lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.3382 - F1: 0.2640
sub_2:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.4638 - F1: 0.4703
sub_3:Test (Best Model) - Loss: 1.4323 - Accuracy: 0.6618 - F1: 0.6242
sub_1:Test (Best Model) - Loss: 1.4385 - Accuracy: 0.4559 - F1: 0.4108
sub_3:Test (Best Model) - Loss: 0.9255 - Accuracy: 0.7206 - F1: 0.6939
sub_2:Test (Best Model) - Loss: 2.2813 - Accuracy: 0.4203 - F1: 0.4216
sub_1:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.6029 - F1: 0.6092
sub_3:Test (Best Model) - Loss: 0.7130 - Accuracy: 0.7647 - F1: 0.7524
sub_1:Test (Best Model) - Loss: 1.4560 - Accuracy: 0.5441 - F1: 0.5344
sub_2:Test (Best Model) - Loss: 1.4711 - Accuracy: 0.5072 - F1: 0.5158
sub_3:Test (Best Model) - Loss: 1.1657 - Accuracy: 0.7059 - F1: 0.6758
sub_2:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.4783 - F1: 0.4190
sub_1:Test (Best Model) - Loss: 1.7185 - Accuracy: 0.5735 - F1: 0.5793
sub_3:Test (Best Model) - Loss: 0.8699 - Accuracy: 0.7206 - F1: 0.6741
sub_2:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.5652 - F1: 0.5343
sub_1:Test (Best Model) - Loss: 2.3703 - Accuracy: 0.3768 - F1: 0.3076
sub_3:Test (Best Model) - Loss: 2.5303 - Accuracy: 0.5507 - F1: 0.5234
sub_1:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.3043 - F1: 0.1977
sub_2:Test (Best Model) - Loss: 0.7374 - Accuracy: 0.6618 - F1: 0.6495
sub_1:Test (Best Model) - Loss: 2.3785 - Accuracy: 0.4928 - F1: 0.4647
sub_3:Test (Best Model) - Loss: 2.3719 - Accuracy: 0.5507 - F1: 0.5324
sub_1:Test (Best Model) - Loss: 2.1401 - Accuracy: 0.4348 - F1: 0.3877
sub_2:Test (Best Model) - Loss: 0.8128 - Accuracy: 0.6324 - F1: 0.6383
sub_3:Test (Best Model) - Loss: 2.1611 - Accuracy: 0.6087 - F1: 0.5849
sub_2:Test (Best Model) - Loss: 0.8418 - Accuracy: 0.4412 - F1: 0.2971
sub_2:Test (Best Model) - Loss: 0.7402 - Accuracy: 0.6912 - F1: 0.6498
sub_1:Test (Best Model) - Loss: 3.4451 - Accuracy: 0.5217 - F1: 0.4976
sub_3:Test (Best Model) - Loss: 3.1919 - Accuracy: 0.5797 - F1: 0.5461
sub_1:Test (Best Model) - Loss: 0.9052 - Accuracy: 0.6618 - F1: 0.6072
sub_3:Test (Best Model) - Loss: 2.2678 - Accuracy: 0.5507 - F1: 0.5029
sub_2:Test (Best Model) - Loss: 0.5943 - Accuracy: 0.7500 - F1: 0.7525
sub_1:Test (Best Model) - Loss: 1.0704 - Accuracy: 0.6912 - F1: 0.6399
sub_3:Test (Best Model) - Loss: 1.1508 - Accuracy: 0.6812 - F1: 0.6549
sub_2:Test (Best Model) - Loss: 1.1562 - Accuracy: 0.6522 - F1: 0.6121
sub_3:Test (Best Model) - Loss: 0.9631 - Accuracy: 0.7101 - F1: 0.6988
sub_2:Test (Best Model) - Loss: 1.0993 - Accuracy: 0.4058 - F1: 0.2725
sub_1:Test (Best Model) - Loss: 0.8836 - Accuracy: 0.6912 - F1: 0.6280
sub_1:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.7206 - F1: 0.6550
sub_3:Test (Best Model) - Loss: 1.1409 - Accuracy: 0.7246 - F1: 0.7170
sub_2:Test (Best Model) - Loss: 1.8131 - Accuracy: 0.6232 - F1: 0.5968
sub_1:Test (Best Model) - Loss: 0.7387 - Accuracy: 0.7500 - F1: 0.7058
sub_2:Test (Best Model) - Loss: 1.0617 - Accuracy: 0.4928 - F1: 0.3700
sub_3:Test (Best Model) - Loss: 0.9336 - Accuracy: 0.7536 - F1: 0.7578
sub_2:Test (Best Model) - Loss: 0.8512 - Accuracy: 0.5072 - F1: 0.4157
sub_3:Test (Best Model) - Loss: 1.0363 - Accuracy: 0.6087 - F1: 0.5871
sub_4:Test (Best Model) - Loss: 1.1346 - Accuracy: 0.4493 - F1: 0.3037
sub_5:Test (Best Model) - Loss: 1.4287 - Accuracy: 0.4412 - F1: 0.3414
sub_6:Test (Best Model) - Loss: 2.2220 - Accuracy: 0.3088 - F1: 0.1936
sub_4:Test (Best Model) - Loss: 1.1654 - Accuracy: 0.4928 - F1: 0.3851
sub_6:Test (Best Model) - Loss: 4.1964 - Accuracy: 0.3676 - F1: 0.2966
sub_4:Test (Best Model) - Loss: 1.1139 - Accuracy: 0.4783 - F1: 0.3923
sub_5:Test (Best Model) - Loss: 3.0131 - Accuracy: 0.5294 - F1: 0.4823
sub_4:Test (Best Model) - Loss: 1.1923 - Accuracy: 0.4348 - F1: 0.3166
sub_6:Test (Best Model) - Loss: 4.2203 - Accuracy: 0.4412 - F1: 0.3693
sub_5:Test (Best Model) - Loss: 1.2093 - Accuracy: 0.6471 - F1: 0.6224
sub_4:Test (Best Model) - Loss: 1.1102 - Accuracy: 0.4203 - F1: 0.3640
sub_4:Test (Best Model) - Loss: 1.5706 - Accuracy: 0.3043 - F1: 0.2269
sub_6:Test (Best Model) - Loss: 4.6426 - Accuracy: 0.3971 - F1: 0.3344
sub_5:Test (Best Model) - Loss: 2.0867 - Accuracy: 0.6029 - F1: 0.5589
sub_4:Test (Best Model) - Loss: 3.3388 - Accuracy: 0.3333 - F1: 0.3008
sub_6:Test (Best Model) - Loss: 4.4085 - Accuracy: 0.4412 - F1: 0.3757
sub_5:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.5147 - F1: 0.4953
sub_6:Test (Best Model) - Loss: 1.9164 - Accuracy: 0.4348 - F1: 0.3071
sub_4:Test (Best Model) - Loss: 1.4210 - Accuracy: 0.5217 - F1: 0.5044
sub_5:Test (Best Model) - Loss: 1.2978 - Accuracy: 0.4118 - F1: 0.3607
sub_6:Test (Best Model) - Loss: 1.1591 - Accuracy: 0.3478 - F1: 0.2690
sub_4:Test (Best Model) - Loss: 1.4057 - Accuracy: 0.3043 - F1: 0.2282
sub_6:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.4348 - F1: 0.4099
sub_5:Test (Best Model) - Loss: 3.5219 - Accuracy: 0.4265 - F1: 0.3900
sub_6:Test (Best Model) - Loss: 1.4880 - Accuracy: 0.5362 - F1: 0.4506
sub_5:Test (Best Model) - Loss: 1.2935 - Accuracy: 0.4559 - F1: 0.3720
sub_4:Test (Best Model) - Loss: 3.2999 - Accuracy: 0.4058 - F1: 0.3429
sub_5:Test (Best Model) - Loss: 3.6092 - Accuracy: 0.4706 - F1: 0.4147
sub_6:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.5507 - F1: 0.4824
sub_4:Test (Best Model) - Loss: 0.9005 - Accuracy: 0.5652 - F1: 0.5335
sub_5:Test (Best Model) - Loss: 1.1488 - Accuracy: 0.4118 - F1: 0.3168
sub_6:Test (Best Model) - Loss: 0.9805 - Accuracy: 0.4783 - F1: 0.4241
sub_5:Test (Best Model) - Loss: 1.4311 - Accuracy: 0.3824 - F1: 0.3099
sub_4:Test (Best Model) - Loss: 0.9449 - Accuracy: 0.5942 - F1: 0.5230
sub_6:Test (Best Model) - Loss: 0.8504 - Accuracy: 0.6522 - F1: 0.5850
sub_4:Test (Best Model) - Loss: 1.0566 - Accuracy: 0.4638 - F1: 0.3672
sub_5:Test (Best Model) - Loss: 1.1989 - Accuracy: 0.5294 - F1: 0.4612
sub_6:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.7101 - F1: 0.7098
sub_4:Test (Best Model) - Loss: 1.0687 - Accuracy: 0.5072 - F1: 0.4313
sub_5:Test (Best Model) - Loss: 1.1779 - Accuracy: 0.4118 - F1: 0.3102
sub_6:Test (Best Model) - Loss: 0.9714 - Accuracy: 0.4058 - F1: 0.3085
sub_6:Test (Best Model) - Loss: 0.9920 - Accuracy: 0.4203 - F1: 0.3472
sub_4:Test (Best Model) - Loss: 1.0793 - Accuracy: 0.5797 - F1: 0.5388
sub_5:Test (Best Model) - Loss: 1.2036 - Accuracy: 0.5294 - F1: 0.4630
sub_5:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.4265 - F1: 0.3787
sub_8:Test (Best Model) - Loss: 1.9791 - Accuracy: 0.2941 - F1: 0.1619
sub_9:Test (Best Model) - Loss: 4.8449 - Accuracy: 0.3824 - F1: 0.4106
sub_7:Test (Best Model) - Loss: 1.0361 - Accuracy: 0.5441 - F1: 0.5302
sub_7:Test (Best Model) - Loss: 1.0663 - Accuracy: 0.6618 - F1: 0.6665
sub_8:Test (Best Model) - Loss: 2.3593 - Accuracy: 0.4265 - F1: 0.3672
sub_9:Test (Best Model) - Loss: 3.0427 - Accuracy: 0.4118 - F1: 0.4364
sub_7:Test (Best Model) - Loss: 1.1063 - Accuracy: 0.5882 - F1: 0.5829
sub_9:Test (Best Model) - Loss: 1.7160 - Accuracy: 0.1176 - F1: 0.0741
sub_7:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.5441 - F1: 0.5332
sub_8:Test (Best Model) - Loss: 2.7970 - Accuracy: 0.3971 - F1: 0.3340
sub_8:Test (Best Model) - Loss: 1.7055 - Accuracy: 0.3235 - F1: 0.2176
sub_7:Test (Best Model) - Loss: 2.4693 - Accuracy: 0.5735 - F1: 0.5549
sub_9:Test (Best Model) - Loss: 3.2704 - Accuracy: 0.3382 - F1: 0.3782
sub_9:Test (Best Model) - Loss: 2.0153 - Accuracy: 0.1912 - F1: 0.2061
sub_8:Test (Best Model) - Loss: 2.9013 - Accuracy: 0.4118 - F1: 0.3221
sub_7:Test (Best Model) - Loss: 1.4318 - Accuracy: 0.6324 - F1: 0.6387
sub_8:Test (Best Model) - Loss: 1.1547 - Accuracy: 0.6176 - F1: 0.6065
sub_9:Test (Best Model) - Loss: 1.0313 - Accuracy: 0.5294 - F1: 0.4520
sub_7:Test (Best Model) - Loss: 0.8890 - Accuracy: 0.5735 - F1: 0.5566
sub_8:Test (Best Model) - Loss: 1.0759 - Accuracy: 0.5441 - F1: 0.4738
sub_9:Test (Best Model) - Loss: 1.4234 - Accuracy: 0.2059 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 1.2779 - Accuracy: 0.6471 - F1: 0.6549
sub_9:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.4559 - F1: 0.4222
sub_8:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.6471 - F1: 0.6427
sub_7:Test (Best Model) - Loss: 1.0232 - Accuracy: 0.6471 - F1: 0.6483
sub_9:Test (Best Model) - Loss: 0.9301 - Accuracy: 0.4706 - F1: 0.4460
sub_8:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.6324 - F1: 0.6299
sub_7:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.6618 - F1: 0.6708
sub_9:Test (Best Model) - Loss: 1.0255 - Accuracy: 0.5294 - F1: 0.4730
sub_8:Test (Best Model) - Loss: 1.2299 - Accuracy: 0.6765 - F1: 0.6727
sub_7:Test (Best Model) - Loss: 2.5812 - Accuracy: 0.6618 - F1: 0.6568
sub_9:Test (Best Model) - Loss: 3.0323 - Accuracy: 0.2206 - F1: 0.2609
sub_8:Test (Best Model) - Loss: 1.9090 - Accuracy: 0.6765 - F1: 0.6594
sub_9:Test (Best Model) - Loss: 3.4243 - Accuracy: 0.2206 - F1: 0.2749
sub_8:Test (Best Model) - Loss: 1.6987 - Accuracy: 0.6176 - F1: 0.5719
sub_7:Test (Best Model) - Loss: 1.2018 - Accuracy: 0.6618 - F1: 0.6532
sub_9:Test (Best Model) - Loss: 3.2347 - Accuracy: 0.2206 - F1: 0.2521
sub_8:Test (Best Model) - Loss: 2.7271 - Accuracy: 0.6471 - F1: 0.6295
sub_7:Test (Best Model) - Loss: 1.1606 - Accuracy: 0.6176 - F1: 0.6194
sub_9:Test (Best Model) - Loss: 2.5449 - Accuracy: 0.2941 - F1: 0.3152
sub_7:Test (Best Model) - Loss: 1.3120 - Accuracy: 0.6324 - F1: 0.6284
sub_8:Test (Best Model) - Loss: 3.3353 - Accuracy: 0.6618 - F1: 0.6452
sub_7:Test (Best Model) - Loss: 0.9699 - Accuracy: 0.6029 - F1: 0.5856
sub_9:Test (Best Model) - Loss: 4.4500 - Accuracy: 0.3088 - F1: 0.3031
sub_8:Test (Best Model) - Loss: 1.7214 - Accuracy: 0.6618 - F1: 0.6339
sub_10:Test (Best Model) - Loss: 4.7120 - Accuracy: 0.4118 - F1: 0.3976
sub_11:Test (Best Model) - Loss: 0.9495 - Accuracy: 0.6232 - F1: 0.5873
sub_12:Test (Best Model) - Loss: 1.7445 - Accuracy: 0.6471 - F1: 0.6550
sub_10:Test (Best Model) - Loss: 4.0744 - Accuracy: 0.3824 - F1: 0.3729
sub_11:Test (Best Model) - Loss: 0.9547 - Accuracy: 0.5942 - F1: 0.5555
sub_12:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.6912 - F1: 0.7008
sub_11:Test (Best Model) - Loss: 1.0136 - Accuracy: 0.5652 - F1: 0.5312
sub_10:Test (Best Model) - Loss: 4.4924 - Accuracy: 0.3971 - F1: 0.3873
sub_12:Test (Best Model) - Loss: 1.5263 - Accuracy: 0.6912 - F1: 0.7032
sub_11:Test (Best Model) - Loss: 0.9475 - Accuracy: 0.6087 - F1: 0.5894
sub_10:Test (Best Model) - Loss: 2.1773 - Accuracy: 0.2647 - F1: 0.2277
sub_11:Test (Best Model) - Loss: 0.8692 - Accuracy: 0.6522 - F1: 0.6130
sub_10:Test (Best Model) - Loss: 5.3349 - Accuracy: 0.3824 - F1: 0.3709
sub_12:Test (Best Model) - Loss: 1.5716 - Accuracy: 0.7500 - F1: 0.7534
sub_11:Test (Best Model) - Loss: 1.4861 - Accuracy: 0.5942 - F1: 0.5464
sub_10:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.6912 - F1: 0.6570
sub_12:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.6324 - F1: 0.6341
sub_11:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.5797 - F1: 0.5244
sub_10:Test (Best Model) - Loss: 2.7384 - Accuracy: 0.6471 - F1: 0.6592
sub_12:Test (Best Model) - Loss: 2.0186 - Accuracy: 0.5652 - F1: 0.5809
sub_11:Test (Best Model) - Loss: 1.2625 - Accuracy: 0.5507 - F1: 0.5218
sub_12:Test (Best Model) - Loss: 1.0804 - Accuracy: 0.5362 - F1: 0.5529
sub_10:Test (Best Model) - Loss: 3.3913 - Accuracy: 0.6324 - F1: 0.6464
sub_11:Test (Best Model) - Loss: 1.1707 - Accuracy: 0.6377 - F1: 0.6114
sub_12:Test (Best Model) - Loss: 1.1379 - Accuracy: 0.5217 - F1: 0.5396
sub_11:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.6087 - F1: 0.5922
sub_10:Test (Best Model) - Loss: 4.3658 - Accuracy: 0.6471 - F1: 0.6626
sub_11:Test (Best Model) - Loss: 1.0239 - Accuracy: 0.5797 - F1: 0.5720
sub_12:Test (Best Model) - Loss: 1.0595 - Accuracy: 0.5362 - F1: 0.5580
sub_10:Test (Best Model) - Loss: 4.6533 - Accuracy: 0.6324 - F1: 0.6388
sub_11:Test (Best Model) - Loss: 0.9879 - Accuracy: 0.6232 - F1: 0.6107
sub_12:Test (Best Model) - Loss: 1.2789 - Accuracy: 0.5217 - F1: 0.5334
sub_10:Test (Best Model) - Loss: 1.0059 - Accuracy: 0.6232 - F1: 0.6089
sub_11:Test (Best Model) - Loss: 1.1553 - Accuracy: 0.4203 - F1: 0.3200
sub_12:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.6029 - F1: 0.5916
sub_11:Test (Best Model) - Loss: 1.1887 - Accuracy: 0.4348 - F1: 0.3506
sub_10:Test (Best Model) - Loss: 1.0161 - Accuracy: 0.6377 - F1: 0.6110
sub_12:Test (Best Model) - Loss: 0.9332 - Accuracy: 0.6765 - F1: 0.6463
sub_10:Test (Best Model) - Loss: 0.9821 - Accuracy: 0.6522 - F1: 0.6510
sub_11:Test (Best Model) - Loss: 1.1873 - Accuracy: 0.6087 - F1: 0.5972
sub_12:Test (Best Model) - Loss: 0.8663 - Accuracy: 0.6324 - F1: 0.6214
sub_10:Test (Best Model) - Loss: 0.9420 - Accuracy: 0.6667 - F1: 0.6368
sub_12:Test (Best Model) - Loss: 0.9709 - Accuracy: 0.6618 - F1: 0.6482
sub_12:Test (Best Model) - Loss: 1.0464 - Accuracy: 0.6324 - F1: 0.5484
sub_10:Test (Best Model) - Loss: 1.2299 - Accuracy: 0.7101 - F1: 0.7029
sub_13:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.4706 - F1: 0.4434
sub_15:Test (Best Model) - Loss: 1.4357 - Accuracy: 0.4265 - F1: 0.3812
sub_14:Test (Best Model) - Loss: 1.7404 - Accuracy: 0.1176 - F1: 0.1014
sub_13:Test (Best Model) - Loss: 1.5938 - Accuracy: 0.5000 - F1: 0.5138
sub_15:Test (Best Model) - Loss: 1.8329 - Accuracy: 0.6324 - F1: 0.6313
sub_14:Test (Best Model) - Loss: 6.0582 - Accuracy: 0.2059 - F1: 0.1922
sub_13:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.5588 - F1: 0.5693
sub_15:Test (Best Model) - Loss: 2.1714 - Accuracy: 0.5294 - F1: 0.5566
sub_14:Test (Best Model) - Loss: 2.5929 - Accuracy: 0.1176 - F1: 0.0989
sub_15:Test (Best Model) - Loss: 1.9348 - Accuracy: 0.6471 - F1: 0.6469
sub_13:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.6176 - F1: 0.6189
sub_15:Test (Best Model) - Loss: 1.7852 - Accuracy: 0.5588 - F1: 0.5685
sub_13:Test (Best Model) - Loss: 1.7601 - Accuracy: 0.4706 - F1: 0.4526
sub_14:Test (Best Model) - Loss: 4.5070 - Accuracy: 0.2794 - F1: 0.2374
sub_13:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3188 - F1: 0.2642
sub_14:Test (Best Model) - Loss: 2.8482 - Accuracy: 0.2059 - F1: 0.1588
sub_15:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6029 - F1: 0.5716
sub_13:Test (Best Model) - Loss: 1.9856 - Accuracy: 0.2609 - F1: 0.2169
sub_14:Test (Best Model) - Loss: 1.8477 - Accuracy: 0.2500 - F1: 0.1720
sub_13:Test (Best Model) - Loss: 1.4680 - Accuracy: 0.3478 - F1: 0.2955
sub_15:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.6176 - F1: 0.5972
sub_14:Test (Best Model) - Loss: 2.1751 - Accuracy: 0.3529 - F1: 0.3442
sub_13:Test (Best Model) - Loss: 1.9780 - Accuracy: 0.2609 - F1: 0.2263
sub_14:Test (Best Model) - Loss: 2.4505 - Accuracy: 0.3235 - F1: 0.3042
sub_15:Test (Best Model) - Loss: 0.5476 - Accuracy: 0.7206 - F1: 0.7139
sub_13:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.3768 - F1: 0.3351
sub_13:Test (Best Model) - Loss: 1.0013 - Accuracy: 0.5294 - F1: 0.5002
sub_14:Test (Best Model) - Loss: 1.8838 - Accuracy: 0.3235 - F1: 0.3085
sub_15:Test (Best Model) - Loss: 0.8007 - Accuracy: 0.6176 - F1: 0.5808
sub_13:Test (Best Model) - Loss: 1.4687 - Accuracy: 0.4706 - F1: 0.4518
sub_15:Test (Best Model) - Loss: 0.6059 - Accuracy: 0.7647 - F1: 0.7562
sub_14:Test (Best Model) - Loss: 1.7731 - Accuracy: 0.3824 - F1: 0.3815
sub_13:Test (Best Model) - Loss: 1.0933 - Accuracy: 0.4412 - F1: 0.3379
sub_15:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.5441 - F1: 0.4823
sub_13:Test (Best Model) - Loss: 1.3262 - Accuracy: 0.5000 - F1: 0.4986
sub_14:Test (Best Model) - Loss: 1.2296 - Accuracy: 0.5588 - F1: 0.5421
sub_13:Test (Best Model) - Loss: 1.0783 - Accuracy: 0.4706 - F1: 0.4760
sub_15:Test (Best Model) - Loss: 1.0066 - Accuracy: 0.6176 - F1: 0.5665
sub_15:Test (Best Model) - Loss: 1.0272 - Accuracy: 0.4853 - F1: 0.4115
sub_14:Test (Best Model) - Loss: 1.4335 - Accuracy: 0.5000 - F1: 0.4865
sub_14:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2794 - F1: 0.1950
sub_15:Test (Best Model) - Loss: 1.2019 - Accuracy: 0.5147 - F1: 0.4814
sub_14:Test (Best Model) - Loss: 1.4224 - Accuracy: 0.2941 - F1: 0.1997
sub_15:Test (Best Model) - Loss: 1.3007 - Accuracy: 0.5735 - F1: 0.5232
sub_14:Test (Best Model) - Loss: 1.5896 - Accuracy: 0.3088 - F1: 0.2348
sub_17:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.5362 - F1: 0.4584
sub_16:Test (Best Model) - Loss: 1.2577 - Accuracy: 0.3382 - F1: 0.2411
sub_16:Test (Best Model) - Loss: 1.2048 - Accuracy: 0.3824 - F1: 0.3674
sub_17:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.4928 - F1: 0.4813
sub_18:Test (Best Model) - Loss: 1.0213 - Accuracy: 0.5217 - F1: 0.5182
sub_17:Test (Best Model) - Loss: 1.0990 - Accuracy: 0.4348 - F1: 0.3743
sub_16:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.3382 - F1: 0.2390
sub_17:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.4058 - F1: 0.3453
sub_18:Test (Best Model) - Loss: 0.9599 - Accuracy: 0.5942 - F1: 0.5809
sub_17:Test (Best Model) - Loss: 1.0645 - Accuracy: 0.5072 - F1: 0.4293
sub_16:Test (Best Model) - Loss: 0.9164 - Accuracy: 0.6176 - F1: 0.6094
sub_18:Test (Best Model) - Loss: 1.0497 - Accuracy: 0.5507 - F1: 0.5296
sub_16:Test (Best Model) - Loss: 1.2584 - Accuracy: 0.3088 - F1: 0.2579
sub_17:Test (Best Model) - Loss: 0.9617 - Accuracy: 0.6087 - F1: 0.5874
sub_18:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.2174 - F1: 0.0893
sub_17:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.3768 - F1: 0.3182
sub_16:Test (Best Model) - Loss: 1.0664 - Accuracy: 0.5882 - F1: 0.5240
sub_18:Test (Best Model) - Loss: 1.0292 - Accuracy: 0.5797 - F1: 0.5642
sub_17:Test (Best Model) - Loss: 1.0708 - Accuracy: 0.5362 - F1: 0.4508
sub_18:Test (Best Model) - Loss: 1.6272 - Accuracy: 0.2206 - F1: 0.1138
sub_16:Test (Best Model) - Loss: 1.4650 - Accuracy: 0.4706 - F1: 0.3989
sub_18:Test (Best Model) - Loss: 1.5255 - Accuracy: 0.4265 - F1: 0.4052
sub_16:Test (Best Model) - Loss: 1.3061 - Accuracy: 0.3676 - F1: 0.2493
sub_17:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.5362 - F1: 0.5334
sub_18:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.4412 - F1: 0.4063
sub_16:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3971 - F1: 0.2985
sub_17:Test (Best Model) - Loss: 1.1270 - Accuracy: 0.5942 - F1: 0.6007
sub_18:Test (Best Model) - Loss: 1.4827 - Accuracy: 0.3824 - F1: 0.3428
sub_16:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.3971 - F1: 0.3177
sub_17:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.5882 - F1: 0.5145
sub_18:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3824 - F1: 0.3449
sub_16:Test (Best Model) - Loss: 2.3768 - Accuracy: 0.3088 - F1: 0.2762
sub_17:Test (Best Model) - Loss: 1.1596 - Accuracy: 0.5294 - F1: 0.5062
sub_17:Test (Best Model) - Loss: 1.1519 - Accuracy: 0.6029 - F1: 0.5582
sub_18:Test (Best Model) - Loss: 1.9940 - Accuracy: 0.5294 - F1: 0.4918
sub_16:Test (Best Model) - Loss: 1.7134 - Accuracy: 0.3824 - F1: 0.3512
sub_18:Test (Best Model) - Loss: 1.8124 - Accuracy: 0.4118 - F1: 0.3658
sub_16:Test (Best Model) - Loss: 1.7456 - Accuracy: 0.4412 - F1: 0.4163
sub_17:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.6324 - F1: 0.5506
sub_18:Test (Best Model) - Loss: 1.7055 - Accuracy: 0.4265 - F1: 0.3859
sub_16:Test (Best Model) - Loss: 1.6510 - Accuracy: 0.2941 - F1: 0.2199
sub_17:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.5294 - F1: 0.4405
sub_18:Test (Best Model) - Loss: 2.0875 - Accuracy: 0.4118 - F1: 0.3551
sub_16:Test (Best Model) - Loss: 1.5152 - Accuracy: 0.3676 - F1: 0.3577
sub_18:Test (Best Model) - Loss: 2.3130 - Accuracy: 0.4853 - F1: 0.4796
sub_19:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.4265 - F1: 0.3968
sub_20:Test (Best Model) - Loss: 1.0244 - Accuracy: 0.4559 - F1: 0.3661
sub_19:Test (Best Model) - Loss: 2.8789 - Accuracy: 0.4706 - F1: 0.4613
sub_21:Test (Best Model) - Loss: 1.6391 - Accuracy: 0.3824 - F1: 0.3534
sub_20:Test (Best Model) - Loss: 1.1883 - Accuracy: 0.6176 - F1: 0.5946
sub_19:Test (Best Model) - Loss: 2.8976 - Accuracy: 0.4412 - F1: 0.4275
sub_20:Test (Best Model) - Loss: 1.2072 - Accuracy: 0.6176 - F1: 0.6042
sub_21:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.5441 - F1: 0.5018
sub_20:Test (Best Model) - Loss: 0.9956 - Accuracy: 0.5588 - F1: 0.4729
sub_19:Test (Best Model) - Loss: 3.4841 - Accuracy: 0.4706 - F1: 0.4622
sub_20:Test (Best Model) - Loss: 1.2539 - Accuracy: 0.6029 - F1: 0.5881
sub_21:Test (Best Model) - Loss: 1.3216 - Accuracy: 0.4706 - F1: 0.4217
sub_19:Test (Best Model) - Loss: 2.4227 - Accuracy: 0.3382 - F1: 0.3177
sub_20:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.7500 - F1: 0.7246
sub_21:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.4412 - F1: 0.4046
sub_19:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.5147 - F1: 0.4871
sub_20:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.7353 - F1: 0.7203
sub_19:Test (Best Model) - Loss: 1.1892 - Accuracy: 0.4265 - F1: 0.3636
sub_21:Test (Best Model) - Loss: 2.2277 - Accuracy: 0.5882 - F1: 0.5533
sub_21:Test (Best Model) - Loss: 0.9091 - Accuracy: 0.5735 - F1: 0.5179
sub_20:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.7794 - F1: 0.7766
sub_19:Test (Best Model) - Loss: 0.9679 - Accuracy: 0.6324 - F1: 0.5956
sub_19:Test (Best Model) - Loss: 1.0677 - Accuracy: 0.4559 - F1: 0.4188
sub_20:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.7353 - F1: 0.7239
sub_21:Test (Best Model) - Loss: 0.8498 - Accuracy: 0.6324 - F1: 0.6136
sub_21:Test (Best Model) - Loss: 0.8266 - Accuracy: 0.6176 - F1: 0.6145
sub_19:Test (Best Model) - Loss: 0.8390 - Accuracy: 0.6765 - F1: 0.6448
sub_20:Test (Best Model) - Loss: 1.5340 - Accuracy: 0.7500 - F1: 0.7397
sub_19:Test (Best Model) - Loss: 1.5766 - Accuracy: 0.5294 - F1: 0.5003
sub_21:Test (Best Model) - Loss: 0.9299 - Accuracy: 0.6618 - F1: 0.6560
sub_19:Test (Best Model) - Loss: 1.3055 - Accuracy: 0.5000 - F1: 0.4530
sub_21:Test (Best Model) - Loss: 0.9245 - Accuracy: 0.6176 - F1: 0.5496
sub_20:Test (Best Model) - Loss: 0.9295 - Accuracy: 0.5942 - F1: 0.5378
sub_19:Test (Best Model) - Loss: 1.1107 - Accuracy: 0.5735 - F1: 0.5428
sub_20:Test (Best Model) - Loss: 0.8705 - Accuracy: 0.6812 - F1: 0.6637
sub_21:Test (Best Model) - Loss: 1.4044 - Accuracy: 0.4412 - F1: 0.3546
sub_19:Test (Best Model) - Loss: 1.1644 - Accuracy: 0.5147 - F1: 0.4617
sub_20:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7391 - F1: 0.7271
sub_21:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.5882 - F1: 0.5435
sub_19:Test (Best Model) - Loss: 1.1146 - Accuracy: 0.5882 - F1: 0.5863
sub_20:Test (Best Model) - Loss: 0.9746 - Accuracy: 0.4638 - F1: 0.3775
sub_21:Test (Best Model) - Loss: 1.5092 - Accuracy: 0.5147 - F1: 0.4567
sub_21:Test (Best Model) - Loss: 1.7564 - Accuracy: 0.4265 - F1: 0.4168
sub_20:Test (Best Model) - Loss: 1.3150 - Accuracy: 0.7536 - F1: 0.7498
sub_21:Test (Best Model) - Loss: 1.7601 - Accuracy: 0.4412 - F1: 0.3821
sub_24:Test (Best Model) - Loss: 1.0589 - Accuracy: 0.4706 - F1: 0.3615
sub_23:Test (Best Model) - Loss: 1.4515 - Accuracy: 0.5217 - F1: 0.4504
sub_22:Test (Best Model) - Loss: 2.0149 - Accuracy: 0.5294 - F1: 0.4945
sub_24:Test (Best Model) - Loss: 1.0759 - Accuracy: 0.4265 - F1: 0.4305
sub_23:Test (Best Model) - Loss: 1.0683 - Accuracy: 0.6087 - F1: 0.5611
sub_22:Test (Best Model) - Loss: 2.3982 - Accuracy: 0.5000 - F1: 0.4577
sub_24:Test (Best Model) - Loss: 1.1080 - Accuracy: 0.4559 - F1: 0.4435
sub_23:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.5072 - F1: 0.4897
sub_24:Test (Best Model) - Loss: 1.0605 - Accuracy: 0.4412 - F1: 0.3483
sub_22:Test (Best Model) - Loss: 1.4504 - Accuracy: 0.3824 - F1: 0.3016
sub_23:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.3188 - F1: 0.2718
sub_24:Test (Best Model) - Loss: 1.1473 - Accuracy: 0.4559 - F1: 0.3704
sub_23:Test (Best Model) - Loss: 1.2963 - Accuracy: 0.3913 - F1: 0.3731
sub_24:Test (Best Model) - Loss: 1.1407 - Accuracy: 0.5000 - F1: 0.4404
sub_22:Test (Best Model) - Loss: 2.2895 - Accuracy: 0.5882 - F1: 0.5459
sub_22:Test (Best Model) - Loss: 1.4915 - Accuracy: 0.6765 - F1: 0.6134
sub_24:Test (Best Model) - Loss: 1.1699 - Accuracy: 0.5147 - F1: 0.4611
sub_23:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.5882 - F1: 0.5566
sub_22:Test (Best Model) - Loss: 1.4584 - Accuracy: 0.4928 - F1: 0.4551
sub_24:Test (Best Model) - Loss: 1.1554 - Accuracy: 0.4853 - F1: 0.4437
sub_23:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.6029 - F1: 0.5822
sub_22:Test (Best Model) - Loss: 1.1919 - Accuracy: 0.5217 - F1: 0.5099
sub_24:Test (Best Model) - Loss: 1.1118 - Accuracy: 0.5147 - F1: 0.4941
sub_23:Test (Best Model) - Loss: 1.0448 - Accuracy: 0.6765 - F1: 0.6685
sub_22:Test (Best Model) - Loss: 1.2611 - Accuracy: 0.4638 - F1: 0.4317
sub_24:Test (Best Model) - Loss: 1.2288 - Accuracy: 0.4853 - F1: 0.4639
sub_23:Test (Best Model) - Loss: 1.4494 - Accuracy: 0.5735 - F1: 0.5199
sub_22:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.4783 - F1: 0.4245
sub_24:Test (Best Model) - Loss: 1.1773 - Accuracy: 0.4118 - F1: 0.3671
sub_23:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.6471 - F1: 0.6248
sub_22:Test (Best Model) - Loss: 1.5530 - Accuracy: 0.4493 - F1: 0.4223
sub_23:Test (Best Model) - Loss: 1.7165 - Accuracy: 0.6087 - F1: 0.5915
sub_24:Test (Best Model) - Loss: 1.0759 - Accuracy: 0.4559 - F1: 0.4264
sub_22:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.3971 - F1: 0.3766
sub_24:Test (Best Model) - Loss: 1.1320 - Accuracy: 0.4706 - F1: 0.4338
sub_22:Test (Best Model) - Loss: 1.2817 - Accuracy: 0.4265 - F1: 0.3913
sub_23:Test (Best Model) - Loss: 1.6510 - Accuracy: 0.6232 - F1: 0.6155
sub_24:Test (Best Model) - Loss: 1.1616 - Accuracy: 0.4559 - F1: 0.4349
sub_23:Test (Best Model) - Loss: 1.0907 - Accuracy: 0.6522 - F1: 0.5738
sub_24:Test (Best Model) - Loss: 1.1057 - Accuracy: 0.4265 - F1: 0.3536
sub_22:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.3824 - F1: 0.3023
sub_22:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.3529 - F1: 0.2674
sub_22:Test (Best Model) - Loss: 1.0572 - Accuracy: 0.4412 - F1: 0.3938
sub_23:Test (Best Model) - Loss: 1.1103 - Accuracy: 0.6522 - F1: 0.6468
sub_23:Test (Best Model) - Loss: 2.1982 - Accuracy: 0.6667 - F1: 0.6536
sub_27:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.5362 - F1: 0.4584
sub_25:Test (Best Model) - Loss: 0.9987 - Accuracy: 0.5652 - F1: 0.4822
sub_26:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.4203 - F1: 0.3325
sub_25:Test (Best Model) - Loss: 0.9694 - Accuracy: 0.6667 - F1: 0.6571
sub_27:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.4928 - F1: 0.4813
sub_27:Test (Best Model) - Loss: 1.0990 - Accuracy: 0.4348 - F1: 0.3743
sub_26:Test (Best Model) - Loss: 1.0076 - Accuracy: 0.5797 - F1: 0.5844
sub_25:Test (Best Model) - Loss: 1.0120 - Accuracy: 0.6957 - F1: 0.6886
sub_27:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.4058 - F1: 0.3453
sub_25:Test (Best Model) - Loss: 0.9399 - Accuracy: 0.5942 - F1: 0.5123
sub_27:Test (Best Model) - Loss: 1.0645 - Accuracy: 0.5072 - F1: 0.4293
sub_25:Test (Best Model) - Loss: 0.9823 - Accuracy: 0.5652 - F1: 0.4877
sub_26:Test (Best Model) - Loss: 0.8880 - Accuracy: 0.5942 - F1: 0.6035
sub_26:Test (Best Model) - Loss: 0.8691 - Accuracy: 0.6377 - F1: 0.6470
sub_27:Test (Best Model) - Loss: 0.9617 - Accuracy: 0.6087 - F1: 0.5874
sub_25:Test (Best Model) - Loss: 0.8497 - Accuracy: 0.5588 - F1: 0.5340
sub_27:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.3768 - F1: 0.3182
sub_25:Test (Best Model) - Loss: 0.7732 - Accuracy: 0.6471 - F1: 0.5805
sub_25:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.6912 - F1: 0.6279
sub_27:Test (Best Model) - Loss: 1.0708 - Accuracy: 0.5362 - F1: 0.4508
sub_25:Test (Best Model) - Loss: 0.7642 - Accuracy: 0.6765 - F1: 0.5850
sub_26:Test (Best Model) - Loss: 0.9373 - Accuracy: 0.5942 - F1: 0.6094
sub_25:Test (Best Model) - Loss: 0.8847 - Accuracy: 0.6176 - F1: 0.6039
sub_27:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.5362 - F1: 0.5334
sub_26:Test (Best Model) - Loss: 0.7348 - Accuracy: 0.6912 - F1: 0.6853
sub_27:Test (Best Model) - Loss: 1.1270 - Accuracy: 0.5942 - F1: 0.6007
sub_25:Test (Best Model) - Loss: 0.4768 - Accuracy: 0.7353 - F1: 0.7401
sub_26:Test (Best Model) - Loss: 0.7282 - Accuracy: 0.6471 - F1: 0.6153
sub_27:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.5882 - F1: 0.5145
sub_26:Test (Best Model) - Loss: 0.8983 - Accuracy: 0.6618 - F1: 0.6445
sub_25:Test (Best Model) - Loss: 0.4727 - Accuracy: 0.7206 - F1: 0.7168
sub_27:Test (Best Model) - Loss: 1.1596 - Accuracy: 0.5294 - F1: 0.5062
sub_25:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.7353 - F1: 0.7392
sub_26:Test (Best Model) - Loss: 0.8543 - Accuracy: 0.6471 - F1: 0.6355
sub_27:Test (Best Model) - Loss: 1.1519 - Accuracy: 0.6029 - F1: 0.5582
sub_25:Test (Best Model) - Loss: 0.7548 - Accuracy: 0.6912 - F1: 0.6691
sub_26:Test (Best Model) - Loss: 0.9062 - Accuracy: 0.6176 - F1: 0.6037
sub_27:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.6324 - F1: 0.5506
sub_25:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.7500 - F1: 0.7401
sub_27:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.5294 - F1: 0.4405
sub_26:Test (Best Model) - Loss: 1.5054 - Accuracy: 0.4706 - F1: 0.4885
sub_26:Test (Best Model) - Loss: 1.2467 - Accuracy: 0.4853 - F1: 0.5165
sub_26:Test (Best Model) - Loss: 1.2801 - Accuracy: 0.5294 - F1: 0.5444
sub_26:Test (Best Model) - Loss: 1.1347 - Accuracy: 0.5441 - F1: 0.5575
sub_26:Test (Best Model) - Loss: 2.1537 - Accuracy: 0.5000 - F1: 0.5072
sub_28:Test (Best Model) - Loss: 1.4120 - Accuracy: 0.2500 - F1: 0.1729
sub_29:Test (Best Model) - Loss: 1.1655 - Accuracy: 0.5735 - F1: 0.5658
sub_29:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.5441 - F1: 0.5342
sub_28:Test (Best Model) - Loss: 1.6710 - Accuracy: 0.3088 - F1: 0.2975
sub_29:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.6324 - F1: 0.6065
sub_28:Test (Best Model) - Loss: 1.7484 - Accuracy: 0.3529 - F1: 0.3349
sub_29:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.5588 - F1: 0.5222
sub_28:Test (Best Model) - Loss: 1.6798 - Accuracy: 0.3235 - F1: 0.3164
sub_29:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.6029 - F1: 0.5919
sub_28:Test (Best Model) - Loss: 2.5336 - Accuracy: 0.4118 - F1: 0.3821
sub_28:Test (Best Model) - Loss: 1.4675 - Accuracy: 0.2647 - F1: 0.2323
sub_29:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.6324 - F1: 0.5756
sub_28:Test (Best Model) - Loss: 1.6635 - Accuracy: 0.3382 - F1: 0.3006
sub_29:Test (Best Model) - Loss: 0.8642 - Accuracy: 0.5882 - F1: 0.5513
sub_28:Test (Best Model) - Loss: 2.4410 - Accuracy: 0.3824 - F1: 0.3060
sub_29:Test (Best Model) - Loss: 0.9349 - Accuracy: 0.6029 - F1: 0.5757
sub_28:Test (Best Model) - Loss: 2.9427 - Accuracy: 0.4265 - F1: 0.3761
sub_29:Test (Best Model) - Loss: 0.9266 - Accuracy: 0.5735 - F1: 0.5589
sub_29:Test (Best Model) - Loss: 1.0222 - Accuracy: 0.6029 - F1: 0.5448
sub_28:Test (Best Model) - Loss: 3.3880 - Accuracy: 0.4265 - F1: 0.3928
sub_29:Test (Best Model) - Loss: 1.1616 - Accuracy: 0.4058 - F1: 0.3932
sub_28:Test (Best Model) - Loss: 2.2914 - Accuracy: 0.3971 - F1: 0.3194
sub_29:Test (Best Model) - Loss: 1.2107 - Accuracy: 0.4203 - F1: 0.4338
sub_28:Test (Best Model) - Loss: 2.5664 - Accuracy: 0.4706 - F1: 0.3927
sub_28:Test (Best Model) - Loss: 1.6720 - Accuracy: 0.3971 - F1: 0.3125
sub_29:Test (Best Model) - Loss: 1.2129 - Accuracy: 0.4348 - F1: 0.3889
sub_29:Test (Best Model) - Loss: 1.0774 - Accuracy: 0.5217 - F1: 0.5238
sub_28:Test (Best Model) - Loss: 2.9230 - Accuracy: 0.4118 - F1: 0.3256
sub_29:Test (Best Model) - Loss: 0.9815 - Accuracy: 0.5072 - F1: 0.5288
sub_28:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.4412 - F1: 0.3722

=== Summary Results ===

acc: 51.67 ± 9.20
F1: 48.06 ± 10.00
acc-in: 68.23 ± 6.60
F1-in: 65.17 ± 7.71
runing time: 2325.20 seconds
