lr: 1e-05
sub_12:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.6250 - F1: 0.6235
sub_21:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6562 - F1: 0.6559
sub_7:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4062 - F1: 0.3914
sub_17:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.4545 - F1: 0.4540
sub_14:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.4910
sub_4:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6970 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5000 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4242 - F1: 0.4221
sub_13:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.5938 - F1: 0.5589
sub_28:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.8125 - F1: 0.8118
sub_8:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.4375 - F1: 0.4170
sub_19:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.7188 - F1: 0.7185
sub_27:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.4545 - F1: 0.4540
sub_2:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.7273 - F1: 0.7232
sub_1:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.6250 - F1: 0.6235
sub_9:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6250 - F1: 0.6235
sub_6:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5938 - F1: 0.5733
sub_5:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.3438 - F1: 0.3108
sub_25:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6364 - F1: 0.6360
sub_16:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5938 - F1: 0.5733
sub_10:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4375 - F1: 0.4000
sub_17:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5455 - F1: 0.5455
sub_29:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5152 - F1: 0.5038
sub_26:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.5758 - F1: 0.5722
sub_23:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4848 - F1: 0.4772
sub_13:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.2812 - F1: 0.2749
sub_15:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6250 - F1: 0.6235
sub_19:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5938 - F1: 0.5901
sub_7:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.8125 - F1: 0.8000
sub_20:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.9375 - F1: 0.9365
sub_18:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.6364 - F1: 0.6192
sub_8:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5312 - F1: 0.5308
sub_21:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4062 - F1: 0.4010
sub_3:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5312 - F1: 0.5195
sub_1:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.7188 - F1: 0.7185
sub_9:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7500 - F1: 0.7500
sub_27:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.5455 - F1: 0.5455
sub_14:Test (Best Model) - Loss: 0.7555 - Accuracy: 0.4062 - F1: 0.2889
sub_10:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5938 - F1: 0.5934
sub_2:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6364 - F1: 0.5909
sub_15:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.7188 - F1: 0.6946
sub_23:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4848 - F1: 0.4672
sub_4:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.7879 - F1: 0.7746
sub_16:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.7500 - F1: 0.7333
sub_17:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5152 - F1: 0.5147
sub_8:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.3438 - F1: 0.3431
sub_25:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5758 - F1: 0.5754
sub_5:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.7812 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.4062 - F1: 0.4010
sub_9:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.8438 - F1: 0.8398
sub_19:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5758 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.8125 - F1: 0.8095
sub_6:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6562 - F1: 0.6559
sub_12:Test (Best Model) - Loss: 0.7191 - Accuracy: 0.4375 - F1: 0.4286
sub_3:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.8125 - F1: 0.8000
sub_11:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6667 - F1: 0.6654
sub_26:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5152 - F1: 0.5038
sub_29:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.7812 - F1: 0.7758
sub_21:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5938 - F1: 0.5901
sub_20:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.4062 - F1: 0.4010
sub_2:Test (Best Model) - Loss: 0.6945 - Accuracy: 0.4545 - F1: 0.4540
sub_16:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.7218 - Accuracy: 0.4062 - F1: 0.3914
sub_27:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5152 - F1: 0.5147
sub_17:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.3939 - F1: 0.3934
sub_14:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4375 - F1: 0.4286
sub_15:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.6250 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5312 - F1: 0.5308
sub_4:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6061 - F1: 0.6046
sub_6:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.5625 - F1: 0.4909
sub_25:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7879 - F1: 0.7871
sub_1:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.5312 - F1: 0.5271
sub_23:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.6061 - F1: 0.5815
sub_22:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.3750 - F1: 0.3651
sub_20:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5938 - F1: 0.5901
sub_2:Test (Best Model) - Loss: 0.7266 - Accuracy: 0.3636 - F1: 0.3613
sub_19:Test (Best Model) - Loss: 0.7330 - Accuracy: 0.3750 - F1: 0.3651
sub_16:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.4375 - F1: 0.4353
sub_18:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.6061 - F1: 0.5460
sub_8:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5625 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4688 - F1: 0.4555
sub_10:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.6562 - F1: 0.6532
sub_14:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5625 - F1: 0.5152
sub_27:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.3939 - F1: 0.3934
sub_26:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5758 - F1: 0.5658
sub_3:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4688 - F1: 0.4231
sub_17:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5455 - F1: 0.5387
sub_6:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.6250 - F1: 0.6235
sub_4:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.3030 - F1: 0.3030
sub_22:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5938 - F1: 0.5733
sub_7:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.3438 - F1: 0.3379
sub_5:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.4818
sub_1:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.3750 - F1: 0.3725
sub_19:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5625 - F1: 0.5152
sub_11:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6667 - F1: 0.6667
sub_28:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6875 - F1: 0.6875
sub_10:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.6250 - F1: 0.6000
sub_18:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5152 - F1: 0.5111
sub_23:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5758 - F1: 0.5658
sub_26:Test (Best Model) - Loss: 0.7070 - Accuracy: 0.4545 - F1: 0.4500
sub_27:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5455 - F1: 0.5387
sub_16:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5625 - F1: 0.5152
sub_9:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.8125 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5000 - F1: 0.4818
sub_25:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5152 - F1: 0.5111
sub_4:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6364 - F1: 0.6192
sub_12:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4062 - F1: 0.3552
sub_14:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.8125 - F1: 0.8095
sub_5:Test (Best Model) - Loss: 0.7183 - Accuracy: 0.2500 - F1: 0.2500
sub_28:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.3750 - F1: 0.3750
sub_11:Test (Best Model) - Loss: 0.7378 - Accuracy: 0.2424 - F1: 0.2396
sub_24:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6250 - F1: 0.6235
sub_29:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.4688 - F1: 0.4640
sub_17:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5758 - F1: 0.5658
sub_15:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.7188 - F1: 0.7185
sub_1:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.2188 - F1: 0.2118
sub_6:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.4667
sub_13:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6364 - F1: 0.6192
sub_22:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5758 - F1: 0.5722
sub_26:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.3636 - F1: 0.3636
sub_7:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.4062 - F1: 0.4010
sub_3:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.6250 - F1: 0.6235
sub_21:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6250 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.5625
sub_2:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.4375 - F1: 0.4375
sub_18:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.7273 - F1: 0.7102
sub_28:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5625 - F1: 0.5608
sub_9:Test (Best Model) - Loss: 0.6249 - Accuracy: 0.7188 - F1: 0.6946
sub_26:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.6250 - F1: 0.6190
sub_20:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.6562 - F1: 0.6476
sub_12:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.6667 - F1: 0.6667
sub_13:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6667 - F1: 0.6667
sub_15:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5625 - F1: 0.5608
sub_11:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5758 - F1: 0.5722
sub_27:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5758 - F1: 0.5658
sub_5:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.7188 - F1: 0.6811
sub_7:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.4688 - F1: 0.4682
sub_23:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6250 - F1: 0.6113
sub_21:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5625 - F1: 0.5152
sub_6:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5455 - F1: 0.5438
sub_14:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.9062 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.6875 - F1: 0.6825
sub_3:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.4848 - F1: 0.4527
sub_19:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.9062 - F1: 0.9054
sub_10:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.7500 - F1: 0.7229
sub_25:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5455 - F1: 0.5438
sub_4:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.7879 - F1: 0.7871
sub_16:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4375 - F1: 0.4170
sub_12:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5152 - F1: 0.5147
sub_22:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5758 - F1: 0.5558
sub_28:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.7812 - F1: 0.7810
sub_13:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.4848 - F1: 0.4829
sub_5:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5312 - F1: 0.4910
sub_6:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.6364 - F1: 0.6192
sub_24:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.5938 - F1: 0.5901
sub_29:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5625 - F1: 0.5625
sub_14:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.4921
sub_21:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4375 - F1: 0.4353
sub_15:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5938 - F1: 0.5836
sub_26:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.6250 - F1: 0.6113
sub_9:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.9062 - F1: 0.9015
sub_23:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6250 - F1: 0.6113
sub_20:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.8125 - F1: 0.8118
sub_10:Test (Best Model) - Loss: 0.7144 - Accuracy: 0.4062 - F1: 0.4010
sub_11:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5758 - F1: 0.5754
sub_16:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.7500 - F1: 0.7460
sub_17:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5455 - F1: 0.5438
sub_7:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5758 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5938 - F1: 0.5934
sub_1:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6061 - F1: 0.6002
sub_28:Test (Best Model) - Loss: 0.7044 - Accuracy: 0.4688 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5152 - F1: 0.5038
sub_19:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4062 - F1: 0.3914
sub_8:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.3125 - F1: 0.3098
sub_13:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4242 - F1: 0.4046
sub_24:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6250 - F1: 0.6000
sub_4:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6061 - F1: 0.5815
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4545 - F1: 0.4540
sub_5:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.7500 - F1: 0.7460
sub_14:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.3750 - F1: 0.3725
sub_25:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5625 - F1: 0.5608
sub_22:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.9091 - F1: 0.9077
sub_18:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4375 - F1: 0.3766
sub_17:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.6061 - F1: 0.6046
sub_28:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.3125 - F1: 0.3016
sub_29:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5938 - F1: 0.5393
sub_21:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.6562 - F1: 0.6267
sub_27:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5455 - F1: 0.5438
sub_12:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.2727 - F1: 0.2721
sub_13:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.3939 - F1: 0.3654
sub_10:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.4286
sub_6:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.1818 - F1: 0.1788
sub_4:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.6061 - F1: 0.6046
sub_9:Test (Best Model) - Loss: 0.6004 - Accuracy: 0.8750 - F1: 0.8704
sub_19:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.2500 - F1: 0.2471
sub_15:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4688 - F1: 0.4640
sub_26:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.7188 - F1: 0.6946
sub_7:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4375 - F1: 0.4170
sub_24:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3750 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6562 - F1: 0.6102
sub_18:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5455 - F1: 0.5438
sub_23:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5312 - F1: 0.5271
sub_11:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6970 - F1: 0.6827
sub_16:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.6250 - F1: 0.6235
sub_1:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7273 - F1: 0.6997
sub_8:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.8438 - F1: 0.8436
sub_29:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5625 - F1: 0.5556
sub_17:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6364 - F1: 0.6333
sub_22:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.3939 - F1: 0.3934
sub_14:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4375 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.4818
sub_21:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.3750 - F1: 0.3750
sub_27:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.6061 - F1: 0.6046
sub_25:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.5000 - F1: 0.4818
sub_10:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.4688 - F1: 0.4421
sub_12:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.3939 - F1: 0.3889
sub_26:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.3125 - F1: 0.2667
sub_28:Test (Best Model) - Loss: 0.7117 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6562 - F1: 0.6390
sub_2:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.3750 - F1: 0.3333
sub_19:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5312 - F1: 0.5077
sub_9:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.3030 - F1: 0.2792
sub_6:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6364 - F1: 0.6360
sub_15:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5938 - F1: 0.5901
sub_1:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5758 - F1: 0.5754
sub_23:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.6875 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5938 - F1: 0.5934
sub_20:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4848 - F1: 0.4527
sub_7:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.5938 - F1: 0.5589
sub_22:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4242 - F1: 0.4242
sub_10:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5455 - F1: 0.4995
sub_16:Test (Best Model) - Loss: 0.6470 - Accuracy: 0.8438 - F1: 0.8436
sub_21:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.3750 - F1: 0.3725
sub_27:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6364 - F1: 0.6333
sub_25:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4688 - F1: 0.4682
sub_29:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.7812 - F1: 0.7703
sub_8:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.3125 - F1: 0.2667
sub_26:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5312 - F1: 0.5308
sub_14:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.7500 - F1: 0.7409
sub_24:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4062 - F1: 0.4057
sub_20:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5312 - F1: 0.5271
sub_23:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.4062 - F1: 0.3914
sub_6:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5455 - F1: 0.5438
sub_13:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5312 - F1: 0.5271
sub_21:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5938 - F1: 0.5901
sub_2:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6875 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.6875 - F1: 0.6825
sub_17:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.7188 - F1: 0.7117
sub_22:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.7500 - F1: 0.7460
sub_18:Test (Best Model) - Loss: 0.7262 - Accuracy: 0.2188 - F1: 0.2180
sub_10:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5152 - F1: 0.5147
sub_3:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6970 - F1: 0.6827
sub_15:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6250 - F1: 0.6113
sub_27:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.4848 - F1: 0.4527
sub_4:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.5455 - F1: 0.5299
sub_28:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5000 - F1: 0.4921
sub_19:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6562 - F1: 0.6102
sub_1:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.3939 - F1: 0.3654
sub_8:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.5312 - F1: 0.5308
sub_20:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5312 - F1: 0.5195
sub_16:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.4688 - F1: 0.4640
sub_11:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.7576 - F1: 0.7381
sub_5:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4062 - F1: 0.4010
sub_29:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5758 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6875 - F1: 0.6667
sub_27:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.7188 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.3636 - F1: 0.3613
sub_7:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6250 - F1: 0.6235
sub_14:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6250 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6250 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6250 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.2500 - F1: 0.2471
sub_4:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5152 - F1: 0.5111
sub_9:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.9062 - F1: 0.9039
sub_24:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5312 - F1: 0.5271
sub_23:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.7879 - F1: 0.7664
sub_6:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5758 - F1: 0.5722
sub_2:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.7576 - F1: 0.7462
sub_11:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.2424 - F1: 0.2311
sub_28:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.7188 - F1: 0.7185
sub_29:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4375 - F1: 0.4170
sub_22:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4688 - F1: 0.4640
sub_10:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.6970 - F1: 0.6944
sub_21:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.5000
sub_16:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5938 - F1: 0.5836
sub_26:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.4980
sub_8:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.8125 - F1: 0.8118
sub_3:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6061 - F1: 0.6061
sub_18:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.7812 - F1: 0.7810
sub_20:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.7274 - Accuracy: 0.3125 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.7812 - F1: 0.7810
sub_5:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5938 - F1: 0.5836
sub_13:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5938 - F1: 0.5836
sub_1:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.7273 - F1: 0.7263
sub_23:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4848 - F1: 0.4772
sub_21:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5312 - F1: 0.5271
sub_6:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.3030 - F1: 0.3005
sub_28:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6562 - F1: 0.6102
sub_7:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5938 - F1: 0.5934
sub_10:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5455 - F1: 0.5438
sub_14:Test (Best Model) - Loss: 0.7164 - Accuracy: 0.4062 - F1: 0.3764
sub_22:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6562 - F1: 0.6390
sub_11:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4848 - F1: 0.4829
sub_12:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.7500 - F1: 0.7500
sub_27:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5836
sub_15:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.8750 - F1: 0.8745
sub_24:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.5938 - F1: 0.5901
sub_2:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5152 - F1: 0.4762
sub_16:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.4688 - F1: 0.4555
sub_23:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.3030 - F1: 0.3030
sub_18:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5938 - F1: 0.5589
sub_17:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5152 - F1: 0.5147
sub_13:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.7188 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6667 - F1: 0.6617
sub_21:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5312 - F1: 0.5308
sub_4:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7879 - F1: 0.7871
sub_1:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.4980
sub_11:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.6970 - F1: 0.6413
sub_25:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5312 - F1: 0.5271
sub_26:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7188 - F1: 0.7117
sub_29:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6875 - F1: 0.6875
sub_14:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5312 - F1: 0.5195
sub_24:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4688 - F1: 0.4640
sub_12:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5938 - F1: 0.5901
sub_27:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5312 - F1: 0.5308
sub_2:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5455 - F1: 0.5438
sub_16:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6250 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.4062 - F1: 0.4010
sub_17:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.5625
sub_9:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.9062 - F1: 0.9062
sub_6:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.6364 - F1: 0.6278
sub_22:Test (Best Model) - Loss: 0.6255 - Accuracy: 0.8750 - F1: 0.8745
sub_20:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6061 - F1: 0.5815
sub_4:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6061 - F1: 0.6002
sub_19:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4062 - F1: 0.4010
sub_23:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.6061 - F1: 0.6046
sub_21:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7188 - F1: 0.6811
sub_26:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.5938 - F1: 0.5934
sub_18:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.7188 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5312 - F1: 0.5308
sub_12:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.4062 - F1: 0.3914
sub_27:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5625 - F1: 0.5625
sub_28:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.3125 - F1: 0.2667
sub_14:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.8485 - F1: 0.8479
sub_22:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.6747 - Accuracy: 0.6364 - F1: 0.6360
sub_23:Test (Best Model) - Loss: 0.6312 - Accuracy: 0.8788 - F1: 0.8759
sub_18:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.5000 - F1: 0.4980
sub_4:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5758 - F1: 0.5754
sub_26:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6250 - F1: 0.6235
sub_7:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.7812 - F1: 0.7793
sub_11:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6970 - F1: 0.6967
sub_17:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.7188 - F1: 0.7117
sub_20:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.8485 - F1: 0.8479
sub_1:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5625 - F1: 0.5625
sub_9:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.8438 - F1: 0.8436
sub_25:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.6250 - F1: 0.6250
sub_27:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.7188 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.7576 - F1: 0.7519
sub_20:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.6970 - F1: 0.6967
sub_11:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.3939 - F1: 0.3797
sub_7:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.8750 - F1: 0.8730
sub_18:Test (Best Model) - Loss: 0.6471 - Accuracy: 0.8438 - F1: 0.8424
sub_2:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.7879 - F1: 0.7746
sub_4:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5758 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6562 - F1: 0.6532
sub_1:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.3030 - F1: 0.2792
sub_5:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6562 - F1: 0.6559
sub_11:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.7812 - F1: 0.7810
sub_29:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.8182 - F1: 0.8180
sub_1:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.8750 - F1: 0.8667
sub_25:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.6250 - F1: 0.6235
sub_29:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6667 - F1: 0.6459
sub_11:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.6970 - F1: 0.6898
sub_25:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4062 - F1: 0.3764
sub_9:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.8750 - F1: 0.8745
sub_29:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.5758 - F1: 0.5658
sub_9:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8125 - F1: 0.8125

=== Summary Results ===

acc: 58.55 ± 5.49
F1: 57.52 ± 5.59
acc-in: 59.71 ± 5.59
F1-in: 58.21 ± 5.85
