lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6250 - F1: 0.6113
sub_1:Test (Best Model) - Loss: 0.5629 - Accuracy: 0.8438 - F1: 0.8424
sub_1:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.5625 - F1: 0.5466
sub_1:Test (Best Model) - Loss: 0.5731 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.5409 - Accuracy: 0.7879 - F1: 0.7746
sub_1:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.6970 - F1: 0.6898
sub_1:Test (Best Model) - Loss: 0.5492 - Accuracy: 0.8485 - F1: 0.8462
sub_1:Test (Best Model) - Loss: 0.5737 - Accuracy: 0.6970 - F1: 0.6413
sub_1:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.7273 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.5759 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.4982 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.5864 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.5139 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.5879 - Accuracy: 0.7500 - F1: 0.7460
sub_2:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.4848 - F1: 0.4772
sub_2:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.4848 - F1: 0.4848
sub_2:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.4848 - F1: 0.4829
sub_2:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.5758 - F1: 0.5417
sub_2:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.6364 - F1: 0.6192
sub_2:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4062 - F1: 0.4057
sub_2:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5625 - F1: 0.5625
sub_2:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5625 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6875 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5312 - F1: 0.4910
sub_2:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.7576 - F1: 0.7381
sub_2:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.4545 - F1: 0.4417
sub_2:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4545 - F1: 0.4288
sub_2:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.4688 - F1: 0.4682
sub_3:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6250 - F1: 0.5844
sub_3:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.3750 - F1: 0.3725
sub_3:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.5455 - F1: 0.5387
sub_3:Test (Best Model) - Loss: 0.7320 - Accuracy: 0.3333 - F1: 0.2798
sub_3:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.7273 - F1: 0.6857
sub_3:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5758 - F1: 0.5754
sub_3:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5455 - F1: 0.5299
sub_3:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.5152 - F1: 0.4545
sub_3:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.3939 - F1: 0.3797
sub_4:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.6173 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.8182 - F1: 0.8036
sub_4:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.7273 - F1: 0.7232
sub_4:Test (Best Model) - Loss: 0.5993 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.5677 - Accuracy: 0.8485 - F1: 0.8462
sub_4:Test (Best Model) - Loss: 0.5947 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4848 - F1: 0.4772
sub_4:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.7576 - F1: 0.7556
sub_4:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.7273 - F1: 0.7273
sub_4:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.6970 - F1: 0.6944
sub_5:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.5625 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.5964 - Accuracy: 0.7188 - F1: 0.7163
sub_5:Test (Best Model) - Loss: 0.6157 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.6162 - Accuracy: 0.5625 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6179 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6163 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.5625 - F1: 0.5466
sub_5:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.5625 - F1: 0.5556
sub_6:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.4688 - F1: 0.4640
sub_6:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.6562 - F1: 0.6559
sub_6:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.4545 - F1: 0.4288
sub_6:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.6667 - F1: 0.6459
sub_6:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5758 - F1: 0.4978
sub_6:Test (Best Model) - Loss: 0.7414 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5455 - F1: 0.4995
sub_6:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5758 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.4848 - F1: 0.4672
sub_6:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.6667 - F1: 0.6654
sub_6:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.5758 - F1: 0.5754
sub_6:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6364 - F1: 0.6360
sub_7:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.6562 - F1: 0.6390
sub_7:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5000 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.6875 - F1: 0.6364
sub_7:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4688 - F1: 0.4640
sub_7:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 0.6470 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.6875 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 0.7185 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.5466
sub_8:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.5625 - F1: 0.5152
sub_8:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.5608
sub_9:Test (Best Model) - Loss: 0.4697 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 0.5073 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.4944 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.5543 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.5793 - Accuracy: 0.7812 - F1: 0.7703
sub_9:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.7188 - F1: 0.6811
sub_9:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.5938 - F1: 0.5901
sub_9:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.5312 - F1: 0.5077
sub_9:Test (Best Model) - Loss: 0.4604 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.5788 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 0.3773 - Accuracy: 0.9375 - F1: 0.9365
sub_10:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.3438 - F1: 0.3431
sub_10:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.5967 - Accuracy: 0.7188 - F1: 0.6632
sub_10:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6250 - F1: 0.6235
sub_10:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6562 - F1: 0.6559
sub_10:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5938 - F1: 0.5901
sub_10:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.5938 - F1: 0.5589
sub_10:Test (Best Model) - Loss: 0.7172 - Accuracy: 0.3750 - F1: 0.3725
sub_10:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5152 - F1: 0.5111
sub_10:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5455 - F1: 0.5387
sub_10:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4848 - F1: 0.4829
sub_10:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6364 - F1: 0.6192
sub_10:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.6061 - F1: 0.6002
sub_11:Test (Best Model) - Loss: 0.7104 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.7771 - Accuracy: 0.3333 - F1: 0.3327
sub_11:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5152 - F1: 0.4545
sub_11:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.7273 - F1: 0.7102
sub_11:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4242 - F1: 0.3365
sub_11:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.5758 - F1: 0.5227
sub_11:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5152 - F1: 0.4923
sub_12:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.6562 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.8438 - F1: 0.8303
sub_12:Test (Best Model) - Loss: 0.5671 - Accuracy: 0.8125 - F1: 0.8000
sub_12:Test (Best Model) - Loss: 0.5965 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 0.5514 - Accuracy: 0.7500 - F1: 0.7229
sub_12:Test (Best Model) - Loss: 0.5296 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.7273 - F1: 0.6997
sub_12:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.5938 - F1: 0.5589
sub_12:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.6562 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5312 - F1: 0.5195
sub_12:Test (Best Model) - Loss: 0.6254 - Accuracy: 0.6875 - F1: 0.6135
sub_12:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.6562 - F1: 0.6476
sub_13:Test (Best Model) - Loss: 0.5623 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.7812 - F1: 0.7625
sub_13:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6250 - F1: 0.6000
sub_13:Test (Best Model) - Loss: 0.5842 - Accuracy: 0.7188 - F1: 0.6632
sub_13:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.6562 - F1: 0.6267
sub_13:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6970 - F1: 0.6944
sub_13:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.7879 - F1: 0.7871
sub_13:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.7273 - F1: 0.7273
sub_13:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.6970 - F1: 0.6827
sub_13:Test (Best Model) - Loss: 0.6142 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.7188 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.5938 - F1: 0.5135
sub_13:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6250 - F1: 0.5844
sub_14:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.5625 - F1: 0.5625
sub_14:Test (Best Model) - Loss: 0.6001 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.5608
sub_14:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6155 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.5577 - Accuracy: 0.8438 - F1: 0.8398
sub_14:Test (Best Model) - Loss: 0.6155 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.7500 - F1: 0.7229
sub_14:Test (Best Model) - Loss: 0.5948 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.7188 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5938 - F1: 0.5733
sub_14:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6875 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.8438 - F1: 0.8359
sub_15:Test (Best Model) - Loss: 0.5770 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5715 - Accuracy: 0.7812 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 0.6100 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6875 - F1: 0.6875
sub_15:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.8125 - F1: 0.8118
sub_15:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.8125 - F1: 0.7922
sub_15:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.6875 - F1: 0.6863
sub_15:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.7193 - Accuracy: 0.3125 - F1: 0.3016
sub_16:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5312 - F1: 0.5077
sub_16:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6085 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4688 - F1: 0.4640
sub_16:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6667 - F1: 0.6553
sub_17:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7576 - F1: 0.7381
sub_17:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6061 - F1: 0.6046
sub_17:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6667 - F1: 0.6553
sub_17:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4545 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 0.7349 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.6250 - F1: 0.6250
sub_17:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.5000 - F1: 0.4980
sub_17:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.5625 - F1: 0.5608
sub_18:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.6667 - F1: 0.6617
sub_18:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6364 - F1: 0.6071
sub_18:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.6364 - F1: 0.6192
sub_18:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.8182 - F1: 0.8167
sub_18:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.5963 - Accuracy: 0.8750 - F1: 0.8730
sub_18:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.7500 - F1: 0.7409
sub_18:Test (Best Model) - Loss: 0.5895 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.5769 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.8125 - F1: 0.8118
sub_18:Test (Best Model) - Loss: 0.5283 - Accuracy: 0.7812 - F1: 0.7703
sub_18:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.7500 - F1: 0.7460
sub_19:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.5938 - F1: 0.5393
sub_19:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.5312 - F1: 0.4910
sub_19:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 0.6487 - Accuracy: 0.6250 - F1: 0.6113
sub_19:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.7188 - F1: 0.7117
sub_19:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.6875 - F1: 0.6761
sub_19:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.6875 - F1: 0.6364
sub_19:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.7188 - F1: 0.6811
sub_19:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.7135 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 0.6110 - Accuracy: 0.7188 - F1: 0.7163
sub_20:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.6250 - F1: 0.6250
sub_20:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 0.5725 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5152 - F1: 0.5147
sub_20:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6364 - F1: 0.6192
sub_20:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.5758 - F1: 0.5754
sub_20:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 0.5764 - Accuracy: 0.6970 - F1: 0.6967
sub_21:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5938 - F1: 0.5836
sub_21:Test (Best Model) - Loss: 0.7312 - Accuracy: 0.5000 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5000 - F1: 0.3816
sub_21:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 0.7522 - Accuracy: 0.3125 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.4688 - F1: 0.4640
sub_21:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.4062 - F1: 0.2889
sub_21:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5938 - F1: 0.5836
sub_21:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.7778 - Accuracy: 0.3750 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 0.7397 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.5625 - F1: 0.5625
sub_22:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.8125 - F1: 0.8000
sub_22:Test (Best Model) - Loss: 0.5974 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6875 - F1: 0.6761
sub_22:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.5628 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.5455 - F1: 0.4995
sub_22:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.7576 - F1: 0.7381
sub_22:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.7879 - F1: 0.7806
sub_22:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5455 - F1: 0.4762
sub_22:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.5758 - F1: 0.4978
sub_22:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.7500 - F1: 0.7490
sub_22:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5000 - F1: 0.4667
sub_22:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.7812 - F1: 0.7625
sub_23:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.7273 - F1: 0.7179
sub_23:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.8485 - F1: 0.8433
sub_23:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.7576 - F1: 0.7519
sub_23:Test (Best Model) - Loss: 0.5640 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6562 - F1: 0.6390
sub_23:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.7188 - F1: 0.7117
sub_23:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.5549 - Accuracy: 0.7273 - F1: 0.7232
sub_23:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.5836 - Accuracy: 0.7273 - F1: 0.7179
sub_23:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.6667 - F1: 0.6330
sub_23:Test (Best Model) - Loss: 0.5315 - Accuracy: 0.8182 - F1: 0.8096
sub_24:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6562 - F1: 0.6559
sub_24:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5000 - F1: 0.5000
sub_24:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.5000 - F1: 0.4667
sub_24:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6875 - F1: 0.6825
sub_24:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.7517 - Accuracy: 0.4062 - F1: 0.3764
sub_24:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5625 - F1: 0.5625
sub_25:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.4242 - F1: 0.3883
sub_25:Test (Best Model) - Loss: 0.7285 - Accuracy: 0.3636 - F1: 0.3636
sub_25:Test (Best Model) - Loss: 0.7153 - Accuracy: 0.5152 - F1: 0.5147
sub_25:Test (Best Model) - Loss: 0.7156 - Accuracy: 0.5758 - F1: 0.5417
sub_25:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5152 - F1: 0.5111
sub_25:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4062 - F1: 0.4057
sub_25:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5938 - F1: 0.5901
sub_25:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5625 - F1: 0.5333
sub_25:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.4375 - F1: 0.4286
sub_25:Test (Best Model) - Loss: 0.7290 - Accuracy: 0.3750 - F1: 0.3651
sub_25:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.5000 - F1: 0.4818
sub_25:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.5938 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.5938 - F1: 0.5733
sub_26:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.7879 - F1: 0.7847
sub_26:Test (Best Model) - Loss: 0.5670 - Accuracy: 0.6667 - F1: 0.6617
sub_26:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.5507 - Accuracy: 0.6970 - F1: 0.6413
sub_26:Test (Best Model) - Loss: 0.4937 - Accuracy: 0.9091 - F1: 0.9077
sub_26:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.6875 - F1: 0.6761
sub_26:Test (Best Model) - Loss: 0.5598 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.6062 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.5530 - Accuracy: 0.8125 - F1: 0.8000
sub_26:Test (Best Model) - Loss: 0.5472 - Accuracy: 0.8125 - F1: 0.8057
sub_26:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 0.5993 - Accuracy: 0.7500 - F1: 0.7409
sub_26:Test (Best Model) - Loss: 0.4988 - Accuracy: 0.9062 - F1: 0.9015
sub_27:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7576 - F1: 0.7381
sub_27:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6061 - F1: 0.6046
sub_27:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4545 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 0.7349 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.6250 - F1: 0.6250
sub_27:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.5000 - F1: 0.4980
sub_27:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.5333
sub_27:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6250 - F1: 0.6113
sub_28:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.7424 - Accuracy: 0.4375 - F1: 0.4170
sub_28:Test (Best Model) - Loss: 0.7266 - Accuracy: 0.6250 - F1: 0.5362
sub_28:Test (Best Model) - Loss: 0.7282 - Accuracy: 0.6250 - F1: 0.5636
sub_28:Test (Best Model) - Loss: 0.7292 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.7736 - Accuracy: 0.5625 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.6562 - F1: 0.6267
sub_28:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 0.7366 - Accuracy: 0.4375 - F1: 0.4170
sub_28:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.3125 - F1: 0.3016
sub_28:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6562 - F1: 0.6532
sub_29:Test (Best Model) - Loss: 0.4188 - Accuracy: 0.8750 - F1: 0.8704
sub_29:Test (Best Model) - Loss: 0.4824 - Accuracy: 0.8438 - F1: 0.8398
sub_29:Test (Best Model) - Loss: 0.4288 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.4258 - Accuracy: 0.9062 - F1: 0.9015
sub_29:Test (Best Model) - Loss: 0.4052 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.4484 - Accuracy: 0.8750 - F1: 0.8730
sub_29:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.4582 - Accuracy: 0.9062 - F1: 0.9039
sub_29:Test (Best Model) - Loss: 0.4353 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.4733 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.4590 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.9697 - F1: 0.9696
sub_29:Test (Best Model) - Loss: 0.3929 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.3852 - Accuracy: 0.9091 - F1: 0.9077

=== Summary Results ===

acc: 63.47 ± 10.13
F1: 61.86 ± 10.46
acc-in: 69.00 ± 7.52
F1-in: 67.26 ± 7.68
