lr: 1e-06
sub_28:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.2500 - F1: 0.2381
sub_4:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.3333 - F1: 0.3327
sub_16:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4062 - F1: 0.4010
sub_25:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_14:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5312 - F1: 0.4684
sub_9:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.4062 - F1: 0.4010
sub_21:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.8125 - F1: 0.8095
sub_3:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4375 - F1: 0.4353
sub_26:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.4242 - F1: 0.4221
sub_22:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6875 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.3030 - F1: 0.2792
sub_18:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5455 - F1: 0.5438
sub_19:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.3750 - F1: 0.3074
sub_11:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.6061 - F1: 0.6002
sub_8:Test (Best Model) - Loss: 0.7388 - Accuracy: 0.3125 - F1: 0.2381
sub_1:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6250 - F1: 0.6113
sub_15:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6562 - F1: 0.6390
sub_27:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6364 - F1: 0.6071
sub_29:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.3750 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.8750 - F1: 0.8750
sub_5:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.8438 - F1: 0.8398
sub_24:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5625 - F1: 0.5466
sub_13:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.7600 - Accuracy: 0.2500 - F1: 0.2000
sub_17:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6364 - F1: 0.6071
sub_21:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.5938 - F1: 0.4340
sub_3:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.2812 - F1: 0.2749
sub_6:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.4062 - F1: 0.3914
sub_23:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4848 - F1: 0.4848
sub_20:Test (Best Model) - Loss: 0.7415 - Accuracy: 0.3125 - F1: 0.2667
sub_4:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6364 - F1: 0.6278
sub_29:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.7500 - F1: 0.7490
sub_22:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.3750 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6970 - F1: 0.6967
sub_11:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5152 - F1: 0.4762
sub_1:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6562 - F1: 0.6532
sub_2:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5758 - F1: 0.5658
sub_25:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.4848 - F1: 0.4829
sub_16:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.3438 - F1: 0.3273
sub_8:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6364 - F1: 0.6278
sub_24:Test (Best Model) - Loss: 0.7260 - Accuracy: 0.2812 - F1: 0.2749
sub_12:Test (Best Model) - Loss: 0.7130 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4062 - F1: 0.4057
sub_14:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6562 - F1: 0.6390
sub_4:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6667 - F1: 0.6617
sub_22:Test (Best Model) - Loss: 0.7439 - Accuracy: 0.3125 - F1: 0.3098
sub_21:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.4375 - F1: 0.4170
sub_28:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.5938 - F1: 0.5901
sub_2:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.7879 - F1: 0.7746
sub_17:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.6364 - F1: 0.6278
sub_16:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6562 - F1: 0.6532
sub_18:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.6364 - F1: 0.6360
sub_11:Test (Best Model) - Loss: 0.7342 - Accuracy: 0.3636 - F1: 0.2667
sub_29:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.4375 - F1: 0.4170
sub_9:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.6250 - F1: 0.6235
sub_8:Test (Best Model) - Loss: 0.6025 - Accuracy: 0.8750 - F1: 0.8667
sub_15:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.4062 - F1: 0.4010
sub_19:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.8438 - F1: 0.8424
sub_13:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.8750 - F1: 0.8745
sub_23:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5758 - F1: 0.5722
sub_25:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.3636 - F1: 0.2993
sub_27:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6970 - F1: 0.6944
sub_5:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.3750 - F1: 0.2727
sub_14:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4688 - F1: 0.4640
sub_24:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.5312 - F1: 0.5077
sub_26:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.5152 - F1: 0.5147
sub_7:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.7500 - F1: 0.7460
sub_12:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.4980
sub_3:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.4375 - F1: 0.4286
sub_22:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6562 - F1: 0.6559
sub_20:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6250 - F1: 0.6113
sub_1:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7273 - F1: 0.7273
sub_28:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8438 - F1: 0.8359
sub_16:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.7500 - F1: 0.7460
sub_10:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6875 - F1: 0.6537
sub_17:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6970 - F1: 0.6944
sub_11:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.7273 - F1: 0.7232
sub_8:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6875 - F1: 0.6863
sub_18:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.8485 - F1: 0.8479
sub_29:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6562 - F1: 0.6390
sub_2:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5152 - F1: 0.5147
sub_25:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.5152 - F1: 0.5111
sub_6:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6562 - F1: 0.6559
sub_23:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5758 - F1: 0.5722
sub_12:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.7188 - F1: 0.7185
sub_26:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4545 - F1: 0.4500
sub_21:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4062 - F1: 0.2889
sub_27:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6875 - F1: 0.6863
sub_7:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5312 - F1: 0.4684
sub_20:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.8125 - F1: 0.8000
sub_13:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.7188 - F1: 0.6632
sub_9:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4062 - F1: 0.4057
sub_4:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.3438 - F1: 0.3431
sub_11:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.4848 - F1: 0.4772
sub_17:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.9394 - F1: 0.9380
sub_18:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6667 - F1: 0.6159
sub_29:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.7273 - F1: 0.7179
sub_1:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6875 - F1: 0.6761
sub_14:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.5625 - F1: 0.5152
sub_15:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.8438 - F1: 0.8424
sub_19:Test (Best Model) - Loss: 0.6520 - Accuracy: 0.7500 - F1: 0.7460
sub_21:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5625 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.9375 - F1: 0.9365
sub_28:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5312 - F1: 0.5195
sub_23:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.7273 - F1: 0.7232
sub_22:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.4688 - F1: 0.4555
sub_25:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4545 - F1: 0.3864
sub_5:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.7812 - F1: 0.7703
sub_24:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6250 - F1: 0.6235
sub_27:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6667 - F1: 0.6553
sub_7:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4062 - F1: 0.4057
sub_6:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4375 - F1: 0.3766
sub_20:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.6875 - F1: 0.6825
sub_3:Test (Best Model) - Loss: 0.7166 - Accuracy: 0.2812 - F1: 0.2805
sub_16:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.4375 - F1: 0.4170
sub_4:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.3939 - F1: 0.3452
sub_13:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.9375 - F1: 0.9365
sub_10:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.7500 - F1: 0.7333
sub_17:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6667 - F1: 0.6553
sub_18:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5938 - F1: 0.5836
sub_29:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.7500 - F1: 0.7333
sub_26:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.8788 - F1: 0.8778
sub_2:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.6759 - Accuracy: 0.7812 - F1: 0.7703
sub_8:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.7188 - F1: 0.6632
sub_21:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6250 - F1: 0.6235
sub_28:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6875 - F1: 0.6537
sub_24:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6667 - F1: 0.6459
sub_22:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.7576 - F1: 0.7381
sub_19:Test (Best Model) - Loss: 0.6691 - Accuracy: 0.5938 - F1: 0.4793
sub_9:Test (Best Model) - Loss: 0.5940 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4375 - F1: 0.4286
sub_27:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.7879 - F1: 0.7871
sub_5:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.7812 - F1: 0.7519
sub_4:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6364 - F1: 0.6278
sub_7:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.5938 - F1: 0.5589
sub_11:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6364 - F1: 0.6360
sub_20:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6250 - F1: 0.6113
sub_6:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.7812 - F1: 0.7519
sub_1:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6562 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.7576 - F1: 0.7462
sub_10:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6875 - F1: 0.6875
sub_13:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.4062 - F1: 0.3764
sub_17:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.7879 - F1: 0.7871
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5312 - F1: 0.5308
sub_2:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6562 - F1: 0.6476
sub_15:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.7188 - F1: 0.7163
sub_26:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6061 - F1: 0.6046
sub_12:Test (Best Model) - Loss: 0.7108 - Accuracy: 0.3939 - F1: 0.3182
sub_28:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5625 - F1: 0.5608
sub_21:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.6562 - F1: 0.6476
sub_4:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6970 - F1: 0.6898
sub_22:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.4848 - F1: 0.3718
sub_19:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.6250 - F1: 0.5362
sub_14:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5938 - F1: 0.5393
sub_9:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.3438 - F1: 0.3379
sub_27:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.6667 - F1: 0.6654
sub_18:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.5938 - F1: 0.5733
sub_16:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5312 - F1: 0.4684
sub_23:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.3750 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.6562 - F1: 0.6476
sub_7:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.8125 - F1: 0.8057
sub_6:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6364 - F1: 0.6333
sub_20:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5312 - F1: 0.5271
sub_3:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5455 - F1: 0.4995
sub_10:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.6562 - F1: 0.5594
sub_1:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.7879 - F1: 0.7746
sub_28:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4688 - F1: 0.3637
sub_8:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.7812 - F1: 0.7703
sub_2:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.3750 - F1: 0.3725
sub_13:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5152 - F1: 0.4762
sub_26:Test (Best Model) - Loss: 0.7153 - Accuracy: 0.4688 - F1: 0.3976
sub_29:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5625 - F1: 0.5152
sub_17:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.6667 - F1: 0.6654
sub_22:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6061 - F1: 0.6061
sub_25:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.5625 - F1: 0.5556
sub_4:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.7576 - F1: 0.7556
sub_11:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.7576 - F1: 0.7519
sub_21:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.5938 - F1: 0.5836
sub_24:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5312 - F1: 0.5077
sub_19:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6250 - F1: 0.5362
sub_15:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5938 - F1: 0.5901
sub_27:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6061 - F1: 0.5815
sub_18:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6562 - F1: 0.5883
sub_12:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5455 - F1: 0.5455
sub_16:Test (Best Model) - Loss: 0.7109 - Accuracy: 0.3750 - F1: 0.2727
sub_9:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.7188 - F1: 0.7163
sub_23:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.7576 - F1: 0.7381
sub_7:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.3750 - F1: 0.3522
sub_26:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.7812 - F1: 0.7793
sub_2:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.7188 - F1: 0.7185
sub_20:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.5625
sub_14:Test (Best Model) - Loss: 0.7208 - Accuracy: 0.3438 - F1: 0.3431
sub_1:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5152 - F1: 0.5038
sub_28:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6875 - F1: 0.6863
sub_13:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5455 - F1: 0.4762
sub_5:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4375 - F1: 0.4286
sub_25:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.3438 - F1: 0.3431
sub_29:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.7188 - F1: 0.7163
sub_4:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.8182 - F1: 0.8180
sub_17:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6061 - F1: 0.5815
sub_11:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5152 - F1: 0.5038
sub_22:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5758 - F1: 0.5417
sub_21:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6562 - F1: 0.6267
sub_15:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.8125 - F1: 0.8118
sub_3:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6364 - F1: 0.6192
sub_27:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6364 - F1: 0.6333
sub_19:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.8125 - F1: 0.8118
sub_23:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.8125 - F1: 0.8057
sub_16:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.7188 - F1: 0.6632
sub_18:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.8438 - F1: 0.8436
sub_6:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.7879 - F1: 0.7806
sub_12:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.3438 - F1: 0.3273
sub_2:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6562 - F1: 0.6559
sub_7:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.7812 - F1: 0.7758
sub_20:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5625 - F1: 0.5466
sub_13:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5152 - F1: 0.3400
sub_10:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5312 - F1: 0.5077
sub_14:Test (Best Model) - Loss: 0.7110 - Accuracy: 0.3438 - F1: 0.3431
sub_1:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.8182 - F1: 0.8036
sub_9:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.4688 - F1: 0.4640
sub_28:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6562 - F1: 0.6267
sub_5:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.6562 - F1: 0.6390
sub_25:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5000 - F1: 0.4667
sub_4:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.3939 - F1: 0.3452
sub_29:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7500 - F1: 0.7460
sub_16:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.4545 - F1: 0.3864
sub_17:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.6364 - F1: 0.6333
sub_15:Test (Best Model) - Loss: 0.6514 - Accuracy: 0.8125 - F1: 0.8118
sub_3:Test (Best Model) - Loss: 0.7157 - Accuracy: 0.3939 - F1: 0.3889
sub_21:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.6875 - F1: 0.6825
sub_19:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.6250 - F1: 0.5362
sub_23:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5000 - F1: 0.4182
sub_26:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5625 - F1: 0.5333
sub_6:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.8182 - F1: 0.8096
sub_10:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5625 - F1: 0.5152
sub_24:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6250 - F1: 0.6113
sub_12:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.6667 - F1: 0.6553
sub_13:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5455 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6667 - F1: 0.6553
sub_14:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.7812 - F1: 0.7625
sub_29:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.8125 - F1: 0.8095
sub_11:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6667 - F1: 0.6654
sub_4:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5758 - F1: 0.5558
sub_8:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5000 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.6297 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4688 - F1: 0.4640
sub_25:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.6653 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 0.7234 - Accuracy: 0.2188 - F1: 0.2118
sub_16:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6562 - F1: 0.6102
sub_15:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.9062 - F1: 0.9062
sub_21:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.2500 - F1: 0.2227
sub_28:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.3438 - F1: 0.3379
sub_6:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.6970 - F1: 0.6726
sub_26:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4688 - F1: 0.4231
sub_20:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.6875 - F1: 0.6825
sub_19:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.7188 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.6667 - F1: 0.6553
sub_18:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.8750 - F1: 0.8667
sub_10:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.3125 - F1: 0.2381
sub_2:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5758 - F1: 0.5754
sub_3:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.6364 - F1: 0.6278
sub_17:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6667 - F1: 0.6553
sub_7:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5938 - F1: 0.5901
sub_27:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5938 - F1: 0.4793
sub_4:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4545 - F1: 0.3864
sub_14:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.3438 - F1: 0.3108
sub_11:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.5758 - F1: 0.5754
sub_8:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5758 - F1: 0.5558
sub_22:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5455 - F1: 0.5438
sub_9:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.8125 - F1: 0.7922
sub_1:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.8182 - F1: 0.8139
sub_25:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4062 - F1: 0.3914
sub_23:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.8125 - F1: 0.8000
sub_16:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.7188 - F1: 0.7046
sub_15:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.4062 - F1: 0.3552
sub_21:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.6562 - F1: 0.6390
sub_6:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.3939 - F1: 0.3797
sub_20:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.4062 - F1: 0.3914
sub_26:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5938 - F1: 0.5901
sub_19:Test (Best Model) - Loss: 0.7239 - Accuracy: 0.3750 - F1: 0.2727
sub_12:Test (Best Model) - Loss: 0.7699 - Accuracy: 0.2188 - F1: 0.1795
sub_4:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.4545 - F1: 0.4288
sub_18:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5938 - F1: 0.5135
sub_7:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.3750 - F1: 0.3725
sub_14:Test (Best Model) - Loss: 0.7323 - Accuracy: 0.0625 - F1: 0.0588
sub_2:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4242 - F1: 0.3883
sub_17:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5938 - F1: 0.4793
sub_24:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.7188 - F1: 0.7185
sub_27:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.7812 - F1: 0.7793
sub_8:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.8750 - F1: 0.8730
sub_22:Test (Best Model) - Loss: 0.7504 - Accuracy: 0.1250 - F1: 0.1111
sub_5:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5625 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6364 - F1: 0.5696
sub_29:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6667 - F1: 0.6159
sub_3:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.8788 - F1: 0.8787
sub_9:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.7188 - F1: 0.7046
sub_23:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.3636 - F1: 0.3419
sub_25:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.7500 - F1: 0.7490
sub_11:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6061 - F1: 0.6061
sub_26:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.8125 - F1: 0.8057
sub_12:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.8438 - F1: 0.8398
sub_15:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.7812 - F1: 0.7703
sub_13:Test (Best Model) - Loss: 0.7404 - Accuracy: 0.2188 - F1: 0.1992
sub_16:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.3750 - F1: 0.3651
sub_6:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.8485 - F1: 0.8462
sub_21:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.5000 - F1: 0.4459
sub_4:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.3939 - F1: 0.3889
sub_7:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.7500 - F1: 0.7409
sub_19:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.5625 - F1: 0.5625
sub_20:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5455 - F1: 0.5438
sub_1:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.2188 - F1: 0.1992
sub_24:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6562 - F1: 0.6476
sub_27:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.5608
sub_8:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.8438 - F1: 0.8398
sub_17:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5000 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5312 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.7188 - F1: 0.7163
sub_14:Test (Best Model) - Loss: 0.6183 - Accuracy: 0.7812 - F1: 0.7625
sub_9:Test (Best Model) - Loss: 0.7114 - Accuracy: 0.2500 - F1: 0.2471
sub_10:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.4545 - F1: 0.4288
sub_29:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.6364 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.5312 - F1: 0.5308
sub_23:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.7273 - F1: 0.7179
sub_25:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6562 - F1: 0.5594
sub_12:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.4459
sub_18:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.7812 - F1: 0.7703
sub_16:Test (Best Model) - Loss: 0.7487 - Accuracy: 0.3125 - F1: 0.2381
sub_26:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.7188 - F1: 0.6946
sub_13:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.8438 - F1: 0.8398
sub_7:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.5625 - F1: 0.5625
sub_21:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6875 - F1: 0.6875
sub_6:Test (Best Model) - Loss: 0.6167 - Accuracy: 0.8182 - F1: 0.8036
sub_2:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.6061 - F1: 0.6002
sub_15:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7188 - F1: 0.7185
sub_3:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6667 - F1: 0.6617
sub_24:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6250 - F1: 0.6250
sub_1:Test (Best Model) - Loss: 0.6134 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6875 - F1: 0.6667
sub_17:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5625 - F1: 0.5608
sub_27:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.2188 - F1: 0.2180
sub_14:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.7188 - F1: 0.7185
sub_28:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.7500 - F1: 0.7460
sub_9:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.8125 - F1: 0.8000
sub_20:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.8788 - F1: 0.8759
sub_11:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.7879 - F1: 0.7806
sub_10:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.6061 - F1: 0.5926
sub_22:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.6875 - F1: 0.6537
sub_26:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.3939 - F1: 0.3934
sub_23:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5455 - F1: 0.5387
sub_13:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.7188 - F1: 0.7185
sub_19:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4375 - F1: 0.4375
sub_7:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.6061 - F1: 0.4850
sub_6:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6970 - F1: 0.6827
sub_21:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.3750 - F1: 0.3522
sub_8:Test (Best Model) - Loss: 0.7337 - Accuracy: 0.1875 - F1: 0.1875
sub_24:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6562 - F1: 0.6390
sub_15:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.0938 - F1: 0.0929
sub_17:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.2188 - F1: 0.2180
sub_16:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5938 - F1: 0.5393
sub_3:Test (Best Model) - Loss: 0.7145 - Accuracy: 0.2727 - F1: 0.2385
sub_5:Test (Best Model) - Loss: 0.6578 - Accuracy: 0.6875 - F1: 0.6364
sub_12:Test (Best Model) - Loss: 0.7050 - Accuracy: 0.4688 - F1: 0.4640
sub_27:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.8125 - F1: 0.8125
sub_1:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.6875 - F1: 0.6135
sub_25:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.6875 - F1: 0.6825
sub_20:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.4242 - F1: 0.4221
sub_18:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4688 - F1: 0.4555
sub_29:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.2424 - F1: 0.2165
sub_14:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4545 - F1: 0.4417
sub_11:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.6667 - F1: 0.6617
sub_13:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6562 - F1: 0.6102
sub_19:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.3750 - F1: 0.3522
sub_28:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4688 - F1: 0.3976
sub_10:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.3939 - F1: 0.3934
sub_17:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.8125 - F1: 0.8125
sub_15:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.7500 - F1: 0.7333
sub_26:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.7500 - F1: 0.7091
sub_3:Test (Best Model) - Loss: 0.6972 - Accuracy: 0.5758 - F1: 0.4978
sub_25:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4375 - F1: 0.3766
sub_12:Test (Best Model) - Loss: 0.6395 - Accuracy: 0.8125 - F1: 0.8118
sub_2:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.4848 - F1: 0.4829
sub_1:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.7500 - F1: 0.7490
sub_5:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6875 - F1: 0.6825
sub_6:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.3030 - F1: 0.2595
sub_18:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.3939 - F1: 0.3934
sub_14:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5000 - F1: 0.4921
sub_9:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6250 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4848 - F1: 0.4772
sub_10:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6061 - F1: 0.6046
sub_19:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.7500 - F1: 0.7490
sub_13:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4375 - F1: 0.4000
sub_20:Test (Best Model) - Loss: 0.6509 - Accuracy: 0.7879 - F1: 0.7871
sub_23:Test (Best Model) - Loss: 0.6992 - Accuracy: 0.4848 - F1: 0.4527
sub_9:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5312 - F1: 0.5308
sub_11:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.2424 - F1: 0.2396
sub_1:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.3750 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.4848 - F1: 0.4848
sub_5:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.4062 - F1: 0.3267

=== Summary Results ===

acc: 59.33 ± 4.27
F1: 57.20 ± 4.59
acc-in: 59.67 ± 4.50
F1-in: 58.14 ± 4.65
