lr: 0.001
sub_1:Test (Best Model) - Loss: 4.3883 - Accuracy: 0.6471 - F1: 0.6366
sub_2:Test (Best Model) - Loss: 4.8047 - Accuracy: 0.5507 - F1: 0.5508
sub_3:Test (Best Model) - Loss: 28.0920 - Accuracy: 0.6618 - F1: 0.6291
sub_1:Test (Best Model) - Loss: 7.4932 - Accuracy: 0.5735 - F1: 0.5717
sub_3:Test (Best Model) - Loss: 23.3473 - Accuracy: 0.5147 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 8.7406 - Accuracy: 0.5797 - F1: 0.5999
sub_1:Test (Best Model) - Loss: 24.1292 - Accuracy: 0.6912 - F1: 0.6652
sub_1:Test (Best Model) - Loss: 26.0619 - Accuracy: 0.6029 - F1: 0.6006
sub_2:Test (Best Model) - Loss: 4.8535 - Accuracy: 0.5507 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 19.9558 - Accuracy: 0.6029 - F1: 0.5552
sub_1:Test (Best Model) - Loss: 12.4434 - Accuracy: 0.5735 - F1: 0.5433
sub_2:Test (Best Model) - Loss: 14.2329 - Accuracy: 0.6087 - F1: 0.6257
sub_3:Test (Best Model) - Loss: 19.5601 - Accuracy: 0.5294 - F1: 0.5038
sub_2:Test (Best Model) - Loss: 5.5843 - Accuracy: 0.4058 - F1: 0.3932
sub_1:Test (Best Model) - Loss: 4.5606 - Accuracy: 0.5072 - F1: 0.5105
sub_3:Test (Best Model) - Loss: 30.8666 - Accuracy: 0.5000 - F1: 0.5063
sub_2:Test (Best Model) - Loss: 1.4865 - Accuracy: 0.6176 - F1: 0.6121
sub_1:Test (Best Model) - Loss: 4.4969 - Accuracy: 0.4783 - F1: 0.4991
sub_3:Test (Best Model) - Loss: 3.1971 - Accuracy: 0.6522 - F1: 0.6555
sub_1:Test (Best Model) - Loss: 3.5880 - Accuracy: 0.5217 - F1: 0.5398
sub_2:Test (Best Model) - Loss: 4.0671 - Accuracy: 0.5735 - F1: 0.5404
sub_2:Test (Best Model) - Loss: 2.9454 - Accuracy: 0.6029 - F1: 0.5495
sub_3:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.8406 - F1: 0.8448
sub_1:Test (Best Model) - Loss: 4.1550 - Accuracy: 0.4638 - F1: 0.4700
sub_2:Test (Best Model) - Loss: 3.4059 - Accuracy: 0.6471 - F1: 0.6006
sub_3:Test (Best Model) - Loss: 1.1713 - Accuracy: 0.7101 - F1: 0.7137
sub_1:Test (Best Model) - Loss: 26.7753 - Accuracy: 0.4203 - F1: 0.4374
sub_3:Test (Best Model) - Loss: 1.6464 - Accuracy: 0.6812 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 1.9379 - Accuracy: 0.6618 - F1: 0.6499
sub_1:Test (Best Model) - Loss: 2.8054 - Accuracy: 0.6618 - F1: 0.6042
sub_3:Test (Best Model) - Loss: 3.2868 - Accuracy: 0.6812 - F1: 0.6864
sub_2:Test (Best Model) - Loss: 2.4494 - Accuracy: 0.5507 - F1: 0.5426
sub_1:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.6765 - F1: 0.6265
sub_3:Test (Best Model) - Loss: 7.9572 - Accuracy: 0.6232 - F1: 0.6029
sub_2:Test (Best Model) - Loss: 4.1777 - Accuracy: 0.4493 - F1: 0.4159
sub_1:Test (Best Model) - Loss: 1.1699 - Accuracy: 0.6324 - F1: 0.5667
sub_3:Test (Best Model) - Loss: 8.4066 - Accuracy: 0.5797 - F1: 0.5595
sub_2:Test (Best Model) - Loss: 8.8574 - Accuracy: 0.5362 - F1: 0.4734
sub_1:Test (Best Model) - Loss: 2.8682 - Accuracy: 0.6324 - F1: 0.5716
sub_3:Test (Best Model) - Loss: 8.3698 - Accuracy: 0.6377 - F1: 0.6095
sub_2:Test (Best Model) - Loss: 12.5137 - Accuracy: 0.3913 - F1: 0.3498
sub_1:Test (Best Model) - Loss: 0.9778 - Accuracy: 0.6912 - F1: 0.6382
sub_2:Test (Best Model) - Loss: 2.1747 - Accuracy: 0.5652 - F1: 0.5061
sub_3:Test (Best Model) - Loss: 8.3717 - Accuracy: 0.6087 - F1: 0.5862
sub_3:Test (Best Model) - Loss: 13.0694 - Accuracy: 0.6812 - F1: 0.6627
sub_5:Test (Best Model) - Loss: 78.6215 - Accuracy: 0.4706 - F1: 0.3630
sub_4:Test (Best Model) - Loss: 4.2286 - Accuracy: 0.6377 - F1: 0.6461
sub_6:Test (Best Model) - Loss: 4.4348 - Accuracy: 0.5147 - F1: 0.4857
sub_6:Test (Best Model) - Loss: 12.4703 - Accuracy: 0.4853 - F1: 0.4243
sub_5:Test (Best Model) - Loss: 86.0120 - Accuracy: 0.5147 - F1: 0.4643
sub_4:Test (Best Model) - Loss: 2.6686 - Accuracy: 0.5507 - F1: 0.5551
sub_6:Test (Best Model) - Loss: 3.5036 - Accuracy: 0.5147 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 2.7314 - Accuracy: 0.6232 - F1: 0.6205
sub_5:Test (Best Model) - Loss: 112.9150 - Accuracy: 0.4706 - F1: 0.4276
sub_4:Test (Best Model) - Loss: 2.3332 - Accuracy: 0.5797 - F1: 0.5799
sub_6:Test (Best Model) - Loss: 22.6712 - Accuracy: 0.4412 - F1: 0.3949
sub_4:Test (Best Model) - Loss: 3.5646 - Accuracy: 0.5797 - F1: 0.5952
sub_5:Test (Best Model) - Loss: 107.2559 - Accuracy: 0.5294 - F1: 0.4364
sub_4:Test (Best Model) - Loss: 9.2401 - Accuracy: 0.4058 - F1: 0.2896
sub_6:Test (Best Model) - Loss: 13.2154 - Accuracy: 0.4118 - F1: 0.3661
sub_4:Test (Best Model) - Loss: 5.2377 - Accuracy: 0.5362 - F1: 0.4956
sub_5:Test (Best Model) - Loss: 64.2668 - Accuracy: 0.3971 - F1: 0.3143
sub_6:Test (Best Model) - Loss: 6.5276 - Accuracy: 0.5072 - F1: 0.4921
sub_4:Test (Best Model) - Loss: 5.0856 - Accuracy: 0.5652 - F1: 0.5313
sub_6:Test (Best Model) - Loss: 6.4663 - Accuracy: 0.4348 - F1: 0.4167
sub_5:Test (Best Model) - Loss: 5.3907 - Accuracy: 0.5882 - F1: 0.5749
sub_6:Test (Best Model) - Loss: 7.2549 - Accuracy: 0.4348 - F1: 0.4033
sub_4:Test (Best Model) - Loss: 6.2290 - Accuracy: 0.4638 - F1: 0.4600
sub_5:Test (Best Model) - Loss: 13.2498 - Accuracy: 0.3235 - F1: 0.2306
sub_6:Test (Best Model) - Loss: 9.5130 - Accuracy: 0.4928 - F1: 0.4726
sub_4:Test (Best Model) - Loss: 3.7634 - Accuracy: 0.4348 - F1: 0.3337
sub_4:Test (Best Model) - Loss: 7.1277 - Accuracy: 0.5217 - F1: 0.4476
sub_5:Test (Best Model) - Loss: 8.8874 - Accuracy: 0.6176 - F1: 0.5986
sub_6:Test (Best Model) - Loss: 17.7853 - Accuracy: 0.5507 - F1: 0.5532
sub_6:Test (Best Model) - Loss: 2.4039 - Accuracy: 0.5652 - F1: 0.5686
sub_4:Test (Best Model) - Loss: 6.4210 - Accuracy: 0.6087 - F1: 0.5773
sub_5:Test (Best Model) - Loss: 13.6668 - Accuracy: 0.4265 - F1: 0.3724
sub_6:Test (Best Model) - Loss: 4.7077 - Accuracy: 0.6087 - F1: 0.5431
sub_5:Test (Best Model) - Loss: 8.6648 - Accuracy: 0.5882 - F1: 0.5704
sub_4:Test (Best Model) - Loss: 7.0657 - Accuracy: 0.6087 - F1: 0.5706
sub_5:Test (Best Model) - Loss: 4.7023 - Accuracy: 0.3971 - F1: 0.3671
sub_6:Test (Best Model) - Loss: 7.1822 - Accuracy: 0.5217 - F1: 0.4929
sub_5:Test (Best Model) - Loss: 1.5407 - Accuracy: 0.6765 - F1: 0.6692
sub_4:Test (Best Model) - Loss: 16.6916 - Accuracy: 0.6087 - F1: 0.5609
sub_6:Test (Best Model) - Loss: 3.7061 - Accuracy: 0.5507 - F1: 0.5236
sub_5:Test (Best Model) - Loss: 2.2525 - Accuracy: 0.5588 - F1: 0.5457
sub_4:Test (Best Model) - Loss: 12.6467 - Accuracy: 0.5652 - F1: 0.5163
sub_6:Test (Best Model) - Loss: 15.7284 - Accuracy: 0.5217 - F1: 0.4395
sub_5:Test (Best Model) - Loss: 1.9424 - Accuracy: 0.7206 - F1: 0.7098
sub_5:Test (Best Model) - Loss: 2.7289 - Accuracy: 0.6765 - F1: 0.6530
sub_7:Test (Best Model) - Loss: 3.2820 - Accuracy: 0.5000 - F1: 0.4889
sub_8:Test (Best Model) - Loss: 9.3431 - Accuracy: 0.5000 - F1: 0.4273
sub_9:Test (Best Model) - Loss: 5.6333 - Accuracy: 0.3824 - F1: 0.3565
sub_9:Test (Best Model) - Loss: 7.2068 - Accuracy: 0.2794 - F1: 0.3180
sub_8:Test (Best Model) - Loss: 6.7905 - Accuracy: 0.5147 - F1: 0.4581
sub_7:Test (Best Model) - Loss: 3.8113 - Accuracy: 0.5882 - F1: 0.5696
sub_9:Test (Best Model) - Loss: 6.5899 - Accuracy: 0.3382 - F1: 0.3569
sub_8:Test (Best Model) - Loss: 5.7062 - Accuracy: 0.4559 - F1: 0.4018
sub_7:Test (Best Model) - Loss: 3.7111 - Accuracy: 0.6324 - F1: 0.6063
sub_9:Test (Best Model) - Loss: 7.6985 - Accuracy: 0.3824 - F1: 0.3970
sub_8:Test (Best Model) - Loss: 21.4233 - Accuracy: 0.4412 - F1: 0.3586
sub_7:Test (Best Model) - Loss: 5.6942 - Accuracy: 0.5000 - F1: 0.4475
sub_9:Test (Best Model) - Loss: 5.9000 - Accuracy: 0.2647 - F1: 0.2702
sub_8:Test (Best Model) - Loss: 9.4295 - Accuracy: 0.4559 - F1: 0.3416
sub_9:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.6912 - F1: 0.6787
sub_7:Test (Best Model) - Loss: 6.5946 - Accuracy: 0.4412 - F1: 0.4359
sub_8:Test (Best Model) - Loss: 7.3706 - Accuracy: 0.5441 - F1: 0.5438
sub_7:Test (Best Model) - Loss: 2.7239 - Accuracy: 0.5882 - F1: 0.6027
sub_8:Test (Best Model) - Loss: 12.8357 - Accuracy: 0.6029 - F1: 0.5650
sub_9:Test (Best Model) - Loss: 4.2744 - Accuracy: 0.5000 - F1: 0.4506
sub_7:Test (Best Model) - Loss: 3.7417 - Accuracy: 0.5882 - F1: 0.6040
sub_8:Test (Best Model) - Loss: 6.1235 - Accuracy: 0.6029 - F1: 0.6221
sub_9:Test (Best Model) - Loss: 2.0614 - Accuracy: 0.4412 - F1: 0.4030
sub_7:Test (Best Model) - Loss: 7.9525 - Accuracy: 0.5882 - F1: 0.5792
sub_8:Test (Best Model) - Loss: 10.5517 - Accuracy: 0.6029 - F1: 0.6022
sub_9:Test (Best Model) - Loss: 5.3026 - Accuracy: 0.4559 - F1: 0.3902
sub_7:Test (Best Model) - Loss: 11.6152 - Accuracy: 0.6029 - F1: 0.6043
sub_8:Test (Best Model) - Loss: 5.4743 - Accuracy: 0.5588 - F1: 0.5733
sub_9:Test (Best Model) - Loss: 20.0692 - Accuracy: 0.5735 - F1: 0.5667
sub_8:Test (Best Model) - Loss: 14.0224 - Accuracy: 0.5441 - F1: 0.4929
sub_9:Test (Best Model) - Loss: 13.8025 - Accuracy: 0.3676 - F1: 0.3420
sub_7:Test (Best Model) - Loss: 5.7516 - Accuracy: 0.5588 - F1: 0.5814
sub_7:Test (Best Model) - Loss: 5.8393 - Accuracy: 0.5441 - F1: 0.5519
sub_8:Test (Best Model) - Loss: 14.8492 - Accuracy: 0.5588 - F1: 0.5487
sub_9:Test (Best Model) - Loss: 27.0757 - Accuracy: 0.4559 - F1: 0.3799
sub_7:Test (Best Model) - Loss: 8.7846 - Accuracy: 0.5882 - F1: 0.5775
sub_8:Test (Best Model) - Loss: 23.3403 - Accuracy: 0.5588 - F1: 0.5064
sub_9:Test (Best Model) - Loss: 33.0226 - Accuracy: 0.2941 - F1: 0.2508
sub_7:Test (Best Model) - Loss: 24.5324 - Accuracy: 0.5294 - F1: 0.5174
sub_8:Test (Best Model) - Loss: 20.5228 - Accuracy: 0.5588 - F1: 0.5203
sub_9:Test (Best Model) - Loss: 27.7619 - Accuracy: 0.3676 - F1: 0.3439
sub_8:Test (Best Model) - Loss: 16.1190 - Accuracy: 0.5147 - F1: 0.4613
sub_9:Test (Best Model) - Loss: 15.0422 - Accuracy: 0.3529 - F1: 0.3361
sub_7:Test (Best Model) - Loss: 11.4343 - Accuracy: 0.5735 - F1: 0.5799
sub_7:Test (Best Model) - Loss: 11.5322 - Accuracy: 0.5588 - F1: 0.5462
sub_11:Test (Best Model) - Loss: 10.2388 - Accuracy: 0.2899 - F1: 0.2479
sub_12:Test (Best Model) - Loss: 5.4251 - Accuracy: 0.5441 - F1: 0.5244
sub_11:Test (Best Model) - Loss: 4.4497 - Accuracy: 0.4203 - F1: 0.4102
sub_10:Test (Best Model) - Loss: 16.6020 - Accuracy: 0.5588 - F1: 0.5177
sub_11:Test (Best Model) - Loss: 7.3899 - Accuracy: 0.3913 - F1: 0.3505
sub_10:Test (Best Model) - Loss: 8.7772 - Accuracy: 0.5147 - F1: 0.4647
sub_12:Test (Best Model) - Loss: 2.7945 - Accuracy: 0.5588 - F1: 0.5525
sub_11:Test (Best Model) - Loss: 9.3665 - Accuracy: 0.4058 - F1: 0.3476
sub_10:Test (Best Model) - Loss: 10.9916 - Accuracy: 0.5147 - F1: 0.4810
sub_11:Test (Best Model) - Loss: 5.0364 - Accuracy: 0.4638 - F1: 0.3854
sub_12:Test (Best Model) - Loss: 2.3120 - Accuracy: 0.5294 - F1: 0.5092
sub_10:Test (Best Model) - Loss: 5.3639 - Accuracy: 0.4265 - F1: 0.3786
sub_11:Test (Best Model) - Loss: 6.9745 - Accuracy: 0.5217 - F1: 0.4723
sub_10:Test (Best Model) - Loss: 6.3628 - Accuracy: 0.4265 - F1: 0.4169
sub_12:Test (Best Model) - Loss: 3.5950 - Accuracy: 0.5735 - F1: 0.5714
sub_11:Test (Best Model) - Loss: 4.4659 - Accuracy: 0.5652 - F1: 0.5377
sub_10:Test (Best Model) - Loss: 39.2435 - Accuracy: 0.4559 - F1: 0.4485
sub_12:Test (Best Model) - Loss: 5.9579 - Accuracy: 0.5294 - F1: 0.5517
sub_11:Test (Best Model) - Loss: 9.6297 - Accuracy: 0.5507 - F1: 0.5196
sub_10:Test (Best Model) - Loss: 111.6261 - Accuracy: 0.4265 - F1: 0.3469
sub_12:Test (Best Model) - Loss: 7.2532 - Accuracy: 0.5217 - F1: 0.5042
sub_11:Test (Best Model) - Loss: 6.8292 - Accuracy: 0.5652 - F1: 0.5585
sub_10:Test (Best Model) - Loss: 109.3617 - Accuracy: 0.3824 - F1: 0.3176
sub_12:Test (Best Model) - Loss: 2.6480 - Accuracy: 0.4783 - F1: 0.4868
sub_10:Test (Best Model) - Loss: 76.6281 - Accuracy: 0.5294 - F1: 0.4557
sub_11:Test (Best Model) - Loss: 10.2685 - Accuracy: 0.5652 - F1: 0.5215
sub_12:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.5652 - F1: 0.5768
sub_10:Test (Best Model) - Loss: 77.4200 - Accuracy: 0.4412 - F1: 0.3991
sub_11:Test (Best Model) - Loss: 1.9339 - Accuracy: 0.5362 - F1: 0.4890
sub_12:Test (Best Model) - Loss: 2.4841 - Accuracy: 0.5217 - F1: 0.5421
sub_10:Test (Best Model) - Loss: 5.8835 - Accuracy: 0.6087 - F1: 0.5997
sub_12:Test (Best Model) - Loss: 2.9280 - Accuracy: 0.4638 - F1: 0.4765
sub_11:Test (Best Model) - Loss: 2.7468 - Accuracy: 0.4928 - F1: 0.4576
sub_10:Test (Best Model) - Loss: 4.0252 - Accuracy: 0.6087 - F1: 0.6049
sub_11:Test (Best Model) - Loss: 1.6630 - Accuracy: 0.5217 - F1: 0.5151
sub_12:Test (Best Model) - Loss: 5.4109 - Accuracy: 0.4412 - F1: 0.4159
sub_10:Test (Best Model) - Loss: 7.1046 - Accuracy: 0.5797 - F1: 0.5476
sub_12:Test (Best Model) - Loss: 2.2701 - Accuracy: 0.4559 - F1: 0.4339
sub_11:Test (Best Model) - Loss: 2.9822 - Accuracy: 0.5797 - F1: 0.5938
sub_10:Test (Best Model) - Loss: 7.8258 - Accuracy: 0.5797 - F1: 0.5619
sub_12:Test (Best Model) - Loss: 1.6975 - Accuracy: 0.6324 - F1: 0.6205
sub_11:Test (Best Model) - Loss: 1.8050 - Accuracy: 0.5217 - F1: 0.5105
sub_10:Test (Best Model) - Loss: 5.9812 - Accuracy: 0.6667 - F1: 0.6600
sub_12:Test (Best Model) - Loss: 2.0434 - Accuracy: 0.6176 - F1: 0.6102
sub_12:Test (Best Model) - Loss: 3.1408 - Accuracy: 0.5735 - F1: 0.5820
sub_15:Test (Best Model) - Loss: 31.9400 - Accuracy: 0.3971 - F1: 0.4143
sub_14:Test (Best Model) - Loss: 26.1815 - Accuracy: 0.4118 - F1: 0.3603
sub_13:Test (Best Model) - Loss: 2.8931 - Accuracy: 0.5882 - F1: 0.5735
sub_15:Test (Best Model) - Loss: 12.6187 - Accuracy: 0.4265 - F1: 0.4328
sub_14:Test (Best Model) - Loss: 29.2165 - Accuracy: 0.2941 - F1: 0.2432
sub_15:Test (Best Model) - Loss: 15.8616 - Accuracy: 0.4853 - F1: 0.4988
sub_13:Test (Best Model) - Loss: 6.6733 - Accuracy: 0.4412 - F1: 0.4530
sub_14:Test (Best Model) - Loss: 38.6142 - Accuracy: 0.3676 - F1: 0.2667
sub_15:Test (Best Model) - Loss: 27.2818 - Accuracy: 0.5588 - F1: 0.5586
sub_13:Test (Best Model) - Loss: 2.4508 - Accuracy: 0.5588 - F1: 0.5788
sub_13:Test (Best Model) - Loss: 4.3969 - Accuracy: 0.5147 - F1: 0.5147
sub_14:Test (Best Model) - Loss: 34.4704 - Accuracy: 0.3529 - F1: 0.2854
sub_15:Test (Best Model) - Loss: 23.0351 - Accuracy: 0.4118 - F1: 0.4409
sub_14:Test (Best Model) - Loss: 36.3792 - Accuracy: 0.3382 - F1: 0.2543
sub_13:Test (Best Model) - Loss: 13.4617 - Accuracy: 0.4559 - F1: 0.4647
sub_15:Test (Best Model) - Loss: 3.3724 - Accuracy: 0.4706 - F1: 0.4945
sub_13:Test (Best Model) - Loss: 5.8302 - Accuracy: 0.5217 - F1: 0.5253
sub_15:Test (Best Model) - Loss: 1.5669 - Accuracy: 0.4706 - F1: 0.4857
sub_14:Test (Best Model) - Loss: 10.0079 - Accuracy: 0.4853 - F1: 0.4365
sub_13:Test (Best Model) - Loss: 5.4751 - Accuracy: 0.4928 - F1: 0.4580
sub_15:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.8235 - F1: 0.8256
sub_14:Test (Best Model) - Loss: 7.0821 - Accuracy: 0.3676 - F1: 0.3358
sub_13:Test (Best Model) - Loss: 16.7521 - Accuracy: 0.4928 - F1: 0.4453
sub_15:Test (Best Model) - Loss: 3.1593 - Accuracy: 0.6176 - F1: 0.5885
sub_14:Test (Best Model) - Loss: 3.5092 - Accuracy: 0.4853 - F1: 0.5035
sub_13:Test (Best Model) - Loss: 10.7667 - Accuracy: 0.5217 - F1: 0.4599
sub_13:Test (Best Model) - Loss: 5.3534 - Accuracy: 0.4783 - F1: 0.4590
sub_14:Test (Best Model) - Loss: 6.1107 - Accuracy: 0.4412 - F1: 0.4422
sub_15:Test (Best Model) - Loss: 1.6233 - Accuracy: 0.6765 - F1: 0.6920
sub_13:Test (Best Model) - Loss: 2.6140 - Accuracy: 0.5441 - F1: 0.5228
sub_13:Test (Best Model) - Loss: 4.1745 - Accuracy: 0.3824 - F1: 0.3755
sub_15:Test (Best Model) - Loss: 7.5474 - Accuracy: 0.6471 - F1: 0.5849
sub_14:Test (Best Model) - Loss: 3.4258 - Accuracy: 0.5147 - F1: 0.5500
sub_13:Test (Best Model) - Loss: 5.2420 - Accuracy: 0.4559 - F1: 0.4061
sub_15:Test (Best Model) - Loss: 5.2708 - Accuracy: 0.6765 - F1: 0.6350
sub_14:Test (Best Model) - Loss: 7.8790 - Accuracy: 0.3088 - F1: 0.2657
sub_15:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.4265 - F1: 0.3654
sub_13:Test (Best Model) - Loss: 6.0039 - Accuracy: 0.4265 - F1: 0.4236
sub_14:Test (Best Model) - Loss: 4.4097 - Accuracy: 0.4559 - F1: 0.4328
sub_15:Test (Best Model) - Loss: 3.8194 - Accuracy: 0.5000 - F1: 0.4943
sub_13:Test (Best Model) - Loss: 10.9747 - Accuracy: 0.4706 - F1: 0.4252
sub_14:Test (Best Model) - Loss: 2.9775 - Accuracy: 0.5735 - F1: 0.5795
sub_15:Test (Best Model) - Loss: 8.1588 - Accuracy: 0.5735 - F1: 0.5477
sub_14:Test (Best Model) - Loss: 4.4236 - Accuracy: 0.5588 - F1: 0.5355
sub_14:Test (Best Model) - Loss: 5.2072 - Accuracy: 0.4706 - F1: 0.4419
sub_16:Test (Best Model) - Loss: 3.4167 - Accuracy: 0.6912 - F1: 0.6906
sub_18:Test (Best Model) - Loss: 4.0218 - Accuracy: 0.5652 - F1: 0.5536
sub_17:Test (Best Model) - Loss: 2.2431 - Accuracy: 0.6087 - F1: 0.6116
sub_16:Test (Best Model) - Loss: 3.9055 - Accuracy: 0.5735 - F1: 0.5631
sub_17:Test (Best Model) - Loss: 2.2811 - Accuracy: 0.6087 - F1: 0.6000
sub_18:Test (Best Model) - Loss: 6.9680 - Accuracy: 0.5072 - F1: 0.4803
sub_16:Test (Best Model) - Loss: 5.7740 - Accuracy: 0.5147 - F1: 0.5103
sub_17:Test (Best Model) - Loss: 3.9184 - Accuracy: 0.6232 - F1: 0.6229
sub_18:Test (Best Model) - Loss: 5.6973 - Accuracy: 0.5072 - F1: 0.4337
sub_17:Test (Best Model) - Loss: 3.1384 - Accuracy: 0.5797 - F1: 0.5709
sub_16:Test (Best Model) - Loss: 3.9821 - Accuracy: 0.5588 - F1: 0.5187
sub_18:Test (Best Model) - Loss: 10.0748 - Accuracy: 0.4783 - F1: 0.4632
sub_17:Test (Best Model) - Loss: 3.0688 - Accuracy: 0.4928 - F1: 0.4951
sub_16:Test (Best Model) - Loss: 3.8727 - Accuracy: 0.4853 - F1: 0.4616
sub_18:Test (Best Model) - Loss: 5.3909 - Accuracy: 0.6522 - F1: 0.6070
sub_17:Test (Best Model) - Loss: 2.8951 - Accuracy: 0.5652 - F1: 0.5678
sub_16:Test (Best Model) - Loss: 13.5548 - Accuracy: 0.5882 - F1: 0.5858
sub_17:Test (Best Model) - Loss: 4.0338 - Accuracy: 0.5072 - F1: 0.5086
sub_18:Test (Best Model) - Loss: 4.5820 - Accuracy: 0.4559 - F1: 0.4204
sub_17:Test (Best Model) - Loss: 1.8936 - Accuracy: 0.5652 - F1: 0.5620
sub_16:Test (Best Model) - Loss: 6.3523 - Accuracy: 0.4559 - F1: 0.4267
sub_18:Test (Best Model) - Loss: 1.9756 - Accuracy: 0.6618 - F1: 0.6489
sub_17:Test (Best Model) - Loss: 5.5684 - Accuracy: 0.5652 - F1: 0.5743
sub_16:Test (Best Model) - Loss: 6.8766 - Accuracy: 0.6029 - F1: 0.5964
sub_17:Test (Best Model) - Loss: 2.9590 - Accuracy: 0.5217 - F1: 0.5296
sub_18:Test (Best Model) - Loss: 1.5299 - Accuracy: 0.6618 - F1: 0.6692
sub_17:Test (Best Model) - Loss: 6.9148 - Accuracy: 0.4853 - F1: 0.4752
sub_16:Test (Best Model) - Loss: 16.5531 - Accuracy: 0.3529 - F1: 0.2954
sub_18:Test (Best Model) - Loss: 2.7428 - Accuracy: 0.6471 - F1: 0.6280
sub_17:Test (Best Model) - Loss: 7.2940 - Accuracy: 0.5588 - F1: 0.5548
sub_16:Test (Best Model) - Loss: 5.4513 - Accuracy: 0.3382 - F1: 0.2817
sub_18:Test (Best Model) - Loss: 2.1825 - Accuracy: 0.5588 - F1: 0.5643
sub_17:Test (Best Model) - Loss: 9.9512 - Accuracy: 0.5882 - F1: 0.5921
sub_18:Test (Best Model) - Loss: 3.1258 - Accuracy: 0.4706 - F1: 0.4104
sub_16:Test (Best Model) - Loss: 8.1070 - Accuracy: 0.4706 - F1: 0.4732
sub_17:Test (Best Model) - Loss: 6.8732 - Accuracy: 0.5441 - F1: 0.5377
sub_16:Test (Best Model) - Loss: 3.9400 - Accuracy: 0.4412 - F1: 0.4211
sub_18:Test (Best Model) - Loss: 7.8100 - Accuracy: 0.4412 - F1: 0.3973
sub_17:Test (Best Model) - Loss: 5.4738 - Accuracy: 0.5735 - F1: 0.5746
sub_18:Test (Best Model) - Loss: 10.0160 - Accuracy: 0.4706 - F1: 0.4274
sub_16:Test (Best Model) - Loss: 6.7737 - Accuracy: 0.3676 - F1: 0.3493
sub_18:Test (Best Model) - Loss: 6.3804 - Accuracy: 0.4706 - F1: 0.4562
sub_16:Test (Best Model) - Loss: 6.4644 - Accuracy: 0.5147 - F1: 0.4936
sub_16:Test (Best Model) - Loss: 4.4883 - Accuracy: 0.4118 - F1: 0.4150
sub_18:Test (Best Model) - Loss: 8.3434 - Accuracy: 0.5441 - F1: 0.5010
sub_19:Test (Best Model) - Loss: 9.1031 - Accuracy: 0.3824 - F1: 0.3852
sub_20:Test (Best Model) - Loss: 3.1560 - Accuracy: 0.5735 - F1: 0.5670
sub_20:Test (Best Model) - Loss: 2.6637 - Accuracy: 0.5882 - F1: 0.5724
sub_21:Test (Best Model) - Loss: 6.1028 - Accuracy: 0.5000 - F1: 0.4551
sub_19:Test (Best Model) - Loss: 12.5765 - Accuracy: 0.3529 - F1: 0.3523
sub_20:Test (Best Model) - Loss: 2.1519 - Accuracy: 0.6176 - F1: 0.6253
sub_21:Test (Best Model) - Loss: 8.3600 - Accuracy: 0.4265 - F1: 0.3818
sub_19:Test (Best Model) - Loss: 6.0856 - Accuracy: 0.3971 - F1: 0.3980
sub_20:Test (Best Model) - Loss: 2.4592 - Accuracy: 0.6324 - F1: 0.6338
sub_21:Test (Best Model) - Loss: 5.1338 - Accuracy: 0.5147 - F1: 0.4610
sub_19:Test (Best Model) - Loss: 11.7836 - Accuracy: 0.3824 - F1: 0.3843
sub_20:Test (Best Model) - Loss: 4.5868 - Accuracy: 0.5588 - F1: 0.5682
sub_21:Test (Best Model) - Loss: 6.0152 - Accuracy: 0.5588 - F1: 0.4847
sub_20:Test (Best Model) - Loss: 4.2035 - Accuracy: 0.6324 - F1: 0.6140
sub_19:Test (Best Model) - Loss: 9.4157 - Accuracy: 0.3088 - F1: 0.3041
sub_21:Test (Best Model) - Loss: 13.0886 - Accuracy: 0.5294 - F1: 0.5031
sub_19:Test (Best Model) - Loss: 5.8159 - Accuracy: 0.5147 - F1: 0.4673
sub_20:Test (Best Model) - Loss: 1.4398 - Accuracy: 0.7059 - F1: 0.6940
sub_21:Test (Best Model) - Loss: 76.6847 - Accuracy: 0.4412 - F1: 0.4189
sub_19:Test (Best Model) - Loss: 4.4487 - Accuracy: 0.4706 - F1: 0.4269
sub_20:Test (Best Model) - Loss: 2.2008 - Accuracy: 0.6765 - F1: 0.6570
sub_21:Test (Best Model) - Loss: 71.5801 - Accuracy: 0.5147 - F1: 0.5052
sub_19:Test (Best Model) - Loss: 3.3656 - Accuracy: 0.5588 - F1: 0.5866
sub_20:Test (Best Model) - Loss: 1.8395 - Accuracy: 0.7059 - F1: 0.6855
sub_21:Test (Best Model) - Loss: 53.3644 - Accuracy: 0.5294 - F1: 0.5056
sub_20:Test (Best Model) - Loss: 3.7610 - Accuracy: 0.6912 - F1: 0.6708
sub_19:Test (Best Model) - Loss: 7.4206 - Accuracy: 0.5147 - F1: 0.5005
sub_21:Test (Best Model) - Loss: 113.6552 - Accuracy: 0.5000 - F1: 0.4937
sub_20:Test (Best Model) - Loss: 2.7345 - Accuracy: 0.5652 - F1: 0.5647
sub_19:Test (Best Model) - Loss: 2.4754 - Accuracy: 0.5882 - F1: 0.5831
sub_21:Test (Best Model) - Loss: 53.2348 - Accuracy: 0.5000 - F1: 0.4852
sub_20:Test (Best Model) - Loss: 6.7524 - Accuracy: 0.4348 - F1: 0.4359
sub_20:Test (Best Model) - Loss: 1.5072 - Accuracy: 0.6957 - F1: 0.7005
sub_19:Test (Best Model) - Loss: 8.1901 - Accuracy: 0.5735 - F1: 0.5345
sub_21:Test (Best Model) - Loss: 1.6821 - Accuracy: 0.6176 - F1: 0.5819
sub_21:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.6176 - F1: 0.5740
sub_19:Test (Best Model) - Loss: 3.2643 - Accuracy: 0.5000 - F1: 0.4822
sub_20:Test (Best Model) - Loss: 4.9041 - Accuracy: 0.5797 - F1: 0.5719
sub_21:Test (Best Model) - Loss: 1.5979 - Accuracy: 0.6029 - F1: 0.5757
sub_19:Test (Best Model) - Loss: 3.4648 - Accuracy: 0.5882 - F1: 0.5876
sub_20:Test (Best Model) - Loss: 8.7570 - Accuracy: 0.5507 - F1: 0.5455
sub_21:Test (Best Model) - Loss: 1.8289 - Accuracy: 0.5588 - F1: 0.5232
sub_19:Test (Best Model) - Loss: 6.4933 - Accuracy: 0.4853 - F1: 0.4662
sub_21:Test (Best Model) - Loss: 2.6090 - Accuracy: 0.5441 - F1: 0.5019
sub_19:Test (Best Model) - Loss: 5.3720 - Accuracy: 0.5735 - F1: 0.5698
sub_23:Test (Best Model) - Loss: 5.6700 - Accuracy: 0.4928 - F1: 0.4832
sub_24:Test (Best Model) - Loss: 4.0443 - Accuracy: 0.4706 - F1: 0.4789
sub_22:Test (Best Model) - Loss: 12.9530 - Accuracy: 0.4559 - F1: 0.3948
sub_22:Test (Best Model) - Loss: 6.8093 - Accuracy: 0.4412 - F1: 0.3646
sub_23:Test (Best Model) - Loss: 2.8187 - Accuracy: 0.5362 - F1: 0.5211
sub_24:Test (Best Model) - Loss: 11.4886 - Accuracy: 0.4265 - F1: 0.4223
sub_23:Test (Best Model) - Loss: 3.7381 - Accuracy: 0.4203 - F1: 0.3542
sub_22:Test (Best Model) - Loss: 23.2253 - Accuracy: 0.5000 - F1: 0.4566
sub_24:Test (Best Model) - Loss: 14.0621 - Accuracy: 0.3971 - F1: 0.4057
sub_22:Test (Best Model) - Loss: 11.0109 - Accuracy: 0.4559 - F1: 0.4129
sub_23:Test (Best Model) - Loss: 6.1102 - Accuracy: 0.5072 - F1: 0.4857
sub_24:Test (Best Model) - Loss: 7.7936 - Accuracy: 0.4118 - F1: 0.4077
sub_22:Test (Best Model) - Loss: 16.7425 - Accuracy: 0.4412 - F1: 0.3731
sub_24:Test (Best Model) - Loss: 7.8578 - Accuracy: 0.4265 - F1: 0.4379
sub_22:Test (Best Model) - Loss: 2.7460 - Accuracy: 0.5362 - F1: 0.5279
sub_23:Test (Best Model) - Loss: 5.6600 - Accuracy: 0.4783 - F1: 0.4691
sub_22:Test (Best Model) - Loss: 1.1518 - Accuracy: 0.5507 - F1: 0.5562
sub_24:Test (Best Model) - Loss: 6.9021 - Accuracy: 0.4853 - F1: 0.5004
sub_23:Test (Best Model) - Loss: 73.9942 - Accuracy: 0.4706 - F1: 0.4453
sub_22:Test (Best Model) - Loss: 1.4837 - Accuracy: 0.5217 - F1: 0.5112
sub_23:Test (Best Model) - Loss: 8.7457 - Accuracy: 0.4853 - F1: 0.4678
sub_24:Test (Best Model) - Loss: 5.0658 - Accuracy: 0.5294 - F1: 0.5458
sub_22:Test (Best Model) - Loss: 3.5550 - Accuracy: 0.4783 - F1: 0.4428
sub_23:Test (Best Model) - Loss: 17.2079 - Accuracy: 0.4706 - F1: 0.4311
sub_24:Test (Best Model) - Loss: 5.7058 - Accuracy: 0.4559 - F1: 0.4503
sub_22:Test (Best Model) - Loss: 2.2707 - Accuracy: 0.4783 - F1: 0.4514
sub_23:Test (Best Model) - Loss: 18.0235 - Accuracy: 0.5000 - F1: 0.4678
sub_24:Test (Best Model) - Loss: 6.0692 - Accuracy: 0.5441 - F1: 0.5510
sub_22:Test (Best Model) - Loss: 20.4014 - Accuracy: 0.2794 - F1: 0.2384
sub_23:Test (Best Model) - Loss: 17.1535 - Accuracy: 0.4853 - F1: 0.4569
sub_24:Test (Best Model) - Loss: 4.0925 - Accuracy: 0.5735 - F1: 0.5955
sub_22:Test (Best Model) - Loss: 12.7624 - Accuracy: 0.2647 - F1: 0.2282
sub_23:Test (Best Model) - Loss: 27.4227 - Accuracy: 0.4058 - F1: 0.3954
sub_24:Test (Best Model) - Loss: 5.2811 - Accuracy: 0.4559 - F1: 0.4750
sub_22:Test (Best Model) - Loss: 17.9386 - Accuracy: 0.2059 - F1: 0.1521
sub_23:Test (Best Model) - Loss: 5.2831 - Accuracy: 0.5072 - F1: 0.5162
sub_24:Test (Best Model) - Loss: 5.6673 - Accuracy: 0.5441 - F1: 0.5229
sub_23:Test (Best Model) - Loss: 10.1953 - Accuracy: 0.4348 - F1: 0.3930
sub_22:Test (Best Model) - Loss: 18.2538 - Accuracy: 0.2794 - F1: 0.2388
sub_23:Test (Best Model) - Loss: 6.0123 - Accuracy: 0.4203 - F1: 0.4143
sub_24:Test (Best Model) - Loss: 15.5155 - Accuracy: 0.3824 - F1: 0.3790
sub_22:Test (Best Model) - Loss: 20.1289 - Accuracy: 0.3088 - F1: 0.2806
sub_23:Test (Best Model) - Loss: 9.7671 - Accuracy: 0.4203 - F1: 0.3913
sub_24:Test (Best Model) - Loss: 4.0400 - Accuracy: 0.4118 - F1: 0.4335
sub_24:Test (Best Model) - Loss: 3.6040 - Accuracy: 0.3676 - F1: 0.4070
sub_25:Test (Best Model) - Loss: 2.5027 - Accuracy: 0.6667 - F1: 0.6811
sub_27:Test (Best Model) - Loss: 2.2431 - Accuracy: 0.6087 - F1: 0.6116
sub_26:Test (Best Model) - Loss: 3.8606 - Accuracy: 0.5797 - F1: 0.5796
sub_25:Test (Best Model) - Loss: 2.8694 - Accuracy: 0.6957 - F1: 0.6902
sub_27:Test (Best Model) - Loss: 2.2811 - Accuracy: 0.6087 - F1: 0.6000
sub_25:Test (Best Model) - Loss: 3.5089 - Accuracy: 0.6522 - F1: 0.6411
sub_26:Test (Best Model) - Loss: 2.0059 - Accuracy: 0.6377 - F1: 0.6449
sub_27:Test (Best Model) - Loss: 3.9184 - Accuracy: 0.6232 - F1: 0.6229
sub_25:Test (Best Model) - Loss: 3.2521 - Accuracy: 0.6377 - F1: 0.6321
sub_27:Test (Best Model) - Loss: 3.1384 - Accuracy: 0.5797 - F1: 0.5709
sub_26:Test (Best Model) - Loss: 1.6898 - Accuracy: 0.6522 - F1: 0.6725
sub_25:Test (Best Model) - Loss: 5.0529 - Accuracy: 0.5507 - F1: 0.5286
sub_26:Test (Best Model) - Loss: 1.9386 - Accuracy: 0.6232 - F1: 0.6312
sub_27:Test (Best Model) - Loss: 3.0688 - Accuracy: 0.4928 - F1: 0.4951
sub_25:Test (Best Model) - Loss: 1.9166 - Accuracy: 0.6029 - F1: 0.6014
sub_26:Test (Best Model) - Loss: 1.8474 - Accuracy: 0.6232 - F1: 0.6219
sub_27:Test (Best Model) - Loss: 2.8951 - Accuracy: 0.5652 - F1: 0.5678
sub_25:Test (Best Model) - Loss: 1.8580 - Accuracy: 0.6471 - F1: 0.6343
sub_27:Test (Best Model) - Loss: 4.0338 - Accuracy: 0.5072 - F1: 0.5086
sub_26:Test (Best Model) - Loss: 3.8714 - Accuracy: 0.5294 - F1: 0.5280
sub_26:Test (Best Model) - Loss: 3.2024 - Accuracy: 0.5294 - F1: 0.5271
sub_27:Test (Best Model) - Loss: 1.8936 - Accuracy: 0.5652 - F1: 0.5620
sub_25:Test (Best Model) - Loss: 0.9713 - Accuracy: 0.7059 - F1: 0.7058
sub_26:Test (Best Model) - Loss: 6.9883 - Accuracy: 0.5294 - F1: 0.5137
sub_27:Test (Best Model) - Loss: 5.5684 - Accuracy: 0.5652 - F1: 0.5743
sub_25:Test (Best Model) - Loss: 0.9839 - Accuracy: 0.7059 - F1: 0.7090
sub_26:Test (Best Model) - Loss: 9.1628 - Accuracy: 0.5588 - F1: 0.5708
sub_27:Test (Best Model) - Loss: 2.9590 - Accuracy: 0.5217 - F1: 0.5296
sub_25:Test (Best Model) - Loss: 1.1917 - Accuracy: 0.7059 - F1: 0.7063
sub_27:Test (Best Model) - Loss: 6.9148 - Accuracy: 0.4853 - F1: 0.4752
sub_26:Test (Best Model) - Loss: 5.4518 - Accuracy: 0.5294 - F1: 0.5113
sub_25:Test (Best Model) - Loss: 2.3425 - Accuracy: 0.6176 - F1: 0.6255
sub_27:Test (Best Model) - Loss: 7.2940 - Accuracy: 0.5588 - F1: 0.5548
sub_26:Test (Best Model) - Loss: 4.4393 - Accuracy: 0.4559 - F1: 0.4529
sub_25:Test (Best Model) - Loss: 1.9025 - Accuracy: 0.7353 - F1: 0.7273
sub_27:Test (Best Model) - Loss: 9.9512 - Accuracy: 0.5882 - F1: 0.5921
sub_26:Test (Best Model) - Loss: 5.6982 - Accuracy: 0.4265 - F1: 0.4413
sub_27:Test (Best Model) - Loss: 6.8732 - Accuracy: 0.5441 - F1: 0.5377
sub_25:Test (Best Model) - Loss: 5.0358 - Accuracy: 0.6176 - F1: 0.6078
sub_26:Test (Best Model) - Loss: 4.0470 - Accuracy: 0.5735 - F1: 0.5734
sub_27:Test (Best Model) - Loss: 5.4738 - Accuracy: 0.5735 - F1: 0.5746
sub_25:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.6912 - F1: 0.6717
sub_26:Test (Best Model) - Loss: 11.7796 - Accuracy: 0.3235 - F1: 0.3288
sub_25:Test (Best Model) - Loss: 1.6531 - Accuracy: 0.6618 - F1: 0.6476
sub_26:Test (Best Model) - Loss: 10.7731 - Accuracy: 0.4706 - F1: 0.4898
sub_29:Test (Best Model) - Loss: 2.5246 - Accuracy: 0.5441 - F1: 0.5231
sub_29:Test (Best Model) - Loss: 5.8332 - Accuracy: 0.5441 - F1: 0.5423
sub_28:Test (Best Model) - Loss: 7.4928 - Accuracy: 0.3971 - F1: 0.3516
sub_29:Test (Best Model) - Loss: 7.7220 - Accuracy: 0.5735 - F1: 0.5793
sub_29:Test (Best Model) - Loss: 8.8397 - Accuracy: 0.4706 - F1: 0.4450
sub_28:Test (Best Model) - Loss: 7.5413 - Accuracy: 0.4118 - F1: 0.3732
sub_29:Test (Best Model) - Loss: 5.2642 - Accuracy: 0.5735 - F1: 0.5747
sub_28:Test (Best Model) - Loss: 5.3589 - Accuracy: 0.3235 - F1: 0.2959
sub_29:Test (Best Model) - Loss: 9.9964 - Accuracy: 0.3088 - F1: 0.2424
sub_29:Test (Best Model) - Loss: 9.1524 - Accuracy: 0.4118 - F1: 0.3306
sub_28:Test (Best Model) - Loss: 6.8630 - Accuracy: 0.3971 - F1: 0.3694
sub_29:Test (Best Model) - Loss: 12.2953 - Accuracy: 0.3971 - F1: 0.3077
sub_28:Test (Best Model) - Loss: 5.5289 - Accuracy: 0.3824 - F1: 0.3509
sub_29:Test (Best Model) - Loss: 33.6757 - Accuracy: 0.4412 - F1: 0.3500
sub_28:Test (Best Model) - Loss: 33.7385 - Accuracy: 0.4265 - F1: 0.3401
sub_29:Test (Best Model) - Loss: 4.1138 - Accuracy: 0.5588 - F1: 0.4929
sub_29:Test (Best Model) - Loss: 2.8568 - Accuracy: 0.4203 - F1: 0.3668
sub_28:Test (Best Model) - Loss: 20.8803 - Accuracy: 0.3971 - F1: 0.3502
sub_29:Test (Best Model) - Loss: 1.6290 - Accuracy: 0.5217 - F1: 0.5076
sub_28:Test (Best Model) - Loss: 16.8487 - Accuracy: 0.4118 - F1: 0.3268
sub_29:Test (Best Model) - Loss: 6.4303 - Accuracy: 0.4493 - F1: 0.3876
sub_28:Test (Best Model) - Loss: 31.7337 - Accuracy: 0.4265 - F1: 0.3433
sub_29:Test (Best Model) - Loss: 2.5408 - Accuracy: 0.4058 - F1: 0.3866
sub_28:Test (Best Model) - Loss: 38.2261 - Accuracy: 0.3824 - F1: 0.3137
sub_29:Test (Best Model) - Loss: 6.6253 - Accuracy: 0.4928 - F1: 0.4541
sub_28:Test (Best Model) - Loss: 33.5014 - Accuracy: 0.2794 - F1: 0.1389
sub_28:Test (Best Model) - Loss: 25.3484 - Accuracy: 0.2353 - F1: 0.1860
sub_28:Test (Best Model) - Loss: 28.9321 - Accuracy: 0.2941 - F1: 0.1645
sub_28:Test (Best Model) - Loss: 44.5746 - Accuracy: 0.3088 - F1: 0.2513
sub_28:Test (Best Model) - Loss: 48.5451 - Accuracy: 0.2647 - F1: 0.1709

=== Summary Results ===

acc: 51.74 ± 6.58
F1: 49.59 ± 7.56
acc-in: 75.98 ± 5.41
F1-in: 75.28 ± 5.57
runing time: 2397.90 seconds
