lr: 0.001
sub_4:Test (Best Model) - Loss: 1.9196 - Accuracy: 0.5652 - F1: 0.5458
sub_6:Test (Best Model) - Loss: 1.5821 - Accuracy: 0.4706 - F1: 0.4113
sub_10:Test (Best Model) - Loss: 2.0978 - Accuracy: 0.4412 - F1: 0.4131
sub_2:Test (Best Model) - Loss: 1.1849 - Accuracy: 0.4203 - F1: 0.3035
sub_9:Test (Best Model) - Loss: 1.1167 - Accuracy: 0.4265 - F1: 0.3589
sub_5:Test (Best Model) - Loss: 1.0836 - Accuracy: 0.5735 - F1: 0.5015
sub_8:Test (Best Model) - Loss: 1.1255 - Accuracy: 0.5735 - F1: 0.5521
sub_7:Test (Best Model) - Loss: 1.7995 - Accuracy: 0.5000 - F1: 0.4691
sub_1:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.7500 - F1: 0.7504
sub_4:Test (Best Model) - Loss: 2.2490 - Accuracy: 0.4928 - F1: 0.4353
sub_3:Test (Best Model) - Loss: 2.5434 - Accuracy: 0.3235 - F1: 0.3399
sub_2:Test (Best Model) - Loss: 0.8783 - Accuracy: 0.6812 - F1: 0.6970
sub_6:Test (Best Model) - Loss: 1.7054 - Accuracy: 0.2647 - F1: 0.2403
sub_10:Test (Best Model) - Loss: 2.5199 - Accuracy: 0.4559 - F1: 0.4087
sub_5:Test (Best Model) - Loss: 1.0136 - Accuracy: 0.5294 - F1: 0.5219
sub_8:Test (Best Model) - Loss: 1.0240 - Accuracy: 0.6324 - F1: 0.6135
sub_9:Test (Best Model) - Loss: 1.2594 - Accuracy: 0.6176 - F1: 0.5452
sub_4:Test (Best Model) - Loss: 1.1713 - Accuracy: 0.6087 - F1: 0.5803
sub_2:Test (Best Model) - Loss: 0.9395 - Accuracy: 0.5942 - F1: 0.5319
sub_10:Test (Best Model) - Loss: 1.0057 - Accuracy: 0.4265 - F1: 0.3505
sub_1:Test (Best Model) - Loss: 1.0886 - Accuracy: 0.5588 - F1: 0.5781
sub_6:Test (Best Model) - Loss: 1.3402 - Accuracy: 0.6176 - F1: 0.6022
sub_9:Test (Best Model) - Loss: 1.2430 - Accuracy: 0.3971 - F1: 0.3141
sub_8:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.4853 - F1: 0.4137
sub_3:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.6176 - F1: 0.6043
sub_2:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.3913 - F1: 0.3029
sub_7:Test (Best Model) - Loss: 0.7366 - Accuracy: 0.6618 - F1: 0.6442
sub_4:Test (Best Model) - Loss: 1.0616 - Accuracy: 0.4348 - F1: 0.3472
sub_5:Test (Best Model) - Loss: 0.9841 - Accuracy: 0.6029 - F1: 0.5357
sub_9:Test (Best Model) - Loss: 1.1860 - Accuracy: 0.3529 - F1: 0.2866
sub_2:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.3913 - F1: 0.3029
sub_1:Test (Best Model) - Loss: 0.8913 - Accuracy: 0.4706 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 0.9770 - Accuracy: 0.4118 - F1: 0.3873
sub_8:Test (Best Model) - Loss: 0.9192 - Accuracy: 0.4559 - F1: 0.3675
sub_3:Test (Best Model) - Loss: 0.9275 - Accuracy: 0.4706 - F1: 0.3921
sub_9:Test (Best Model) - Loss: 1.2552 - Accuracy: 0.3971 - F1: 0.3538
sub_6:Test (Best Model) - Loss: 2.3046 - Accuracy: 0.4118 - F1: 0.3407
sub_2:Test (Best Model) - Loss: 1.0742 - Accuracy: 0.4265 - F1: 0.3579
sub_3:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.3529 - F1: 0.2661
sub_1:Test (Best Model) - Loss: 1.0559 - Accuracy: 0.4118 - F1: 0.3300
sub_6:Test (Best Model) - Loss: 1.2131 - Accuracy: 0.3824 - F1: 0.2972
sub_5:Test (Best Model) - Loss: 1.8093 - Accuracy: 0.7059 - F1: 0.6435
sub_10:Test (Best Model) - Loss: 3.3545 - Accuracy: 0.4118 - F1: 0.3690
sub_9:Test (Best Model) - Loss: 1.3010 - Accuracy: 0.3676 - F1: 0.2821
sub_4:Test (Best Model) - Loss: 1.2635 - Accuracy: 0.6087 - F1: 0.5907
sub_1:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.3824 - F1: 0.3121
sub_2:Test (Best Model) - Loss: 1.3019 - Accuracy: 0.3088 - F1: 0.2067
sub_3:Test (Best Model) - Loss: 2.0907 - Accuracy: 0.3235 - F1: 0.2428
sub_7:Test (Best Model) - Loss: 1.1286 - Accuracy: 0.6324 - F1: 0.6610
sub_6:Test (Best Model) - Loss: 1.2036 - Accuracy: 0.3913 - F1: 0.3091
sub_8:Test (Best Model) - Loss: 1.5329 - Accuracy: 0.6029 - F1: 0.5840
sub_4:Test (Best Model) - Loss: 1.0474 - Accuracy: 0.4493 - F1: 0.3927
sub_9:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.4559 - F1: 0.3125
sub_5:Test (Best Model) - Loss: 0.8691 - Accuracy: 0.6324 - F1: 0.5895
sub_1:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4348 - F1: 0.3438
sub_8:Test (Best Model) - Loss: 0.9373 - Accuracy: 0.5588 - F1: 0.4236
sub_2:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.4118 - F1: 0.3353
sub_3:Test (Best Model) - Loss: 0.8867 - Accuracy: 0.4058 - F1: 0.3485
sub_4:Test (Best Model) - Loss: 0.8952 - Accuracy: 0.4638 - F1: 0.3514
sub_6:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.4493 - F1: 0.3930
sub_2:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.3971 - F1: 0.3173
sub_10:Test (Best Model) - Loss: 1.1902 - Accuracy: 0.5735 - F1: 0.4992
sub_2:Test (Best Model) - Loss: 1.2473 - Accuracy: 0.3529 - F1: 0.2639
sub_8:Test (Best Model) - Loss: 0.8781 - Accuracy: 0.5147 - F1: 0.4754
sub_9:Test (Best Model) - Loss: 0.7611 - Accuracy: 0.6618 - F1: 0.5954
sub_4:Test (Best Model) - Loss: 0.5202 - Accuracy: 0.7826 - F1: 0.7776
sub_10:Test (Best Model) - Loss: 1.1692 - Accuracy: 0.3824 - F1: 0.3029
sub_5:Test (Best Model) - Loss: 1.5016 - Accuracy: 0.4853 - F1: 0.4392
sub_7:Test (Best Model) - Loss: 0.8702 - Accuracy: 0.5294 - F1: 0.4059
sub_6:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.5507 - F1: 0.4735
sub_2:Test (Best Model) - Loss: 1.0704 - Accuracy: 0.4783 - F1: 0.4175
sub_1:Test (Best Model) - Loss: 2.4787 - Accuracy: 0.4348 - F1: 0.3438
sub_8:Test (Best Model) - Loss: 1.0044 - Accuracy: 0.6029 - F1: 0.4993
sub_9:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.4559 - F1: 0.3307
sub_7:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.5147 - F1: 0.4849
sub_4:Test (Best Model) - Loss: 0.8993 - Accuracy: 0.4928 - F1: 0.4089
sub_6:Test (Best Model) - Loss: 1.1516 - Accuracy: 0.4058 - F1: 0.3325
sub_3:Test (Best Model) - Loss: 2.1179 - Accuracy: 0.5507 - F1: 0.5266
sub_2:Test (Best Model) - Loss: 1.1519 - Accuracy: 0.4493 - F1: 0.2945
sub_9:Test (Best Model) - Loss: 1.1698 - Accuracy: 0.3971 - F1: 0.3250
sub_10:Test (Best Model) - Loss: 5.1651 - Accuracy: 0.3088 - F1: 0.2581
sub_6:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3188 - F1: 0.2137
sub_5:Test (Best Model) - Loss: 0.7799 - Accuracy: 0.6618 - F1: 0.6592
sub_8:Test (Best Model) - Loss: 0.8783 - Accuracy: 0.4706 - F1: 0.3750
sub_1:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.4203 - F1: 0.3632
sub_2:Test (Best Model) - Loss: 0.9984 - Accuracy: 0.4638 - F1: 0.3047
sub_4:Test (Best Model) - Loss: 0.4071 - Accuracy: 0.8116 - F1: 0.8073
sub_7:Test (Best Model) - Loss: 2.3104 - Accuracy: 0.2794 - F1: 0.1471
sub_2:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.3768 - F1: 0.2979
sub_6:Test (Best Model) - Loss: 1.1402 - Accuracy: 0.5072 - F1: 0.5117
sub_5:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.4118 - F1: 0.3891
sub_9:Test (Best Model) - Loss: 1.3469 - Accuracy: 0.6029 - F1: 0.5868
sub_3:Test (Best Model) - Loss: 1.7920 - Accuracy: 0.5652 - F1: 0.5550
sub_8:Test (Best Model) - Loss: 0.5593 - Accuracy: 0.7647 - F1: 0.7683
sub_4:Test (Best Model) - Loss: 0.9888 - Accuracy: 0.4638 - F1: 0.3944
sub_1:Test (Best Model) - Loss: 1.1252 - Accuracy: 0.4348 - F1: 0.3422
sub_6:Test (Best Model) - Loss: 1.6307 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.2340 - Accuracy: 0.5147 - F1: 0.4972
sub_2:Test (Best Model) - Loss: 1.0612 - Accuracy: 0.5362 - F1: 0.5394
sub_7:Test (Best Model) - Loss: 2.5918 - Accuracy: 0.4559 - F1: 0.4117
sub_6:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2754 - F1: 0.1310
sub_3:Test (Best Model) - Loss: 1.4374 - Accuracy: 0.3768 - F1: 0.2821
sub_6:Test (Best Model) - Loss: 1.1241 - Accuracy: 0.4058 - F1: 0.3169
sub_4:Test (Best Model) - Loss: 0.9738 - Accuracy: 0.5217 - F1: 0.3666
sub_10:Test (Best Model) - Loss: 0.8915 - Accuracy: 0.6618 - F1: 0.5827
sub_8:Test (Best Model) - Loss: 0.7865 - Accuracy: 0.6912 - F1: 0.6935
sub_9:Test (Best Model) - Loss: 0.9868 - Accuracy: 0.4265 - F1: 0.3161
sub_6:Test (Best Model) - Loss: 1.2220 - Accuracy: 0.3768 - F1: 0.2878
sub_1:Test (Best Model) - Loss: 1.8611 - Accuracy: 0.4203 - F1: 0.3672
sub_4:Test (Best Model) - Loss: 1.0533 - Accuracy: 0.4783 - F1: 0.3621
sub_5:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.6765 - F1: 0.6778
sub_8:Test (Best Model) - Loss: 0.7171 - Accuracy: 0.7647 - F1: 0.7729
sub_9:Test (Best Model) - Loss: 1.1174 - Accuracy: 0.4853 - F1: 0.3961
sub_3:Test (Best Model) - Loss: 2.2992 - Accuracy: 0.5217 - F1: 0.4952
sub_1:Test (Best Model) - Loss: 0.8915 - Accuracy: 0.4706 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 1.0473 - Accuracy: 0.6812 - F1: 0.6974
sub_4:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.6232 - F1: 0.6378
sub_9:Test (Best Model) - Loss: 1.2537 - Accuracy: 0.4118 - F1: 0.3649
sub_7:Test (Best Model) - Loss: 3.3301 - Accuracy: 0.3088 - F1: 0.2025
sub_10:Test (Best Model) - Loss: 1.0555 - Accuracy: 0.4493 - F1: 0.3752
sub_3:Test (Best Model) - Loss: 2.6036 - Accuracy: 0.3478 - F1: 0.3128
sub_8:Test (Best Model) - Loss: 0.7971 - Accuracy: 0.6471 - F1: 0.5361
sub_4:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.6667 - F1: 0.6560
sub_5:Test (Best Model) - Loss: 1.0378 - Accuracy: 0.4412 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 1.0361 - Accuracy: 0.4706 - F1: 0.3750
sub_9:Test (Best Model) - Loss: 1.3298 - Accuracy: 0.4559 - F1: 0.3652
sub_10:Test (Best Model) - Loss: 1.0161 - Accuracy: 0.5942 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.9499 - Accuracy: 0.6912 - F1: 0.6272
sub_7:Test (Best Model) - Loss: 3.5951 - Accuracy: 0.3971 - F1: 0.3315
sub_10:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.6377 - F1: 0.6003
sub_8:Test (Best Model) - Loss: 0.5281 - Accuracy: 0.8382 - F1: 0.8446
sub_3:Test (Best Model) - Loss: 2.7982 - Accuracy: 0.4928 - F1: 0.3903
sub_7:Test (Best Model) - Loss: 2.8723 - Accuracy: 0.2647 - F1: 0.1216
sub_5:Test (Best Model) - Loss: 1.0399 - Accuracy: 0.4559 - F1: 0.3420
sub_8:Test (Best Model) - Loss: 1.1996 - Accuracy: 0.6176 - F1: 0.6347
sub_10:Test (Best Model) - Loss: 1.8207 - Accuracy: 0.4783 - F1: 0.4843
sub_1:Test (Best Model) - Loss: 0.8001 - Accuracy: 0.6471 - F1: 0.6522
sub_1:Test (Best Model) - Loss: 0.8832 - Accuracy: 0.4706 - F1: 0.3977
sub_5:Test (Best Model) - Loss: 1.1097 - Accuracy: 0.6471 - F1: 0.6191
sub_7:Test (Best Model) - Loss: 1.5282 - Accuracy: 0.4412 - F1: 0.4140
sub_3:Test (Best Model) - Loss: 1.4858 - Accuracy: 0.5072 - F1: 0.4607
sub_1:Test (Best Model) - Loss: 0.8628 - Accuracy: 0.5294 - F1: 0.4808
sub_5:Test (Best Model) - Loss: 0.9672 - Accuracy: 0.6471 - F1: 0.5868
sub_3:Test (Best Model) - Loss: 2.4677 - Accuracy: 0.5507 - F1: 0.5275
sub_7:Test (Best Model) - Loss: 2.2814 - Accuracy: 0.5588 - F1: 0.4723
sub_5:Test (Best Model) - Loss: 1.8588 - Accuracy: 0.4706 - F1: 0.4208
sub_3:Test (Best Model) - Loss: 2.0491 - Accuracy: 0.4058 - F1: 0.3982
sub_7:Test (Best Model) - Loss: 1.2074 - Accuracy: 0.7500 - F1: 0.7459
sub_7:Test (Best Model) - Loss: 1.9777 - Accuracy: 0.4265 - F1: 0.4045
sub_7:Test (Best Model) - Loss: 1.4354 - Accuracy: 0.3971 - F1: 0.3176
sub_12:Test (Best Model) - Loss: 1.2527 - Accuracy: 0.3824 - F1: 0.2987
sub_16:Test (Best Model) - Loss: 1.1281 - Accuracy: 0.4853 - F1: 0.4135
sub_14:Test (Best Model) - Loss: 2.9454 - Accuracy: 0.2353 - F1: 0.1733
sub_11:Test (Best Model) - Loss: 1.0242 - Accuracy: 0.5362 - F1: 0.4119
sub_17:Test (Best Model) - Loss: 1.0672 - Accuracy: 0.4783 - F1: 0.4800
sub_18:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.5362 - F1: 0.5001
sub_20:Test (Best Model) - Loss: 1.4512 - Accuracy: 0.6176 - F1: 0.5738
sub_19:Test (Best Model) - Loss: 1.4174 - Accuracy: 0.3676 - F1: 0.2706
sub_12:Test (Best Model) - Loss: 1.1818 - Accuracy: 0.3971 - F1: 0.3125
sub_15:Test (Best Model) - Loss: 0.8328 - Accuracy: 0.6912 - F1: 0.7003
sub_16:Test (Best Model) - Loss: 1.0243 - Accuracy: 0.4265 - F1: 0.3016
sub_13:Test (Best Model) - Loss: 3.4121 - Accuracy: 0.4118 - F1: 0.2874
sub_18:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.6232 - F1: 0.6290
sub_17:Test (Best Model) - Loss: 0.9362 - Accuracy: 0.4638 - F1: 0.3827
sub_11:Test (Best Model) - Loss: 1.0450 - Accuracy: 0.4638 - F1: 0.3827
sub_12:Test (Best Model) - Loss: 1.2119 - Accuracy: 0.3971 - F1: 0.3141
sub_19:Test (Best Model) - Loss: 2.9003 - Accuracy: 0.3529 - F1: 0.3207
sub_14:Test (Best Model) - Loss: 2.8751 - Accuracy: 0.2794 - F1: 0.3446
sub_16:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.4118 - F1: 0.3333
sub_18:Test (Best Model) - Loss: 0.8588 - Accuracy: 0.4928 - F1: 0.4031
sub_20:Test (Best Model) - Loss: 1.7323 - Accuracy: 0.4853 - F1: 0.4323
sub_16:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.3235 - F1: 0.2236
sub_12:Test (Best Model) - Loss: 1.1158 - Accuracy: 0.4118 - F1: 0.3300
sub_19:Test (Best Model) - Loss: 1.1005 - Accuracy: 0.4265 - F1: 0.3270
sub_15:Test (Best Model) - Loss: 0.7569 - Accuracy: 0.6618 - F1: 0.6822
sub_14:Test (Best Model) - Loss: 3.1343 - Accuracy: 0.1324 - F1: 0.1192
sub_16:Test (Best Model) - Loss: 1.4459 - Accuracy: 0.3235 - F1: 0.2222
sub_17:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.7101 - F1: 0.7259
sub_11:Test (Best Model) - Loss: 1.0771 - Accuracy: 0.6087 - F1: 0.5743
sub_12:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.3971 - F1: 0.3428
sub_13:Test (Best Model) - Loss: 2.8966 - Accuracy: 0.4265 - F1: 0.3082
sub_18:Test (Best Model) - Loss: 0.8469 - Accuracy: 0.6087 - F1: 0.5691
sub_20:Test (Best Model) - Loss: 1.0288 - Accuracy: 0.4559 - F1: 0.3944
sub_15:Test (Best Model) - Loss: 0.9610 - Accuracy: 0.4853 - F1: 0.4200
sub_17:Test (Best Model) - Loss: 0.9365 - Accuracy: 0.4638 - F1: 0.3697
sub_19:Test (Best Model) - Loss: 3.3939 - Accuracy: 0.2500 - F1: 0.2369
sub_11:Test (Best Model) - Loss: 1.0242 - Accuracy: 0.5217 - F1: 0.5066
sub_14:Test (Best Model) - Loss: 3.2279 - Accuracy: 0.2353 - F1: 0.2069
sub_12:Test (Best Model) - Loss: 2.0518 - Accuracy: 0.4638 - F1: 0.3821
sub_20:Test (Best Model) - Loss: 1.0684 - Accuracy: 0.4265 - F1: 0.3400
sub_13:Test (Best Model) - Loss: 1.7989 - Accuracy: 0.2941 - F1: 0.1538
sub_17:Test (Best Model) - Loss: 0.9910 - Accuracy: 0.4348 - F1: 0.3422
sub_19:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.3235 - F1: 0.2389
sub_16:Test (Best Model) - Loss: 1.9499 - Accuracy: 0.2647 - F1: 0.1930
sub_18:Test (Best Model) - Loss: 0.8497 - Accuracy: 0.5797 - F1: 0.5699
sub_11:Test (Best Model) - Loss: 1.1070 - Accuracy: 0.4783 - F1: 0.3194
sub_15:Test (Best Model) - Loss: 1.0225 - Accuracy: 0.4412 - F1: 0.3455
sub_12:Test (Best Model) - Loss: 1.1693 - Accuracy: 0.4058 - F1: 0.3392
sub_14:Test (Best Model) - Loss: 3.5542 - Accuracy: 0.2941 - F1: 0.2631
sub_20:Test (Best Model) - Loss: 1.8098 - Accuracy: 0.3971 - F1: 0.3141
sub_17:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.4493 - F1: 0.3514
sub_19:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.6176 - F1: 0.5850
sub_18:Test (Best Model) - Loss: 1.0673 - Accuracy: 0.5588 - F1: 0.5514
sub_12:Test (Best Model) - Loss: 0.9771 - Accuracy: 0.4783 - F1: 0.4107
sub_20:Test (Best Model) - Loss: 1.0321 - Accuracy: 0.5147 - F1: 0.4228
sub_16:Test (Best Model) - Loss: 2.2519 - Accuracy: 0.4412 - F1: 0.4609
sub_13:Test (Best Model) - Loss: 1.1212 - Accuracy: 0.5147 - F1: 0.4835
sub_14:Test (Best Model) - Loss: 1.4230 - Accuracy: 0.2353 - F1: 0.1570
sub_12:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.3768 - F1: 0.2878
sub_18:Test (Best Model) - Loss: 1.2897 - Accuracy: 0.3824 - F1: 0.3051
sub_16:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.0337 - Accuracy: 0.4853 - F1: 0.3940
sub_11:Test (Best Model) - Loss: 1.0306 - Accuracy: 0.6812 - F1: 0.6759
sub_20:Test (Best Model) - Loss: 0.9408 - Accuracy: 0.4412 - F1: 0.3558
sub_15:Test (Best Model) - Loss: 1.6718 - Accuracy: 0.3235 - F1: 0.3316
sub_16:Test (Best Model) - Loss: 1.2242 - Accuracy: 0.3676 - F1: 0.2745
sub_13:Test (Best Model) - Loss: 2.1179 - Accuracy: 0.2647 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 1.1904 - Accuracy: 0.3913 - F1: 0.3118
sub_18:Test (Best Model) - Loss: 0.4730 - Accuracy: 0.8676 - F1: 0.8739
sub_11:Test (Best Model) - Loss: 1.2337 - Accuracy: 0.3623 - F1: 0.3036
sub_19:Test (Best Model) - Loss: 1.0405 - Accuracy: 0.4559 - F1: 0.3872
sub_15:Test (Best Model) - Loss: 0.8837 - Accuracy: 0.5000 - F1: 0.4281
sub_20:Test (Best Model) - Loss: 0.9764 - Accuracy: 0.5441 - F1: 0.5319
sub_17:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.5942 - F1: 0.5435
sub_19:Test (Best Model) - Loss: 0.9898 - Accuracy: 0.4412 - F1: 0.3493
sub_14:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.7500 - F1: 0.7437
sub_18:Test (Best Model) - Loss: 0.9965 - Accuracy: 0.4118 - F1: 0.3268
sub_16:Test (Best Model) - Loss: 1.7955 - Accuracy: 0.5735 - F1: 0.5946
sub_12:Test (Best Model) - Loss: 0.9394 - Accuracy: 0.5000 - F1: 0.4266
sub_20:Test (Best Model) - Loss: 0.9946 - Accuracy: 0.4412 - F1: 0.3615
sub_11:Test (Best Model) - Loss: 0.9838 - Accuracy: 0.5507 - F1: 0.5225
sub_17:Test (Best Model) - Loss: 0.9205 - Accuracy: 0.4638 - F1: 0.3647
sub_12:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3382 - F1: 0.2441
sub_14:Test (Best Model) - Loss: 0.8714 - Accuracy: 0.4559 - F1: 0.3798
sub_20:Test (Best Model) - Loss: 0.7865 - Accuracy: 0.6324 - F1: 0.5662
sub_15:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6618 - F1: 0.6764
sub_13:Test (Best Model) - Loss: 3.6845 - Accuracy: 0.3188 - F1: 0.3006
sub_16:Test (Best Model) - Loss: 1.6937 - Accuracy: 0.2941 - F1: 0.1841
sub_17:Test (Best Model) - Loss: 1.1860 - Accuracy: 0.3768 - F1: 0.2878
sub_18:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.4853 - F1: 0.4773
sub_19:Test (Best Model) - Loss: 0.9298 - Accuracy: 0.5735 - F1: 0.5759
sub_12:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.6912 - F1: 0.6331
sub_17:Test (Best Model) - Loss: 1.2718 - Accuracy: 0.3768 - F1: 0.2878
sub_16:Test (Best Model) - Loss: 1.7462 - Accuracy: 0.2500 - F1: 0.1414
sub_14:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.7059 - F1: 0.7111
sub_11:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.6232 - F1: 0.6136
sub_20:Test (Best Model) - Loss: 0.7398 - Accuracy: 0.7246 - F1: 0.7348
sub_15:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.5588 - F1: 0.5445
sub_12:Test (Best Model) - Loss: 0.9588 - Accuracy: 0.4559 - F1: 0.3640
sub_18:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.5735 - F1: 0.5660
sub_17:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.3971 - F1: 0.3157
sub_20:Test (Best Model) - Loss: 1.0270 - Accuracy: 0.5797 - F1: 0.4845
sub_16:Test (Best Model) - Loss: 2.6186 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 2.3991 - Accuracy: 0.3382 - F1: 0.3469
sub_11:Test (Best Model) - Loss: 1.9473 - Accuracy: 0.2609 - F1: 0.1084
sub_18:Test (Best Model) - Loss: 1.3043 - Accuracy: 0.5147 - F1: 0.5240
sub_20:Test (Best Model) - Loss: 0.9305 - Accuracy: 0.5362 - F1: 0.4204
sub_13:Test (Best Model) - Loss: 3.3804 - Accuracy: 0.2319 - F1: 0.2213
sub_16:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.3529 - F1: 0.2654
sub_12:Test (Best Model) - Loss: 0.8896 - Accuracy: 0.5000 - F1: 0.4593
sub_14:Test (Best Model) - Loss: 1.1599 - Accuracy: 0.5000 - F1: 0.4704
sub_17:Test (Best Model) - Loss: 1.0794 - Accuracy: 0.4118 - F1: 0.3216
sub_16:Test (Best Model) - Loss: 1.5919 - Accuracy: 0.2941 - F1: 0.1723
sub_20:Test (Best Model) - Loss: 0.9508 - Accuracy: 0.5362 - F1: 0.4531
sub_19:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.4559 - F1: 0.4015
sub_18:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.4706 - F1: 0.4689
sub_15:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.5441 - F1: 0.5265
sub_13:Test (Best Model) - Loss: 0.8095 - Accuracy: 0.6377 - F1: 0.5619
sub_14:Test (Best Model) - Loss: 1.0819 - Accuracy: 0.5735 - F1: 0.5821
sub_13:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3043 - F1: 0.2568
sub_11:Test (Best Model) - Loss: 3.4715 - Accuracy: 0.2609 - F1: 0.2204
sub_20:Test (Best Model) - Loss: 0.9462 - Accuracy: 0.7101 - F1: 0.7055
sub_19:Test (Best Model) - Loss: 2.4824 - Accuracy: 0.4118 - F1: 0.4069
sub_14:Test (Best Model) - Loss: 0.4885 - Accuracy: 0.8676 - F1: 0.8710
sub_17:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.4853 - F1: 0.3757
sub_15:Test (Best Model) - Loss: 1.0039 - Accuracy: 0.6471 - F1: 0.6615
sub_18:Test (Best Model) - Loss: 1.8207 - Accuracy: 0.5882 - F1: 0.5669
sub_17:Test (Best Model) - Loss: 1.1015 - Accuracy: 0.4118 - F1: 0.3200
sub_15:Test (Best Model) - Loss: 0.9083 - Accuracy: 0.4706 - F1: 0.4502
sub_14:Test (Best Model) - Loss: 2.1263 - Accuracy: 0.3382 - F1: 0.3223
sub_18:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.5882 - F1: 0.6050
sub_13:Test (Best Model) - Loss: 2.8984 - Accuracy: 0.3333 - F1: 0.2394
sub_15:Test (Best Model) - Loss: 1.5149 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.6029 - F1: 0.5488
sub_19:Test (Best Model) - Loss: 1.0635 - Accuracy: 0.4706 - F1: 0.4120
sub_14:Test (Best Model) - Loss: 0.5779 - Accuracy: 0.7941 - F1: 0.7964
sub_11:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.7391 - F1: 0.7546
sub_15:Test (Best Model) - Loss: 1.3071 - Accuracy: 0.3676 - F1: 0.2950
sub_14:Test (Best Model) - Loss: 3.5813 - Accuracy: 0.2206 - F1: 0.1491
sub_13:Test (Best Model) - Loss: 0.8161 - Accuracy: 0.5735 - F1: 0.5238
sub_19:Test (Best Model) - Loss: 1.1851 - Accuracy: 0.4412 - F1: 0.3800
sub_15:Test (Best Model) - Loss: 0.8907 - Accuracy: 0.5441 - F1: 0.4940
sub_11:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.4348 - F1: 0.3916
sub_13:Test (Best Model) - Loss: 1.7345 - Accuracy: 0.3824 - F1: 0.2410
sub_15:Test (Best Model) - Loss: 0.8972 - Accuracy: 0.5000 - F1: 0.4218
sub_11:Test (Best Model) - Loss: 0.9292 - Accuracy: 0.5362 - F1: 0.4410
sub_13:Test (Best Model) - Loss: 2.0050 - Accuracy: 0.2059 - F1: 0.1362
sub_13:Test (Best Model) - Loss: 1.2079 - Accuracy: 0.5294 - F1: 0.4771
sub_11:Test (Best Model) - Loss: 1.7320 - Accuracy: 0.4348 - F1: 0.3620
sub_13:Test (Best Model) - Loss: 1.0553 - Accuracy: 0.4265 - F1: 0.2809
sub_24:Test (Best Model) - Loss: 1.9528 - Accuracy: 0.6471 - F1: 0.5987
sub_23:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.3913 - F1: 0.3108
sub_27:Test (Best Model) - Loss: 1.0672 - Accuracy: 0.4783 - F1: 0.4800
sub_22:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.3824 - F1: 0.3369
sub_26:Test (Best Model) - Loss: 0.5792 - Accuracy: 0.7971 - F1: 0.8063
sub_28:Test (Best Model) - Loss: 1.0474 - Accuracy: 0.5147 - F1: 0.5041
sub_25:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.8116 - F1: 0.8222
sub_21:Test (Best Model) - Loss: 0.9951 - Accuracy: 0.5735 - F1: 0.5579
sub_29:Test (Best Model) - Loss: 0.9425 - Accuracy: 0.6324 - F1: 0.6489
sub_27:Test (Best Model) - Loss: 0.9362 - Accuracy: 0.4638 - F1: 0.3827
sub_22:Test (Best Model) - Loss: 1.4505 - Accuracy: 0.5147 - F1: 0.4963
sub_28:Test (Best Model) - Loss: 0.7825 - Accuracy: 0.6618 - F1: 0.6571
sub_26:Test (Best Model) - Loss: 0.8459 - Accuracy: 0.5507 - F1: 0.5078
sub_24:Test (Best Model) - Loss: 0.9782 - Accuracy: 0.5441 - F1: 0.5300
sub_23:Test (Best Model) - Loss: 1.6814 - Accuracy: 0.4493 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.4118 - F1: 0.3502
sub_29:Test (Best Model) - Loss: 0.9741 - Accuracy: 0.5735 - F1: 0.5837
sub_22:Test (Best Model) - Loss: 0.9438 - Accuracy: 0.4412 - F1: 0.4322
sub_26:Test (Best Model) - Loss: 0.8653 - Accuracy: 0.5072 - F1: 0.4281
sub_25:Test (Best Model) - Loss: 0.8731 - Accuracy: 0.6377 - F1: 0.6346
sub_24:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7500 - F1: 0.7458
sub_23:Test (Best Model) - Loss: 0.9334 - Accuracy: 0.4783 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 0.8223 - Accuracy: 0.7059 - F1: 0.6978
sub_29:Test (Best Model) - Loss: 0.9533 - Accuracy: 0.4559 - F1: 0.3640
sub_27:Test (Best Model) - Loss: 0.5307 - Accuracy: 0.7101 - F1: 0.7259
sub_23:Test (Best Model) - Loss: 1.1045 - Accuracy: 0.3913 - F1: 0.3029
sub_21:Test (Best Model) - Loss: 0.8298 - Accuracy: 0.7059 - F1: 0.7015
sub_25:Test (Best Model) - Loss: 1.0276 - Accuracy: 0.4493 - F1: 0.3705
sub_28:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.2353 - F1: 0.1645
sub_27:Test (Best Model) - Loss: 0.9365 - Accuracy: 0.4638 - F1: 0.3697
sub_23:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.3478 - F1: 0.2681
sub_24:Test (Best Model) - Loss: 0.9639 - Accuracy: 0.6324 - F1: 0.6147
sub_22:Test (Best Model) - Loss: 1.1035 - Accuracy: 0.5000 - F1: 0.4570
sub_26:Test (Best Model) - Loss: 0.8838 - Accuracy: 0.5362 - F1: 0.4942
sub_28:Test (Best Model) - Loss: 1.4961 - Accuracy: 0.3088 - F1: 0.1958
sub_25:Test (Best Model) - Loss: 1.0314 - Accuracy: 0.4203 - F1: 0.3332
sub_29:Test (Best Model) - Loss: 1.0343 - Accuracy: 0.4265 - F1: 0.3433
sub_27:Test (Best Model) - Loss: 0.9910 - Accuracy: 0.4348 - F1: 0.3422
sub_26:Test (Best Model) - Loss: 1.0156 - Accuracy: 0.4638 - F1: 0.3827
sub_22:Test (Best Model) - Loss: 1.0348 - Accuracy: 0.2206 - F1: 0.2634
sub_29:Test (Best Model) - Loss: 1.1981 - Accuracy: 0.3971 - F1: 0.3141
sub_25:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.4058 - F1: 0.3400
sub_28:Test (Best Model) - Loss: 2.3621 - Accuracy: 0.1912 - F1: 0.1605
sub_23:Test (Best Model) - Loss: 1.2942 - Accuracy: 0.4118 - F1: 0.3155
sub_21:Test (Best Model) - Loss: 0.7718 - Accuracy: 0.5588 - F1: 0.4550
sub_24:Test (Best Model) - Loss: 0.9945 - Accuracy: 0.4412 - F1: 0.3956
sub_27:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.4493 - F1: 0.3514
sub_26:Test (Best Model) - Loss: 1.0250 - Accuracy: 0.4412 - F1: 0.3749
sub_25:Test (Best Model) - Loss: 1.5887 - Accuracy: 0.3088 - F1: 0.2611
sub_21:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.4559 - F1: 0.3008
sub_22:Test (Best Model) - Loss: 0.8633 - Accuracy: 0.6957 - F1: 0.6909
sub_24:Test (Best Model) - Loss: 1.3342 - Accuracy: 0.4412 - F1: 0.3461
sub_23:Test (Best Model) - Loss: 1.4779 - Accuracy: 0.4412 - F1: 0.3744
sub_28:Test (Best Model) - Loss: 4.0286 - Accuracy: 0.3971 - F1: 0.3099
sub_29:Test (Best Model) - Loss: 0.8665 - Accuracy: 0.5735 - F1: 0.5730
sub_26:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.4853 - F1: 0.4313
sub_21:Test (Best Model) - Loss: 1.7156 - Accuracy: 0.2794 - F1: 0.1463
sub_22:Test (Best Model) - Loss: 0.7895 - Accuracy: 0.6522 - F1: 0.6376
sub_24:Test (Best Model) - Loss: 0.9166 - Accuracy: 0.6618 - F1: 0.6584
sub_23:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.3676 - F1: 0.2952
sub_26:Test (Best Model) - Loss: 1.1700 - Accuracy: 0.4412 - F1: 0.3722
sub_25:Test (Best Model) - Loss: 0.6302 - Accuracy: 0.6029 - F1: 0.5574
sub_29:Test (Best Model) - Loss: 0.8850 - Accuracy: 0.4706 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 2.6422 - Accuracy: 0.2206 - F1: 0.1699
sub_27:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.5942 - F1: 0.5435
sub_22:Test (Best Model) - Loss: 1.5676 - Accuracy: 0.4783 - F1: 0.4569
sub_21:Test (Best Model) - Loss: 1.4686 - Accuracy: 0.3971 - F1: 0.2750
sub_26:Test (Best Model) - Loss: 0.8723 - Accuracy: 0.6765 - F1: 0.5995
sub_24:Test (Best Model) - Loss: 0.7354 - Accuracy: 0.6912 - F1: 0.7040
sub_27:Test (Best Model) - Loss: 0.9205 - Accuracy: 0.4638 - F1: 0.3647
sub_25:Test (Best Model) - Loss: 1.5395 - Accuracy: 0.3382 - F1: 0.2429
sub_29:Test (Best Model) - Loss: 0.8318 - Accuracy: 0.6029 - F1: 0.5527
sub_23:Test (Best Model) - Loss: 1.1397 - Accuracy: 0.5147 - F1: 0.4517
sub_28:Test (Best Model) - Loss: 2.3552 - Accuracy: 0.2353 - F1: 0.1978
sub_22:Test (Best Model) - Loss: 1.0385 - Accuracy: 0.4348 - F1: 0.3438
sub_27:Test (Best Model) - Loss: 1.1860 - Accuracy: 0.3768 - F1: 0.2878
sub_24:Test (Best Model) - Loss: 0.9513 - Accuracy: 0.6324 - F1: 0.6299
sub_21:Test (Best Model) - Loss: 0.9818 - Accuracy: 0.4559 - F1: 0.2977
sub_26:Test (Best Model) - Loss: 1.6375 - Accuracy: 0.5588 - F1: 0.5354
sub_25:Test (Best Model) - Loss: 0.9030 - Accuracy: 0.5294 - F1: 0.4632
sub_22:Test (Best Model) - Loss: 2.0192 - Accuracy: 0.3913 - F1: 0.3143
sub_27:Test (Best Model) - Loss: 1.2718 - Accuracy: 0.3768 - F1: 0.2878
sub_29:Test (Best Model) - Loss: 0.8652 - Accuracy: 0.4706 - F1: 0.3750
sub_23:Test (Best Model) - Loss: 1.1095 - Accuracy: 0.3971 - F1: 0.3583
sub_28:Test (Best Model) - Loss: 2.2256 - Accuracy: 0.2500 - F1: 0.1368
sub_22:Test (Best Model) - Loss: 1.1913 - Accuracy: 0.6618 - F1: 0.6086
sub_26:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.5147 - F1: 0.5376
sub_24:Test (Best Model) - Loss: 0.8765 - Accuracy: 0.5441 - F1: 0.5307
sub_27:Test (Best Model) - Loss: 1.1289 - Accuracy: 0.3971 - F1: 0.3157
sub_21:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.7941 - F1: 0.7862
sub_23:Test (Best Model) - Loss: 1.0836 - Accuracy: 0.4203 - F1: 0.3300
sub_25:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.4559 - F1: 0.4004
sub_27:Test (Best Model) - Loss: 1.0794 - Accuracy: 0.4118 - F1: 0.3216
sub_28:Test (Best Model) - Loss: 2.3330 - Accuracy: 0.4118 - F1: 0.3311
sub_22:Test (Best Model) - Loss: 1.6770 - Accuracy: 0.2059 - F1: 0.1548
sub_29:Test (Best Model) - Loss: 0.8598 - Accuracy: 0.4706 - F1: 0.3768
sub_24:Test (Best Model) - Loss: 1.1714 - Accuracy: 0.4853 - F1: 0.3951
sub_26:Test (Best Model) - Loss: 1.5521 - Accuracy: 0.3971 - F1: 0.3207
sub_23:Test (Best Model) - Loss: 1.8919 - Accuracy: 0.4493 - F1: 0.4575
sub_21:Test (Best Model) - Loss: 0.7592 - Accuracy: 0.6176 - F1: 0.5177
sub_25:Test (Best Model) - Loss: 1.5533 - Accuracy: 0.6029 - F1: 0.5777
sub_28:Test (Best Model) - Loss: 1.5349 - Accuracy: 0.5588 - F1: 0.5023
sub_29:Test (Best Model) - Loss: 0.9233 - Accuracy: 0.4493 - F1: 0.3874
sub_24:Test (Best Model) - Loss: 1.1936 - Accuracy: 0.5882 - F1: 0.5639
sub_22:Test (Best Model) - Loss: 1.5786 - Accuracy: 0.3235 - F1: 0.2245
sub_26:Test (Best Model) - Loss: 1.8319 - Accuracy: 0.3971 - F1: 0.2985
sub_27:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.4853 - F1: 0.3757
sub_28:Test (Best Model) - Loss: 0.9558 - Accuracy: 0.6029 - F1: 0.5270
sub_21:Test (Best Model) - Loss: 1.6540 - Accuracy: 0.4265 - F1: 0.3554
sub_29:Test (Best Model) - Loss: 0.9065 - Accuracy: 0.5507 - F1: 0.4831
sub_27:Test (Best Model) - Loss: 1.1015 - Accuracy: 0.4118 - F1: 0.3200
sub_23:Test (Best Model) - Loss: 1.1985 - Accuracy: 0.4203 - F1: 0.3886
sub_25:Test (Best Model) - Loss: 1.8435 - Accuracy: 0.5735 - F1: 0.5233
sub_22:Test (Best Model) - Loss: 0.9254 - Accuracy: 0.4559 - F1: 0.3657
sub_21:Test (Best Model) - Loss: 2.1483 - Accuracy: 0.3676 - F1: 0.2383
sub_24:Test (Best Model) - Loss: 2.1506 - Accuracy: 0.4412 - F1: 0.4124
sub_26:Test (Best Model) - Loss: 0.8573 - Accuracy: 0.6471 - F1: 0.6584
sub_29:Test (Best Model) - Loss: 1.0683 - Accuracy: 0.5797 - F1: 0.5714
sub_28:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.3971 - F1: 0.3029
sub_27:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.6029 - F1: 0.5488
sub_23:Test (Best Model) - Loss: 1.1290 - Accuracy: 0.4638 - F1: 0.4083
sub_22:Test (Best Model) - Loss: 0.9738 - Accuracy: 0.4412 - F1: 0.3541
sub_21:Test (Best Model) - Loss: 0.7949 - Accuracy: 0.5147 - F1: 0.3365
sub_25:Test (Best Model) - Loss: 1.0372 - Accuracy: 0.7059 - F1: 0.7115
sub_29:Test (Best Model) - Loss: 0.9174 - Accuracy: 0.5652 - F1: 0.5192
sub_24:Test (Best Model) - Loss: 1.7084 - Accuracy: 0.5000 - F1: 0.4830
sub_28:Test (Best Model) - Loss: 1.4277 - Accuracy: 0.5000 - F1: 0.4411
sub_23:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.4203 - F1: 0.3348
sub_26:Test (Best Model) - Loss: 1.3344 - Accuracy: 0.5147 - F1: 0.5445
sub_29:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.4348 - F1: 0.4506
sub_21:Test (Best Model) - Loss: 2.5301 - Accuracy: 0.4412 - F1: 0.3922
sub_24:Test (Best Model) - Loss: 2.1517 - Accuracy: 0.6324 - F1: 0.6177
sub_25:Test (Best Model) - Loss: 0.9186 - Accuracy: 0.6765 - F1: 0.6800
sub_21:Test (Best Model) - Loss: 1.0076 - Accuracy: 0.4853 - F1: 0.3256
sub_25:Test (Best Model) - Loss: 1.2521 - Accuracy: 0.6765 - F1: 0.6336

=== Summary Results ===

acc: 48.38 ± 6.06
F1: 42.64 ± 7.33
acc-in: 61.39 ± 9.07
F1-in: 55.09 ± 11.32
runing time: 1242.62 seconds
