lr: 0.001
sub_1:Test (Best Model) - Loss: 1.6827 - Accuracy: 0.6618 - F1: 0.6647
sub_2:Test (Best Model) - Loss: 2.1679 - Accuracy: 0.5072 - F1: 0.4991
sub_3:Test (Best Model) - Loss: 4.4281 - Accuracy: 0.7353 - F1: 0.6965
sub_1:Test (Best Model) - Loss: 2.1403 - Accuracy: 0.5588 - F1: 0.5593
sub_3:Test (Best Model) - Loss: 2.6543 - Accuracy: 0.6912 - F1: 0.7030
sub_1:Test (Best Model) - Loss: 2.4260 - Accuracy: 0.6765 - F1: 0.6784
sub_2:Test (Best Model) - Loss: 3.0566 - Accuracy: 0.5362 - F1: 0.5151
sub_3:Test (Best Model) - Loss: 1.1621 - Accuracy: 0.7059 - F1: 0.7115
sub_1:Test (Best Model) - Loss: 5.5448 - Accuracy: 0.5882 - F1: 0.5826
sub_2:Test (Best Model) - Loss: 1.7335 - Accuracy: 0.5942 - F1: 0.5689
sub_3:Test (Best Model) - Loss: 2.5476 - Accuracy: 0.7353 - F1: 0.7373
sub_1:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.6618 - F1: 0.6649
sub_2:Test (Best Model) - Loss: 1.8127 - Accuracy: 0.7391 - F1: 0.7092
sub_3:Test (Best Model) - Loss: 2.7755 - Accuracy: 0.5735 - F1: 0.5539
sub_1:Test (Best Model) - Loss: 6.3982 - Accuracy: 0.4783 - F1: 0.4731
sub_2:Test (Best Model) - Loss: 2.4299 - Accuracy: 0.4783 - F1: 0.4787
sub_1:Test (Best Model) - Loss: 3.8529 - Accuracy: 0.4638 - F1: 0.4406
sub_3:Test (Best Model) - Loss: 2.1377 - Accuracy: 0.6087 - F1: 0.6003
sub_2:Test (Best Model) - Loss: 1.5081 - Accuracy: 0.5882 - F1: 0.5823
sub_3:Test (Best Model) - Loss: 3.2662 - Accuracy: 0.6087 - F1: 0.5991
sub_1:Test (Best Model) - Loss: 4.5799 - Accuracy: 0.5652 - F1: 0.5502
sub_2:Test (Best Model) - Loss: 0.7342 - Accuracy: 0.6471 - F1: 0.6517
sub_3:Test (Best Model) - Loss: 2.4719 - Accuracy: 0.6377 - F1: 0.6290
sub_1:Test (Best Model) - Loss: 2.9176 - Accuracy: 0.6377 - F1: 0.6435
sub_2:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.6471 - F1: 0.6608
sub_3:Test (Best Model) - Loss: 5.1986 - Accuracy: 0.5797 - F1: 0.5563
sub_1:Test (Best Model) - Loss: 8.6214 - Accuracy: 0.5362 - F1: 0.5289
sub_3:Test (Best Model) - Loss: 4.1743 - Accuracy: 0.6522 - F1: 0.6378
sub_2:Test (Best Model) - Loss: 0.9304 - Accuracy: 0.6765 - F1: 0.6833
sub_3:Test (Best Model) - Loss: 2.3020 - Accuracy: 0.6667 - F1: 0.6166
sub_1:Test (Best Model) - Loss: 1.5632 - Accuracy: 0.7206 - F1: 0.6733
sub_2:Test (Best Model) - Loss: 0.5662 - Accuracy: 0.7059 - F1: 0.7111
sub_3:Test (Best Model) - Loss: 3.1111 - Accuracy: 0.7246 - F1: 0.7256
sub_1:Test (Best Model) - Loss: 2.8142 - Accuracy: 0.7059 - F1: 0.6504
sub_2:Test (Best Model) - Loss: 1.7136 - Accuracy: 0.6087 - F1: 0.5724
sub_3:Test (Best Model) - Loss: 6.8510 - Accuracy: 0.6812 - F1: 0.6272
sub_1:Test (Best Model) - Loss: 1.4230 - Accuracy: 0.7206 - F1: 0.6743
sub_2:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.6087 - F1: 0.5478
sub_3:Test (Best Model) - Loss: 3.0712 - Accuracy: 0.7101 - F1: 0.7129
sub_1:Test (Best Model) - Loss: 0.9077 - Accuracy: 0.7353 - F1: 0.6907
sub_2:Test (Best Model) - Loss: 3.1381 - Accuracy: 0.3478 - F1: 0.3050
sub_3:Test (Best Model) - Loss: 2.6354 - Accuracy: 0.7101 - F1: 0.6926
sub_2:Test (Best Model) - Loss: 2.5188 - Accuracy: 0.6232 - F1: 0.5997
sub_1:Test (Best Model) - Loss: 0.9780 - Accuracy: 0.7647 - F1: 0.7644
sub_2:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.5652 - F1: 0.5005
sub_5:Test (Best Model) - Loss: 6.1031 - Accuracy: 0.4853 - F1: 0.4686
sub_6:Test (Best Model) - Loss: 12.7586 - Accuracy: 0.4118 - F1: 0.3171
sub_4:Test (Best Model) - Loss: 5.6943 - Accuracy: 0.5072 - F1: 0.4461
sub_6:Test (Best Model) - Loss: 11.1179 - Accuracy: 0.4265 - F1: 0.3422
sub_4:Test (Best Model) - Loss: 5.2508 - Accuracy: 0.5507 - F1: 0.4934
sub_5:Test (Best Model) - Loss: 4.7418 - Accuracy: 0.5882 - F1: 0.5454
sub_6:Test (Best Model) - Loss: 16.6377 - Accuracy: 0.3676 - F1: 0.2749
sub_4:Test (Best Model) - Loss: 3.4485 - Accuracy: 0.5797 - F1: 0.5380
sub_5:Test (Best Model) - Loss: 2.3854 - Accuracy: 0.7500 - F1: 0.7532
sub_6:Test (Best Model) - Loss: 7.9561 - Accuracy: 0.4265 - F1: 0.3642
sub_4:Test (Best Model) - Loss: 3.6743 - Accuracy: 0.5652 - F1: 0.5229
sub_5:Test (Best Model) - Loss: 3.6509 - Accuracy: 0.6324 - F1: 0.6049
sub_6:Test (Best Model) - Loss: 6.0825 - Accuracy: 0.4265 - F1: 0.3645
sub_4:Test (Best Model) - Loss: 4.1370 - Accuracy: 0.5362 - F1: 0.4753
sub_5:Test (Best Model) - Loss: 4.1494 - Accuracy: 0.5441 - F1: 0.4998
sub_6:Test (Best Model) - Loss: 2.1176 - Accuracy: 0.4928 - F1: 0.4112
sub_4:Test (Best Model) - Loss: 10.6219 - Accuracy: 0.3623 - F1: 0.2612
sub_6:Test (Best Model) - Loss: 2.1190 - Accuracy: 0.5072 - F1: 0.4431
sub_5:Test (Best Model) - Loss: 9.3596 - Accuracy: 0.5000 - F1: 0.4487
sub_4:Test (Best Model) - Loss: 7.3007 - Accuracy: 0.3623 - F1: 0.3090
sub_5:Test (Best Model) - Loss: 7.2976 - Accuracy: 0.3676 - F1: 0.2690
sub_6:Test (Best Model) - Loss: 3.0946 - Accuracy: 0.4928 - F1: 0.3977
sub_4:Test (Best Model) - Loss: 4.3266 - Accuracy: 0.4493 - F1: 0.4330
sub_5:Test (Best Model) - Loss: 11.2144 - Accuracy: 0.4559 - F1: 0.4006
sub_6:Test (Best Model) - Loss: 2.6822 - Accuracy: 0.4493 - F1: 0.3828
sub_4:Test (Best Model) - Loss: 3.3726 - Accuracy: 0.4928 - F1: 0.4233
sub_5:Test (Best Model) - Loss: 7.2299 - Accuracy: 0.5000 - F1: 0.4451
sub_4:Test (Best Model) - Loss: 4.4792 - Accuracy: 0.3913 - F1: 0.3314
sub_6:Test (Best Model) - Loss: 2.5681 - Accuracy: 0.6232 - F1: 0.5613
sub_5:Test (Best Model) - Loss: 16.5368 - Accuracy: 0.5000 - F1: 0.4342
sub_4:Test (Best Model) - Loss: 2.3243 - Accuracy: 0.7101 - F1: 0.6925
sub_6:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.5942 - F1: 0.5843
sub_5:Test (Best Model) - Loss: 4.8453 - Accuracy: 0.4853 - F1: 0.3810
sub_4:Test (Best Model) - Loss: 3.1530 - Accuracy: 0.6232 - F1: 0.5803
sub_5:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.6471 - F1: 0.6402
sub_6:Test (Best Model) - Loss: 1.2547 - Accuracy: 0.7101 - F1: 0.6943
sub_4:Test (Best Model) - Loss: 1.8649 - Accuracy: 0.6087 - F1: 0.5751
sub_5:Test (Best Model) - Loss: 1.2846 - Accuracy: 0.7059 - F1: 0.6991
sub_6:Test (Best Model) - Loss: 1.2517 - Accuracy: 0.6377 - F1: 0.6398
sub_4:Test (Best Model) - Loss: 6.7401 - Accuracy: 0.6087 - F1: 0.5725
sub_5:Test (Best Model) - Loss: 1.0606 - Accuracy: 0.6324 - F1: 0.6220
sub_6:Test (Best Model) - Loss: 1.9560 - Accuracy: 0.5942 - F1: 0.5848
sub_4:Test (Best Model) - Loss: 3.1219 - Accuracy: 0.6812 - F1: 0.6709
sub_6:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.6377 - F1: 0.6230
sub_5:Test (Best Model) - Loss: 1.1701 - Accuracy: 0.7353 - F1: 0.7102
sub_7:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.6618 - F1: 0.6391
sub_8:Test (Best Model) - Loss: 16.4686 - Accuracy: 0.3676 - F1: 0.2999
sub_9:Test (Best Model) - Loss: 6.7807 - Accuracy: 0.3824 - F1: 0.3733
sub_7:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.7500 - F1: 0.7607
sub_7:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.6176 - F1: 0.6019
sub_8:Test (Best Model) - Loss: 10.0463 - Accuracy: 0.3824 - F1: 0.3148
sub_9:Test (Best Model) - Loss: 6.5873 - Accuracy: 0.3971 - F1: 0.4238
sub_8:Test (Best Model) - Loss: 7.5883 - Accuracy: 0.3971 - F1: 0.3332
sub_7:Test (Best Model) - Loss: 2.3014 - Accuracy: 0.6618 - F1: 0.6361
sub_9:Test (Best Model) - Loss: 6.4090 - Accuracy: 0.3824 - F1: 0.4044
sub_8:Test (Best Model) - Loss: 7.4080 - Accuracy: 0.4706 - F1: 0.4345
sub_8:Test (Best Model) - Loss: 10.7352 - Accuracy: 0.3824 - F1: 0.2788
sub_7:Test (Best Model) - Loss: 7.3322 - Accuracy: 0.6176 - F1: 0.5994
sub_9:Test (Best Model) - Loss: 6.9190 - Accuracy: 0.3971 - F1: 0.4000
sub_8:Test (Best Model) - Loss: 2.8663 - Accuracy: 0.6324 - F1: 0.6188
sub_7:Test (Best Model) - Loss: 3.1451 - Accuracy: 0.5882 - F1: 0.5981
sub_8:Test (Best Model) - Loss: 6.6813 - Accuracy: 0.4853 - F1: 0.4118
sub_9:Test (Best Model) - Loss: 8.7479 - Accuracy: 0.4265 - F1: 0.4336
sub_8:Test (Best Model) - Loss: 2.3107 - Accuracy: 0.5588 - F1: 0.5497
sub_7:Test (Best Model) - Loss: 1.5044 - Accuracy: 0.7059 - F1: 0.7166
sub_9:Test (Best Model) - Loss: 1.5417 - Accuracy: 0.5735 - F1: 0.5111
sub_8:Test (Best Model) - Loss: 3.1466 - Accuracy: 0.6029 - F1: 0.5964
sub_7:Test (Best Model) - Loss: 2.3231 - Accuracy: 0.6912 - F1: 0.6922
sub_9:Test (Best Model) - Loss: 4.4567 - Accuracy: 0.4706 - F1: 0.4272
sub_8:Test (Best Model) - Loss: 3.9163 - Accuracy: 0.6471 - F1: 0.6193
sub_8:Test (Best Model) - Loss: 5.2734 - Accuracy: 0.6471 - F1: 0.6175
sub_7:Test (Best Model) - Loss: 3.1279 - Accuracy: 0.6912 - F1: 0.6956
sub_9:Test (Best Model) - Loss: 2.4447 - Accuracy: 0.5735 - F1: 0.5039
sub_8:Test (Best Model) - Loss: 5.4723 - Accuracy: 0.6618 - F1: 0.6309
sub_9:Test (Best Model) - Loss: 2.0502 - Accuracy: 0.5882 - F1: 0.5797
sub_7:Test (Best Model) - Loss: 4.7651 - Accuracy: 0.6765 - F1: 0.6797
sub_9:Test (Best Model) - Loss: 3.7629 - Accuracy: 0.4559 - F1: 0.4321
sub_8:Test (Best Model) - Loss: 11.8682 - Accuracy: 0.5588 - F1: 0.5220
sub_7:Test (Best Model) - Loss: 4.3824 - Accuracy: 0.6176 - F1: 0.6101
sub_9:Test (Best Model) - Loss: 5.6047 - Accuracy: 0.2500 - F1: 0.2338
sub_7:Test (Best Model) - Loss: 1.4420 - Accuracy: 0.6176 - F1: 0.6185
sub_8:Test (Best Model) - Loss: 5.8091 - Accuracy: 0.6618 - F1: 0.6474
sub_9:Test (Best Model) - Loss: 7.3094 - Accuracy: 0.3676 - F1: 0.3868
sub_8:Test (Best Model) - Loss: 4.9628 - Accuracy: 0.6176 - F1: 0.5995
sub_7:Test (Best Model) - Loss: 2.4086 - Accuracy: 0.5735 - F1: 0.5861
sub_9:Test (Best Model) - Loss: 10.5069 - Accuracy: 0.2794 - F1: 0.2938
sub_9:Test (Best Model) - Loss: 8.1128 - Accuracy: 0.2647 - F1: 0.2815
sub_7:Test (Best Model) - Loss: 2.7433 - Accuracy: 0.6029 - F1: 0.6004
sub_7:Test (Best Model) - Loss: 3.0605 - Accuracy: 0.5882 - F1: 0.5856
sub_9:Test (Best Model) - Loss: 9.3882 - Accuracy: 0.3824 - F1: 0.3666
sub_12:Test (Best Model) - Loss: 6.2285 - Accuracy: 0.5294 - F1: 0.5228
sub_10:Test (Best Model) - Loss: 11.1073 - Accuracy: 0.4265 - F1: 0.4168
sub_11:Test (Best Model) - Loss: 1.1801 - Accuracy: 0.5797 - F1: 0.5787
sub_11:Test (Best Model) - Loss: 1.4807 - Accuracy: 0.4493 - F1: 0.4000
sub_12:Test (Best Model) - Loss: 2.9189 - Accuracy: 0.5147 - F1: 0.5007
sub_11:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.6087 - F1: 0.6061
sub_10:Test (Best Model) - Loss: 6.3482 - Accuracy: 0.3824 - F1: 0.3695
sub_10:Test (Best Model) - Loss: 5.0328 - Accuracy: 0.3824 - F1: 0.3713
sub_12:Test (Best Model) - Loss: 1.7233 - Accuracy: 0.6324 - F1: 0.6454
sub_11:Test (Best Model) - Loss: 2.9700 - Accuracy: 0.5362 - F1: 0.5200
sub_10:Test (Best Model) - Loss: 5.6937 - Accuracy: 0.3529 - F1: 0.3441
sub_12:Test (Best Model) - Loss: 6.1951 - Accuracy: 0.5882 - F1: 0.5850
sub_10:Test (Best Model) - Loss: 7.6613 - Accuracy: 0.3676 - F1: 0.3981
sub_11:Test (Best Model) - Loss: 1.5056 - Accuracy: 0.5652 - F1: 0.5318
sub_10:Test (Best Model) - Loss: 4.0521 - Accuracy: 0.5882 - F1: 0.5768
sub_11:Test (Best Model) - Loss: 1.6552 - Accuracy: 0.6087 - F1: 0.5615
sub_12:Test (Best Model) - Loss: 5.0867 - Accuracy: 0.5441 - F1: 0.5567
sub_12:Test (Best Model) - Loss: 3.4203 - Accuracy: 0.5217 - F1: 0.5382
sub_10:Test (Best Model) - Loss: 8.9253 - Accuracy: 0.6176 - F1: 0.6085
sub_12:Test (Best Model) - Loss: 0.9627 - Accuracy: 0.5507 - F1: 0.5635
sub_11:Test (Best Model) - Loss: 2.8371 - Accuracy: 0.6087 - F1: 0.5770
sub_10:Test (Best Model) - Loss: 9.9382 - Accuracy: 0.5882 - F1: 0.6012
sub_12:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.5217 - F1: 0.5457
sub_11:Test (Best Model) - Loss: 1.9341 - Accuracy: 0.5797 - F1: 0.5385
sub_10:Test (Best Model) - Loss: 8.3365 - Accuracy: 0.6029 - F1: 0.6199
sub_12:Test (Best Model) - Loss: 0.9332 - Accuracy: 0.5652 - F1: 0.5930
sub_11:Test (Best Model) - Loss: 5.5547 - Accuracy: 0.5652 - F1: 0.5098
sub_10:Test (Best Model) - Loss: 12.7277 - Accuracy: 0.6324 - F1: 0.6315
sub_11:Test (Best Model) - Loss: 4.1950 - Accuracy: 0.6522 - F1: 0.5702
sub_12:Test (Best Model) - Loss: 4.7369 - Accuracy: 0.4638 - F1: 0.4551
sub_12:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.6324 - F1: 0.6066
sub_11:Test (Best Model) - Loss: 1.7018 - Accuracy: 0.5507 - F1: 0.5524
sub_10:Test (Best Model) - Loss: 3.1404 - Accuracy: 0.7391 - F1: 0.7303
sub_10:Test (Best Model) - Loss: 2.5306 - Accuracy: 0.6522 - F1: 0.6424
sub_11:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.6087 - F1: 0.6058
sub_12:Test (Best Model) - Loss: 7.2298 - Accuracy: 0.3824 - F1: 0.3235
sub_10:Test (Best Model) - Loss: 2.2274 - Accuracy: 0.6377 - F1: 0.6287
sub_11:Test (Best Model) - Loss: 1.4195 - Accuracy: 0.6232 - F1: 0.6242
sub_12:Test (Best Model) - Loss: 5.2241 - Accuracy: 0.5588 - F1: 0.5423
sub_10:Test (Best Model) - Loss: 1.7441 - Accuracy: 0.6667 - F1: 0.6462
sub_11:Test (Best Model) - Loss: 1.2033 - Accuracy: 0.6377 - F1: 0.6342
sub_12:Test (Best Model) - Loss: 1.8176 - Accuracy: 0.5588 - F1: 0.5366
sub_11:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.5652 - F1: 0.5632
sub_10:Test (Best Model) - Loss: 2.8890 - Accuracy: 0.7101 - F1: 0.7090
sub_12:Test (Best Model) - Loss: 2.8371 - Accuracy: 0.5294 - F1: 0.5208
sub_14:Test (Best Model) - Loss: 18.8281 - Accuracy: 0.2353 - F1: 0.2143
sub_15:Test (Best Model) - Loss: 6.3588 - Accuracy: 0.6176 - F1: 0.6172
sub_13:Test (Best Model) - Loss: 3.8943 - Accuracy: 0.5294 - F1: 0.5391
sub_14:Test (Best Model) - Loss: 12.4884 - Accuracy: 0.3529 - F1: 0.3108
sub_13:Test (Best Model) - Loss: 2.1374 - Accuracy: 0.5294 - F1: 0.5363
sub_15:Test (Best Model) - Loss: 6.6100 - Accuracy: 0.5441 - F1: 0.5434
sub_13:Test (Best Model) - Loss: 2.1947 - Accuracy: 0.4706 - F1: 0.4600
sub_15:Test (Best Model) - Loss: 4.9260 - Accuracy: 0.5882 - F1: 0.5823
sub_14:Test (Best Model) - Loss: 10.3296 - Accuracy: 0.3088 - F1: 0.2796
sub_15:Test (Best Model) - Loss: 2.2674 - Accuracy: 0.7353 - F1: 0.7266
sub_13:Test (Best Model) - Loss: 2.7485 - Accuracy: 0.5735 - F1: 0.5660
sub_15:Test (Best Model) - Loss: 7.4045 - Accuracy: 0.5441 - F1: 0.5471
sub_14:Test (Best Model) - Loss: 12.9324 - Accuracy: 0.3235 - F1: 0.2909
sub_13:Test (Best Model) - Loss: 3.6819 - Accuracy: 0.4118 - F1: 0.3768
sub_13:Test (Best Model) - Loss: 3.9454 - Accuracy: 0.4058 - F1: 0.3592
sub_15:Test (Best Model) - Loss: 0.8369 - Accuracy: 0.6765 - F1: 0.6628
sub_14:Test (Best Model) - Loss: 25.3561 - Accuracy: 0.2353 - F1: 0.1489
sub_15:Test (Best Model) - Loss: 1.2545 - Accuracy: 0.6324 - F1: 0.6392
sub_13:Test (Best Model) - Loss: 5.9763 - Accuracy: 0.2899 - F1: 0.2512
sub_14:Test (Best Model) - Loss: 5.9733 - Accuracy: 0.4412 - F1: 0.4497
sub_15:Test (Best Model) - Loss: 0.5899 - Accuracy: 0.7941 - F1: 0.7943
sub_14:Test (Best Model) - Loss: 6.8397 - Accuracy: 0.4559 - F1: 0.4309
sub_13:Test (Best Model) - Loss: 9.5797 - Accuracy: 0.4493 - F1: 0.4027
sub_15:Test (Best Model) - Loss: 1.2481 - Accuracy: 0.7059 - F1: 0.7083
sub_14:Test (Best Model) - Loss: 5.6502 - Accuracy: 0.5294 - F1: 0.5492
sub_13:Test (Best Model) - Loss: 9.7617 - Accuracy: 0.3043 - F1: 0.2409
sub_14:Test (Best Model) - Loss: 5.0333 - Accuracy: 0.5735 - F1: 0.5521
sub_15:Test (Best Model) - Loss: 0.7565 - Accuracy: 0.7794 - F1: 0.7867
sub_14:Test (Best Model) - Loss: 5.5632 - Accuracy: 0.3824 - F1: 0.3663
sub_13:Test (Best Model) - Loss: 9.8056 - Accuracy: 0.2174 - F1: 0.1637
sub_15:Test (Best Model) - Loss: 3.7006 - Accuracy: 0.5441 - F1: 0.4475
sub_13:Test (Best Model) - Loss: 2.4902 - Accuracy: 0.4853 - F1: 0.4633
sub_14:Test (Best Model) - Loss: 3.4214 - Accuracy: 0.5882 - F1: 0.5469
sub_15:Test (Best Model) - Loss: 2.2746 - Accuracy: 0.6324 - F1: 0.5838
sub_14:Test (Best Model) - Loss: 4.1288 - Accuracy: 0.4265 - F1: 0.3939
sub_13:Test (Best Model) - Loss: 5.5769 - Accuracy: 0.5147 - F1: 0.4760
sub_14:Test (Best Model) - Loss: 2.4575 - Accuracy: 0.4706 - F1: 0.4607
sub_15:Test (Best Model) - Loss: 4.3749 - Accuracy: 0.6324 - F1: 0.5678
sub_13:Test (Best Model) - Loss: 7.6255 - Accuracy: 0.5000 - F1: 0.4599
sub_14:Test (Best Model) - Loss: 4.4998 - Accuracy: 0.5294 - F1: 0.5281
sub_15:Test (Best Model) - Loss: 3.2163 - Accuracy: 0.5588 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 9.0145 - Accuracy: 0.3971 - F1: 0.3449
sub_14:Test (Best Model) - Loss: 5.5248 - Accuracy: 0.3824 - F1: 0.3800
sub_15:Test (Best Model) - Loss: 4.2063 - Accuracy: 0.5882 - F1: 0.5256
sub_13:Test (Best Model) - Loss: 5.9931 - Accuracy: 0.4706 - F1: 0.4341
sub_18:Test (Best Model) - Loss: 2.5681 - Accuracy: 0.5507 - F1: 0.5110
sub_16:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.7353 - F1: 0.7231
sub_17:Test (Best Model) - Loss: 1.9172 - Accuracy: 0.6087 - F1: 0.6073
sub_16:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.7059 - F1: 0.6965
sub_18:Test (Best Model) - Loss: 0.9634 - Accuracy: 0.7246 - F1: 0.7273
sub_17:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.6087 - F1: 0.6067
sub_16:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.7059 - F1: 0.7078
sub_17:Test (Best Model) - Loss: 1.8064 - Accuracy: 0.6087 - F1: 0.6120
sub_18:Test (Best Model) - Loss: 1.9876 - Accuracy: 0.6232 - F1: 0.6209
sub_16:Test (Best Model) - Loss: 1.5361 - Accuracy: 0.7059 - F1: 0.7018
sub_18:Test (Best Model) - Loss: 2.5124 - Accuracy: 0.5797 - F1: 0.5792
sub_17:Test (Best Model) - Loss: 1.9646 - Accuracy: 0.5797 - F1: 0.5776
sub_16:Test (Best Model) - Loss: 1.4270 - Accuracy: 0.7500 - F1: 0.7507
sub_18:Test (Best Model) - Loss: 2.9511 - Accuracy: 0.5652 - F1: 0.5109
sub_17:Test (Best Model) - Loss: 1.0614 - Accuracy: 0.6087 - F1: 0.5863
sub_16:Test (Best Model) - Loss: 6.6298 - Accuracy: 0.4412 - F1: 0.3712
sub_18:Test (Best Model) - Loss: 9.2132 - Accuracy: 0.3529 - F1: 0.3011
sub_17:Test (Best Model) - Loss: 1.1214 - Accuracy: 0.5507 - F1: 0.5573
sub_17:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.5652 - F1: 0.5518
sub_18:Test (Best Model) - Loss: 4.0944 - Accuracy: 0.3971 - F1: 0.3753
sub_16:Test (Best Model) - Loss: 6.5961 - Accuracy: 0.3382 - F1: 0.2324
sub_17:Test (Best Model) - Loss: 1.8513 - Accuracy: 0.5507 - F1: 0.5573
sub_18:Test (Best Model) - Loss: 2.3685 - Accuracy: 0.5441 - F1: 0.5229
sub_16:Test (Best Model) - Loss: 4.2690 - Accuracy: 0.5294 - F1: 0.5125
sub_17:Test (Best Model) - Loss: 2.4046 - Accuracy: 0.4493 - F1: 0.4751
sub_16:Test (Best Model) - Loss: 3.1104 - Accuracy: 0.6176 - F1: 0.5784
sub_18:Test (Best Model) - Loss: 3.2833 - Accuracy: 0.5441 - F1: 0.5272
sub_17:Test (Best Model) - Loss: 1.6881 - Accuracy: 0.5217 - F1: 0.5245
sub_18:Test (Best Model) - Loss: 3.5325 - Accuracy: 0.4706 - F1: 0.4814
sub_17:Test (Best Model) - Loss: 2.6846 - Accuracy: 0.5294 - F1: 0.4789
sub_16:Test (Best Model) - Loss: 4.7448 - Accuracy: 0.3971 - F1: 0.3379
sub_18:Test (Best Model) - Loss: 3.3994 - Accuracy: 0.5147 - F1: 0.4720
sub_17:Test (Best Model) - Loss: 1.4524 - Accuracy: 0.5735 - F1: 0.5288
sub_16:Test (Best Model) - Loss: 5.8518 - Accuracy: 0.4853 - F1: 0.4588
sub_17:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.5588 - F1: 0.4890
sub_18:Test (Best Model) - Loss: 6.0060 - Accuracy: 0.5000 - F1: 0.4938
sub_17:Test (Best Model) - Loss: 1.6944 - Accuracy: 0.6176 - F1: 0.5358
sub_18:Test (Best Model) - Loss: 4.5049 - Accuracy: 0.5735 - F1: 0.5722
sub_16:Test (Best Model) - Loss: 4.0141 - Accuracy: 0.5441 - F1: 0.4967
sub_17:Test (Best Model) - Loss: 3.1556 - Accuracy: 0.6765 - F1: 0.6332
sub_18:Test (Best Model) - Loss: 2.7949 - Accuracy: 0.3971 - F1: 0.4017
sub_16:Test (Best Model) - Loss: 8.0677 - Accuracy: 0.4412 - F1: 0.3536
sub_18:Test (Best Model) - Loss: 4.8157 - Accuracy: 0.4853 - F1: 0.4846
sub_16:Test (Best Model) - Loss: 6.0651 - Accuracy: 0.4706 - F1: 0.4528
sub_16:Test (Best Model) - Loss: 5.0202 - Accuracy: 0.5294 - F1: 0.4451
sub_20:Test (Best Model) - Loss: 2.0684 - Accuracy: 0.6765 - F1: 0.6594
sub_19:Test (Best Model) - Loss: 12.1776 - Accuracy: 0.3529 - F1: 0.2983
sub_21:Test (Best Model) - Loss: 2.9132 - Accuracy: 0.6176 - F1: 0.5767
sub_20:Test (Best Model) - Loss: 1.5168 - Accuracy: 0.6029 - F1: 0.5805
sub_19:Test (Best Model) - Loss: 6.5778 - Accuracy: 0.4559 - F1: 0.4442
sub_21:Test (Best Model) - Loss: 2.0666 - Accuracy: 0.6029 - F1: 0.5625
sub_20:Test (Best Model) - Loss: 1.8844 - Accuracy: 0.6324 - F1: 0.6205
sub_19:Test (Best Model) - Loss: 6.5244 - Accuracy: 0.4559 - F1: 0.4335
sub_20:Test (Best Model) - Loss: 1.1779 - Accuracy: 0.6471 - F1: 0.6400
sub_19:Test (Best Model) - Loss: 5.0096 - Accuracy: 0.3529 - F1: 0.3367
sub_21:Test (Best Model) - Loss: 3.5376 - Accuracy: 0.5147 - F1: 0.4317
sub_20:Test (Best Model) - Loss: 1.8410 - Accuracy: 0.6029 - F1: 0.5838
sub_19:Test (Best Model) - Loss: 7.4898 - Accuracy: 0.3529 - F1: 0.3509
sub_20:Test (Best Model) - Loss: 1.7448 - Accuracy: 0.7206 - F1: 0.6975
sub_21:Test (Best Model) - Loss: 4.1480 - Accuracy: 0.5735 - F1: 0.5119
sub_19:Test (Best Model) - Loss: 5.5352 - Accuracy: 0.6618 - F1: 0.6466
sub_20:Test (Best Model) - Loss: 1.9064 - Accuracy: 0.7059 - F1: 0.6978
sub_21:Test (Best Model) - Loss: 3.9316 - Accuracy: 0.6324 - F1: 0.5891
sub_20:Test (Best Model) - Loss: 0.9279 - Accuracy: 0.7500 - F1: 0.7412
sub_19:Test (Best Model) - Loss: 2.0750 - Accuracy: 0.5000 - F1: 0.4232
sub_21:Test (Best Model) - Loss: 0.8325 - Accuracy: 0.6765 - F1: 0.6792
sub_20:Test (Best Model) - Loss: 1.2145 - Accuracy: 0.6765 - F1: 0.6584
sub_19:Test (Best Model) - Loss: 1.5035 - Accuracy: 0.6471 - F1: 0.6320
sub_21:Test (Best Model) - Loss: 4.2607 - Accuracy: 0.6618 - F1: 0.6567
sub_20:Test (Best Model) - Loss: 3.0653 - Accuracy: 0.7353 - F1: 0.7327
sub_19:Test (Best Model) - Loss: 5.7280 - Accuracy: 0.5735 - F1: 0.5348
sub_20:Test (Best Model) - Loss: 1.4795 - Accuracy: 0.6522 - F1: 0.6437
sub_21:Test (Best Model) - Loss: 1.5840 - Accuracy: 0.6471 - F1: 0.6422
sub_19:Test (Best Model) - Loss: 1.9037 - Accuracy: 0.5882 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 2.3111 - Accuracy: 0.6667 - F1: 0.6716
sub_21:Test (Best Model) - Loss: 1.8811 - Accuracy: 0.6765 - F1: 0.6716
sub_19:Test (Best Model) - Loss: 7.6047 - Accuracy: 0.5441 - F1: 0.5267
sub_20:Test (Best Model) - Loss: 1.1593 - Accuracy: 0.6522 - F1: 0.6353
sub_19:Test (Best Model) - Loss: 4.2961 - Accuracy: 0.5147 - F1: 0.5211
sub_21:Test (Best Model) - Loss: 1.9701 - Accuracy: 0.6618 - F1: 0.6496
sub_20:Test (Best Model) - Loss: 1.8023 - Accuracy: 0.6232 - F1: 0.6087
sub_20:Test (Best Model) - Loss: 3.0628 - Accuracy: 0.6377 - F1: 0.6362
sub_19:Test (Best Model) - Loss: 2.5362 - Accuracy: 0.6324 - F1: 0.6278
sub_21:Test (Best Model) - Loss: 1.8546 - Accuracy: 0.6618 - F1: 0.6348
sub_19:Test (Best Model) - Loss: 5.3358 - Accuracy: 0.5882 - F1: 0.5782
sub_21:Test (Best Model) - Loss: 1.8852 - Accuracy: 0.6471 - F1: 0.5997
sub_19:Test (Best Model) - Loss: 3.5677 - Accuracy: 0.6176 - F1: 0.6011
sub_21:Test (Best Model) - Loss: 1.5407 - Accuracy: 0.6618 - F1: 0.6162
sub_21:Test (Best Model) - Loss: 2.7858 - Accuracy: 0.6912 - F1: 0.6722
sub_21:Test (Best Model) - Loss: 4.1092 - Accuracy: 0.6029 - F1: 0.5540
sub_23:Test (Best Model) - Loss: 4.5427 - Accuracy: 0.5797 - F1: 0.5008
sub_22:Test (Best Model) - Loss: 4.2485 - Accuracy: 0.4853 - F1: 0.4637
sub_24:Test (Best Model) - Loss: 3.6226 - Accuracy: 0.5000 - F1: 0.4933
sub_23:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.6377 - F1: 0.6272
sub_22:Test (Best Model) - Loss: 6.2830 - Accuracy: 0.4853 - F1: 0.4462
sub_24:Test (Best Model) - Loss: 2.6037 - Accuracy: 0.5735 - F1: 0.5774
sub_23:Test (Best Model) - Loss: 1.4382 - Accuracy: 0.6232 - F1: 0.5552
sub_24:Test (Best Model) - Loss: 1.9617 - Accuracy: 0.4118 - F1: 0.4036
sub_23:Test (Best Model) - Loss: 1.5296 - Accuracy: 0.6087 - F1: 0.5875
sub_22:Test (Best Model) - Loss: 6.2564 - Accuracy: 0.5147 - F1: 0.4443
sub_23:Test (Best Model) - Loss: 1.6882 - Accuracy: 0.5797 - F1: 0.5531
sub_24:Test (Best Model) - Loss: 2.1196 - Accuracy: 0.4559 - F1: 0.4473
sub_22:Test (Best Model) - Loss: 8.6681 - Accuracy: 0.6029 - F1: 0.5606
sub_24:Test (Best Model) - Loss: 3.5716 - Accuracy: 0.5441 - F1: 0.5214
sub_23:Test (Best Model) - Loss: 5.3678 - Accuracy: 0.5735 - F1: 0.5288
sub_22:Test (Best Model) - Loss: 8.8699 - Accuracy: 0.5441 - F1: 0.5129
sub_23:Test (Best Model) - Loss: 5.3914 - Accuracy: 0.5441 - F1: 0.4563
sub_24:Test (Best Model) - Loss: 4.1954 - Accuracy: 0.4412 - F1: 0.4265
sub_22:Test (Best Model) - Loss: 3.7683 - Accuracy: 0.5797 - F1: 0.5182
sub_23:Test (Best Model) - Loss: 1.8560 - Accuracy: 0.6618 - F1: 0.6241
sub_22:Test (Best Model) - Loss: 2.1052 - Accuracy: 0.6522 - F1: 0.6299
sub_24:Test (Best Model) - Loss: 2.1107 - Accuracy: 0.5735 - F1: 0.5780
sub_23:Test (Best Model) - Loss: 4.6411 - Accuracy: 0.6029 - F1: 0.5337
sub_22:Test (Best Model) - Loss: 3.1234 - Accuracy: 0.6957 - F1: 0.6927
sub_23:Test (Best Model) - Loss: 4.4767 - Accuracy: 0.5588 - F1: 0.5207
sub_24:Test (Best Model) - Loss: 3.1893 - Accuracy: 0.5588 - F1: 0.5461
sub_22:Test (Best Model) - Loss: 4.5800 - Accuracy: 0.5507 - F1: 0.5396
sub_23:Test (Best Model) - Loss: 3.8390 - Accuracy: 0.5652 - F1: 0.5532
sub_22:Test (Best Model) - Loss: 3.1301 - Accuracy: 0.5942 - F1: 0.5746
sub_24:Test (Best Model) - Loss: 1.9033 - Accuracy: 0.6176 - F1: 0.6232
sub_23:Test (Best Model) - Loss: 1.9399 - Accuracy: 0.6812 - F1: 0.6892
sub_22:Test (Best Model) - Loss: 3.0042 - Accuracy: 0.3382 - F1: 0.2801
sub_24:Test (Best Model) - Loss: 2.0129 - Accuracy: 0.4706 - F1: 0.4557
sub_23:Test (Best Model) - Loss: 5.8528 - Accuracy: 0.6087 - F1: 0.5918
sub_22:Test (Best Model) - Loss: 8.4486 - Accuracy: 0.3088 - F1: 0.2664
sub_24:Test (Best Model) - Loss: 4.2667 - Accuracy: 0.5000 - F1: 0.4925
sub_23:Test (Best Model) - Loss: 4.4469 - Accuracy: 0.6957 - F1: 0.6823
sub_22:Test (Best Model) - Loss: 8.5663 - Accuracy: 0.2647 - F1: 0.2375
sub_24:Test (Best Model) - Loss: 5.4271 - Accuracy: 0.5294 - F1: 0.5197
sub_23:Test (Best Model) - Loss: 7.6159 - Accuracy: 0.6087 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 6.5598 - Accuracy: 0.3382 - F1: 0.3085
sub_24:Test (Best Model) - Loss: 2.2064 - Accuracy: 0.5000 - F1: 0.5207
sub_22:Test (Best Model) - Loss: 6.4341 - Accuracy: 0.3235 - F1: 0.2877
sub_24:Test (Best Model) - Loss: 4.7348 - Accuracy: 0.3971 - F1: 0.3785
sub_24:Test (Best Model) - Loss: 3.7393 - Accuracy: 0.4853 - F1: 0.4971
sub_26:Test (Best Model) - Loss: 2.2668 - Accuracy: 0.5362 - F1: 0.5355
sub_25:Test (Best Model) - Loss: 1.5925 - Accuracy: 0.7101 - F1: 0.7037
sub_27:Test (Best Model) - Loss: 1.9172 - Accuracy: 0.6087 - F1: 0.6073
sub_26:Test (Best Model) - Loss: 2.0304 - Accuracy: 0.6087 - F1: 0.6144
sub_25:Test (Best Model) - Loss: 1.3171 - Accuracy: 0.7246 - F1: 0.7200
sub_27:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.6087 - F1: 0.6067
sub_26:Test (Best Model) - Loss: 1.5878 - Accuracy: 0.5942 - F1: 0.5916
sub_25:Test (Best Model) - Loss: 1.9463 - Accuracy: 0.7246 - F1: 0.7189
sub_27:Test (Best Model) - Loss: 1.8064 - Accuracy: 0.6087 - F1: 0.6120
sub_25:Test (Best Model) - Loss: 2.2573 - Accuracy: 0.6957 - F1: 0.6878
sub_26:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.6087 - F1: 0.6114
sub_27:Test (Best Model) - Loss: 1.9646 - Accuracy: 0.5797 - F1: 0.5776
sub_25:Test (Best Model) - Loss: 2.4355 - Accuracy: 0.7391 - F1: 0.7382
sub_26:Test (Best Model) - Loss: 1.2473 - Accuracy: 0.6087 - F1: 0.6133
sub_27:Test (Best Model) - Loss: 1.0614 - Accuracy: 0.6087 - F1: 0.5863
sub_25:Test (Best Model) - Loss: 1.4976 - Accuracy: 0.6176 - F1: 0.6045
sub_27:Test (Best Model) - Loss: 1.1214 - Accuracy: 0.5507 - F1: 0.5573
sub_26:Test (Best Model) - Loss: 1.7521 - Accuracy: 0.5588 - F1: 0.5531
sub_27:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.5652 - F1: 0.5518
sub_25:Test (Best Model) - Loss: 0.8680 - Accuracy: 0.6324 - F1: 0.6222
sub_26:Test (Best Model) - Loss: 0.9375 - Accuracy: 0.6471 - F1: 0.6285
sub_27:Test (Best Model) - Loss: 1.8513 - Accuracy: 0.5507 - F1: 0.5573
sub_25:Test (Best Model) - Loss: 1.9661 - Accuracy: 0.5441 - F1: 0.5263
sub_26:Test (Best Model) - Loss: 1.0424 - Accuracy: 0.6029 - F1: 0.5842
sub_27:Test (Best Model) - Loss: 2.4046 - Accuracy: 0.4493 - F1: 0.4751
sub_25:Test (Best Model) - Loss: 0.9625 - Accuracy: 0.6618 - F1: 0.6557
sub_26:Test (Best Model) - Loss: 1.4426 - Accuracy: 0.6618 - F1: 0.6491
sub_25:Test (Best Model) - Loss: 1.6477 - Accuracy: 0.6618 - F1: 0.6484
sub_27:Test (Best Model) - Loss: 1.6881 - Accuracy: 0.5217 - F1: 0.5245
sub_26:Test (Best Model) - Loss: 1.0562 - Accuracy: 0.6471 - F1: 0.6200
sub_26:Test (Best Model) - Loss: 1.9935 - Accuracy: 0.5441 - F1: 0.5248
sub_25:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.6912 - F1: 0.6901
sub_27:Test (Best Model) - Loss: 2.6846 - Accuracy: 0.5294 - F1: 0.4789
sub_27:Test (Best Model) - Loss: 1.4524 - Accuracy: 0.5735 - F1: 0.5288
sub_26:Test (Best Model) - Loss: 3.6639 - Accuracy: 0.5588 - F1: 0.5194
sub_25:Test (Best Model) - Loss: 2.0465 - Accuracy: 0.6618 - F1: 0.5885
sub_27:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.5588 - F1: 0.4890
sub_26:Test (Best Model) - Loss: 3.5281 - Accuracy: 0.6176 - F1: 0.5623
sub_25:Test (Best Model) - Loss: 1.6345 - Accuracy: 0.7059 - F1: 0.6349
sub_27:Test (Best Model) - Loss: 1.6944 - Accuracy: 0.6176 - F1: 0.5358
sub_26:Test (Best Model) - Loss: 2.1874 - Accuracy: 0.5294 - F1: 0.4923
sub_25:Test (Best Model) - Loss: 0.8163 - Accuracy: 0.7206 - F1: 0.6648
sub_26:Test (Best Model) - Loss: 4.4116 - Accuracy: 0.4559 - F1: 0.4344
sub_27:Test (Best Model) - Loss: 3.1556 - Accuracy: 0.6765 - F1: 0.6332
sub_25:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.7059 - F1: 0.6715
sub_28:Test (Best Model) - Loss: 5.9098 - Accuracy: 0.3529 - F1: 0.2929
sub_29:Test (Best Model) - Loss: 1.8571 - Accuracy: 0.6176 - F1: 0.6201
sub_28:Test (Best Model) - Loss: 5.2961 - Accuracy: 0.4118 - F1: 0.3801
sub_29:Test (Best Model) - Loss: 1.9161 - Accuracy: 0.5735 - F1: 0.5489
sub_28:Test (Best Model) - Loss: 4.3176 - Accuracy: 0.3971 - F1: 0.3817
sub_29:Test (Best Model) - Loss: 2.7267 - Accuracy: 0.6471 - F1: 0.6279
sub_28:Test (Best Model) - Loss: 6.0874 - Accuracy: 0.4118 - F1: 0.3585
sub_29:Test (Best Model) - Loss: 2.4910 - Accuracy: 0.6029 - F1: 0.5813
sub_28:Test (Best Model) - Loss: 11.2468 - Accuracy: 0.4412 - F1: 0.3733
sub_29:Test (Best Model) - Loss: 3.4810 - Accuracy: 0.5882 - F1: 0.5880
sub_28:Test (Best Model) - Loss: 11.8066 - Accuracy: 0.4706 - F1: 0.3750
sub_29:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.6471 - F1: 0.6475
sub_28:Test (Best Model) - Loss: 10.1047 - Accuracy: 0.4559 - F1: 0.3729
sub_29:Test (Best Model) - Loss: 1.4766 - Accuracy: 0.5735 - F1: 0.5675
sub_29:Test (Best Model) - Loss: 1.8114 - Accuracy: 0.6029 - F1: 0.5920
sub_28:Test (Best Model) - Loss: 5.3691 - Accuracy: 0.4853 - F1: 0.4127
sub_29:Test (Best Model) - Loss: 1.2629 - Accuracy: 0.5294 - F1: 0.4997
sub_28:Test (Best Model) - Loss: 8.4007 - Accuracy: 0.4559 - F1: 0.3607
sub_29:Test (Best Model) - Loss: 1.5403 - Accuracy: 0.7059 - F1: 0.7028
sub_29:Test (Best Model) - Loss: 2.3048 - Accuracy: 0.4493 - F1: 0.4346
sub_28:Test (Best Model) - Loss: 6.9572 - Accuracy: 0.4412 - F1: 0.4135
sub_29:Test (Best Model) - Loss: 1.2009 - Accuracy: 0.5072 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 19.6236 - Accuracy: 0.3529 - F1: 0.2571
sub_29:Test (Best Model) - Loss: 2.7874 - Accuracy: 0.4783 - F1: 0.4674
sub_28:Test (Best Model) - Loss: 7.8191 - Accuracy: 0.3824 - F1: 0.3023
sub_29:Test (Best Model) - Loss: 3.4578 - Accuracy: 0.3913 - F1: 0.3529
sub_28:Test (Best Model) - Loss: 9.9345 - Accuracy: 0.4118 - F1: 0.3351
sub_28:Test (Best Model) - Loss: 8.2614 - Accuracy: 0.3824 - F1: 0.3288
sub_29:Test (Best Model) - Loss: 2.1986 - Accuracy: 0.4928 - F1: 0.4873
sub_28:Test (Best Model) - Loss: 11.4207 - Accuracy: 0.3235 - F1: 0.2905

=== Summary Results ===

acc: 55.75 ± 7.44
F1: 53.34 ± 8.00
acc-in: 83.08 ± 4.42
F1-in: 82.52 ± 4.75
runing time: 2437.09 seconds
