lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.5738 - Accuracy: 0.7500 - F1: 0.7460
sub_1:Test (Best Model) - Loss: 0.5158 - Accuracy: 0.7500 - F1: 0.7460
sub_1:Test (Best Model) - Loss: 0.5847 - Accuracy: 0.7500 - F1: 0.7460
sub_1:Test (Best Model) - Loss: 0.4063 - Accuracy: 0.8750 - F1: 0.8704
sub_1:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.4485 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.4326 - Accuracy: 0.8788 - F1: 0.8778
sub_1:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7879 - F1: 0.7847
sub_1:Test (Best Model) - Loss: 1.0567 - Accuracy: 0.7576 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.8353 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.9144 - Accuracy: 0.8125 - F1: 0.8000
sub_1:Test (Best Model) - Loss: 0.3560 - Accuracy: 0.8438 - F1: 0.8398
sub_1:Test (Best Model) - Loss: 0.3378 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.2547 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.4509 - Accuracy: 0.8438 - F1: 0.8398
sub_2:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 1.6703 - Accuracy: 0.7879 - F1: 0.7746
sub_2:Test (Best Model) - Loss: 2.0099 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 1.7665 - Accuracy: 0.6061 - F1: 0.5926
sub_2:Test (Best Model) - Loss: 1.9195 - Accuracy: 0.4688 - F1: 0.4640
sub_2:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 1.1279 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 1.0854 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.9334 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 1.8380 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.9324 - Accuracy: 0.7273 - F1: 0.7263
sub_2:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 1.9656 - Accuracy: 0.6970 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 1.6711 - Accuracy: 0.4688 - F1: 0.4555
sub_3:Test (Best Model) - Loss: 1.6680 - Accuracy: 0.5000 - F1: 0.4818
sub_3:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 1.4502 - Accuracy: 0.6875 - F1: 0.6761
sub_3:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.5625 - F1: 0.5625
sub_3:Test (Best Model) - Loss: 1.5875 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 1.4584 - Accuracy: 0.4545 - F1: 0.4417
sub_3:Test (Best Model) - Loss: 0.9765 - Accuracy: 0.6061 - F1: 0.6061
sub_3:Test (Best Model) - Loss: 2.2051 - Accuracy: 0.4848 - F1: 0.4063
sub_3:Test (Best Model) - Loss: 1.5548 - Accuracy: 0.4545 - F1: 0.4288
sub_3:Test (Best Model) - Loss: 2.5273 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 2.6428 - Accuracy: 0.4242 - F1: 0.4046
sub_3:Test (Best Model) - Loss: 1.8358 - Accuracy: 0.4848 - F1: 0.4328
sub_3:Test (Best Model) - Loss: 2.3677 - Accuracy: 0.5152 - F1: 0.5038
sub_3:Test (Best Model) - Loss: 2.5624 - Accuracy: 0.3030 - F1: 0.2595
sub_4:Test (Best Model) - Loss: 1.2257 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.5921 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.8498 - Accuracy: 0.7879 - F1: 0.7664
sub_4:Test (Best Model) - Loss: 0.2783 - Accuracy: 0.9091 - F1: 0.9060
sub_4:Test (Best Model) - Loss: 1.2668 - Accuracy: 0.7273 - F1: 0.6857
sub_4:Test (Best Model) - Loss: 0.9215 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 1.4492 - Accuracy: 0.6364 - F1: 0.5696
sub_4:Test (Best Model) - Loss: 0.8920 - Accuracy: 0.6970 - F1: 0.6827
sub_4:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 2.0787 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.5802 - Accuracy: 0.7273 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.6364 - F1: 0.6192
sub_4:Test (Best Model) - Loss: 0.5720 - Accuracy: 0.7576 - F1: 0.7574
sub_4:Test (Best Model) - Loss: 0.5311 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.2507 - Accuracy: 0.8485 - F1: 0.8462
sub_5:Test (Best Model) - Loss: 2.2813 - Accuracy: 0.4688 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 1.2704 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 2.7860 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 1.4035 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 1.6754 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 1.1862 - Accuracy: 0.4375 - F1: 0.4000
sub_5:Test (Best Model) - Loss: 1.1013 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 1.0084 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.8312 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 1.2107 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 1.2809 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 1.5423 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.4906 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 1.0816 - Accuracy: 0.5938 - F1: 0.5901
sub_6:Test (Best Model) - Loss: 1.4547 - Accuracy: 0.5000 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.8278 - Accuracy: 0.8125 - F1: 0.8000
sub_6:Test (Best Model) - Loss: 2.4692 - Accuracy: 0.5455 - F1: 0.5171
sub_6:Test (Best Model) - Loss: 2.8999 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 1.7946 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 2.7910 - Accuracy: 0.4242 - F1: 0.3660
sub_6:Test (Best Model) - Loss: 2.2252 - Accuracy: 0.5455 - F1: 0.4995
sub_6:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.6667 - F1: 0.5935
sub_6:Test (Best Model) - Loss: 1.6372 - Accuracy: 0.6061 - F1: 0.5460
sub_6:Test (Best Model) - Loss: 1.2293 - Accuracy: 0.6364 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 1.2763 - Accuracy: 0.6667 - F1: 0.6553
sub_6:Test (Best Model) - Loss: 1.7050 - Accuracy: 0.6364 - F1: 0.5417
sub_7:Test (Best Model) - Loss: 0.9316 - Accuracy: 0.6875 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 1.4819 - Accuracy: 0.5000 - F1: 0.4459
sub_7:Test (Best Model) - Loss: 1.9261 - Accuracy: 0.5938 - F1: 0.5836
sub_7:Test (Best Model) - Loss: 1.1777 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 1.5210 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 2.4200 - Accuracy: 0.4062 - F1: 0.3914
sub_7:Test (Best Model) - Loss: 1.7300 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 2.0057 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 1.6275 - Accuracy: 0.4375 - F1: 0.4000
sub_7:Test (Best Model) - Loss: 1.2216 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.4674 - Accuracy: 0.6250 - F1: 0.6113
sub_7:Test (Best Model) - Loss: 2.2089 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.9079 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.5938 - F1: 0.5934
sub_8:Test (Best Model) - Loss: 1.6736 - Accuracy: 0.5625 - F1: 0.5152
sub_8:Test (Best Model) - Loss: 1.7517 - Accuracy: 0.6562 - F1: 0.5883
sub_8:Test (Best Model) - Loss: 1.2046 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.8979 - Accuracy: 0.7812 - F1: 0.7625
sub_8:Test (Best Model) - Loss: 2.0220 - Accuracy: 0.6562 - F1: 0.5594
sub_8:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 1.9316 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.5938 - F1: 0.5589
sub_8:Test (Best Model) - Loss: 2.7767 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 1.4916 - Accuracy: 0.4375 - F1: 0.4375
sub_8:Test (Best Model) - Loss: 0.8499 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.7812 - F1: 0.7703
sub_8:Test (Best Model) - Loss: 1.4785 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 0.8919 - Accuracy: 0.6875 - F1: 0.6667
sub_9:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.3732 - Accuracy: 0.8438 - F1: 0.8398
sub_9:Test (Best Model) - Loss: 0.3130 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.4973 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.7639 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 1.6360 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.7188 - F1: 0.7046
sub_9:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.6250 - F1: 0.6190
sub_9:Test (Best Model) - Loss: 1.5101 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 1.1248 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 2.3307 - Accuracy: 0.6562 - F1: 0.6532
sub_9:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.8438 - F1: 0.8424
sub_9:Test (Best Model) - Loss: 2.3289 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 1.2875 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 1.4586 - Accuracy: 0.7812 - F1: 0.7703
sub_10:Test (Best Model) - Loss: 1.2659 - Accuracy: 0.5938 - F1: 0.5393
sub_10:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.4688 - F1: 0.4231
sub_10:Test (Best Model) - Loss: 0.7460 - Accuracy: 0.6875 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 1.2243 - Accuracy: 0.6250 - F1: 0.6000
sub_10:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 1.7657 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 1.6798 - Accuracy: 0.5000 - F1: 0.4980
sub_10:Test (Best Model) - Loss: 1.7317 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 2.0786 - Accuracy: 0.5312 - F1: 0.4684
sub_10:Test (Best Model) - Loss: 2.3798 - Accuracy: 0.4688 - F1: 0.4555
sub_10:Test (Best Model) - Loss: 1.9182 - Accuracy: 0.5455 - F1: 0.5299
sub_10:Test (Best Model) - Loss: 2.1783 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.5590 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 1.7071 - Accuracy: 0.6061 - F1: 0.5815
sub_11:Test (Best Model) - Loss: 2.9175 - Accuracy: 0.5152 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 2.0123 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 2.1914 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 1.7708 - Accuracy: 0.5455 - F1: 0.5455
sub_11:Test (Best Model) - Loss: 3.2049 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 1.6985 - Accuracy: 0.5758 - F1: 0.4653
sub_11:Test (Best Model) - Loss: 1.7123 - Accuracy: 0.5455 - F1: 0.4457
sub_11:Test (Best Model) - Loss: 1.0840 - Accuracy: 0.7273 - F1: 0.7102
sub_11:Test (Best Model) - Loss: 2.4809 - Accuracy: 0.4848 - F1: 0.4063
sub_11:Test (Best Model) - Loss: 1.4552 - Accuracy: 0.6667 - F1: 0.5935
sub_11:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.6061 - F1: 0.5815
sub_11:Test (Best Model) - Loss: 1.1950 - Accuracy: 0.6970 - F1: 0.6591
sub_11:Test (Best Model) - Loss: 1.4753 - Accuracy: 0.6061 - F1: 0.5460
sub_11:Test (Best Model) - Loss: 1.2079 - Accuracy: 0.6667 - F1: 0.6330
sub_11:Test (Best Model) - Loss: 1.6552 - Accuracy: 0.5758 - F1: 0.4978
sub_12:Test (Best Model) - Loss: 0.8677 - Accuracy: 0.7812 - F1: 0.7625
sub_12:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 1.0756 - Accuracy: 0.7812 - F1: 0.7625
sub_12:Test (Best Model) - Loss: 0.7438 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 1.2878 - Accuracy: 0.6562 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 0.9243 - Accuracy: 0.6970 - F1: 0.6726
sub_12:Test (Best Model) - Loss: 0.8451 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.8842 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.6667 - F1: 0.6159
sub_12:Test (Best Model) - Loss: 0.3970 - Accuracy: 0.8182 - F1: 0.8096
sub_12:Test (Best Model) - Loss: 1.1235 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 1.8961 - Accuracy: 0.5938 - F1: 0.5733
sub_12:Test (Best Model) - Loss: 1.0522 - Accuracy: 0.7188 - F1: 0.7046
sub_12:Test (Best Model) - Loss: 1.7864 - Accuracy: 0.6250 - F1: 0.5844
sub_12:Test (Best Model) - Loss: 1.6666 - Accuracy: 0.6875 - F1: 0.6364
sub_13:Test (Best Model) - Loss: 0.3181 - Accuracy: 0.8438 - F1: 0.8398
sub_13:Test (Best Model) - Loss: 0.4895 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3003 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.2233 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.2372 - Accuracy: 0.9375 - F1: 0.9365
sub_13:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.7879 - F1: 0.7664
sub_13:Test (Best Model) - Loss: 0.3209 - Accuracy: 0.8485 - F1: 0.8479
sub_13:Test (Best Model) - Loss: 0.5171 - Accuracy: 0.7879 - F1: 0.7871
sub_13:Test (Best Model) - Loss: 0.8105 - Accuracy: 0.7273 - F1: 0.7179
sub_13:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.6970 - F1: 0.6591
sub_13:Test (Best Model) - Loss: 0.4817 - Accuracy: 0.8438 - F1: 0.8436
sub_13:Test (Best Model) - Loss: 0.7124 - Accuracy: 0.7500 - F1: 0.7409
sub_13:Test (Best Model) - Loss: 0.3823 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.5155 - Accuracy: 0.8750 - F1: 0.8750
sub_13:Test (Best Model) - Loss: 1.1476 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 0.7686 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.8718 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.5190 - Accuracy: 0.8125 - F1: 0.8095
sub_14:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.3505 - Accuracy: 0.9375 - F1: 0.9373
sub_14:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 1.0074 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.6313 - Accuracy: 0.7812 - F1: 0.7625
sub_14:Test (Best Model) - Loss: 0.8483 - Accuracy: 0.7188 - F1: 0.6811
sub_14:Test (Best Model) - Loss: 1.7587 - Accuracy: 0.5938 - F1: 0.4793
sub_14:Test (Best Model) - Loss: 1.2111 - Accuracy: 0.7188 - F1: 0.7046
sub_14:Test (Best Model) - Loss: 1.2280 - Accuracy: 0.6875 - F1: 0.6135
sub_14:Test (Best Model) - Loss: 0.9031 - Accuracy: 0.8125 - F1: 0.8057
sub_15:Test (Best Model) - Loss: 2.2886 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.3184 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.9841 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 1.4014 - Accuracy: 0.7812 - F1: 0.7703
sub_15:Test (Best Model) - Loss: 1.0869 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.7500 - F1: 0.7460
sub_15:Test (Best Model) - Loss: 3.1056 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 2.0691 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 1.6978 - Accuracy: 0.6875 - F1: 0.6761
sub_15:Test (Best Model) - Loss: 2.3301 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 1.4486 - Accuracy: 0.4688 - F1: 0.4555
sub_15:Test (Best Model) - Loss: 2.5290 - Accuracy: 0.4375 - F1: 0.3455
sub_15:Test (Best Model) - Loss: 2.1935 - Accuracy: 0.4375 - F1: 0.4000
sub_15:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 1.2025 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 1.0836 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 1.1167 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 1.1429 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 1.5194 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 2.0510 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 1.4316 - Accuracy: 0.6562 - F1: 0.6267
sub_16:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 2.2116 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.8953 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 1.8559 - Accuracy: 0.5625 - F1: 0.4909
sub_16:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 2.0936 - Accuracy: 0.4375 - F1: 0.3455
sub_17:Test (Best Model) - Loss: 1.5168 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 0.9495 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.8723 - Accuracy: 0.5455 - F1: 0.5438
sub_17:Test (Best Model) - Loss: 1.1680 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 1.4950 - Accuracy: 0.3939 - F1: 0.3797
sub_17:Test (Best Model) - Loss: 1.4283 - Accuracy: 0.4242 - F1: 0.3660
sub_17:Test (Best Model) - Loss: 1.8443 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 2.0467 - Accuracy: 0.6061 - F1: 0.5662
sub_17:Test (Best Model) - Loss: 1.1813 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 1.6718 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 2.1342 - Accuracy: 0.5000 - F1: 0.4667
sub_17:Test (Best Model) - Loss: 1.6375 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.6562 - F1: 0.6267
sub_18:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.4769 - Accuracy: 0.7879 - F1: 0.7746
sub_18:Test (Best Model) - Loss: 0.5272 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.6203 - Accuracy: 0.8182 - F1: 0.8096
sub_18:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.8788 - F1: 0.8778
sub_18:Test (Best Model) - Loss: 0.9240 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.7667 - Accuracy: 0.6562 - F1: 0.6559
sub_18:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7812 - F1: 0.7625
sub_18:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 1.0872 - Accuracy: 0.6875 - F1: 0.6537
sub_18:Test (Best Model) - Loss: 0.4779 - Accuracy: 0.9062 - F1: 0.9039
sub_18:Test (Best Model) - Loss: 0.7764 - Accuracy: 0.8125 - F1: 0.8095
sub_18:Test (Best Model) - Loss: 0.5744 - Accuracy: 0.7812 - F1: 0.7625
sub_19:Test (Best Model) - Loss: 2.6656 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 1.4007 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 1.6461 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 1.4656 - Accuracy: 0.5938 - F1: 0.5589
sub_19:Test (Best Model) - Loss: 1.7801 - Accuracy: 0.4688 - F1: 0.3191
sub_19:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.7500 - F1: 0.7229
sub_19:Test (Best Model) - Loss: 1.7991 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 1.6508 - Accuracy: 0.5625 - F1: 0.5466
sub_19:Test (Best Model) - Loss: 2.0580 - Accuracy: 0.5000 - F1: 0.4667
sub_19:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.6250 - F1: 0.6190
sub_19:Test (Best Model) - Loss: 0.8527 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.7500 - F1: 0.7460
sub_19:Test (Best Model) - Loss: 0.9852 - Accuracy: 0.6250 - F1: 0.6250
sub_20:Test (Best Model) - Loss: 1.5811 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 0.9362 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.6562 - F1: 0.6267
sub_20:Test (Best Model) - Loss: 1.4069 - Accuracy: 0.5625 - F1: 0.5152
sub_20:Test (Best Model) - Loss: 2.2898 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 1.6824 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 1.8091 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 2.2136 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.7500 - F1: 0.7409
sub_20:Test (Best Model) - Loss: 1.1918 - Accuracy: 0.8125 - F1: 0.8057
sub_20:Test (Best Model) - Loss: 3.1186 - Accuracy: 0.4545 - F1: 0.4288
sub_20:Test (Best Model) - Loss: 1.8569 - Accuracy: 0.6364 - F1: 0.6071
sub_20:Test (Best Model) - Loss: 2.0326 - Accuracy: 0.5455 - F1: 0.5387
sub_20:Test (Best Model) - Loss: 3.2904 - Accuracy: 0.5758 - F1: 0.5417
sub_20:Test (Best Model) - Loss: 1.6462 - Accuracy: 0.6364 - F1: 0.6333
sub_21:Test (Best Model) - Loss: 3.1677 - Accuracy: 0.3750 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 2.1283 - Accuracy: 0.3125 - F1: 0.3016
sub_21:Test (Best Model) - Loss: 2.9176 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 1.7879 - Accuracy: 0.4375 - F1: 0.4375
sub_21:Test (Best Model) - Loss: 1.8514 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.5625 - F1: 0.5556
sub_21:Test (Best Model) - Loss: 1.5597 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 1.4890 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 1.8123 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 1.9561 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 1.9391 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 2.4138 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 2.8128 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 2.6012 - Accuracy: 0.3438 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 2.0904 - Accuracy: 0.3438 - F1: 0.3273
sub_22:Test (Best Model) - Loss: 1.0138 - Accuracy: 0.5938 - F1: 0.5836
sub_22:Test (Best Model) - Loss: 1.2044 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.6250 - F1: 0.5636
sub_22:Test (Best Model) - Loss: 1.0388 - Accuracy: 0.7188 - F1: 0.6811
sub_22:Test (Best Model) - Loss: 1.6730 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 1.5250 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 1.2396 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 2.3089 - Accuracy: 0.5758 - F1: 0.4225
sub_22:Test (Best Model) - Loss: 2.0599 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 1.1554 - Accuracy: 0.7500 - F1: 0.7490
sub_22:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.7812 - F1: 0.7793
sub_22:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 0.9587 - Accuracy: 0.8125 - F1: 0.7922
sub_22:Test (Best Model) - Loss: 0.8689 - Accuracy: 0.7188 - F1: 0.6946
sub_23:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.7273 - F1: 0.7102
sub_23:Test (Best Model) - Loss: 1.1060 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 0.9282 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 1.0969 - Accuracy: 0.6667 - F1: 0.5935
sub_23:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 1.1833 - Accuracy: 0.6250 - F1: 0.6190
sub_23:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.7500 - F1: 0.7333
sub_23:Test (Best Model) - Loss: 0.5367 - Accuracy: 0.7812 - F1: 0.7793
sub_23:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 1.1495 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 1.4596 - Accuracy: 0.6364 - F1: 0.5909
sub_23:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.8485 - F1: 0.8390
sub_24:Test (Best Model) - Loss: 1.1389 - Accuracy: 0.4688 - F1: 0.3976
sub_24:Test (Best Model) - Loss: 1.7647 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 1.2382 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 1.6413 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 1.3404 - Accuracy: 0.5312 - F1: 0.5077
sub_24:Test (Best Model) - Loss: 1.1417 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 1.5477 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 1.0174 - Accuracy: 0.6250 - F1: 0.6235
sub_24:Test (Best Model) - Loss: 0.5520 - Accuracy: 0.7188 - F1: 0.7185
sub_24:Test (Best Model) - Loss: 1.6417 - Accuracy: 0.3438 - F1: 0.3431
sub_24:Test (Best Model) - Loss: 1.6548 - Accuracy: 0.5312 - F1: 0.5271
sub_24:Test (Best Model) - Loss: 1.9144 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 1.9937 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 2.6337 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 1.8519 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 2.0324 - Accuracy: 0.5152 - F1: 0.4762
sub_25:Test (Best Model) - Loss: 1.9533 - Accuracy: 0.4848 - F1: 0.3265
sub_25:Test (Best Model) - Loss: 1.9858 - Accuracy: 0.5455 - F1: 0.4995
sub_25:Test (Best Model) - Loss: 1.5768 - Accuracy: 0.5312 - F1: 0.4684
sub_25:Test (Best Model) - Loss: 0.9107 - Accuracy: 0.5938 - F1: 0.5135
sub_25:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 1.6594 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 1.0508 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 0.7843 - Accuracy: 0.6562 - F1: 0.6532
sub_25:Test (Best Model) - Loss: 1.7061 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.9472 - Accuracy: 0.7188 - F1: 0.6946
sub_25:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.5938 - F1: 0.5135
sub_25:Test (Best Model) - Loss: 2.2389 - Accuracy: 0.6250 - F1: 0.5844
sub_26:Test (Best Model) - Loss: 1.1097 - Accuracy: 0.6970 - F1: 0.6898
sub_26:Test (Best Model) - Loss: 1.9707 - Accuracy: 0.6667 - F1: 0.6459
sub_26:Test (Best Model) - Loss: 1.0022 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.7050 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.8007 - Accuracy: 0.7812 - F1: 0.7703
sub_26:Test (Best Model) - Loss: 1.0379 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 1.3357 - Accuracy: 0.7500 - F1: 0.7500
sub_26:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.7188 - F1: 0.6811
sub_26:Test (Best Model) - Loss: 0.9259 - Accuracy: 0.7500 - F1: 0.7229
sub_26:Test (Best Model) - Loss: 0.2758 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.9667 - Accuracy: 0.6875 - F1: 0.6135
sub_26:Test (Best Model) - Loss: 1.2650 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.3045 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.8611 - Accuracy: 0.7812 - F1: 0.7519
sub_27:Test (Best Model) - Loss: 1.5168 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.9495 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.8723 - Accuracy: 0.5455 - F1: 0.5438
sub_27:Test (Best Model) - Loss: 1.1680 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 1.4950 - Accuracy: 0.3939 - F1: 0.3797
sub_27:Test (Best Model) - Loss: 1.4283 - Accuracy: 0.4242 - F1: 0.3660
sub_27:Test (Best Model) - Loss: 1.8443 - Accuracy: 0.5152 - F1: 0.5147
sub_27:Test (Best Model) - Loss: 2.0467 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 1.1813 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 1.6718 - Accuracy: 0.5000 - F1: 0.4667
sub_27:Test (Best Model) - Loss: 2.1342 - Accuracy: 0.5000 - F1: 0.4667
sub_27:Test (Best Model) - Loss: 1.6375 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.6562 - F1: 0.6267
sub_28:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7188 - F1: 0.7046
sub_28:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 2.7909 - Accuracy: 0.5000 - F1: 0.3816
sub_28:Test (Best Model) - Loss: 2.8736 - Accuracy: 0.4062 - F1: 0.3764
sub_28:Test (Best Model) - Loss: 5.0429 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 2.6749 - Accuracy: 0.4688 - F1: 0.4231
sub_28:Test (Best Model) - Loss: 3.3328 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 2.2584 - Accuracy: 0.5625 - F1: 0.4909
sub_28:Test (Best Model) - Loss: 7.4618 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 2.4535 - Accuracy: 0.3750 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 1.7075 - Accuracy: 0.3750 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 1.1751 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 1.0796 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 1.4145 - Accuracy: 0.4062 - F1: 0.4010
sub_29:Test (Best Model) - Loss: 1.7683 - Accuracy: 0.7188 - F1: 0.6632
sub_29:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.8301 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 1.6454 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 1.2257 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.1307 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2527 - Accuracy: 0.8750 - F1: 0.8745
sub_29:Test (Best Model) - Loss: 0.1636 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.0812 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.0759 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.4675 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2744 - Accuracy: 0.9394 - F1: 0.9380
sub_29:Test (Best Model) - Loss: 0.0777 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 0.0228 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.9091 - F1: 0.9077

=== Summary Results ===

acc: 64.47 ± 11.25
F1: 62.07 ± 11.72
acc-in: 73.28 ± 8.60
F1-in: 70.73 ± 9.47
