lr: 1e-06
sub_2:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.6667 - F1: 0.6617
sub_3:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.5000 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4242 - F1: 0.4221
sub_16:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5938 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5938 - F1: 0.5934
sub_14:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5312 - F1: 0.4684
sub_13:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5625 - F1: 0.5152
sub_22:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4242 - F1: 0.4221
sub_12:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6875 - F1: 0.6875
sub_21:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6562 - F1: 0.6559
sub_4:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6970 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6061 - F1: 0.5662
sub_6:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5938 - F1: 0.5733
sub_8:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.5938 - F1: 0.5901
sub_28:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.7135 - Accuracy: 0.3438 - F1: 0.3108
sub_15:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.3750 - F1: 0.3333
sub_26:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.4848 - F1: 0.4772
sub_11:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.3030 - F1: 0.2595
sub_3:Test (Best Model) - Loss: 0.7145 - Accuracy: 0.4062 - F1: 0.4010
sub_20:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.8125 - F1: 0.8125
sub_7:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.3750 - F1: 0.3651
sub_24:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5312 - F1: 0.5308
sub_18:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5455 - F1: 0.5171
sub_29:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.7500 - F1: 0.7490
sub_25:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.6364 - F1: 0.6360
sub_9:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5312 - F1: 0.5308
sub_1:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.4375 - F1: 0.4170
sub_2:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4242 - F1: 0.4221
sub_23:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.3939 - F1: 0.3934
sub_14:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4375 - F1: 0.4353
sub_8:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5312 - F1: 0.5195
sub_22:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.7188 - F1: 0.6632
sub_21:Test (Best Model) - Loss: 0.7266 - Accuracy: 0.2812 - F1: 0.2805
sub_13:Test (Best Model) - Loss: 0.7445 - Accuracy: 0.2812 - F1: 0.2749
sub_28:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.4062 - F1: 0.3914
sub_4:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6667 - F1: 0.6553
sub_27:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.4545 - F1: 0.4500
sub_12:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.7500 - F1: 0.7229
sub_16:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7188 - F1: 0.7046
sub_10:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5312 - F1: 0.5077
sub_5:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.6875 - F1: 0.6135
sub_15:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5000 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.7177 - Accuracy: 0.4062 - F1: 0.4010
sub_26:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4848 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.7500 - F1: 0.7333
sub_18:Test (Best Model) - Loss: 0.7102 - Accuracy: 0.5152 - F1: 0.4261
sub_17:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.4545 - F1: 0.4500
sub_19:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.7188 - F1: 0.7185
sub_7:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4062 - F1: 0.4057
sub_25:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4848 - F1: 0.4829
sub_24:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.4375 - F1: 0.4353
sub_29:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.6299 - Accuracy: 0.7500 - F1: 0.7490
sub_21:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5625 - F1: 0.5608
sub_11:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5758 - F1: 0.5754
sub_14:Test (Best Model) - Loss: 0.7573 - Accuracy: 0.3750 - F1: 0.2727
sub_1:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.6250 - F1: 0.6250
sub_22:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.7500 - F1: 0.7409
sub_12:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.3125 - F1: 0.3098
sub_23:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.3636 - F1: 0.3541
sub_13:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.3438 - F1: 0.3379
sub_28:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.4062 - F1: 0.4010
sub_2:Test (Best Model) - Loss: 0.7367 - Accuracy: 0.3030 - F1: 0.2926
sub_4:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4848 - F1: 0.4772
sub_27:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4848 - F1: 0.4829
sub_16:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5938 - F1: 0.5836
sub_10:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.4375 - F1: 0.4375
sub_20:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.4688 - F1: 0.4555
sub_15:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.6875 - F1: 0.6667
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.5000 - F1: 0.3816
sub_26:Test (Best Model) - Loss: 0.7121 - Accuracy: 0.3333 - F1: 0.3278
sub_3:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5000 - F1: 0.4980
sub_8:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.2812 - F1: 0.2805
sub_5:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.8125 - F1: 0.7922
sub_19:Test (Best Model) - Loss: 0.7476 - Accuracy: 0.3125 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.3636 - F1: 0.3613
sub_29:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.3438 - F1: 0.3431
sub_9:Test (Best Model) - Loss: 0.7501 - Accuracy: 0.1250 - F1: 0.1216
sub_17:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4848 - F1: 0.4829
sub_21:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.3438 - F1: 0.3379
sub_11:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6667 - F1: 0.6667
sub_23:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.3939 - F1: 0.3797
sub_22:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.2812 - F1: 0.2633
sub_25:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.7273 - F1: 0.7232
sub_13:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.4062 - F1: 0.4057
sub_20:Test (Best Model) - Loss: 0.7339 - Accuracy: 0.3125 - F1: 0.3016
sub_2:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4242 - F1: 0.4221
sub_24:Test (Best Model) - Loss: 0.7288 - Accuracy: 0.3125 - F1: 0.3016
sub_27:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.3333 - F1: 0.3327
sub_12:Test (Best Model) - Loss: 0.7190 - Accuracy: 0.3750 - F1: 0.3651
sub_6:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5312 - F1: 0.5308
sub_15:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.3750 - F1: 0.3651
sub_4:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.2727 - F1: 0.2721
sub_16:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.3750 - F1: 0.3725
sub_28:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.4688 - F1: 0.4682
sub_26:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.3939 - F1: 0.3889
sub_29:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.3125 - F1: 0.3016
sub_8:Test (Best Model) - Loss: 0.7313 - Accuracy: 0.3438 - F1: 0.3273
sub_3:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.2188 - F1: 0.2180
sub_7:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4062 - F1: 0.4057
sub_1:Test (Best Model) - Loss: 0.7556 - Accuracy: 0.1562 - F1: 0.1488
sub_9:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6875 - F1: 0.6667
sub_21:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5625 - F1: 0.5333
sub_14:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.6562 - F1: 0.6102
sub_23:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5758 - F1: 0.5417
sub_22:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5312 - F1: 0.5077
sub_13:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.3750 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.4062 - F1: 0.4057
sub_28:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.3750 - F1: 0.3750
sub_17:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.3333 - F1: 0.3327
sub_12:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.3750 - F1: 0.3074
sub_24:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5312 - F1: 0.5271
sub_19:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.6562 - F1: 0.6532
sub_11:Test (Best Model) - Loss: 0.7471 - Accuracy: 0.2121 - F1: 0.2114
sub_10:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.5938 - F1: 0.5901
sub_29:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4375 - F1: 0.3455
sub_15:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5000 - F1: 0.4667
sub_18:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6061 - F1: 0.5815
sub_26:Test (Best Model) - Loss: 0.7251 - Accuracy: 0.3030 - F1: 0.3005
sub_20:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5312 - F1: 0.5271
sub_6:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.5000 - F1: 0.4818
sub_27:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4848 - F1: 0.4772
sub_16:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.4375 - F1: 0.3766
sub_7:Test (Best Model) - Loss: 0.7408 - Accuracy: 0.2812 - F1: 0.2633
sub_3:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4848 - F1: 0.4527
sub_21:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4688 - F1: 0.3976
sub_28:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4062 - F1: 0.3914
sub_25:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4848 - F1: 0.4829
sub_14:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.5625 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.6250 - F1: 0.5362
sub_1:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4688 - F1: 0.4682
sub_4:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4848 - F1: 0.4829
sub_24:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5625 - F1: 0.5625
sub_17:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4848 - F1: 0.4772
sub_2:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4062 - F1: 0.4010
sub_26:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.4375 - F1: 0.4286
sub_11:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5152 - F1: 0.5147
sub_29:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.3750 - F1: 0.3725
sub_27:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6061 - F1: 0.5926
sub_20:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5312 - F1: 0.5308
sub_16:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.4375 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5312 - F1: 0.5077
sub_23:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5758 - F1: 0.5658
sub_9:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.7812 - F1: 0.7703
sub_6:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.3636 - F1: 0.3541
sub_22:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3939 - F1: 0.3934
sub_18:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.3750 - F1: 0.3750
sub_8:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5625 - F1: 0.5466
sub_19:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.7188 - F1: 0.7117
sub_3:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.5152 - F1: 0.4545
sub_28:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6562 - F1: 0.6476
sub_21:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.4062 - F1: 0.4010
sub_7:Test (Best Model) - Loss: 0.7327 - Accuracy: 0.3438 - F1: 0.3431
sub_12:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.6667 - F1: 0.6667
sub_17:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6364 - F1: 0.6192
sub_14:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7188 - F1: 0.7117
sub_15:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5938 - F1: 0.5901
sub_4:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6364 - F1: 0.6360
sub_1:Test (Best Model) - Loss: 0.7383 - Accuracy: 0.1562 - F1: 0.1488
sub_26:Test (Best Model) - Loss: 0.7091 - Accuracy: 0.3438 - F1: 0.3273
sub_2:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5938 - F1: 0.5393
sub_11:Test (Best Model) - Loss: 0.7053 - Accuracy: 0.4848 - F1: 0.4829
sub_5:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5312 - F1: 0.5195
sub_29:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.7188 - F1: 0.7046
sub_27:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5758 - F1: 0.5722
sub_23:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6501 - Accuracy: 0.7500 - F1: 0.7460
sub_6:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5758 - F1: 0.5658
sub_28:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.3438 - F1: 0.3431
sub_22:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.4242 - F1: 0.4046
sub_8:Test (Best Model) - Loss: 0.7145 - Accuracy: 0.4375 - F1: 0.4286
sub_25:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4242 - F1: 0.4242
sub_24:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5000 - F1: 0.5000
sub_17:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5758 - F1: 0.5722
sub_18:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.5312 - F1: 0.5077
sub_13:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.6364 - F1: 0.6360
sub_12:Test (Best Model) - Loss: 0.7058 - Accuracy: 0.4848 - F1: 0.4848
sub_7:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.3438 - F1: 0.3431
sub_15:Test (Best Model) - Loss: 0.7072 - Accuracy: 0.4375 - F1: 0.4286
sub_21:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.5938 - F1: 0.5589
sub_4:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.5000 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.7500 - F1: 0.7333
sub_11:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5152 - F1: 0.5111
sub_3:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4242 - F1: 0.4046
sub_2:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.3438 - F1: 0.3108
sub_1:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.5152 - F1: 0.5038
sub_19:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.3438 - F1: 0.3379
sub_20:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.3125 - F1: 0.3016
sub_26:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 0.7109 - Accuracy: 0.4062 - F1: 0.3764
sub_29:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.6364 - F1: 0.6333
sub_5:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6250 - F1: 0.6113
sub_23:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6250 - F1: 0.6113
sub_8:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5312 - F1: 0.5077
sub_6:Test (Best Model) - Loss: 0.6989 - Accuracy: 0.4242 - F1: 0.4242
sub_9:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.7500 - F1: 0.7091
sub_22:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7576 - F1: 0.7519
sub_24:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.5625 - F1: 0.5333
sub_17:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.6364 - F1: 0.6333
sub_1:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6667 - F1: 0.6330
sub_7:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.5000 - F1: 0.4980
sub_18:Test (Best Model) - Loss: 0.7097 - Accuracy: 0.3750 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.4688 - F1: 0.4555
sub_4:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5758 - F1: 0.5722
sub_19:Test (Best Model) - Loss: 0.7430 - Accuracy: 0.1875 - F1: 0.1875
sub_12:Test (Best Model) - Loss: 0.7039 - Accuracy: 0.4545 - F1: 0.4417
sub_13:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4545 - F1: 0.4500
sub_21:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.3125 - F1: 0.3098
sub_11:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5758 - F1: 0.5417
sub_3:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.3030 - F1: 0.2792
sub_20:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.3750 - F1: 0.3651
sub_16:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6562 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 0.7397 - Accuracy: 0.3125 - F1: 0.2667
sub_29:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.4062 - F1: 0.3914
sub_27:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.6364 - F1: 0.6333
sub_23:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.4375 - F1: 0.4353
sub_5:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.3750 - F1: 0.3725
sub_6:Test (Best Model) - Loss: 0.7412 - Accuracy: 0.1818 - F1: 0.1788
sub_10:Test (Best Model) - Loss: 0.7240 - Accuracy: 0.3750 - F1: 0.3725
sub_28:Test (Best Model) - Loss: 0.7345 - Accuracy: 0.3750 - F1: 0.3074
sub_1:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5758 - F1: 0.5754
sub_22:Test (Best Model) - Loss: 0.7239 - Accuracy: 0.3030 - F1: 0.3030
sub_8:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.5000 - F1: 0.4459
sub_2:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5625 - F1: 0.5608
sub_17:Test (Best Model) - Loss: 0.6842 - Accuracy: 0.6364 - F1: 0.6333
sub_14:Test (Best Model) - Loss: 0.7273 - Accuracy: 0.3125 - F1: 0.3125
sub_11:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.1818 - F1: 0.1788
sub_25:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5000 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4688 - F1: 0.4555
sub_4:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.3939 - F1: 0.3452
sub_13:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4242 - F1: 0.4046
sub_12:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.2727 - F1: 0.2721
sub_19:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4375 - F1: 0.4000
sub_9:Test (Best Model) - Loss: 0.7276 - Accuracy: 0.2812 - F1: 0.2805
sub_21:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.3125 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.6364 - F1: 0.6071
sub_15:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.4062 - F1: 0.3552
sub_18:Test (Best Model) - Loss: 0.7381 - Accuracy: 0.1250 - F1: 0.1111
sub_26:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4848 - F1: 0.4527
sub_7:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.3438 - F1: 0.3273
sub_29:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.3125 - F1: 0.3016
sub_23:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.3125 - F1: 0.2667
sub_6:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.2812 - F1: 0.2805
sub_1:Test (Best Model) - Loss: 0.7142 - Accuracy: 0.3030 - F1: 0.2595
sub_11:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4242 - F1: 0.4221
sub_5:Test (Best Model) - Loss: 0.7488 - Accuracy: 0.1562 - F1: 0.1488
sub_22:Test (Best Model) - Loss: 0.7097 - Accuracy: 0.3333 - F1: 0.3327
sub_8:Test (Best Model) - Loss: 0.7255 - Accuracy: 0.2500 - F1: 0.2500
sub_2:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6364 - F1: 0.6071
sub_17:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4848 - F1: 0.4527
sub_28:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4688 - F1: 0.4555
sub_14:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.3125 - F1: 0.2381
sub_25:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.4062 - F1: 0.3914
sub_4:Test (Best Model) - Loss: 0.7167 - Accuracy: 0.4242 - F1: 0.4157
sub_13:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.2727 - F1: 0.2143
sub_20:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.4375 - F1: 0.4353
sub_12:Test (Best Model) - Loss: 0.7192 - Accuracy: 0.3939 - F1: 0.3889
sub_27:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.5938 - F1: 0.5836
sub_19:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5938 - F1: 0.5589
sub_3:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3030 - F1: 0.3005
sub_21:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.4062 - F1: 0.4010
sub_24:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5938 - F1: 0.5733
sub_15:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.3125 - F1: 0.3098
sub_29:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.4545 - F1: 0.4540
sub_9:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4375 - F1: 0.3766
sub_10:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.3750 - F1: 0.3651
sub_6:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5152 - F1: 0.5111
sub_23:Test (Best Model) - Loss: 0.7120 - Accuracy: 0.4062 - F1: 0.4010
sub_18:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.5312 - F1: 0.5271
sub_22:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7500 - F1: 0.7409
sub_1:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4242 - F1: 0.4221
sub_11:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6667 - F1: 0.6159
sub_8:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.7188 - F1: 0.7185
sub_17:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.5938 - F1: 0.5836
sub_13:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5938 - F1: 0.5934
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.4848 - F1: 0.4772
sub_14:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5938 - F1: 0.5836
sub_5:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.3125 - F1: 0.3098
sub_28:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.6250 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.3939 - F1: 0.3889
sub_27:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4062 - F1: 0.4010
sub_25:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4688 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5625 - F1: 0.5556
sub_19:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5000 - F1: 0.4459
sub_16:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.7812 - F1: 0.7810
sub_15:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5625 - F1: 0.5608
sub_29:Test (Best Model) - Loss: 0.7118 - Accuracy: 0.3636 - F1: 0.3541
sub_22:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.3438 - F1: 0.3431
sub_24:Test (Best Model) - Loss: 0.7153 - Accuracy: 0.3750 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4375 - F1: 0.4375
sub_3:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.6061 - F1: 0.6061
sub_21:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4062 - F1: 0.4010
sub_23:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.6667 - F1: 0.6459
sub_8:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5312 - F1: 0.5195
sub_26:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.4062 - F1: 0.4010
sub_1:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4062 - F1: 0.4057
sub_10:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.7576 - F1: 0.7556
sub_18:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.6562 - F1: 0.6559
sub_17:Test (Best Model) - Loss: 0.7004 - Accuracy: 0.4062 - F1: 0.4010
sub_20:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4545 - F1: 0.4288
sub_5:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.5312 - F1: 0.5308
sub_9:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.4980
sub_14:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6800 - Accuracy: 0.6250 - F1: 0.5844
sub_4:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.6061 - F1: 0.6046
sub_2:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.4545 - F1: 0.4500
sub_12:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6250 - F1: 0.6190
sub_22:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.6562 - F1: 0.6390
sub_16:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.3750 - F1: 0.3522
sub_6:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.3636 - F1: 0.3419
sub_19:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4688 - F1: 0.4421
sub_28:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5938 - F1: 0.5135
sub_24:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.2812 - F1: 0.2805
sub_3:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5758 - F1: 0.5754
sub_23:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4545 - F1: 0.4500
sub_7:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.3438 - F1: 0.3431
sub_29:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6667 - F1: 0.6459
sub_8:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5000 - F1: 0.4818
sub_18:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.3750 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.7050 - Accuracy: 0.3333 - F1: 0.3177
sub_21:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5312 - F1: 0.5271
sub_1:Test (Best Model) - Loss: 0.7092 - Accuracy: 0.4688 - F1: 0.4682
sub_10:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4848 - F1: 0.4848
sub_26:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5000 - F1: 0.4980
sub_4:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5152 - F1: 0.5111
sub_13:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.1875 - F1: 0.1843
sub_14:Test (Best Model) - Loss: 0.7448 - Accuracy: 0.3438 - F1: 0.3108
sub_5:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.4375 - F1: 0.4375
sub_9:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.4375 - F1: 0.4353
sub_12:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6562 - F1: 0.6532
sub_23:Test (Best Model) - Loss: 0.7527 - Accuracy: 0.2121 - F1: 0.2114
sub_15:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5625 - F1: 0.5152
sub_17:Test (Best Model) - Loss: 0.7081 - Accuracy: 0.4375 - F1: 0.4375
sub_3:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.7879 - F1: 0.7847
sub_28:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5938 - F1: 0.5901
sub_22:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.8438 - F1: 0.8424
sub_19:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.3438 - F1: 0.3273
sub_6:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.3030 - F1: 0.3005
sub_25:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5938 - F1: 0.5733
sub_20:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4848 - F1: 0.4672
sub_8:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.3750 - F1: 0.3522
sub_24:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4062 - F1: 0.3914
sub_18:Test (Best Model) - Loss: 0.7214 - Accuracy: 0.3750 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.4688 - F1: 0.4682
sub_7:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.3438 - F1: 0.3379
sub_29:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6970 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4848 - F1: 0.4848
sub_11:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.2424 - F1: 0.2165
sub_10:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.5455 - F1: 0.5438
sub_13:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5625 - F1: 0.5625
sub_1:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.4062 - F1: 0.4010
sub_26:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.5312 - F1: 0.5271
sub_15:Test (Best Model) - Loss: 0.7346 - Accuracy: 0.2812 - F1: 0.2805
sub_28:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.3125 - F1: 0.2667
sub_3:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6667 - F1: 0.6553
sub_17:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5312 - F1: 0.5308
sub_19:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.5312 - F1: 0.5308
sub_9:Test (Best Model) - Loss: 0.7351 - Accuracy: 0.2812 - F1: 0.2805
sub_27:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5312 - F1: 0.5308
sub_12:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5312 - F1: 0.5308
sub_6:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.4848 - F1: 0.4848
sub_22:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5625 - F1: 0.5625
sub_23:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.4848 - F1: 0.4848
sub_14:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4062 - F1: 0.4010
sub_20:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6364 - F1: 0.6333
sub_4:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4242 - F1: 0.4242
sub_8:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.7812 - F1: 0.7793
sub_29:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.4242 - F1: 0.4046
sub_18:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.7188 - F1: 0.7163
sub_7:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6875 - F1: 0.6863
sub_25:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.4688 - F1: 0.4682
sub_21:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6875 - F1: 0.6364
sub_13:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7500 - F1: 0.7409
sub_11:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.7879 - F1: 0.7847
sub_26:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.5312 - F1: 0.5308
sub_10:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6970 - F1: 0.6944
sub_9:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5000 - F1: 0.4980
sub_15:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.8438 - F1: 0.8424
sub_12:Test (Best Model) - Loss: 0.7300 - Accuracy: 0.3750 - F1: 0.3651
sub_5:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.3750 - F1: 0.3750
sub_24:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.7500 - F1: 0.7490
sub_17:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.4688 - F1: 0.4555
sub_23:Test (Best Model) - Loss: 0.6414 - Accuracy: 0.7879 - F1: 0.7806
sub_1:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6562 - F1: 0.6559
sub_14:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4688 - F1: 0.4640
sub_27:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6250 - F1: 0.6000
sub_6:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6061 - F1: 0.6002
sub_18:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.6250 - F1: 0.6190
sub_20:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6970 - F1: 0.6967
sub_25:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4375 - F1: 0.4286
sub_2:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.7576 - F1: 0.7462
sub_7:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5625 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 0.7078 - Accuracy: 0.4545 - F1: 0.4540
sub_8:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.3125 - F1: 0.3098
sub_4:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.4848 - F1: 0.4772
sub_9:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5938 - F1: 0.5934
sub_16:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.4688 - F1: 0.4682
sub_1:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.8438 - F1: 0.8359
sub_5:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7500 - F1: 0.7333
sub_25:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.6250 - F1: 0.6250
sub_20:Test (Best Model) - Loss: 0.7514 - Accuracy: 0.2727 - F1: 0.2556
sub_5:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5938 - F1: 0.5934
sub_25:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5312 - F1: 0.5308
sub_25:Test (Best Model) - Loss: 0.7319 - Accuracy: 0.2500 - F1: 0.2381

=== Summary Results ===

acc: 49.44 ± 2.94
F1: 48.20 ± 2.99
acc-in: 49.49 ± 4.55
F1-in: 47.80 ± 4.65
