lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.5200 - Accuracy: 0.7812 - F1: 0.7703
sub_1:Test (Best Model) - Loss: 0.5459 - Accuracy: 0.6875 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.3937 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.5276 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.7313 - Accuracy: 0.7576 - F1: 0.7273
sub_1:Test (Best Model) - Loss: 0.4896 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.7273 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.6970 - F1: 0.6413
sub_1:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.7273 - F1: 0.6997
sub_1:Test (Best Model) - Loss: 0.4373 - Accuracy: 0.8438 - F1: 0.8359
sub_1:Test (Best Model) - Loss: 0.3384 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.1864 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.8438 - F1: 0.8359
sub_2:Test (Best Model) - Loss: 0.9912 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 1.4600 - Accuracy: 0.7576 - F1: 0.7381
sub_2:Test (Best Model) - Loss: 1.5458 - Accuracy: 0.7576 - F1: 0.7462
sub_2:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.4688 - F1: 0.4421
sub_2:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.7500 - F1: 0.7409
sub_2:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 0.7653 - Accuracy: 0.6562 - F1: 0.6267
sub_2:Test (Best Model) - Loss: 0.8275 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 1.1398 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.8190 - Accuracy: 0.7273 - F1: 0.7273
sub_2:Test (Best Model) - Loss: 0.8146 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 0.7964 - Accuracy: 0.6970 - F1: 0.6967
sub_3:Test (Best Model) - Loss: 1.4723 - Accuracy: 0.5938 - F1: 0.5901
sub_3:Test (Best Model) - Loss: 1.4399 - Accuracy: 0.5000 - F1: 0.4818
sub_3:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 1.2899 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.5625 - F1: 0.5466
sub_3:Test (Best Model) - Loss: 0.9805 - Accuracy: 0.6061 - F1: 0.5815
sub_3:Test (Best Model) - Loss: 1.4889 - Accuracy: 0.4242 - F1: 0.4221
sub_3:Test (Best Model) - Loss: 1.1402 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 1.5505 - Accuracy: 0.5152 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 1.7215 - Accuracy: 0.5455 - F1: 0.4995
sub_3:Test (Best Model) - Loss: 2.1903 - Accuracy: 0.5152 - F1: 0.4545
sub_3:Test (Best Model) - Loss: 1.6321 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 1.5420 - Accuracy: 0.4242 - F1: 0.3365
sub_3:Test (Best Model) - Loss: 1.7798 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 1.8957 - Accuracy: 0.3636 - F1: 0.3239
sub_4:Test (Best Model) - Loss: 1.1766 - Accuracy: 0.6667 - F1: 0.6330
sub_4:Test (Best Model) - Loss: 0.6026 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7273 - F1: 0.6997
sub_4:Test (Best Model) - Loss: 0.7586 - Accuracy: 0.7576 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 1.0345 - Accuracy: 0.6970 - F1: 0.6591
sub_4:Test (Best Model) - Loss: 1.2730 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 0.9974 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 1.4910 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 2.0907 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.9489 - Accuracy: 0.5758 - F1: 0.5227
sub_4:Test (Best Model) - Loss: 0.4779 - Accuracy: 0.7576 - F1: 0.7574
sub_4:Test (Best Model) - Loss: 0.4931 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.3903 - Accuracy: 0.8485 - F1: 0.8390
sub_5:Test (Best Model) - Loss: 2.1338 - Accuracy: 0.3750 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 2.5264 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 1.6484 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 1.0822 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 0.8400 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.8933 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.7711 - Accuracy: 0.7188 - F1: 0.7046
sub_5:Test (Best Model) - Loss: 1.1776 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.9597 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 1.4621 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.6250 - F1: 0.6113
sub_5:Test (Best Model) - Loss: 1.2093 - Accuracy: 0.5312 - F1: 0.5271
sub_6:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 0.9991 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 1.2614 - Accuracy: 0.7188 - F1: 0.7046
sub_6:Test (Best Model) - Loss: 1.1440 - Accuracy: 0.5938 - F1: 0.5836
sub_6:Test (Best Model) - Loss: 1.0439 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 2.7048 - Accuracy: 0.5152 - F1: 0.3400
sub_6:Test (Best Model) - Loss: 3.2182 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 2.3568 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 1.9738 - Accuracy: 0.4848 - F1: 0.3265
sub_6:Test (Best Model) - Loss: 2.5304 - Accuracy: 0.5455 - F1: 0.4457
sub_6:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.6061 - F1: 0.5196
sub_6:Test (Best Model) - Loss: 1.1233 - Accuracy: 0.6364 - F1: 0.5909
sub_6:Test (Best Model) - Loss: 1.1206 - Accuracy: 0.5758 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.9798 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 1.2523 - Accuracy: 0.6667 - F1: 0.6159
sub_7:Test (Best Model) - Loss: 0.9313 - Accuracy: 0.6562 - F1: 0.6102
sub_7:Test (Best Model) - Loss: 1.3381 - Accuracy: 0.5000 - F1: 0.4459
sub_7:Test (Best Model) - Loss: 1.7068 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.9958 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 2.3622 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 1.4612 - Accuracy: 0.4062 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 1.9553 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 1.0890 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 1.4472 - Accuracy: 0.5000 - F1: 0.5000
sub_7:Test (Best Model) - Loss: 2.0383 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 1.0319 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.8983 - Accuracy: 0.6875 - F1: 0.6875
sub_8:Test (Best Model) - Loss: 1.5558 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 1.6945 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 1.0607 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.8648 - Accuracy: 0.8438 - F1: 0.8303
sub_8:Test (Best Model) - Loss: 1.6853 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 1.7408 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 0.8102 - Accuracy: 0.6562 - F1: 0.6267
sub_8:Test (Best Model) - Loss: 1.6703 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 1.2604 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.4525 - Accuracy: 0.4062 - F1: 0.4010
sub_8:Test (Best Model) - Loss: 0.9391 - Accuracy: 0.6875 - F1: 0.6667
sub_8:Test (Best Model) - Loss: 0.7726 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 0.7765 - Accuracy: 0.6562 - F1: 0.6102
sub_8:Test (Best Model) - Loss: 0.8093 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.4001 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.7188 - F1: 0.6946
sub_9:Test (Best Model) - Loss: 0.4164 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.7579 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.5699 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.6562 - F1: 0.6559
sub_9:Test (Best Model) - Loss: 1.0441 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 1.1764 - Accuracy: 0.5000 - F1: 0.4980
sub_9:Test (Best Model) - Loss: 0.7803 - Accuracy: 0.6562 - F1: 0.6559
sub_9:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.6875 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 0.8866 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 1.0407 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 1.5868 - Accuracy: 0.6562 - F1: 0.6532
sub_9:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6875 - F1: 0.6761
sub_10:Test (Best Model) - Loss: 1.1274 - Accuracy: 0.5625 - F1: 0.5333
sub_10:Test (Best Model) - Loss: 1.1544 - Accuracy: 0.5000 - F1: 0.4667
sub_10:Test (Best Model) - Loss: 0.9393 - Accuracy: 0.5625 - F1: 0.5152
sub_10:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.5938 - F1: 0.5393
sub_10:Test (Best Model) - Loss: 1.5602 - Accuracy: 0.5312 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 1.5599 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 1.5177 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 1.5021 - Accuracy: 0.5000 - F1: 0.4921
sub_10:Test (Best Model) - Loss: 1.7099 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 1.6170 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.5152 - F1: 0.5111
sub_10:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.4848 - F1: 0.4829
sub_10:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.6061 - F1: 0.5926
sub_11:Test (Best Model) - Loss: 2.5450 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 2.2700 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 2.1598 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 1.7361 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 2.2271 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 1.5631 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 1.0863 - Accuracy: 0.5758 - F1: 0.5227
sub_11:Test (Best Model) - Loss: 2.1046 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.5611 - Accuracy: 0.6364 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 1.1641 - Accuracy: 0.5152 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 1.0271 - Accuracy: 0.7273 - F1: 0.6997
sub_11:Test (Best Model) - Loss: 1.6425 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.0928 - Accuracy: 0.6970 - F1: 0.6591
sub_11:Test (Best Model) - Loss: 1.5146 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.8869 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 0.9240 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 0.9874 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 1.4432 - Accuracy: 0.6250 - F1: 0.5636
sub_12:Test (Best Model) - Loss: 1.1238 - Accuracy: 0.6364 - F1: 0.5696
sub_12:Test (Best Model) - Loss: 1.4235 - Accuracy: 0.6364 - F1: 0.5696
sub_12:Test (Best Model) - Loss: 0.7628 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 1.1634 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 1.0455 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 1.5036 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 0.9627 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 1.4263 - Accuracy: 0.6250 - F1: 0.5844
sub_12:Test (Best Model) - Loss: 1.2087 - Accuracy: 0.7188 - F1: 0.6811
sub_13:Test (Best Model) - Loss: 0.3833 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.8125 - F1: 0.8095
sub_13:Test (Best Model) - Loss: 0.2532 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.4208 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.3730 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 1.0888 - Accuracy: 0.6061 - F1: 0.6002
sub_13:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.8182 - F1: 0.8180
sub_13:Test (Best Model) - Loss: 0.3166 - Accuracy: 0.8485 - F1: 0.8390
sub_13:Test (Best Model) - Loss: 0.8887 - Accuracy: 0.6364 - F1: 0.6278
sub_13:Test (Best Model) - Loss: 0.9517 - Accuracy: 0.6364 - F1: 0.6192
sub_13:Test (Best Model) - Loss: 0.5782 - Accuracy: 0.6875 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 0.5784 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.4958 - Accuracy: 0.8750 - F1: 0.8730
sub_13:Test (Best Model) - Loss: 0.5387 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3686 - Accuracy: 0.9375 - F1: 0.9365
sub_14:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.6562 - F1: 0.6102
sub_14:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.6875 - F1: 0.6875
sub_14:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.5718 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.8554 - Accuracy: 0.6250 - F1: 0.5844
sub_14:Test (Best Model) - Loss: 0.8914 - Accuracy: 0.6562 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 0.7254 - Accuracy: 0.6250 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 0.9792 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 1.2238 - Accuracy: 0.6562 - F1: 0.5883
sub_14:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.7558 - Accuracy: 0.6562 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 1.0018 - Accuracy: 0.6250 - F1: 0.5844
sub_14:Test (Best Model) - Loss: 1.7925 - Accuracy: 0.4375 - F1: 0.4170
sub_14:Test (Best Model) - Loss: 0.8876 - Accuracy: 0.7500 - F1: 0.7091
sub_15:Test (Best Model) - Loss: 1.8752 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.2518 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 1.5755 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 1.8559 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 1.2018 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 1.8545 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 1.0054 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 1.5876 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 2.2598 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 1.1102 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 1.1770 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 1.4433 - Accuracy: 0.4688 - F1: 0.4640
sub_15:Test (Best Model) - Loss: 1.3134 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.4688 - F1: 0.4682
sub_16:Test (Best Model) - Loss: 1.1486 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.9745 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 1.2279 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 1.0279 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 1.2026 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 2.0608 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.5312 - F1: 0.4386
sub_16:Test (Best Model) - Loss: 1.5415 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 1.5477 - Accuracy: 0.5000 - F1: 0.4459
sub_17:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.6667 - F1: 0.6330
sub_17:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6364 - F1: 0.6071
sub_17:Test (Best Model) - Loss: 1.1991 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 1.0346 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.9105 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 1.4108 - Accuracy: 0.4545 - F1: 0.4417
sub_17:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.5455 - F1: 0.4995
sub_17:Test (Best Model) - Loss: 1.7685 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 1.0537 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 1.0846 - Accuracy: 0.6250 - F1: 0.6190
sub_17:Test (Best Model) - Loss: 1.7346 - Accuracy: 0.6250 - F1: 0.5844
sub_17:Test (Best Model) - Loss: 1.2570 - Accuracy: 0.5938 - F1: 0.5733
sub_17:Test (Best Model) - Loss: 1.7656 - Accuracy: 0.5625 - F1: 0.5466
sub_18:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.5180 - Accuracy: 0.7273 - F1: 0.7273
sub_18:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.7273 - F1: 0.7232
sub_18:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.7576 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 0.4643 - Accuracy: 0.8182 - F1: 0.8139
sub_18:Test (Best Model) - Loss: 0.7735 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.5888 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.6131 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.7812 - F1: 0.7625
sub_18:Test (Best Model) - Loss: 0.4630 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.7188 - F1: 0.6946
sub_18:Test (Best Model) - Loss: 0.9424 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.5533 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.5920 - Accuracy: 0.8125 - F1: 0.8057
sub_19:Test (Best Model) - Loss: 2.3023 - Accuracy: 0.5312 - F1: 0.3469
sub_19:Test (Best Model) - Loss: 1.4481 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 2.3247 - Accuracy: 0.4688 - F1: 0.3637
sub_19:Test (Best Model) - Loss: 1.6791 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 1.8621 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 1.2138 - Accuracy: 0.5312 - F1: 0.4684
sub_19:Test (Best Model) - Loss: 1.0248 - Accuracy: 0.6562 - F1: 0.6267
sub_19:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 1.4135 - Accuracy: 0.5938 - F1: 0.5733
sub_19:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 1.0865 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 0.9835 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.7279 - Accuracy: 0.7812 - F1: 0.7519
sub_20:Test (Best Model) - Loss: 1.4683 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 1.2519 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 1.4468 - Accuracy: 0.6562 - F1: 0.6102
sub_20:Test (Best Model) - Loss: 1.1271 - Accuracy: 0.6875 - F1: 0.6364
sub_20:Test (Best Model) - Loss: 1.9598 - Accuracy: 0.5938 - F1: 0.5135
sub_20:Test (Best Model) - Loss: 1.7031 - Accuracy: 0.6875 - F1: 0.6825
sub_20:Test (Best Model) - Loss: 1.7357 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 1.6648 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 1.4738 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 2.4718 - Accuracy: 0.4848 - F1: 0.4772
sub_20:Test (Best Model) - Loss: 2.3571 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 2.1249 - Accuracy: 0.5152 - F1: 0.4762
sub_20:Test (Best Model) - Loss: 3.1075 - Accuracy: 0.6061 - F1: 0.5662
sub_20:Test (Best Model) - Loss: 1.7570 - Accuracy: 0.6970 - F1: 0.6413
sub_21:Test (Best Model) - Loss: 2.1156 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 2.1896 - Accuracy: 0.3438 - F1: 0.3379
sub_21:Test (Best Model) - Loss: 1.9029 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 1.6813 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 1.8179 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 1.4341 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.5312 - F1: 0.4910
sub_21:Test (Best Model) - Loss: 1.6388 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.5312 - F1: 0.4684
sub_21:Test (Best Model) - Loss: 1.4869 - Accuracy: 0.5312 - F1: 0.5271
sub_21:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 1.6965 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 2.4000 - Accuracy: 0.3750 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 1.9179 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 1.8915 - Accuracy: 0.4688 - F1: 0.4231
sub_22:Test (Best Model) - Loss: 0.9890 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 1.1016 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.6875 - F1: 0.6667
sub_22:Test (Best Model) - Loss: 0.9426 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.9746 - Accuracy: 0.7500 - F1: 0.7091
sub_22:Test (Best Model) - Loss: 1.2431 - Accuracy: 0.6364 - F1: 0.5696
sub_22:Test (Best Model) - Loss: 1.2929 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 1.1629 - Accuracy: 0.7576 - F1: 0.7273
sub_22:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 1.5454 - Accuracy: 0.5758 - F1: 0.4653
sub_22:Test (Best Model) - Loss: 0.8240 - Accuracy: 0.7500 - F1: 0.7091
sub_22:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.8194 - Accuracy: 0.6875 - F1: 0.6667
sub_22:Test (Best Model) - Loss: 0.8622 - Accuracy: 0.7500 - F1: 0.7409
sub_22:Test (Best Model) - Loss: 0.9253 - Accuracy: 0.7500 - F1: 0.7333
sub_23:Test (Best Model) - Loss: 0.9144 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.9597 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.8437 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 1.2638 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 0.8528 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.8433 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.4878 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.5013 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.6875 - F1: 0.6875
sub_23:Test (Best Model) - Loss: 1.4358 - Accuracy: 0.6364 - F1: 0.5696
sub_23:Test (Best Model) - Loss: 0.7883 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.8789 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 1.0709 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 1.0903 - Accuracy: 0.7273 - F1: 0.6857
sub_24:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 1.5460 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 1.1060 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 1.4399 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 1.2022 - Accuracy: 0.5000 - F1: 0.4818
sub_24:Test (Best Model) - Loss: 1.2474 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 1.0332 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.0235 - Accuracy: 0.5625 - F1: 0.5556
sub_24:Test (Best Model) - Loss: 0.8778 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.7628 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 1.5829 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 1.5372 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 1.8978 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.5312 - F1: 0.4910
sub_25:Test (Best Model) - Loss: 1.9826 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 1.5631 - Accuracy: 0.5152 - F1: 0.5038
sub_25:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.5152 - F1: 0.4762
sub_25:Test (Best Model) - Loss: 1.8209 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 2.2394 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.8208 - Accuracy: 0.6562 - F1: 0.6102
sub_25:Test (Best Model) - Loss: 1.1693 - Accuracy: 0.6562 - F1: 0.6532
sub_25:Test (Best Model) - Loss: 1.2005 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 1.0390 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 1.0439 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 1.5025 - Accuracy: 0.6875 - F1: 0.6537
sub_25:Test (Best Model) - Loss: 1.2231 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 1.4627 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 1.7010 - Accuracy: 0.6875 - F1: 0.6364
sub_26:Test (Best Model) - Loss: 1.1520 - Accuracy: 0.6667 - F1: 0.6553
sub_26:Test (Best Model) - Loss: 1.8302 - Accuracy: 0.6364 - F1: 0.5909
sub_26:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.7576 - F1: 0.7381
sub_26:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.7879 - F1: 0.7746
sub_26:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.7576 - F1: 0.7273
sub_26:Test (Best Model) - Loss: 0.7620 - Accuracy: 0.7500 - F1: 0.7333
sub_26:Test (Best Model) - Loss: 1.0309 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.6250 - F1: 0.6190
sub_26:Test (Best Model) - Loss: 0.8070 - Accuracy: 0.7500 - F1: 0.7409
sub_26:Test (Best Model) - Loss: 0.9121 - Accuracy: 0.6562 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 0.3258 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.8750 - F1: 0.8667
sub_26:Test (Best Model) - Loss: 0.7952 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.5160 - Accuracy: 0.8438 - F1: 0.8303
sub_26:Test (Best Model) - Loss: 0.4963 - Accuracy: 0.7812 - F1: 0.7519
sub_27:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.6667 - F1: 0.6330
sub_27:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6364 - F1: 0.6071
sub_27:Test (Best Model) - Loss: 1.1991 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 1.0346 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 0.9105 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 1.4108 - Accuracy: 0.4545 - F1: 0.4417
sub_27:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.5455 - F1: 0.4995
sub_27:Test (Best Model) - Loss: 1.7685 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 1.0537 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 1.0846 - Accuracy: 0.6250 - F1: 0.6190
sub_27:Test (Best Model) - Loss: 1.7346 - Accuracy: 0.6250 - F1: 0.5844
sub_27:Test (Best Model) - Loss: 1.2570 - Accuracy: 0.5938 - F1: 0.5733
sub_27:Test (Best Model) - Loss: 1.7656 - Accuracy: 0.5625 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.6875 - F1: 0.6761
sub_28:Test (Best Model) - Loss: 0.9455 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 2.2991 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 1.9983 - Accuracy: 0.4375 - F1: 0.4170
sub_28:Test (Best Model) - Loss: 2.5197 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 3.3657 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 2.6268 - Accuracy: 0.4375 - F1: 0.4286
sub_28:Test (Best Model) - Loss: 2.2700 - Accuracy: 0.5938 - F1: 0.5135
sub_28:Test (Best Model) - Loss: 4.9881 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 1.4783 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 1.2102 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 1.1395 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 1.4624 - Accuracy: 0.6250 - F1: 0.6250
sub_28:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.4688 - F1: 0.4555
sub_29:Test (Best Model) - Loss: 1.2912 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.9024 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.7812 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.6875 - F1: 0.6135
sub_29:Test (Best Model) - Loss: 0.4297 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.1318 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.1095 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.3513 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.4526 - Accuracy: 0.8788 - F1: 0.8778
sub_29:Test (Best Model) - Loss: 0.4665 - Accuracy: 0.8788 - F1: 0.8778
sub_29:Test (Best Model) - Loss: 0.1902 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.3119 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.9091 - F1: 0.9077

=== Summary Results ===

acc: 63.75 ± 9.86
F1: 61.03 ± 10.45
acc-in: 71.00 ± 8.08
F1-in: 68.23 ± 8.97
