lr: 0.001
sub_11:Test (Best Model) - Loss: 1.2859 - Accuracy: 0.5072 - F1: 0.4623
sub_15:Test (Best Model) - Loss: 1.1453 - Accuracy: 0.4853 - F1: 0.4524
sub_5:Test (Best Model) - Loss: 0.9109 - Accuracy: 0.6029 - F1: 0.5808
sub_9:Test (Best Model) - Loss: 2.0903 - Accuracy: 0.6471 - F1: 0.5774
sub_4:Test (Best Model) - Loss: 0.5613 - Accuracy: 0.7971 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.7647 - F1: 0.7824
sub_12:Test (Best Model) - Loss: 1.1816 - Accuracy: 0.5294 - F1: 0.5083
sub_2:Test (Best Model) - Loss: 9.2388 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 3.5944 - Accuracy: 0.3235 - F1: 0.3456
sub_10:Test (Best Model) - Loss: 2.3819 - Accuracy: 0.4265 - F1: 0.3942
sub_1:Test (Best Model) - Loss: 1.5360 - Accuracy: 0.5441 - F1: 0.5399
sub_15:Test (Best Model) - Loss: 0.9114 - Accuracy: 0.4559 - F1: 0.3452
sub_13:Test (Best Model) - Loss: 3.0292 - Accuracy: 0.2647 - F1: 0.1381
sub_11:Test (Best Model) - Loss: 1.2288 - Accuracy: 0.5652 - F1: 0.5392
sub_14:Test (Best Model) - Loss: 3.3476 - Accuracy: 0.2941 - F1: 0.3164
sub_3:Test (Best Model) - Loss: 1.5297 - Accuracy: 0.3382 - F1: 0.3439
sub_6:Test (Best Model) - Loss: 2.1841 - Accuracy: 0.4706 - F1: 0.4144
sub_7:Test (Best Model) - Loss: 0.4531 - Accuracy: 0.8088 - F1: 0.8137
sub_8:Test (Best Model) - Loss: 0.7406 - Accuracy: 0.7206 - F1: 0.7367
sub_5:Test (Best Model) - Loss: 0.9587 - Accuracy: 0.5147 - F1: 0.5273
sub_2:Test (Best Model) - Loss: 0.8189 - Accuracy: 0.6957 - F1: 0.6633
sub_3:Test (Best Model) - Loss: 2.3647 - Accuracy: 0.3235 - F1: 0.2814
sub_12:Test (Best Model) - Loss: 2.2302 - Accuracy: 0.4706 - F1: 0.4257
sub_11:Test (Best Model) - Loss: 0.9595 - Accuracy: 0.5942 - F1: 0.5374
sub_14:Test (Best Model) - Loss: 2.5084 - Accuracy: 0.2206 - F1: 0.2038
sub_9:Test (Best Model) - Loss: 1.7876 - Accuracy: 0.6176 - F1: 0.5615
sub_4:Test (Best Model) - Loss: 0.9153 - Accuracy: 0.6377 - F1: 0.6234
sub_8:Test (Best Model) - Loss: 1.5553 - Accuracy: 0.4118 - F1: 0.3407
sub_15:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.5294 - F1: 0.5553
sub_10:Test (Best Model) - Loss: 1.7993 - Accuracy: 0.2941 - F1: 0.2372
sub_13:Test (Best Model) - Loss: 3.1969 - Accuracy: 0.4559 - F1: 0.3513
sub_7:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.7353 - F1: 0.7240
sub_11:Test (Best Model) - Loss: 0.9473 - Accuracy: 0.6087 - F1: 0.5354
sub_1:Test (Best Model) - Loss: 1.1340 - Accuracy: 0.5588 - F1: 0.5601
sub_9:Test (Best Model) - Loss: 1.7034 - Accuracy: 0.2500 - F1: 0.1133
sub_4:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.5652 - F1: 0.5479
sub_6:Test (Best Model) - Loss: 2.0968 - Accuracy: 0.4118 - F1: 0.3286
sub_2:Test (Best Model) - Loss: 1.0965 - Accuracy: 0.6667 - F1: 0.5862
sub_5:Test (Best Model) - Loss: 2.6462 - Accuracy: 0.3824 - F1: 0.2845
sub_9:Test (Best Model) - Loss: 1.1968 - Accuracy: 0.3824 - F1: 0.2972
sub_14:Test (Best Model) - Loss: 2.9992 - Accuracy: 0.1471 - F1: 0.1569
sub_11:Test (Best Model) - Loss: 1.0175 - Accuracy: 0.5507 - F1: 0.4875
sub_13:Test (Best Model) - Loss: 1.8685 - Accuracy: 0.2941 - F1: 0.2748
sub_3:Test (Best Model) - Loss: 1.4495 - Accuracy: 0.5441 - F1: 0.5064
sub_1:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.4265 - F1: 0.3680
sub_8:Test (Best Model) - Loss: 0.5786 - Accuracy: 0.7647 - F1: 0.7818
sub_7:Test (Best Model) - Loss: 2.0092 - Accuracy: 0.6029 - F1: 0.5667
sub_10:Test (Best Model) - Loss: 2.6097 - Accuracy: 0.3676 - F1: 0.2851
sub_12:Test (Best Model) - Loss: 2.1949 - Accuracy: 0.4706 - F1: 0.4390
sub_2:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.4493 - F1: 0.4142
sub_14:Test (Best Model) - Loss: 2.5882 - Accuracy: 0.0882 - F1: 0.0517
sub_4:Test (Best Model) - Loss: 1.0349 - Accuracy: 0.6087 - F1: 0.6047
sub_9:Test (Best Model) - Loss: 2.0107 - Accuracy: 0.5882 - F1: 0.5262
sub_1:Test (Best Model) - Loss: 1.0655 - Accuracy: 0.4265 - F1: 0.3433
sub_11:Test (Best Model) - Loss: 0.9482 - Accuracy: 0.6667 - F1: 0.6305
sub_15:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.5882 - F1: 0.5939
sub_5:Test (Best Model) - Loss: 3.5193 - Accuracy: 0.4706 - F1: 0.4341
sub_13:Test (Best Model) - Loss: 4.8206 - Accuracy: 0.2353 - F1: 0.1338
sub_14:Test (Best Model) - Loss: 2.2463 - Accuracy: 0.3529 - F1: 0.2523
sub_9:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.4118 - F1: 0.3502
sub_8:Test (Best Model) - Loss: 0.5401 - Accuracy: 0.7941 - F1: 0.8060
sub_10:Test (Best Model) - Loss: 3.5637 - Accuracy: 0.3676 - F1: 0.3933
sub_3:Test (Best Model) - Loss: 3.0287 - Accuracy: 0.4853 - F1: 0.4341
sub_7:Test (Best Model) - Loss: 0.4194 - Accuracy: 0.8088 - F1: 0.8017
sub_6:Test (Best Model) - Loss: 2.8790 - Accuracy: 0.3824 - F1: 0.2987
sub_4:Test (Best Model) - Loss: 5.8172 - Accuracy: 0.4348 - F1: 0.2959
sub_1:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.4853 - F1: 0.4271
sub_12:Test (Best Model) - Loss: 3.0396 - Accuracy: 0.4265 - F1: 0.4025
sub_11:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.7246 - F1: 0.7286
sub_10:Test (Best Model) - Loss: 3.6026 - Accuracy: 0.3382 - F1: 0.2699
sub_8:Test (Best Model) - Loss: 0.9097 - Accuracy: 0.4265 - F1: 0.3584
sub_3:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.3913 - F1: 0.3551
sub_6:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.3824 - F1: 0.2987
sub_2:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.7101 - F1: 0.6921
sub_4:Test (Best Model) - Loss: 1.2110 - Accuracy: 0.3913 - F1: 0.2863
sub_1:Test (Best Model) - Loss: 1.9902 - Accuracy: 0.4348 - F1: 0.3438
sub_14:Test (Best Model) - Loss: 0.5166 - Accuracy: 0.8088 - F1: 0.8010
sub_15:Test (Best Model) - Loss: 0.9539 - Accuracy: 0.6176 - F1: 0.6385
sub_10:Test (Best Model) - Loss: 0.9994 - Accuracy: 0.4118 - F1: 0.3883
sub_12:Test (Best Model) - Loss: 1.3419 - Accuracy: 0.4559 - F1: 0.4269
sub_13:Test (Best Model) - Loss: 1.3320 - Accuracy: 0.4118 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 1.2616 - Accuracy: 0.5735 - F1: 0.5708
sub_5:Test (Best Model) - Loss: 2.7485 - Accuracy: 0.6324 - F1: 0.6167
sub_11:Test (Best Model) - Loss: 1.0775 - Accuracy: 0.4928 - F1: 0.4649
sub_2:Test (Best Model) - Loss: 0.4879 - Accuracy: 0.7059 - F1: 0.6903
sub_9:Test (Best Model) - Loss: 1.0770 - Accuracy: 0.6618 - F1: 0.5922
sub_8:Test (Best Model) - Loss: 0.5779 - Accuracy: 0.7206 - F1: 0.7190
sub_13:Test (Best Model) - Loss: 0.8796 - Accuracy: 0.4493 - F1: 0.3395
sub_6:Test (Best Model) - Loss: 2.1583 - Accuracy: 0.4265 - F1: 0.3645
sub_3:Test (Best Model) - Loss: 4.5870 - Accuracy: 0.3623 - F1: 0.2953
sub_4:Test (Best Model) - Loss: 0.3108 - Accuracy: 0.8261 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 1.1426 - Accuracy: 0.3824 - F1: 0.3034
sub_6:Test (Best Model) - Loss: 0.8886 - Accuracy: 0.6087 - F1: 0.5408
sub_5:Test (Best Model) - Loss: 0.5587 - Accuracy: 0.7206 - F1: 0.7149
sub_12:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.4058 - F1: 0.3388
sub_1:Test (Best Model) - Loss: 2.7392 - Accuracy: 0.3913 - F1: 0.3029
sub_10:Test (Best Model) - Loss: 1.7665 - Accuracy: 0.3824 - F1: 0.3460
sub_13:Test (Best Model) - Loss: 2.4452 - Accuracy: 0.3333 - F1: 0.2153
sub_7:Test (Best Model) - Loss: 5.9644 - Accuracy: 0.4412 - F1: 0.3524
sub_15:Test (Best Model) - Loss: 0.7274 - Accuracy: 0.6765 - F1: 0.6045
sub_2:Test (Best Model) - Loss: 1.1829 - Accuracy: 0.5147 - F1: 0.4867
sub_8:Test (Best Model) - Loss: 0.4675 - Accuracy: 0.7794 - F1: 0.7883
sub_14:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.6471 - F1: 0.6036
sub_6:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.3478 - F1: 0.2700
sub_11:Test (Best Model) - Loss: 1.9196 - Accuracy: 0.5072 - F1: 0.4494
sub_9:Test (Best Model) - Loss: 1.6449 - Accuracy: 0.5147 - F1: 0.5026
sub_1:Test (Best Model) - Loss: 1.7157 - Accuracy: 0.4058 - F1: 0.3169
sub_13:Test (Best Model) - Loss: 1.3430 - Accuracy: 0.5507 - F1: 0.4488
sub_3:Test (Best Model) - Loss: 1.9268 - Accuracy: 0.5507 - F1: 0.4646
sub_6:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.3478 - F1: 0.2724
sub_4:Test (Best Model) - Loss: 0.8621 - Accuracy: 0.5217 - F1: 0.5062
sub_12:Test (Best Model) - Loss: 1.5081 - Accuracy: 0.4783 - F1: 0.3950
sub_5:Test (Best Model) - Loss: 0.8885 - Accuracy: 0.5294 - F1: 0.5217
sub_8:Test (Best Model) - Loss: 0.8760 - Accuracy: 0.5000 - F1: 0.5210
sub_9:Test (Best Model) - Loss: 1.1811 - Accuracy: 0.5294 - F1: 0.5116
sub_7:Test (Best Model) - Loss: 2.6614 - Accuracy: 0.3676 - F1: 0.2952
sub_2:Test (Best Model) - Loss: 1.7820 - Accuracy: 0.4412 - F1: 0.2939
sub_1:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.4348 - F1: 0.3438
sub_15:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.7206 - F1: 0.7078
sub_11:Test (Best Model) - Loss: 1.7291 - Accuracy: 0.4783 - F1: 0.4097
sub_6:Test (Best Model) - Loss: 1.1493 - Accuracy: 0.4348 - F1: 0.4127
sub_10:Test (Best Model) - Loss: 2.8242 - Accuracy: 0.5147 - F1: 0.4921
sub_14:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.7059 - F1: 0.7172
sub_8:Test (Best Model) - Loss: 0.3248 - Accuracy: 0.8235 - F1: 0.8327
sub_13:Test (Best Model) - Loss: 1.5149 - Accuracy: 0.5507 - F1: 0.5269
sub_6:Test (Best Model) - Loss: 1.5554 - Accuracy: 0.3333 - F1: 0.2389
sub_9:Test (Best Model) - Loss: 0.8019 - Accuracy: 0.7059 - F1: 0.6312
sub_15:Test (Best Model) - Loss: 1.7555 - Accuracy: 0.3971 - F1: 0.3207
sub_3:Test (Best Model) - Loss: 3.5914 - Accuracy: 0.6377 - F1: 0.6002
sub_2:Test (Best Model) - Loss: 0.9997 - Accuracy: 0.4559 - F1: 0.4034
sub_10:Test (Best Model) - Loss: 1.5137 - Accuracy: 0.3529 - F1: 0.3478
sub_5:Test (Best Model) - Loss: 2.2712 - Accuracy: 0.4118 - F1: 0.3773
sub_11:Test (Best Model) - Loss: 1.9679 - Accuracy: 0.4203 - F1: 0.3997
sub_7:Test (Best Model) - Loss: 1.5135 - Accuracy: 0.5735 - F1: 0.5023
sub_13:Test (Best Model) - Loss: 4.2625 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 2.4643 - Accuracy: 0.4783 - F1: 0.4207
sub_2:Test (Best Model) - Loss: 1.1770 - Accuracy: 0.5000 - F1: 0.4745
sub_1:Test (Best Model) - Loss: 2.2567 - Accuracy: 0.4348 - F1: 0.3422
sub_9:Test (Best Model) - Loss: 0.9812 - Accuracy: 0.6176 - F1: 0.6264
sub_4:Test (Best Model) - Loss: 3.9299 - Accuracy: 0.5072 - F1: 0.3823
sub_6:Test (Best Model) - Loss: 1.0521 - Accuracy: 0.6522 - F1: 0.6304
sub_13:Test (Best Model) - Loss: 3.1831 - Accuracy: 0.3235 - F1: 0.2280
sub_8:Test (Best Model) - Loss: 0.9680 - Accuracy: 0.6618 - F1: 0.6083
sub_3:Test (Best Model) - Loss: 2.1336 - Accuracy: 0.4928 - F1: 0.4737
sub_9:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.2794 - F1: 0.1495
sub_1:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.7647 - F1: 0.7772
sub_14:Test (Best Model) - Loss: 0.9159 - Accuracy: 0.7206 - F1: 0.7244
sub_7:Test (Best Model) - Loss: 3.6569 - Accuracy: 0.4706 - F1: 0.3939
sub_5:Test (Best Model) - Loss: 0.8891 - Accuracy: 0.5588 - F1: 0.5708
sub_12:Test (Best Model) - Loss: 1.5861 - Accuracy: 0.4638 - F1: 0.4583
sub_15:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6765 - F1: 0.6738
sub_6:Test (Best Model) - Loss: 1.3008 - Accuracy: 0.5072 - F1: 0.4704
sub_3:Test (Best Model) - Loss: 4.0554 - Accuracy: 0.4638 - F1: 0.3494
sub_11:Test (Best Model) - Loss: 3.3113 - Accuracy: 0.4493 - F1: 0.3973
sub_8:Test (Best Model) - Loss: 0.4322 - Accuracy: 0.8676 - F1: 0.8736
sub_7:Test (Best Model) - Loss: 5.1725 - Accuracy: 0.3971 - F1: 0.3312
sub_10:Test (Best Model) - Loss: 2.6773 - Accuracy: 0.5735 - F1: 0.5076
sub_4:Test (Best Model) - Loss: 0.3955 - Accuracy: 0.7391 - F1: 0.7063
sub_2:Test (Best Model) - Loss: 2.7623 - Accuracy: 0.4493 - F1: 0.4442
sub_13:Test (Best Model) - Loss: 3.7251 - Accuracy: 0.2647 - F1: 0.1950
sub_7:Test (Best Model) - Loss: 1.9400 - Accuracy: 0.2794 - F1: 0.1753
sub_10:Test (Best Model) - Loss: 1.1331 - Accuracy: 0.5217 - F1: 0.4771
sub_6:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.5217 - F1: 0.5277
sub_15:Test (Best Model) - Loss: 1.0631 - Accuracy: 0.5441 - F1: 0.5349
sub_1:Test (Best Model) - Loss: 0.7918 - Accuracy: 0.6912 - F1: 0.6790
sub_5:Test (Best Model) - Loss: 1.1100 - Accuracy: 0.5882 - F1: 0.5828
sub_14:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.7500 - F1: 0.7215
sub_2:Test (Best Model) - Loss: 4.2954 - Accuracy: 0.3478 - F1: 0.2540
sub_4:Test (Best Model) - Loss: 0.4961 - Accuracy: 0.7536 - F1: 0.7484
sub_9:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.5588 - F1: 0.4844
sub_6:Test (Best Model) - Loss: 1.0573 - Accuracy: 0.4203 - F1: 0.3315
sub_12:Test (Best Model) - Loss: 2.0702 - Accuracy: 0.4928 - F1: 0.4099
sub_8:Test (Best Model) - Loss: 1.1575 - Accuracy: 0.6176 - F1: 0.6483
sub_3:Test (Best Model) - Loss: 2.1732 - Accuracy: 0.4348 - F1: 0.3485
sub_11:Test (Best Model) - Loss: 3.6233 - Accuracy: 0.3333 - F1: 0.2889
sub_14:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.4706 - F1: 0.4283
sub_10:Test (Best Model) - Loss: 2.9447 - Accuracy: 0.4203 - F1: 0.3259
sub_9:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.3824 - F1: 0.2987
sub_13:Test (Best Model) - Loss: 3.1790 - Accuracy: 0.2206 - F1: 0.1465
sub_6:Test (Best Model) - Loss: 1.0602 - Accuracy: 0.6087 - F1: 0.6133
sub_5:Test (Best Model) - Loss: 2.1007 - Accuracy: 0.4265 - F1: 0.3735
sub_15:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.6324 - F1: 0.5835
sub_14:Test (Best Model) - Loss: 1.4212 - Accuracy: 0.3676 - F1: 0.2944
sub_3:Test (Best Model) - Loss: 2.4713 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.9212 - Accuracy: 0.6957 - F1: 0.6515
sub_12:Test (Best Model) - Loss: 1.1995 - Accuracy: 0.4265 - F1: 0.3350
sub_1:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.7500 - F1: 0.7669
sub_7:Test (Best Model) - Loss: 1.5845 - Accuracy: 0.6912 - F1: 0.6155
sub_8:Test (Best Model) - Loss: 1.4931 - Accuracy: 0.6471 - F1: 0.6102
sub_2:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.4493 - F1: 0.4685
sub_15:Test (Best Model) - Loss: 1.1879 - Accuracy: 0.3824 - F1: 0.3034
sub_12:Test (Best Model) - Loss: 0.9514 - Accuracy: 0.4559 - F1: 0.3813
sub_11:Test (Best Model) - Loss: 1.6192 - Accuracy: 0.5652 - F1: 0.5339
sub_2:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.3768 - F1: 0.2878
sub_12:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.6176 - F1: 0.5856
sub_4:Test (Best Model) - Loss: 1.5844 - Accuracy: 0.6667 - F1: 0.6009
sub_2:Test (Best Model) - Loss: 1.6941 - Accuracy: 0.3478 - F1: 0.2568
sub_5:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.7206 - F1: 0.6760
sub_3:Test (Best Model) - Loss: 5.3298 - Accuracy: 0.5942 - F1: 0.5462
sub_8:Test (Best Model) - Loss: 1.0263 - Accuracy: 0.4412 - F1: 0.3832
sub_10:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.7681 - F1: 0.7781
sub_13:Test (Best Model) - Loss: 5.1873 - Accuracy: 0.3676 - F1: 0.2842
sub_14:Test (Best Model) - Loss: 1.8480 - Accuracy: 0.3529 - F1: 0.2681
sub_7:Test (Best Model) - Loss: 2.1629 - Accuracy: 0.5294 - F1: 0.4953
sub_15:Test (Best Model) - Loss: 1.0027 - Accuracy: 0.6912 - F1: 0.6748
sub_12:Test (Best Model) - Loss: 2.7226 - Accuracy: 0.2647 - F1: 0.1139
sub_1:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.6912 - F1: 0.6931
sub_11:Test (Best Model) - Loss: 3.2574 - Accuracy: 0.4203 - F1: 0.3607
sub_7:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.4412 - F1: 0.4753
sub_10:Test (Best Model) - Loss: 0.9955 - Accuracy: 0.6667 - F1: 0.6335
sub_3:Test (Best Model) - Loss: 1.0907 - Accuracy: 0.6957 - F1: 0.6953
sub_4:Test (Best Model) - Loss: 0.3705 - Accuracy: 0.7826 - F1: 0.7902
sub_13:Test (Best Model) - Loss: 7.3331 - Accuracy: 0.3235 - F1: 0.2311
sub_15:Test (Best Model) - Loss: 1.7525 - Accuracy: 0.3824 - F1: 0.3138
sub_10:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.4493 - F1: 0.4091
sub_12:Test (Best Model) - Loss: 1.0572 - Accuracy: 0.4559 - F1: 0.3998
sub_5:Test (Best Model) - Loss: 1.7134 - Accuracy: 0.5588 - F1: 0.5150
sub_14:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.7206 - F1: 0.6742
sub_4:Test (Best Model) - Loss: 0.9977 - Accuracy: 0.6522 - F1: 0.5975
sub_5:Test (Best Model) - Loss: 1.2467 - Accuracy: 0.6029 - F1: 0.5527
sub_15:Test (Best Model) - Loss: 0.8729 - Accuracy: 0.5147 - F1: 0.4999
sub_7:Test (Best Model) - Loss: 3.4642 - Accuracy: 0.6176 - F1: 0.5175
sub_1:Test (Best Model) - Loss: 0.3499 - Accuracy: 0.8382 - F1: 0.8488
sub_14:Test (Best Model) - Loss: 0.8296 - Accuracy: 0.7794 - F1: 0.7751
sub_5:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.6618 - F1: 0.6117
sub_19:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4559 - F1: 0.4038
sub_24:Test (Best Model) - Loss: 1.3505 - Accuracy: 0.3235 - F1: 0.2877
sub_20:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.6176 - F1: 0.5749
sub_26:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6957 - F1: 0.7113
sub_23:Test (Best Model) - Loss: 1.0697 - Accuracy: 0.3768 - F1: 0.3143
sub_22:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.5588 - F1: 0.5307
sub_29:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.5294 - F1: 0.4881
sub_25:Test (Best Model) - Loss: 1.0321 - Accuracy: 0.7826 - F1: 0.7773
sub_20:Test (Best Model) - Loss: 1.1918 - Accuracy: 0.4265 - F1: 0.3926
sub_16:Test (Best Model) - Loss: 1.6752 - Accuracy: 0.3382 - F1: 0.3420
sub_28:Test (Best Model) - Loss: 1.4446 - Accuracy: 0.4706 - F1: 0.4677
sub_18:Test (Best Model) - Loss: 1.2081 - Accuracy: 0.6812 - F1: 0.6274
sub_17:Test (Best Model) - Loss: 0.9250 - Accuracy: 0.6957 - F1: 0.6957
sub_21:Test (Best Model) - Loss: 1.0918 - Accuracy: 0.6029 - F1: 0.5733
sub_19:Test (Best Model) - Loss: 2.8798 - Accuracy: 0.3235 - F1: 0.2144
sub_27:Test (Best Model) - Loss: 0.9250 - Accuracy: 0.6957 - F1: 0.6957
sub_23:Test (Best Model) - Loss: 1.1692 - Accuracy: 0.2899 - F1: 0.2879
sub_29:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.3971 - F1: 0.3157
sub_26:Test (Best Model) - Loss: 0.8663 - Accuracy: 0.6232 - F1: 0.6302
sub_17:Test (Best Model) - Loss: 1.0057 - Accuracy: 0.5072 - F1: 0.4741
sub_27:Test (Best Model) - Loss: 1.0057 - Accuracy: 0.5072 - F1: 0.4741
sub_20:Test (Best Model) - Loss: 1.7302 - Accuracy: 0.4118 - F1: 0.3588
sub_19:Test (Best Model) - Loss: 3.0793 - Accuracy: 0.3382 - F1: 0.2694
sub_23:Test (Best Model) - Loss: 1.5537 - Accuracy: 0.3913 - F1: 0.3173
sub_18:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.7971 - F1: 0.7943
sub_24:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6618 - F1: 0.6584
sub_29:Test (Best Model) - Loss: 1.1058 - Accuracy: 0.5441 - F1: 0.4828
sub_25:Test (Best Model) - Loss: 1.0050 - Accuracy: 0.7246 - F1: 0.7011
sub_22:Test (Best Model) - Loss: 2.1669 - Accuracy: 0.5441 - F1: 0.5123
sub_28:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.5441 - F1: 0.5296
sub_23:Test (Best Model) - Loss: 1.2459 - Accuracy: 0.3913 - F1: 0.3161
sub_18:Test (Best Model) - Loss: 0.9286 - Accuracy: 0.4783 - F1: 0.4479
sub_21:Test (Best Model) - Loss: 1.0239 - Accuracy: 0.4853 - F1: 0.4024
sub_16:Test (Best Model) - Loss: 2.7473 - Accuracy: 0.3088 - F1: 0.2838
sub_17:Test (Best Model) - Loss: 1.0653 - Accuracy: 0.4348 - F1: 0.3490
sub_23:Test (Best Model) - Loss: 1.1191 - Accuracy: 0.3913 - F1: 0.3181
sub_27:Test (Best Model) - Loss: 1.0653 - Accuracy: 0.4348 - F1: 0.3490
sub_29:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.3676 - F1: 0.2967
sub_19:Test (Best Model) - Loss: 3.9490 - Accuracy: 0.3088 - F1: 0.2600
sub_20:Test (Best Model) - Loss: 0.8670 - Accuracy: 0.6029 - F1: 0.6094
sub_23:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.3824 - F1: 0.2972
sub_25:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.8696 - F1: 0.8694
sub_26:Test (Best Model) - Loss: 0.9198 - Accuracy: 0.6522 - F1: 0.6273
sub_24:Test (Best Model) - Loss: 0.5252 - Accuracy: 0.7500 - F1: 0.7472
sub_28:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.7059 - F1: 0.6977
sub_21:Test (Best Model) - Loss: 1.0598 - Accuracy: 0.5294 - F1: 0.4737
sub_17:Test (Best Model) - Loss: 1.0532 - Accuracy: 0.4203 - F1: 0.3383
sub_27:Test (Best Model) - Loss: 1.0532 - Accuracy: 0.4203 - F1: 0.3383
sub_22:Test (Best Model) - Loss: 2.9775 - Accuracy: 0.5147 - F1: 0.4953
sub_23:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.3529 - F1: 0.2887
sub_18:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.7101 - F1: 0.6996
sub_16:Test (Best Model) - Loss: 3.0759 - Accuracy: 0.2941 - F1: 0.2966
sub_26:Test (Best Model) - Loss: 0.9450 - Accuracy: 0.4493 - F1: 0.3818
sub_29:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.5441 - F1: 0.5259
sub_20:Test (Best Model) - Loss: 5.6339 - Accuracy: 0.3529 - F1: 0.2786
sub_23:Test (Best Model) - Loss: 1.6199 - Accuracy: 0.3676 - F1: 0.2806
sub_22:Test (Best Model) - Loss: 1.2457 - Accuracy: 0.3676 - F1: 0.3239
sub_17:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.6522 - F1: 0.6451
sub_24:Test (Best Model) - Loss: 0.7451 - Accuracy: 0.7059 - F1: 0.7013
sub_19:Test (Best Model) - Loss: 4.2497 - Accuracy: 0.2794 - F1: 0.2367
sub_25:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.7391 - F1: 0.7364
sub_27:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.6522 - F1: 0.6451
sub_29:Test (Best Model) - Loss: 0.9383 - Accuracy: 0.4706 - F1: 0.3750
sub_17:Test (Best Model) - Loss: 1.2419 - Accuracy: 0.4058 - F1: 0.3755
sub_18:Test (Best Model) - Loss: 0.7785 - Accuracy: 0.6667 - F1: 0.6431
sub_28:Test (Best Model) - Loss: 1.7371 - Accuracy: 0.4706 - F1: 0.4524
sub_21:Test (Best Model) - Loss: 0.8820 - Accuracy: 0.7647 - F1: 0.7724
sub_27:Test (Best Model) - Loss: 1.2419 - Accuracy: 0.4058 - F1: 0.3755
sub_26:Test (Best Model) - Loss: 0.9478 - Accuracy: 0.6232 - F1: 0.6112
sub_22:Test (Best Model) - Loss: 4.8859 - Accuracy: 0.4412 - F1: 0.3393
sub_25:Test (Best Model) - Loss: 4.1553 - Accuracy: 0.3768 - F1: 0.2972
sub_19:Test (Best Model) - Loss: 1.5755 - Accuracy: 0.5882 - F1: 0.5774
sub_24:Test (Best Model) - Loss: 0.7045 - Accuracy: 0.7794 - F1: 0.7888
sub_16:Test (Best Model) - Loss: 3.6475 - Accuracy: 0.4706 - F1: 0.3944
sub_18:Test (Best Model) - Loss: 0.9167 - Accuracy: 0.4559 - F1: 0.3657
sub_21:Test (Best Model) - Loss: 1.0636 - Accuracy: 0.4706 - F1: 0.3543
sub_23:Test (Best Model) - Loss: 1.0375 - Accuracy: 0.3382 - F1: 0.3493
sub_17:Test (Best Model) - Loss: 1.9761 - Accuracy: 0.3768 - F1: 0.2878
sub_26:Test (Best Model) - Loss: 0.9914 - Accuracy: 0.4559 - F1: 0.3808
sub_29:Test (Best Model) - Loss: 0.9648 - Accuracy: 0.4118 - F1: 0.3828
sub_20:Test (Best Model) - Loss: 0.7403 - Accuracy: 0.7353 - F1: 0.6877
sub_27:Test (Best Model) - Loss: 1.9761 - Accuracy: 0.3768 - F1: 0.2878
sub_22:Test (Best Model) - Loss: 0.8627 - Accuracy: 0.5797 - F1: 0.5683
sub_28:Test (Best Model) - Loss: 1.8865 - Accuracy: 0.4706 - F1: 0.3776
sub_17:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.3623 - F1: 0.2730
sub_16:Test (Best Model) - Loss: 5.1779 - Accuracy: 0.3088 - F1: 0.2007
sub_24:Test (Best Model) - Loss: 1.0835 - Accuracy: 0.6471 - F1: 0.6073
sub_25:Test (Best Model) - Loss: 2.8362 - Accuracy: 0.5147 - F1: 0.5062
sub_19:Test (Best Model) - Loss: 1.2220 - Accuracy: 0.4853 - F1: 0.4549
sub_27:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.3623 - F1: 0.2730
sub_23:Test (Best Model) - Loss: 2.2129 - Accuracy: 0.3971 - F1: 0.3384
sub_28:Test (Best Model) - Loss: 3.8152 - Accuracy: 0.0882 - F1: 0.0602
sub_20:Test (Best Model) - Loss: 0.9701 - Accuracy: 0.5441 - F1: 0.5357
sub_29:Test (Best Model) - Loss: 1.1927 - Accuracy: 0.4706 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 1.1156 - Accuracy: 0.5072 - F1: 0.4505
sub_18:Test (Best Model) - Loss: 0.6022 - Accuracy: 0.8676 - F1: 0.8589
sub_26:Test (Best Model) - Loss: 1.4871 - Accuracy: 0.4853 - F1: 0.4390
sub_21:Test (Best Model) - Loss: 0.7309 - Accuracy: 0.6912 - F1: 0.6504
sub_23:Test (Best Model) - Loss: 0.9954 - Accuracy: 0.5217 - F1: 0.4818
sub_19:Test (Best Model) - Loss: 1.0434 - Accuracy: 0.3971 - F1: 0.3601
sub_26:Test (Best Model) - Loss: 1.0523 - Accuracy: 0.4265 - F1: 0.3675
sub_24:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.7059 - F1: 0.6753
sub_23:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.4348 - F1: 0.3194
sub_16:Test (Best Model) - Loss: 5.7621 - Accuracy: 0.4412 - F1: 0.4217
sub_17:Test (Best Model) - Loss: 1.1548 - Accuracy: 0.3913 - F1: 0.4063
sub_28:Test (Best Model) - Loss: 3.8798 - Accuracy: 0.2059 - F1: 0.1892
sub_20:Test (Best Model) - Loss: 0.7420 - Accuracy: 0.6765 - F1: 0.6927
sub_25:Test (Best Model) - Loss: 2.8475 - Accuracy: 0.5735 - F1: 0.5223
sub_22:Test (Best Model) - Loss: 2.0847 - Accuracy: 0.4493 - F1: 0.3915
sub_27:Test (Best Model) - Loss: 1.1548 - Accuracy: 0.3913 - F1: 0.4063
sub_18:Test (Best Model) - Loss: 0.7673 - Accuracy: 0.7353 - F1: 0.7349
sub_19:Test (Best Model) - Loss: 0.9532 - Accuracy: 0.6912 - F1: 0.6933
sub_29:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.4559 - F1: 0.3675
sub_28:Test (Best Model) - Loss: 2.3533 - Accuracy: 0.2941 - F1: 0.1668
sub_23:Test (Best Model) - Loss: 0.9962 - Accuracy: 0.4348 - F1: 0.3438
sub_26:Test (Best Model) - Loss: 1.0062 - Accuracy: 0.4412 - F1: 0.3558
sub_21:Test (Best Model) - Loss: 1.2536 - Accuracy: 0.7353 - F1: 0.6612
sub_20:Test (Best Model) - Loss: 0.9345 - Accuracy: 0.5000 - F1: 0.5143
sub_17:Test (Best Model) - Loss: 3.4049 - Accuracy: 0.3478 - F1: 0.2695
sub_18:Test (Best Model) - Loss: 0.9634 - Accuracy: 0.4412 - F1: 0.3524
sub_16:Test (Best Model) - Loss: 6.9206 - Accuracy: 0.1618 - F1: 0.2149
sub_27:Test (Best Model) - Loss: 3.4049 - Accuracy: 0.3478 - F1: 0.2695
sub_24:Test (Best Model) - Loss: 1.0593 - Accuracy: 0.6029 - F1: 0.5650
sub_25:Test (Best Model) - Loss: 1.5905 - Accuracy: 0.4559 - F1: 0.3731
sub_26:Test (Best Model) - Loss: 1.1740 - Accuracy: 0.4412 - F1: 0.3788
sub_20:Test (Best Model) - Loss: 0.7544 - Accuracy: 0.7059 - F1: 0.6578
sub_17:Test (Best Model) - Loss: 1.1217 - Accuracy: 0.4118 - F1: 0.3506
sub_27:Test (Best Model) - Loss: 1.1217 - Accuracy: 0.4118 - F1: 0.3506
sub_22:Test (Best Model) - Loss: 1.0220 - Accuracy: 0.4928 - F1: 0.4556
sub_19:Test (Best Model) - Loss: 2.2232 - Accuracy: 0.3824 - F1: 0.3432
sub_23:Test (Best Model) - Loss: 3.0020 - Accuracy: 0.3623 - F1: 0.2850
sub_29:Test (Best Model) - Loss: 0.8343 - Accuracy: 0.5441 - F1: 0.5315
sub_28:Test (Best Model) - Loss: 3.3275 - Accuracy: 0.3824 - F1: 0.3638
sub_20:Test (Best Model) - Loss: 0.8203 - Accuracy: 0.8261 - F1: 0.8288
sub_26:Test (Best Model) - Loss: 2.9270 - Accuracy: 0.5588 - F1: 0.5027
sub_16:Test (Best Model) - Loss: 2.1946 - Accuracy: 0.5441 - F1: 0.5213
sub_18:Test (Best Model) - Loss: 1.0029 - Accuracy: 0.5735 - F1: 0.5647
sub_25:Test (Best Model) - Loss: 0.8015 - Accuracy: 0.7206 - F1: 0.7299
sub_24:Test (Best Model) - Loss: 1.1114 - Accuracy: 0.6324 - F1: 0.6505
sub_17:Test (Best Model) - Loss: 1.7677 - Accuracy: 0.6471 - F1: 0.5918
sub_22:Test (Best Model) - Loss: 1.7307 - Accuracy: 0.5072 - F1: 0.4884
sub_16:Test (Best Model) - Loss: 2.1436 - Accuracy: 0.3235 - F1: 0.3081
sub_27:Test (Best Model) - Loss: 1.7677 - Accuracy: 0.6471 - F1: 0.5918
sub_23:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.4058 - F1: 0.3318
sub_19:Test (Best Model) - Loss: 2.0150 - Accuracy: 0.5588 - F1: 0.5417
sub_21:Test (Best Model) - Loss: 0.8722 - Accuracy: 0.5882 - F1: 0.4700
sub_16:Test (Best Model) - Loss: 2.5052 - Accuracy: 0.2647 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.4928 - F1: 0.4931
sub_26:Test (Best Model) - Loss: 2.1726 - Accuracy: 0.5147 - F1: 0.4776
sub_20:Test (Best Model) - Loss: 0.8132 - Accuracy: 0.6377 - F1: 0.6170
sub_28:Test (Best Model) - Loss: 2.1537 - Accuracy: 0.3971 - F1: 0.3736
sub_25:Test (Best Model) - Loss: 3.2528 - Accuracy: 0.4265 - F1: 0.3629
sub_17:Test (Best Model) - Loss: 0.8878 - Accuracy: 0.6324 - F1: 0.6328
sub_18:Test (Best Model) - Loss: 2.7404 - Accuracy: 0.5000 - F1: 0.5010
sub_27:Test (Best Model) - Loss: 0.8878 - Accuracy: 0.6324 - F1: 0.6328
sub_22:Test (Best Model) - Loss: 5.8907 - Accuracy: 0.2500 - F1: 0.1807
sub_21:Test (Best Model) - Loss: 1.8492 - Accuracy: 0.6324 - F1: 0.5853
sub_19:Test (Best Model) - Loss: 1.8883 - Accuracy: 0.3382 - F1: 0.3411
sub_28:Test (Best Model) - Loss: 1.0755 - Accuracy: 0.5147 - F1: 0.4581
sub_26:Test (Best Model) - Loss: 2.3304 - Accuracy: 0.5441 - F1: 0.4870
sub_24:Test (Best Model) - Loss: 0.7445 - Accuracy: 0.8088 - F1: 0.8077
sub_29:Test (Best Model) - Loss: 0.7920 - Accuracy: 0.6812 - F1: 0.6099
sub_25:Test (Best Model) - Loss: 2.0962 - Accuracy: 0.5588 - F1: 0.5474
sub_17:Test (Best Model) - Loss: 0.9073 - Accuracy: 0.6471 - F1: 0.5967
sub_16:Test (Best Model) - Loss: 4.6456 - Accuracy: 0.3088 - F1: 0.2656
sub_27:Test (Best Model) - Loss: 0.9073 - Accuracy: 0.6471 - F1: 0.5967
sub_20:Test (Best Model) - Loss: 1.0668 - Accuracy: 0.5942 - F1: 0.5658
sub_29:Test (Best Model) - Loss: 0.9223 - Accuracy: 0.6522 - F1: 0.6027
sub_18:Test (Best Model) - Loss: 1.8544 - Accuracy: 0.6029 - F1: 0.5832
sub_24:Test (Best Model) - Loss: 4.0151 - Accuracy: 0.2794 - F1: 0.1805
sub_16:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2647 - F1: 0.1765
sub_22:Test (Best Model) - Loss: 2.0899 - Accuracy: 0.5441 - F1: 0.5232
sub_19:Test (Best Model) - Loss: 1.8768 - Accuracy: 0.6029 - F1: 0.5805
sub_28:Test (Best Model) - Loss: 0.9775 - Accuracy: 0.5000 - F1: 0.5014
sub_26:Test (Best Model) - Loss: 1.9883 - Accuracy: 0.5000 - F1: 0.4945
sub_17:Test (Best Model) - Loss: 0.8205 - Accuracy: 0.6176 - F1: 0.6048
sub_18:Test (Best Model) - Loss: 2.1345 - Accuracy: 0.5000 - F1: 0.5034
sub_16:Test (Best Model) - Loss: 3.3891 - Accuracy: 0.3088 - F1: 0.2507
sub_27:Test (Best Model) - Loss: 0.8205 - Accuracy: 0.6176 - F1: 0.6048
sub_21:Test (Best Model) - Loss: 4.8454 - Accuracy: 0.2647 - F1: 0.1250
sub_19:Test (Best Model) - Loss: 2.6563 - Accuracy: 0.4265 - F1: 0.3920
sub_25:Test (Best Model) - Loss: 1.1621 - Accuracy: 0.6324 - F1: 0.6292
sub_22:Test (Best Model) - Loss: 4.7982 - Accuracy: 0.2500 - F1: 0.1037
sub_29:Test (Best Model) - Loss: 1.9380 - Accuracy: 0.6522 - F1: 0.6347
sub_24:Test (Best Model) - Loss: 1.7956 - Accuracy: 0.4559 - F1: 0.4055
sub_20:Test (Best Model) - Loss: 0.7636 - Accuracy: 0.7536 - F1: 0.7614
sub_28:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.6029 - F1: 0.5629
sub_21:Test (Best Model) - Loss: 1.2304 - Accuracy: 0.4559 - F1: 0.3218
sub_16:Test (Best Model) - Loss: 4.5088 - Accuracy: 0.3235 - F1: 0.2665
sub_18:Test (Best Model) - Loss: 1.5069 - Accuracy: 0.5000 - F1: 0.4997
sub_19:Test (Best Model) - Loss: 2.0331 - Accuracy: 0.4706 - F1: 0.4554
sub_26:Test (Best Model) - Loss: 1.8062 - Accuracy: 0.5735 - F1: 0.5721
sub_25:Test (Best Model) - Loss: 1.8720 - Accuracy: 0.4118 - F1: 0.3466
sub_22:Test (Best Model) - Loss: 3.2052 - Accuracy: 0.3529 - F1: 0.3266
sub_16:Test (Best Model) - Loss: 2.1315 - Accuracy: 0.2941 - F1: 0.2809
sub_20:Test (Best Model) - Loss: 0.9386 - Accuracy: 0.7536 - F1: 0.7453
sub_24:Test (Best Model) - Loss: 2.5804 - Accuracy: 0.2941 - F1: 0.1641
sub_28:Test (Best Model) - Loss: 3.5517 - Accuracy: 0.4706 - F1: 0.3393
sub_29:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.6522 - F1: 0.6471
sub_21:Test (Best Model) - Loss: 2.3152 - Accuracy: 0.4265 - F1: 0.3491
sub_18:Test (Best Model) - Loss: 0.8900 - Accuracy: 0.4706 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 5.2546 - Accuracy: 0.4265 - F1: 0.3945
sub_24:Test (Best Model) - Loss: 7.4498 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.1300 - Accuracy: 0.5735 - F1: 0.4792
sub_21:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3824 - F1: 0.2517
sub_28:Test (Best Model) - Loss: 0.9601 - Accuracy: 0.5882 - F1: 0.5393
sub_25:Test (Best Model) - Loss: 1.0435 - Accuracy: 0.7794 - F1: 0.7864
sub_21:Test (Best Model) - Loss: 2.6964 - Accuracy: 0.3529 - F1: 0.2586
sub_24:Test (Best Model) - Loss: 4.3507 - Accuracy: 0.3382 - F1: 0.2589
sub_21:Test (Best Model) - Loss: 1.7817 - Accuracy: 0.6324 - F1: 0.5697

=== Summary Results ===

acc: 50.86 ± 7.72
F1: 46.38 ± 8.75
acc-in: 71.86 ± 9.36
F1-in: 68.65 ± 10.93
runing time: 2452.68 seconds
