lr: 0.001
sub_1:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5625 - F1: 0.4167
sub_1:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.5152 - F1: 0.5111
sub_1:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5455 - F1: 0.4058
sub_1:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5152 - F1: 0.5038
sub_1:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.4545 - F1: 0.4540
sub_1:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.4545 - F1: 0.4107
sub_1:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4688 - F1: 0.4231
sub_1:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.6562 - F1: 0.6102
sub_1:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.6364 - F1: 0.5696
sub_2:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6250 - F1: 0.5000
sub_2:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6875 - F1: 0.6135
sub_2:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6562 - F1: 0.5594
sub_2:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.6250 - F1: 0.5362
sub_2:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6562 - F1: 0.5594
sub_2:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.6667 - F1: 0.5935
sub_2:Test (Best Model) - Loss: 0.6286 - Accuracy: 0.6970 - F1: 0.6591
sub_2:Test (Best Model) - Loss: 0.6091 - Accuracy: 0.6970 - F1: 0.6591
sub_2:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6364 - F1: 0.5696
sub_2:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.6667 - F1: 0.5935
sub_3:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5000 - F1: 0.3816
sub_3:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.5000 - F1: 0.3816
sub_3:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5000 - F1: 0.4459
sub_3:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.5758 - F1: 0.4225
sub_3:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5758 - F1: 0.4653
sub_3:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5455 - F1: 0.4762
sub_3:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5455 - F1: 0.5171
sub_3:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5152 - F1: 0.3400
sub_3:Test (Best Model) - Loss: 0.7206 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.5455 - F1: 0.5455
sub_3:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.5455 - F1: 0.4457
sub_3:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5152 - F1: 0.4545
sub_4:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5758 - F1: 0.5417
sub_4:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6364 - F1: 0.5696
sub_4:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6061 - F1: 0.5460
sub_4:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5758 - F1: 0.5227
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.4545 - F1: 0.4107
sub_4:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5455 - F1: 0.4058
sub_4:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.4545 - F1: 0.3543
sub_4:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.3636 - F1: 0.3419
sub_4:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5758 - F1: 0.5658
sub_4:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4848 - F1: 0.4328
sub_4:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5152 - F1: 0.4923
sub_4:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4848 - F1: 0.4527
sub_5:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5312 - F1: 0.3469
sub_5:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5000 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6562 - F1: 0.5594
sub_5:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.5976 - Accuracy: 0.6875 - F1: 0.6135
sub_5:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.5938 - F1: 0.4340
sub_5:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.5938 - F1: 0.4340
sub_5:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5000 - F1: 0.4921
sub_6:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.5000 - F1: 0.4818
sub_6:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5312 - F1: 0.4910
sub_6:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.6364 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.7576 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.6364 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5758 - F1: 0.4225
sub_6:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.6970 - F1: 0.6413
sub_6:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6364 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.6364 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5455 - F1: 0.4995
sub_7:Test (Best Model) - Loss: 0.7590 - Accuracy: 0.4688 - F1: 0.3976
sub_7:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.3438 - F1: 0.3379
sub_7:Test (Best Model) - Loss: 0.8386 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 0.7760 - Accuracy: 0.3750 - F1: 0.3074
sub_7:Test (Best Model) - Loss: 0.7878 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.5312 - F1: 0.3469
sub_7:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4688 - F1: 0.3637
sub_7:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5938 - F1: 0.4340
sub_7:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.6423 - Accuracy: 0.6875 - F1: 0.6135
sub_8:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7188 - F1: 0.7163
sub_8:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.5938 - F1: 0.5393
sub_8:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5625 - F1: 0.4167
sub_8:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.6250 - F1: 0.5636
sub_8:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.5938 - F1: 0.4340
sub_8:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.7996 - Accuracy: 0.3750 - F1: 0.3725
sub_9:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.7216 - Accuracy: 0.3750 - F1: 0.3725
sub_9:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.3750 - F1: 0.3725
sub_9:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4688 - F1: 0.4231
sub_9:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4375 - F1: 0.4286
sub_9:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.3438 - F1: 0.3431
sub_9:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.5938 - F1: 0.4340
sub_9:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.7126 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.2812 - F1: 0.2451
sub_10:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.6250 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.7409 - Accuracy: 0.3750 - F1: 0.3522
sub_10:Test (Best Model) - Loss: 0.7260 - Accuracy: 0.2500 - F1: 0.2381
sub_10:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.7642 - Accuracy: 0.4062 - F1: 0.2889
sub_10:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.5152 - F1: 0.4923
sub_10:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4848 - F1: 0.4063
sub_10:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.4242 - F1: 0.4242
sub_10:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.5152 - F1: 0.4261
sub_10:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5152 - F1: 0.4261
sub_11:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4848 - F1: 0.3718
sub_11:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.6970 - F1: 0.6827
sub_11:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5455 - F1: 0.4995
sub_11:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5152 - F1: 0.3889
sub_11:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.4545 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6061 - F1: 0.5196
sub_11:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6364 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5758 - F1: 0.4225
sub_11:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6061 - F1: 0.4850
sub_12:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.6875 - F1: 0.6135
sub_12:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.6250 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.6477 - Accuracy: 0.6875 - F1: 0.6537
sub_12:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.6250 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6667 - F1: 0.5935
sub_12:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5152 - F1: 0.4923
sub_12:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6667 - F1: 0.6330
sub_12:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.5758 - F1: 0.4225
sub_12:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.4062 - F1: 0.4057
sub_12:Test (Best Model) - Loss: 0.7466 - Accuracy: 0.3125 - F1: 0.3016
sub_12:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5938 - F1: 0.5836
sub_13:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.6250 - F1: 0.5000
sub_13:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.6250 - F1: 0.6000
sub_13:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.4182
sub_13:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5938 - F1: 0.4340
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.4242 - F1: 0.2979
sub_13:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.5938 - F1: 0.5836
sub_13:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6250 - F1: 0.5000
sub_13:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6250 - F1: 0.5844
sub_13:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.5000 - F1: 0.4182
sub_14:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5938 - F1: 0.4793
sub_14:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5938 - F1: 0.4793
sub_14:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5938 - F1: 0.4340
sub_14:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5938 - F1: 0.5135
sub_14:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5938 - F1: 0.5135
sub_14:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5938 - F1: 0.5135
sub_14:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.5000 - F1: 0.3333
sub_15:Test (Best Model) - Loss: 0.7586 - Accuracy: 0.4062 - F1: 0.3764
sub_15:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.3438 - F1: 0.3108
sub_15:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.4688 - F1: 0.3637
sub_15:Test (Best Model) - Loss: 0.7895 - Accuracy: 0.4375 - F1: 0.3455
sub_15:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.5312 - F1: 0.3469
sub_15:Test (Best Model) - Loss: 0.7567 - Accuracy: 0.4688 - F1: 0.4421
sub_15:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5000 - F1: 0.3333
sub_15:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5938 - F1: 0.4340
sub_15:Test (Best Model) - Loss: 0.6719 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5625 - F1: 0.5333
sub_15:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.6290 - Accuracy: 0.6250 - F1: 0.5636
sub_16:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5000 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.6562 - F1: 0.6476
sub_16:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.7188 - F1: 0.7117
sub_16:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.7812 - F1: 0.7810
sub_16:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 0.5379 - Accuracy: 0.8125 - F1: 0.8057
sub_16:Test (Best Model) - Loss: 0.7126 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5938 - F1: 0.5589
sub_16:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.7500 - F1: 0.7409
sub_16:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.5938 - F1: 0.5393
sub_16:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.6250 - F1: 0.5844
sub_17:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5758 - F1: 0.4225
sub_17:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.3529
sub_17:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5152 - F1: 0.3889
sub_17:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.5758 - F1: 0.4978
sub_17:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5758 - F1: 0.4653
sub_17:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.4062 - F1: 0.3552
sub_17:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.2188 - F1: 0.2180
sub_17:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.7577 - Accuracy: 0.3438 - F1: 0.2874
sub_17:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.3125 - F1: 0.3098
sub_18:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.5455 - F1: 0.4058
sub_18:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5152 - F1: 0.3889
sub_18:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5455 - F1: 0.3529
sub_18:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.5455 - F1: 0.4762
sub_18:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.6250 - F1: 0.5636
sub_18:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5312 - F1: 0.4910
sub_18:Test (Best Model) - Loss: 0.7262 - Accuracy: 0.5625 - F1: 0.5556
sub_18:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.4688 - F1: 0.4640
sub_18:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.5625 - F1: 0.4167
sub_18:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5938 - F1: 0.5836
sub_19:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5312 - F1: 0.4386
sub_19:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.5625 - F1: 0.5333
sub_19:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6875 - F1: 0.6667
sub_19:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6562 - F1: 0.5594
sub_19:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.3438 - F1: 0.3273
sub_19:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.7500 - F1: 0.7091
sub_19:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.5938 - F1: 0.4340
sub_19:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.6562 - F1: 0.5594
sub_20:Test (Best Model) - Loss: 0.7160 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5000 - F1: 0.4182
sub_20:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4375 - F1: 0.3766
sub_20:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4375 - F1: 0.3455
sub_20:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5152 - F1: 0.3889
sub_20:Test (Best Model) - Loss: 0.7169 - Accuracy: 0.5758 - F1: 0.4225
sub_20:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.4545 - F1: 0.4288
sub_20:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.6061 - F1: 0.4850
sub_20:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.6061 - F1: 0.4850
sub_21:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5312 - F1: 0.3992
sub_21:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5000 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.7210 - Accuracy: 0.5000 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.7560 - Accuracy: 0.4688 - F1: 0.4231
sub_21:Test (Best Model) - Loss: 0.7659 - Accuracy: 0.3750 - F1: 0.3522
sub_21:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.5625 - F1: 0.4167
sub_21:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.5000 - F1: 0.4459
sub_21:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5938 - F1: 0.4340
sub_21:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.5333
sub_21:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.7414 - Accuracy: 0.4688 - F1: 0.4555
sub_22:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5625 - F1: 0.5152
sub_22:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5000 - F1: 0.4818
sub_22:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5938 - F1: 0.5393
sub_22:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6562 - F1: 0.6102
sub_22:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.5455 - F1: 0.3529
sub_22:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.7576 - F1: 0.7462
sub_22:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 0.6029 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.8125 - F1: 0.8000
sub_22:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.5938 - F1: 0.5934
sub_22:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5312 - F1: 0.5271
sub_22:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.6562 - F1: 0.6476
sub_23:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.6970 - F1: 0.6898
sub_23:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5455 - F1: 0.4058
sub_23:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.6970 - F1: 0.6591
sub_23:Test (Best Model) - Loss: 0.5843 - Accuracy: 0.6970 - F1: 0.6413
sub_23:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.8182 - F1: 0.8167
sub_23:Test (Best Model) - Loss: 0.6246 - Accuracy: 0.6562 - F1: 0.5883
sub_23:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5938 - F1: 0.5135
sub_23:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.5938 - F1: 0.4340
sub_23:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.6562 - F1: 0.5883
sub_23:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.7838 - Accuracy: 0.4242 - F1: 0.2979
sub_23:Test (Best Model) - Loss: 0.8493 - Accuracy: 0.4242 - F1: 0.3365
sub_23:Test (Best Model) - Loss: 0.8271 - Accuracy: 0.4545 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.5152 - F1: 0.3889
sub_23:Test (Best Model) - Loss: 0.7697 - Accuracy: 0.5455 - F1: 0.4058
sub_24:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.4062 - F1: 0.3914
sub_24:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3816
sub_24:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4062 - F1: 0.3914
sub_24:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5938 - F1: 0.4340
sub_24:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5938 - F1: 0.5135
sub_24:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5000 - F1: 0.3333
sub_24:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4375 - F1: 0.4000
sub_24:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5000 - F1: 0.3816
sub_24:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5938 - F1: 0.4340
sub_24:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.5938 - F1: 0.5135
sub_25:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.5455 - F1: 0.3529
sub_25:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6061 - F1: 0.4850
sub_25:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.6364 - F1: 0.5417
sub_25:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6061 - F1: 0.4850
sub_25:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.6364 - F1: 0.5417
sub_25:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5938 - F1: 0.4340
sub_25:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6562 - F1: 0.5883
sub_25:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.6562 - F1: 0.5594
sub_25:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.6562 - F1: 0.5594
sub_25:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4375 - F1: 0.3455
sub_25:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.5312 - F1: 0.4910
sub_25:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5938 - F1: 0.4340
sub_26:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.7172 - Accuracy: 0.4545 - F1: 0.3125
sub_26:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.4545 - F1: 0.3864
sub_26:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.5152 - F1: 0.3400
sub_26:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.5455 - F1: 0.3529
sub_26:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5938 - F1: 0.4340
sub_26:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.4062 - F1: 0.4010
sub_26:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6562 - F1: 0.6102
sub_26:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5000 - F1: 0.3333
sub_26:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5758 - F1: 0.4225
sub_27:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.6061 - F1: 0.5926
sub_27:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.3529
sub_27:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5152 - F1: 0.3889
sub_27:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.5758 - F1: 0.4978
sub_27:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.5758 - F1: 0.4653
sub_27:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.4062 - F1: 0.3552
sub_27:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.2188 - F1: 0.2180
sub_27:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.7577 - Accuracy: 0.3438 - F1: 0.2874
sub_27:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.3125 - F1: 0.3098
sub_28:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5312 - F1: 0.3469
sub_28:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5312 - F1: 0.3469
sub_28:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.4182
sub_29:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6250 - F1: 0.5636
sub_29:Test (Best Model) - Loss: 0.7448 - Accuracy: 0.5000 - F1: 0.4459
sub_29:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.7351 - Accuracy: 0.3438 - F1: 0.2874
sub_29:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.4545 - F1: 0.4417
sub_29:Test (Best Model) - Loss: 0.7408 - Accuracy: 0.3939 - F1: 0.3654
sub_29:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.5455 - F1: 0.4457
sub_29:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.5152 - F1: 0.3400
sub_29:Test (Best Model) - Loss: 0.7742 - Accuracy: 0.2727 - F1: 0.2667

=== Summary Results ===

acc: 55.22 ± 4.39
F1: 44.56 ± 6.14
acc-in: 62.66 ± 4.08
F1-in: 48.94 ± 7.67
