lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.5176 - Accuracy: 0.7500 - F1: 0.7490
sub_1:Test (Best Model) - Loss: 0.4052 - Accuracy: 0.7812 - F1: 0.7703
sub_1:Test (Best Model) - Loss: 0.5811 - Accuracy: 0.7812 - F1: 0.7625
sub_1:Test (Best Model) - Loss: 0.1292 - Accuracy: 0.9688 - F1: 0.9680
sub_1:Test (Best Model) - Loss: 0.4921 - Accuracy: 0.7812 - F1: 0.7703
sub_1:Test (Best Model) - Loss: 0.7943 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.3120 - Accuracy: 0.9394 - F1: 0.9380
sub_1:Test (Best Model) - Loss: 0.7465 - Accuracy: 0.8182 - F1: 0.8096
sub_1:Test (Best Model) - Loss: 0.9312 - Accuracy: 0.8485 - F1: 0.8390
sub_1:Test (Best Model) - Loss: 0.3153 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.4449 - Accuracy: 0.8750 - F1: 0.8730
sub_1:Test (Best Model) - Loss: 0.9493 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.2222 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.3917 - Accuracy: 0.8438 - F1: 0.8359
sub_2:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.6667 - F1: 0.6654
sub_2:Test (Best Model) - Loss: 1.8396 - Accuracy: 0.7879 - F1: 0.7806
sub_2:Test (Best Model) - Loss: 2.1018 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.6348 - Accuracy: 0.7273 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 1.5931 - Accuracy: 0.7879 - F1: 0.7806
sub_2:Test (Best Model) - Loss: 1.0376 - Accuracy: 0.6250 - F1: 0.6000
sub_2:Test (Best Model) - Loss: 1.5623 - Accuracy: 0.5000 - F1: 0.4182
sub_2:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.8125 - F1: 0.8095
sub_2:Test (Best Model) - Loss: 0.9653 - Accuracy: 0.7500 - F1: 0.7409
sub_2:Test (Best Model) - Loss: 1.0270 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 1.5203 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 1.7429 - Accuracy: 0.6364 - F1: 0.6278
sub_2:Test (Best Model) - Loss: 0.9104 - Accuracy: 0.6364 - F1: 0.6360
sub_2:Test (Best Model) - Loss: 1.0024 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 1.1809 - Accuracy: 0.6364 - F1: 0.6360
sub_3:Test (Best Model) - Loss: 1.9597 - Accuracy: 0.5312 - F1: 0.4684
sub_3:Test (Best Model) - Loss: 1.5215 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 1.5893 - Accuracy: 0.5625 - F1: 0.5333
sub_3:Test (Best Model) - Loss: 1.6307 - Accuracy: 0.5938 - F1: 0.5836
sub_3:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.5938 - F1: 0.5733
sub_3:Test (Best Model) - Loss: 1.1671 - Accuracy: 0.6364 - F1: 0.6360
sub_3:Test (Best Model) - Loss: 1.8379 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.4848 - F1: 0.4772
sub_3:Test (Best Model) - Loss: 1.8243 - Accuracy: 0.5152 - F1: 0.4545
sub_3:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.5152 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 2.9343 - Accuracy: 0.4545 - F1: 0.4107
sub_3:Test (Best Model) - Loss: 2.4756 - Accuracy: 0.3636 - F1: 0.2667
sub_3:Test (Best Model) - Loss: 2.0673 - Accuracy: 0.4848 - F1: 0.4063
sub_3:Test (Best Model) - Loss: 2.5302 - Accuracy: 0.5455 - F1: 0.4058
sub_3:Test (Best Model) - Loss: 2.5585 - Accuracy: 0.3939 - F1: 0.3182
sub_4:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.6970 - F1: 0.6827
sub_4:Test (Best Model) - Loss: 0.5812 - Accuracy: 0.8485 - F1: 0.8433
sub_4:Test (Best Model) - Loss: 0.9893 - Accuracy: 0.7273 - F1: 0.7179
sub_4:Test (Best Model) - Loss: 0.4574 - Accuracy: 0.8788 - F1: 0.8731
sub_4:Test (Best Model) - Loss: 0.7562 - Accuracy: 0.8485 - F1: 0.8433
sub_4:Test (Best Model) - Loss: 1.2054 - Accuracy: 0.6364 - F1: 0.5696
sub_4:Test (Best Model) - Loss: 1.9141 - Accuracy: 0.5758 - F1: 0.4978
sub_4:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.6667 - F1: 0.6553
sub_4:Test (Best Model) - Loss: 2.2792 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 2.7651 - Accuracy: 0.6364 - F1: 0.6071
sub_4:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 0.9874 - Accuracy: 0.7576 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.4893 - Accuracy: 0.8788 - F1: 0.8759
sub_4:Test (Best Model) - Loss: 0.8421 - Accuracy: 0.6970 - F1: 0.6967
sub_4:Test (Best Model) - Loss: 0.4950 - Accuracy: 0.8182 - F1: 0.8036
sub_5:Test (Best Model) - Loss: 2.4996 - Accuracy: 0.4688 - F1: 0.4555
sub_5:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 3.1173 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 1.9516 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 2.1933 - Accuracy: 0.5000 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 1.1345 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 1.2326 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 1.1088 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 1.5183 - Accuracy: 0.7812 - F1: 0.7625
sub_5:Test (Best Model) - Loss: 1.1444 - Accuracy: 0.7812 - F1: 0.7625
sub_5:Test (Best Model) - Loss: 1.7807 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 1.4214 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 2.0780 - Accuracy: 0.4688 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 2.0420 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 2.1235 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 1.5700 - Accuracy: 0.6875 - F1: 0.6537
sub_6:Test (Best Model) - Loss: 1.4341 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.1325 - Accuracy: 0.6562 - F1: 0.6476
sub_6:Test (Best Model) - Loss: 0.7896 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 2.3456 - Accuracy: 0.4848 - F1: 0.4848
sub_6:Test (Best Model) - Loss: 2.7780 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 1.9660 - Accuracy: 0.5455 - F1: 0.4995
sub_6:Test (Best Model) - Loss: 2.3352 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 3.3504 - Accuracy: 0.5455 - F1: 0.3529
sub_6:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.6970 - F1: 0.6726
sub_6:Test (Best Model) - Loss: 0.7649 - Accuracy: 0.6364 - F1: 0.6192
sub_6:Test (Best Model) - Loss: 1.2677 - Accuracy: 0.6061 - F1: 0.5662
sub_6:Test (Best Model) - Loss: 1.3009 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.6667 - F1: 0.6159
sub_7:Test (Best Model) - Loss: 1.0885 - Accuracy: 0.6875 - F1: 0.6364
sub_7:Test (Best Model) - Loss: 1.7164 - Accuracy: 0.5312 - F1: 0.4684
sub_7:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 1.0084 - Accuracy: 0.6875 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 2.4298 - Accuracy: 0.4375 - F1: 0.4286
sub_7:Test (Best Model) - Loss: 1.6323 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 1.8182 - Accuracy: 0.4062 - F1: 0.3552
sub_7:Test (Best Model) - Loss: 1.8388 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 1.4840 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 1.6481 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 2.3187 - Accuracy: 0.5312 - F1: 0.5271
sub_7:Test (Best Model) - Loss: 1.1872 - Accuracy: 0.6250 - F1: 0.6235
sub_7:Test (Best Model) - Loss: 0.8172 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 1.7754 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 2.1540 - Accuracy: 0.6250 - F1: 0.5844
sub_8:Test (Best Model) - Loss: 1.4608 - Accuracy: 0.5938 - F1: 0.5836
sub_8:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.8467 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 1.1855 - Accuracy: 0.7188 - F1: 0.6946
sub_8:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 1.1976 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 2.0132 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.9534 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 1.0863 - Accuracy: 0.5938 - F1: 0.5901
sub_8:Test (Best Model) - Loss: 1.0925 - Accuracy: 0.7500 - F1: 0.7490
sub_8:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.6875 - F1: 0.6825
sub_8:Test (Best Model) - Loss: 0.7846 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 0.9642 - Accuracy: 0.6562 - F1: 0.6267
sub_9:Test (Best Model) - Loss: 0.2990 - Accuracy: 0.9375 - F1: 0.9365
sub_9:Test (Best Model) - Loss: 1.0511 - Accuracy: 0.8438 - F1: 0.8359
sub_9:Test (Best Model) - Loss: 0.0907 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.2342 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.8278 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.8445 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 1.5269 - Accuracy: 0.8125 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 1.2884 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 1.1366 - Accuracy: 0.5312 - F1: 0.5077
sub_9:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.8125 - F1: 0.8000
sub_9:Test (Best Model) - Loss: 1.4986 - Accuracy: 0.7812 - F1: 0.7810
sub_9:Test (Best Model) - Loss: 2.4353 - Accuracy: 0.8125 - F1: 0.8095
sub_9:Test (Best Model) - Loss: 2.3791 - Accuracy: 0.6875 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 1.8228 - Accuracy: 0.8438 - F1: 0.8424
sub_9:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.7812 - F1: 0.7625
sub_10:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.5312 - F1: 0.4386
sub_10:Test (Best Model) - Loss: 1.6598 - Accuracy: 0.4375 - F1: 0.3455
sub_10:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.6875 - F1: 0.6875
sub_10:Test (Best Model) - Loss: 1.0944 - Accuracy: 0.6250 - F1: 0.6000
sub_10:Test (Best Model) - Loss: 1.5513 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 1.8808 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 1.2889 - Accuracy: 0.6250 - F1: 0.6113
sub_10:Test (Best Model) - Loss: 1.6835 - Accuracy: 0.5000 - F1: 0.4818
sub_10:Test (Best Model) - Loss: 1.9974 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 1.7106 - Accuracy: 0.4375 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 2.1863 - Accuracy: 0.5152 - F1: 0.5111
sub_10:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.5455 - F1: 0.5387
sub_10:Test (Best Model) - Loss: 1.4526 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 1.8002 - Accuracy: 0.5758 - F1: 0.5417
sub_10:Test (Best Model) - Loss: 1.7714 - Accuracy: 0.5758 - F1: 0.5658
sub_11:Test (Best Model) - Loss: 3.2563 - Accuracy: 0.4545 - F1: 0.4107
sub_11:Test (Best Model) - Loss: 2.2547 - Accuracy: 0.4242 - F1: 0.4046
sub_11:Test (Best Model) - Loss: 2.1845 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 1.9587 - Accuracy: 0.4848 - F1: 0.4829
sub_11:Test (Best Model) - Loss: 2.0855 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 1.5180 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.9424 - Accuracy: 0.5455 - F1: 0.5171
sub_11:Test (Best Model) - Loss: 1.8790 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 3.0751 - Accuracy: 0.4545 - F1: 0.3864
sub_11:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.6667 - F1: 0.6159
sub_11:Test (Best Model) - Loss: 1.6606 - Accuracy: 0.4545 - F1: 0.4288
sub_11:Test (Best Model) - Loss: 0.9941 - Accuracy: 0.6970 - F1: 0.6827
sub_11:Test (Best Model) - Loss: 1.6494 - Accuracy: 0.5455 - F1: 0.4762
sub_11:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 1.9038 - Accuracy: 0.6364 - F1: 0.5909
sub_12:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.8438 - F1: 0.8398
sub_12:Test (Best Model) - Loss: 1.0549 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 1.2030 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 1.5770 - Accuracy: 0.7188 - F1: 0.7046
sub_12:Test (Best Model) - Loss: 0.7496 - Accuracy: 0.7879 - F1: 0.7746
sub_12:Test (Best Model) - Loss: 1.1594 - Accuracy: 0.6364 - F1: 0.5909
sub_12:Test (Best Model) - Loss: 1.0253 - Accuracy: 0.6970 - F1: 0.6413
sub_12:Test (Best Model) - Loss: 0.7966 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.8469 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 1.2041 - Accuracy: 0.6250 - F1: 0.6000
sub_12:Test (Best Model) - Loss: 1.5004 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.9679 - Accuracy: 0.8125 - F1: 0.8095
sub_12:Test (Best Model) - Loss: 2.6717 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 1.4050 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.4772 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.3157 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.2284 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.4073 - Accuracy: 0.8438 - F1: 0.8359
sub_13:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.7879 - F1: 0.7664
sub_13:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.8485 - F1: 0.8462
sub_13:Test (Best Model) - Loss: 0.3242 - Accuracy: 0.8485 - F1: 0.8485
sub_13:Test (Best Model) - Loss: 1.1963 - Accuracy: 0.7879 - F1: 0.7871
sub_13:Test (Best Model) - Loss: 0.7657 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.8773 - Accuracy: 0.8125 - F1: 0.8125
sub_13:Test (Best Model) - Loss: 0.8161 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.5466 - Accuracy: 0.8125 - F1: 0.8118
sub_13:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.7812 - F1: 0.7793
sub_13:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.7643 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.8642 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 0.4411 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 0.4189 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 1.1953 - Accuracy: 0.6250 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 0.6055 - Accuracy: 0.7188 - F1: 0.7185
sub_14:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.6250 - F1: 0.5362
sub_14:Test (Best Model) - Loss: 0.8174 - Accuracy: 0.7188 - F1: 0.6946
sub_14:Test (Best Model) - Loss: 1.0953 - Accuracy: 0.7188 - F1: 0.6632
sub_14:Test (Best Model) - Loss: 1.0980 - Accuracy: 0.6875 - F1: 0.6364
sub_14:Test (Best Model) - Loss: 1.9284 - Accuracy: 0.6562 - F1: 0.5883
sub_14:Test (Best Model) - Loss: 1.4585 - Accuracy: 0.6562 - F1: 0.5594
sub_14:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.7188 - F1: 0.6632
sub_15:Test (Best Model) - Loss: 2.3637 - Accuracy: 0.8125 - F1: 0.8000
sub_15:Test (Best Model) - Loss: 1.5427 - Accuracy: 0.6875 - F1: 0.6863
sub_15:Test (Best Model) - Loss: 1.5032 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 0.9484 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 2.0478 - Accuracy: 0.6250 - F1: 0.6250
sub_15:Test (Best Model) - Loss: 3.8249 - Accuracy: 0.5000 - F1: 0.4980
sub_15:Test (Best Model) - Loss: 1.4720 - Accuracy: 0.6562 - F1: 0.6532
sub_15:Test (Best Model) - Loss: 2.7647 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 1.9247 - Accuracy: 0.6562 - F1: 0.6390
sub_15:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.7500 - F1: 0.7229
sub_15:Test (Best Model) - Loss: 1.5793 - Accuracy: 0.6250 - F1: 0.6000
sub_15:Test (Best Model) - Loss: 1.6735 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 1.7995 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.5312 - F1: 0.5271
sub_16:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 1.4508 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.5938 - F1: 0.5901
sub_16:Test (Best Model) - Loss: 1.6349 - Accuracy: 0.7188 - F1: 0.7185
sub_16:Test (Best Model) - Loss: 1.0500 - Accuracy: 0.7812 - F1: 0.7793
sub_16:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 1.7228 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 1.9915 - Accuracy: 0.7500 - F1: 0.7333
sub_16:Test (Best Model) - Loss: 1.5345 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 2.4567 - Accuracy: 0.5625 - F1: 0.4909
sub_16:Test (Best Model) - Loss: 1.7928 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 2.2102 - Accuracy: 0.5000 - F1: 0.3816
sub_17:Test (Best Model) - Loss: 1.4868 - Accuracy: 0.6364 - F1: 0.6192
sub_17:Test (Best Model) - Loss: 1.0171 - Accuracy: 0.6061 - F1: 0.5815
sub_17:Test (Best Model) - Loss: 1.0108 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 1.4309 - Accuracy: 0.6667 - F1: 0.5935
sub_17:Test (Best Model) - Loss: 0.8146 - Accuracy: 0.6667 - F1: 0.6667
sub_17:Test (Best Model) - Loss: 1.9073 - Accuracy: 0.3636 - F1: 0.3636
sub_17:Test (Best Model) - Loss: 1.8466 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 2.4731 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 1.1883 - Accuracy: 0.5758 - F1: 0.5558
sub_17:Test (Best Model) - Loss: 1.0364 - Accuracy: 0.5758 - F1: 0.5227
sub_17:Test (Best Model) - Loss: 1.0208 - Accuracy: 0.5938 - F1: 0.5836
sub_17:Test (Best Model) - Loss: 1.2492 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 1.9989 - Accuracy: 0.5312 - F1: 0.4684
sub_17:Test (Best Model) - Loss: 1.8939 - Accuracy: 0.5312 - F1: 0.5271
sub_17:Test (Best Model) - Loss: 1.7258 - Accuracy: 0.5625 - F1: 0.5333
sub_18:Test (Best Model) - Loss: 0.5397 - Accuracy: 0.6970 - F1: 0.6967
sub_18:Test (Best Model) - Loss: 0.4894 - Accuracy: 0.7879 - F1: 0.7746
sub_18:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.7576 - F1: 0.7574
sub_18:Test (Best Model) - Loss: 0.5780 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.3768 - Accuracy: 0.8182 - F1: 0.8096
sub_18:Test (Best Model) - Loss: 0.7764 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.8438 - F1: 0.8359
sub_18:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.7812 - F1: 0.7810
sub_18:Test (Best Model) - Loss: 1.2536 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.4778 - Accuracy: 0.8438 - F1: 0.8398
sub_18:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.6066 - Accuracy: 0.8438 - F1: 0.8359
sub_19:Test (Best Model) - Loss: 2.9782 - Accuracy: 0.5312 - F1: 0.3992
sub_19:Test (Best Model) - Loss: 1.8144 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 1.2300 - Accuracy: 0.6250 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 3.4166 - Accuracy: 0.5312 - F1: 0.3992
sub_19:Test (Best Model) - Loss: 1.5160 - Accuracy: 0.6250 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 2.8768 - Accuracy: 0.5000 - F1: 0.3816
sub_19:Test (Best Model) - Loss: 1.9520 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 0.8554 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 1.8031 - Accuracy: 0.5000 - F1: 0.4459
sub_19:Test (Best Model) - Loss: 1.9311 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 3.3683 - Accuracy: 0.4062 - F1: 0.3267
sub_19:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.4688 - F1: 0.4555
sub_19:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.5938 - F1: 0.5901
sub_19:Test (Best Model) - Loss: 0.9241 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 0.9174 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 1.5138 - Accuracy: 0.6875 - F1: 0.6863
sub_20:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.7500 - F1: 0.7229
sub_20:Test (Best Model) - Loss: 1.5782 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 2.8120 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 1.7234 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 2.0627 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 1.5696 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 2.0898 - Accuracy: 0.6250 - F1: 0.6000
sub_20:Test (Best Model) - Loss: 1.0751 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 2.8036 - Accuracy: 0.5758 - F1: 0.5417
sub_20:Test (Best Model) - Loss: 3.1481 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 2.2060 - Accuracy: 0.5758 - F1: 0.5658
sub_20:Test (Best Model) - Loss: 3.8480 - Accuracy: 0.6061 - F1: 0.5815
sub_20:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.6970 - F1: 0.6827
sub_21:Test (Best Model) - Loss: 2.9604 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 2.4202 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 2.2313 - Accuracy: 0.3125 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 2.4361 - Accuracy: 0.4375 - F1: 0.3766
sub_21:Test (Best Model) - Loss: 2.6257 - Accuracy: 0.3438 - F1: 0.3431
sub_21:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 1.6598 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 2.2858 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 2.2267 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 1.6797 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 1.6649 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 2.2120 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 2.4198 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 3.0320 - Accuracy: 0.2812 - F1: 0.2749
sub_21:Test (Best Model) - Loss: 1.9548 - Accuracy: 0.5625 - F1: 0.5152
sub_22:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.5938 - F1: 0.5901
sub_22:Test (Best Model) - Loss: 1.5540 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 1.1644 - Accuracy: 0.6562 - F1: 0.6102
sub_22:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.7500 - F1: 0.7229
sub_22:Test (Best Model) - Loss: 1.7583 - Accuracy: 0.5758 - F1: 0.4653
sub_22:Test (Best Model) - Loss: 1.8096 - Accuracy: 0.6667 - F1: 0.5935
sub_22:Test (Best Model) - Loss: 1.0028 - Accuracy: 0.7879 - F1: 0.7664
sub_22:Test (Best Model) - Loss: 1.9571 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 1.2367 - Accuracy: 0.6667 - F1: 0.6330
sub_22:Test (Best Model) - Loss: 1.0133 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.7188 - F1: 0.7163
sub_22:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.9265 - Accuracy: 0.7188 - F1: 0.6632
sub_22:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.7812 - F1: 0.7703
sub_23:Test (Best Model) - Loss: 0.8497 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.9549 - Accuracy: 0.7576 - F1: 0.7381
sub_23:Test (Best Model) - Loss: 0.4221 - Accuracy: 0.8788 - F1: 0.8759
sub_23:Test (Best Model) - Loss: 0.9058 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.8788 - F1: 0.8759
sub_23:Test (Best Model) - Loss: 0.8297 - Accuracy: 0.7188 - F1: 0.7046
sub_23:Test (Best Model) - Loss: 0.9467 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.3419 - Accuracy: 0.8750 - F1: 0.8730
sub_23:Test (Best Model) - Loss: 0.9386 - Accuracy: 0.7188 - F1: 0.7185
sub_23:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.8125 - F1: 0.8125
sub_23:Test (Best Model) - Loss: 1.1344 - Accuracy: 0.7576 - F1: 0.7273
sub_23:Test (Best Model) - Loss: 0.8125 - Accuracy: 0.7273 - F1: 0.6997
sub_23:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 1.1572 - Accuracy: 0.8182 - F1: 0.8036
sub_23:Test (Best Model) - Loss: 1.1397 - Accuracy: 0.6970 - F1: 0.6591
sub_24:Test (Best Model) - Loss: 1.2003 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 1.9372 - Accuracy: 0.3750 - F1: 0.3522
sub_24:Test (Best Model) - Loss: 1.8441 - Accuracy: 0.4375 - F1: 0.4353
sub_24:Test (Best Model) - Loss: 1.5590 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 1.9504 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.5312 - F1: 0.5077
sub_24:Test (Best Model) - Loss: 1.5324 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 1.4044 - Accuracy: 0.6250 - F1: 0.5844
sub_24:Test (Best Model) - Loss: 0.8936 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.8710 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 2.1655 - Accuracy: 0.5625 - F1: 0.5333
sub_24:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 1.6415 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 2.4885 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 1.8298 - Accuracy: 0.5312 - F1: 0.5077
sub_25:Test (Best Model) - Loss: 1.9425 - Accuracy: 0.3636 - F1: 0.2993
sub_25:Test (Best Model) - Loss: 1.6561 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 2.3883 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 1.9687 - Accuracy: 0.4242 - F1: 0.2979
sub_25:Test (Best Model) - Loss: 2.1823 - Accuracy: 0.5152 - F1: 0.4762
sub_25:Test (Best Model) - Loss: 1.7012 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.9501 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 1.4844 - Accuracy: 0.5000 - F1: 0.4667
sub_25:Test (Best Model) - Loss: 1.5318 - Accuracy: 0.6250 - F1: 0.5362
sub_25:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.5938 - F1: 0.4793
sub_25:Test (Best Model) - Loss: 1.0631 - Accuracy: 0.6562 - F1: 0.6476
sub_25:Test (Best Model) - Loss: 1.1845 - Accuracy: 0.7500 - F1: 0.7229
sub_25:Test (Best Model) - Loss: 1.4656 - Accuracy: 0.6562 - F1: 0.6390
sub_25:Test (Best Model) - Loss: 1.3208 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 1.7237 - Accuracy: 0.5938 - F1: 0.5589
sub_26:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.5758 - F1: 0.5658
sub_26:Test (Best Model) - Loss: 2.2226 - Accuracy: 0.6667 - F1: 0.6459
sub_26:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.8182 - F1: 0.8096
sub_26:Test (Best Model) - Loss: 0.5220 - Accuracy: 0.8485 - F1: 0.8390
sub_26:Test (Best Model) - Loss: 0.8906 - Accuracy: 0.7879 - F1: 0.7847
sub_26:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.9301 - Accuracy: 0.7812 - F1: 0.7758
sub_26:Test (Best Model) - Loss: 1.0495 - Accuracy: 0.7500 - F1: 0.7229
sub_26:Test (Best Model) - Loss: 0.7801 - Accuracy: 0.8125 - F1: 0.8057
sub_26:Test (Best Model) - Loss: 1.0259 - Accuracy: 0.7812 - F1: 0.7625
sub_26:Test (Best Model) - Loss: 0.1245 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 1.3369 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.2581 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 1.4868 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 1.0171 - Accuracy: 0.6061 - F1: 0.5815
sub_27:Test (Best Model) - Loss: 1.0108 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 1.4309 - Accuracy: 0.6667 - F1: 0.5935
sub_27:Test (Best Model) - Loss: 0.8146 - Accuracy: 0.6667 - F1: 0.6667
sub_27:Test (Best Model) - Loss: 1.9073 - Accuracy: 0.3636 - F1: 0.3636
sub_27:Test (Best Model) - Loss: 1.8466 - Accuracy: 0.5758 - F1: 0.5417
sub_27:Test (Best Model) - Loss: 2.4731 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 1.1883 - Accuracy: 0.5758 - F1: 0.5558
sub_27:Test (Best Model) - Loss: 1.0364 - Accuracy: 0.5758 - F1: 0.5227
sub_27:Test (Best Model) - Loss: 1.0208 - Accuracy: 0.5938 - F1: 0.5836
sub_27:Test (Best Model) - Loss: 1.2492 - Accuracy: 0.5625 - F1: 0.5556
sub_27:Test (Best Model) - Loss: 1.9989 - Accuracy: 0.5312 - F1: 0.4684
sub_27:Test (Best Model) - Loss: 1.8939 - Accuracy: 0.5312 - F1: 0.5271
sub_27:Test (Best Model) - Loss: 1.7258 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 1.2669 - Accuracy: 0.5938 - F1: 0.5393
sub_28:Test (Best Model) - Loss: 1.8517 - Accuracy: 0.5938 - F1: 0.5836
sub_28:Test (Best Model) - Loss: 2.4967 - Accuracy: 0.5312 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 2.7960 - Accuracy: 0.5312 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 3.0442 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 3.3822 - Accuracy: 0.4688 - F1: 0.4555
sub_28:Test (Best Model) - Loss: 5.1469 - Accuracy: 0.3438 - F1: 0.3379
sub_28:Test (Best Model) - Loss: 3.3275 - Accuracy: 0.5938 - F1: 0.5393
sub_28:Test (Best Model) - Loss: 8.6597 - Accuracy: 0.5625 - F1: 0.5333
sub_28:Test (Best Model) - Loss: 1.5683 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 1.9778 - Accuracy: 0.3750 - F1: 0.3725
sub_28:Test (Best Model) - Loss: 3.0166 - Accuracy: 0.4688 - F1: 0.3976
sub_28:Test (Best Model) - Loss: 1.8215 - Accuracy: 0.6875 - F1: 0.6825
sub_28:Test (Best Model) - Loss: 1.5561 - Accuracy: 0.5000 - F1: 0.5000
sub_29:Test (Best Model) - Loss: 1.8087 - Accuracy: 0.7188 - F1: 0.6632
sub_29:Test (Best Model) - Loss: 0.8967 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 1.8484 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 1.7333 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.8438 - F1: 0.8303
sub_29:Test (Best Model) - Loss: 0.2951 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.2262 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.1896 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.0160 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2630 - Accuracy: 0.8438 - F1: 0.8424
sub_29:Test (Best Model) - Loss: 0.2816 - Accuracy: 0.9394 - F1: 0.9389
sub_29:Test (Best Model) - Loss: 1.0348 - Accuracy: 0.8182 - F1: 0.8167
sub_29:Test (Best Model) - Loss: 0.1987 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.3075 - Accuracy: 0.9394 - F1: 0.9380

=== Summary Results ===

acc: 65.16 ± 11.46
F1: 62.75 ± 12.27
acc-in: 73.62 ± 8.84
F1-in: 71.02 ± 9.78
