lr: 0.001
sub_22:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.6176 - F1: 0.5992
sub_18:Test (Best Model) - Loss: 0.8860 - Accuracy: 0.6812 - F1: 0.6631
sub_10:Test (Best Model) - Loss: 1.1971 - Accuracy: 0.5294 - F1: 0.5647
sub_8:Test (Best Model) - Loss: 1.0668 - Accuracy: 0.7059 - F1: 0.6427
sub_24:Test (Best Model) - Loss: 0.9168 - Accuracy: 0.6618 - F1: 0.6683
sub_6:Test (Best Model) - Loss: 1.0692 - Accuracy: 0.4853 - F1: 0.4486
sub_29:Test (Best Model) - Loss: 1.0181 - Accuracy: 0.5441 - F1: 0.5808
sub_26:Test (Best Model) - Loss: 0.8674 - Accuracy: 0.7246 - F1: 0.7303
sub_2:Test (Best Model) - Loss: 0.8603 - Accuracy: 0.7391 - F1: 0.7343
sub_17:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.7101 - F1: 0.7051
sub_28:Test (Best Model) - Loss: 1.1490 - Accuracy: 0.6471 - F1: 0.5728
sub_4:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.6522 - F1: 0.6524
sub_11:Test (Best Model) - Loss: 0.8840 - Accuracy: 0.6667 - F1: 0.6602
sub_12:Test (Best Model) - Loss: 0.8559 - Accuracy: 0.6765 - F1: 0.6957
sub_5:Test (Best Model) - Loss: 1.0020 - Accuracy: 0.6618 - F1: 0.6062
sub_23:Test (Best Model) - Loss: 0.8881 - Accuracy: 0.6667 - F1: 0.6198
sub_14:Test (Best Model) - Loss: 1.2227 - Accuracy: 0.4412 - F1: 0.3922
sub_19:Test (Best Model) - Loss: 1.2516 - Accuracy: 0.3971 - F1: 0.3870
sub_16:Test (Best Model) - Loss: 0.8229 - Accuracy: 0.6176 - F1: 0.6363
sub_7:Test (Best Model) - Loss: 0.5505 - Accuracy: 0.9706 - F1: 0.9676
sub_3:Test (Best Model) - Loss: 1.1283 - Accuracy: 0.5735 - F1: 0.5274
sub_20:Test (Best Model) - Loss: 0.9579 - Accuracy: 0.6176 - F1: 0.5912
sub_1:Test (Best Model) - Loss: 1.0616 - Accuracy: 0.6029 - F1: 0.6034
sub_21:Test (Best Model) - Loss: 0.7734 - Accuracy: 0.7941 - F1: 0.7983
sub_9:Test (Best Model) - Loss: 1.0379 - Accuracy: 0.4559 - F1: 0.5093
sub_25:Test (Best Model) - Loss: 0.3950 - Accuracy: 0.9275 - F1: 0.9217
sub_15:Test (Best Model) - Loss: 0.8722 - Accuracy: 0.6471 - F1: 0.6579
sub_22:Test (Best Model) - Loss: 1.0936 - Accuracy: 0.6029 - F1: 0.5417
sub_13:Test (Best Model) - Loss: 1.1717 - Accuracy: 0.5441 - F1: 0.5146
sub_27:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.7101 - F1: 0.7051
sub_8:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.5588 - F1: 0.5278
sub_18:Test (Best Model) - Loss: 0.9552 - Accuracy: 0.6087 - F1: 0.6021
sub_24:Test (Best Model) - Loss: 1.0629 - Accuracy: 0.5441 - F1: 0.5504
sub_6:Test (Best Model) - Loss: 0.9655 - Accuracy: 0.5882 - F1: 0.5279
sub_29:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.4853 - F1: 0.5333
sub_10:Test (Best Model) - Loss: 1.3291 - Accuracy: 0.4265 - F1: 0.4790
sub_28:Test (Best Model) - Loss: 1.4267 - Accuracy: 0.5000 - F1: 0.4563
sub_11:Test (Best Model) - Loss: 0.8764 - Accuracy: 0.7246 - F1: 0.7210
sub_7:Test (Best Model) - Loss: 0.5107 - Accuracy: 0.9118 - F1: 0.9094
sub_3:Test (Best Model) - Loss: 0.8102 - Accuracy: 0.7500 - F1: 0.7512
sub_4:Test (Best Model) - Loss: 0.8762 - Accuracy: 0.6667 - F1: 0.6424
sub_17:Test (Best Model) - Loss: 0.8091 - Accuracy: 0.7101 - F1: 0.7015
sub_26:Test (Best Model) - Loss: 0.8552 - Accuracy: 0.6232 - F1: 0.6400
sub_12:Test (Best Model) - Loss: 1.0837 - Accuracy: 0.5882 - F1: 0.5741
sub_23:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.8116 - F1: 0.8201
sub_2:Test (Best Model) - Loss: 0.8364 - Accuracy: 0.7101 - F1: 0.7056
sub_9:Test (Best Model) - Loss: 1.0794 - Accuracy: 0.4118 - F1: 0.4597
sub_5:Test (Best Model) - Loss: 0.9211 - Accuracy: 0.7353 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 1.1064 - Accuracy: 0.5294 - F1: 0.5084
sub_14:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.3971 - F1: 0.3224
sub_13:Test (Best Model) - Loss: 1.0779 - Accuracy: 0.5882 - F1: 0.5401
sub_16:Test (Best Model) - Loss: 0.8773 - Accuracy: 0.5882 - F1: 0.5908
sub_20:Test (Best Model) - Loss: 0.9041 - Accuracy: 0.6471 - F1: 0.6199
sub_22:Test (Best Model) - Loss: 1.0452 - Accuracy: 0.6324 - F1: 0.5714
sub_15:Test (Best Model) - Loss: 0.8136 - Accuracy: 0.6912 - F1: 0.7026
sub_25:Test (Best Model) - Loss: 0.4658 - Accuracy: 0.9420 - F1: 0.9430
sub_19:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.3971 - F1: 0.4088
sub_21:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.8529 - F1: 0.8517
sub_8:Test (Best Model) - Loss: 1.1869 - Accuracy: 0.5441 - F1: 0.5191
sub_29:Test (Best Model) - Loss: 1.0441 - Accuracy: 0.4706 - F1: 0.5168
sub_28:Test (Best Model) - Loss: 1.2356 - Accuracy: 0.5588 - F1: 0.5079
sub_27:Test (Best Model) - Loss: 0.8091 - Accuracy: 0.7101 - F1: 0.7015
sub_10:Test (Best Model) - Loss: 1.2526 - Accuracy: 0.4412 - F1: 0.4778
sub_18:Test (Best Model) - Loss: 0.9087 - Accuracy: 0.6377 - F1: 0.6611
sub_1:Test (Best Model) - Loss: 1.0285 - Accuracy: 0.5441 - F1: 0.5387
sub_12:Test (Best Model) - Loss: 0.9489 - Accuracy: 0.6765 - F1: 0.6809
sub_5:Test (Best Model) - Loss: 1.0139 - Accuracy: 0.7059 - F1: 0.6386
sub_7:Test (Best Model) - Loss: 0.5495 - Accuracy: 0.9412 - F1: 0.9365
sub_11:Test (Best Model) - Loss: 0.9418 - Accuracy: 0.6957 - F1: 0.6817
sub_26:Test (Best Model) - Loss: 0.7920 - Accuracy: 0.6957 - F1: 0.6991
sub_13:Test (Best Model) - Loss: 1.0433 - Accuracy: 0.5588 - F1: 0.5347
sub_17:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.7391 - F1: 0.7413
sub_24:Test (Best Model) - Loss: 1.0443 - Accuracy: 0.6324 - F1: 0.6513
sub_16:Test (Best Model) - Loss: 1.0595 - Accuracy: 0.5588 - F1: 0.5791
sub_14:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.4118 - F1: 0.3559
sub_3:Test (Best Model) - Loss: 0.7844 - Accuracy: 0.7059 - F1: 0.6731
sub_9:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.3971 - F1: 0.4249
sub_6:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.4706 - F1: 0.4259
sub_15:Test (Best Model) - Loss: 0.8834 - Accuracy: 0.5882 - F1: 0.5694
sub_25:Test (Best Model) - Loss: 0.4516 - Accuracy: 0.9275 - F1: 0.9253
sub_21:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8235 - F1: 0.8200
sub_20:Test (Best Model) - Loss: 0.9343 - Accuracy: 0.6471 - F1: 0.6199
sub_5:Test (Best Model) - Loss: 1.1406 - Accuracy: 0.6618 - F1: 0.6120
sub_8:Test (Best Model) - Loss: 1.0305 - Accuracy: 0.6176 - F1: 0.5934
sub_23:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.6667 - F1: 0.6384
sub_19:Test (Best Model) - Loss: 1.4609 - Accuracy: 0.3824 - F1: 0.3930
sub_4:Test (Best Model) - Loss: 1.0232 - Accuracy: 0.6087 - F1: 0.5907
sub_22:Test (Best Model) - Loss: 1.0112 - Accuracy: 0.6324 - F1: 0.5988
sub_10:Test (Best Model) - Loss: 1.2538 - Accuracy: 0.4118 - F1: 0.4644
sub_18:Test (Best Model) - Loss: 1.0130 - Accuracy: 0.5797 - F1: 0.5823
sub_2:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.4783 - F1: 0.4074
sub_27:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.7391 - F1: 0.7413
sub_7:Test (Best Model) - Loss: 0.5417 - Accuracy: 0.8971 - F1: 0.8965
sub_29:Test (Best Model) - Loss: 1.1283 - Accuracy: 0.5588 - F1: 0.5978
sub_16:Test (Best Model) - Loss: 0.9455 - Accuracy: 0.5588 - F1: 0.5815
sub_11:Test (Best Model) - Loss: 0.9157 - Accuracy: 0.7246 - F1: 0.7268
sub_14:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.4118 - F1: 0.3490
sub_1:Test (Best Model) - Loss: 1.1793 - Accuracy: 0.5294 - F1: 0.5191
sub_24:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.5735 - F1: 0.5680
sub_17:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.7536 - F1: 0.7586
sub_13:Test (Best Model) - Loss: 1.1501 - Accuracy: 0.5735 - F1: 0.5267
sub_28:Test (Best Model) - Loss: 1.4651 - Accuracy: 0.5441 - F1: 0.5018
sub_3:Test (Best Model) - Loss: 0.8296 - Accuracy: 0.7059 - F1: 0.7023
sub_25:Test (Best Model) - Loss: 0.5470 - Accuracy: 0.9275 - F1: 0.9280
sub_26:Test (Best Model) - Loss: 1.0087 - Accuracy: 0.6232 - F1: 0.6157
sub_21:Test (Best Model) - Loss: 0.6086 - Accuracy: 0.8382 - F1: 0.8351
sub_5:Test (Best Model) - Loss: 1.0194 - Accuracy: 0.6176 - F1: 0.5682
sub_9:Test (Best Model) - Loss: 1.0414 - Accuracy: 0.4706 - F1: 0.5209
sub_19:Test (Best Model) - Loss: 1.3189 - Accuracy: 0.4118 - F1: 0.4159
sub_18:Test (Best Model) - Loss: 0.9442 - Accuracy: 0.6232 - F1: 0.6309
sub_22:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.4853 - F1: 0.4355
sub_12:Test (Best Model) - Loss: 0.9607 - Accuracy: 0.6324 - F1: 0.6002
sub_20:Test (Best Model) - Loss: 0.8688 - Accuracy: 0.6765 - F1: 0.6484
sub_15:Test (Best Model) - Loss: 0.9369 - Accuracy: 0.5441 - F1: 0.5282
sub_10:Test (Best Model) - Loss: 1.1920 - Accuracy: 0.4412 - F1: 0.5009
sub_8:Test (Best Model) - Loss: 1.1287 - Accuracy: 0.5882 - F1: 0.5595
sub_23:Test (Best Model) - Loss: 0.9732 - Accuracy: 0.6812 - F1: 0.6531
sub_2:Test (Best Model) - Loss: 0.8857 - Accuracy: 0.7101 - F1: 0.6902
sub_27:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.7536 - F1: 0.7586
sub_29:Test (Best Model) - Loss: 1.2926 - Accuracy: 0.4706 - F1: 0.5031
sub_16:Test (Best Model) - Loss: 0.8750 - Accuracy: 0.6176 - F1: 0.6159
sub_4:Test (Best Model) - Loss: 0.9348 - Accuracy: 0.6232 - F1: 0.6355
sub_6:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.4559 - F1: 0.4202
sub_14:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3971 - F1: 0.3173
sub_13:Test (Best Model) - Loss: 1.1043 - Accuracy: 0.5000 - F1: 0.4552
sub_28:Test (Best Model) - Loss: 1.4490 - Accuracy: 0.5000 - F1: 0.4327
sub_11:Test (Best Model) - Loss: 0.8083 - Accuracy: 0.7391 - F1: 0.7370
sub_1:Test (Best Model) - Loss: 1.1263 - Accuracy: 0.5000 - F1: 0.4823
sub_3:Test (Best Model) - Loss: 0.9315 - Accuracy: 0.6324 - F1: 0.5962
sub_21:Test (Best Model) - Loss: 0.7693 - Accuracy: 0.7794 - F1: 0.7822
sub_25:Test (Best Model) - Loss: 0.4744 - Accuracy: 0.9565 - F1: 0.9547
sub_7:Test (Best Model) - Loss: 0.3768 - Accuracy: 0.9118 - F1: 0.9038
sub_18:Test (Best Model) - Loss: 1.1011 - Accuracy: 0.3971 - F1: 0.4211
sub_22:Test (Best Model) - Loss: 1.1154 - Accuracy: 0.5507 - F1: 0.4960
sub_24:Test (Best Model) - Loss: 1.0324 - Accuracy: 0.5588 - F1: 0.5526
sub_15:Test (Best Model) - Loss: 0.8923 - Accuracy: 0.6618 - F1: 0.6669
sub_17:Test (Best Model) - Loss: 0.7396 - Accuracy: 0.7391 - F1: 0.7398
sub_26:Test (Best Model) - Loss: 0.7726 - Accuracy: 0.7246 - F1: 0.7395
sub_10:Test (Best Model) - Loss: 1.2384 - Accuracy: 0.4559 - F1: 0.3657
sub_12:Test (Best Model) - Loss: 0.9825 - Accuracy: 0.6029 - F1: 0.5846
sub_19:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3676 - F1: 0.3624
sub_8:Test (Best Model) - Loss: 0.8371 - Accuracy: 0.6912 - F1: 0.6329
sub_5:Test (Best Model) - Loss: 0.7664 - Accuracy: 0.7647 - F1: 0.7119
sub_9:Test (Best Model) - Loss: 1.2382 - Accuracy: 0.3529 - F1: 0.4055
sub_14:Test (Best Model) - Loss: 1.2062 - Accuracy: 0.4118 - F1: 0.4035
sub_4:Test (Best Model) - Loss: 0.8797 - Accuracy: 0.6232 - F1: 0.6202
sub_27:Test (Best Model) - Loss: 0.7396 - Accuracy: 0.7391 - F1: 0.7398
sub_23:Test (Best Model) - Loss: 0.9396 - Accuracy: 0.6812 - F1: 0.6317
sub_1:Test (Best Model) - Loss: 0.9013 - Accuracy: 0.5797 - F1: 0.6068
sub_21:Test (Best Model) - Loss: 0.5459 - Accuracy: 0.8824 - F1: 0.8831
sub_18:Test (Best Model) - Loss: 1.1650 - Accuracy: 0.3824 - F1: 0.4371
sub_7:Test (Best Model) - Loss: 0.9281 - Accuracy: 0.6912 - F1: 0.6464
sub_2:Test (Best Model) - Loss: 1.0558 - Accuracy: 0.6087 - F1: 0.5708
sub_6:Test (Best Model) - Loss: 1.0984 - Accuracy: 0.5588 - F1: 0.5374
sub_25:Test (Best Model) - Loss: 0.8097 - Accuracy: 0.6912 - F1: 0.6642
sub_22:Test (Best Model) - Loss: 1.0364 - Accuracy: 0.5507 - F1: 0.4956
sub_11:Test (Best Model) - Loss: 0.8331 - Accuracy: 0.6957 - F1: 0.6851
sub_20:Test (Best Model) - Loss: 0.9836 - Accuracy: 0.5882 - F1: 0.5552
sub_16:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.7500 - F1: 0.7595
sub_13:Test (Best Model) - Loss: 1.1281 - Accuracy: 0.5652 - F1: 0.5133
sub_29:Test (Best Model) - Loss: 0.5074 - Accuracy: 0.8382 - F1: 0.8478
sub_24:Test (Best Model) - Loss: 0.8998 - Accuracy: 0.6765 - F1: 0.5994
sub_3:Test (Best Model) - Loss: 1.0130 - Accuracy: 0.6957 - F1: 0.6498
sub_26:Test (Best Model) - Loss: 0.9264 - Accuracy: 0.5882 - F1: 0.5795
sub_17:Test (Best Model) - Loss: 1.1888 - Accuracy: 0.5362 - F1: 0.4979
sub_8:Test (Best Model) - Loss: 0.9313 - Accuracy: 0.6765 - F1: 0.6220
sub_10:Test (Best Model) - Loss: 1.1753 - Accuracy: 0.4706 - F1: 0.4320
sub_28:Test (Best Model) - Loss: 1.6382 - Accuracy: 0.4118 - F1: 0.3638
sub_14:Test (Best Model) - Loss: 1.2344 - Accuracy: 0.3824 - F1: 0.3474
sub_23:Test (Best Model) - Loss: 1.0120 - Accuracy: 0.5147 - F1: 0.4128
sub_7:Test (Best Model) - Loss: 1.0397 - Accuracy: 0.6765 - F1: 0.6104
sub_9:Test (Best Model) - Loss: 0.9525 - Accuracy: 0.4706 - F1: 0.4075
sub_16:Test (Best Model) - Loss: 0.7880 - Accuracy: 0.7500 - F1: 0.7527
sub_6:Test (Best Model) - Loss: 0.9650 - Accuracy: 0.6087 - F1: 0.6132
sub_5:Test (Best Model) - Loss: 0.9293 - Accuracy: 0.7353 - F1: 0.6458
sub_27:Test (Best Model) - Loss: 1.1888 - Accuracy: 0.5362 - F1: 0.4979
sub_19:Test (Best Model) - Loss: 1.1552 - Accuracy: 0.6176 - F1: 0.6010
sub_12:Test (Best Model) - Loss: 0.5342 - Accuracy: 0.8116 - F1: 0.8166
sub_11:Test (Best Model) - Loss: 0.8703 - Accuracy: 0.6812 - F1: 0.6762
sub_25:Test (Best Model) - Loss: 0.8182 - Accuracy: 0.6618 - F1: 0.6268
sub_15:Test (Best Model) - Loss: 0.5474 - Accuracy: 0.8382 - F1: 0.8467
sub_4:Test (Best Model) - Loss: 0.5096 - Accuracy: 0.8406 - F1: 0.8490
sub_26:Test (Best Model) - Loss: 0.9229 - Accuracy: 0.6618 - F1: 0.6511
sub_10:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.3676 - F1: 0.2821
sub_3:Test (Best Model) - Loss: 1.0107 - Accuracy: 0.6957 - F1: 0.6688
sub_2:Test (Best Model) - Loss: 0.6290 - Accuracy: 0.7941 - F1: 0.7925
sub_1:Test (Best Model) - Loss: 1.0052 - Accuracy: 0.5652 - F1: 0.5596
sub_18:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.4853 - F1: 0.5003
sub_22:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.5797 - F1: 0.5582
sub_29:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.7941 - F1: 0.8001
sub_21:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.8382 - F1: 0.8345
sub_13:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.5072 - F1: 0.4385
sub_20:Test (Best Model) - Loss: 1.0781 - Accuracy: 0.6618 - F1: 0.6263
sub_17:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.4493 - F1: 0.4253
sub_24:Test (Best Model) - Loss: 0.8677 - Accuracy: 0.6912 - F1: 0.6653
sub_28:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.4559 - F1: 0.3867
sub_9:Test (Best Model) - Loss: 0.9422 - Accuracy: 0.5441 - F1: 0.4782
sub_8:Test (Best Model) - Loss: 0.9737 - Accuracy: 0.6912 - F1: 0.6300
sub_23:Test (Best Model) - Loss: 1.2324 - Accuracy: 0.5000 - F1: 0.4130
sub_14:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.3971 - F1: 0.3722
sub_7:Test (Best Model) - Loss: 1.0846 - Accuracy: 0.6618 - F1: 0.5889
sub_6:Test (Best Model) - Loss: 0.9295 - Accuracy: 0.6522 - F1: 0.6460
sub_15:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.7353 - F1: 0.7430
sub_27:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.4493 - F1: 0.4253
sub_16:Test (Best Model) - Loss: 0.8253 - Accuracy: 0.6618 - F1: 0.6758
sub_19:Test (Best Model) - Loss: 0.9070 - Accuracy: 0.6324 - F1: 0.6600
sub_5:Test (Best Model) - Loss: 0.8979 - Accuracy: 0.7059 - F1: 0.6403
sub_4:Test (Best Model) - Loss: 0.7124 - Accuracy: 0.7826 - F1: 0.7959
sub_25:Test (Best Model) - Loss: 0.8529 - Accuracy: 0.7353 - F1: 0.7236
sub_10:Test (Best Model) - Loss: 1.3028 - Accuracy: 0.3824 - F1: 0.2972
sub_12:Test (Best Model) - Loss: 0.6255 - Accuracy: 0.7826 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.7877 - Accuracy: 0.7391 - F1: 0.7266
sub_2:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.7941 - F1: 0.8013
sub_26:Test (Best Model) - Loss: 0.9807 - Accuracy: 0.5735 - F1: 0.5582
sub_22:Test (Best Model) - Loss: 1.0706 - Accuracy: 0.5507 - F1: 0.5037
sub_18:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.3971 - F1: 0.4546
sub_1:Test (Best Model) - Loss: 0.9305 - Accuracy: 0.6377 - F1: 0.6095
sub_3:Test (Best Model) - Loss: 1.0243 - Accuracy: 0.6957 - F1: 0.6698
sub_20:Test (Best Model) - Loss: 0.9019 - Accuracy: 0.7206 - F1: 0.6800
sub_17:Test (Best Model) - Loss: 1.2612 - Accuracy: 0.4493 - F1: 0.4315
sub_14:Test (Best Model) - Loss: 1.1759 - Accuracy: 0.3382 - F1: 0.3458
sub_24:Test (Best Model) - Loss: 0.9254 - Accuracy: 0.6324 - F1: 0.5667
sub_21:Test (Best Model) - Loss: 0.5149 - Accuracy: 0.8824 - F1: 0.8834
sub_8:Test (Best Model) - Loss: 0.7992 - Accuracy: 0.6765 - F1: 0.6267
sub_27:Test (Best Model) - Loss: 1.2612 - Accuracy: 0.4493 - F1: 0.4315
sub_5:Test (Best Model) - Loss: 0.8619 - Accuracy: 0.7353 - F1: 0.6523
sub_10:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.2794 - F1: 0.1405
sub_16:Test (Best Model) - Loss: 0.9655 - Accuracy: 0.5882 - F1: 0.5443
sub_15:Test (Best Model) - Loss: 0.8549 - Accuracy: 0.7206 - F1: 0.7210
sub_29:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.7500 - F1: 0.7593
sub_9:Test (Best Model) - Loss: 0.8700 - Accuracy: 0.5588 - F1: 0.5234
sub_7:Test (Best Model) - Loss: 0.9823 - Accuracy: 0.6618 - F1: 0.5996
sub_4:Test (Best Model) - Loss: 0.5061 - Accuracy: 0.8551 - F1: 0.8573
sub_18:Test (Best Model) - Loss: 1.1064 - Accuracy: 0.4559 - F1: 0.5111
sub_12:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.7391 - F1: 0.7424
sub_19:Test (Best Model) - Loss: 0.8256 - Accuracy: 0.7059 - F1: 0.7191
sub_28:Test (Best Model) - Loss: 1.7743 - Accuracy: 0.4412 - F1: 0.3639
sub_25:Test (Best Model) - Loss: 0.7306 - Accuracy: 0.7500 - F1: 0.7313
sub_13:Test (Best Model) - Loss: 1.1586 - Accuracy: 0.5507 - F1: 0.5035
sub_6:Test (Best Model) - Loss: 1.0615 - Accuracy: 0.5942 - F1: 0.5841
sub_21:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.8529 - F1: 0.8510
sub_23:Test (Best Model) - Loss: 1.1143 - Accuracy: 0.5294 - F1: 0.4628
sub_11:Test (Best Model) - Loss: 0.8658 - Accuracy: 0.6522 - F1: 0.6078
sub_26:Test (Best Model) - Loss: 1.3286 - Accuracy: 0.4559 - F1: 0.4595
sub_14:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3824 - F1: 0.3498
sub_10:Test (Best Model) - Loss: 0.9044 - Accuracy: 0.6667 - F1: 0.6330
sub_16:Test (Best Model) - Loss: 0.9289 - Accuracy: 0.6912 - F1: 0.6996
sub_24:Test (Best Model) - Loss: 0.9012 - Accuracy: 0.6912 - F1: 0.6191
sub_3:Test (Best Model) - Loss: 0.9512 - Accuracy: 0.6957 - F1: 0.6680
sub_2:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.7794 - F1: 0.7902
sub_20:Test (Best Model) - Loss: 0.9302 - Accuracy: 0.7059 - F1: 0.6933
sub_1:Test (Best Model) - Loss: 1.0062 - Accuracy: 0.5652 - F1: 0.5521
sub_17:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.5217 - F1: 0.5262
sub_29:Test (Best Model) - Loss: 0.7478 - Accuracy: 0.7353 - F1: 0.7398
sub_8:Test (Best Model) - Loss: 0.8368 - Accuracy: 0.7206 - F1: 0.6878
sub_5:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.7647 - F1: 0.7188
sub_22:Test (Best Model) - Loss: 1.2773 - Accuracy: 0.4348 - F1: 0.3847
sub_12:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.7246 - F1: 0.7151
sub_18:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.5735 - F1: 0.5892
sub_4:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.8116 - F1: 0.8004
sub_9:Test (Best Model) - Loss: 0.9494 - Accuracy: 0.4559 - F1: 0.4105
sub_7:Test (Best Model) - Loss: 0.8948 - Accuracy: 0.7059 - F1: 0.6268
sub_19:Test (Best Model) - Loss: 0.8417 - Accuracy: 0.7059 - F1: 0.7233
sub_15:Test (Best Model) - Loss: 0.6786 - Accuracy: 0.8235 - F1: 0.8324
sub_16:Test (Best Model) - Loss: 0.9800 - Accuracy: 0.5882 - F1: 0.5731
sub_28:Test (Best Model) - Loss: 1.6735 - Accuracy: 0.4265 - F1: 0.3624
sub_27:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.5217 - F1: 0.5262
sub_3:Test (Best Model) - Loss: 0.9877 - Accuracy: 0.6812 - F1: 0.6442
sub_10:Test (Best Model) - Loss: 1.0321 - Accuracy: 0.5652 - F1: 0.5187
sub_24:Test (Best Model) - Loss: 0.8835 - Accuracy: 0.7059 - F1: 0.6404
sub_13:Test (Best Model) - Loss: 1.1541 - Accuracy: 0.5362 - F1: 0.5101
sub_6:Test (Best Model) - Loss: 1.0851 - Accuracy: 0.5942 - F1: 0.5820
sub_11:Test (Best Model) - Loss: 0.7497 - Accuracy: 0.7681 - F1: 0.7539
sub_25:Test (Best Model) - Loss: 0.7924 - Accuracy: 0.7500 - F1: 0.7189
sub_8:Test (Best Model) - Loss: 1.0083 - Accuracy: 0.6176 - F1: 0.5972
sub_14:Test (Best Model) - Loss: 0.7901 - Accuracy: 0.6765 - F1: 0.6822
sub_21:Test (Best Model) - Loss: 0.4169 - Accuracy: 0.8676 - F1: 0.8699
sub_22:Test (Best Model) - Loss: 0.9946 - Accuracy: 0.6324 - F1: 0.5955
sub_20:Test (Best Model) - Loss: 0.9248 - Accuracy: 0.6912 - F1: 0.6398
sub_23:Test (Best Model) - Loss: 0.8611 - Accuracy: 0.5882 - F1: 0.5371
sub_2:Test (Best Model) - Loss: 0.5448 - Accuracy: 0.8088 - F1: 0.8117
sub_12:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.7826 - F1: 0.7810
sub_18:Test (Best Model) - Loss: 0.9868 - Accuracy: 0.6176 - F1: 0.6198
sub_29:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.6912 - F1: 0.6907
sub_17:Test (Best Model) - Loss: 1.2803 - Accuracy: 0.4348 - F1: 0.4242
sub_5:Test (Best Model) - Loss: 1.1056 - Accuracy: 0.5294 - F1: 0.4414
sub_4:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.8261 - F1: 0.8290
sub_7:Test (Best Model) - Loss: 0.8766 - Accuracy: 0.7059 - F1: 0.6919
sub_15:Test (Best Model) - Loss: 0.7674 - Accuracy: 0.7794 - F1: 0.7869
sub_19:Test (Best Model) - Loss: 0.9173 - Accuracy: 0.6324 - F1: 0.6353
sub_16:Test (Best Model) - Loss: 0.8552 - Accuracy: 0.6471 - F1: 0.6506
sub_25:Test (Best Model) - Loss: 0.8527 - Accuracy: 0.6912 - F1: 0.6920
sub_1:Test (Best Model) - Loss: 1.2417 - Accuracy: 0.5072 - F1: 0.4633
sub_27:Test (Best Model) - Loss: 1.2803 - Accuracy: 0.4348 - F1: 0.4242
sub_26:Test (Best Model) - Loss: 0.9837 - Accuracy: 0.6029 - F1: 0.6038
sub_9:Test (Best Model) - Loss: 1.0324 - Accuracy: 0.5441 - F1: 0.5089
sub_10:Test (Best Model) - Loss: 0.8785 - Accuracy: 0.6667 - F1: 0.6323
sub_13:Test (Best Model) - Loss: 1.0542 - Accuracy: 0.5797 - F1: 0.5258
sub_3:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.7971 - F1: 0.8029
sub_12:Test (Best Model) - Loss: 0.8494 - Accuracy: 0.7794 - F1: 0.7865
sub_20:Test (Best Model) - Loss: 0.8867 - Accuracy: 0.6912 - F1: 0.6418
sub_28:Test (Best Model) - Loss: 1.6818 - Accuracy: 0.4412 - F1: 0.3757
sub_6:Test (Best Model) - Loss: 0.9736 - Accuracy: 0.5942 - F1: 0.5914
sub_14:Test (Best Model) - Loss: 0.7698 - Accuracy: 0.7353 - F1: 0.7402
sub_11:Test (Best Model) - Loss: 0.7097 - Accuracy: 0.8116 - F1: 0.8156
sub_18:Test (Best Model) - Loss: 1.1410 - Accuracy: 0.4706 - F1: 0.4468
sub_8:Test (Best Model) - Loss: 1.0633 - Accuracy: 0.5882 - F1: 0.5904
sub_24:Test (Best Model) - Loss: 0.8122 - Accuracy: 0.7353 - F1: 0.7504
sub_22:Test (Best Model) - Loss: 0.9561 - Accuracy: 0.6324 - F1: 0.6327
sub_21:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.7794 - F1: 0.7415
sub_17:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.5882 - F1: 0.5771
sub_1:Test (Best Model) - Loss: 0.9625 - Accuracy: 0.6912 - F1: 0.6409
sub_19:Test (Best Model) - Loss: 1.0249 - Accuracy: 0.5882 - F1: 0.5563
sub_3:Test (Best Model) - Loss: 0.7837 - Accuracy: 0.8116 - F1: 0.8250
sub_2:Test (Best Model) - Loss: 0.5633 - Accuracy: 0.8235 - F1: 0.8273
sub_7:Test (Best Model) - Loss: 0.8178 - Accuracy: 0.7206 - F1: 0.7007
sub_5:Test (Best Model) - Loss: 1.0407 - Accuracy: 0.6912 - F1: 0.6118
sub_20:Test (Best Model) - Loss: 0.9649 - Accuracy: 0.6522 - F1: 0.6216
sub_10:Test (Best Model) - Loss: 0.9645 - Accuracy: 0.6232 - F1: 0.5856
sub_29:Test (Best Model) - Loss: 0.8598 - Accuracy: 0.6667 - F1: 0.6303
sub_15:Test (Best Model) - Loss: 0.9106 - Accuracy: 0.7059 - F1: 0.6500
sub_25:Test (Best Model) - Loss: 0.8198 - Accuracy: 0.6765 - F1: 0.6497
sub_26:Test (Best Model) - Loss: 1.2275 - Accuracy: 0.4265 - F1: 0.4589
sub_16:Test (Best Model) - Loss: 0.8905 - Accuracy: 0.6176 - F1: 0.6216
sub_23:Test (Best Model) - Loss: 0.8708 - Accuracy: 0.6912 - F1: 0.6492
sub_8:Test (Best Model) - Loss: 1.0829 - Accuracy: 0.5735 - F1: 0.5614
sub_27:Test (Best Model) - Loss: 0.8968 - Accuracy: 0.5882 - F1: 0.5771
sub_28:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.4265 - F1: 0.3306
sub_14:Test (Best Model) - Loss: 0.5449 - Accuracy: 0.8382 - F1: 0.8431
sub_4:Test (Best Model) - Loss: 0.9210 - Accuracy: 0.6522 - F1: 0.6201
sub_6:Test (Best Model) - Loss: 0.7992 - Accuracy: 0.6957 - F1: 0.6355
sub_18:Test (Best Model) - Loss: 1.1038 - Accuracy: 0.5294 - F1: 0.5336
sub_13:Test (Best Model) - Loss: 1.4564 - Accuracy: 0.4118 - F1: 0.3071
sub_24:Test (Best Model) - Loss: 0.7397 - Accuracy: 0.7647 - F1: 0.7747
sub_9:Test (Best Model) - Loss: 1.0281 - Accuracy: 0.6324 - F1: 0.6305
sub_12:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.7647 - F1: 0.7656
sub_21:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.7059 - F1: 0.6342
sub_2:Test (Best Model) - Loss: 1.1542 - Accuracy: 0.5072 - F1: 0.4673
sub_22:Test (Best Model) - Loss: 0.9645 - Accuracy: 0.6324 - F1: 0.6170
sub_16:Test (Best Model) - Loss: 0.9063 - Accuracy: 0.6618 - F1: 0.6752
sub_7:Test (Best Model) - Loss: 0.8246 - Accuracy: 0.7500 - F1: 0.7451
sub_1:Test (Best Model) - Loss: 0.9415 - Accuracy: 0.6471 - F1: 0.6073
sub_20:Test (Best Model) - Loss: 0.8701 - Accuracy: 0.6812 - F1: 0.6721
sub_3:Test (Best Model) - Loss: 0.7205 - Accuracy: 0.8116 - F1: 0.8146
sub_10:Test (Best Model) - Loss: 0.9263 - Accuracy: 0.6522 - F1: 0.6432
sub_11:Test (Best Model) - Loss: 0.5225 - Accuracy: 0.8116 - F1: 0.8143
sub_5:Test (Best Model) - Loss: 0.7962 - Accuracy: 0.7353 - F1: 0.7313
sub_25:Test (Best Model) - Loss: 0.9651 - Accuracy: 0.6029 - F1: 0.5786
sub_23:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.4638 - F1: 0.4278
sub_17:Test (Best Model) - Loss: 0.8307 - Accuracy: 0.6765 - F1: 0.6638
sub_29:Test (Best Model) - Loss: 0.9022 - Accuracy: 0.7101 - F1: 0.6616
sub_19:Test (Best Model) - Loss: 1.1845 - Accuracy: 0.4853 - F1: 0.4596
sub_8:Test (Best Model) - Loss: 1.1256 - Accuracy: 0.5735 - F1: 0.5437
sub_15:Test (Best Model) - Loss: 0.9212 - Accuracy: 0.6618 - F1: 0.6264
sub_18:Test (Best Model) - Loss: 1.1471 - Accuracy: 0.5147 - F1: 0.5190
sub_28:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.4265 - F1: 0.3299
sub_12:Test (Best Model) - Loss: 0.7919 - Accuracy: 0.8088 - F1: 0.8187
sub_14:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.7941 - F1: 0.7911
sub_4:Test (Best Model) - Loss: 0.8612 - Accuracy: 0.6377 - F1: 0.6173
sub_26:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4412 - F1: 0.4607
sub_16:Test (Best Model) - Loss: 0.8724 - Accuracy: 0.7353 - F1: 0.7500
sub_2:Test (Best Model) - Loss: 1.0254 - Accuracy: 0.5362 - F1: 0.5020
sub_6:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.6812 - F1: 0.6097
sub_27:Test (Best Model) - Loss: 0.8307 - Accuracy: 0.6765 - F1: 0.6638
sub_24:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.7500 - F1: 0.7509
sub_13:Test (Best Model) - Loss: 1.4279 - Accuracy: 0.4706 - F1: 0.3840
sub_25:Test (Best Model) - Loss: 0.8906 - Accuracy: 0.6029 - F1: 0.5630
sub_7:Test (Best Model) - Loss: 0.7679 - Accuracy: 0.7941 - F1: 0.7942
sub_3:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.8116 - F1: 0.8200
sub_11:Test (Best Model) - Loss: 0.7499 - Accuracy: 0.7971 - F1: 0.7791
sub_21:Test (Best Model) - Loss: 0.7988 - Accuracy: 0.7500 - F1: 0.7071
sub_22:Test (Best Model) - Loss: 1.0756 - Accuracy: 0.5882 - F1: 0.5597
sub_20:Test (Best Model) - Loss: 0.9145 - Accuracy: 0.6667 - F1: 0.6620
sub_9:Test (Best Model) - Loss: 0.9041 - Accuracy: 0.6765 - F1: 0.6705
sub_8:Test (Best Model) - Loss: 1.0637 - Accuracy: 0.6324 - F1: 0.5922
sub_29:Test (Best Model) - Loss: 0.8662 - Accuracy: 0.6812 - F1: 0.6371
sub_14:Test (Best Model) - Loss: 0.7665 - Accuracy: 0.7794 - F1: 0.7695
sub_17:Test (Best Model) - Loss: 1.0185 - Accuracy: 0.5441 - F1: 0.5663
sub_15:Test (Best Model) - Loss: 1.0806 - Accuracy: 0.5588 - F1: 0.4863
sub_19:Test (Best Model) - Loss: 1.0247 - Accuracy: 0.5147 - F1: 0.5159
sub_1:Test (Best Model) - Loss: 1.0158 - Accuracy: 0.6324 - F1: 0.6000
sub_26:Test (Best Model) - Loss: 1.1519 - Accuracy: 0.5294 - F1: 0.5130
sub_6:Test (Best Model) - Loss: 0.8874 - Accuracy: 0.6957 - F1: 0.6599
sub_23:Test (Best Model) - Loss: 1.2761 - Accuracy: 0.4783 - F1: 0.4235
sub_28:Test (Best Model) - Loss: 1.3227 - Accuracy: 0.3971 - F1: 0.3199
sub_5:Test (Best Model) - Loss: 1.0100 - Accuracy: 0.5294 - F1: 0.4685
sub_2:Test (Best Model) - Loss: 0.9580 - Accuracy: 0.5507 - F1: 0.5426
sub_12:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.7206 - F1: 0.7309
sub_27:Test (Best Model) - Loss: 1.0185 - Accuracy: 0.5441 - F1: 0.5663
sub_4:Test (Best Model) - Loss: 0.9170 - Accuracy: 0.6377 - F1: 0.6173
sub_25:Test (Best Model) - Loss: 0.8515 - Accuracy: 0.6765 - F1: 0.6699
sub_11:Test (Best Model) - Loss: 0.7290 - Accuracy: 0.7826 - F1: 0.7686
sub_24:Test (Best Model) - Loss: 0.5227 - Accuracy: 0.8235 - F1: 0.8374
sub_3:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.8261 - F1: 0.8314
sub_13:Test (Best Model) - Loss: 1.3615 - Accuracy: 0.4706 - F1: 0.4157
sub_20:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.6087 - F1: 0.5698
sub_7:Test (Best Model) - Loss: 0.7889 - Accuracy: 0.6912 - F1: 0.6471
sub_21:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.7794 - F1: 0.7481
sub_15:Test (Best Model) - Loss: 0.9154 - Accuracy: 0.7059 - F1: 0.6401
sub_29:Test (Best Model) - Loss: 0.9942 - Accuracy: 0.6522 - F1: 0.6226
sub_17:Test (Best Model) - Loss: 0.9566 - Accuracy: 0.6176 - F1: 0.5808
sub_19:Test (Best Model) - Loss: 1.0583 - Accuracy: 0.5441 - F1: 0.5054
sub_23:Test (Best Model) - Loss: 1.4211 - Accuracy: 0.4783 - F1: 0.4172
sub_6:Test (Best Model) - Loss: 0.9585 - Accuracy: 0.6812 - F1: 0.6082
sub_12:Test (Best Model) - Loss: 0.7499 - Accuracy: 0.7647 - F1: 0.7470
sub_1:Test (Best Model) - Loss: 0.9199 - Accuracy: 0.6471 - F1: 0.6287
sub_5:Test (Best Model) - Loss: 0.8774 - Accuracy: 0.7059 - F1: 0.6632
sub_26:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3382 - F1: 0.3814
sub_9:Test (Best Model) - Loss: 1.0623 - Accuracy: 0.6324 - F1: 0.6292
sub_22:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.6029 - F1: 0.5731
sub_27:Test (Best Model) - Loss: 0.9566 - Accuracy: 0.6176 - F1: 0.5808
sub_28:Test (Best Model) - Loss: 1.6223 - Accuracy: 0.3824 - F1: 0.3084
sub_24:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.7794 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.4559 - F1: 0.3799
sub_2:Test (Best Model) - Loss: 1.0837 - Accuracy: 0.5072 - F1: 0.4600
sub_4:Test (Best Model) - Loss: 0.9821 - Accuracy: 0.6377 - F1: 0.6282
sub_11:Test (Best Model) - Loss: 0.7474 - Accuracy: 0.7536 - F1: 0.7434
sub_20:Test (Best Model) - Loss: 1.0338 - Accuracy: 0.6522 - F1: 0.6375
sub_17:Test (Best Model) - Loss: 0.9475 - Accuracy: 0.6176 - F1: 0.5959
sub_15:Test (Best Model) - Loss: 1.0681 - Accuracy: 0.6765 - F1: 0.6345
sub_21:Test (Best Model) - Loss: 0.7094 - Accuracy: 0.7500 - F1: 0.7080
sub_6:Test (Best Model) - Loss: 0.9082 - Accuracy: 0.6667 - F1: 0.6031
sub_23:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.4638 - F1: 0.4135
sub_19:Test (Best Model) - Loss: 0.9718 - Accuracy: 0.5735 - F1: 0.5411
sub_1:Test (Best Model) - Loss: 0.9804 - Accuracy: 0.6912 - F1: 0.6260
sub_29:Test (Best Model) - Loss: 1.0375 - Accuracy: 0.6812 - F1: 0.6395
sub_28:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.4559 - F1: 0.4107
sub_26:Test (Best Model) - Loss: 1.1567 - Accuracy: 0.5294 - F1: 0.5472
sub_27:Test (Best Model) - Loss: 0.9475 - Accuracy: 0.6176 - F1: 0.5959
sub_13:Test (Best Model) - Loss: 1.3261 - Accuracy: 0.4412 - F1: 0.3662
sub_2:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.5217 - F1: 0.4807
sub_9:Test (Best Model) - Loss: 1.1032 - Accuracy: 0.6471 - F1: 0.6429
sub_4:Test (Best Model) - Loss: 0.9726 - Accuracy: 0.7246 - F1: 0.6565
sub_23:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4638 - F1: 0.4161
sub_9:Test (Best Model) - Loss: 1.0083 - Accuracy: 0.5735 - F1: 0.5478

=== Summary Results ===

acc: 62.96 ± 9.00
F1: 60.91 ± 9.57
acc-in: 92.47 ± 3.01
F1-in: 92.27 ± 3.29
