lr: 1e-06
sub_16:Test (Best Model) - Loss: 0.4705 - Accuracy: 0.8750 - F1: 0.8750
sub_25:Test (Best Model) - Loss: 0.7285 - Accuracy: 0.5455 - F1: 0.4995
sub_12:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.6875 - F1: 0.6863
sub_11:Test (Best Model) - Loss: 0.4991 - Accuracy: 0.7576 - F1: 0.7519
sub_20:Test (Best Model) - Loss: 0.3411 - Accuracy: 0.9062 - F1: 0.9062
sub_3:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.3643 - Accuracy: 0.9688 - F1: 0.9685
sub_1:Test (Best Model) - Loss: 0.2600 - Accuracy: 0.9688 - F1: 0.9685
sub_9:Test (Best Model) - Loss: 0.2632 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.4738 - Accuracy: 0.8750 - F1: 0.8730
sub_19:Test (Best Model) - Loss: 0.1642 - Accuracy: 0.9375 - F1: 0.9373
sub_22:Test (Best Model) - Loss: 0.3720 - Accuracy: 0.9375 - F1: 0.9373
sub_17:Test (Best Model) - Loss: 0.4073 - Accuracy: 0.8182 - F1: 0.8139
sub_5:Test (Best Model) - Loss: 0.7789 - Accuracy: 0.5000 - F1: 0.4182
sub_15:Test (Best Model) - Loss: 0.2338 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3248 - Accuracy: 0.9091 - F1: 0.9091
sub_27:Test (Best Model) - Loss: 0.4073 - Accuracy: 0.8182 - F1: 0.8139
sub_2:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.6061 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.1203 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.9898 - Accuracy: 0.4688 - F1: 0.3637
sub_6:Test (Best Model) - Loss: 0.4310 - Accuracy: 0.8750 - F1: 0.8704
sub_14:Test (Best Model) - Loss: 0.9881 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.7625 - Accuracy: 0.4688 - F1: 0.4421
sub_10:Test (Best Model) - Loss: 0.4504 - Accuracy: 0.8438 - F1: 0.8436
sub_28:Test (Best Model) - Loss: 0.4314 - Accuracy: 0.8125 - F1: 0.8000
sub_18:Test (Best Model) - Loss: 0.4735 - Accuracy: 0.8788 - F1: 0.8787
sub_7:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.7957 - Accuracy: 0.4375 - F1: 0.3455
sub_29:Test (Best Model) - Loss: 0.8742 - Accuracy: 0.3750 - F1: 0.3333
sub_25:Test (Best Model) - Loss: 0.8240 - Accuracy: 0.4242 - F1: 0.4242
sub_12:Test (Best Model) - Loss: 0.2682 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.4688 - F1: 0.4640
sub_20:Test (Best Model) - Loss: 0.3618 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.1180 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.6061 - F1: 0.5460
sub_22:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6250 - F1: 0.5636
sub_3:Test (Best Model) - Loss: 0.9431 - Accuracy: 0.2188 - F1: 0.2118
sub_15:Test (Best Model) - Loss: 0.3819 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.2313 - Accuracy: 0.9688 - F1: 0.9685
sub_26:Test (Best Model) - Loss: 0.3589 - Accuracy: 0.8788 - F1: 0.8787
sub_24:Test (Best Model) - Loss: 0.2155 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.4576 - Accuracy: 0.7576 - F1: 0.7462
sub_12:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.6875 - F1: 0.6364
sub_9:Test (Best Model) - Loss: 0.3419 - Accuracy: 0.8438 - F1: 0.8398
sub_21:Test (Best Model) - Loss: 1.1279 - Accuracy: 0.2812 - F1: 0.2805
sub_20:Test (Best Model) - Loss: 0.8802 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 0.3606 - Accuracy: 0.8750 - F1: 0.8667
sub_16:Test (Best Model) - Loss: 0.7977 - Accuracy: 0.5625 - F1: 0.5466
sub_29:Test (Best Model) - Loss: 0.4818 - Accuracy: 0.6875 - F1: 0.6135
sub_2:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.5758 - F1: 0.5658
sub_7:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.4934 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.2636 - Accuracy: 0.9091 - F1: 0.9060
sub_10:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.6250 - F1: 0.5362
sub_17:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.7576 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.3645 - Accuracy: 0.9375 - F1: 0.9352
sub_25:Test (Best Model) - Loss: 0.3217 - Accuracy: 0.8485 - F1: 0.8462
sub_28:Test (Best Model) - Loss: 0.7943 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.5165 - Accuracy: 0.7576 - F1: 0.7519
sub_5:Test (Best Model) - Loss: 0.4435 - Accuracy: 0.9062 - F1: 0.9062
sub_6:Test (Best Model) - Loss: 0.4343 - Accuracy: 0.7812 - F1: 0.7703
sub_14:Test (Best Model) - Loss: 1.2267 - Accuracy: 0.4688 - F1: 0.3637
sub_20:Test (Best Model) - Loss: 0.4374 - Accuracy: 0.7812 - F1: 0.7758
sub_22:Test (Best Model) - Loss: 0.3027 - Accuracy: 0.8438 - F1: 0.8303
sub_13:Test (Best Model) - Loss: 0.4210 - Accuracy: 0.8438 - F1: 0.8303
sub_1:Test (Best Model) - Loss: 0.4132 - Accuracy: 0.8750 - F1: 0.8704
sub_12:Test (Best Model) - Loss: 0.5717 - Accuracy: 0.7500 - F1: 0.7409
sub_23:Test (Best Model) - Loss: 0.2791 - Accuracy: 0.9394 - F1: 0.9380
sub_11:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.7273 - F1: 0.6997
sub_7:Test (Best Model) - Loss: 0.5681 - Accuracy: 0.6875 - F1: 0.6825
sub_16:Test (Best Model) - Loss: 0.4546 - Accuracy: 0.8125 - F1: 0.8057
sub_17:Test (Best Model) - Loss: 0.2380 - Accuracy: 0.9091 - F1: 0.9060
sub_28:Test (Best Model) - Loss: 0.8808 - Accuracy: 0.6562 - F1: 0.5594
sub_9:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.6562 - F1: 0.6476
sub_19:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.6562 - F1: 0.6267
sub_15:Test (Best Model) - Loss: 0.4631 - Accuracy: 0.8125 - F1: 0.7922
sub_27:Test (Best Model) - Loss: 0.2380 - Accuracy: 0.9091 - F1: 0.9060
sub_21:Test (Best Model) - Loss: 0.5682 - Accuracy: 0.6875 - F1: 0.6667
sub_20:Test (Best Model) - Loss: 0.9381 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.6422 - Accuracy: 0.6250 - F1: 0.6000
sub_14:Test (Best Model) - Loss: 1.1022 - Accuracy: 0.2188 - F1: 0.1992
sub_2:Test (Best Model) - Loss: 0.4880 - Accuracy: 0.8788 - F1: 0.8759
sub_24:Test (Best Model) - Loss: 0.3862 - Accuracy: 0.8750 - F1: 0.8667
sub_22:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.4014 - Accuracy: 0.8750 - F1: 0.8704
sub_16:Test (Best Model) - Loss: 1.1766 - Accuracy: 0.3750 - F1: 0.2727
sub_26:Test (Best Model) - Loss: 0.2474 - Accuracy: 0.9697 - F1: 0.9692
sub_4:Test (Best Model) - Loss: 0.4484 - Accuracy: 0.7879 - F1: 0.7746
sub_8:Test (Best Model) - Loss: 0.3118 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.3650 - Accuracy: 0.9062 - F1: 0.9039
sub_23:Test (Best Model) - Loss: 0.3769 - Accuracy: 0.8182 - F1: 0.8036
sub_25:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.5152 - F1: 0.5147
sub_21:Test (Best Model) - Loss: 0.9032 - Accuracy: 0.4062 - F1: 0.3914
sub_11:Test (Best Model) - Loss: 0.5113 - Accuracy: 0.7273 - F1: 0.6997
sub_29:Test (Best Model) - Loss: 0.3262 - Accuracy: 0.9062 - F1: 0.9039
sub_12:Test (Best Model) - Loss: 1.0712 - Accuracy: 0.3125 - F1: 0.2874
sub_17:Test (Best Model) - Loss: 0.4514 - Accuracy: 0.8485 - F1: 0.8462
sub_1:Test (Best Model) - Loss: 0.2923 - Accuracy: 0.9375 - F1: 0.9352
sub_10:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.6875 - F1: 0.6364
sub_6:Test (Best Model) - Loss: 0.3178 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.8394 - Accuracy: 0.4848 - F1: 0.3718
sub_7:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.2812 - F1: 0.2195
sub_14:Test (Best Model) - Loss: 2.3138 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.1885 - Accuracy: 0.9697 - F1: 0.9692
sub_27:Test (Best Model) - Loss: 0.4514 - Accuracy: 0.8485 - F1: 0.8462
sub_19:Test (Best Model) - Loss: 1.5440 - Accuracy: 0.4375 - F1: 0.3455
sub_15:Test (Best Model) - Loss: 0.1999 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.9257 - Accuracy: 0.4062 - F1: 0.2889
sub_5:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.7188 - F1: 0.7117
sub_25:Test (Best Model) - Loss: 1.0087 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7709 - Accuracy: 0.3750 - F1: 0.3522
sub_29:Test (Best Model) - Loss: 1.0298 - Accuracy: 0.4062 - F1: 0.2889
sub_11:Test (Best Model) - Loss: 1.5014 - Accuracy: 0.4242 - F1: 0.2979
sub_3:Test (Best Model) - Loss: 0.5392 - Accuracy: 0.7188 - F1: 0.7163
sub_1:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6364 - F1: 0.6071
sub_28:Test (Best Model) - Loss: 0.3914 - Accuracy: 0.9375 - F1: 0.9373
sub_9:Test (Best Model) - Loss: 0.2889 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 1.0623 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.4236 - Accuracy: 0.8485 - F1: 0.8433
sub_5:Test (Best Model) - Loss: 1.1889 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 1.6676 - Accuracy: 0.0625 - F1: 0.0588
sub_23:Test (Best Model) - Loss: 0.4014 - Accuracy: 0.8788 - F1: 0.8787
sub_2:Test (Best Model) - Loss: 0.3067 - Accuracy: 0.9697 - F1: 0.9692
sub_24:Test (Best Model) - Loss: 0.4187 - Accuracy: 0.8750 - F1: 0.8667
sub_11:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.6667 - F1: 0.6654
sub_10:Test (Best Model) - Loss: 1.5128 - Accuracy: 0.4375 - F1: 0.3043
sub_4:Test (Best Model) - Loss: 0.3581 - Accuracy: 0.8788 - F1: 0.8759
sub_8:Test (Best Model) - Loss: 0.6003 - Accuracy: 0.7188 - F1: 0.6946
sub_3:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.3438 - F1: 0.2558
sub_16:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.8317 - Accuracy: 0.4062 - F1: 0.2889
sub_6:Test (Best Model) - Loss: 1.6861 - Accuracy: 0.4062 - F1: 0.2889
sub_14:Test (Best Model) - Loss: 0.4132 - Accuracy: 0.9375 - F1: 0.9352
sub_28:Test (Best Model) - Loss: 1.7283 - Accuracy: 0.4375 - F1: 0.3043
sub_12:Test (Best Model) - Loss: 0.4161 - Accuracy: 0.8485 - F1: 0.8433
sub_18:Test (Best Model) - Loss: 1.5671 - Accuracy: 0.4545 - F1: 0.3125
sub_13:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.6875 - F1: 0.6825
sub_23:Test (Best Model) - Loss: 1.2395 - Accuracy: 0.3636 - F1: 0.2667
sub_20:Test (Best Model) - Loss: 0.3675 - Accuracy: 0.9375 - F1: 0.9365
sub_2:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.4545 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 1.0637 - Accuracy: 0.1875 - F1: 0.1746
sub_8:Test (Best Model) - Loss: 1.5050 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.6875 - F1: 0.6825
sub_26:Test (Best Model) - Loss: 0.4084 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.7946 - Accuracy: 0.5625 - F1: 0.4167
sub_16:Test (Best Model) - Loss: 0.8913 - Accuracy: 0.5312 - F1: 0.4684
sub_7:Test (Best Model) - Loss: 0.7562 - Accuracy: 0.4688 - F1: 0.3637
sub_22:Test (Best Model) - Loss: 0.8740 - Accuracy: 0.4242 - F1: 0.4221
sub_19:Test (Best Model) - Loss: 0.4004 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.4887 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.6061 - F1: 0.5926
sub_20:Test (Best Model) - Loss: 1.0140 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 1.5567 - Accuracy: 0.1515 - F1: 0.1316
sub_12:Test (Best Model) - Loss: 0.7793 - Accuracy: 0.5758 - F1: 0.4978
sub_29:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 1.0850 - Accuracy: 0.2188 - F1: 0.2118
sub_27:Test (Best Model) - Loss: 0.7485 - Accuracy: 0.6061 - F1: 0.5926
sub_4:Test (Best Model) - Loss: 0.7662 - Accuracy: 0.4545 - F1: 0.3543
sub_19:Test (Best Model) - Loss: 1.2958 - Accuracy: 0.0312 - F1: 0.0303
sub_28:Test (Best Model) - Loss: 0.7626 - Accuracy: 0.4375 - F1: 0.3043
sub_22:Test (Best Model) - Loss: 1.1178 - Accuracy: 0.2727 - F1: 0.2667
sub_15:Test (Best Model) - Loss: 0.2662 - Accuracy: 0.9688 - F1: 0.9685
sub_5:Test (Best Model) - Loss: 0.1588 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.9925 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.3030 - F1: 0.2326
sub_9:Test (Best Model) - Loss: 0.3317 - Accuracy: 0.9062 - F1: 0.9054
sub_13:Test (Best Model) - Loss: 1.0936 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 1.2674 - Accuracy: 0.4242 - F1: 0.2979
sub_20:Test (Best Model) - Loss: 0.8618 - Accuracy: 0.4375 - F1: 0.3455
sub_3:Test (Best Model) - Loss: 1.1011 - Accuracy: 0.3030 - F1: 0.2595
sub_1:Test (Best Model) - Loss: 0.2671 - Accuracy: 0.9697 - F1: 0.9692
sub_18:Test (Best Model) - Loss: 1.3144 - Accuracy: 0.4062 - F1: 0.2889
sub_23:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.8125 - F1: 0.8095
sub_10:Test (Best Model) - Loss: 0.5989 - Accuracy: 0.7812 - F1: 0.7703
sub_27:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.3030 - F1: 0.2326
sub_16:Test (Best Model) - Loss: 0.8198 - Accuracy: 0.4375 - F1: 0.3455
sub_28:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.0000 - F1: 0.0000
sub_8:Test (Best Model) - Loss: 1.4987 - Accuracy: 0.4062 - F1: 0.2889
sub_22:Test (Best Model) - Loss: 0.7237 - Accuracy: 0.6364 - F1: 0.6278
sub_26:Test (Best Model) - Loss: 0.9464 - Accuracy: 0.3438 - F1: 0.3431
sub_12:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.9091 - F1: 0.9060
sub_20:Test (Best Model) - Loss: 0.3759 - Accuracy: 0.8485 - F1: 0.8485
sub_25:Test (Best Model) - Loss: 1.0616 - Accuracy: 0.1875 - F1: 0.1843
sub_29:Test (Best Model) - Loss: 0.2190 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.3941 - Accuracy: 0.8485 - F1: 0.8390
sub_14:Test (Best Model) - Loss: 0.9996 - Accuracy: 0.2812 - F1: 0.2805
sub_23:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.0625 - F1: 0.0625
sub_6:Test (Best Model) - Loss: 0.4516 - Accuracy: 0.8485 - F1: 0.8462
sub_2:Test (Best Model) - Loss: 0.3516 - Accuracy: 0.9062 - F1: 0.9039
sub_19:Test (Best Model) - Loss: 0.1477 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.6875 - F1: 0.6364
sub_16:Test (Best Model) - Loss: 0.2710 - Accuracy: 0.9688 - F1: 0.9685
sub_4:Test (Best Model) - Loss: 0.3365 - Accuracy: 0.8788 - F1: 0.8731
sub_7:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.8130 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3941 - Accuracy: 0.8485 - F1: 0.8390
sub_21:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6562 - F1: 0.6390
sub_29:Test (Best Model) - Loss: 0.5735 - Accuracy: 0.5938 - F1: 0.5589
sub_14:Test (Best Model) - Loss: 1.0110 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.9969 - Accuracy: 0.3939 - F1: 0.3797
sub_28:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.8438 - F1: 0.8303
sub_19:Test (Best Model) - Loss: 0.7999 - Accuracy: 0.4375 - F1: 0.3043
sub_18:Test (Best Model) - Loss: 0.8259 - Accuracy: 0.3438 - F1: 0.3431
sub_1:Test (Best Model) - Loss: 0.8922 - Accuracy: 0.3333 - F1: 0.2798
sub_11:Test (Best Model) - Loss: 0.7963 - Accuracy: 0.4545 - F1: 0.4500
sub_8:Test (Best Model) - Loss: 0.5284 - Accuracy: 0.6562 - F1: 0.5594
sub_22:Test (Best Model) - Loss: 1.0707 - Accuracy: 0.4545 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 1.0642 - Accuracy: 0.5455 - F1: 0.3529
sub_12:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.6061 - F1: 0.5662
sub_3:Test (Best Model) - Loss: 0.4983 - Accuracy: 0.6970 - F1: 0.6413
sub_25:Test (Best Model) - Loss: 0.1548 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.9128 - Accuracy: 0.4688 - F1: 0.4231
sub_24:Test (Best Model) - Loss: 0.4744 - Accuracy: 0.8438 - F1: 0.8424
sub_7:Test (Best Model) - Loss: 0.9891 - Accuracy: 0.3438 - F1: 0.3379
sub_14:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.7188 - F1: 0.7117
sub_9:Test (Best Model) - Loss: 0.4982 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.2878 - Accuracy: 0.8750 - F1: 0.8704
sub_13:Test (Best Model) - Loss: 1.3965 - Accuracy: 0.4545 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 0.8125 - Accuracy: 0.5455 - F1: 0.4762
sub_28:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.4688 - F1: 0.3637
sub_23:Test (Best Model) - Loss: 0.6739 - Accuracy: 0.4688 - F1: 0.3976
sub_11:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.4545 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 0.9224 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.4545 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 1.9840 - Accuracy: 0.4062 - F1: 0.2889
sub_5:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7188 - F1: 0.7046
sub_29:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 0.3632 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.8125 - Accuracy: 0.5455 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.5455 - F1: 0.4457
sub_21:Test (Best Model) - Loss: 0.9870 - Accuracy: 0.4062 - F1: 0.2889
sub_19:Test (Best Model) - Loss: 0.3860 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.3268 - Accuracy: 0.8438 - F1: 0.8303
sub_8:Test (Best Model) - Loss: 0.3380 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.5006 - Accuracy: 0.6667 - F1: 0.6459
sub_10:Test (Best Model) - Loss: 0.4295 - Accuracy: 0.9062 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.4883 - Accuracy: 0.8125 - F1: 0.8118
sub_22:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.4242 - F1: 0.3365
sub_25:Test (Best Model) - Loss: 0.5499 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.2441 - Accuracy: 0.9697 - F1: 0.9692
sub_13:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.6061 - F1: 0.4850
sub_24:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.7188 - F1: 0.6946
sub_6:Test (Best Model) - Loss: 0.7354 - Accuracy: 0.4545 - F1: 0.3543
sub_9:Test (Best Model) - Loss: 0.4406 - Accuracy: 0.8750 - F1: 0.8667
sub_28:Test (Best Model) - Loss: 0.1984 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.6875 - F1: 0.6761
sub_20:Test (Best Model) - Loss: 0.7117 - Accuracy: 0.5455 - F1: 0.4457
sub_16:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 1.1474 - Accuracy: 0.3750 - F1: 0.2727
sub_23:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.4375 - F1: 0.3043
sub_5:Test (Best Model) - Loss: 0.4955 - Accuracy: 0.5625 - F1: 0.5152
sub_2:Test (Best Model) - Loss: 0.4888 - Accuracy: 0.7500 - F1: 0.7490
sub_26:Test (Best Model) - Loss: 0.5542 - Accuracy: 0.6250 - F1: 0.6000
sub_17:Test (Best Model) - Loss: 0.2992 - Accuracy: 0.9697 - F1: 0.9692
sub_15:Test (Best Model) - Loss: 0.2413 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.6364 - F1: 0.5417
sub_24:Test (Best Model) - Loss: 0.7174 - Accuracy: 0.5000 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 1.0796 - Accuracy: 0.4545 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 1.7985 - Accuracy: 0.4545 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 0.4296 - Accuracy: 0.8438 - F1: 0.8436
sub_21:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.6562 - F1: 0.6390
sub_18:Test (Best Model) - Loss: 0.3572 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.4388 - Accuracy: 0.8485 - F1: 0.8479
sub_8:Test (Best Model) - Loss: 0.5817 - Accuracy: 0.5938 - F1: 0.5589
sub_27:Test (Best Model) - Loss: 0.2992 - Accuracy: 0.9697 - F1: 0.9692
sub_19:Test (Best Model) - Loss: 0.7365 - Accuracy: 0.6250 - F1: 0.6113
sub_26:Test (Best Model) - Loss: 0.9351 - Accuracy: 0.4688 - F1: 0.3637
sub_25:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.5938 - F1: 0.5589
sub_1:Test (Best Model) - Loss: 0.8354 - Accuracy: 0.4545 - F1: 0.3125
sub_10:Test (Best Model) - Loss: 0.3759 - Accuracy: 0.9688 - F1: 0.9685
sub_13:Test (Best Model) - Loss: 0.5196 - Accuracy: 0.6970 - F1: 0.6827
sub_24:Test (Best Model) - Loss: 1.1400 - Accuracy: 0.4375 - F1: 0.3043
sub_6:Test (Best Model) - Loss: 0.5078 - Accuracy: 0.8182 - F1: 0.8096
sub_2:Test (Best Model) - Loss: 0.4563 - Accuracy: 0.6250 - F1: 0.6000
sub_16:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.4062 - F1: 0.2889
sub_12:Test (Best Model) - Loss: 0.7936 - Accuracy: 0.5312 - F1: 0.4684
sub_3:Test (Best Model) - Loss: 0.3541 - Accuracy: 0.9091 - F1: 0.9077
sub_28:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.3014 - Accuracy: 0.8788 - F1: 0.8731
sub_29:Test (Best Model) - Loss: 0.8991 - Accuracy: 0.4848 - F1: 0.3265
sub_5:Test (Best Model) - Loss: 0.4022 - Accuracy: 0.8125 - F1: 0.8118
sub_14:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.6875 - F1: 0.6135
sub_22:Test (Best Model) - Loss: 0.5636 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.4848 - F1: 0.3718
sub_23:Test (Best Model) - Loss: 0.5112 - Accuracy: 0.6562 - F1: 0.6390
sub_2:Test (Best Model) - Loss: 0.3108 - Accuracy: 0.9375 - F1: 0.9352
sub_12:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_4:Test (Best Model) - Loss: 0.4049 - Accuracy: 0.7576 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 0.1076 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.6160 - Accuracy: 0.5312 - F1: 0.4684
sub_1:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.3939 - F1: 0.2826
sub_11:Test (Best Model) - Loss: 0.4165 - Accuracy: 0.9091 - F1: 0.9077
sub_6:Test (Best Model) - Loss: 0.5083 - Accuracy: 0.7879 - F1: 0.7871
sub_18:Test (Best Model) - Loss: 1.0956 - Accuracy: 0.3438 - F1: 0.2558
sub_10:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5938 - F1: 0.5135
sub_21:Test (Best Model) - Loss: 1.0859 - Accuracy: 0.4375 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 1.0371 - Accuracy: 0.3438 - F1: 0.2874
sub_7:Test (Best Model) - Loss: 0.3495 - Accuracy: 0.8750 - F1: 0.8745
sub_26:Test (Best Model) - Loss: 0.1717 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.8693 - Accuracy: 0.5758 - F1: 0.4225
sub_12:Test (Best Model) - Loss: 0.7959 - Accuracy: 0.5000 - F1: 0.3333
sub_24:Test (Best Model) - Loss: 0.3997 - Accuracy: 0.8125 - F1: 0.8095
sub_25:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.2336 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.8302 - Accuracy: 0.3125 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.3013 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.6250 - F1: 0.6190
sub_13:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.6364 - F1: 0.6333
sub_28:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.5312 - F1: 0.5308
sub_27:Test (Best Model) - Loss: 0.2336 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.6250 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.4954 - Accuracy: 0.6875 - F1: 0.6761
sub_12:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.9341 - Accuracy: 0.3636 - F1: 0.2993
sub_19:Test (Best Model) - Loss: 0.2645 - Accuracy: 0.9688 - F1: 0.9680
sub_11:Test (Best Model) - Loss: 0.9061 - Accuracy: 0.4848 - F1: 0.4063
sub_23:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.7576 - F1: 0.7273
sub_5:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.5938 - F1: 0.5589
sub_1:Test (Best Model) - Loss: 0.8867 - Accuracy: 0.4375 - F1: 0.3455
sub_4:Test (Best Model) - Loss: 1.1772 - Accuracy: 0.4848 - F1: 0.3718
sub_7:Test (Best Model) - Loss: 0.9673 - Accuracy: 0.4688 - F1: 0.3637
sub_2:Test (Best Model) - Loss: 0.3256 - Accuracy: 0.9697 - F1: 0.9692
sub_3:Test (Best Model) - Loss: 1.0471 - Accuracy: 0.4545 - F1: 0.3125
sub_18:Test (Best Model) - Loss: 0.3334 - Accuracy: 0.8750 - F1: 0.8750
sub_10:Test (Best Model) - Loss: 0.3229 - Accuracy: 0.9394 - F1: 0.9380
sub_16:Test (Best Model) - Loss: 0.4895 - Accuracy: 0.7500 - F1: 0.7229
sub_13:Test (Best Model) - Loss: 0.5528 - Accuracy: 0.6250 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 1.2106 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.6061 - F1: 0.4850
sub_9:Test (Best Model) - Loss: 0.2480 - Accuracy: 0.9375 - F1: 0.9352
sub_11:Test (Best Model) - Loss: 1.4264 - Accuracy: 0.1212 - F1: 0.1081
sub_28:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.5451 - Accuracy: 0.6562 - F1: 0.5883
sub_19:Test (Best Model) - Loss: 0.3938 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.2611 - Accuracy: 0.9697 - F1: 0.9696
sub_26:Test (Best Model) - Loss: 0.3527 - Accuracy: 0.9375 - F1: 0.9365
sub_14:Test (Best Model) - Loss: 0.7719 - Accuracy: 0.6250 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.3307 - Accuracy: 0.8750 - F1: 0.8745
sub_25:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.7188 - F1: 0.6632
sub_17:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6562 - F1: 0.6102
sub_15:Test (Best Model) - Loss: 0.2552 - Accuracy: 0.9688 - F1: 0.9685
sub_24:Test (Best Model) - Loss: 0.4053 - Accuracy: 0.8438 - F1: 0.8436
sub_28:Test (Best Model) - Loss: 0.3522 - Accuracy: 0.9375 - F1: 0.9365
sub_22:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.6875 - F1: 0.6135
sub_5:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.7520 - Accuracy: 0.6364 - F1: 0.6192
sub_16:Test (Best Model) - Loss: 0.7607 - Accuracy: 0.6250 - F1: 0.5362
sub_27:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.6562 - F1: 0.6102
sub_9:Test (Best Model) - Loss: 0.8217 - Accuracy: 0.4375 - F1: 0.3043
sub_8:Test (Best Model) - Loss: 0.4553 - Accuracy: 0.8438 - F1: 0.8359
sub_6:Test (Best Model) - Loss: 1.0876 - Accuracy: 0.2727 - F1: 0.2385
sub_7:Test (Best Model) - Loss: 0.6037 - Accuracy: 0.6250 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 1.0750 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.2874 - Accuracy: 0.8788 - F1: 0.8787
sub_2:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8788 - F1: 0.8731
sub_29:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.7576 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.2991 - Accuracy: 0.9375 - F1: 0.9352
sub_19:Test (Best Model) - Loss: 0.9596 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.5397 - Accuracy: 0.8788 - F1: 0.8731
sub_11:Test (Best Model) - Loss: 0.1751 - Accuracy: 0.9697 - F1: 0.9692
sub_22:Test (Best Model) - Loss: 0.7991 - Accuracy: 0.6875 - F1: 0.6135
sub_26:Test (Best Model) - Loss: 0.3612 - Accuracy: 0.8438 - F1: 0.8303
sub_10:Test (Best Model) - Loss: 0.4657 - Accuracy: 0.6970 - F1: 0.6944
sub_6:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5455 - F1: 0.3529
sub_2:Test (Best Model) - Loss: 0.4678 - Accuracy: 0.7576 - F1: 0.7273
sub_13:Test (Best Model) - Loss: 0.8329 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.3599 - Accuracy: 0.8750 - F1: 0.8750
sub_25:Test (Best Model) - Loss: 0.4627 - Accuracy: 0.7188 - F1: 0.6632
sub_8:Test (Best Model) - Loss: 0.4828 - Accuracy: 0.8750 - F1: 0.8667
sub_17:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6250 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.6116 - Accuracy: 0.7500 - F1: 0.7091
sub_5:Test (Best Model) - Loss: 0.8155 - Accuracy: 0.5625 - F1: 0.4589
sub_18:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.4375 - F1: 0.3766
sub_27:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6250 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.3185 - Accuracy: 0.9091 - F1: 0.9088
sub_15:Test (Best Model) - Loss: 0.3848 - Accuracy: 0.7812 - F1: 0.7519
sub_7:Test (Best Model) - Loss: 0.4879 - Accuracy: 0.8125 - F1: 0.8118
sub_11:Test (Best Model) - Loss: 1.0419 - Accuracy: 0.2121 - F1: 0.2114
sub_3:Test (Best Model) - Loss: 1.0208 - Accuracy: 0.5758 - F1: 0.4225
sub_17:Test (Best Model) - Loss: 1.0501 - Accuracy: 0.3750 - F1: 0.2727
sub_1:Test (Best Model) - Loss: 0.3019 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.6562 - F1: 0.5883
sub_10:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.6061 - F1: 0.5926
sub_4:Test (Best Model) - Loss: 0.3814 - Accuracy: 0.8485 - F1: 0.8433
sub_24:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.5312 - F1: 0.5271
sub_25:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.6250 - F1: 0.5000
sub_27:Test (Best Model) - Loss: 1.0501 - Accuracy: 0.3750 - F1: 0.2727
sub_2:Test (Best Model) - Loss: 1.0945 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.5049 - Accuracy: 0.6562 - F1: 0.5594
sub_8:Test (Best Model) - Loss: 0.5694 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.6364 - F1: 0.5909
sub_5:Test (Best Model) - Loss: 0.3818 - Accuracy: 0.8125 - F1: 0.7922
sub_19:Test (Best Model) - Loss: 0.4939 - Accuracy: 0.6562 - F1: 0.5594
sub_17:Test (Best Model) - Loss: 0.7426 - Accuracy: 0.5000 - F1: 0.4182
sub_13:Test (Best Model) - Loss: 1.4354 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.3526 - Accuracy: 0.8750 - F1: 0.8667
sub_24:Test (Best Model) - Loss: 1.0096 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.5312 - F1: 0.4910
sub_27:Test (Best Model) - Loss: 0.7426 - Accuracy: 0.5000 - F1: 0.4182
sub_7:Test (Best Model) - Loss: 0.8264 - Accuracy: 0.5625 - F1: 0.4167
sub_3:Test (Best Model) - Loss: 0.8961 - Accuracy: 0.5455 - F1: 0.4058
sub_1:Test (Best Model) - Loss: 0.4012 - Accuracy: 0.6875 - F1: 0.6135
sub_21:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.6875 - F1: 0.6135
sub_15:Test (Best Model) - Loss: 0.4709 - Accuracy: 0.8125 - F1: 0.7922
sub_13:Test (Best Model) - Loss: 0.7779 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 1.0007 - Accuracy: 0.4545 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 0.5929 - Accuracy: 0.6875 - F1: 0.6667
sub_26:Test (Best Model) - Loss: 0.9603 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.9502 - Accuracy: 0.5312 - F1: 0.5195
sub_9:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5625 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6418 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.5455 - F1: 0.3529
sub_13:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6562 - F1: 0.6532
sub_23:Test (Best Model) - Loss: 0.5146 - Accuracy: 0.8182 - F1: 0.8036
sub_18:Test (Best Model) - Loss: 0.4855 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.3265 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.6250 - F1: 0.5000
sub_3:Test (Best Model) - Loss: 0.7653 - Accuracy: 0.6061 - F1: 0.4850
sub_15:Test (Best Model) - Loss: 0.4622 - Accuracy: 0.7500 - F1: 0.7091
sub_10:Test (Best Model) - Loss: 0.5388 - Accuracy: 0.6667 - F1: 0.6159
sub_4:Test (Best Model) - Loss: 0.4018 - Accuracy: 0.8182 - F1: 0.8036
sub_9:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.7812 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 0.9740 - Accuracy: 0.4688 - F1: 0.4231
sub_23:Test (Best Model) - Loss: 0.9906 - Accuracy: 0.5455 - F1: 0.3529
sub_4:Test (Best Model) - Loss: 0.5499 - Accuracy: 0.6667 - F1: 0.5935
sub_15:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.7500 - F1: 0.7091
sub_9:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.7500 - F1: 0.7091

=== Summary Results ===

acc: 65.90 ± 7.31
F1: 61.03 ± 8.45
acc-in: 75.21 ± 5.89
F1-in: 71.13 ± 6.42
