lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4688 - F1: 0.4421
sub_1:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5000 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.3750 - F1: 0.3725
sub_1:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6562 - F1: 0.5883
sub_1:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5000 - F1: 0.4818
sub_1:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5758 - F1: 0.5558
sub_1:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.6061 - F1: 0.5926
sub_1:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.4848 - F1: 0.4672
sub_1:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6970 - F1: 0.6898
sub_1:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.7273 - F1: 0.7232
sub_1:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5938 - F1: 0.5934
sub_1:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.6562 - F1: 0.6390
sub_1:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.6250 - F1: 0.6235
sub_1:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.4375 - F1: 0.4353
sub_1:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.6667 - F1: 0.6553
sub_2:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5455 - F1: 0.5438
sub_2:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5758 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5312 - F1: 0.4386
sub_2:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.5312 - F1: 0.5308
sub_2:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5312 - F1: 0.5195
sub_2:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4375 - F1: 0.4286
sub_2:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.4818
sub_2:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5152 - F1: 0.5038
sub_2:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5455 - F1: 0.5299
sub_2:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4848 - F1: 0.4848
sub_2:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4848 - F1: 0.4829
sub_3:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.7188 - F1: 0.7185
sub_3:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.4682
sub_3:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4062 - F1: 0.3914
sub_3:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4688 - F1: 0.4421
sub_3:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5758 - F1: 0.5558
sub_3:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5455 - F1: 0.5455
sub_3:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.6667 - F1: 0.6553
sub_3:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6061 - F1: 0.5662
sub_3:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.3939 - F1: 0.3797
sub_3:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.3939 - F1: 0.3934
sub_3:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4545 - F1: 0.4540
sub_3:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4545 - F1: 0.4417
sub_4:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.6061 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.4848 - F1: 0.4672
sub_4:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5455 - F1: 0.4995
sub_4:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6364 - F1: 0.5909
sub_4:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5758 - F1: 0.5722
sub_4:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.6061 - F1: 0.6046
sub_4:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5758 - F1: 0.5417
sub_4:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5758 - F1: 0.5754
sub_4:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.3939 - F1: 0.3654
sub_4:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4848 - F1: 0.4527
sub_4:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6061 - F1: 0.5662
sub_4:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4848 - F1: 0.4829
sub_4:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.4545 - F1: 0.4288
sub_5:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5312 - F1: 0.5195
sub_5:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5938 - F1: 0.5733
sub_5:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6875 - F1: 0.6863
sub_5:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5000 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.4688 - F1: 0.4231
sub_5:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.5000 - F1: 0.4667
sub_6:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.4353
sub_6:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.6562 - F1: 0.6532
sub_6:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5625 - F1: 0.5333
sub_6:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4375 - F1: 0.4170
sub_6:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4545 - F1: 0.4417
sub_6:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5152 - F1: 0.4545
sub_6:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.5455 - F1: 0.4762
sub_6:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.3939 - F1: 0.2826
sub_6:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5455 - F1: 0.5299
sub_6:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6364 - F1: 0.6360
sub_6:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5758 - F1: 0.5558
sub_6:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5758 - F1: 0.5722
sub_6:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5455 - F1: 0.5455
sub_6:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.3333 - F1: 0.3278
sub_7:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4062 - F1: 0.3914
sub_7:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5312 - F1: 0.5195
sub_7:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.3438 - F1: 0.3431
sub_7:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.5000 - F1: 0.4459
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6875 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.2500 - F1: 0.2381
sub_7:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.5466
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.6250 - F1: 0.5844
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5312 - F1: 0.5308
sub_7:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5000 - F1: 0.4980
sub_8:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4688 - F1: 0.4640
sub_8:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4062 - F1: 0.4057
sub_8:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5312 - F1: 0.5308
sub_8:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5625 - F1: 0.5333
sub_8:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4688 - F1: 0.4555
sub_8:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4688 - F1: 0.4231
sub_8:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.4921
sub_8:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.4667
sub_8:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.6250 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.4353
sub_8:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5625 - F1: 0.5608
sub_8:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.3125 - F1: 0.2874
sub_8:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4688 - F1: 0.4682
sub_8:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6562 - F1: 0.6390
sub_9:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6562 - F1: 0.6102
sub_9:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5938 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.6875 - F1: 0.6761
sub_9:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6562 - F1: 0.5883
sub_9:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5625 - F1: 0.5556
sub_9:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.4688 - F1: 0.4555
sub_9:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6250 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.4062 - F1: 0.3764
sub_9:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5938 - F1: 0.5836
sub_10:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.7188 - F1: 0.7117
sub_10:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4375 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.3750 - F1: 0.3522
sub_10:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.6562 - F1: 0.6532
sub_10:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.4688 - F1: 0.4231
sub_10:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4242 - F1: 0.4046
sub_10:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5152 - F1: 0.5147
sub_10:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.4545 - F1: 0.4540
sub_11:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5455 - F1: 0.5438
sub_11:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6364 - F1: 0.6333
sub_11:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4242 - F1: 0.4157
sub_11:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5455 - F1: 0.5299
sub_11:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.4242 - F1: 0.4221
sub_11:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4848 - F1: 0.4772
sub_11:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.2727 - F1: 0.2721
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5455 - F1: 0.5387
sub_11:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.3636 - F1: 0.3541
sub_11:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.3030 - F1: 0.2926
sub_11:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.4848 - F1: 0.4829
sub_11:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6970 - F1: 0.6944
sub_11:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.3333 - F1: 0.3177
sub_12:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.6875 - F1: 0.6667
sub_12:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.5625
sub_12:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.6562 - F1: 0.6267
sub_12:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.4688 - F1: 0.4231
sub_12:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5938 - F1: 0.5901
sub_12:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5455 - F1: 0.5299
sub_12:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.6061 - F1: 0.6046
sub_12:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6364 - F1: 0.5909
sub_12:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6061 - F1: 0.5662
sub_12:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.4688 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4688 - F1: 0.4640
sub_12:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4062 - F1: 0.4057
sub_12:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.6250 - F1: 0.6113
sub_12:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6562 - F1: 0.6476
sub_13:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.5608
sub_13:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5758 - F1: 0.5754
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.5387
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5152 - F1: 0.4923
sub_13:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.3636 - F1: 0.3636
sub_13:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5455 - F1: 0.5455
sub_13:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4375 - F1: 0.4286
sub_13:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4688 - F1: 0.4682
sub_13:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5312 - F1: 0.5308
sub_13:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5312 - F1: 0.5195
sub_13:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5000 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5625 - F1: 0.5556
sub_14:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.6875 - F1: 0.6825
sub_14:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5938 - F1: 0.5836
sub_14:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.4375 - F1: 0.4286
sub_14:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.4688 - F1: 0.4682
sub_14:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6250 - F1: 0.6190
sub_14:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4375 - F1: 0.4353
sub_14:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5000 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.3750 - F1: 0.3651
sub_14:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4688 - F1: 0.4682
sub_14:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.7500 - F1: 0.7333
sub_15:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5000 - F1: 0.4818
sub_15:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5625 - F1: 0.5556
sub_15:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6875 - F1: 0.6825
sub_15:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5625 - F1: 0.5625
sub_15:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5625 - F1: 0.5625
sub_15:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5312 - F1: 0.5195
sub_15:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5938 - F1: 0.5393
sub_15:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.6562 - F1: 0.6559
sub_16:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4688 - F1: 0.4421
sub_16:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5312 - F1: 0.4386
sub_16:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5625 - F1: 0.5625
sub_16:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5625 - F1: 0.5625
sub_16:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5938 - F1: 0.5836
sub_16:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.4375 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5938 - F1: 0.5934
sub_17:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.4500
sub_17:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.6667 - F1: 0.6654
sub_17:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4545 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4848 - F1: 0.4672
sub_17:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6667 - F1: 0.6553
sub_17:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4242 - F1: 0.4242
sub_17:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.3939 - F1: 0.3934
sub_17:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4242 - F1: 0.4221
sub_17:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.4980
sub_17:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4688 - F1: 0.4555
sub_17:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4062 - F1: 0.3914
sub_17:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5312 - F1: 0.5195
sub_17:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4062 - F1: 0.3914
sub_18:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5758 - F1: 0.5658
sub_18:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.4848 - F1: 0.4772
sub_18:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5758 - F1: 0.5722
sub_18:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6061 - F1: 0.6002
sub_18:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5152 - F1: 0.4923
sub_18:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.4688 - F1: 0.4640
sub_18:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4688 - F1: 0.4682
sub_18:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6250 - F1: 0.6235
sub_18:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.4688 - F1: 0.4682
sub_18:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.4688 - F1: 0.4682
sub_18:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5312 - F1: 0.5077
sub_18:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5625 - F1: 0.5466
sub_18:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.3750 - F1: 0.3750
sub_19:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.4921
sub_19:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4375 - F1: 0.3455
sub_19:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.3125 - F1: 0.3098
sub_19:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5312 - F1: 0.4910
sub_19:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5312 - F1: 0.5195
sub_19:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.6250 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.4688 - F1: 0.4682
sub_19:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.7188 - F1: 0.7185
sub_20:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5312 - F1: 0.4910
sub_20:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5312 - F1: 0.5195
sub_20:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5000 - F1: 0.4667
sub_20:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5938 - F1: 0.5733
sub_20:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5625 - F1: 0.5333
sub_20:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5934
sub_20:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5455 - F1: 0.5438
sub_20:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5152 - F1: 0.4923
sub_20:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5455 - F1: 0.5171
sub_20:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5758 - F1: 0.5754
sub_21:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.6250 - F1: 0.6235
sub_21:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4375 - F1: 0.4375
sub_21:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.4688 - F1: 0.4682
sub_21:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4375 - F1: 0.4375
sub_21:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5000 - F1: 0.4980
sub_21:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4375 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.6562 - F1: 0.6476
sub_21:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5938 - F1: 0.5934
sub_21:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.2188 - F1: 0.2180
sub_21:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4688 - F1: 0.4421
sub_22:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6562 - F1: 0.6532
sub_22:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4375 - F1: 0.4375
sub_22:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6562 - F1: 0.6476
sub_22:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6562 - F1: 0.6559
sub_22:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5625 - F1: 0.5556
sub_22:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5152 - F1: 0.4261
sub_22:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5758 - F1: 0.5754
sub_22:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.4545 - F1: 0.4417
sub_22:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.6364 - F1: 0.5909
sub_22:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4242 - F1: 0.4242
sub_22:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.6250 - F1: 0.6235
sub_22:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5000 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5625 - F1: 0.5152
sub_22:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.4353
sub_23:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5152 - F1: 0.4923
sub_23:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4848 - F1: 0.4672
sub_23:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4545 - F1: 0.4540
sub_23:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6061 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.6061 - F1: 0.6002
sub_23:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.6250 - F1: 0.6000
sub_23:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5000 - F1: 0.4818
sub_23:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5938 - F1: 0.5733
sub_23:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5625 - F1: 0.5466
sub_23:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.3939 - F1: 0.3797
sub_23:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.6061 - F1: 0.6002
sub_23:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6667 - F1: 0.6654
sub_23:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5152 - F1: 0.3889
sub_23:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6667 - F1: 0.6553
sub_24:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4688 - F1: 0.4555
sub_24:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4062 - F1: 0.4057
sub_24:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4688 - F1: 0.4231
sub_24:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6562 - F1: 0.6390
sub_24:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5625 - F1: 0.5625
sub_24:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5000 - F1: 0.4921
sub_25:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.3939 - F1: 0.3797
sub_25:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.3636 - F1: 0.2993
sub_25:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.5455 - F1: 0.5387
sub_25:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4545 - F1: 0.4417
sub_25:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.6562 - F1: 0.6267
sub_25:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5938 - F1: 0.5589
sub_25:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.3438 - F1: 0.3379
sub_25:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.6250 - F1: 0.6190
sub_25:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.5000 - F1: 0.4459
sub_25:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5938 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5625 - F1: 0.5466
sub_26:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.6061 - F1: 0.6046
sub_26:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5152 - F1: 0.4923
sub_26:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6364 - F1: 0.6192
sub_26:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5152 - F1: 0.4923
sub_26:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.4848 - F1: 0.4672
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4062 - F1: 0.4057
sub_26:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6250 - F1: 0.6190
sub_26:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5312 - F1: 0.5271
sub_26:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6562 - F1: 0.6532
sub_26:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6875 - F1: 0.6875
sub_26:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5000 - F1: 0.4980
sub_26:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6562 - F1: 0.6390
sub_26:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.6250 - F1: 0.6235
sub_26:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4545 - F1: 0.4500
sub_27:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6364 - F1: 0.6278
sub_27:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.6667 - F1: 0.6654
sub_27:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4545 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4848 - F1: 0.4672
sub_27:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.4242 - F1: 0.4242
sub_27:Test (Best Model) - Loss: 0.7107 - Accuracy: 0.3939 - F1: 0.3934
sub_27:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4242 - F1: 0.4221
sub_27:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.4980
sub_27:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4688 - F1: 0.4555
sub_27:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4062 - F1: 0.3914
sub_27:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5312 - F1: 0.5195
sub_27:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4062 - F1: 0.3914
sub_28:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5938 - F1: 0.5934
sub_28:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5312 - F1: 0.4684
sub_28:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.3438 - F1: 0.3431
sub_28:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.7188 - F1: 0.7163
sub_28:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5312 - F1: 0.5308
sub_28:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4375 - F1: 0.4000
sub_28:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.4818
sub_28:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5938 - F1: 0.5836
sub_29:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6875 - F1: 0.6761
sub_29:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5938 - F1: 0.5934
sub_29:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.7188 - F1: 0.7046
sub_29:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.8125 - F1: 0.8000
sub_29:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.7188 - F1: 0.7185
sub_29:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.7500 - F1: 0.7490
sub_29:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.8125 - F1: 0.8095
sub_29:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6250 - F1: 0.6190
sub_29:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.8125 - F1: 0.8057
sub_29:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.6667 - F1: 0.6654
sub_29:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.7576 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6667 - F1: 0.6654
sub_29:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.7879 - F1: 0.7847
sub_29:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6061 - F1: 0.6061

=== Summary Results ===

acc: 54.42 ± 4.74
F1: 53.09 ± 4.73
acc-in: 60.30 ± 4.80
F1-in: 58.43 ± 5.07
