1: 0.5196
sub_22:Test (Best Model) - Loss: 0.9024 - Accuracy: 0.6875 - F1: 0.6667
sub_22:Test (Best Model) - Loss: 0.7320 - Accuracy: 0.6562 - F1: 0.6476
sub_22:Test (Best Model) - Loss: 0.9944 - Accuracy: 0.6250 - F1: 0.5362
sub_22:Test (Best Model) - Loss: 0.7521 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 0.8276 - Accuracy: 0.7188 - F1: 0.7046
sub_23:Test (Best Model) - Loss: 1.0066 - Accuracy: 0.7273 - F1: 0.6997
sub_23:Test (Best Model) - Loss: 0.8887 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 0.8570 - Accuracy: 0.6667 - F1: 0.6159
sub_23:Test (Best Model) - Loss: 0.9779 - Accuracy: 0.6364 - F1: 0.5417
sub_23:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 1.0665 - Accuracy: 0.4688 - F1: 0.4682
sub_23:Test (Best Model) - Loss: 0.7676 - Accuracy: 0.6250 - F1: 0.6250
sub_23:Test (Best Model) - Loss: 0.5020 - Accuracy: 0.7188 - F1: 0.7163
sub_23:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.6562 - F1: 0.6532
sub_23:Test (Best Model) - Loss: 0.9441 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 0.9092 - Accuracy: 0.6667 - F1: 0.6159
sub_23:Test (Best Model) - Loss: 0.7732 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 1.2597 - Accuracy: 0.6061 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.6061 - F1: 0.4850
sub_24:Test (Best Model) - Loss: 1.2668 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.5121 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 1.2607 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 1.1423 - Accuracy: 0.5000 - F1: 0.4667
sub_24:Test (Best Model) - Loss: 1.0753 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.9158 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 1.0167 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.8183 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.7188 - F1: 0.7163
sub_24:Test (Best Model) - Loss: 1.5643 - Accuracy: 0.5938 - F1: 0.5733
sub_24:Test (Best Model) - Loss: 1.3173 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.4800 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 1.7410 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.4960 - Accuracy: 0.5938 - F1: 0.5733
sub_25:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 1.3236 - Accuracy: 0.4545 - F1: 0.4288
sub_25:Test (Best Model) - Loss: 1.5714 - Accuracy: 0.5455 - F1: 0.5171
sub_25:Test (Best Model) - Loss: 1.6290 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 1.7583 - Accuracy: 0.4848 - F1: 0.3718
sub_25:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.7637 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 0.9191 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 1.0014 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 1.0259 - Accuracy: 0.6562 - F1: 0.6102
sub_25:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.7500 - F1: 0.7091
sub_25:Test (Best Model) - Loss: 1.1451 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.5625 - F1: 0.4909
sub_25:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.6562 - F1: 0.6102
sub_26:Test (Best Model) - Loss: 1.1628 - Accuracy: 0.6667 - F1: 0.6459
sub_26:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.6970 - F1: 0.6591
sub_26:Test (Best Model) - Loss: 0.9554 - Accuracy: 0.7273 - F1: 0.6997
sub_26:Test (Best Model) - Loss: 0.7135 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.6059 - Accuracy: 0.6970 - F1: 0.6413
sub_26:Test (Best Model) - Loss: 0.7847 - Accuracy: 0.6562 - F1: 0.6559
sub_26:Test (Best Model) - Loss: 0.8336 - Accuracy: 0.6250 - F1: 0.6250
sub_26:Test (Best Model) - Loss: 0.9463 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.8729 - Accuracy: 0.7500 - F1: 0.7333
sub_26:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.6875 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 0.3014 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.6295 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5393 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.4965 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 1.1180 - Accuracy: 0.6364 - F1: 0.6071
sub_27:Test (Best Model) - Loss: 0.9165 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 0.9338 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 1.1456 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 0.9509 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.4545 - F1: 0.4500
sub_27:Test (Best Model) - Loss: 1.2394 - Accuracy: 0.5152 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.5455 - F1: 0.4995
sub_27:Test (Best Model) - Loss: 1.0164 - Accuracy: 0.5152 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.9112 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 1.0897 - Accuracy: 0.5938 - F1: 0.5589
sub_27:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.5312 - F1: 0.5077
sub_27:Test (Best Model) - Loss: 1.1244 - Accuracy: 0.6562 - F1: 0.6390
sub_27:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 0.9989 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 1.0457 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 1.7062 - Accuracy: 0.5312 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 1.1999 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 2.1346 - Accuracy: 0.4375 - F1: 0.3455
sub_28:Test (Best Model) - Loss: 2.3265 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 1.2783 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 3.1963 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 1.2522 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 1.1727 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.5625 - F1: 0.5556
sub_28:Test (Best Model) - Loss: 1.1892 - Accuracy: 0.4062 - F1: 0.3764
sub_29:Test (Best Model) - Loss: 1.0602 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.9047 - Accuracy: 0.7812 - F1: 0.7625
sub_29:Test (Best Model) - Loss: 1.0608 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.6875 - F1: 0.6135
sub_29:Test (Best Model) - Loss: 0.2307 - Accuracy: 0.9062 - F1: 0.9039
sub_29:Test (Best Model) - Loss: 0.1846 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1711 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2105 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.1792 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.8182 - F1: 0.8096
sub_29:Test (Best Model) - Loss: 0.3087 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.4257 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.3502 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 62.84 ± 10.00
F1: 59.79 ± 10.74
acc-in: 69.97 ± 7.25
F1-in: 67.14 ± 8.15
